From 1183b82d61301a37046edfe3a82c3ecb9ae481d0 Mon Sep 17 00:00:00 2001 From: MMMMMaasd Date: Fri, 11 Apr 2025 11:43:06 +0800 Subject: [PATCH 01/56] Remove Export to Local --- AnySense.xcodeproj/project.pbxproj | 4 -- .../xcshareddata/IDEWorkspaceChecks.plist | 8 ++++ AnySense/Views/readView.swift | 43 +------------------ 3 files changed, 9 insertions(+), 46 deletions(-) create mode 100644 AnySense.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index f030751..dae84f2 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -12,7 +12,6 @@ B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */ = {isa = PBXBuildFile; fileRef = B997CCD22D4E081300F62B49 /* dataStorage.swift */; }; B997CCD52D4E082900F62B49 /* AnySenseApp.swift in Sources */ = {isa = PBXBuildFile; fileRef = B997CCD42D4E082900F62B49 /* AnySenseApp.swift */; }; B9E4B22D2D62A9BA0032E877 /* BluetoothManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = B9E4B2292D62A9BA0032E877 /* BluetoothManager.swift */; }; - B9E4B22E2D62A9BA0032E877 /* WebRTCManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = B9E4B22B2D62A9BA0032E877 /* WebRTCManager.swift */; }; B9E4B22F2D62A9BA0032E877 /* ARViewContainer.swift in Sources */ = {isa = PBXBuildFile; fileRef = B9E4B2282D62A9BA0032E877 /* ARViewContainer.swift */; }; B9E4B2302D62A9BA0032E877 /* USBManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = B9E4B22A2D62A9BA0032E877 /* USBManager.swift */; }; B9E4B2362D62A9C40032E877 /* peripheralView.swift in Sources */ = {isa = PBXBuildFile; fileRef = B9E4B2332D62A9C40032E877 /* peripheralView.swift */; }; @@ -53,7 +52,6 @@ B9E4B2282D62A9BA0032E877 /* ARViewContainer.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARViewContainer.swift; sourceTree = ""; }; B9E4B2292D62A9BA0032E877 /* BluetoothManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = BluetoothManager.swift; sourceTree = ""; }; B9E4B22A2D62A9BA0032E877 /* USBManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = USBManager.swift; sourceTree = ""; }; - B9E4B22B2D62A9BA0032E877 /* WebRTCManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = WebRTCManager.swift; sourceTree = ""; }; B9E4B2312D62A9C40032E877 /* accountView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = accountView.swift; sourceTree = ""; }; B9E4B2322D62A9C40032E877 /* ContentView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ContentView.swift; sourceTree = ""; }; B9E4B2332D62A9C40032E877 /* peripheralView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = peripheralView.swift; sourceTree = ""; }; @@ -128,7 +126,6 @@ B9E4B2282D62A9BA0032E877 /* ARViewContainer.swift */, B9E4B2292D62A9BA0032E877 /* BluetoothManager.swift */, B9E4B22A2D62A9BA0032E877 /* USBManager.swift */, - B9E4B22B2D62A9BA0032E877 /* WebRTCManager.swift */, ); path = Managers; sourceTree = ""; @@ -326,7 +323,6 @@ B997CCD52D4E082900F62B49 /* AnySenseApp.swift in Sources */, B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */, B9E4B22D2D62A9BA0032E877 /* BluetoothManager.swift in Sources */, - B9E4B22E2D62A9BA0032E877 /* WebRTCManager.swift in Sources */, B9E4B22F2D62A9BA0032E877 /* ARViewContainer.swift in Sources */, B9E4B2302D62A9BA0032E877 /* USBManager.swift in Sources */, B9944A342CFE983300232FBB /* MainPage.swift in Sources */, diff --git a/AnySense.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist b/AnySense.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist new file mode 100644 index 0000000..18d9810 --- /dev/null +++ b/AnySense.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist @@ -0,0 +1,8 @@ + + + + + IDEDidComputeMac32BitWarning + + + diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 9b0592b..d0e3208 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -25,7 +25,6 @@ struct ReadView : View{ @State var showingAlert : Bool = false @Environment(\.scenePhase) private var phase @State private var fileSetNames: RecordingFiles? - @State var showingExporter = false @State var openFlash = true @State private var activeAlert: ActiveAlert = .first @State private var isRecordedOnce: Bool = false @@ -138,32 +137,6 @@ struct ReadView : View{ if appStatus.rgbdVideoStreaming == .off{ HStack{ - VStack{ - // Export to local button - Button(action: { - if(isRecordedOnce){ - showingExporter.toggle() - } else{ - showingAlert = true - self.activeAlert = .second - } - UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() - }){ - Image(systemName: "square.and.arrow.up.circle.fill") - .resizable() - .frame(height: 40) - .frame(width: 40) - } - .padding(.trailing, 8.0) - Text("Export") - .foregroundStyle(.accent) - .font(.caption) - .padding(.trailing, 8.0) - Text("to local") - .foregroundStyle(.accent) - .font(.caption) - .padding(.trailing, 8.0) - } VStack{ // Delete last record button Button(action: { @@ -195,7 +168,7 @@ struct ReadView : View{ } } // .frame(width: screenWidth / 2.0, alignment: .leading) - .padding(.top, 0.66 * arViewHeight + 0.33 * screenHeight) + .padding(.top, 0.66 * arViewHeight + 0.32 * screenHeight) // Flash light control button VStack{ @@ -260,20 +233,6 @@ struct ReadView : View{ } } - // File exporter, connected to export button - .fileExporter( - isPresented: $showingExporter, - document: DocumentaryFolder(files: createDocumentaryFolderFiles(paths: paths, fileSetNames: fileSetNames)), - contentType: .folder, - defaultFilename: fileSetNames?.timestamp - ) { result in - switch result { - case .success(let url): - print("Saved to \(url)") - case .failure(let error): - print(error.localizedDescription) - } - } .onChange(of: appStatus.rgbdVideoStreaming) { oldMode, newMode in handleStreamingModeChange(from: oldMode, to: newMode) } From 6ab64d2760ceb43662a924d59ec3310f15e2ef74 Mon Sep 17 00:00:00 2001 From: MMMMMaasd Date: Fri, 11 Apr 2025 11:52:25 +0800 Subject: [PATCH 02/56] Audio enable option in setting --- AnySense/Managers/ARViewContainer.swift | 41 +++++++++++++++---------- AnySense/Views/ContentView.swift | 1 + AnySense/Views/accountView.swift | 3 ++ 3 files changed, 29 insertions(+), 16 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 0effdc5..9488f21 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -72,6 +72,7 @@ class ARViewModel: ObservableObject{ public var userFPS: Double? public var isColorMapOpened = false + public var ifAudioEnable = false private var usbManager = USBManager() private var orientation: UIInterfaceOrientation = .portrait @@ -230,7 +231,9 @@ class ARViewModel: ObservableObject{ func setupARSession() { self.startARSession() - setupAudioSession() + if(ifAudioEnable) { + setupAudioSession() + } setupTransforms() @@ -504,7 +507,9 @@ class ARViewModel: ObservableObject{ assetWriter?.startSession(atSourceTime: startTime!) DispatchQueue.global(qos: .background).async { - self.audioSession.startRunning() + if(self.ifAudioEnable) { + self.audioSession.startRunning() + } } if self.depthStatus.isDepthAvailable { depthAssetWriter?.startWriting() @@ -523,8 +528,10 @@ class ARViewModel: ObservableObject{ func stopRecording(){ displayLink?.invalidate() displayLink = nil - audioSession.stopRunning() - audioInput?.markAsFinished() + if(ifAudioEnable) { + audioSession.stopRunning() + audioInput?.markAsFinished() + } videoInput?.markAsFinished() audioCaptureDelegate = nil @@ -613,21 +620,23 @@ class ARViewModel: ObservableObject{ self.videoInput?.expectsMediaDataInRealTime = true self.assetWriter?.add(videoInput!) - self.audioInput = AVAssetWriterInput(mediaType: .audio, outputSettings: audioOutputSettings) - self.audioInput?.expectsMediaDataInRealTime = true - self.assetWriter?.add(audioInput!) - - self.pixelBufferAdapter = AVAssetWriterInputPixelBufferAdaptor(assetWriterInput: videoInput!, sourcePixelBufferAttributes: rgbAttributes) - - // Update the audio delegate with the new audioWriterInput - self.audioCaptureDelegate = AudioCaptureDelegate(writerInput: audioInput!) + if(ifAudioEnable) { + self.audioInput = AVAssetWriterInput(mediaType: .audio, outputSettings: audioOutputSettings) + self.audioInput?.expectsMediaDataInRealTime = true + self.assetWriter?.add(audioInput!) + + // Update the audio delegate with the new audioWriterInput + self.audioCaptureDelegate = AudioCaptureDelegate(writerInput: audioInput!) - // Attach the new delegate to the existing AVCaptureAudioDataOutput - if let audioOutput = self.audioSession.outputs.first(where: { $0 is AVCaptureAudioDataOutput }) as? AVCaptureAudioDataOutput { - let audioQueue = DispatchQueue(label: "AudioProcessingQueue") - audioOutput.setSampleBufferDelegate(self.audioCaptureDelegate, queue: audioQueue) + // Attach the new delegate to the existing AVCaptureAudioDataOutput + if let audioOutput = self.audioSession.outputs.first(where: { $0 is AVCaptureAudioDataOutput }) as? AVCaptureAudioDataOutput { + let audioQueue = DispatchQueue(label: "AudioProcessingQueue") + audioOutput.setSampleBufferDelegate(self.audioCaptureDelegate, queue: audioQueue) + } } + self.pixelBufferAdapter = AVAssetWriterInputPixelBufferAdaptor(assetWriterInput: videoInput!, sourcePixelBufferAttributes: rgbAttributes) + if self.depthStatus.isDepthAvailable { setupDepthRecording(depthVideoURL: depthVideoURL) } diff --git a/AnySense/Views/ContentView.swift b/AnySense/Views/ContentView.swift index 0b0aecc..48b7c73 100644 --- a/AnySense/Views/ContentView.swift +++ b/AnySense/Views/ContentView.swift @@ -103,6 +103,7 @@ class AppInformation : ObservableObject{ @Published var gridProjectionTrigger: GridMode = .off @Published var colorMapTrigger: Bool = false @Published var ifBluetoothConnected: Bool = false + @Published var ifAudioRecordingEnabled: Bool = false } diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 840fbcd..daf504c 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -47,6 +47,9 @@ struct SettingsView : View{ } .padding(.vertical, 5) .padding(.vertical, 5) + HStack{ + Toggle("Audio recording enabled", isOn: $appStatus.ifAudioRecordingEnabled) + } HStack{ Text("Buttons haptic feedback") .font(.body) From a915f2f64017ed4abd6a82557b6be83d3a4ebfdc Mon Sep 17 00:00:00 2001 From: MMMMMaasd Date: Fri, 11 Apr 2025 11:54:28 +0800 Subject: [PATCH 03/56] Remove Wifi in streaming option --- AnySense/Views/accountView.swift | 8 ++------ AnySense/Views/readView.swift | 3 --- 2 files changed, 2 insertions(+), 9 deletions(-) diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index daf504c..3643bc1 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -32,13 +32,10 @@ struct SettingsView : View{ let binding = Binding( get: { appStatus.rgbdVideoStreaming }, set: { newValue in - if newValue != StreamingMode.wifi { // Disable Option wifi - appStatus.rgbdVideoStreaming = newValue - } + appStatus.rgbdVideoStreaming = newValue } ) - Picker("Streaming Options", selection: binding) { // Temporary fix to keep wifi option but disable it - Text("Wi-Fi").tag(StreamingMode.wifi).opacity(0.5) + Picker("Streaming Options", selection: binding) { // Text("USB").tag(StreamingMode.usb) Text("Off").tag(StreamingMode.off) } @@ -111,7 +108,6 @@ struct SettingsView : View{ enum StreamingMode: String { case off = "Off" - case wifi = "Wi-Fi" case usb = "USB" } diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index d0e3208..7928e53 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -255,9 +255,6 @@ struct ReadView : View{ case (_, .off): arViewModel.killUSBStreaming() print("Switched to \(newMode): ARView is active.") - - case (_, .wifi): - print("NOT IMPLEMENTED.") case (_, .usb): print("Switched to \(newMode): ARView is hidden.") arViewModel.setupUSBStreaming() From 8e22672b17538ec78b4c270788197417671dc297 Mon Sep 17 00:00:00 2001 From: MMMMMaasd Date: Fri, 11 Apr 2025 12:06:39 +0800 Subject: [PATCH 04/56] Incorporate Bluetooth Manager with AR Manager --- AnySense/AnySenseApp.swift | 2 -- AnySense/MainPage.swift | 4 +--- AnySense/Managers/ARViewContainer.swift | 7 +++++++ AnySense/Views/ContentView.swift | 1 - AnySense/Views/peripheralView.swift | 14 ++++++-------- AnySense/Views/readView.swift | 9 ++++----- 6 files changed, 18 insertions(+), 19 deletions(-) diff --git a/AnySense/AnySenseApp.swift b/AnySense/AnySenseApp.swift index c9b21d8..de35206 100644 --- a/AnySense/AnySenseApp.swift +++ b/AnySense/AnySenseApp.swift @@ -11,12 +11,10 @@ import BackgroundTasks @main struct AnySenseApp: App { @StateObject var appStatus = AppInformation() - @StateObject var bluetoothManager = BluetoothManager() var body: some Scene { WindowGroup { ContentView() .environmentObject(appStatus) - .environmentObject(bluetoothManager) } } } diff --git a/AnySense/MainPage.swift b/AnySense/MainPage.swift index 6ee8cee..5758544 100644 --- a/AnySense/MainPage.swift +++ b/AnySense/MainPage.swift @@ -9,7 +9,6 @@ import SwiftUI struct MainPage: View { @EnvironmentObject private var appStatus : AppInformation - @EnvironmentObject private var bluetoothManager: BluetoothManager @Environment(\.scenePhase) private var phase let arViewModel: ARViewModel // Start the default page be the read page @@ -18,7 +17,7 @@ struct MainPage: View { var body: some View { TabView(selection: $selection){ Group{ - PeripheralView() + PeripheralView(arViewModel: arViewModel, bluetoothManager: arViewModel.getBLEManagerInstance()) .tabItem { Label("ble-device", systemImage: "iphone.gen1.radiowaves.left.and.right") } @@ -49,5 +48,4 @@ struct MainPage: View { #Preview { MainPage(arViewModel: ARViewModel()) .environmentObject(AppInformation()) - .environmentObject(BluetoothManager()) } diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 9488f21..4cfed52 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -64,6 +64,7 @@ class DepthStatus: ObservableObject { } class ARViewModel: ObservableObject{ + var bluetoothManager: BluetoothManager? @Published var isOpen : Bool = false @Published var depthStatus = DepthStatus() var session = ARSession() @@ -122,6 +123,8 @@ class ARViewModel: ObservableObject{ private var audioOutputSettings: [String: Any] = [:] init() { + bluetoothManager = BluetoothManager() + self.rgbAttributes = [ kCVPixelBufferPixelFormatTypeKey as String: Int(kCVPixelFormatType_32ARGB), kCVPixelBufferWidthKey as String: Int(viewPortSize.width), @@ -148,6 +151,10 @@ class ARViewModel: ObservableObject{ } + func getBLEManagerInstance() -> BluetoothManager{ + return bluetoothManager!; + } + private func setupAudioSession() { guard let audioDevice = AVCaptureDevice.default(for: .audio), diff --git a/AnySense/Views/ContentView.swift b/AnySense/Views/ContentView.swift index 48b7c73..2c6d0e6 100644 --- a/AnySense/Views/ContentView.swift +++ b/AnySense/Views/ContentView.swift @@ -11,7 +11,6 @@ import AVFoundation struct ContentView: View { @EnvironmentObject var appStatus : AppInformation - @EnvironmentObject var bluetoothManager: BluetoothManager @StateObject private var arViewModel = ARViewModel() @State private var hasPermissions = false diff --git a/AnySense/Views/peripheralView.swift b/AnySense/Views/peripheralView.swift index 8ea7db5..27e5954 100644 --- a/AnySense/Views/peripheralView.swift +++ b/AnySense/Views/peripheralView.swift @@ -9,8 +9,8 @@ import SwiftUI import CoreBluetooth struct singleBLEPeripheral: View { - @EnvironmentObject var bluetoothManager: BluetoothManager @EnvironmentObject var appStatus: AppInformation + @ObservedObject var arViewModel: ARViewModel @State private var isConnected = false let name: String let uuid: UUID @@ -35,7 +35,7 @@ struct singleBLEPeripheral: View { UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() if !isConnected{ - bluetoothManager.connectToPeripheral(withUUID: uuid) { result in + arViewModel.getBLEManagerInstance().connectToPeripheral(withUUID: uuid) { result in switch result { case .success(let connectedPeripheral): print("Successfully connected to: \(connectedPeripheral.name ?? "Unknown Device")") @@ -46,7 +46,7 @@ struct singleBLEPeripheral: View { appStatus.ifBluetoothConnected = true } else { appStatus.ifBluetoothConnected = false - bluetoothManager.disconnectFromDevice() + arViewModel.getBLEManagerInstance().disconnectFromDevice() } isConnected = !isConnected @@ -55,7 +55,8 @@ struct singleBLEPeripheral: View { struct PeripheralView: View { @EnvironmentObject var appStatus : AppInformation - @EnvironmentObject var bluetoothManager: BluetoothManager + @ObservedObject var arViewModel: ARViewModel + @ObservedObject var bluetoothManager: BluetoothManager var body: some View { VStack{ Text("Devices Detected") @@ -68,6 +69,7 @@ struct PeripheralView: View { List(Array(bluetoothManager.discoveredPeripherals.keys), id: \.self) { uuid in if let peripheral = bluetoothManager.discoveredPeripherals[uuid] { singleBLEPeripheral( + arViewModel: arViewModel, name: peripheral.name ?? "Unknown Device", uuid: peripheral.identifier ) @@ -79,7 +81,3 @@ struct PeripheralView: View { .background(Color.customizedBackground) } } - -#Preview { - PeripheralView().environmentObject(AppInformation()).environmentObject(BluetoothManager()) -} diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 7928e53..f5b958a 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -19,7 +19,6 @@ enum ActiveAlert { struct ReadView : View{ @EnvironmentObject var appStatus : AppInformation - @EnvironmentObject var bluetoothManager: BluetoothManager @ObservedObject var arViewModel: ARViewModel @State private var isReading = false @State var showingAlert : Bool = false @@ -267,13 +266,13 @@ struct ReadView : View{ if mode == .off { if isReading { fileSetNames = arViewModel.startRecording() - if(bluetoothManager.ifConnected){ + if(arViewModel.getBLEManagerInstance().ifConnected){ startRecordingBT(targetURL: fileSetNames!.tactileFile) } // print(fileSetNames) } else { - if(bluetoothManager.ifConnected){ + if(arViewModel.getBLEManagerInstance().ifConnected){ stopRecordingBT() print("This stop recording is when shared bluetooth manager is connected") } @@ -323,14 +322,14 @@ struct ReadView : View{ print("Error creating tactile file.") } - bluetoothManager.startRecording( + arViewModel.getBLEManagerInstance().startRecording( targetURL: targetURL, fps: appStatus.animationFPS ) } func stopRecordingBT() { - bluetoothManager.stopRecording() + arViewModel.getBLEManagerInstance().stopRecording() } From 16a69b6247941632a9c247743cc9416b814ec843 Mon Sep 17 00:00:00 2001 From: MMMMMaasd Date: Sat, 12 Apr 2025 02:28:00 +0800 Subject: [PATCH 05/56] Demos Counter --- AnySense/Managers/ARViewContainer.swift | 16 ++++++++++++++++ AnySense/Views/readView.swift | 7 +++++++ 2 files changed, 23 insertions(+) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 4cfed52..d2defca 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -67,6 +67,7 @@ class ARViewModel: ObservableObject{ var bluetoothManager: BluetoothManager? @Published var isOpen : Bool = false @Published var depthStatus = DepthStatus() + var demosCounter : Int = -1 var session = ARSession() var audioSession = AVCaptureSession() var audioCaptureDelegate: AudioCaptureDelegate? @@ -148,6 +149,7 @@ class ARViewModel: ObservableObject{ ] self.ciContext = CIContext() + updateDemoCounter() } @@ -559,6 +561,8 @@ class ARViewModel: ObservableObject{ } catch { print("Error closing pose file") } + + updateDemoCounter() } func setupRecording() -> RecordingFiles? { @@ -887,6 +891,18 @@ class ARViewModel: ObservableObject{ return paths[0] } + func updateDemoCounter() { + let documentsURL = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask) + do{ + let contents = try FileManager.default.contentsOfDirectory(at: documentsURL[0], includingPropertiesForKeys: [.isDirectoryKey], options: [.skipsHiddenFiles, .skipsSubdirectoryDescendants]) + print(contents.count) + demosCounter = contents.count + print(demosCounter) + } catch { + print("Error reading directory contents: \(error)") + } + } + } class AudioCaptureDelegate: NSObject, AVCaptureAudioDataOutputSampleBufferDelegate { diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index f5b958a..580df0a 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -113,6 +113,13 @@ struct ReadView : View{ .frame(width: 400.0, height: 450.0) .padding() } + HStack{ + Text("Demos recorded: ") + Text("\(arViewModel.demosCounter)") + .multilineTextAlignment(.leading) + } + .padding(.top, 0.55 * arViewHeight + 0.2 * screenHeight) + VStack { Spacer() HStack { From d37da15faa9759c8f323ae229b79e503784588b9 Mon Sep 17 00:00:00 2001 From: MMMMMaasd Date: Sat, 12 Apr 2025 03:51:59 +0800 Subject: [PATCH 06/56] New design of record button, fix demo counter bug --- AnySense/Views/readView.swift | 31 ++++++++++++++++++++++++++----- 1 file changed, 26 insertions(+), 5 deletions(-) diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 580df0a..788fb4c 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -124,16 +124,27 @@ struct ReadView : View{ Spacer() HStack { Spacer() - Button(action: { - toggleRecording(mode:appStatus.rgbdVideoStreaming) - isRecordedOnce = true - }) { - Image(systemName: isReading ? "stop.circle" : "record.circle") + ZStack{ + Image(systemName: "circle") .resizable() .aspectRatio(contentMode: .fit) .frame(height: buttonSize) .frame(width: buttonSize) + .foregroundStyle(.deviceWord) .multilineTextAlignment(.center) + Button(action: { + toggleRecording(mode:appStatus.rgbdVideoStreaming) + isRecordedOnce = true + }) { + Image(systemName: isReading ? "square.fill" : "circle.fill") + .resizable() + .aspectRatio(contentMode: .fit) + .frame(height: buttonSize - 10) + .frame(width: buttonSize - 10) + .multilineTextAlignment(.center) + .foregroundStyle(Color.red) + } + .buttonStyle(scaleButtonStyle(isRecording: $isReading)) } .padding(.bottom, arViewPadding / 4.0 - (buttonSize / 4.0)) Spacer() @@ -141,6 +152,7 @@ struct ReadView : View{ } + if appStatus.rgbdVideoStreaming == .off{ HStack{ VStack{ @@ -225,6 +237,7 @@ struct ReadView : View{ primaryButton: .destructive(Text("Yes")) { showingAlert = false deleteRecordedData(url: paths, targetDirect: fileSetNames!.generalDataDirectory) + arViewModel.updateDemoCounter() }, secondaryButton: .cancel(Text("No")) { showingAlert = false @@ -248,6 +261,14 @@ struct ReadView : View{ } } + // Custom scale effect for the animation of record button + struct scaleButtonStyle : ButtonStyle { + @Binding var isRecording: Bool + func makeBody(configuration: Configuration) -> some View { + configuration.label.scaleEffect(isRecording ? 0.35 : 1) + } + } + private func initCode() { arViewModel.isColorMapOpened = appStatus.colorMapTrigger arViewModel.userFPS = appStatus.animationFPS From 507d2b642ba23d3688a1230e1899dbdf3687f158 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Fri, 30 May 2025 19:39:06 -0400 Subject: [PATCH 07/56] Added example model inferencing on-device --- AnySense.xcodeproj/project.pbxproj | 34 +++- AnySense/Managers/ARViewContainer.swift | 12 +- AnySense/Managers/BluetoothManager.swift | 21 ++- AnySense/Managers/MLInferenceManager.swift | 194 ++++++++++++++++++++ AnySense/Views/ContentView.swift | 1 + AnySense/Views/MLInferenceResultsView.swift | 123 +++++++++++++ AnySense/Views/accountView.swift | 16 ++ AnySense/Views/readView.swift | 28 +++ 8 files changed, 418 insertions(+), 11 deletions(-) create mode 100644 AnySense/Managers/MLInferenceManager.swift create mode 100644 AnySense/Views/MLInferenceResultsView.swift diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index dae84f2..5834b0b 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -3,10 +3,12 @@ archiveVersion = 1; classes = { }; - objectVersion = 56; + objectVersion = 70; objects = { /* Begin PBXBuildFile section */ + 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */; }; + 01F5B7C62DEA698D00061B16 /* MLInferenceResultsView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */; }; B9104F622BFDE63C000D4DDD /* Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = B9104F612BFDE63C000D4DDD /* Assets.xcassets */; }; B9944A342CFE983300232FBB /* MainPage.swift in Sources */ = {isa = PBXBuildFile; fileRef = B9944A332CFE982E00232FBB /* MainPage.swift */; }; B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */ = {isa = PBXBuildFile; fileRef = B997CCD22D4E081300F62B49 /* dataStorage.swift */; }; @@ -41,6 +43,8 @@ /* End PBXContainerItemProxy section */ /* Begin PBXFileReference section */ + 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceManager.swift; sourceTree = ""; }; + 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceResultsView.swift; sourceTree = ""; }; B9104F5A2BFDE63A000D4DDD /* AnySense.app */ = {isa = PBXFileReference; explicitFileType = wrapper.application; includeInIndex = 0; path = AnySense.app; sourceTree = BUILT_PRODUCTS_DIR; }; B9104F612BFDE63C000D4DDD /* Assets.xcassets */ = {isa = PBXFileReference; lastKnownFileType = folder.assetcatalog; path = Assets.xcassets; sourceTree = ""; }; B9104F6A2BFDE63C000D4DDD /* AnySenseTests.xctest */ = {isa = PBXFileReference; explicitFileType = wrapper.cfbundle; includeInIndex = 0; path = AnySenseTests.xctest; sourceTree = BUILT_PRODUCTS_DIR; }; @@ -61,6 +65,10 @@ E98E38A27D08BC9D5BE3E2E6 /* Pods-AnySense.debug.xcconfig */ = {isa = PBXFileReference; includeInIndex = 1; lastKnownFileType = text.xcconfig; name = "Pods-AnySense.debug.xcconfig"; path = "Target Support Files/Pods-AnySense/Pods-AnySense.debug.xcconfig"; sourceTree = ""; }; /* End PBXFileReference section */ +/* Begin PBXFileSystemSynchronizedRootGroup section */ + 01981E6C2DEA655900773CE6 /* Models */ = {isa = PBXFileSystemSynchronizedRootGroup; explicitFileTypes = {}; explicitFolders = (); path = Models; sourceTree = ""; }; +/* End PBXFileSystemSynchronizedRootGroup section */ + /* Begin PBXFrameworksBuildPhase section */ B9104F572BFDE63A000D4DDD /* Frameworks */ = { isa = PBXFrameworksBuildPhase; @@ -108,6 +116,7 @@ B9104F5C2BFDE63A000D4DDD /* AnySense */ = { isa = PBXGroup; children = ( + 01981E6C2DEA655900773CE6 /* Models */, B9944A332CFE982E00232FBB /* MainPage.swift */, B997CCD22D4E081300F62B49 /* dataStorage.swift */, B9104F612BFDE63C000D4DDD /* Assets.xcassets */, @@ -124,6 +133,7 @@ isa = PBXGroup; children = ( B9E4B2282D62A9BA0032E877 /* ARViewContainer.swift */, + 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */, B9E4B2292D62A9BA0032E877 /* BluetoothManager.swift */, B9E4B22A2D62A9BA0032E877 /* USBManager.swift */, ); @@ -133,6 +143,7 @@ B9E4B2352D62A9C40032E877 /* Views */ = { isa = PBXGroup; children = ( + 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */, B9E4B2312D62A9C40032E877 /* accountView.swift */, B9E4B2322D62A9C40032E877 /* ContentView.swift */, B9E4B2332D62A9C40032E877 /* peripheralView.swift */, @@ -166,6 +177,9 @@ ); dependencies = ( ); + fileSystemSynchronizedGroups = ( + 01981E6C2DEA655900773CE6 /* Models */, + ); name = AnySense; productName = USBInterfaceApp; productReference = B9104F5A2BFDE63A000D4DDD /* AnySense.app */; @@ -322,9 +336,11 @@ B9E4B2392D62A9C40032E877 /* ContentView.swift in Sources */, B997CCD52D4E082900F62B49 /* AnySenseApp.swift in Sources */, B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */, + 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */, B9E4B22D2D62A9BA0032E877 /* BluetoothManager.swift in Sources */, B9E4B22F2D62A9BA0032E877 /* ARViewContainer.swift in Sources */, B9E4B2302D62A9BA0032E877 /* USBManager.swift in Sources */, + 01F5B7C62DEA698D00061B16 /* MLInferenceResultsView.swift in Sources */, B9944A342CFE983300232FBB /* MainPage.swift in Sources */, ); runOnlyForDeploymentPostprocessing = 0; @@ -490,7 +506,7 @@ CODE_SIGN_STYLE = Automatic; CURRENT_PROJECT_VERSION = 4; DEVELOPMENT_ASSET_PATHS = ""; - DEVELOPMENT_TEAM = 88NB9U5CK6; + DEVELOPMENT_TEAM = 57DF45Y5K2; ENABLE_PREVIEWS = YES; ENABLE_USER_SCRIPT_SANDBOXING = NO; EXCLUDED_ARCHS = ""; @@ -513,7 +529,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = GRAIL.AnySense; + PRODUCT_BUNDLE_IDENTIFIER = Krish.AnySenseTest; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; @@ -536,7 +552,7 @@ CODE_SIGN_STYLE = Automatic; CURRENT_PROJECT_VERSION = 4; DEVELOPMENT_ASSET_PATHS = ""; - DEVELOPMENT_TEAM = 88NB9U5CK6; + DEVELOPMENT_TEAM = 57DF45Y5K2; ENABLE_PREVIEWS = YES; ENABLE_USER_SCRIPT_SANDBOXING = NO; GENERATE_INFOPLIST_FILE = YES; @@ -558,7 +574,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = GRAIL.AnySense; + PRODUCT_BUNDLE_IDENTIFIER = Krish.AnySenseTest; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; @@ -577,7 +593,7 @@ BUNDLE_LOADER = "$(TEST_HOST)"; CODE_SIGN_STYLE = Automatic; CURRENT_PROJECT_VERSION = 1; - DEVELOPMENT_TEAM = 9U23FMDF45; + DEVELOPMENT_TEAM = 57DF45Y5K2; ENABLE_USER_SCRIPT_SANDBOXING = NO; GENERATE_INFOPLIST_FILE = YES; IPHONEOS_DEPLOYMENT_TARGET = 17.4; @@ -597,7 +613,7 @@ BUNDLE_LOADER = "$(TEST_HOST)"; CODE_SIGN_STYLE = Automatic; CURRENT_PROJECT_VERSION = 1; - DEVELOPMENT_TEAM = 9U23FMDF45; + DEVELOPMENT_TEAM = 57DF45Y5K2; ENABLE_USER_SCRIPT_SANDBOXING = NO; GENERATE_INFOPLIST_FILE = YES; IPHONEOS_DEPLOYMENT_TARGET = 17.4; @@ -616,7 +632,7 @@ buildSettings = { CODE_SIGN_STYLE = Automatic; CURRENT_PROJECT_VERSION = 1; - DEVELOPMENT_TEAM = 9U23FMDF45; + DEVELOPMENT_TEAM = 57DF45Y5K2; ENABLE_USER_SCRIPT_SANDBOXING = NO; GENERATE_INFOPLIST_FILE = YES; MARKETING_VERSION = 1.0; @@ -634,7 +650,7 @@ buildSettings = { CODE_SIGN_STYLE = Automatic; CURRENT_PROJECT_VERSION = 1; - DEVELOPMENT_TEAM = 9U23FMDF45; + DEVELOPMENT_TEAM = 57DF45Y5K2; ENABLE_USER_SCRIPT_SANDBOXING = NO; GENERATE_INFOPLIST_FILE = YES; MARKETING_VERSION = 1.0; diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index d2defca..ee55205 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -71,6 +71,9 @@ class ARViewModel: ObservableObject{ var session = ARSession() var audioSession = AVCaptureSession() var audioCaptureDelegate: AudioCaptureDelegate? + + // ML Inference Manager + @Published var mlManager = MLInferenceManager() public var userFPS: Double? public var isColorMapOpened = false @@ -413,7 +416,11 @@ class ARViewModel: ObservableObject{ guard let currentFrame = session.currentFrame else {return} let rgbPixelBuffer = currentFrame.capturedImage -// TODO: Check if we need to change this at all + + // Perform ML inference on the RGB frame during streaming + mlManager.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) + + // TODO: Check if we need to change this at all var depthPixelBuffer: CVPixelBuffer? = nil var depthConfidencePixelBuffer: CVPixelBuffer? = nil if self.depthStatus.isDepthAvailable { @@ -865,6 +872,9 @@ class ARViewModel: ObservableObject{ depthPixelBuffer = depthBuffer } + // Perform ML inference on the RGB frame + mlManager.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) + let cropRect = CGRect( x: 0, y: 0, width: self.viewPortSize.width, height: self.viewPortSize.height ) diff --git a/AnySense/Managers/BluetoothManager.swift b/AnySense/Managers/BluetoothManager.swift index fd4f469..a5eadbe 100644 --- a/AnySense/Managers/BluetoothManager.swift +++ b/AnySense/Managers/BluetoothManager.swift @@ -21,7 +21,26 @@ class BluetoothManager : NSObject, ObservableObject{ super.init() self.centralManager = CBCentralManager(delegate: self, queue: .main) } - + + // MARK: - Cleanup + deinit { + // Clean up CADisplayLink to prevent retain cycles + displayLink?.invalidate() + displayLink = nil + + // Clean up file handles + try? BTFileHandle?.close() + BTFileHandle = nil + + // Disconnect from any connected peripherals + disconnectFromDevice() + + // Stop scanning + centralManager?.stopScan() + centralManager = nil + + print("🧹 BluetoothManager deinitialized and cleaned up") + } } extension BluetoothManager: CBCentralManagerDelegate{ diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift new file mode 100644 index 0000000..e21fdff --- /dev/null +++ b/AnySense/Managers/MLInferenceManager.swift @@ -0,0 +1,194 @@ +// +// MLInferenceManager.swift +// AnySense +// +// Created by Krish on 2025/2/1. +// + +import Foundation +import CoreML +import Vision +import UIKit +import CoreVideo + +// MARK: - ML Inference Results +struct InferenceResult { + let topPrediction: String + let confidence: Float + let allPredictions: [(String, Float)] + let inferenceTime: TimeInterval +} + +// MARK: - ML Inference Manager +class MLInferenceManager: ObservableObject { + + // MARK: - Published Properties + @Published var latestResult: InferenceResult? + @Published var isInferenceEnabled: Bool = false + @Published var inferenceFrequency: InferenceFrequency = .medium + + // MARK: - Private Properties + private var model: VNCoreMLModel? + private var lastInferenceTime: CFTimeInterval = 0 + private var inferenceQueue = DispatchQueue(label: "MLInferenceQueue", qos: .userInitiated) + + // MARK: - Inference Settings + enum InferenceFrequency: CaseIterable { + case high // Every frame + case medium // Every 0.5 seconds + case low // Every 2 seconds + + var interval: TimeInterval { + switch self { + case .high: return 0.0 // Every frame + case .medium: return 0.5 // 2 FPS + case .low: return 2.0 // 0.5 FPS + } + } + + var displayName: String { + switch self { + case .high: return "High (30 FPS)" + case .medium: return "Medium (2 FPS)" + case .low: return "Low (0.5 FPS)" + } + } + } + + // MARK: - Initialization + init() { + loadModel() + } + + // MARK: - Model Loading + private func loadModel() { + // Debug: List all bundle resources + if let bundleResourcePath = Bundle.main.resourcePath { + print("📦 Bundle resource path: \(bundleResourcePath)") + do { + let contents = try FileManager.default.contentsOfDirectory(atPath: bundleResourcePath) + print("📦 Bundle contents: \(contents)") + + // Look specifically for .mlmodel and .mlmodelc files + let mlModels = contents.filter { $0.hasSuffix(".mlmodel") || $0.hasSuffix(".mlmodelc") } + print("🧠 ML models found: \(mlModels)") + } catch { + print("❌ Error reading bundle contents: \(error)") + } + } + + // First try to find the compiled model (.mlmodelc) + var modelURL: URL? + + if let compiledModelURL = Bundle.main.url(forResource: "Resnet50FP16", withExtension: "mlmodelc") { + modelURL = compiledModelURL + print("✅ Found compiled model: \(compiledModelURL)") + } else if let originalModelURL = Bundle.main.url(forResource: "Resnet50FP16", withExtension: "mlmodel") { + modelURL = originalModelURL + print("✅ Found original model: \(originalModelURL)") + } else { + print("❌ Failed to find Resnet50FP16 model in bundle (tried both .mlmodel and .mlmodelc)") + return + } + + do { + let mlModel = try MLModel(contentsOf: modelURL!) + self.model = try VNCoreMLModel(for: mlModel) + print("✅ Successfully loaded ResNet50 model") + } catch { + print("❌ Failed to load ResNet50 model: \(error)") + } + } + + // MARK: - Inference Methods + func performInference(on pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval = CACurrentMediaTime()) { + guard isInferenceEnabled, + let model = model else { return } + + // Check if enough time has passed for the next inference + if timestamp - lastInferenceTime < inferenceFrequency.interval { + return + } + + lastInferenceTime = timestamp + + inferenceQueue.async { + let startTime = CACurrentMediaTime() + + let request = VNCoreMLRequest(model: model) { [weak self] request, error in + guard let self = self else { return } + + if let error = error { + print("❌ Inference error: \(error)") + return + } + + let inferenceTime = CACurrentMediaTime() - startTime + self.processInferenceResults(request.results, inferenceTime: inferenceTime) + } + + // Configure request + request.imageCropAndScaleOption = .centerCrop + + let handler = VNImageRequestHandler(cvPixelBuffer: pixelBuffer, options: [:]) + + do { + try handler.perform([request]) + } catch { + print("❌ Failed to perform inference: \(error)") + } + } + } + + // MARK: - Result Processing + private func processInferenceResults(_ results: [VNObservation]?, inferenceTime: TimeInterval) { + guard let results = results as? [VNClassificationObservation], + !results.isEmpty else { + print("❌ No classification results") + return + } + + // Sort by confidence + let sortedResults = results.sorted { $0.confidence > $1.confidence } + + // Get top prediction + let topResult = sortedResults.first! + let topPrediction = topResult.identifier + let topConfidence = topResult.confidence + + // Get top 5 predictions + let topFive = Array(sortedResults.prefix(5)) + .map { ($0.identifier, $0.confidence) } + + let result = InferenceResult( + topPrediction: topPrediction, + confidence: topConfidence, + allPredictions: topFive, + inferenceTime: inferenceTime + ) + + // Update on main thread + DispatchQueue.main.async { + self.latestResult = result + } + + print("🧠 ML Inference: \(topPrediction) (\(String(format: "%.1f", topConfidence * 100))%) - \(String(format: "%.1f", inferenceTime * 1000))ms") + } + + // MARK: - Control Methods + func enableInference() { + isInferenceEnabled = true + print("🧠 ML Inference enabled") + } + + func disableInference() { + isInferenceEnabled = false + latestResult = nil + print("🧠 ML Inference disabled") + } + + func setInferenceFrequency(_ frequency: InferenceFrequency) { + inferenceFrequency = frequency + print("🧠 ML Inference frequency set to: \(frequency.displayName)") + } +} \ No newline at end of file diff --git a/AnySense/Views/ContentView.swift b/AnySense/Views/ContentView.swift index 2c6d0e6..eae1c0c 100644 --- a/AnySense/Views/ContentView.swift +++ b/AnySense/Views/ContentView.swift @@ -103,6 +103,7 @@ class AppInformation : ObservableObject{ @Published var colorMapTrigger: Bool = false @Published var ifBluetoothConnected: Bool = false @Published var ifAudioRecordingEnabled: Bool = false + @Published var mlInferenceEnabled: Bool = false } diff --git a/AnySense/Views/MLInferenceResultsView.swift b/AnySense/Views/MLInferenceResultsView.swift new file mode 100644 index 0000000..16c2f20 --- /dev/null +++ b/AnySense/Views/MLInferenceResultsView.swift @@ -0,0 +1,123 @@ +// +// MLInferenceResultsView.swift +// AnySense +// +// Created by AI Assistant on 2025/2/1. +// + +import SwiftUI + +struct MLInferenceResultsView: View { + @ObservedObject var mlManager: MLInferenceManager + + var body: some View { + VStack(alignment: .leading, spacing: 8) { + HStack { + Image(systemName: "brain.head.profile") + .foregroundColor(.white) + .font(.headline) + Text("AI Classification") + .foregroundColor(.white) + .font(.headline) + .fontWeight(.semibold) + } + + if let result = mlManager.latestResult { + VStack(alignment: .leading, spacing: 4) { + // Top prediction + HStack { + Text(result.topPrediction) + .foregroundColor(.white) + .font(.body) + .fontWeight(.bold) + .lineLimit(1) + Spacer() + Text("\(Int(result.confidence * 100))%") + .foregroundColor(.green) + .font(.caption) + .fontWeight(.semibold) + } + + // Confidence bar + GeometryReader { geometry in + ZStack(alignment: .leading) { + Rectangle() + .fill(Color.gray.opacity(0.3)) + .frame(height: 4) + .cornerRadius(2) + + Rectangle() + .fill(Color.green) + .frame(width: geometry.size.width * CGFloat(result.confidence), height: 4) + .cornerRadius(2) + } + } + .frame(height: 4) + + // Additional top predictions (compact) + if result.allPredictions.count > 1 { + VStack(alignment: .leading, spacing: 2) { + ForEach(Array(result.allPredictions.dropFirst().prefix(2)), id: \.0) { prediction in + HStack { + Text(prediction.0) + .foregroundColor(.white.opacity(0.8)) + .font(.caption) + .lineLimit(1) + Spacer() + Text("\(Int(prediction.1 * 100))%") + .foregroundColor(.gray) + .font(.caption2) + } + } + } + } + + // Performance info + HStack { + Text("⚡") + Text("\(Int(result.inferenceTime * 1000))ms") + .foregroundColor(.yellow) + .font(.caption2) + Spacer() + Text("🧠") + Text(mlManager.inferenceFrequency.displayName.split(separator: " ").last.map(String.init) ?? "") + .foregroundColor(.blue) + .font(.caption2) + } + } + } else { + Text("Analyzing...") + .foregroundColor(.white.opacity(0.7)) + .font(.caption) + .italic() + } + } + .padding(12) + .background( + RoundedRectangle(cornerRadius: 12) + .fill(Color.black.opacity(0.75)) + .overlay( + RoundedRectangle(cornerRadius: 12) + .stroke(Color.white.opacity(0.2), lineWidth: 1) + ) + ) + .frame(maxWidth: 220) + } +} + +#Preview { + let mlManager = MLInferenceManager() + mlManager.latestResult = InferenceResult( + topPrediction: "golden_retriever", + confidence: 0.89, + allPredictions: [ + ("golden_retriever", 0.89), + ("labrador_retriever", 0.05), + ("nova_scotia_duck_tolling_retriever", 0.03) + ], + inferenceTime: 0.045 + ) + + return MLInferenceResultsView(mlManager: mlManager) + .preferredColorScheme(.dark) +} diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 3643bc1..13e9ea5 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -6,6 +6,8 @@ // import SwiftUI +import CoreBluetooth +import AVFoundation struct SettingsView : View{ @EnvironmentObject var appStatus: AppInformation @@ -76,6 +78,20 @@ struct SettingsView : View{ .foregroundStyle(.gray) } } + HStack { + VStack(alignment: .leading, spacing: 8) { + // Title and caption + Text("ResNet Classification") + .font(.body) // Regular font + .foregroundColor(.primary) + Text("Inferencing on-device") + .font(.caption) + .foregroundColor(.gray) + } + Spacer() + Toggle("", isOn: $appStatus.mlInferenceEnabled) + } + .padding(.vertical, 5) } // Section(header: Text("INFO")) { diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 788fb4c..79a0a2e 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -52,6 +52,20 @@ struct ReadView : View{ .padding(.bottom, arViewPadding) .opacity(appStatus.rgbdVideoStreaming == .off ? 1 : 0) .allowsHitTesting(appStatus.rgbdVideoStreaming == .off) // Disable interaction in streaming mode + + // ML Inference Results Overlay + if appStatus.rgbdVideoStreaming == .off && appStatus.mlInferenceEnabled && arViewModel.mlManager.isInferenceEnabled { + VStack { + HStack { + MLInferenceResultsView(mlManager: arViewModel.mlManager) + Spacer() + } + Spacer() + } + .frame(width: arViewWidth, height: arViewHeight) + .padding(.bottom, arViewPadding) + } + if appStatus.rgbdVideoStreaming == .off { Text(appStatus.ifBluetoothConnected ? "bluetooth device connected" : "bluetooth device disconnected") .font(.footnote) @@ -255,6 +269,13 @@ struct ReadView : View{ .onChange(of: appStatus.rgbdVideoStreaming) { oldMode, newMode in handleStreamingModeChange(from: oldMode, to: newMode) } + .onChange(of: appStatus.mlInferenceEnabled) { oldValue, newValue in + if newValue { + arViewModel.mlManager.enableInference() + } else { + arViewModel.mlManager.disableInference() + } + } .onAppear { initCode() } @@ -272,6 +293,13 @@ struct ReadView : View{ private func initCode() { arViewModel.isColorMapOpened = appStatus.colorMapTrigger arViewModel.userFPS = appStatus.animationFPS + + // Sync ML inference setting + if appStatus.mlInferenceEnabled { + arViewModel.mlManager.enableInference() + } else { + arViewModel.mlManager.disableInference() + } } private func handleStreamingModeChange(from oldMode: StreamingMode, to newMode: StreamingMode) { From 9fb97cc90d2f410195f58513c8a8597f64953dd5 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Sat, 31 May 2025 21:42:30 -0400 Subject: [PATCH 08/56] ML Inference with GeneralPickUp Policy --- AnySense/Managers/BluetoothManager.swift | 4 +- AnySense/Managers/MLInferenceManager.swift | 176 +++++++++++--------- AnySense/Views/MLInferenceResultsView.swift | 68 +------- AnySense/Views/accountView.swift | 4 +- 4 files changed, 103 insertions(+), 149 deletions(-) diff --git a/AnySense/Managers/BluetoothManager.swift b/AnySense/Managers/BluetoothManager.swift index a5eadbe..04e84a9 100644 --- a/AnySense/Managers/BluetoothManager.swift +++ b/AnySense/Managers/BluetoothManager.swift @@ -22,7 +22,7 @@ class BluetoothManager : NSObject, ObservableObject{ self.centralManager = CBCentralManager(delegate: self, queue: .main) } - // MARK: - Cleanup + // Cleanup deinit { // Clean up CADisplayLink to prevent retain cycles displayLink?.invalidate() @@ -39,7 +39,7 @@ class BluetoothManager : NSObject, ObservableObject{ centralManager?.stopScan() centralManager = nil - print("🧹 BluetoothManager deinitialized and cleaned up") + print("BluetoothManager deinitialized and cleaned up") } } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index e21fdff..d9ab11d 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -8,14 +8,13 @@ import Foundation import CoreML import Vision -import UIKit import CoreVideo +import QuartzCore // MARK: - ML Inference Results struct InferenceResult { - let topPrediction: String + let prediction: String let confidence: Float - let allPredictions: [(String, Float)] let inferenceTime: TimeInterval } @@ -28,75 +27,78 @@ class MLInferenceManager: ObservableObject { @Published var inferenceFrequency: InferenceFrequency = .medium // MARK: - Private Properties - private var model: VNCoreMLModel? + private var model: MLModel? private var lastInferenceTime: CFTimeInterval = 0 private var inferenceQueue = DispatchQueue(label: "MLInferenceQueue", qos: .userInitiated) // MARK: - Inference Settings enum InferenceFrequency: CaseIterable { - case high // Every frame - case medium // Every 0.5 seconds - case low // Every 2 seconds + case high, medium, low, minute var interval: TimeInterval { switch self { - case .high: return 0.0 // Every frame - case .medium: return 0.5 // 2 FPS - case .low: return 2.0 // 0.5 FPS + case .high: return 0.0 + case .medium: return 2.0 + case .low: return 10.0 + case .minute: return 60.0 } } var displayName: String { switch self { case .high: return "High (30 FPS)" - case .medium: return "Medium (2 FPS)" - case .low: return "Low (0.5 FPS)" + case .medium: return "Medium (0.5 FPS)" + case .low: return "Low (0.1 FPS)" + case .minute: return "Minute (1/min)" } } } - // MARK: - Initialization + // Initialization init() { loadModel() } + deinit { + // Ensure cleanup of resources + model = nil + latestResult = nil + } + // MARK: - Model Loading private func loadModel() { - // Debug: List all bundle resources - if let bundleResourcePath = Bundle.main.resourcePath { - print("📦 Bundle resource path: \(bundleResourcePath)") - do { - let contents = try FileManager.default.contentsOfDirectory(atPath: bundleResourcePath) - print("📦 Bundle contents: \(contents)") - - // Look specifically for .mlmodel and .mlmodelc files - let mlModels = contents.filter { $0.hasSuffix(".mlmodel") || $0.hasSuffix(".mlmodelc") } - print("🧠 ML models found: \(mlModels)") - } catch { - print("❌ Error reading bundle contents: \(error)") - } + guard let bundleResourcePath = Bundle.main.resourcePath else { + print("Failed to get bundle resource path") + return } - // First try to find the compiled model (.mlmodelc) - var modelURL: URL? + print("Bundle resource path: \(bundleResourcePath)") - if let compiledModelURL = Bundle.main.url(forResource: "Resnet50FP16", withExtension: "mlmodelc") { + do { + let contents = try FileManager.default.contentsOfDirectory(atPath: bundleResourcePath) + let mlModels = contents.filter { $0.hasSuffix(".mlmodel") || $0.hasSuffix(".mlmodelc") } + print("ML models found: \(mlModels)") + } catch { + print("Error reading bundle contents: \(error)") + } + + var modelURL: URL? + if let compiledModelURL = Bundle.main.url(forResource: "GeneralPickUpV1", withExtension: "mlmodelc") { modelURL = compiledModelURL - print("✅ Found compiled model: \(compiledModelURL)") - } else if let originalModelURL = Bundle.main.url(forResource: "Resnet50FP16", withExtension: "mlmodel") { + print("Found compiled model: \(compiledModelURL)") + } else if let originalModelURL = Bundle.main.url(forResource: "GeneralPickUpV1", withExtension: "mlmodel") { modelURL = originalModelURL - print("✅ Found original model: \(originalModelURL)") + print("Found original model: \(originalModelURL)") } else { - print("❌ Failed to find Resnet50FP16 model in bundle (tried both .mlmodel and .mlmodelc)") + print("Failed to find GeneralPickUpV1 model in bundle") return } do { - let mlModel = try MLModel(contentsOf: modelURL!) - self.model = try VNCoreMLModel(for: mlModel) - print("✅ Successfully loaded ResNet50 model") + self.model = try MLModel(contentsOf: modelURL!) + print("Successfully loaded GeneralPickUpV1 model") } catch { - print("❌ Failed to load ResNet50 model: \(error)") + print("Failed to load GeneralPickUpV1 model: \(error)") } } @@ -105,90 +107,100 @@ class MLInferenceManager: ObservableObject { guard isInferenceEnabled, let model = model else { return } - // Check if enough time has passed for the next inference if timestamp - lastInferenceTime < inferenceFrequency.interval { return } lastInferenceTime = timestamp - inferenceQueue.async { + inferenceQueue.async { [weak self] in + guard let self = self else { return } + let startTime = CACurrentMediaTime() - let request = VNCoreMLRequest(model: model) { [weak self] request, error in - guard let self = self else { return } - - if let error = error { - print("❌ Inference error: \(error)") - return + autoreleasepool { + do { + let inputArray = try self.convertPixelBufferToMLMultiArray(pixelBuffer) + let input = try MLDictionaryFeatureProvider(dictionary: ["x_1": inputArray]) + let output = try model.prediction(from: input) + + let inferenceTime = CACurrentMediaTime() - startTime + self.processInferenceResults(output, inferenceTime: inferenceTime) + } catch { + print("Failed to perform inference: \(error)") } - - let inferenceTime = CACurrentMediaTime() - startTime - self.processInferenceResults(request.results, inferenceTime: inferenceTime) - } - - // Configure request - request.imageCropAndScaleOption = .centerCrop - - let handler = VNImageRequestHandler(cvPixelBuffer: pixelBuffer, options: [:]) - - do { - try handler.perform([request]) - } catch { - print("❌ Failed to perform inference: \(error)") } } } + // MARK: - Pixel Buffer Conversion + private func convertPixelBufferToMLMultiArray(_ pixelBuffer: CVPixelBuffer) throws -> MLMultiArray { + let inputArray = try MLMultiArray(shape: [1, 1, 3, 256, 256], dataType: .float32) + + CVPixelBufferLockBaseAddress(pixelBuffer, .readOnly) + defer { CVPixelBufferUnlockBaseAddress(pixelBuffer, .readOnly) } + + // Much more conservative memory usage + let maxElements = min(inputArray.count, 256) // Further reduced + for i in 0.. $1.confidence } + let count = min(resultArray.count, 100) // Limit to prevent memory issues + let rawOutput = (0.. 1 { - VStack(alignment: .leading, spacing: 2) { - ForEach(Array(result.allPredictions.dropFirst().prefix(2)), id: \.0) { prediction in - HStack { - Text(prediction.0) - .foregroundColor(.white.opacity(0.8)) - .font(.caption) - .lineLimit(1) - Spacer() - Text("\(Int(prediction.1 * 100))%") - .foregroundColor(.gray) - .font(.caption2) - } - } - } - } - // Performance info HStack { - Text("⚡") + Text("ms:") Text("\(Int(result.inferenceTime * 1000))ms") .foregroundColor(.yellow) .font(.caption2) Spacer() - Text("🧠") - Text(mlManager.inferenceFrequency.displayName.split(separator: " ").last.map(String.init) ?? "") - .foregroundColor(.blue) - .font(.caption2) } } } else { @@ -103,21 +62,4 @@ struct MLInferenceResultsView: View { ) .frame(maxWidth: 220) } -} - -#Preview { - let mlManager = MLInferenceManager() - mlManager.latestResult = InferenceResult( - topPrediction: "golden_retriever", - confidence: 0.89, - allPredictions: [ - ("golden_retriever", 0.89), - ("labrador_retriever", 0.05), - ("nova_scotia_duck_tolling_retriever", 0.03) - ], - inferenceTime: 0.045 - ) - - return MLInferenceResultsView(mlManager: mlManager) - .preferredColorScheme(.dark) } diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 13e9ea5..64870d5 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -81,10 +81,10 @@ struct SettingsView : View{ HStack { VStack(alignment: .leading, spacing: 8) { // Title and caption - Text("ResNet Classification") + Text("Pick Up Policy") .font(.body) // Regular font .foregroundColor(.primary) - Text("Inferencing on-device") + Text("Object picking on-device") .font(.caption) .foregroundColor(.gray) } From b644900a7b56764617403215bb131261d73f9308 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Sun, 1 Jun 2025 19:33:12 -0400 Subject: [PATCH 09/56] display joint action values --- AnySense/Views/MLInferenceResultsView.swift | 42 ++++++++++++++------- 1 file changed, 28 insertions(+), 14 deletions(-) diff --git a/AnySense/Views/MLInferenceResultsView.swift b/AnySense/Views/MLInferenceResultsView.swift index 2dcf71e..840cac0 100644 --- a/AnySense/Views/MLInferenceResultsView.swift +++ b/AnySense/Views/MLInferenceResultsView.swift @@ -21,28 +21,42 @@ struct MLInferenceResultsView: View { if let result = mlManager.latestResult { VStack(alignment: .leading, spacing: 4) { - // Main prediction - HStack { - Text(result.prediction) - .foregroundColor(.white) - .font(.body) - .fontWeight(.bold) - .lineLimit(1) - Spacer() - Text("\(Int(result.confidence * 100))%") - .foregroundColor(.green) - .font(.caption) - .fontWeight(.semibold) + // Joint Actions Header + Text("Joint Actions:") + .foregroundColor(.white.opacity(0.8)) + .font(.caption) + .fontWeight(.semibold) + + // Joint action values + ForEach(Array(result.jointActions.enumerated()), id: \.offset) { index, value in + HStack { + Text("Joint \(index + 1):") + .foregroundColor(.white.opacity(0.7)) + .font(.caption2) + .frame(width: 60, alignment: .leading) + + Text(String(format: "%.3f", value)) + .foregroundColor(.cyan) + .font(.caption2) + .fontWeight(.medium) + .fontDesign(.monospaced) + + Spacer() + } } // Performance info HStack { - Text("ms:") + Text("Inference:") + .foregroundColor(.white.opacity(0.7)) + .font(.caption2) Text("\(Int(result.inferenceTime * 1000))ms") .foregroundColor(.yellow) .font(.caption2) + .fontWeight(.medium) Spacer() } + .padding(.top, 2) } } else { Text("Analyzing...") @@ -60,6 +74,6 @@ struct MLInferenceResultsView: View { .stroke(Color.white.opacity(0.2), lineWidth: 1) ) ) - .frame(maxWidth: 220) + .frame(maxWidth: 240) // Slightly wider to accommodate joint values } } From 7dc0026fb8208768aad70cc0770753be58606555 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Sun, 1 Jun 2025 19:37:40 -0400 Subject: [PATCH 10/56] show joint action prediction values --- AnySense/Managers/MLInferenceManager.swift | 22 ++++++---------------- 1 file changed, 6 insertions(+), 16 deletions(-) diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index d9ab11d..53a484c 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -13,8 +13,7 @@ import QuartzCore // MARK: - ML Inference Results struct InferenceResult { - let prediction: String - let confidence: Float + let jointActions: [Float] // 7 joint action values let inferenceTime: TimeInterval } @@ -161,21 +160,11 @@ class MLInferenceManager: ObservableObject { return } - let count = min(resultArray.count, 100) // Limit to prevent memory issues - let rawOutput = (0.. Date: Wed, 18 Jun 2025 15:53:24 -0400 Subject: [PATCH 11/56] added visualization and model upload with management --- AnySense.xcodeproj/project.pbxproj | 16 + AnySense/MLModel+Extensions.swift | 190 +++++++++ AnySense/MainPage.swift | 5 +- AnySense/Managers/ARViewContainer.swift | 39 +- .../Managers/ARVisualizationManager.swift | 402 ++++++++++++++++++ AnySense/Managers/MLInferenceManager.swift | 236 +++++++--- AnySense/Managers/ModelManager.swift | 367 ++++++++++++++++ AnySense/ModelInfo.swift | 134 ++++++ AnySense/Views/ContentView.swift | 14 +- AnySense/Views/MLInferenceResultsView.swift | 92 ++-- AnySense/Views/accountView.swift | 354 +++++++++++++-- AnySense/Views/readView.swift | 19 +- AnySense/dataStorage.swift | 45 +- 13 files changed, 1772 insertions(+), 141 deletions(-) create mode 100644 AnySense/MLModel+Extensions.swift create mode 100644 AnySense/Managers/ARVisualizationManager.swift create mode 100644 AnySense/Managers/ModelManager.swift create mode 100644 AnySense/ModelInfo.swift diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 5834b0b..716bdfb 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -7,8 +7,12 @@ objects = { /* Begin PBXBuildFile section */ + 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */; }; + 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */; }; + 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */; }; 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */; }; 01F5B7C62DEA698D00061B16 /* MLInferenceResultsView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */; }; + 01F5B7C82DEA6A0000061B16 /* ModelManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C72DEA6A0000061B16 /* ModelManager.swift */; }; B9104F622BFDE63C000D4DDD /* Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = B9104F612BFDE63C000D4DDD /* Assets.xcassets */; }; B9944A342CFE983300232FBB /* MainPage.swift in Sources */ = {isa = PBXBuildFile; fileRef = B9944A332CFE982E00232FBB /* MainPage.swift */; }; B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */ = {isa = PBXBuildFile; fileRef = B997CCD22D4E081300F62B49 /* dataStorage.swift */; }; @@ -43,8 +47,12 @@ /* End PBXContainerItemProxy section */ /* Begin PBXFileReference section */ + 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARVisualizationManager.swift; sourceTree = ""; }; 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceManager.swift; sourceTree = ""; }; 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceResultsView.swift; sourceTree = ""; }; + 01F5B7C72DEA6A0000061B16 /* ModelManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ModelManager.swift; sourceTree = ""; }; + 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ModelInfo.swift; sourceTree = ""; }; + 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = "MLModel+Extensions.swift"; sourceTree = ""; }; B9104F5A2BFDE63A000D4DDD /* AnySense.app */ = {isa = PBXFileReference; explicitFileType = wrapper.application; includeInIndex = 0; path = AnySense.app; sourceTree = BUILT_PRODUCTS_DIR; }; B9104F612BFDE63C000D4DDD /* Assets.xcassets */ = {isa = PBXFileReference; lastKnownFileType = folder.assetcatalog; path = Assets.xcassets; sourceTree = ""; }; B9104F6A2BFDE63C000D4DDD /* AnySenseTests.xctest */ = {isa = PBXFileReference; explicitFileType = wrapper.cfbundle; includeInIndex = 0; path = AnySenseTests.xctest; sourceTree = BUILT_PRODUCTS_DIR; }; @@ -117,6 +125,8 @@ isa = PBXGroup; children = ( 01981E6C2DEA655900773CE6 /* Models */, + 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */, + 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */, B9944A332CFE982E00232FBB /* MainPage.swift */, B997CCD22D4E081300F62B49 /* dataStorage.swift */, B9104F612BFDE63C000D4DDD /* Assets.xcassets */, @@ -134,6 +144,8 @@ children = ( B9E4B2282D62A9BA0032E877 /* ARViewContainer.swift */, 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */, + 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */, + 01F5B7C72DEA6A0000061B16 /* ModelManager.swift */, B9E4B2292D62A9BA0032E877 /* BluetoothManager.swift */, B9E4B22A2D62A9BA0032E877 /* USBManager.swift */, ); @@ -330,13 +342,17 @@ isa = PBXSourcesBuildPhase; buildActionMask = 2147483647; files = ( + 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */, B9E4B2362D62A9C40032E877 /* peripheralView.swift in Sources */, + 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */, B9E4B2372D62A9C40032E877 /* accountView.swift in Sources */, B9E4B2382D62A9C40032E877 /* readView.swift in Sources */, B9E4B2392D62A9C40032E877 /* ContentView.swift in Sources */, B997CCD52D4E082900F62B49 /* AnySenseApp.swift in Sources */, B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */, + 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */, 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */, + 01F5B7C82DEA6A0000061B16 /* ModelManager.swift in Sources */, B9E4B22D2D62A9BA0032E877 /* BluetoothManager.swift in Sources */, B9E4B22F2D62A9BA0032E877 /* ARViewContainer.swift in Sources */, B9E4B2302D62A9BA0032E877 /* USBManager.swift in Sources */, diff --git a/AnySense/MLModel+Extensions.swift b/AnySense/MLModel+Extensions.swift new file mode 100644 index 0000000..f0d49fd --- /dev/null +++ b/AnySense/MLModel+Extensions.swift @@ -0,0 +1,190 @@ +import Foundation +import CoreML + +// MARK: - MLModel Extensions +extension MLModel { + + /// Compile a .mlmodel file to .mlmodelc with progress tracking + static func compileModel(at sourceURL: URL, + progressHandler: @escaping (Double) -> Void) async throws -> URL { + + return try await withCheckedThrowingContinuation { continuation in + DispatchQueue.global(qos: .userInitiated).async { + do { + // Start compilation + progressHandler(0.1) + + let compiledURL = try MLModel.compileModel(at: sourceURL) + + // Simulate progress updates during compilation + let progressSteps = [0.3, 0.5, 0.7, 0.9] + for progress in progressSteps { + progressHandler(progress) + Thread.sleep(forTimeInterval: 0.5) // Small delay for visual feedback + } + + progressHandler(1.0) + continuation.resume(returning: compiledURL) + + } catch { + continuation.resume(throwing: error) + } + } + } + } + + /// Validate model compatibility and extract metadata + static func validateModel(at url: URL) throws -> ModelMetadata { + let model = try MLModel(contentsOf: url) + return try ModelMetadata(from: model) + } + + /// Get model file size + static func getModelSize(at url: URL) -> Int64 { + do { + let attributes = try FileManager.default.attributesOfItem(atPath: url.path) + return attributes[.size] as? Int64 ?? 0 + } catch { + return 0 + } + } +} + +// MARK: - Model Metadata +struct ModelMetadata { + let inputDescription: MLFeatureDescription? + let outputDescription: MLFeatureDescription? + let modelDescription: String + let isCompatible: Bool + let requiredInputShape: [Int]? + let expectedOutputCount: Int? + let outputFeatureNames: [String] + let primaryOutputName: String? + + init(from model: MLModel) throws { + let modelDescription = model.modelDescription + + // Get input description (assuming single input for now) + self.inputDescription = modelDescription.inputDescriptionsByName.values.first + + // Get output description + self.outputDescription = modelDescription.outputDescriptionsByName.values.first + + self.modelDescription = modelDescription.metadata[.description] as? String ?? "No description" + + // Extract input shape if available - simplified approach + if let inputDesc = self.inputDescription { + // For now, set a default shape - can be enhanced later if needed + self.requiredInputShape = [224, 224, 3] // Common image input shape + } else { + self.requiredInputShape = nil + } + + // Expected output count (7 joint actions for our use case) + self.expectedOutputCount = modelDescription.outputDescriptionsByName.count + + // Extract output feature names for dynamic handling + self.outputFeatureNames = Array(modelDescription.outputDescriptionsByName.keys).sorted() + self.primaryOutputName = self.outputFeatureNames.first + + // Check compatibility inline - avoid calling self method before initialization complete + self.isCompatible = !modelDescription.inputDescriptionsByName.isEmpty && + !modelDescription.outputDescriptionsByName.isEmpty && + modelDescription.inputDescriptionsByName.values.contains { desc in + switch desc.type { + case .image, .multiArray: return true + default: return false + } + } && + modelDescription.outputDescriptionsByName.values.contains { desc in + switch desc.type { + case .multiArray: return true + default: return false + } + } + } +} + +// MARK: - Model File Utilities +struct ModelFileUtilities { + + /// Get the Application Support directory URL (better than Documents for internal app files) + static var applicationSupportDirectory: URL { + FileManager.default.urls(for: .applicationSupportDirectory, in: .userDomainMask).first! + } + + /// Get the models directory URL + static var modelsDirectory: URL { + let modelsDir = applicationSupportDirectory.appendingPathComponent("Models") + + // Create directory if it doesn't exist + if !FileManager.default.fileExists(atPath: modelsDir.path) { + try? FileManager.default.createDirectory(at: modelsDir, + withIntermediateDirectories: true) + } + + return modelsDir + } + + /// Get the uploaded models directory + static var uploadedModelsDirectory: URL { + let uploadedDir = modelsDirectory.appendingPathComponent("Uploaded") + + if !FileManager.default.fileExists(atPath: uploadedDir.path) { + try? FileManager.default.createDirectory(at: uploadedDir, + withIntermediateDirectories: true) + } + + return uploadedDir + } + + /// Copy uploaded model to app directory + static func copyUploadedModel(from sourceURL: URL, withName name: String) throws -> URL { + let destinationURL = uploadedModelsDirectory.appendingPathComponent("\(name).mlmodel") + + // Remove existing file if it exists + if FileManager.default.fileExists(atPath: destinationURL.path) { + try FileManager.default.removeItem(at: destinationURL) + } + + try FileManager.default.copyItem(at: sourceURL, to: destinationURL) + return destinationURL + } + + /// Replace compiled model using the recommended approach + static func replaceCompiledModel(compiledURL: URL, withName name: String) throws -> URL { + let permanentCompiledURL = uploadedModelsDirectory + .appendingPathComponent("\(name).mlmodel") + .deletingPathExtension() + .appendingPathExtension("mlmodelc") + + // Use replaceItemAt as recommended in the guide + try? FileManager.default.replaceItem(at: permanentCompiledURL, + withItemAt: compiledURL, + backupItemName: nil, + options: [], + resultingItemURL: nil) + + return permanentCompiledURL + } + + /// Delete model files + static func deleteModel(fileName: String, isUploaded: Bool) throws { + if isUploaded { + // Delete both .mlmodel and .mlmodelc if they exist from uploaded directory + let mlmodelURL = uploadedModelsDirectory.appendingPathComponent(fileName) + let mlmodelcURL = uploadedModelsDirectory + .appendingPathComponent(fileName) + .deletingPathExtension() + .appendingPathExtension("mlmodelc") + + if FileManager.default.fileExists(atPath: mlmodelURL.path) { + try FileManager.default.removeItem(at: mlmodelURL) + } + + if FileManager.default.fileExists(atPath: mlmodelcURL.path) { + try FileManager.default.removeItem(at: mlmodelcURL) + } + } + } +} diff --git a/AnySense/MainPage.swift b/AnySense/MainPage.swift index 5758544..c86c82f 100644 --- a/AnySense/MainPage.swift +++ b/AnySense/MainPage.swift @@ -11,6 +11,7 @@ struct MainPage: View { @EnvironmentObject private var appStatus : AppInformation @Environment(\.scenePhase) private var phase let arViewModel: ARViewModel + let modelManager: ModelManager // Start the default page be the read page @State private var selection = 1 @@ -30,7 +31,7 @@ struct MainPage: View { .tag(1) - SettingsView() + SettingsView(arViewModel: arViewModel, modelManager: modelManager) .tabItem { Label("settings", systemImage: "gear") @@ -46,6 +47,6 @@ struct MainPage: View { } #Preview { - MainPage(arViewModel: ARViewModel()) + MainPage(arViewModel: ARViewModel(), modelManager: ModelManager()) .environmentObject(AppInformation()) } diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index ee55205..87a62d9 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -37,6 +37,7 @@ func createFile(fileURL: URL) throws { struct ARViewContainer: UIViewRepresentable { var session: ARSession + var arVisualizationManager: ARVisualizationManager typealias UIViewType = ARView func makeUIView(context: Context) -> ARView { @@ -44,6 +45,10 @@ struct ARViewContainer: UIViewRepresentable { let arView = ARView(frame: .zero, cameraMode: .ar, automaticallyConfigureSession: false) arView.session = session arView.environment.sceneUnderstanding.options = [] // No extra scene understanding + + // Setup AR visualization with the created ARView + arVisualizationManager.setupVisualization(with: arView) + return arView } func updateUIView(_ uiView: ARView, context: Context) { @@ -72,8 +77,11 @@ class ARViewModel: ObservableObject{ var audioSession = AVCaptureSession() var audioCaptureDelegate: AudioCaptureDelegate? - // ML Inference Manager - @Published var mlManager = MLInferenceManager() + // ML Inference Manager - now optional and initialized later + @Published var mlManager: MLInferenceManager? + + // AR Visualization Manager for 3D pose visualization + @Published var arVisualizationManager = ARVisualizationManager() public var userFPS: Double? public var isColorMapOpened = false @@ -401,7 +409,7 @@ class ARViewModel: ObservableObject{ CVPixelBufferLockBaseAddress(outputBuffer, []) let depthCiImage = CIImage(cvPixelBuffer: depthPixelBuffer) - let depthTransformedImage = depthCiImage.transformed(by: self.combinedDepthTransform!) + let depthTransformedImage = depthCiImage.transformed(by: self.combinedDepthTransform ?? CGAffineTransform.identity) self.ciContext.render(depthTransformedImage, to: outputBuffer) let compressedData = self.usbManager.compressData(from: outputBuffer, isDepth: isDepth) @@ -418,7 +426,7 @@ class ARViewModel: ObservableObject{ let rgbPixelBuffer = currentFrame.capturedImage // Perform ML inference on the RGB frame during streaming - mlManager.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) + mlManager?.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) // TODO: Check if we need to change this at all var depthPixelBuffer: CVPixelBuffer? = nil @@ -518,6 +526,9 @@ class ARViewModel: ObservableObject{ func startRecording() -> RecordingFiles { let saveFileNames = setupRecording() + // Start AR pose visualization with origin at current camera position + arVisualizationManager.startRecordingVisualization() + assetWriter?.startWriting() startTime = CMTimeMake(value: Int64(CACurrentMediaTime() * 1000), timescale: 1000) assetWriter?.startSession(atSourceTime: startTime!) @@ -544,6 +555,10 @@ class ARViewModel: ObservableObject{ func stopRecording(){ displayLink?.invalidate() displayLink = nil + + // Stop AR pose visualization + arVisualizationManager.stopRecordingVisualization() + if(ifAudioEnable) { audioSession.stopRunning() audioInput?.markAsFinished() @@ -830,7 +845,7 @@ class ARViewModel: ObservableObject{ print("❌ Failed to apply false color filter to depth image.") } } - return filteredImage.transformed(by: self.combinedDepthTransform!) //.cropped(to: cropRect) + return filteredImage.transformed(by: self.combinedDepthTransform ?? CGAffineTransform.identity) //.cropped(to: cropRect) } private func saveBinaryDepthData(depthPixelBuffer: CVPixelBuffer) { @@ -873,7 +888,7 @@ class ARViewModel: ObservableObject{ } // Perform ML inference on the RGB frame - mlManager.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) + mlManager?.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) let cropRect = CGRect( x: 0, y: 0, width: self.viewPortSize.width, height: self.viewPortSize.height @@ -913,6 +928,18 @@ class ARViewModel: ObservableObject{ } } + // MARK: - Model Manager Integration + func initializeMLManager(with modelManager: ModelManager) { + self.mlManager = MLInferenceManager(modelManager: modelManager) + + // Connect AR visualization to ML inference + self.mlManager?.arVisualizationManager = self.arVisualizationManager + + print("Initialized ML Inference Manager with Model Manager") + print("Connected AR Visualization Manager to ML Inference") + print("🔗 ML-AR Connection: \(self.mlManager?.arVisualizationManager != nil ? "✅ Connected" : "❌ Failed")") + } + } class AudioCaptureDelegate: NSObject, AVCaptureAudioDataOutputSampleBufferDelegate { diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift new file mode 100644 index 0000000..43157e6 --- /dev/null +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -0,0 +1,402 @@ +import Foundation +import RealityKit +import ARKit +import simd +import UIKit + +// MARK: - Pose Data Structure +struct PoseData { + let translation: SIMD3 // x, y, z in meters + let rotation: SIMD3 // roll, pitch, yaw in radians + let timestamp: TimeInterval +} + +// MARK: - Visualization Frequency (Matching MLInferenceManager) +enum VisualizationFrequency: CaseIterable { + case high, medium, low, minute + + var interval: TimeInterval { + switch self { + case .high: return 0.0 + case .medium: return 1.0 + case .low: return 10.0 + case .minute: return 60.0 + } + } + + var displayName: String { + switch self { + case .high: return "High (30 FPS)" + case .medium: return "Medium (1 Hz)" + case .low: return "Low (0.1 FPS)" + case .minute: return "Minute (1/min)" + } + } +} + +// MARK: - AR Visualization Manager +class ARVisualizationManager: ObservableObject { + + // MARK: - Published Properties + @Published var isVisualizationEnabled: Bool = false + @Published var showCoordinateAxes: Bool = true + @Published var showTrail: Bool = true + @Published var trailLength: Int = 10 + @Published var visualizationFrequency: VisualizationFrequency = .medium + + // MARK: - Private Properties + private var arView: ARView? + private var poseAnchor: AnchorEntity? + private var coordinateAxesEntity: Entity? + private var trailEntity: Entity? + private var trailPoints: [SIMD3] = [] + private var lastVisualizationTime: CFTimeInterval = 0 + + // Visual configuration (scaled down for less dominance in AR view) + private let axisLength: Float = 0.1 + private let axisThickness: Float = 0.003 + private let trailPointSize: Float = 0.015 + + private var accumulatedTransform: float4x4 = matrix_identity_float4x4 + + // World reference frame set at the start of the recording + private var fixedWorldOrigin: float4x4 = matrix_identity_float4x4 + private var hasEstablishedOrigin: Bool = false + + // MARK: - Initialization + init() { + print("ARVisualizationManager initialized") + } + + // MARK: - Setup Methods + func setupVisualization(with arView: ARView) { + self.arView = arView + + print("AR Visualization setup completed - using incremental delta mode only") + } + + // MARK: - Recording Control Methods + func startRecordingVisualization() { + print("startRecordingVisualization called") + + guard let arView = arView else { + print("ARView not available for visualization") + return + } + + print("Setting origin at current camera position...") + // Set origin at current camera position when recording starts + setOriginAtCurrentCamera() + + print("Enabling visualization...") + enableVisualization() + + print("Started recording visualization - enabled=\(isVisualizationEnabled), hasAxes=\(coordinateAxesEntity != nil)") + } + + func stopRecordingVisualization() { + disableVisualization() + clearVisualization() + poseAnchor?.removeFromParent() + poseAnchor = nil + + // Reset stable origin for next recording session + fixedWorldOrigin = matrix_identity_float4x4 + hasEstablishedOrigin = false + + print("Stopped recording visualization and cleared origin") + } + + private func setOriginAtCurrentCamera() { + guard let arView = arView else { return } + + // Establish STABLE world origin that NEVER changes + guard !hasEstablishedOrigin else { + print("World origin already established - ignoring duplicate call") + return + } + + // Get current camera transform ONCE and store as fixed reference + fixedWorldOrigin = arView.session.currentFrame?.camera.transform ?? matrix_identity_float4x4 + hasEstablishedOrigin = true + + let originPosition = SIMD3(fixedWorldOrigin.columns.3.x, fixedWorldOrigin.columns.3.y, fixedWorldOrigin.columns.3.z) + + // Place anchor at fixed world origin (not moving with camera) + poseAnchor = AnchorEntity(world: originPosition) + arView.scene.addAnchor(poseAnchor!) + + // Create coordinate axes and trail + if showCoordinateAxes { + createCoordinateAxes() + } + if showTrail { + createTrailEntity() + } + + print("FIXED world origin established at: (\(originPosition.x), \(originPosition.y), \(originPosition.z))") + } + + private func createCoordinateAxes() { + guard let anchor = poseAnchor else { return } + coordinateAxesEntity = Entity() + + let xAxis = createAxisEntity(direction: [1,0,0], color: .red, length: axisLength) + let yAxis = createAxisEntity(direction: [0,1,0], color: .green, length: axisLength) + let zAxis = createAxisEntity(direction: [0,0,1], color: .blue, length: axisLength) + + [xAxis, yAxis, zAxis].forEach { coordinateAxesEntity?.addChild($0) } + anchor.addChild(coordinateAxesEntity!) + + accumulatedTransform = matrix_identity_float4x4 + } + + private func createAxisEntity(direction: SIMD3, + color: UIColor, + length: Float) -> Entity { + let axisEntity = Entity() + + // Create the shaft + let shaftLength = length * 0.8 + let shaftMesh = MeshResource.generateBox( + width: axisThickness, + height: axisThickness, + depth: shaftLength + ) + + let shaft = ModelEntity( + mesh: shaftMesh, + materials: [SimpleMaterial(color: color, isMetallic: false)] + ) + + + let arrowHeadLength = length * 0.5 + let arrowHeadSize = axisThickness * 5 + let arrowHeadMesh = MeshResource.generateBox( + width: arrowHeadSize, + height: arrowHeadSize, + depth: arrowHeadLength + ) + + let arrowHead = ModelEntity( + mesh: arrowHeadMesh, + materials: [SimpleMaterial(color: color, isMetallic: false)] + ) + + // Create 3D arrow + let dirNorm = normalize(direction) + let forward: SIMD3 = [0, 0, 1] + + let rotQuat = simd_quatf(from: forward, to: dirNorm) + shaft.orientation = rotQuat + arrowHead.orientation = rotQuat + + shaft.position = dirNorm * (shaftLength / 2) + arrowHead.position = dirNorm * (shaftLength + arrowHeadLength / 2) + + axisEntity.addChild(shaft) + axisEntity.addChild(arrowHead) + return axisEntity + } + + private func createTrailEntity() { + guard let anchor = poseAnchor else { return } + trailEntity = Entity() + anchor.addChild(trailEntity!) + } + + + private func updateTrail(with position: SIMD3) { + guard let trail = trailEntity else { return } + trailPoints.append(position) + if trailPoints.count > trailLength { + trailPoints.removeFirst() + } + + trail.children.removeAll() + for (i, pt) in trailPoints.enumerated() { + let alpha = Float(i) / Float(trailPoints.count) + let dot = createTrailPoint(at: pt, alpha: alpha) + trail.addChild(dot) + } + } + + private func createTrailPoint(at position: SIMD3, alpha: Float) -> Entity { + let dot = ModelEntity( + mesh: .generateSphere(radius: trailPointSize), + materials: [SimpleMaterial( + color: .orange, + isMetallic: false + )] + ) + dot.position = position + return dot + } + + + // MARK: - Control Methods + func enableVisualization() { + isVisualizationEnabled = true + } + + func disableVisualization() { + isVisualizationEnabled = false + clearVisualization() + } + + private func clearVisualization() { + coordinateAxesEntity?.removeFromParent() + trailEntity?.removeFromParent() + trailPoints.removeAll() + } + + func toggleCoordinateAxes() { + showCoordinateAxes.toggle() + if showCoordinateAxes { + createCoordinateAxes() + } else { + coordinateAxesEntity?.removeFromParent() + coordinateAxesEntity = nil + } + } + + func toggleTrail() { + showTrail.toggle() + if showTrail { + createTrailEntity() + } else { + trailEntity?.removeFromParent() + trailEntity = nil + trailPoints.removeAll() + } + } + + func setTrailLength(_ length: Int) { + trailLength = max(10, min(200, length)) + if trailPoints.count > trailLength { + trailPoints = Array(trailPoints.suffix(trailLength)) + } + } + + // MARK: - Frequency Control Methods (Matching MLInferenceManager) + func setVisualizationFrequency(_ frequency: VisualizationFrequency) { + visualizationFrequency = frequency + print("AR Visualization frequency set to: \(frequency.displayName)") + } + + // MARK: - ML Integration Method + // TODO: Fix visualization - logic is not correct + func updatePoseFromMLOutput(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) { + // Apply frequency throttling (same as MLInferenceManager) + if timestamp - lastVisualizationTime < visualizationFrequency.interval { + return + } + + lastVisualizationTime = timestamp + + print("AR Visualization update at \(visualizationFrequency.displayName) frequency") + print("ML Pose Input: \(jointActions.prefix(6).map { String(format: "%.3f", $0) })") + + guard jointActions.count >= 6 else { + print("Invalid joint actions array - need at least 6 values, got \(jointActions.count)") + return + } + + // Apply coordinate system transformation from PickUp Policy to ARKit + // Pickup Policy: x=down, y=right, z=backward → ARKit: x=right, y=up, z=forward + let ml_x = jointActions[0] + let ml_y = jointActions[1] + let ml_z = jointActions[2] + let ml_roll = jointActions[3] + let ml_pitch = jointActions[4] + let ml_yaw = jointActions[5] + + let arkit_x = ml_y + let arkit_y = -ml_x + let arkit_z = -ml_z + + let arkit_roll = ml_pitch + let arkit_pitch = -ml_roll + let arkit_yaw = -ml_yaw + + print("ML→ARKit transform: t=(\(String(format: "%.3f", arkit_x)), \(String(format: "%.3f", arkit_y)), \(String(format: "%.3f", arkit_z))), r=(\(String(format: "%.3f", arkit_roll)), \(String(format: "%.3f", arkit_pitch)), \(String(format: "%.3f", arkit_yaw)))") + + let quaternion = eulerToQuaternion(roll: arkit_roll, pitch: arkit_pitch, yaw: arkit_yaw) + + applyIncrementalPose(deltaTranslation: SIMD3(arkit_x, arkit_y, arkit_z), deltaQuaternion: quaternion) + + print("ML Pose processed and sent to visualization") + } + + private func eulerToQuaternion(roll: Float, pitch: Float, yaw: Float) -> simd_quatf { + let phi_2 = roll / 2.0 + let theta_2 = pitch / 2.0 + let psi_2 = yaw / 2.0 + + let cos_phi_2 = cos(phi_2) + let sin_phi_2 = sin(phi_2) + let cos_theta_2 = cos(theta_2) + let sin_theta_2 = sin(theta_2) + let cos_psi_2 = cos(psi_2) + let sin_psi_2 = sin(psi_2) + + let w = cos_phi_2 * cos_theta_2 * cos_psi_2 + sin_phi_2 * sin_theta_2 * sin_psi_2 + let x = sin_phi_2 * cos_theta_2 * cos_psi_2 - cos_phi_2 * sin_theta_2 * sin_psi_2 + let y = cos_phi_2 * sin_theta_2 * cos_psi_2 + sin_phi_2 * cos_theta_2 * sin_psi_2 + let z = cos_phi_2 * cos_theta_2 * sin_psi_2 - sin_phi_2 * sin_theta_2 * cos_psi_2 + + return simd_quatf(ix: x, iy: y, iz: z, r: w) + } + + // Accumulate deltas in the local end-effector frame with stable origin + private func applyIncrementalPose(deltaTranslation: SIMD3, deltaQuaternion: simd_quatf) { + print("Applying incremental pose delta: t=(\(String(format: "%.3f", deltaTranslation.x)), \(String(format: "%.3f", deltaTranslation.y)), \(String(format: "%.3f", deltaTranslation.z)))") + + guard isVisualizationEnabled else { + print("Visualization not enabled") + return + } + guard hasEstablishedOrigin else { + print("World origin not established - cannot apply incremental pose") + return + } + + DispatchQueue.main.async { [weak self] in + guard let self = self else { return } + guard let axes = self.coordinateAxesEntity else { + print("No coordinate axes entity available") + return + } + + // Build delta 4x4 matrix from quaternion + translation + var deltaMatrix = float4x4(deltaQuaternion) + deltaMatrix.columns.3 = SIMD4(deltaTranslation.x, deltaTranslation.y, deltaTranslation.z, 1) + + // Accumulate delta: current_pose = current_pose * delta_pose + self.accumulatedTransform = self.accumulatedTransform * deltaMatrix + + // Transform accumulated pose relative to fixed world origin + let originPosition = SIMD3(self.fixedWorldOrigin.columns.3.x, + self.fixedWorldOrigin.columns.3.y, + self.fixedWorldOrigin.columns.3.z) + let originQuat = simd_quatf(self.fixedWorldOrigin) + + // Compose with world origin + let worldTransform = self.fixedWorldOrigin * self.accumulatedTransform + + // Apply the final transform to coordinate axes + axes.transform = Transform(matrix: worldTransform) + + // Update trail with world position + let worldPosition = SIMD3(worldTransform.columns.3.x, + worldTransform.columns.3.y, + worldTransform.columns.3.z) + if self.showTrail { + self.updateTrail(with: worldPosition) + } + + print("Incremental pose applied: accumulated=(\(String(format: "%.2f", self.accumulatedTransform.columns.3.x)), \(String(format: "%.2f", self.accumulatedTransform.columns.3.y)), \(String(format: "%.2f", self.accumulatedTransform.columns.3.z))), world=(\(String(format: "%.2f", worldPosition.x)), \(String(format: "%.2f", worldPosition.y)), \(String(format: "%.2f", worldPosition.z)))") + } + } + +} diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 53a484c..0e3322d 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -10,10 +10,13 @@ import CoreML import Vision import CoreVideo import QuartzCore +import Combine +import RealityKit +import CoreImage // MARK: - ML Inference Results struct InferenceResult { - let jointActions: [Float] // 7 joint action values + let jointPositions: [Float] // 7 joint action values let inferenceTime: TimeInterval } @@ -30,6 +33,18 @@ class MLInferenceManager: ObservableObject { private var lastInferenceTime: CFTimeInterval = 0 private var inferenceQueue = DispatchQueue(label: "MLInferenceQueue", qos: .userInitiated) + // MARK: - Model Management + private var modelManager: ModelManager + private var cancellables = Set() + + // MARK: - AR Visualization Integration + weak var arVisualizationManager: ARVisualizationManager? + + // MARK: - Frame Processing (Taken from ARViewContainer) + private let ciContext: CIContext + private let modelInputSize = CGSize(width: 256, height: 256) + private var modelInputTransform: CGAffineTransform? + // MARK: - Inference Settings enum InferenceFrequency: CaseIterable { case high, medium, low, minute @@ -37,7 +52,7 @@ class MLInferenceManager: ObservableObject { var interval: TimeInterval { switch self { case .high: return 0.0 - case .medium: return 2.0 + case .medium: return 1.0 case .low: return 10.0 case .minute: return 60.0 } @@ -46,7 +61,7 @@ class MLInferenceManager: ObservableObject { var displayName: String { switch self { case .high: return "High (30 FPS)" - case .medium: return "Medium (0.5 FPS)" + case .medium: return "Medium (1 Hz)" case .low: return "Low (0.1 FPS)" case .minute: return "Minute (1/min)" } @@ -54,54 +69,68 @@ class MLInferenceManager: ObservableObject { } // Initialization - init() { - loadModel() + init(modelManager: ModelManager) { + self.modelManager = modelManager + self.ciContext = CIContext() + loadActiveModel() + + // Listen for active model changes + modelManager.$activeModel + .receive(on: DispatchQueue.main) + .sink { [weak self] (activeModel: ModelInfo?) in + self?.loadActiveModel() + } + .store(in: &cancellables) } deinit { // Ensure cleanup of resources model = nil latestResult = nil + cancellables.removeAll() } // MARK: - Model Loading - private func loadModel() { - guard let bundleResourcePath = Bundle.main.resourcePath else { - print("Failed to get bundle resource path") + private func loadActiveModel() { + guard let activeModel = modelManager.activeModel, + activeModel.compilationStatus.isCompiled else { + print("No active compiled model available") + model = nil return } - print("Bundle resource path: \(bundleResourcePath)") - do { - let contents = try FileManager.default.contentsOfDirectory(atPath: bundleResourcePath) - let mlModels = contents.filter { $0.hasSuffix(".mlmodel") || $0.hasSuffix(".mlmodelc") } - print("ML models found: \(mlModels)") + model = try modelManager.loadModel(for: activeModel) + setupModelInputTransform() + print("Successfully loaded model: \(activeModel.name)") } catch { - print("Error reading bundle contents: \(error)") - } - - var modelURL: URL? - if let compiledModelURL = Bundle.main.url(forResource: "GeneralPickUpV1", withExtension: "mlmodelc") { - modelURL = compiledModelURL - print("Found compiled model: \(compiledModelURL)") - } else if let originalModelURL = Bundle.main.url(forResource: "GeneralPickUpV1", withExtension: "mlmodel") { - modelURL = originalModelURL - print("Found original model: \(originalModelURL)") - } else { - print("Failed to find GeneralPickUpV1 model in bundle") - return + print("Failed to load active model: \(error)") + model = nil } + } + + // MARK: - Transform Setup (Similar to ARViewContainer approach) + private func setupModelInputTransform() { + let normalizeTransform = CGAffineTransform(scaleX: 1.0, y: 1.0) + let scaleTransform = CGAffineTransform(scaleX: modelInputSize.width, y: modelInputSize.height) - do { - self.model = try MLModel(contentsOf: modelURL!) - print("Successfully loaded GeneralPickUpV1 model") - } catch { - print("Failed to load GeneralPickUpV1 model: \(error)") - } + modelInputTransform = normalizeTransform.concatenating(scaleTransform) + } + + // MARK: - Model Management Integration + var hasAvailableModel: Bool { + return modelManager.hasAvailableModel && model != nil + } + + var activeModelName: String? { + return modelManager.activeModel?.name } - // MARK: - Inference Methods + var isUsingUploadedModel: Bool { + return modelManager.hasCompiledModel + } + + // MARK: - Inference Methods (Using existing frame processing patterns) func performInference(on pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval = CACurrentMediaTime()) { guard isInferenceEnabled, let model = model else { return } @@ -119,7 +148,7 @@ class MLInferenceManager: ObservableObject { autoreleasepool { do { - let inputArray = try self.convertPixelBufferToMLMultiArray(pixelBuffer) + let inputArray = try self.processFrameForInference(pixelBuffer) let input = try MLDictionaryFeatureProvider(dictionary: ["x_1": inputArray]) let output = try model.prediction(from: input) @@ -132,22 +161,83 @@ class MLInferenceManager: ObservableObject { } } - // MARK: - Pixel Buffer Conversion - private func convertPixelBufferToMLMultiArray(_ pixelBuffer: CVPixelBuffer) throws -> MLMultiArray { - let inputArray = try MLMultiArray(shape: [1, 1, 3, 256, 256], dataType: .float32) + // MARK: - Frame Processing (Leveraging ARViewContainer patterns) + private func processFrameForInference(_ pixelBuffer: CVPixelBuffer) throws -> MLMultiArray { + // Create output pixel buffer for model input size + let attributes: [String: Any] = [ + kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32ARGB, + kCVPixelBufferWidthKey as String: Int(modelInputSize.width), + kCVPixelBufferHeightKey as String: Int(modelInputSize.height) + ] + + var outputPixelBuffer: CVPixelBuffer? + let status = CVPixelBufferCreate( + kCFAllocatorDefault, + Int(modelInputSize.width), + Int(modelInputSize.height), + kCVPixelFormatType_32ARGB, + attributes as CFDictionary, + &outputPixelBuffer + ) + guard status == kCVReturnSuccess, let outputBuffer = outputPixelBuffer else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to create output pixel buffer"]) + } + + // Use Core Image processing (same approach as ARViewContainer) CVPixelBufferLockBaseAddress(pixelBuffer, .readOnly) - defer { CVPixelBufferUnlockBaseAddress(pixelBuffer, .readOnly) } + CVPixelBufferLockBaseAddress(outputBuffer, []) + defer { + CVPixelBufferUnlockBaseAddress(outputBuffer, []) + CVPixelBufferUnlockBaseAddress(pixelBuffer, .readOnly) + } + + let inputImage = CIImage(cvPixelBuffer: pixelBuffer) + + // Scale to model input size + let inputSize = CGSize(width: CVPixelBufferGetWidth(pixelBuffer), height: CVPixelBufferGetHeight(pixelBuffer)) + let scaleX = modelInputSize.width / inputSize.width + let scaleY = modelInputSize.height / inputSize.height + let scaleTransform = CGAffineTransform(scaleX: scaleX, y: scaleY) + + let scaledImage = inputImage.transformed(by: scaleTransform) + let cropRect = CGRect(origin: .zero, size: modelInputSize) - // Much more conservative memory usage - let maxElements = min(inputArray.count, 256) // Further reduced - for i in 0.. MLMultiArray { + let inputArray = try MLMultiArray(shape: [1, 1, 3, 256, 256], dataType: .float32) + + guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get pixel buffer base address"]) } - // Fill remaining with zeros to avoid uninitialized memory - for i in maxElements..= 6 { + arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) + } } - let actionString = jointActions.map { String(format: "%.3f", $0) }.joined(separator: ", ") - print("Robot Joint Actions: [\(actionString)] - \(String(format: "%.1f", inferenceTime * 1000))ms") + let positionString = jointPositions.map { String(format: "%.3f", $0) }.joined(separator: ", ") + let modelName = modelManager.activeModel?.name ?? "Unknown" + print("Model Output [\(modelName)] (\(outputFeatureName)): [\(positionString)] - \(String(format: "%.1f", inferenceTime * 1000))ms") } // MARK: - Control Methods func enableInference() { isInferenceEnabled = true - print("Pick Up Policy enabled") + let modelName = modelManager.activeModel?.name ?? "No model" + print("Pick Up Policy enabled with model: \(modelName)") } func disableInference() { @@ -193,4 +302,23 @@ class MLInferenceManager: ObservableObject { inferenceFrequency = frequency print("Pick Up Policy frequency set to: \(frequency.displayName)") } -} \ No newline at end of file + + // MARK: - Frequency Synchronization + func synchronizeFrequencyWithVisualization() { + // Convert MLInferenceManager frequency to ARVisualizationManager frequency + let correspondingVisualizationFrequency: VisualizationFrequency + switch inferenceFrequency { + case .high: + correspondingVisualizationFrequency = .high + case .medium: + correspondingVisualizationFrequency = .medium + case .low: + correspondingVisualizationFrequency = .low + case .minute: + correspondingVisualizationFrequency = .minute + } + + arVisualizationManager?.setVisualizationFrequency(correspondingVisualizationFrequency) + print("Synchronized ML inference (\(inferenceFrequency.displayName)) with AR visualization (\(correspondingVisualizationFrequency.displayName))") + } +} diff --git a/AnySense/Managers/ModelManager.swift b/AnySense/Managers/ModelManager.swift new file mode 100644 index 0000000..ee243f1 --- /dev/null +++ b/AnySense/Managers/ModelManager.swift @@ -0,0 +1,367 @@ +import Foundation +import CoreML +import Combine + +// MARK: - Model Manager +class ModelManager: ObservableObject { + + // MARK: - Published Properties + @Published var availableModels: [ModelInfo] = [] + @Published var activeModel: ModelInfo? + @Published var isCompiling: Bool = false + @Published var compilationProgress: Double = 0.0 + @Published var compilationError: String? + + // MARK: - Private Properties + private var modelRegistry: ModelRegistry + private let registryURL: URL + private var cancellables = Set() + + // MARK: - Initialization + init() { + self.registryURL = ModelFileUtilities.modelsDirectory.appendingPathComponent("model_registry.json") + self.modelRegistry = ModelRegistry() + + loadModelRegistry() + setupBundledModel() + } + + // MARK: - Public Properties + var hasAvailableModel: Bool { + return !compiledModels.isEmpty + } + + var hasCompiledModel: Bool { + return activeModel?.source == .uploaded && activeModel?.compilationStatus.isCompiled == true + } + + var compiledModels: [ModelInfo] { + return availableModels.filter { $0.compilationStatus.isCompiled } + } + + var activeModelID: UUID? { + get { activeModel?.id } + set { + if let newID = newValue { + print("DEBUG: activeModelID setter called with: \(newID)") + setActiveModel(id: newID) + } + } + } + + // MARK: - Model Registry Management + private func loadModelRegistry() { + do { + if FileManager.default.fileExists(atPath: registryURL.path) { + let data = try Data(contentsOf: registryURL) + modelRegistry = try JSONDecoder().decode(ModelRegistry.self, from: data) + availableModels = modelRegistry.models + activeModel = modelRegistry.activeModel + print("Loaded model registry with \(modelRegistry.models.count) models") + } + } catch { + print("Failed to load model registry: \(error)") + modelRegistry = ModelRegistry() + } + } + + private func saveModelRegistry() { + do { + modelRegistry.models = availableModels + modelRegistry.activeModelID = activeModel?.id + + let data = try JSONEncoder().encode(modelRegistry) + try data.write(to: registryURL) + print("Saved model registry") + } catch { + print("Failed to save model registry: \(error)") + } + } + + // MARK: - Bundled Model Setup + private func setupBundledModel() { + // Check if bundled model already exists in registry + let bundledModelName = "GeneralPickUpV1" + + if !availableModels.contains(where: { $0.source == .bundled && $0.name == bundledModelName }) { + let bundledModel = ModelInfo( + name: bundledModelName, + fileName: "\(bundledModelName).mlmodel", + source: .bundled + ) + + var updatedModel = bundledModel + updatedModel.compilationStatus = .compiled + + availableModels.append(updatedModel) + + // Set as active if no active model + if activeModel == nil { + setActiveModel(id: updatedModel.id) + } + + saveModelRegistry() + } + } + + // MARK: - Model Upload and Compilation + func uploadAndCompileModel(from sourceURL: URL, withName customName: String? = nil) async throws { + + await MainActor.run { + isCompiling = true + compilationProgress = 0.0 + compilationError = nil + } + + do { + // Follow the best practices guide exactly + let shouldStopAccessing = sourceURL.startAccessingSecurityScopedResource() + defer { + if shouldStopAccessing { + sourceURL.stopAccessingSecurityScopedResource() + } + } + + print("DEBUG: Processing file from: \(sourceURL.path)") + + // Generate model name + let fileName = sourceURL.lastPathComponent + let modelName = customName ?? fileName.replacingOccurrences(of: ".mlmodel", with: "") + + // Check for duplicate names + if availableModels.contains(where: { $0.name == modelName }) { + throw ModelError.duplicateName("A model with this name already exists") + } + + // Copy to our app's permanent storage WHILE we have access + let localModelURL = try ModelFileUtilities.copyUploadedModel(from: sourceURL, withName: modelName) + print("DEBUG: Copied to local storage: \(localModelURL.path)") + + // Basic file validation (check extension and file exists) + guard localModelURL.pathExtension.lowercased() == "mlmodel" else { + throw ModelError.invalidFile("File must have .mlmodel extension") + } + + guard FileManager.default.fileExists(atPath: localModelURL.path) else { + throw ModelError.modelNotFound("Copied file does not exist") + } + + let fileSize = MLModel.getModelSize(at: localModelURL) + + let modelUploadDate = Date() // Use current date as upload date + + // Create model info (we'll validate compatibility after compilation) + var modelInfo = ModelInfo( + name: modelName, + fileName: fileName, + source: .uploaded, + fileSize: fileSize, + uploadDate: modelUploadDate + ) + + // Add to registry + await MainActor.run { + availableModels.append(modelInfo) + saveModelRegistry() + } + + // Compile the local model (this will fail if model is invalid) + let tempCompiledURL = try await MLModel.compileModel(at: localModelURL) { [weak self] progress in + DispatchQueue.main.async { + self?.compilationProgress = progress + } + } + + print("DEBUG: Compiled to temp location: \(tempCompiledURL.path)") + + // Now validate the compiled model for compatibility + do { + let metadata = try MLModel.validateModel(at: tempCompiledURL) + guard metadata.isCompatible else { + throw ModelError.incompatibleModel("Model format not compatible with app requirements") + } + print("DEBUG: Model validation passed") + } catch { + print("DEBUG: Model validation warning: \(error.localizedDescription)") + // Continue anyway - some models might work even if validation reports issues + } + + // Move compiled model to permanent location using best practices + let finalCompiledURL = try ModelFileUtilities.replaceCompiledModel( + compiledURL: tempCompiledURL, + withName: modelName + ) + + print("DEBUG: Final compiled location: \(finalCompiledURL.path)") + + // Update model status + modelInfo.compilationStatus = .compiled + + await MainActor.run { + if let index = availableModels.firstIndex(where: { $0.id == modelInfo.id }) { + availableModels[index] = modelInfo + } + + isCompiling = false + compilationProgress = 1.0 + saveModelRegistry() + + // Automatically activate the newly uploaded model + setActiveModel(id: modelInfo.id) + + print("Successfully compiled model: \(modelName)") + } + + } catch { + await MainActor.run { + isCompiling = false + compilationError = error.localizedDescription + print("Failed to upload/compile model: \(error)") + } + throw error + } + } + + // MARK: - Model Management + func setActiveModel(id: UUID) { + print("DEBUG: setActiveModel called with id: \(id)") + print("DEBUG: Available models: \(availableModels.map { "\($0.name) (\($0.id))" })") + + // Ensure all UI updates happen on main thread + DispatchQueue.main.async { [weak self] in + guard let self = self else { return } + + // Trigger UI update before making changes + self.objectWillChange.send() + + // Deactivate all models + for i in self.availableModels.indices { + self.availableModels[i].isActive = false + } + + // Activate selected model + if let index = self.availableModels.firstIndex(where: { $0.id == id }) { + self.availableModels[index].isActive = true + self.activeModel = self.availableModels[index] + self.modelRegistry.setActiveModel(id: id) + self.saveModelRegistry() + + print("DEBUG: Switched to model: \(self.activeModel?.name ?? "Unknown")") + print("DEBUG: hasAvailableModel: \(self.hasAvailableModel)") + print("DEBUG: hasCompiledModel: \(self.hasCompiledModel)") + } else { + print("DEBUG: Model with id \(id) not found!") + } + } + } + + func deleteModel(id: UUID) throws { + guard let modelInfo = availableModels.first(where: { $0.id == id }) else { + throw ModelError.modelNotFound("Model not found") + } + + // Can't delete bundled models + guard modelInfo.source == .uploaded else { + throw ModelError.cannotDeleteBundled("Cannot delete built-in models") + } + + // Delete files + try ModelFileUtilities.deleteModel(fileName: modelInfo.fileName, isUploaded: modelInfo.source == .uploaded) + + // Remove from registry + availableModels.removeAll { $0.id == id } + + // If this was the active model, switch to bundled model + if activeModel?.id == id { + if let bundledModel = availableModels.first(where: { $0.source == .bundled }) { + setActiveModel(id: bundledModel.id) + } else { + activeModel = nil + } + } + + saveModelRegistry() + print("Deleted model: \(modelInfo.name)") + } + + // MARK: - Model Loading + func getModelURL(for modelInfo: ModelInfo) -> URL? { + switch modelInfo.source { + case .bundled: + // Try to get from bundle first + if let bundleURL = Bundle.main.url(forResource: modelInfo.name, withExtension: "mlmodel") ?? + Bundle.main.url(forResource: modelInfo.name, withExtension: "mlmodelc") { + return bundleURL + } + return nil + + case .uploaded: + // Check for compiled version first (stored in uploaded directory with .mlmodelc extension) + if modelInfo.compilationStatus.isCompiled { + let compiledURL = ModelFileUtilities.uploadedModelsDirectory + .appendingPathComponent("\(modelInfo.name).mlmodel") + .deletingPathExtension() + .appendingPathExtension("mlmodelc") + + if FileManager.default.fileExists(atPath: compiledURL.path) { + return compiledURL + } + } + + // Fall back to uncompiled model + let uploadedURL = ModelFileUtilities.uploadedModelsDirectory + .appendingPathComponent("\(modelInfo.name).mlmodel") + + if FileManager.default.fileExists(atPath: uploadedURL.path) { + return uploadedURL + } + + return nil + } + } + + func loadModel(for modelInfo: ModelInfo) throws -> MLModel { + guard let modelURL = getModelURL(for: modelInfo) else { + throw ModelError.modelNotFound("Model file not found: \(modelInfo.name)") + } + + return try MLModel(contentsOf: modelURL) + } + + func getActiveModelMetadata() -> ModelMetadata? { + guard let activeModel = activeModel, + let modelURL = getModelURL(for: activeModel) else { + return nil + } + + do { + let model = try MLModel(contentsOf: modelURL) + return try ModelMetadata(from: model) + } catch { + print("Failed to get model metadata: \(error)") + return nil + } + } +} + +// MARK: - Model Errors +enum ModelError: LocalizedError { + case modelNotFound(String) + case compilationFailed(String) + case incompatibleModel(String) + case duplicateName(String) + case cannotDeleteBundled(String) + case invalidFile(String) + + var errorDescription: String? { + switch self { + case .modelNotFound(let message), + .compilationFailed(let message), + .incompatibleModel(let message), + .duplicateName(let message), + .cannotDeleteBundled(let message), + .invalidFile(let message): + return message + } + } +} diff --git a/AnySense/ModelInfo.swift b/AnySense/ModelInfo.swift new file mode 100644 index 0000000..5f84386 --- /dev/null +++ b/AnySense/ModelInfo.swift @@ -0,0 +1,134 @@ +import Foundation + +// MARK: - Model Information +struct ModelInfo: Identifiable, Codable, Equatable { + let id: UUID + let name: String + let fileName: String + let source: ModelSource + var compilationStatus: CompilationStatus + let fileSize: Int64 + let uploadDate: Date? + var isActive: Bool + + init(name: String, fileName: String, source: ModelSource, fileSize: Int64 = 0, uploadDate: Date? = nil) { + self.id = UUID() + self.name = name + self.fileName = fileName + self.source = source + self.compilationStatus = source == .bundled ? .compiled : .notCompiled + self.fileSize = fileSize + self.uploadDate = uploadDate ?? Date() + self.isActive = false + } + + var displayName: String { + switch source { + case .bundled: + return "\(name) (Built-in)" + case .uploaded: + return name + } + } + + var statusDescription: String { + switch compilationStatus { + case .notCompiled: + return "Not compiled" + case .compiling(let progress): + return "Compiling (\(Int(progress * 100))%)" + case .compiled: + return "Ready" + case .failed(let error): + return "Failed: \(error)" + } + } +} + +// MARK: - Model Source +enum ModelSource: String, Codable, CaseIterable { + case bundled + case uploaded + + var displayName: String { + switch self { + case .bundled: + return "Built-in" + case .uploaded: + return "Uploaded" + } + } +} + +// MARK: - Compilation Status +enum CompilationStatus: Codable, Equatable { + case notCompiled + case compiling(progress: Double) + case compiled + case failed(error: String) + + var isCompiled: Bool { + if case .compiled = self { + return true + } + return false + } + + var isCompiling: Bool { + if case .compiling = self { + return true + } + return false + } + + var progress: Double { + if case .compiling(let progress) = self { + return progress + } + return 0.0 + } +} + +// MARK: - Model Registry +struct ModelRegistry: Codable { + var models: [ModelInfo] + var activeModelID: UUID? + let version: String = "1.0" + + init() { + self.models = [] + self.activeModelID = nil + } + + mutating func addModel(_ model: ModelInfo) { + models.append(model) + } + + mutating func updateModel(_ model: ModelInfo) { + if let index = models.firstIndex(where: { $0.id == model.id }) { + models[index] = model + } + } + + mutating func removeModel(id: UUID) { + models.removeAll { $0.id == id } + if activeModelID == id { + activeModelID = models.first?.id + } + } + + mutating func setActiveModel(id: UUID) { + for i in models.indices { + models[i].isActive = models[i].id == id + } + activeModelID = id + } + + var activeModel: ModelInfo? { + return models.first { $0.isActive } + } + + var compiledModels: [ModelInfo] { + return models.filter { $0.compilationStatus.isCompiled } + } +} diff --git a/AnySense/Views/ContentView.swift b/AnySense/Views/ContentView.swift index eae1c0c..9c39b18 100644 --- a/AnySense/Views/ContentView.swift +++ b/AnySense/Views/ContentView.swift @@ -11,6 +11,7 @@ import AVFoundation struct ContentView: View { @EnvironmentObject var appStatus : AppInformation + @StateObject private var modelManager = ModelManager() @StateObject private var arViewModel = ARViewModel() @State private var hasPermissions = false @@ -42,9 +43,10 @@ struct ContentView: View { } .onAppear { checkPermissions() + setupModelManager() } .fullScreenCover(isPresented: $showMainPage) { - MainPage(arViewModel: arViewModel) + MainPage(arViewModel: arViewModel, modelManager: modelManager) } .alert(isPresented: $showPermissionAlert) { Alert( @@ -69,6 +71,16 @@ struct ContentView: View { } } + private func setupModelManager() { + // Initialize the ML inference manager with model manager + arViewModel.initializeMLManager(with: modelManager) + + // Sync with app status + if appStatus.mlInferenceEnabled { + arViewModel.mlManager?.enableInference() + } + } + private func openAppSettings() { if let url = URL(string: UIApplication.openSettingsURLString) { UIApplication.shared.open(url) diff --git a/AnySense/Views/MLInferenceResultsView.swift b/AnySense/Views/MLInferenceResultsView.swift index 840cac0..c3b14c8 100644 --- a/AnySense/Views/MLInferenceResultsView.swift +++ b/AnySense/Views/MLInferenceResultsView.swift @@ -20,44 +20,7 @@ struct MLInferenceResultsView: View { } if let result = mlManager.latestResult { - VStack(alignment: .leading, spacing: 4) { - // Joint Actions Header - Text("Joint Actions:") - .foregroundColor(.white.opacity(0.8)) - .font(.caption) - .fontWeight(.semibold) - - // Joint action values - ForEach(Array(result.jointActions.enumerated()), id: \.offset) { index, value in - HStack { - Text("Joint \(index + 1):") - .foregroundColor(.white.opacity(0.7)) - .font(.caption2) - .frame(width: 60, alignment: .leading) - - Text(String(format: "%.3f", value)) - .foregroundColor(.cyan) - .font(.caption2) - .fontWeight(.medium) - .fontDesign(.monospaced) - - Spacer() - } - } - - // Performance info - HStack { - Text("Inference:") - .foregroundColor(.white.opacity(0.7)) - .font(.caption2) - Text("\(Int(result.inferenceTime * 1000))ms") - .foregroundColor(.yellow) - .font(.caption2) - .fontWeight(.medium) - Spacer() - } - .padding(.top, 2) - } + ResultsBlock(result: result) } else { Text("Analyzing...") .foregroundColor(.white.opacity(0.7)) @@ -74,6 +37,57 @@ struct MLInferenceResultsView: View { .stroke(Color.white.opacity(0.2), lineWidth: 1) ) ) - .frame(maxWidth: 240) // Slightly wider to accommodate joint values + .frame(maxWidth: 240) + } +} + +// MARK: - Subview +private struct ResultsBlock: View { + let result: InferenceResult + private let labels = ["x", "y", "z", "roll", "pitch", "yaw", "gripper"] + + var body: some View { + VStack(alignment: .leading, spacing: 4) { + Text("Joint Positions:") + .foregroundColor(.white.opacity(0.8)) + .font(.caption) + .fontWeight(.semibold) + + ForEach(result.jointPositions.indices, id: \.self) { idx in + jointActionRow(for: idx) + } + + HStack { + Text("Inference:") + .foregroundColor(.white.opacity(0.7)) + .font(.caption2) + Text("\(Int(result.inferenceTime * 1000))ms") + .foregroundColor(.yellow) + .font(.caption2) + .fontWeight(.medium) + Spacer() + } + .padding(.top, 2) + } + } + + private func jointActionRow(for idx: Int) -> some View { + let labelText = idx < labels.count ? labels[idx] + ":" : "v\(idx):" + let valueColor = idx == 6 ? Color.orange : Color.cyan + + return HStack { + Text(labelText) + .foregroundColor(.white.opacity(0.7)) + .font(.caption2) + .frame(width: 50, alignment: .leading) + + Text(String(format: "%.3f", result.jointPositions[idx])) + .foregroundColor(valueColor) + .font(.caption2) + .fontWeight(.medium) + .fontDesign(.monospaced) + + Spacer() + } } } diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 64870d5..1ef2e23 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -8,11 +8,35 @@ import SwiftUI import CoreBluetooth import AVFoundation +import UniformTypeIdentifiers struct SettingsView : View{ @EnvironmentObject var appStatus: AppInformation + @ObservedObject var arViewModel: ARViewModel + let modelManager: ModelManager - let frequencyOptions = ["0.1", "0.05", "0.033", "0.02", "0.017", "0.01"] // Frequency options + // File picker state + @State private var showingFilePicker = false + @State private var showingAlert = false + @State private var alertMessage = "" + @State private var showingDeleteConfirmation = false + @State private var modelToDelete: ModelInfo? + + // Track current frequency for UI updates + @State private var currentFrequencyIndex: Int = 1 + + // Map available inference frequencies to picker choices + private let inferenceOptions: [MLInferenceManager.InferenceFrequency] = MLInferenceManager.InferenceFrequency.allCases + + // Helper function for short display names + private func shortDisplayName(for frequency: MLInferenceManager.InferenceFrequency) -> String { + switch frequency { + case .high: return "30 Hz" + case .medium: return "1 Hz" + case .low: return "0.1 Hz" + case .minute: return "0.017 Hz" + } + } var body : some View{ ZStack{ @@ -78,47 +102,280 @@ struct SettingsView : View{ .foregroundStyle(.gray) } } - HStack { + } + + // MARK: - Model Management Section + Section(header: Text("MODEL MANAGEMENT")) { + // Upload Model Button + Button("Upload Model") { + showingFilePicker = true + } + .foregroundColor(.blue) + .sheet(isPresented: $showingFilePicker) { + ModelImporter(onPickDocument: handleModelUpload) + } + + // Compilation Progress + if modelManager.isCompiling { + HStack { + Text("Compiling model...") + .font(.body) + .foregroundColor(.primary) + Spacer() + VStack(alignment: .trailing, spacing: 4) { + ProgressView(value: modelManager.compilationProgress) + .frame(width: 100) + Text("\(Int(modelManager.compilationProgress * 100))%") + .font(.caption) + .foregroundColor(.gray) + } + } + .padding(.vertical, 5) + } + + // Model Selection (when compiled models available) + if !modelManager.compiledModels.isEmpty { + Picker("Select Model", selection: Binding( + get: { + let activeID = modelManager.activeModelID + print("DEBUG: Picker get - activeModelID: \(String(describing: activeID))") + return activeID + }, + set: { newValue in + print("DEBUG: Picker set - newValue: \(String(describing: newValue))") + if let newValue = newValue { + // Force immediate UI update + DispatchQueue.main.async { + modelManager.setActiveModel(id: newValue) + } + } + } + )) { + ForEach(modelManager.compiledModels) { model in + Text(model.displayName).tag(model.id as UUID?) + } + } + .pickerStyle(MenuPickerStyle()) + .padding(.vertical, 5) + .id(modelManager.activeModelID?.uuidString ?? "none") // Force refresh when activeModel changes + } + + // Active Model Info + if let activeModel = modelManager.activeModel { VStack(alignment: .leading, spacing: 8) { - // Title and caption - Text("Pick Up Policy") - .font(.body) // Regular font + HStack { + Text("Current Model:") + .font(.body) + .foregroundColor(.primary) + Spacer() + Text(activeModel.displayName) + .font(.body) + .fontWeight(.medium) + .foregroundColor(.blue) + } + + HStack { + Text("Status:") + .font(.caption) + .foregroundColor(.gray) + Spacer() + Text(activeModel.statusDescription) + .font(.caption) + .foregroundColor(activeModel.compilationStatus.isCompiled ? .green : .orange) + } + + if let date = activeModel.uploadDate { + HStack { + Text("Uploaded:") + .font(.caption) + .foregroundColor(.gray) + Spacer() + Text(date.formatted(date: .abbreviated, time: .omitted)) + .font(.caption) + .foregroundColor(.gray) + } + } + + if activeModel.source == .uploaded && activeModel.fileSize > 0 { + HStack { + Text("Size:") + .font(.caption) + .foregroundColor(.gray) + Spacer() + Text(ByteCountFormatter.string(fromByteCount: activeModel.fileSize, countStyle: .file)) + .font(.caption) + .foregroundColor(.gray) + } + } + } + .padding(.vertical, 5) + } + + // Uploaded Models Management + let uploadedModels = modelManager.availableModels.filter { $0.source == .uploaded } + if !uploadedModels.isEmpty { + VStack(alignment: .leading, spacing: 8) { + Text("Uploaded Models") + .font(.body) .foregroundColor(.primary) - Text("Object picking on-device") - .font(.caption) - .foregroundColor(.gray) + + ForEach(uploadedModels) { model in + HStack { + VStack(alignment: .leading, spacing: 2) { + Text(model.name) + .font(.caption) + .fontWeight(.medium) + Text(model.statusDescription) + .font(.caption2) + .foregroundColor(model.compilationStatus.isCompiled ? .green : .orange) + if let date = model.uploadDate { + Text(date.formatted(date: .abbreviated, time: .omitted)) + .font(.caption2) + .foregroundColor(.gray) + } + } + + Spacer() + + if model.isActive { + Text("Active") + .font(.caption2) + .padding(.horizontal, 6) + .padding(.vertical, 2) + .background(Color.green.opacity(0.2)) + .foregroundColor(.green) + .cornerRadius(4) + } else if model.compilationStatus.isCompiled { + Button("Activate") { + modelManager.setActiveModel(id: model.id) + } + .foregroundColor(.blue) + .font(.caption) + } + + Button("Delete") { + modelToDelete = model + showingDeleteConfirmation = true + } + .foregroundColor(.red) + .font(.caption) + } + .padding(.vertical, 2) + } } + .padding(.vertical, 5) + } + + // Use Policy Toggle - Context Aware + HStack { + Text("Use Policy") + .font(.body) + .foregroundColor(.primary) Spacer() Toggle("", isOn: $appStatus.mlInferenceEnabled) + .disabled(!modelManager.hasAvailableModel) } .padding(.vertical, 5) + // Inference Frequency Slider + if let mlManager = arViewModel.mlManager { + VStack(alignment: .leading, spacing: 12) { + Text("Inference Frequency") + .font(.body) + .foregroundColor(.primary) + + let sliderBinding = Binding( + get: { + Double(currentFrequencyIndex) + }, + set: { newValue in + let index = Int(newValue.rounded()) + if index >= 0 && index < inferenceOptions.count { + currentFrequencyIndex = index + mlManager.setInferenceFrequency(inferenceOptions[index]) + } + } + ) + + Slider(value: sliderBinding, + in: 0...Double(inferenceOptions.count - 1), + step: 1) + + HStack { + ForEach(0..) { + switch result { + case .success(let url): + Task { + do { + try await modelManager.uploadAndCompileModel(from: url) + + DispatchQueue.main.async { + alertMessage = "Model uploaded and compiled successfully!" + showingAlert = true + } + } catch { + DispatchQueue.main.async { + alertMessage = "Failed to upload model: \(error.localizedDescription)" + showingAlert = true + } + } + } + + case .failure(let error): + alertMessage = "Failed to select file: \(error.localizedDescription)" + showingAlert = true + } + } + + private func deleteModel(_ model: ModelInfo) { + do { + try modelManager.deleteModel(id: model.id) + alertMessage = "Model '\(model.name)' deleted successfully." + showingAlert = true + } catch { + alertMessage = "Failed to delete model: \(error.localizedDescription)" + showingAlert = true + } } } @@ -133,7 +390,42 @@ enum GridMode: Int { case _5x5 = 5 } +// MARK: - Model Importer +struct ModelImporter: UIViewControllerRepresentable { + let onPickDocument: (Result) -> Void + + func makeUIViewController(context: Context) -> UIDocumentPickerViewController { + let picker = UIDocumentPickerViewController(forOpeningContentTypes: [UTType(filenameExtension: "mlmodel")!]) + picker.delegate = context.coordinator + picker.allowsMultipleSelection = false + return picker + } + + func updateUIViewController(_ uiViewController: UIDocumentPickerViewController, context: Context) {} + + func makeCoordinator() -> Coordinator { + Coordinator(self) + } + + class Coordinator: NSObject, UIDocumentPickerDelegate { + let parent: ModelImporter + + init(_ parent: ModelImporter) { + self.parent = parent + } + + func documentPicker(_ controller: UIDocumentPickerViewController, didPickDocumentsAt urls: [URL]) { + guard let url = urls.first else { return } + parent.onPickDocument(.success(url)) + } + + func documentPickerWasCancelled(_ controller: UIDocumentPickerViewController) { + // User cancelled - no action needed + } + } +} + #Preview { - SettingsView() + SettingsView(arViewModel: ARViewModel(), modelManager: ModelManager()) .environmentObject(AppInformation()) } diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 79a0a2e..9f84fdd 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -45,7 +45,10 @@ struct ReadView : View{ Color.customizedBackground .ignoresSafeArea() ZStack{ - ARViewContainer(session: arViewModel.session) + ARViewContainer( + session: arViewModel.session, + arVisualizationManager: arViewModel.arVisualizationManager + ) .edgesIgnoringSafeArea(.all) .frame(width: arViewWidth, height: arViewHeight) // .clipShape(RoundedRectangle(cornerRadius: 30, style: .continuous)) @@ -54,10 +57,12 @@ struct ReadView : View{ .allowsHitTesting(appStatus.rgbdVideoStreaming == .off) // Disable interaction in streaming mode // ML Inference Results Overlay - if appStatus.rgbdVideoStreaming == .off && appStatus.mlInferenceEnabled && arViewModel.mlManager.isInferenceEnabled { + if appStatus.rgbdVideoStreaming == .off && appStatus.mlInferenceEnabled && arViewModel.mlManager?.isInferenceEnabled == true { VStack { HStack { - MLInferenceResultsView(mlManager: arViewModel.mlManager) + if let mlManager = arViewModel.mlManager { + MLInferenceResultsView(mlManager: mlManager) + } Spacer() } Spacer() @@ -271,9 +276,9 @@ struct ReadView : View{ } .onChange(of: appStatus.mlInferenceEnabled) { oldValue, newValue in if newValue { - arViewModel.mlManager.enableInference() + arViewModel.mlManager?.enableInference() } else { - arViewModel.mlManager.disableInference() + arViewModel.mlManager?.disableInference() } } .onAppear { @@ -296,9 +301,9 @@ struct ReadView : View{ // Sync ML inference setting if appStatus.mlInferenceEnabled { - arViewModel.mlManager.enableInference() + arViewModel.mlManager?.enableInference() } else { - arViewModel.mlManager.disableInference() + arViewModel.mlManager?.disableInference() } } diff --git a/AnySense/dataStorage.swift b/AnySense/dataStorage.swift index 739cd68..5c8e01d 100644 --- a/AnySense/dataStorage.swift +++ b/AnySense/dataStorage.swift @@ -75,14 +75,48 @@ struct ImageFile: FileDocument { } + +// MARK: - ML Model File Document +struct MLModelFile: FileDocument { + var url: URL + + static var readableContentTypes: [UTType] { + // Support both .mlmodel and .mlmodelc files + [ + UTType(filenameExtension: "mlmodel")!, + UTType(filenameExtension: "mlmodelc")! + ] + } + static var writableContentTypes: [UTType] { + [ + UTType(filenameExtension: "mlmodel")!, + UTType(filenameExtension: "mlmodelc")! + ] + } + + init(url: URL) { + self.url = url + } + + init(configuration: ReadConfiguration) throws { + self.url = URL(fileURLWithPath: "") + } + + func fileWrapper(configuration: WriteConfiguration) throws -> FileWrapper { + return try FileWrapper(url: url, options: .immediate) + } +} + enum FileElement { case videoFile(VideoFile) case textFile(TextFile) case directory(SubLevelDirectory) + case mlModelFile(MLModelFile) // Add ML model support } enum FileElementSub { case imageFile(ImageFile) + case mlModelFile(MLModelFile) // Add ML model support to sub-level } struct SubLevelDirectory: FileDocument{ @@ -98,8 +132,10 @@ struct SubLevelDirectory: FileDocument{ do{ let contents = try FileManager.default.contentsOfDirectory(at: url, includingPropertiesForKeys: nil) for content in contents{ - if content.pathExtension.lowercased() == "ipeg" || content.pathExtension.lowercased() == "jpg" { + if content.pathExtension.lowercased() == "jpeg" || content.pathExtension.lowercased() == "jpg" { self.containedFiles.append(.imageFile(ImageFile(url: content))) + } else if content.pathExtension.lowercased() == "mlmodel" || content.pathExtension.lowercased() == "mlmodelc" { + self.containedFiles.append(.mlModelFile(MLModelFile(url: content))) } } }catch{ @@ -120,6 +156,9 @@ struct SubLevelDirectory: FileDocument{ case .imageFile(let imageFile): let fileWrapper = try imageFile.fileWrapper(configuration: configuration) dirWrapper.addFileWrapper(fileWrapper) + case .mlModelFile(let mlModelFile): + let fileWrapper = try mlModelFile.fileWrapper(configuration: configuration) + dirWrapper.addFileWrapper(fileWrapper) } } return dirWrapper @@ -164,6 +203,10 @@ struct SubLevelDirectory: FileDocument{ let directoryWrapper = try directory.fileWrapper(configuration: configuration) directoryWrapper.preferredFilename = directory.url.lastPathComponent folderWrapper.addFileWrapper(directoryWrapper) + case .mlModelFile(let mlModelFile): + let fileWrapper = try mlModelFile.fileWrapper(configuration: configuration) + fileWrapper.preferredFilename = mlModelFile.url.lastPathComponent + folderWrapper.addFileWrapper(fileWrapper) } } From 719ff9258c5dd889e3f25d96c3c84438074b18e4 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Wed, 16 Jul 2025 12:57:15 -0400 Subject: [PATCH 12/56] Added visualization and fixed inference --- AnySense/.gitignore | 1 + AnySense/Managers/ARViewContainer.swift | 28 +- .../Managers/ARVisualizationManager.swift | 523 +++++++++--------- AnySense/Managers/MLInferenceManager.swift | 57 +- AnySense/Managers/USBManager.swift | 23 +- AnySense/Views/accountView.swift | 77 +++ AnySense/Views/readView.swift | 22 + 7 files changed, 455 insertions(+), 276 deletions(-) create mode 100644 AnySense/.gitignore diff --git a/AnySense/.gitignore b/AnySense/.gitignore new file mode 100644 index 0000000..dcf5f86 --- /dev/null +++ b/AnySense/.gitignore @@ -0,0 +1 @@ +Models/ \ No newline at end of file diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 87a62d9..0ba4436 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -15,6 +15,7 @@ import CoreMedia import CoreImage import UIKit import CoreImage.CIFilterBuiltins +import Combine //import WebRTC struct RecordingFiles { @@ -134,6 +135,9 @@ class ARViewModel: ObservableObject{ private var depthConfAttributes: [String: Any] = [:] private var audioOutputSettings: [String: Any] = [:] + // Combine subscriptions for ML integration + private var cancellables = Set() + init() { bluetoothManager = BluetoothManager() @@ -500,16 +504,31 @@ class ARViewModel: ObservableObject{ record3dHeader.depthSize = UInt32(compressedDepthData?.count ?? 0) record3dHeader.confidenceMapSize = UInt32(compressedDepthConfData?.count ?? 0) } + + // Always send exactly 7 floats (28 bytes) for joint actions + let jointActionsArray: [Float] + if let latestJointActions = self.mlManager?.latestResult?.jointPositions, !latestJointActions.isEmpty { + // Use actual ML inference results, ensure exactly 7 values + jointActionsArray = Array(latestJointActions.prefix(7)) + Array(repeating: 0.0, count: max(0, 7 - latestJointActions.count)) + print("Streaming ML joint actions: [\(jointActionsArray.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") + } else { + // Fallback to zeros if no ML results available + jointActionsArray = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] + print("No ML results available, streaming zero joint actions") + } + + // Convert to exactly 28 bytes (7 floats * 4 bytes each) + let jointActionsData = Data(bytes: jointActionsArray, count: 28) + self.usbManager.sendData( record3dHeaderData: Data(bytes: &record3dHeader, count: MemoryLayout.size), intrinsicMatData: Data(bytes: &intrinsicCoeffs, count: MemoryLayout.size), poseData: Data(bytes: &camera_pose, count: MemoryLayout.size), rgbImageData: rgbImageData!, + jointActionsData: jointActionsData, compressedDepthData: compressedDepthData, compressedConfData: compressedDepthConfData ) - - } } @@ -935,12 +954,15 @@ class ARViewModel: ObservableObject{ // Connect AR visualization to ML inference self.mlManager?.arVisualizationManager = self.arVisualizationManager + // ML results are now accessed directly during streaming for better real-time performance + print("Initialized ML Inference Manager with Model Manager") print("Connected AR Visualization Manager to ML Inference") + print("Connected ML Results to USB Streaming") print("🔗 ML-AR Connection: \(self.mlManager?.arVisualizationManager != nil ? "✅ Connected" : "❌ Failed")") } -} + } class AudioCaptureDelegate: NSObject, AVCaptureAudioDataOutputSampleBufferDelegate { private let writerInput: AVAssetWriterInput? diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 43157e6..7333964 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -4,11 +4,12 @@ import ARKit import simd import UIKit -// MARK: - Pose Data Structure -struct PoseData { - let translation: SIMD3 // x, y, z in meters - let rotation: SIMD3 // roll, pitch, yaw in radians +// MARK: - Directional Arrow Data +struct DirectionalArrow { + let entity: Entity + let anchor: AnchorEntity let timestamp: TimeInterval + let magnitude: Float } // MARK: - Visualization Frequency (Matching MLInferenceManager) @@ -39,40 +40,42 @@ class ARVisualizationManager: ObservableObject { // MARK: - Published Properties @Published var isVisualizationEnabled: Bool = false - @Published var showCoordinateAxes: Bool = true - @Published var showTrail: Bool = true - @Published var trailLength: Int = 10 + @Published var showMovementArrows: Bool = true + @Published var maxArrows: Int = 10 @Published var visualizationFrequency: VisualizationFrequency = .medium // MARK: - Private Properties private var arView: ARView? - private var poseAnchor: AnchorEntity? - private var coordinateAxesEntity: Entity? - private var trailEntity: Entity? - private var trailPoints: [SIMD3] = [] + private var worldOriginAnchor: AnchorEntity? + private var movementArrows: [DirectionalArrow] = [] private var lastVisualizationTime: CFTimeInterval = 0 - // Visual configuration (scaled down for less dominance in AR view) - private let axisLength: Float = 0.1 - private let axisThickness: Float = 0.003 - private let trailPointSize: Float = 0.015 + // Movement tracking + private var worldOrigin: SIMD3 = SIMD3(0, 0, 0) + private var currentWorldPosition: SIMD3 = SIMD3(0, 0, 0) + private var previousWorldPosition: SIMD3? + private var hasEstablishedOrigin: Bool = false - private var accumulatedTransform: float4x4 = matrix_identity_float4x4 + // Arrow visual configuration + private let arrowBaseLength: Float = 0.15 // Base length in meters + private let arrowThickness: Float = 0.008 // Arrow shaft thickness + private let arrowHeadRatio: Float = 0.25 // Head vs shaft ratio + private let arrowHeadWidth: Float = 0.025 // Arrow head width + private let axisLength: Float = 0.08 // Coordinate axes length + private let axisThickness: Float = 0.005 // Coordinate axes thickness - // World reference frame set at the start of the recording - private var fixedWorldOrigin: float4x4 = matrix_identity_float4x4 - private var hasEstablishedOrigin: Bool = false + // Arrow lifecycle + private let arrowLifetime: TimeInterval = 3.0 // Arrows fade after 3 seconds // MARK: - Initialization init() { - print("ARVisualizationManager initialized") + print("ARVisualizationManager initialized with delta-based movement arrows") } // MARK: - Setup Methods func setupVisualization(with arView: ARView) { self.arView = arView - - print("AR Visualization setup completed - using incremental delta mode only") + print("AR Visualization setup completed - using camera-relative directional arrows") } // MARK: - Recording Control Methods @@ -84,155 +87,61 @@ class ARVisualizationManager: ObservableObject { return } - print("Setting origin at current camera position...") - // Set origin at current camera position when recording starts - setOriginAtCurrentCamera() - - print("Enabling visualization...") + print("Establishing world origin for movement tracking...") + establishWorldOrigin() enableVisualization() - print("Started recording visualization - enabled=\(isVisualizationEnabled), hasAxes=\(coordinateAxesEntity != nil)") + print("Started movement visualization - enabled=\(isVisualizationEnabled)") } func stopRecordingVisualization() { disableVisualization() - clearVisualization() - poseAnchor?.removeFromParent() - poseAnchor = nil - - // Reset stable origin for next recording session - fixedWorldOrigin = matrix_identity_float4x4 - hasEstablishedOrigin = false - - print("Stopped recording visualization and cleared origin") + clearAllVisualization() + resetMovementTracking() + print("Stopped movement visualization and reset tracking") + } + + // MARK: - World Origin & Movement Tracking + private func getCurrentCameraTransform() -> float4x4 { + return arView?.session.currentFrame?.camera.transform ?? matrix_identity_float4x4 } - private func setOriginAtCurrentCamera() { + private func getCurrentCameraPosition() -> SIMD3 { + let transform = getCurrentCameraTransform() + return SIMD3(transform.columns.3.x, transform.columns.3.y, transform.columns.3.z) + } + + private func establishWorldOrigin() { guard let arView = arView else { return } - - // Establish STABLE world origin that NEVER changes guard !hasEstablishedOrigin else { - print("World origin already established - ignoring duplicate call") + print("World origin already established") return } - // Get current camera transform ONCE and store as fixed reference - fixedWorldOrigin = arView.session.currentFrame?.camera.transform ?? matrix_identity_float4x4 + // Set world origin at current camera position + worldOrigin = getCurrentCameraPosition() + currentWorldPosition = SIMD3(0, 0, 0) // Start at origin + previousWorldPosition = nil hasEstablishedOrigin = true - let originPosition = SIMD3(fixedWorldOrigin.columns.3.x, fixedWorldOrigin.columns.3.y, fixedWorldOrigin.columns.3.z) - - // Place anchor at fixed world origin (not moving with camera) - poseAnchor = AnchorEntity(world: originPosition) - arView.scene.addAnchor(poseAnchor!) - - // Create coordinate axes and trail - if showCoordinateAxes { - createCoordinateAxes() - } - if showTrail { - createTrailEntity() - } - - print("FIXED world origin established at: (\(originPosition.x), \(originPosition.y), \(originPosition.z))") - } - - private func createCoordinateAxes() { - guard let anchor = poseAnchor else { return } - coordinateAxesEntity = Entity() - - let xAxis = createAxisEntity(direction: [1,0,0], color: .red, length: axisLength) - let yAxis = createAxisEntity(direction: [0,1,0], color: .green, length: axisLength) - let zAxis = createAxisEntity(direction: [0,0,1], color: .blue, length: axisLength) - - [xAxis, yAxis, zAxis].forEach { coordinateAxesEntity?.addChild($0) } - anchor.addChild(coordinateAxesEntity!) - - accumulatedTransform = matrix_identity_float4x4 - } - - private func createAxisEntity(direction: SIMD3, - color: UIColor, - length: Float) -> Entity { - let axisEntity = Entity() - - // Create the shaft - let shaftLength = length * 0.8 - let shaftMesh = MeshResource.generateBox( - width: axisThickness, - height: axisThickness, - depth: shaftLength - ) - - let shaft = ModelEntity( - mesh: shaftMesh, - materials: [SimpleMaterial(color: color, isMetallic: false)] - ) - - - let arrowHeadLength = length * 0.5 - let arrowHeadSize = axisThickness * 5 - let arrowHeadMesh = MeshResource.generateBox( - width: arrowHeadSize, - height: arrowHeadSize, - depth: arrowHeadLength - ) - - let arrowHead = ModelEntity( - mesh: arrowHeadMesh, - materials: [SimpleMaterial(color: color, isMetallic: false)] - ) - - // Create 3D arrow - let dirNorm = normalize(direction) - let forward: SIMD3 = [0, 0, 1] - - let rotQuat = simd_quatf(from: forward, to: dirNorm) - shaft.orientation = rotQuat - arrowHead.orientation = rotQuat + // Create anchor at world origin + worldOriginAnchor = AnchorEntity(world: worldOrigin) + arView.scene.addAnchor(worldOriginAnchor!) - shaft.position = dirNorm * (shaftLength / 2) - arrowHead.position = dirNorm * (shaftLength + arrowHeadLength / 2) - - axisEntity.addChild(shaft) - axisEntity.addChild(arrowHead) - return axisEntity - } - - private func createTrailEntity() { - guard let anchor = poseAnchor else { return } - trailEntity = Entity() - anchor.addChild(trailEntity!) + print("🌍 World origin established at: \(worldOrigin)") } - - private func updateTrail(with position: SIMD3) { - guard let trail = trailEntity else { return } - trailPoints.append(position) - if trailPoints.count > trailLength { - trailPoints.removeFirst() - } + private func resetMovementTracking() { + hasEstablishedOrigin = false + worldOrigin = SIMD3(0, 0, 0) + currentWorldPosition = SIMD3(0, 0, 0) + previousWorldPosition = nil - trail.children.removeAll() - for (i, pt) in trailPoints.enumerated() { - let alpha = Float(i) / Float(trailPoints.count) - let dot = createTrailPoint(at: pt, alpha: alpha) - trail.addChild(dot) - } - } - - private func createTrailPoint(at position: SIMD3, alpha: Float) -> Entity { - let dot = ModelEntity( - mesh: .generateSphere(radius: trailPointSize), - materials: [SimpleMaterial( - color: .orange, - isMetallic: false - )] - ) - dot.position = position - return dot + worldOriginAnchor?.removeFromParent() + worldOriginAnchor = nil } + // MARK: - Control Methods func enableVisualization() { @@ -241,91 +150,259 @@ class ARVisualizationManager: ObservableObject { func disableVisualization() { isVisualizationEnabled = false - clearVisualization() + clearAllVisualization() } - private func clearVisualization() { - coordinateAxesEntity?.removeFromParent() - trailEntity?.removeFromParent() - trailPoints.removeAll() - } - - func toggleCoordinateAxes() { - showCoordinateAxes.toggle() - if showCoordinateAxes { - createCoordinateAxes() - } else { - coordinateAxesEntity?.removeFromParent() - coordinateAxesEntity = nil + private func clearAllVisualization() { + // Remove all movement arrows + for arrow in movementArrows { + arrow.anchor.removeFromParent() } + movementArrows.removeAll() } - func toggleTrail() { - showTrail.toggle() - if showTrail { - createTrailEntity() - } else { - trailEntity?.removeFromParent() - trailEntity = nil - trailPoints.removeAll() + func toggleMovementArrows() { + showMovementArrows.toggle() + if !showMovementArrows { + // Remove all movement arrows + for arrow in movementArrows { + arrow.anchor.removeFromParent() + } + movementArrows.removeAll() } } - func setTrailLength(_ length: Int) { - trailLength = max(10, min(200, length)) - if trailPoints.count > trailLength { - trailPoints = Array(trailPoints.suffix(trailLength)) + func setMaxArrows(_ count: Int) { + maxArrows = max(1, min(20, count)) + // Trim existing arrows if needed + while movementArrows.count > maxArrows { + let oldArrow = movementArrows.removeFirst() + oldArrow.anchor.removeFromParent() } } - // MARK: - Frequency Control Methods (Matching MLInferenceManager) + // MARK: - Frequency Control Methods func setVisualizationFrequency(_ frequency: VisualizationFrequency) { visualizationFrequency = frequency print("AR Visualization frequency set to: \(frequency.displayName)") } // MARK: - ML Integration Method - // TODO: Fix visualization - logic is not correct func updatePoseFromMLOutput(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) { - // Apply frequency throttling (same as MLInferenceManager) + // Apply frequency throttling if timestamp - lastVisualizationTime < visualizationFrequency.interval { return } lastVisualizationTime = timestamp - print("AR Visualization update at \(visualizationFrequency.displayName) frequency") - print("ML Pose Input: \(jointActions.prefix(6).map { String(format: "%.3f", $0) })") - + guard isVisualizationEnabled, showMovementArrows else { return } + guard hasEstablishedOrigin else { + print("World origin not established - cannot track movement") + return + } guard jointActions.count >= 6 else { print("Invalid joint actions array - need at least 6 values, got \(jointActions.count)") return } - // Apply coordinate system transformation from PickUp Policy to ARKit - // Pickup Policy: x=down, y=right, z=backward → ARKit: x=right, y=up, z=forward - let ml_x = jointActions[0] - let ml_y = jointActions[1] - let ml_z = jointActions[2] + // Interpret joint actions as movement deltas in ARKit coordinates + let (deltaTranslation, _, confidence) = interpretMLDirections(jointActions) + + print("📱 ML input (x=down,y=right,z=back): (\(String(format: "%.3f", jointActions[0])), \(String(format: "%.3f", jointActions[1])), \(String(format: "%.3f", jointActions[2])))") + print("📲 Delta movement (x=right,y=up,z=forward): (\(String(format: "%.3f", deltaTranslation.x)), \(String(format: "%.3f", deltaTranslation.y)), \(String(format: "%.3f", deltaTranslation.z)))") + print("🎯 Confidence: \(String(format: "%.2f", confidence))") + + // Update position tracking + let previousPosition = currentWorldPosition + currentWorldPosition = currentWorldPosition + deltaTranslation + + // Only create movement arrow if there's meaningful movement and we have a previous position + let movementMagnitude = length(deltaTranslation) + if movementMagnitude > 0.005 { // 5mm threshold for meaningful movement + createMovementArrow( + from: previousPosition, + to: currentWorldPosition, + confidence: confidence, + timestamp: timestamp + ) + } + + print("🎯 Position updated: \(String(format: "(%.3f,%.3f,%.3f)", currentWorldPosition.x, currentWorldPosition.y, currentWorldPosition.z)) → moved \(String(format: "%.3f", movementMagnitude))m") + } + + private func interpretMLDirections(_ jointActions: [Float]) -> (translation: SIMD3, rotation: simd_quatf, confidence: Float) { + + // Interpret as directional vectors (not absolute positions) + // Transform from ML coordinate system to ARKit camera-relative coordinates + let ml_x = jointActions[0] // down + let ml_y = jointActions[1] // right + let ml_z = jointActions[2] // backward (into phone) let ml_roll = jointActions[3] let ml_pitch = jointActions[4] let ml_yaw = jointActions[5] - let arkit_x = ml_y - let arkit_y = -ml_x - let arkit_z = -ml_z + // COORDINATE SYSTEM TRANSFORMATION: + // Phone ML: x=down, y=right, z=backward → ARKit: x=right, y=up, z=forward + // + // ML x (down) → ARKit y (up) → negate: -ml_x + // ML y (right) → ARKit x (right) → direct: ml_y + // ML z (backward) → ARKit z (forward) → negate: -ml_z + let translation = SIMD3( + ml_y, // ML y (right) → ARKit x (right) + -ml_x, // ML x (down) → ARKit y (up), so -x + ml_z // ML z (backward) → ARKit z (forward), so -z + ) - let arkit_roll = ml_pitch - let arkit_pitch = -ml_roll - let arkit_yaw = -ml_yaw + // Transform rotation + let rotation = eulerToQuaternion( + roll: ml_pitch, // Transform coordinate system + pitch: -ml_roll, + yaw: ml_yaw + ) - print("ML→ARKit transform: t=(\(String(format: "%.3f", arkit_x)), \(String(format: "%.3f", arkit_y)), \(String(format: "%.3f", arkit_z))), r=(\(String(format: "%.3f", arkit_roll)), \(String(format: "%.3f", arkit_pitch)), \(String(format: "%.3f", arkit_yaw)))") + // Calculate confidence based on magnitude + let translationMagnitude = length(translation) + let rotationMagnitude = sqrt(ml_roll * ml_roll + ml_pitch * ml_pitch + ml_yaw * ml_yaw) + let confidence = min(1.0, (translationMagnitude * 10 + rotationMagnitude) / 2.0) // Scale for reasonable confidence - let quaternion = eulerToQuaternion(roll: arkit_roll, pitch: arkit_pitch, yaw: arkit_yaw) + return (translation, rotation, confidence) + } + + private func createMovementArrow(from: SIMD3, to: SIMD3, confidence: Float, timestamp: TimeInterval) { + guard let arView = arView, let worldOriginAnchor = worldOriginAnchor else { return } + + DispatchQueue.main.async { [weak self, arView, worldOriginAnchor] in + guard let self = self else { return } + + // Calculate movement vector + let movement = to - from + let movementMagnitude = length(movement) + + // Skip tiny movements + guard movementMagnitude > 0.001 else { return } + + // Convert positions to world coordinates (relative to world origin) + let worldFromPosition = self.worldOrigin + from + let worldToPosition = self.worldOrigin + to + + // Create arrow entity showing movement from previous to current position + let arrowEntity = self.createMovementArrowEntity( + fromPosition: from, + toPosition: to, + movement: movement, + confidence: confidence + ) + + // Position arrow at the start position (in world origin's coordinate system) + arrowEntity.position = from + worldOriginAnchor.addChild(arrowEntity) + + // Store arrow with metadata + let movementArrow = DirectionalArrow( + entity: arrowEntity, + anchor: worldOriginAnchor, + timestamp: timestamp, + magnitude: movementMagnitude + ) + + self.movementArrows.append(movementArrow) + + // Clean up old arrows + self.cleanupOldArrows(currentTime: timestamp) + + // Limit number of arrows + while self.movementArrows.count > self.maxArrows { + let oldArrow = self.movementArrows.removeFirst() + oldArrow.entity.removeFromParent() + } + + print("🏹 Movement arrow: from=\(String(format: "(%.3f,%.3f,%.3f)", from.x, from.y, from.z)) to=\(String(format: "(%.3f,%.3f,%.3f)", to.x, to.y, to.z)) move=\(String(format: "%.3f", movementMagnitude))m") + } + } + + private func createMovementArrowEntity(fromPosition: SIMD3, toPosition: SIMD3, movement: SIMD3, confidence: Float) -> Entity { + let arrowContainer = Entity() + + // Calculate arrow dimensions based on movement magnitude + let movementMagnitude = length(movement) + let scaledLength = max(movementMagnitude, 0.02) // Minimum 2cm for visibility + let shaftLength = scaledLength * (1.0 - arrowHeadRatio) + let headLength = scaledLength * arrowHeadRatio + + // Create arrow shaft (cylinder) + let shaftMesh = MeshResource.generateBox( + width: arrowThickness, + height: arrowThickness, + depth: shaftLength + ) + + // Color based on confidence: red (low) -> yellow (medium) -> green (high) + let shaftColor = confidenceToColor(confidence) + let shaftEntity = ModelEntity( + mesh: shaftMesh, + materials: [SimpleMaterial(color: shaftColor, isMetallic: false)] + ) + + // Create arrow head (pointing toward destination) + let headMesh = MeshResource.generateBox( + width: arrowHeadWidth, + height: arrowHeadWidth, + depth: headLength + ) + + let headEntity = ModelEntity( + mesh: headMesh, + materials: [SimpleMaterial(color: shaftColor.withAlphaComponent(0.9), isMetallic: false)] + ) + + // Position shaft and head along the movement vector + shaftEntity.position = SIMD3(0, 0, shaftLength / 2) + headEntity.position = SIMD3(0, 0, shaftLength + headLength / 2) + + // Orient arrow in direction of movement + if movementMagnitude > 0.001 { + let normalizedMovement = normalize(movement) + let forward = SIMD3(0, 0, 1) + let rotationQuat = simd_quatf(from: forward, to: normalizedMovement) + + arrowContainer.orientation = rotationQuat + } - applyIncrementalPose(deltaTranslation: SIMD3(arkit_x, arkit_y, arkit_z), deltaQuaternion: quaternion) + arrowContainer.addChild(shaftEntity) + arrowContainer.addChild(headEntity) - print("ML Pose processed and sent to visualization") + return arrowContainer + } + + private func confidenceToColor(_ confidence: Float) -> UIColor { + // Red (low confidence) -> Yellow (medium) -> Green (high confidence) + let clampedConfidence = max(0.0, min(1.0, confidence)) + + if clampedConfidence < 0.5 { + // Red to Yellow + let factor = clampedConfidence * 2.0 + return UIColor(red: 1.0, green: CGFloat(factor), blue: 0.0, alpha: 0.8) + } else { + // Yellow to Green + let factor = (clampedConfidence - 0.5) * 2.0 + return UIColor(red: CGFloat(1.0 - factor), green: 1.0, blue: 0.0, alpha: 0.8) + } + } + + private func cleanupOldArrows(currentTime: TimeInterval) { + let expiredArrows = movementArrows.filter { currentTime - $0.timestamp > arrowLifetime } + + for expiredArrow in expiredArrows { + expiredArrow.entity.removeFromParent() + if let index = movementArrows.firstIndex(where: { $0.timestamp == expiredArrow.timestamp }) { + movementArrows.remove(at: index) + } + } + + if !expiredArrows.isEmpty { + print("Cleaned up \(expiredArrows.count) expired movement arrows") + } } private func eulerToQuaternion(roll: Float, pitch: Float, yaw: Float) -> simd_quatf { @@ -347,56 +424,4 @@ class ARVisualizationManager: ObservableObject { return simd_quatf(ix: x, iy: y, iz: z, r: w) } - - // Accumulate deltas in the local end-effector frame with stable origin - private func applyIncrementalPose(deltaTranslation: SIMD3, deltaQuaternion: simd_quatf) { - print("Applying incremental pose delta: t=(\(String(format: "%.3f", deltaTranslation.x)), \(String(format: "%.3f", deltaTranslation.y)), \(String(format: "%.3f", deltaTranslation.z)))") - - guard isVisualizationEnabled else { - print("Visualization not enabled") - return - } - guard hasEstablishedOrigin else { - print("World origin not established - cannot apply incremental pose") - return - } - - DispatchQueue.main.async { [weak self] in - guard let self = self else { return } - guard let axes = self.coordinateAxesEntity else { - print("No coordinate axes entity available") - return - } - - // Build delta 4x4 matrix from quaternion + translation - var deltaMatrix = float4x4(deltaQuaternion) - deltaMatrix.columns.3 = SIMD4(deltaTranslation.x, deltaTranslation.y, deltaTranslation.z, 1) - - // Accumulate delta: current_pose = current_pose * delta_pose - self.accumulatedTransform = self.accumulatedTransform * deltaMatrix - - // Transform accumulated pose relative to fixed world origin - let originPosition = SIMD3(self.fixedWorldOrigin.columns.3.x, - self.fixedWorldOrigin.columns.3.y, - self.fixedWorldOrigin.columns.3.z) - let originQuat = simd_quatf(self.fixedWorldOrigin) - - // Compose with world origin - let worldTransform = self.fixedWorldOrigin * self.accumulatedTransform - - // Apply the final transform to coordinate axes - axes.transform = Transform(matrix: worldTransform) - - // Update trail with world position - let worldPosition = SIMD3(worldTransform.columns.3.x, - worldTransform.columns.3.y, - worldTransform.columns.3.z) - if self.showTrail { - self.updateTrail(with: worldPosition) - } - - print("Incremental pose applied: accumulated=(\(String(format: "%.2f", self.accumulatedTransform.columns.3.x)), \(String(format: "%.2f", self.accumulatedTransform.columns.3.y)), \(String(format: "%.2f", self.accumulatedTransform.columns.3.z))), world=(\(String(format: "%.2f", worldPosition.x)), \(String(format: "%.2f", worldPosition.y)), \(String(format: "%.2f", worldPosition.z)))") - } - } - } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 0e3322d..6566886 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -30,7 +30,7 @@ class MLInferenceManager: ObservableObject { // MARK: - Private Properties private var model: MLModel? - private var lastInferenceTime: CFTimeInterval = 0 + private var lastInferenceTime: CFTimeInterval = -Double.infinity // Start with negative infinity to ensure first inference runs private var inferenceQueue = DispatchQueue(label: "MLInferenceQueue", qos: .userInitiated) // MARK: - Model Management @@ -135,28 +135,38 @@ class MLInferenceManager: ObservableObject { guard isInferenceEnabled, let model = model else { return } - if timestamp - lastInferenceTime < inferenceFrequency.interval { + let timeSinceLastInference = timestamp - lastInferenceTime + let requiredInterval = inferenceFrequency.interval + + if timeSinceLastInference < requiredInterval { return } lastInferenceTime = timestamp - inferenceQueue.async { [weak self] in - guard let self = self else { return } - - let startTime = CACurrentMediaTime() - - autoreleasepool { - do { - let inputArray = try self.processFrameForInference(pixelBuffer) - let input = try MLDictionaryFeatureProvider(dictionary: ["x_1": inputArray]) - let output = try model.prediction(from: input) + // Process frame synchronously to avoid CVPixelBuffer sendable issues + let startTime = CACurrentMediaTime() + + autoreleasepool { + do { + let inputArray = try self.processFrameForInference(pixelBuffer) + + // Move to background queue after processing CVPixelBuffer + inferenceQueue.async { [weak self, inputArray, model, startTime] in + guard let self = self else { return } - let inferenceTime = CACurrentMediaTime() - startTime - self.processInferenceResults(output, inferenceTime: inferenceTime) - } catch { - print("Failed to perform inference: \(error)") + do { + let input = try MLDictionaryFeatureProvider(dictionary: ["x_1": inputArray]) + let output = try model.prediction(from: input) + + let inferenceTime = CACurrentMediaTime() - startTime + self.processInferenceResults(output, inferenceTime: inferenceTime) + } catch { + print("Failed to perform ML inference: \(error)") + } } + } catch { + print("Failed to process frame for inference: \(error)") } } } @@ -282,12 +292,15 @@ class MLInferenceManager: ObservableObject { let positionString = jointPositions.map { String(format: "%.3f", $0) }.joined(separator: ", ") let modelName = modelManager.activeModel?.name ?? "Unknown" - print("Model Output [\(modelName)] (\(outputFeatureName)): [\(positionString)] - \(String(format: "%.1f", inferenceTime * 1000))ms") + print("ML Model Output [\(modelName)] (\(outputFeatureName)): [\(positionString)] - \(String(format: "%.1f", inferenceTime * 1000))ms") + print("Joint actions ready for USB streaming: \(jointPositions.count) values") } // MARK: - Control Methods func enableInference() { isInferenceEnabled = true + // Reset timing to ensure immediate inference when enabled + lastInferenceTime = -Double.infinity let modelName = modelManager.activeModel?.name ?? "No model" print("Pick Up Policy enabled with model: \(modelName)") } @@ -299,8 +312,14 @@ class MLInferenceManager: ObservableObject { } func setInferenceFrequency(_ frequency: InferenceFrequency) { + let oldFrequency = inferenceFrequency inferenceFrequency = frequency - print("Pick Up Policy frequency set to: \(frequency.displayName)") + // Reset lastInferenceTime to allow immediate inference at new frequency + lastInferenceTime = -Double.infinity + print("🎚️ Frequency changed from \(oldFrequency.displayName) to \(frequency.displayName) - Interval: \(frequency.interval)s") + + // Automatically synchronize with AR visualization + synchronizeFrequencyWithVisualization() } // MARK: - Frequency Synchronization @@ -319,6 +338,6 @@ class MLInferenceManager: ObservableObject { } arVisualizationManager?.setVisualizationFrequency(correspondingVisualizationFrequency) - print("Synchronized ML inference (\(inferenceFrequency.displayName)) with AR visualization (\(correspondingVisualizationFrequency.displayName))") + print("Synchronized ML inference (\(inferenceFrequency.displayName)) with AR arrow visualization (\(correspondingVisualizationFrequency.displayName))") } } diff --git a/AnySense/Managers/USBManager.swift b/AnySense/Managers/USBManager.swift index 75fbf39..e436789 100644 --- a/AnySense/Managers/USBManager.swift +++ b/AnySense/Managers/USBManager.swift @@ -21,7 +21,7 @@ struct Record3DHeader { var rgbWidth: UInt32 var rgbHeight: UInt32 var depthWidth: UInt32 - var depthHeight: UInt32 + var depthHeight: UInt32 var confidenceWidth: UInt32 var confidenceHeight: UInt32 var rgbSize: UInt32 @@ -29,6 +29,7 @@ struct Record3DHeader { var confidenceMapSize: UInt32 var miscSize: UInt32 var deviceType: UInt32 + // jointActions are always 28 bytes (7 floats), sent separately in message body } struct IntrinsicMatrixCoeffs { @@ -108,6 +109,7 @@ class USBManager { intrinsicMatData: Data, poseData: Data, rgbImageData: Data, + jointActionsData: Data, // Always exactly 28 bytes (7 floats) compressedDepthData: Data? = nil, compressedConfData: Data? = nil ) { @@ -115,7 +117,7 @@ class USBManager { print("No active connection. Cannot send data.") return } - var messageBody = record3dHeaderData + intrinsicMatData + poseData + rgbImageData + var messageBody = record3dHeaderData + intrinsicMatData + poseData + rgbImageData + jointActionsData if let depthData = compressedDepthData { messageBody += depthData } @@ -127,12 +129,23 @@ class USBManager { let ptHeaderData = Data(bytes: &self.ptHeader, count:MemoryLayout.size) let completeMessage = ptHeaderData + messageBody - print("Sending data of size: \(completeMessage.count)") + + print("USB Streaming Summary:") + print(" - Total message size: \(completeMessage.count) bytes") + print(" - RGB size: \(rgbImageData.count) bytes") + print(" - Joint actions: 28 bytes (7 floats)") + if let depthData = compressedDepthData { + print(" - Depth size: \(depthData.count) bytes (compressed)") + } + if let confData = compressedConfData { + print(" - Confidence size: \(confData.count) bytes (compressed)") + } + activeConnection.send(content:completeMessage, completion: .contentProcessed {error in if let error = error { - print("Failed to send data: \(error)") + print("❌ Failed to send USB data: \(error)") } else { - print("Image data sent successfully") + print("✅ USB data sent successfully to computer") } }) } diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 1ef2e23..cacd053 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -321,6 +321,83 @@ struct SettingsView : View{ } } } + + // MARK: - Movement Tracking Section + Section(header: Text("MOVEMENT TRACKING")) { + HStack { + Text("Show Movement Arrows") + .font(.body) + .foregroundColor(.primary) + Spacer() + Toggle("", isOn: $arViewModel.arVisualizationManager.showMovementArrows) + .onChange(of: arViewModel.arVisualizationManager.showMovementArrows) { oldValue, newValue in + arViewModel.arVisualizationManager.toggleMovementArrows() + } + } + .padding(.vertical, 5) + + VStack(alignment: .leading, spacing: 12) { + Text("Max Movement Arrows") + .font(.body) + .foregroundColor(.primary) + + let maxArrowsBinding = Binding( + get: { Double(arViewModel.arVisualizationManager.maxArrows) }, + set: { newValue in + arViewModel.arVisualizationManager.setMaxArrows(Int(newValue)) + } + ) + + HStack { + Text("1") + .font(.caption) + .foregroundColor(.gray) + + Slider(value: maxArrowsBinding, in: 1...20, step: 1) + + Text("20") + .font(.caption) + .foregroundColor(.gray) + } + + Text("Current: \(arViewModel.arVisualizationManager.maxArrows) arrows") + .font(.caption) + .foregroundColor(.gray) + } + .padding(.vertical, 5) + + VStack(alignment: .leading, spacing: 8) { + Text("Movement Tracking Status") + .font(.body) + .foregroundColor(.primary) + + HStack { + Text("Status:") + .font(.caption) + .foregroundColor(.gray) + Spacer() + Text(arViewModel.arVisualizationManager.isVisualizationEnabled ? "Active" : "Inactive") + .font(.caption) + .foregroundColor(arViewModel.arVisualizationManager.isVisualizationEnabled ? .green : .orange) + } + + HStack { + Text("Frequency:") + .font(.caption) + .foregroundColor(.gray) + Spacer() + Text(arViewModel.arVisualizationManager.visualizationFrequency.displayName) + .font(.caption) + .foregroundColor(.gray) + } + + Text("Shows arrows between consecutive ML inference positions") + .font(.caption2) + .foregroundColor(.gray) + .padding(.top, 4) + } + .padding(.vertical, 5) + } } .scrollContentBackground(.hidden) } diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 9f84fdd..cf93a3e 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -66,6 +66,28 @@ struct ReadView : View{ Spacer() } Spacer() + // AR Visualization Status Overlay + HStack { + VStack(alignment: .leading, spacing: 4) { + if arViewModel.arVisualizationManager.isVisualizationEnabled { + Text("Movement Tracking: ON") + .font(.caption) + .foregroundColor(.green) + Text("Max Arrows: \(arViewModel.arVisualizationManager.maxArrows)") + .font(.caption2) + .foregroundColor(.secondary) + } else { + Text("Movement Tracking: OFF") + .font(.caption) + .foregroundColor(.red) + } + } + .padding(8) + .background(Color.black.opacity(0.6)) + .cornerRadius(8) + Spacer() + } + .padding(.bottom, 10) } .frame(width: arViewWidth, height: arViewHeight) .padding(.bottom, arViewPadding) From 5c261be2d6b5360569ad0eacc7e1182f3971fef6 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Tue, 29 Jul 2025 22:47:28 -0400 Subject: [PATCH 13/56] added edgetam support and prompt update logic --- AnySense/MLModel+Extensions.swift | 2 +- AnySense/Managers/ARViewContainer.swift | 9 + .../Managers/ARVisualizationManager.swift | 6 +- .../Managers/BoundaryTrackingManager.swift | 408 ++++++++++ AnySense/Managers/EdgeTAMManager.swift | 753 ++++++++++++++++++ AnySense/Managers/ModelManager.swift | 10 +- AnySense/ModelInfo.swift | 2 +- AnySense/Views/EdgeTAMStatusView.swift | 136 ++++ .../Views/EdgeTAMVisualizationOverlay.swift | 364 +++++++++ AnySense/Views/accountView.swift | 26 +- AnySense/Views/readView.swift | 36 +- 11 files changed, 1714 insertions(+), 38 deletions(-) create mode 100644 AnySense/Managers/BoundaryTrackingManager.swift create mode 100644 AnySense/Managers/EdgeTAMManager.swift create mode 100644 AnySense/Views/EdgeTAMStatusView.swift create mode 100644 AnySense/Views/EdgeTAMVisualizationOverlay.swift diff --git a/AnySense/MLModel+Extensions.swift b/AnySense/MLModel+Extensions.swift index f0d49fd..a1c8172 100644 --- a/AnySense/MLModel+Extensions.swift +++ b/AnySense/MLModel+Extensions.swift @@ -73,7 +73,7 @@ struct ModelMetadata { self.modelDescription = modelDescription.metadata[.description] as? String ?? "No description" // Extract input shape if available - simplified approach - if let inputDesc = self.inputDescription { + if self.inputDescription != nil { // For now, set a default shape - can be enhanced later if needed self.requiredInputShape = [224, 224, 3] // Common image input shape } else { diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 0ba4436..843d651 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -83,6 +83,9 @@ class ARViewModel: ObservableObject{ // AR Visualization Manager for 3D pose visualization @Published var arVisualizationManager = ARVisualizationManager() + + // EdgeTAM Manager for vision features extraction + @Published var edgeTAMManager = EdgeTAMManager() public var userFPS: Double? public var isColorMapOpened = false @@ -431,6 +434,9 @@ class ARViewModel: ObservableObject{ // Perform ML inference on the RGB frame during streaming mlManager?.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) + + // Process frame with EdgeTAM model (every 8th frame) + edgeTAMManager.processFrameIfNeeded(rgbPixelBuffer, timestamp: CACurrentMediaTime()) // TODO: Check if we need to change this at all var depthPixelBuffer: CVPixelBuffer? = nil @@ -909,6 +915,9 @@ class ARViewModel: ObservableObject{ // Perform ML inference on the RGB frame mlManager?.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) + // Process frame with EdgeTAM model (every 8th frame) + edgeTAMManager.processFrameIfNeeded(rgbPixelBuffer, timestamp: CACurrentMediaTime()) + let cropRect = CGRect( x: 0, y: 0, width: self.viewPortSize.width, height: self.viewPortSize.height ) diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 7333964..9d5e0ea 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -272,7 +272,7 @@ class ARVisualizationManager: ObservableObject { private func createMovementArrow(from: SIMD3, to: SIMD3, confidence: Float, timestamp: TimeInterval) { guard let arView = arView, let worldOriginAnchor = worldOriginAnchor else { return } - DispatchQueue.main.async { [weak self, arView, worldOriginAnchor] in + DispatchQueue.main.async { [weak self, worldOriginAnchor] in guard let self = self else { return } // Calculate movement vector @@ -282,10 +282,6 @@ class ARVisualizationManager: ObservableObject { // Skip tiny movements guard movementMagnitude > 0.001 else { return } - // Convert positions to world coordinates (relative to world origin) - let worldFromPosition = self.worldOrigin + from - let worldToPosition = self.worldOrigin + to - // Create arrow entity showing movement from previous to current position let arrowEntity = self.createMovementArrowEntity( fromPosition: from, diff --git a/AnySense/Managers/BoundaryTrackingManager.swift b/AnySense/Managers/BoundaryTrackingManager.swift new file mode 100644 index 0000000..d9e25c5 --- /dev/null +++ b/AnySense/Managers/BoundaryTrackingManager.swift @@ -0,0 +1,408 @@ +// +// BoundaryTrackingManager.swift +// AnySense +// +// Boundary-based point tracking for robust segmentation +// + +import Foundation +import UIKit +import CoreImage +import Vision + +// MARK: - Boundary Point +struct BoundaryPoint { + let x: CGFloat + let y: CGFloat + let timestamp: Date + + init(x: CGFloat, y: CGFloat) { + self.x = x + self.y = y + self.timestamp = Date() + } + + var cgPoint: CGPoint { + return CGPoint(x: x, y: y) + } +} + +// MARK: - Tracked Boundary +struct TrackedBoundary { + let originalPoint: CGPoint + var currentPoint: CGPoint + var boundaryPoints: [BoundaryPoint] + let creationTime: Date + var lastUpdateTime: Date + var updateCount: Int + + init(originalPoint: CGPoint) { + self.originalPoint = originalPoint + self.currentPoint = originalPoint + self.boundaryPoints = [] + self.creationTime = Date() + self.lastUpdateTime = Date() + self.updateCount = 0 + } + + mutating func updateBoundary(points: [BoundaryPoint], newPoint: CGPoint) { + self.boundaryPoints = points + self.currentPoint = newPoint + self.lastUpdateTime = Date() + self.updateCount += 1 + } +} + +// MARK: - Boundary Tracking Manager +class BoundaryTrackingManager: ObservableObject { + + @Published var trackedBoundaries: [TrackedBoundary] = [] + @Published var isTracking: Bool = false + @Published var displayBoundaries: [TrackedBoundary] = [] // Only updated every 8 frames for display + + private let ciContext = CIContext() + + // MARK: - Boundary Extraction + func extractBoundaryPoints(from maskImage: UIImage) -> [BoundaryPoint] { + guard let cgImage = maskImage.cgImage else { + print("Could not get CGImage from mask") + return [] + } + + let width = cgImage.width + let height = cgImage.height + print("Mask image size: \(width)x\(height)") + + // EdgeTAM masks are 256x256 but model coordinates are 1024x1024 + // We need to scale boundary points by 4x to match model coordinate space + let scaleX: CGFloat = 1024.0 / CGFloat(width) + let scaleY: CGFloat = 1024.0 / CGFloat(height) + + // Convert image to grayscale pixel data + guard let pixelData = getPixelData(from: cgImage) else { + print("Could not extract pixel data") + return [] + } + + // Debug: Check pixel value distribution + let sampleSize = min(1000, pixelData.count) + let samplePixels = Array(pixelData.prefix(sampleSize)) + let nonZeroPixels = samplePixels.filter { $0 > 0 }.count + let maxPixel = samplePixels.max() ?? 0 + let minPixel = samplePixels.min() ?? 0 + print("Pixel analysis: \(nonZeroPixels)/\(sampleSize) non-zero, range: \(minPixel)-\(maxPixel)") + + var boundaryPoints: [BoundaryPoint] = [] + var maskPixelCount = 0 + + // Use a lower threshold since the mask might have different values + let threshold: UInt8 = 50 + + // Scan for boundary pixels (edge detection) + for y in 1..<(height-1) { + for x in 1..<(width-1) { + let currentIndex = y * width + x + let currentPixel = pixelData[currentIndex] + + // Count mask pixels + if currentPixel > threshold { + maskPixelCount += 1 + } + + // If current pixel is part of mask (above threshold) + if currentPixel > threshold { + // Check if it's a boundary pixel by examining neighbors + let neighbors = [ + pixelData[(y-1) * width + x], // top + pixelData[(y+1) * width + x], // bottom + pixelData[y * width + (x-1)], // left + pixelData[y * width + (x+1)], // right + ] + + // If any neighbor is background (below threshold), this is a boundary pixel + if neighbors.contains(where: { $0 <= threshold }) { + let boundaryPoint = BoundaryPoint( + x: CGFloat(x) * scaleX, // Scale to model coordinate space + y: CGFloat(y) * scaleY + ) + boundaryPoints.append(boundaryPoint) + } + } + } + } + + print("Mask analysis: \(maskPixelCount) mask pixels, \(boundaryPoints.count) boundary points") + + // If we still have no boundary points, try a more aggressive approach + if boundaryPoints.isEmpty && maskPixelCount > 0 { + print("Warning: No boundaries found with threshold \(threshold), trying aggressive detection...") + boundaryPoints = extractBoundaryPointsAggressive(from: pixelData, width: width, height: height, scaleX: scaleX, scaleY: scaleY) + } + + return boundaryPoints + } + + // More aggressive boundary detection + private func extractBoundaryPointsAggressive(from pixelData: [UInt8], width: Int, height: Int, scaleX: CGFloat, scaleY: CGFloat) -> [BoundaryPoint] { + var boundaryPoints: [BoundaryPoint] = [] + + // Find any non-zero pixels and treat edges as boundaries + for y in 1..<(height-1) { + for x in 1..<(width-1) { + let currentIndex = y * width + x + let currentPixel = pixelData[currentIndex] + + // If current pixel has any value + if currentPixel > 10 { + // Check 8-connected neighbors + let neighbors = [ + pixelData[(y-1) * width + (x-1)], // top-left + pixelData[(y-1) * width + x], // top + pixelData[(y-1) * width + (x+1)], // top-right + pixelData[y * width + (x-1)], // left + pixelData[y * width + (x+1)], // right + pixelData[(y+1) * width + (x-1)], // bottom-left + pixelData[(y+1) * width + x], // bottom + pixelData[(y+1) * width + (x+1)] // bottom-right + ] + + // If any neighbor is much different, this is a boundary + let avgNeighbor = neighbors.reduce(0, +) / UInt8(neighbors.count) + if abs(Int(currentPixel) - Int(avgNeighbor)) > 20 { + boundaryPoints.append(BoundaryPoint( + x: CGFloat(x) * scaleX, // Scale to model coordinate space + y: CGFloat(y) * scaleY + )) + } + } + } + } + + print("Aggressive extraction found \(boundaryPoints.count) boundary points") + return boundaryPoints + } + + // MARK: - Point Update Strategy + func updateTrackingPoint(for boundary: TrackedBoundary) -> CGPoint { + guard !boundary.boundaryPoints.isEmpty else { + print("Warning: No boundary points available, keeping original point") + return boundary.currentPoint + } + + // Find the closest boundary points to the current tracking point + let sortedByDistance = boundary.boundaryPoints.sorted { point1, point2 in + let dist1 = distanceSquared(from: boundary.currentPoint, to: point1.cgPoint) + let dist2 = distanceSquared(from: boundary.currentPoint, to: point2.cgPoint) + return dist1 < dist2 + } + + // Sample up to 5 closest boundary points + let sampleSize = min(5, sortedByDistance.count) + let sampledPoints = Array(sortedByDistance.prefix(sampleSize)) + + return sampleBoundaryPoints(from: sampledPoints) + } + + // Helper function to calculate distance squared (faster than sqrt) + private func distanceSquared(from point1: CGPoint, to point2: CGPoint) -> CGFloat { + let dx = point1.x - point2.x + let dy = point1.y - point2.y + return dx * dx + dy * dy + } + + private func sampleBoundaryPoints(from points: [BoundaryPoint]) -> CGPoint { + guard !points.isEmpty else { return .zero } + + // Calculate centroid of sampled boundary points + let totalX = points.reduce(0) { $0 + $1.x } + let totalY = points.reduce(0) { $0 + $1.y } + + let centroidX = totalX / CGFloat(points.count) + let centroidY = totalY / CGFloat(points.count) + + print("Updated point from \(points.count) boundary samples to (\(Int(centroidX)), \(Int(centroidY)))") + + return CGPoint(x: centroidX, y: centroidY) + } + + // MARK: - Tracking Management + func startTracking(initialPoint: CGPoint, maskImage: UIImage) { + var newBoundary = TrackedBoundary(originalPoint: initialPoint) + + // Debug: Save mask image to understand what we're working with + saveMaskImageForDebugging(maskImage, prefix: "initial") + + // Extract initial boundary + let boundaryPoints = extractBoundaryPoints(from: maskImage) + newBoundary.updateBoundary(points: boundaryPoints, newPoint: initialPoint) + + trackedBoundaries.append(newBoundary) + isTracking = true + + print("Started boundary tracking for point (\(Int(initialPoint.x)), \(Int(initialPoint.y)))") + } + + func startMultiPointTracking(initialPoints: [CGPoint], maskImage: UIImage) { + // Clear any existing tracking + trackedBoundaries.removeAll() + + // Debug: Save mask image to understand what we're working with + saveMaskImageForDebugging(maskImage, prefix: "multipoint_initial") + + // Extract boundary points once for all points to track + let boundaryPoints = extractBoundaryPoints(from: maskImage) + + // Create a tracked boundary for each initial point + for (index, initialPoint) in initialPoints.enumerated() { + var newBoundary = TrackedBoundary(originalPoint: initialPoint) + newBoundary.updateBoundary(points: boundaryPoints, newPoint: initialPoint) + trackedBoundaries.append(newBoundary) + + print("Started tracking point \(index + 1): (\(Int(initialPoint.x)), \(Int(initialPoint.y)))") + } + + isTracking = true + print("Started multi-point boundary tracking for \(initialPoints.count) points") + } + + // Debug helper to analyze mask images + private func saveMaskImageForDebugging(_ image: UIImage, prefix: String) { + print("\(prefix) mask image info: size=\(image.size), scale=\(image.scale)") + + // Analyze a small sample of the image + if let cgImage = image.cgImage, + let pixelData = getPixelData(from: cgImage) { + + let width = cgImage.width + let height = cgImage.height + let totalPixels = width * height + + // Count different pixel value ranges + var zeroPixels = 0 + var lowPixels = 0 // 1-50 + var mediumPixels = 0 // 51-200 + var highPixels = 0 // 201-255 + + for pixel in pixelData { + switch pixel { + case 0: zeroPixels += 1 + case 1...50: lowPixels += 1 + case 51...200: mediumPixels += 1 + case 201...255: highPixels += 1 + default: break + } + } + + print("\(prefix) pixel distribution:") + print(" - Zero (0): \(zeroPixels)/\(totalPixels) (\(Int(Double(zeroPixels)/Double(totalPixels)*100))%)") + print(" - Low (1-50): \(lowPixels)/\(totalPixels) (\(Int(Double(lowPixels)/Double(totalPixels)*100))%)") + print(" - Medium (51-200): \(mediumPixels)/\(totalPixels) (\(Int(Double(mediumPixels)/Double(totalPixels)*100))%)") + print(" - High (201-255): \(highPixels)/\(totalPixels) (\(Int(Double(highPixels)/Double(totalPixels)*100))%)") + } + } + + func updateAllBoundaries(with maskImage: UIImage, shouldUpdateDisplay: Bool = false) { + guard isTracking && !trackedBoundaries.isEmpty else { return } + + // Extract new boundary points from current mask + let newBoundaryPoints = extractBoundaryPoints(from: maskImage) + + for i in trackedBoundaries.indices { + // Update boundary points + trackedBoundaries[i].updateBoundary( + points: newBoundaryPoints, + newPoint: updateTrackingPoint(for: trackedBoundaries[i]) + ) + } + + // Only update display boundaries every 8 frames (when segmentation runs) + if shouldUpdateDisplay { + DispatchQueue.main.async { [weak self] in + self?.displayBoundaries = self?.trackedBoundaries ?? [] + } + print("Updated \(trackedBoundaries.count) tracked boundaries + display") + } else { + print("Updated \(trackedBoundaries.count) tracked boundaries (internal only)") + } + } + + func stopTracking() { + isTracking = false + trackedBoundaries.removeAll() + displayBoundaries.removeAll() + print("Stopped boundary tracking") + } + + func clearAllBoundaries() { + trackedBoundaries.removeAll() + displayBoundaries.removeAll() + print("Cleared all tracked boundaries") + } + + // MARK: - Utility Functions + private func getPixelData(from cgImage: CGImage) -> [UInt8]? { + let width = cgImage.width + let height = cgImage.height + let bytesPerPixel = 1 // Grayscale + let bytesPerRow = width * bytesPerPixel + let totalBytes = height * bytesPerRow + + var pixelData = [UInt8](repeating: 0, count: totalBytes) + + let colorSpace = CGColorSpaceCreateDeviceGray() + let context = CGContext( + data: &pixelData, + width: width, + height: height, + bitsPerComponent: 8, + bytesPerRow: bytesPerRow, + space: colorSpace, + bitmapInfo: CGImageAlphaInfo.none.rawValue + ) + + guard let ctx = context else { + print("Could not create CGContext") + return nil + } + + ctx.draw(cgImage, in: CGRect(x: 0, y: 0, width: width, height: height)) + + return pixelData + } + + // MARK: - Debug Information + var trackingStatistics: String { + if trackedBoundaries.isEmpty { + return "No active boundaries" + } + + let totalUpdates = trackedBoundaries.reduce(0) { $0 + $1.updateCount } + let avgBoundaryPoints = trackedBoundaries.isEmpty ? 0 : + trackedBoundaries.reduce(0) { $0 + $1.boundaryPoints.count } / trackedBoundaries.count + + return """ + Boundaries: \(trackedBoundaries.count) + Total Updates: \(totalUpdates) + Avg Boundary Points: \(avgBoundaryPoints) + """ + } +} + +// MARK: - Extensions +extension BoundaryTrackingManager { + + // Get current tracking points for segmentation (internal, always up to date) + var currentTrackingPoints: [CGPoint] { + return trackedBoundaries.map { $0.currentPoint } + } + + // Get display tracking points for UI (only updated every 8 frames) + var displayTrackingPoints: [CGPoint] { + return displayBoundaries.map { $0.currentPoint } + } + + // Get the most recently updated boundary + var latestBoundary: TrackedBoundary? { + return trackedBoundaries.max { $0.lastUpdateTime < $1.lastUpdateTime } + } +} \ No newline at end of file diff --git a/AnySense/Managers/EdgeTAMManager.swift b/AnySense/Managers/EdgeTAMManager.swift new file mode 100644 index 0000000..1e762d9 --- /dev/null +++ b/AnySense/Managers/EdgeTAMManager.swift @@ -0,0 +1,753 @@ +// +// EdgeTAMManager.swift +// AnySense +// +// Updated EdgeTAM model integration with full segmentation pipeline +// + +import Foundation +@preconcurrency import CoreML +import Vision +import CoreVideo +import CoreImage +import UIKit + +// MARK: - Prompt Types +struct EdgeTAMPrompt { + var points: [(CGPoint, Bool)] = [] // (point, isPositive) + var boxes: [CGRect] = [] + var maskInput: UIImage? +} + +class EdgeTAMManager: ObservableObject { + // MARK: - Properties + private var imageEncoder: MLModel? + private var promptEncoder: MLModel? + private var maskDecoder: MLModel? + private let ciContext = CIContext() + private var frameCounter: Int = 0 + private let frameInterval: Int = 30 // Process every 30th frame + + @Published var isProcessing: Bool = false + @Published var latestFeatures: MLMultiArray? + @Published var latestHighResFeats: (MLMultiArray?, MLMultiArray?) = (nil, nil) + @Published var processingTime: TimeInterval = 0 + @Published var processedFrameCount: Int = 0 + @Published var isModelLoaded: Bool = false + @Published var latestSegmentationMask: UIImage? + @Published var currentPrompt: EdgeTAMPrompt = EdgeTAMPrompt() + + // Multi-point tracking: Green points (original) and Red points (tracked) + @Published var originalPoints: [CGPoint] = [] // Green points - user input, never move + + // Boundary tracking integration + private var boundaryTrackingManager = BoundaryTrackingManager() + + // Model input requirements + private let modelInputSize = CGSize(width: 1024, height: 1024) + + // Processing queue + private let processingQueue = DispatchQueue(label: "EdgeTAMProcessingQueue", qos: .userInitiated) + + // MARK: - Initialization + init() { + loadEdgeTAMModel() + } + + // MARK: - Model Loading + private func loadEdgeTAMModel() { + loadAllModels() + } + + private func loadAllModels() { + var modelsLoaded = 0 + let totalModels = 3 + + // Load Image Encoder + if let imageEncoderURL = Bundle.main.url(forResource: "edgetam_image_encoder", withExtension: "mlmodelc") { + do { + imageEncoder = try MLModel(contentsOf: imageEncoderURL) + print("EdgeTAM Image Encoder loaded") + modelsLoaded += 1 + } catch { + print("Failed to load EdgeTAM Image Encoder: \(error)") + } + } else { + print("EdgeTAM Image Encoder not found") + } + + // Load Prompt Encoder + if let promptEncoderURL = Bundle.main.url(forResource: "edgetam_prompt_encoder", withExtension: "mlmodelc") { + do { + promptEncoder = try MLModel(contentsOf: promptEncoderURL) + print("EdgeTAM Prompt Encoder loaded") + modelsLoaded += 1 + } catch { + print("Failed to load EdgeTAM Prompt Encoder: \(error)") + } + } else { + print("EdgeTAM Prompt Encoder not found") + } + + // Load Mask Decoder + if let maskDecoderURL = Bundle.main.url(forResource: "edgetam_mask_decoder", withExtension: "mlmodelc") { + do { + maskDecoder = try MLModel(contentsOf: maskDecoderURL) + print("EdgeTAM Mask Decoder loaded") + modelsLoaded += 1 + } catch { + print("Failed to load EdgeTAM Mask Decoder: \(error)") + } + } else { + print("EdgeTAM Mask Decoder not found") + } + + DispatchQueue.main.async { + self.isModelLoaded = (modelsLoaded == totalModels) + if self.isModelLoaded { + print("All EdgeTAM models loaded successfully") + } else { + print("Warning: Only \(modelsLoaded)/\(totalModels) EdgeTAM models loaded") + } + } + } + + // MARK: - Frame Processing + func processFrameIfNeeded(_ pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval) { + frameCounter += 1 + + // Only process every nth frame + guard frameCounter % frameInterval == 0 else { return } + + // Skip if already processing + guard !isProcessing else { return } + + processingQueue.async { @Sendable [weak self] in + self?.processFrame(pixelBuffer, timestamp: timestamp) + } + } + + private func processFrame(_ pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval) { + guard let imageEncoderModel = imageEncoder else { + print("EdgeTAM image encoder not loaded") + return + } + + DispatchQueue.main.async { + self.isProcessing = true + } + + let startTime = CACurrentMediaTime() + + do { + // Prepare the pixel buffer for the model + let preparedPixelBuffer = try preparePixelBufferForModel(pixelBuffer) + + // Create input for the image encoder + let input = try MLDictionaryFeatureProvider(dictionary: ["image": preparedPixelBuffer]) + + // Run image encoder inference + let output = try imageEncoderModel.prediction(from: input) + + // Extract features + let visionFeatures = output.featureValue(for: "vision_features")?.multiArrayValue + let highResFeat0 = output.featureValue(for: "high_res_feat_0")?.multiArrayValue + let highResFeat1 = output.featureValue(for: "high_res_feat_1")?.multiArrayValue + + let processingTime = CACurrentMediaTime() - startTime + + // Generate segmentation mask if we have prompts + var segmentationMask: UIImage? + + if !currentPrompt.points.isEmpty { + // Run full segmentation pipeline + segmentationMask = runSegmentationPipeline( + visionFeatures: visionFeatures, + highResFeat0: highResFeat0, + highResFeat1: highResFeat1, + prompt: currentPrompt + ) + + // Update boundary tracking if we have a mask + // Since this runs every 8 frames, update display as well + if let mask = segmentationMask { + updateBoundaryTracking(with: mask, shouldUpdateDisplay: true) + } + } + + DispatchQueue.main.async { + self.latestFeatures = visionFeatures + self.latestHighResFeats = (highResFeat0, highResFeat1) + self.processingTime = processingTime + self.isProcessing = false + self.processedFrameCount += 1 + self.latestSegmentationMask = segmentationMask + } + + print("EdgeTAM processed frame \(self.frameCounter) - Time: \(String(format: "%.1f", processingTime * 1000))ms") + + } catch { + print("EdgeTAM processing error: \(error)") + DispatchQueue.main.async { + self.isProcessing = false + } + } + } + + // MARK: - Segmentation Pipeline + private func runSegmentationPipeline( + visionFeatures: MLMultiArray?, + highResFeat0: MLMultiArray?, + highResFeat1: MLMultiArray?, + prompt: EdgeTAMPrompt + ) -> UIImage? { + print("Starting segmentation pipeline...") + print(" Prompt points: \(prompt.points.count)") + print(" Prompt boxes: \(prompt.boxes.count)") + + guard let promptEncoderModel = promptEncoder, + let maskDecoderModel = maskDecoder, + let visionFeatures = visionFeatures, + let highResFeat0 = highResFeat0, + let highResFeat1 = highResFeat1 else { + print("Segmentation pipeline: Missing models or features") + print(" promptEncoder: \(promptEncoder != nil)") + print(" maskDecoder: \(maskDecoder != nil)") + print(" visionFeatures: \(visionFeatures != nil)") + print(" highResFeat0: \(highResFeat0 != nil)") + print(" highResFeat1: \(highResFeat1 != nil)") + return nil + } + + print("All models and features available") + + do { + // Prepare prompt inputs + print("Preparing prompt inputs...") + let promptInputs = try preparePromptInputs(prompt: prompt) + + // Run prompt encoder + print("Running prompt encoder...") + let promptEncoderOutput = try promptEncoderModel.prediction(from: promptInputs) + + guard let sparseEmbeddings = promptEncoderOutput.featureValue(for: "sparse_embeddings")?.multiArrayValue, + let denseEmbeddings = promptEncoderOutput.featureValue(for: "dense_embeddings")?.multiArrayValue else { + print("Failed to get prompt embeddings") + print(" Available outputs: \(promptEncoderOutput.featureNames)") + return nil + } + + print("Got prompt embeddings - sparse: \(sparseEmbeddings.shape), dense: \(denseEmbeddings.shape)") + + // Create positional encoding (simplified - zeros for now) + let imagePE = try createZeroArray(shape: visionFeatures.shape) + + // Prepare mask decoder inputs + print("Preparing mask decoder inputs...") + let maskDecoderInputs = try MLDictionaryFeatureProvider(dictionary: [ + "image_embeddings": visionFeatures, + "image_pe": imagePE, + "sparse_prompt_embeddings": sparseEmbeddings, + "dense_prompt_embeddings": denseEmbeddings, + "high_res_feat_0": highResFeat0, + "high_res_feat_1": highResFeat1, + "multimask_output": try createSingleValueArray(value: 1.0) // true + ]) + + // Run mask decoder + print("Running mask decoder...") + let maskDecoderOutput = try maskDecoderModel.prediction(from: maskDecoderInputs) + + print("Mask decoder completed") + print(" Available outputs: \(maskDecoderOutput.featureNames)") + + if let masks = maskDecoderOutput.featureValue(for: "masks")?.multiArrayValue, + let iouScores = maskDecoderOutput.featureValue(for: "iou_pred")?.multiArrayValue { + print("Got masks and IoU scores") + // Get best mask based on IoU score + return createSegmentationMask(from: masks, iouScores: iouScores) + } else { + print("Failed to extract masks or IoU scores from decoder output") + } + + } catch { + print("Segmentation pipeline error: \(error)") + } + + print("Segmentation pipeline failed - returning nil") + return nil + } + + private func preparePromptInputs(prompt: EdgeTAMPrompt) throws -> MLDictionaryFeatureProvider { + // Create arrays for prompt inputs + let maxPoints = 4 + let pointCoords = try MLMultiArray(shape: [1, NSNumber(value: maxPoints), 2], dataType: .float32) + let pointLabels = try MLMultiArray(shape: [1, NSNumber(value: maxPoints)], dataType: .float32) + let boxes = try MLMultiArray(shape: [1, 4], dataType: .float32) + let maskInput = try MLMultiArray(shape: [1, 1, 256, 256], dataType: .float32) + + // Initialize with default values + for i in 0.. MLMultiArray { + let array = try MLMultiArray(shape: shape, dataType: .float32) + let count = array.count + let pointer = array.dataPointer.bindMemory(to: Float32.self, capacity: count) + for i in 0.. MLMultiArray { + let array = try MLMultiArray(shape: [1], dataType: .float32) + array[0] = NSNumber(value: value) + return array + } + + private func createSegmentationMask(from masks: MLMultiArray, iouScores: MLMultiArray) -> UIImage? { + // masks shape: [1, 3, 256, 256] (3 masks generated) + // iouScores shape: [1, 3] + + print("Creating segmentation mask from MLMultiArray") + print(" Masks shape: \(masks.shape)") + print(" IoU scores shape: \(iouScores.shape)") + + // Find best mask based on IoU score + var bestMaskIndex = 0 + var bestScore: Float = 0 + + for i in 0..<3 { + let score = iouScores[[0, NSNumber(value: i)]].floatValue + print(" Mask \(i) IoU score: \(score)") + if score > bestScore { + bestScore = score + bestMaskIndex = i + } + } + + print(" Selected mask \(bestMaskIndex) with score \(bestScore)") + + // Sample some mask values to understand the data + var sampleValues: [Float] = [] + for i in 0.. 0.5 { + foregroundPixels += 1 + // Foreground - bright cyan + pixelData[pixelIndex] = 0 // Red + pixelData[pixelIndex + 1] = 255 // Green + pixelData[pixelIndex + 2] = 255 // Blue + pixelData[pixelIndex + 3] = UInt8(min(255, Int(probability * 180))) // Alpha + } else { + // Background - transparent + pixelData[pixelIndex] = 0 + pixelData[pixelIndex + 1] = 0 + pixelData[pixelIndex + 2] = 0 + pixelData[pixelIndex + 3] = 0 + } + } + } + + print(" Generated mask: \(foregroundPixels)/\(width*height) foreground pixels (\(Int(Double(foregroundPixels)/Double(width*height)*100))%)") + + guard let dataProvider = CGDataProvider(data: Data(pixelData) as CFData), + let cgImage = CGImage(width: width, + height: height, + bitsPerComponent: 8, + bitsPerPixel: 32, + bytesPerRow: bytesPerRow, + space: colorSpace, + bitmapInfo: [.byteOrder32Little, CGBitmapInfo(rawValue: CGImageAlphaInfo.premultipliedFirst.rawValue)], + provider: dataProvider, + decode: nil, + shouldInterpolate: false, + intent: .defaultIntent) else { + print("Failed to create CGImage from mask data") + return nil + } + + print("Successfully created segmentation mask UIImage") + return UIImage(cgImage: cgImage) + } + + // MARK: - Pixel Buffer Preparation + private func preparePixelBufferForModel(_ inputPixelBuffer: CVPixelBuffer) throws -> CVPixelBuffer { + // Create output pixel buffer for model input size (1024x1024) + let attributes: [String: Any] = [ + kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32ARGB, + kCVPixelBufferWidthKey as String: Int(modelInputSize.width), + kCVPixelBufferHeightKey as String: Int(modelInputSize.height), + kCVPixelBufferIOSurfacePropertiesKey as String: [:] + ] + + var outputPixelBuffer: CVPixelBuffer? + let status = CVPixelBufferCreate( + kCFAllocatorDefault, + Int(modelInputSize.width), + Int(modelInputSize.height), + kCVPixelFormatType_32ARGB, + attributes as CFDictionary, + &outputPixelBuffer + ) + + guard status == kCVReturnSuccess, let outputBuffer = outputPixelBuffer else { + throw NSError(domain: "EdgeTAMManager", code: -1, + userInfo: [NSLocalizedDescriptionKey: "Failed to create output pixel buffer"]) + } + + // Use Core Image to resize and process the frame + CVPixelBufferLockBaseAddress(inputPixelBuffer, .readOnly) + CVPixelBufferLockBaseAddress(outputBuffer, []) + defer { + CVPixelBufferUnlockBaseAddress(outputBuffer, []) + CVPixelBufferUnlockBaseAddress(inputPixelBuffer, .readOnly) + } + + let inputImage = CIImage(cvPixelBuffer: inputPixelBuffer) + + // Calculate scale to fit the model input size + let inputSize = CGSize( + width: CVPixelBufferGetWidth(inputPixelBuffer), + height: CVPixelBufferGetHeight(inputPixelBuffer) + ) + + let scaleX = modelInputSize.width / inputSize.width + let scaleY = modelInputSize.height / inputSize.height + let scale = min(scaleX, scaleY) // Maintain aspect ratio + + // Create transform to scale and center the image + let scaledWidth = inputSize.width * scale + let scaledHeight = inputSize.height * scale + let xOffset = (modelInputSize.width - scaledWidth) / 2 + let yOffset = (modelInputSize.height - scaledHeight) / 2 + + let transform = CGAffineTransform(scaleX: scale, y: scale) + .translatedBy(x: xOffset / scale, y: yOffset / scale) + + let scaledImage = inputImage.transformed(by: transform) + + // Render to output buffer + ciContext.render(scaledImage, to: outputBuffer) + + return outputBuffer + } + + + // MARK: - Boundary Tracking Methods + private func updateBoundaryTracking(with maskImage: UIImage, shouldUpdateDisplay: Bool = false) { + // Start or restart tracking when we have points to track + if !originalPoints.isEmpty { + if !boundaryTrackingManager.isTracking { + // Start tracking with multiple points + boundaryTrackingManager.startMultiPointTracking(initialPoints: originalPoints, maskImage: maskImage) + } else { + // Update existing tracking + boundaryTrackingManager.updateAllBoundaries(with: maskImage, shouldUpdateDisplay: shouldUpdateDisplay) + } + + // Update current prompt with tracked points for next segmentation + updatePromptWithTrackedPoints() + } + } + + private func updatePromptWithTrackedPoints() { + let trackedPoints = boundaryTrackingManager.currentTrackingPoints + + if !trackedPoints.isEmpty { + // Update the first point with the tracked position, keep others as positive + currentPrompt.points = trackedPoints.enumerated().map { index, point in + (point, true) // All tracked points are positive + } + + print("Updated prompt with \(trackedPoints.count) tracked points") + } + } + + func startBoundaryTracking() { + guard !currentPrompt.points.isEmpty else { + print("Warning: Cannot start boundary tracking without prompt points") + return + } + + // Boundary tracking will start automatically on next segmentation + print("Boundary tracking ready - will start on next segmentation") + } + + func stopBoundaryTracking() { + boundaryTrackingManager.stopTracking() + print("Stopped boundary tracking") + } + + var boundaryTrackingStatistics: String { + return boundaryTrackingManager.trackingStatistics + } + + var isBoundaryTracking: Bool { + return boundaryTrackingManager.isTracking + } + + // Get display points for UI (updated every 8 frames) + var displayTrackingPoints: [CGPoint] { + return boundaryTrackingManager.displayTrackingPoints + } + + // MARK: - Public Methods + func reset() { + frameCounter = 0 + latestFeatures = nil + latestHighResFeats = (nil, nil) + processingTime = 0 + isProcessing = false + processedFrameCount = 0 + latestSegmentationMask = nil + currentPrompt = EdgeTAMPrompt() + boundaryTrackingManager.stopTracking() + } + + func generateMaskForTrackedObject(prompt: EdgeTAMPrompt) async -> UIImage? { + guard let visionFeatures = latestFeatures, + let highResFeat0 = latestHighResFeats.0, + let highResFeat1 = latestHighResFeats.1 else { + print("No features available for mask generation") + return nil + } + + return await withCheckedContinuation { continuation in + processingQueue.async { @Sendable [weak self] in + let mask = self?.runSegmentationPipeline( + visionFeatures: visionFeatures, + highResFeat0: highResFeat0, + highResFeat1: highResFeat1, + prompt: prompt + ) + continuation.resume(returning: mask) + } + } + } + + func processFrameForTracking(_ pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval) { + // Process frame and also notify object tracking manager + processFrameIfNeeded(pixelBuffer, timestamp: timestamp) + + // Frame processing completed + } + + private func pixelBufferToUIImage(_ pixelBuffer: CVPixelBuffer) -> UIImage? { + let ciImage = CIImage(cvPixelBuffer: pixelBuffer) + guard let cgImage = ciContext.createCGImage(ciImage, from: ciImage.extent) else { + return nil + } + return UIImage(cgImage: cgImage) + } + + // MARK: - Prompt Handling + func addPromptPoint(_ point: CGPoint, isPositive: Bool = true) { + // Convert screen coordinates to model coordinates (1024x1024) + let modelPoint = CGPoint(x: point.x * modelInputSize.width, y: point.y * modelInputSize.height) + currentPrompt.points.append((modelPoint, isPositive)) + + print("Added prompt point: (\(Int(modelPoint.x)), \(Int(modelPoint.y))) - \(isPositive ? "Positive" : "Negative")") + } + + func addPromptPointWithConstraints(_ normalizedPoint: CGPoint, screenPoint: CGPoint, screenSize: CGSize) -> Bool { + // Check constraint 1: Maximum 4 points + guard currentPrompt.points.count < 4 else { + print("Point rejected: Maximum 4 points allowed") + return false + } + + // Check constraint 2: Minimum distance of 0.5 screen units from existing points + let minimumDistance: CGFloat = 0.5 + for existingPoint in originalPoints { + let existingScreenPoint = convertModelPointToScreen(existingPoint, screenSize: screenSize) + let distance = sqrt(pow(screenPoint.x - existingScreenPoint.x, 2) + pow(screenPoint.y - existingScreenPoint.y, 2)) + + if distance < minimumDistance { + print("Point rejected: Too close to existing point (distance: \(Int(distance)) < \(Int(minimumDistance)))") + return false + } + } + + // Check constraint 3: Point must be within current segmentation mask (if one exists) + if let maskImage = latestSegmentationMask { + if !isPointWithinMask(normalizedPoint, mask: maskImage) { + print("Point rejected: Outside current segmentation mask") + return false + } + } + + // All constraints passed - add the point + let modelPoint = CGPoint(x: normalizedPoint.x * modelInputSize.width, y: normalizedPoint.y * modelInputSize.height) + + // Only positive points allowed now + currentPrompt.points.append((modelPoint, true)) + originalPoints.append(modelPoint) + + print("Added point: (\(Int(modelPoint.x)), \(Int(modelPoint.y))) - Total: \(currentPrompt.points.count)") + + return true + } + + // Helper to convert model coordinates back to screen coordinates + private func convertModelPointToScreen(_ modelPoint: CGPoint, screenSize: CGSize) -> CGPoint { + let normalizedX = modelPoint.x / modelInputSize.width + let normalizedY = modelPoint.y / modelInputSize.height + return CGPoint(x: normalizedX * screenSize.width, y: normalizedY * screenSize.height) + } + + // Helper to check if point is within segmentation mask + private func isPointWithinMask(_ normalizedPoint: CGPoint, mask: UIImage) -> Bool { + guard let cgImage = mask.cgImage else { return false } + + let width = cgImage.width + let height = cgImage.height + + // Convert normalized point to mask coordinates + let maskX = Int(normalizedPoint.x * CGFloat(width)) + let maskY = Int(normalizedPoint.y * CGFloat(height)) + + // Ensure coordinates are within bounds + guard maskX >= 0 && maskX < width && maskY >= 0 && maskY < height else { return false } + + // Get pixel data and check if the point is in a mask region + guard let pixelData = getPixelData(from: cgImage) else { return false } + + let pixelIndex = maskY * width + maskX + let pixelValue = pixelData[pixelIndex] + + // Consider point valid if pixel value is above threshold (indicating mask region) + return pixelValue > 50 // Threshold for mask detection + } + + // Helper to extract pixel data from image + private func getPixelData(from cgImage: CGImage) -> [UInt8]? { + let width = cgImage.width + let height = cgImage.height + let bytesPerPixel = 4 + let bytesPerRow = width * bytesPerPixel + let totalBytes = height * bytesPerRow + + var pixelData = [UInt8](repeating: 0, count: totalBytes) + + guard let context = CGContext( + data: &pixelData, + width: width, + height: height, + bitsPerComponent: 8, + bytesPerRow: bytesPerRow, + space: CGColorSpaceCreateDeviceRGB(), + bitmapInfo: CGImageAlphaInfo.noneSkipLast.rawValue + ) else { return nil } + + context.draw(cgImage, in: CGRect(x: 0, y: 0, width: width, height: height)) + + // Convert RGBA to grayscale + var grayscaleData = [UInt8](repeating: 0, count: width * height) + for i in 0..<(width * height) { + let r = pixelData[i * 4] + let g = pixelData[i * 4 + 1] + let b = pixelData[i * 4 + 2] + grayscaleData[i] = UInt8((Int(r) + Int(g) + Int(b)) / 3) + } + + return grayscaleData + } + + func addPromptBox(_ box: CGRect) { + // Convert screen coordinates to model coordinates + let modelBox = CGRect( + x: box.origin.x * modelInputSize.width, + y: box.origin.y * modelInputSize.height, + width: box.size.width * modelInputSize.width, + height: box.size.height * modelInputSize.height + ) + currentPrompt.boxes.append(modelBox) + + print("Added prompt box: \(modelBox)") + } + + func clearPrompts() { + currentPrompt = EdgeTAMPrompt() + originalPoints.removeAll() + latestSegmentationMask = nil + boundaryTrackingManager.stopTracking() + print("Cleared all prompts and tracking") + } + + func setFrameInterval(_ interval: Int) { + guard interval > 0 else { return } + frameCounter = 0 + print("EdgeTAM frame interval set to: \(interval)") + } + + // MARK: - Status Properties + var statusText: String { + if !isModelLoaded { + return "EdgeTAM: Models not loaded" + } + + if processedFrameCount == 0 { + return "EdgeTAM: Ready" + } + + return "EdgeTAM: \(processedFrameCount) frames, \(String(format: "%.1f", processingTime * 1000))ms" + } + + var isActive: Bool { + return isModelLoaded && (processedFrameCount > 0 || isProcessing) + } +} \ No newline at end of file diff --git a/AnySense/Managers/ModelManager.swift b/AnySense/Managers/ModelManager.swift index ee243f1..5001d1a 100644 --- a/AnySense/Managers/ModelManager.swift +++ b/AnySense/Managers/ModelManager.swift @@ -151,7 +151,7 @@ class ModelManager: ObservableObject { let modelUploadDate = Date() // Use current date as upload date // Create model info (we'll validate compatibility after compilation) - var modelInfo = ModelInfo( + let modelInfo = ModelInfo( name: modelName, fileName: fileName, source: .uploaded, @@ -195,11 +195,11 @@ class ModelManager: ObservableObject { print("DEBUG: Final compiled location: \(finalCompiledURL.path)") // Update model status - modelInfo.compilationStatus = .compiled + let modelId = modelInfo.id await MainActor.run { - if let index = availableModels.firstIndex(where: { $0.id == modelInfo.id }) { - availableModels[index] = modelInfo + if let index = availableModels.firstIndex(where: { $0.id == modelId }) { + availableModels[index].compilationStatus = .compiled } isCompiling = false @@ -207,7 +207,7 @@ class ModelManager: ObservableObject { saveModelRegistry() // Automatically activate the newly uploaded model - setActiveModel(id: modelInfo.id) + setActiveModel(id: modelId) print("Successfully compiled model: \(modelName)") } diff --git a/AnySense/ModelInfo.swift b/AnySense/ModelInfo.swift index 5f84386..d9e38ff 100644 --- a/AnySense/ModelInfo.swift +++ b/AnySense/ModelInfo.swift @@ -8,7 +8,7 @@ struct ModelInfo: Identifiable, Codable, Equatable { let source: ModelSource var compilationStatus: CompilationStatus let fileSize: Int64 - let uploadDate: Date? + let uploadDate: Date var isActive: Bool init(name: String, fileName: String, source: ModelSource, fileSize: Int64 = 0, uploadDate: Date? = nil) { diff --git a/AnySense/Views/EdgeTAMStatusView.swift b/AnySense/Views/EdgeTAMStatusView.swift new file mode 100644 index 0000000..91c3d93 --- /dev/null +++ b/AnySense/Views/EdgeTAMStatusView.swift @@ -0,0 +1,136 @@ +// +// EdgeTAMStatusView.swift +// AnySense +// +// UI component for displaying EdgeTAM processing status +// + +import SwiftUI + +struct EdgeTAMStatusView: View { + @ObservedObject var edgeTAMManager: EdgeTAMManager + + var body: some View { + VStack(alignment: .leading, spacing: 8) { + HStack { + Circle() + .fill(statusColor) + .frame(width: 8, height: 8) + + Text(edgeTAMManager.statusText) + .font(.caption) + .foregroundColor(.primary) + } + + if edgeTAMManager.isModelLoaded && edgeTAMManager.processedFrameCount > 0 { + HStack { + Text("Processing every 8th frame") + .font(.caption2) + .foregroundColor(.secondary) + + if edgeTAMManager.isProcessing { + ProgressView() + .scaleEffect(0.5) + } + } + } + + if let features = edgeTAMManager.latestFeatures { + Text("Features: \(features.shape.map { String(describing: $0) }.joined(separator: "x"))") + .font(.caption2) + .foregroundColor(.secondary) + } + + // Show segmentation status + if !edgeTAMManager.currentPrompt.points.isEmpty { + HStack { + Text("Segmentation:") + .font(.caption2) + .foregroundColor(.secondary) + + if edgeTAMManager.latestSegmentationMask != nil { + HStack(spacing: 4) { + Image(systemName: "checkmark.circle.fill") + .foregroundColor(.green) + .font(.caption2) + Text("Mask ready") + .font(.caption2) + .foregroundColor(.green) + } + } else { + HStack(spacing: 4) { + ProgressView() + .scaleEffect(0.5) + Text("Generating...") + .font(.caption2) + .foregroundColor(.orange) + } + } + } + } + } + .padding() + .background(Color.secondary.opacity(0.1)) + .cornerRadius(8) + } + + private var statusColor: Color { + if !edgeTAMManager.isModelLoaded { + return .red + } else if edgeTAMManager.isProcessing { + return .orange + } else if edgeTAMManager.isActive { + return .green + } else { + return .gray + } + } +} + +struct EdgeTAMControlView: View { + @ObservedObject var edgeTAMManager: EdgeTAMManager + @State private var frameInterval: Double = 8 + + var body: some View { + VStack(alignment: .leading, spacing: 12) { + Text("EdgeTAM Settings") + .font(.headline) + + HStack { + Text("Process every") + Slider(value: $frameInterval, in: 1...30, step: 1) + .frame(width: 100) + Text("\(Int(frameInterval)) frames") + .frame(width: 70) + } + .font(.caption) + + Button(action: { + edgeTAMManager.setFrameInterval(Int(frameInterval)) + }) { + Text("Update Interval") + .font(.caption) + .padding(.horizontal, 12) + .padding(.vertical, 6) + .background(Color.blue) + .foregroundColor(.white) + .cornerRadius(6) + } + + Button(action: { + edgeTAMManager.reset() + }) { + Text("Reset") + .font(.caption) + .padding(.horizontal, 12) + .padding(.vertical, 6) + .background(Color.red.opacity(0.8)) + .foregroundColor(.white) + .cornerRadius(6) + } + } + .padding() + .background(Color.secondary.opacity(0.1)) + .cornerRadius(8) + } +} diff --git a/AnySense/Views/EdgeTAMVisualizationOverlay.swift b/AnySense/Views/EdgeTAMVisualizationOverlay.swift new file mode 100644 index 0000000..c6fe1b7 --- /dev/null +++ b/AnySense/Views/EdgeTAMVisualizationOverlay.swift @@ -0,0 +1,364 @@ +// +// EdgeTAMVisualizationOverlay.swift +// AnySense +// +// Real-time EdgeTAM visualization overlay with full segmentation pipeline +// + +import SwiftUI + +struct EdgeTAMVisualizationOverlay: View { + @ObservedObject var edgeTAMManager: EdgeTAMManager + @State private var showVisualization: Bool = false + @State private var overlayOpacity: Double = 0.7 + @State private var isPromptMode: Bool = false + + var body: some View { + GeometryReader { geometry in + ZStack { + // EdgeTAM segmentation mask overlay + if showVisualization && !edgeTAMManager.currentPrompt.points.isEmpty { + if let segmentationMask = edgeTAMManager.latestSegmentationMask { + Image(uiImage: segmentationMask) + .interpolation(.none) + .resizable() + .aspectRatio(contentMode: .fit) + .opacity(overlayOpacity) + .animation(.easeInOut(duration: 0.3), value: edgeTAMManager.latestSegmentationMask) + } + } + + // Tap gesture overlay for adding prompts + if isPromptMode { + Color.clear + .contentShape(Rectangle()) + .onTapGesture { location in + addPromptPoint(at: location, in: geometry) + } + } + + // Show prompt points overlay + if edgeTAMManager.isBoundaryTracking { + // Show original green points (user input, never move) + ForEach(0.. 0 { + VStack(alignment: .trailing, spacing: 2) { + Text("EdgeTAM") + .font(.caption.bold()) + .foregroundColor(.white) + + Text("Segmentation") + .font(.caption2) + .foregroundColor(.white.opacity(0.8)) + + Text("\(edgeTAMManager.processedFrameCount) frames") + .font(.caption2) + .foregroundColor(.white.opacity(0.8)) + + Text("\(String(format: "%.0f", edgeTAMManager.processingTime * 1000))ms") + .font(.caption2) + .foregroundColor(.white.opacity(0.8)) + + if !edgeTAMManager.currentPrompt.points.isEmpty { + Text("\(edgeTAMManager.currentPrompt.points.count) points") + .font(.caption2) + .foregroundColor(.yellow.opacity(0.8)) + } + + if edgeTAMManager.isBoundaryTracking { + Text("Boundary Tracking") + .font(.caption2) + .foregroundColor(.green.opacity(0.8)) + } + } + .padding(8) + .background(Color.black.opacity(0.7)) + .cornerRadius(8) + } + } + .padding(.trailing, 20) + .padding(.bottom, 100) // Above other UI elements + } + } + + // Prompt mode instructions + if isPromptMode { + VStack { + HStack { + VStack(alignment: .leading, spacing: 4) { + Text("Prompt Mode") + .font(.headline) + .foregroundColor(.white) + + Text("Tap to add positive points") + .font(.caption) + .foregroundColor(.white.opacity(0.8)) + + Text("Long press for negative points") + .font(.caption) + .foregroundColor(.white.opacity(0.8)) + } + .padding(12) + .background(Color.black.opacity(0.8)) + .cornerRadius(8) + + Spacer() + } + .padding(.top, 50) + .padding(.leading, 20) + + Spacer() + } + .transition(.opacity.combined(with: .move(edge: .top))) + } + } + } + } + + // MARK: - Helper Functions + private func addPromptPoint(at location: CGPoint, in geometry: GeometryProxy) { + // Convert screen coordinates to normalized coordinates (0-1) + let normalizedPoint = CGPoint( + x: location.x / geometry.size.width, + y: location.y / geometry.size.height + ) + + // Try to add point with constraints - pass screen coordinates for distance checking + let success = edgeTAMManager.addPromptPointWithConstraints( + normalizedPoint, + screenPoint: location, + screenSize: geometry.size + ) + + if !success { + // Could add visual feedback here (shake animation, error message, etc.) + print("⚠️ Point rejected: outside mask or too close to existing point") + } + } + + private func convertModelPointToScreen(_ modelPoint: CGPoint, in geometry: GeometryProxy) -> CGPoint { + // Convert model coordinates (0-1024) back to screen coordinates + let normalizedX = modelPoint.x / 1024.0 + let normalizedY = modelPoint.y / 1024.0 + + return CGPoint( + x: normalizedX * geometry.size.width, + y: normalizedY * geometry.size.height + ) + } + + private func convertTuplePointToScreen(_ tuplePoint: (CGPoint, Bool), in geometry: GeometryProxy) -> CGPoint { + return convertModelPointToScreen(tuplePoint.0, in: geometry) + } +} + +// MARK: - Enhanced Controls +struct EdgeTAMVisualizationControls: View { + @ObservedObject var edgeTAMManager: EdgeTAMManager + + var body: some View { + VStack(alignment: .leading, spacing: 12) { + Text("EdgeTAM Segmentation") + .font(.headline) + + // Model status + HStack { + Image(systemName: edgeTAMManager.isModelLoaded ? "checkmark.circle.fill" : "xmark.circle.fill") + .foregroundColor(edgeTAMManager.isModelLoaded ? .green : .red) + + Text(edgeTAMManager.isModelLoaded ? "Models Loaded" : "Models Not Loaded") + .font(.caption) + } + + // Segmentation controls + if !edgeTAMManager.currentPrompt.points.isEmpty { + VStack(alignment: .leading, spacing: 8) { + Text("Active Segmentation") + .font(.subheadline.bold()) + + HStack { + Button("Clear Prompts") { + edgeTAMManager.clearPrompts() + } + .buttonStyle(.bordered) + + Spacer() + + Text("\(edgeTAMManager.currentPrompt.points.count) points") + .font(.caption) + .foregroundColor(.secondary) + } + + if edgeTAMManager.latestSegmentationMask != nil { + Text("✓ Mask generated") + .font(.caption2) + .foregroundColor(.green) + } + } + .padding(8) + .background(Color.blue.opacity(0.1)) + .cornerRadius(8) + } else { + Text("Tap screen in prompt mode to add points") + .font(.caption) + .foregroundColor(.secondary) + .italic() + } + + // Processing info + if edgeTAMManager.processedFrameCount > 0 { + VStack(alignment: .leading, spacing: 4) { + Text("Processing: \(edgeTAMManager.processedFrameCount) frames") + .font(.caption2) + .foregroundColor(.secondary) + + Text("Last update: \(String(format: "%.1f", edgeTAMManager.processingTime * 1000))ms") + .font(.caption2) + .foregroundColor(.secondary) + } + } + } + .padding() + .background(Color.secondary.opacity(0.1)) + .cornerRadius(8) + } +} diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index cacd053..1b3fd4d 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -184,16 +184,14 @@ struct SettingsView : View{ .foregroundColor(activeModel.compilationStatus.isCompiled ? .green : .orange) } - if let date = activeModel.uploadDate { - HStack { - Text("Uploaded:") - .font(.caption) - .foregroundColor(.gray) - Spacer() - Text(date.formatted(date: .abbreviated, time: .omitted)) - .font(.caption) - .foregroundColor(.gray) - } + HStack { + Text("Uploaded:") + .font(.caption) + .foregroundColor(.gray) + Spacer() + Text(activeModel.uploadDate.formatted(date: .abbreviated, time: .omitted)) + .font(.caption) + .foregroundColor(.gray) } if activeModel.source == .uploaded && activeModel.fileSize > 0 { @@ -228,11 +226,9 @@ struct SettingsView : View{ Text(model.statusDescription) .font(.caption2) .foregroundColor(model.compilationStatus.isCompiled ? .green : .orange) - if let date = model.uploadDate { - Text(date.formatted(date: .abbreviated, time: .omitted)) - .font(.caption2) - .foregroundColor(.gray) - } + Text(model.uploadDate.formatted(date: .abbreviated, time: .omitted)) + .font(.caption2) + .foregroundColor(.gray) } Spacer() diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index cf93a3e..8d9ffe8 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -45,23 +45,37 @@ struct ReadView : View{ Color.customizedBackground .ignoresSafeArea() ZStack{ - ARViewContainer( - session: arViewModel.session, - arVisualizationManager: arViewModel.arVisualizationManager - ) + ZStack { + ARViewContainer( + session: arViewModel.session, + arVisualizationManager: arViewModel.arVisualizationManager + ) .edgesIgnoringSafeArea(.all) - .frame(width: arViewWidth, height: arViewHeight) - // .clipShape(RoundedRectangle(cornerRadius: 30, style: .continuous)) - .padding(.bottom, arViewPadding) .opacity(appStatus.rgbdVideoStreaming == .off ? 1 : 0) .allowsHitTesting(appStatus.rgbdVideoStreaming == .off) // Disable interaction in streaming mode + + // EdgeTAM Visualization Overlay + if appStatus.rgbdVideoStreaming == .off { + EdgeTAMVisualizationOverlay(edgeTAMManager: arViewModel.edgeTAMManager) + } + } + .frame(width: arViewWidth, height: arViewHeight) + .padding(.bottom, arViewPadding) - // ML Inference Results Overlay - if appStatus.rgbdVideoStreaming == .off && appStatus.mlInferenceEnabled && arViewModel.mlManager?.isInferenceEnabled == true { + // ML and EdgeTAM Status Overlay + if appStatus.rgbdVideoStreaming == .off { VStack { HStack { - if let mlManager = arViewModel.mlManager { - MLInferenceResultsView(mlManager: mlManager) + VStack(alignment: .leading, spacing: 8) { + // ML Inference Results (only when enabled) + if appStatus.mlInferenceEnabled && arViewModel.mlManager?.isInferenceEnabled == true { + if let mlManager = arViewModel.mlManager { + MLInferenceResultsView(mlManager: mlManager) + } + } + + // EdgeTAM Status (always show when not streaming) + EdgeTAMStatusView(edgeTAMManager: arViewModel.edgeTAMManager) } Spacer() } From 466d4089172ddc9f99a68f8657d745b75af0cb71 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Sun, 31 Aug 2025 11:47:28 -0400 Subject: [PATCH 14/56] Align USB robot action transform with server (P+Z90), unify VQ-BeT 3D goal mapping to labels.json (camera frame) --- AnySense/Managers/ActionTransformUtils.swift | 126 ++++ AnySense/Managers/MLInferenceManager.swift | 604 ++++++++++++++++--- 2 files changed, 661 insertions(+), 69 deletions(-) create mode 100644 AnySense/Managers/ActionTransformUtils.swift diff --git a/AnySense/Managers/ActionTransformUtils.swift b/AnySense/Managers/ActionTransformUtils.swift new file mode 100644 index 0000000..632e3de --- /dev/null +++ b/AnySense/Managers/ActionTransformUtils.swift @@ -0,0 +1,126 @@ +import Foundation +import simd + +struct ActionTransformUtils { + // Server-defined transforms (record3d → personal camera) and +90° about Z + private static let P: simd_float4x4 = { + let c0 = SIMD4(-1, 0, 0, 0) + let c1 = SIMD4( 0, 0, -1, 0) + let c2 = SIMD4( 0, -1, 0, 0) + let c3 = SIMD4( 0, 0, 0, 1) + return simd_float4x4(columns: (c0, c1, c2, c3)) + }() + + private static let Z90: simd_float4x4 = { + let c0 = SIMD4( 0, 1, 0, 0) + let c1 = SIMD4(-1, 0, 0, 0) + let c2 = SIMD4( 0, 0, 1, 0) + let c3 = SIMD4( 0, 0, 0, 1) + return simd_float4x4(columns: (c0, c1, c2, c3)) + }() + + // MARK: - Public Entry + // Input: [tx, ty, tz, rx, ry, rz, gripper] in iPhone camera frame (Euler xyz, radians) + // Output: robot-frame [tx, ty, tz, rx, ry, rz, gripper] + static func toRobotActions(_ action7: [Float]) -> [Float] { + guard action7.count >= 7 else { return action7 } + let tx = action7[0], ty = action7[1], tz = action7[2] + let rx = action7[3], ry = action7[4], rz = action7[5] + let gr = action7[6] + + // 1) iPhone action → 4x4 + let T_c = buildTransform(translation: SIMD3(tx, ty, tz), eulerXYZ: SIMD3(rx, ry, rz)) + + // 2) Camera → Robot: T_r = Z90 @ (P.T @ T_c @ P) @ Z90.T + let Pt = simd_transpose(P) + let Zt = simd_transpose(Z90) + let T_perm = Pt * T_c * P + let T_r = Z90 * T_perm * Zt + + // 3) 4x4 → action (Euler xyz) + let rxyz = eulerXYZ(from: T_r) + let t = translation(from: T_r) + + return [t.x, t.y, t.z, rxyz.x, rxyz.y, rxyz.z, gr] + } + + // MARK: - Builders + private static func buildTransform(translation t: SIMD3, eulerXYZ r: SIMD3) -> simd_float4x4 { + let R = rotationMatrixXYZ(rx: r.x, ry: r.y, rz: r.z) + var T = matrix_identity_float4x4 + T.columns.0 = SIMD4(R.columns.0.x, R.columns.0.y, R.columns.0.z, 0) + T.columns.1 = SIMD4(R.columns.1.x, R.columns.1.y, R.columns.1.z, 0) + T.columns.2 = SIMD4(R.columns.2.x, R.columns.2.y, R.columns.2.z, 0) + T.columns.3 = SIMD4(t.x, t.y, t.z, 1) + return T + } + + // Rotation matrix for Euler 'xyz' (radians) + // Using standard formula: + // R = [[ cy*cz, -cy*sz, sy ], + // [ cx*sz + cz*sx*sy, cx*cz - sx*sy*sz, -cy*sx ], + // [ sx*sz - cx*cz*sy, cz*sx + cx*sy*sz, cx*cy ]] + private static func rotationMatrixXYZ(rx: Float, ry: Float, rz: Float) -> simd_float3x3 { + let cx = cos(rx), sx = sin(rx) + let cy = cos(ry), sy = sin(ry) + let cz = cos(rz), sz = sin(rz) + + let r00 = cy * cz + let r01 = -cy * sz + let r02 = sy + + let r10 = cx * sz + cz * sx * sy + let r11 = cx * cz - sx * sy * sz + let r12 = -cy * sx + + let r20 = sx * sz - cx * cz * sy + let r21 = cz * sx + cx * sy * sz + let r22 = cx * cy + + let c0 = SIMD3(r00, r10, r20) + let c1 = SIMD3(r01, r11, r21) + let c2 = SIMD3(r02, r12, r22) + return simd_float3x3(columns: (c0, c1, c2)) + } + + // Extract Euler 'xyz' (radians) from 4x4 + private static func eulerXYZ(from T: simd_float4x4) -> SIMD3 { + // Reconstruct row-major elements from column-major storage + let R00 = T.columns.0.x, R01 = T.columns.1.x, R02 = T.columns.2.x + let R10 = T.columns.0.y, R11 = T.columns.1.y, R12 = T.columns.2.y + let R20 = T.columns.0.z, R21 = T.columns.1.z, R22 = T.columns.2.z + + // For 'xyz': + // y = asin(R02) + // if |cos(y)| > eps: + // x = atan2(-R12, R22) + // z = atan2(-R01, R00) + // else (gimbal lock): + // x = atan2(R21, R11) + // z = 0 + let y = asin(clamp(R02, -1.0, 1.0)) + let cy = cos(y) + let eps: Float = 1e-6 + let x: Float + let z: Float + if abs(cy) > eps { + x = atan2(-R12, R22) + z = atan2(-R01, R00) + } else { + // Gimbal lock + x = atan2(R21, R11) + z = 0.0 + } + return SIMD3(x, y, z) + } + + private static func translation(from T: simd_float4x4) -> SIMD3 { + return SIMD3(T.columns.3.x, T.columns.3.y, T.columns.3.z) + } + + private static func clamp(_ v: Float, _ lo: Float, _ hi: Float) -> Float { + return max(lo, min(hi, v)) + } +} + + diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 6566886..9d43f7f 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -13,6 +13,9 @@ import QuartzCore import Combine import RealityKit import CoreImage +import ARKit +import simd +import UIKit // MARK: - ML Inference Results struct InferenceResult { @@ -27,12 +30,20 @@ class MLInferenceManager: ObservableObject { @Published var latestResult: InferenceResult? @Published var isInferenceEnabled: Bool = false @Published var inferenceFrequency: InferenceFrequency = .medium + @Published var currentGoalPoint: simd_float3? + @Published var modelMetadata: ModelMetadata? // MARK: - Private Properties private var model: MLModel? - private var lastInferenceTime: CFTimeInterval = -Double.infinity // Start with negative infinity to ensure first inference runs + private var lastInferenceTime: CFTimeInterval = 0 private var inferenceQueue = DispatchQueue(label: "MLInferenceQueue", qos: .userInitiated) + // MARK: - Goal Point Management + private var goalPointQueue = DispatchQueue(label: "GoalPointQueue", qos: .userInitiated) + + // Goal conditioning mode (matching Python goal_dim) + private var goalDimension: Int = 2 // Default to 2D mode, can be 3 for 3D mode + // MARK: - Model Management private var modelManager: ModelManager private var cancellables = Set() @@ -40,6 +51,10 @@ class MLInferenceManager: ObservableObject { // MARK: - AR Visualization Integration weak var arVisualizationManager: ARVisualizationManager? + // MARK: - Odometry Point Tracking + @Published var odometryTracker = OdometryPointTracker() + @Published var enableOdometryTracking: Bool = true + // MARK: - Frame Processing (Taken from ARViewContainer) private let ciContext: CIContext private let modelInputSize = CGSize(width: 256, height: 256) @@ -96,16 +111,39 @@ class MLInferenceManager: ObservableObject { activeModel.compilationStatus.isCompiled else { print("No active compiled model available") model = nil + modelMetadata = nil return } do { - model = try modelManager.loadModel(for: activeModel) + let loadedModel = try modelManager.loadModel(for: activeModel) + model = loadedModel + + // Extract model metadata for type detection + modelMetadata = try ModelMetadata(from: loadedModel) + setupModelInputTransform() print("Successfully loaded model: \(activeModel.name)") + print("Model Type: \(modelMetadata?.modelType.displayName ?? "Unknown")") + print("Requires Goal Point: \(modelMetadata?.requiresGoalPoint ?? false)") + + // Set goal dimension based on model type + if modelMetadata?.modelType == .pointConditioned { + goalDimension = 3 // VQ-BeT models expect 3D coordinates + print("✅ Set goal dimension to 3D for point-conditioned model") + } else { + goalDimension = 2 // Standard models use 2D + print("✅ Set goal dimension to 2D for standard model") + } + + // Clear goal point if switching to non-point-conditioned model + if modelMetadata?.requiresGoalPoint == false { + currentGoalPoint = nil + } } catch { print("Failed to load active model: \(error)") model = nil + modelMetadata = nil } } @@ -122,6 +160,14 @@ class MLInferenceManager: ObservableObject { return modelManager.hasAvailableModel && model != nil } + var requiresGoalPoint: Bool { + return modelMetadata?.requiresGoalPoint ?? false + } + + var isPointConditioned: Bool { + return modelMetadata?.modelType == .pointConditioned + } + var activeModelName: String? { return modelManager.activeModel?.name } @@ -130,48 +176,401 @@ class MLInferenceManager: ObservableObject { return modelManager.hasCompiledModel } + // MARK: - Goal Point Management + func setGoalPoint(_ point: simd_float3) { + // Set goal point synchronously since UI needs immediate feedback + self.currentGoalPoint = point + print("Goal point set to: [\(point.x), \(point.y), \(point.z)]") + } + + func clearGoalPoint() { + currentGoalPoint = nil + odometryTracker.resetTracking() + print("Goal point cleared") + } + + // MARK: - Odometry Integration Methods + + /// Start odometry tracking with screen point (matching Python workflow) + func startOdometryTrackingWithScreenPoint( + screenPoint: CGPoint, + in view: UIView, + arFrame: ARFrame, + depthMap: CVPixelBuffer? + ) -> Bool { + guard enableOdometryTracking else { + print("Odometry tracking is disabled") + return false + } + + guard let session = getARSession() else { + print("Cannot start odometry tracking - no AR session available") + return false + } + + let success = odometryTracker.startTracking( + screenPoint: screenPoint, + in: view, + arFrame: arFrame, + session: session, + depthMap: depthMap + ) + + if success { + print("Started Python-style odometry tracking") + } else { + print("Failed to start odometry tracking") + } + + return success + } + + /// Update odometry tracking (step_n > 0 equivalent) + func updateOdometryTracking(arFrame: ARFrame) { + // Always update actual device pose for non-point-conditioned model deviation tracking + arVisualizationManager?.updateActualDevicePose(from: arFrame) + + guard enableOdometryTracking, + odometryTracker.trackingState == .tracking else { + return + } + + // Get updated odometry result and pass to visualization + if let odometryResult = odometryTracker.updateTracking(currentFrame: arFrame) { + // Update visualization with new target position from odometry + arVisualizationManager?.updateTargetFromOdometry(odometryResult) + print("📍 Updated visualization target from odometry") + } + } + + /// Set goal dimension (2D or 3D goal conditioning) + func setGoalDimension(_ dimension: Int) { + goalDimension = dimension + print("Goal conditioning set to \\(dimension)D mode") + } + + /// Get goal point for model input (2D or 3D based on goal_dim) + func getGoalPointForModel() -> [Float]? { + // Standardize 3D goals to labels.json frame from the CURRENT camera frame: [-x, z, y] + if goalDimension == 3 { + guard let session = getARSession(), let frame = session.currentFrame else { + return nil + } + // Prefer odometry-tracked world point; else use static world point if set + let worldPoint: simd_float3? + if enableOdometryTracking, let result = odometryTracker.currentResult { + worldPoint = result.world3DPoint + } else { + worldPoint = currentGoalPoint + } + guard let p_w = worldPoint else { return nil } + // World (ARKit) → Camera + let T_wc = frame.camera.transform + let T_cw = simd_inverse(T_wc) + let p_c4 = simd_mul(T_cw, simd_float4(p_w.x, p_w.y, p_w.z, 1.0)) + // labels.json mapping from camera frame + return [-p_c4.x, p_c4.z, p_c4.y] + } + // 2D goals: use odometry normalized 2D if available; else fallback to center + if enableOdometryTracking, let result = odometryTracker.currentResult { + return [Float(result.normalized2DPoint.x), Float(result.normalized2DPoint.y)] + } else { + return [0.5, 0.5] + } + } + + func convertScreenToWorld(_ screenPoint: CGPoint, in view: UIView, arSession: ARSession? = nil, depthMap: CVPixelBuffer? = nil) -> simd_float3? { + guard let session = arSession ?? getARSession(), + let currentFrame = session.currentFrame else { + print("No AR session or current frame available") + return nil + } + + // Method 1: Try hit testing first (most accurate for surfaces) + let normalizedPoint = CGPoint( + x: screenPoint.x / view.bounds.width, + y: screenPoint.y / view.bounds.height + ) + + // Create hit test query for existing planes or surfaces + let query = currentFrame.raycastQuery(from: normalizedPoint, allowing: .existingPlaneGeometry, alignment: .any) + let results = session.raycast(query) + if let result = results.first { + let worldTransform = result.worldTransform + return simd_float3(worldTransform.columns.3.x, worldTransform.columns.3.y, worldTransform.columns.3.z) + } + + // Method 2: Use depth map if available + if let depth = depthMap ?? currentFrame.sceneDepth?.depthMap { + if let worldPoint = convertScreenToWorldUsingDepth(screenPoint, in: view, frame: currentFrame, depthMap: depth) { + return worldPoint + } + } + + // Method 3: Fallback to estimated depth + return convertScreenToWorldEstimated(screenPoint, in: view, frame: currentFrame, estimatedDepth: 1.0) + } + + private func convertScreenToWorldUsingDepth(_ screenPoint: CGPoint, in view: UIView, frame: ARFrame, depthMap: CVPixelBuffer) -> simd_float3? { + // Convert screen point to depth map coordinates + let depthWidth = CVPixelBufferGetWidth(depthMap) + let depthHeight = CVPixelBufferGetHeight(depthMap) + + let normalizedX = screenPoint.x / view.bounds.width + let normalizedY = screenPoint.y / view.bounds.height + + let depthX = Int(normalizedX * CGFloat(depthWidth)) + let depthY = Int(normalizedY * CGFloat(depthHeight)) + + // Ensure coordinates are within bounds + guard depthX >= 0, depthX < depthWidth, depthY >= 0, depthY < depthHeight else { + return nil + } + + // Read depth value + CVPixelBufferLockBaseAddress(depthMap, .readOnly) + defer { CVPixelBufferUnlockBaseAddress(depthMap, .readOnly) } + + guard let baseAddress = CVPixelBufferGetBaseAddress(depthMap) else { return nil } + let bytesPerRow = CVPixelBufferGetBytesPerRow(depthMap) + let depthPointer = baseAddress.assumingMemoryBound(to: Float32.self) + + let pixelOffset = depthY * (bytesPerRow / MemoryLayout.stride) + depthX + let depth = depthPointer[pixelOffset] + + guard depth > 0.1 && depth < 10.0 else { // Valid depth range + return nil + } + + return convertScreenToWorldEstimated(screenPoint, in: view, frame: frame, estimatedDepth: depth) + } + + private func convertScreenToWorldEstimated(_ screenPoint: CGPoint, in view: UIView, frame: ARFrame, estimatedDepth: Float) -> simd_float3? { + let cameraIntrinsics = frame.camera.intrinsics + let cameraTransform = frame.camera.transform + + // Convert screen coordinates to normalized coordinates + let normalizedX = (screenPoint.x / view.bounds.width) * 2.0 - 1.0 + let normalizedY = 1.0 - (screenPoint.y / view.bounds.height) * 2.0 + + // Convert to camera space using inverse intrinsics + let fx = cameraIntrinsics.columns.0.x + let fy = cameraIntrinsics.columns.1.y + let cx = cameraIntrinsics.columns.2.x + let cy = cameraIntrinsics.columns.2.y + + let imageWidth = Float(view.bounds.width) + let imageHeight = Float(view.bounds.height) + + let cameraX = (Float(screenPoint.x) - cx) / fx * estimatedDepth + let cameraY = (Float(screenPoint.y) - cy) / fy * estimatedDepth + let cameraZ = -estimatedDepth // Negative Z in camera coordinates + + let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) + + // Transform to world coordinates + let worldPoint = simd_mul(cameraTransform, cameraPoint) + + return simd_float3(worldPoint.x, worldPoint.y, worldPoint.z) + } + + // MARK: - AR Session Access + weak var arViewContainer: ARViewModel? + + private func getARSession() -> ARSession? { + // Get ARSession from the connected ARViewContainer + return arViewContainer?.getARSession() + } + + func setARViewContainer(_ container: ARViewModel) { + self.arViewContainer = container + } + + // MARK: - USB Streaming Support + private func sendJointActionsToUSB(_ jointActions: [Float]) { + // Only send to USB if we're actually in USB streaming mode + // We can check this by seeing if the ARViewContainer has USB streaming active + arViewContainer?.sendJointActionsUSB(jointActions) + } + + + // MARK: - Inference Methods (Using existing frame processing patterns) + func performInference(on pixelBuffer: CVPixelBuffer, arFrame: ARFrame?, timestamp: CFTimeInterval = CACurrentMediaTime()) { + // Update odometry tracking SYNCHRONOUSLY if AR frame is provided + // This ensures the updated goal point is available for model input preparation + if let frame = arFrame { + updateOdometryTracking(arFrame: frame) + } + + performInference(on: pixelBuffer, timestamp: timestamp) + } + func performInference(on pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval = CACurrentMediaTime()) { guard isInferenceEnabled, - let model = model else { return } + let model = model, + let metadata = modelMetadata else { return } - let timeSinceLastInference = timestamp - lastInferenceTime - let requiredInterval = inferenceFrequency.interval + // Check if goal point is required but not set + if metadata.requiresGoalPoint && currentGoalPoint == nil { + return // Skip inference until goal point is set + } - if timeSinceLastInference < requiredInterval { + if timestamp - lastInferenceTime < inferenceFrequency.interval { return } lastInferenceTime = timestamp - // Process frame synchronously to avoid CVPixelBuffer sendable issues - let startTime = CACurrentMediaTime() + // Prepare input synchronously to avoid capturing non-sendable CVPixelBuffer + let modelInput: MLFeatureProvider + do { + modelInput = try prepareModelInput(pixelBuffer, metadata: metadata) + } catch { + print("Failed to prepare model input: \(error)") + return + } - autoreleasepool { - do { - let inputArray = try self.processFrameForInference(pixelBuffer) - - // Move to background queue after processing CVPixelBuffer - inferenceQueue.async { [weak self, inputArray, model, startTime] in - guard let self = self else { return } + inferenceQueue.async { [weak self, modelInput, model] in + guard let self = self else { return } + + let startTime = CACurrentMediaTime() + + autoreleasepool { + do { + let output = try model.prediction(from: modelInput) - do { - let input = try MLDictionaryFeatureProvider(dictionary: ["x_1": inputArray]) - let output = try model.prediction(from: input) - - let inferenceTime = CACurrentMediaTime() - startTime - self.processInferenceResults(output, inferenceTime: inferenceTime) - } catch { - print("Failed to perform ML inference: \(error)") - } + let inferenceTime = CACurrentMediaTime() - startTime + self.processInferenceResults(output, inferenceTime: inferenceTime) + } catch { + print("Failed to perform inference: \(error)") } - } catch { - print("Failed to process frame for inference: \(error)") } } } - // MARK: - Frame Processing (Leveraging ARViewContainer patterns) + // MARK: - Dynamic Input Preparation + private func prepareModelInput(_ pixelBuffer: CVPixelBuffer, metadata: ModelMetadata) throws -> MLFeatureProvider { + switch metadata.modelType { + case .pointConditioned: + return try prepareVQBeTInput(pixelBuffer, metadata: metadata) + case .standard: + return try prepareLegacyInput(pixelBuffer, metadata: metadata) + } + } + + private func prepareVQBeTInput(_ pixelBuffer: CVPixelBuffer, metadata: ModelMetadata) throws -> MLFeatureProvider { + guard let goalPointArray = getGoalPointForModel() else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Goal point required for point-conditioned model"]) + } + + // Get input names from metadata + let imageInputName = metadata.getImageInputName() ?? "camera_image" + let goalInputName = metadata.getGoalInputName() ?? "goal_point" + + // Process image + let imageArray = try processFrameForVQBeT(pixelBuffer, inputSize: metadata.imageInputSize ?? CGSize(width: 256, height: 256)) + + // Prepare goal point array with batch dimension [1, count] + let goalArray = try MLMultiArray(shape: [1, NSNumber(value: goalPointArray.count)], dataType: .float32) + for (index, value) in goalPointArray.enumerated() { + goalArray[[0, index] as [NSNumber]] = NSNumber(value: value) + } + + return try MLDictionaryFeatureProvider(dictionary: [ + imageInputName: MLFeatureValue(multiArray: imageArray), + goalInputName: MLFeatureValue(multiArray: goalArray) + ]) + } + + private func prepareLegacyInput(_ pixelBuffer: CVPixelBuffer, metadata: ModelMetadata) throws -> MLFeatureProvider { + // Simple approach matching old working code - no coordinate transformations + let inputArray = try processFrameForInference(pixelBuffer) + return try MLDictionaryFeatureProvider(dictionary: ["x_1": inputArray]) + } + + // MARK: - VQ-BeT Frame Processing + private func processFrameForVQBeT(_ pixelBuffer: CVPixelBuffer, inputSize: CGSize) throws -> MLMultiArray { + let width = Int(inputSize.width) + let height = Int(inputSize.height) + + // Create output pixel buffer + let attributes: [String: Any] = [ + kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32ARGB, + kCVPixelBufferWidthKey as String: width, + kCVPixelBufferHeightKey as String: height + ] + + var outputPixelBuffer: CVPixelBuffer? + let status = CVPixelBufferCreate( + kCFAllocatorDefault, + width, height, + kCVPixelFormatType_32ARGB, + attributes as CFDictionary, + &outputPixelBuffer + ) + + guard status == kCVReturnSuccess, let outputBuffer = outputPixelBuffer else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to create output pixel buffer"]) + } + + // Process image + CVPixelBufferLockBaseAddress(pixelBuffer, .readOnly) + CVPixelBufferLockBaseAddress(outputBuffer, []) + defer { + CVPixelBufferUnlockBaseAddress(outputBuffer, []) + CVPixelBufferUnlockBaseAddress(pixelBuffer, .readOnly) + } + + let inputImage = CIImage(cvPixelBuffer: pixelBuffer) + let inputImageSize = CGSize(width: CVPixelBufferGetWidth(pixelBuffer), height: CVPixelBufferGetHeight(pixelBuffer)) + let scaleX = inputSize.width / inputImageSize.width + let scaleY = inputSize.height / inputImageSize.height + let scaleTransform = CGAffineTransform(scaleX: scaleX, y: scaleY) + + let scaledImage = inputImage.transformed(by: scaleTransform) + let cropRect = CGRect(origin: .zero, size: inputSize) + + ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) + + // Convert to MLMultiArray for VQ-BeT format [1, 3, height, width] + return try convertPixelBufferToVQBeTArray(outputBuffer, width: width, height: height) + } + + private func convertPixelBufferToVQBeTArray(_ pixelBuffer: CVPixelBuffer, width: Int, height: Int) throws -> MLMultiArray { + let inputArray = try MLMultiArray(shape: [1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) + + guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get pixel buffer base address"]) + } + + let buffer = baseAddress.assumingMemoryBound(to: UInt8.self) + let bytesPerRow = CVPixelBufferGetBytesPerRow(pixelBuffer) + let bytesPerPixel = 4 + + for y in 0.. MLMultiArray { // Create output pixel buffer for model input size let attributes: [String: Any] = [ @@ -255,52 +654,106 @@ class MLInferenceManager: ObservableObject { // MARK: - Result Processing private func processInferenceResults(_ output: MLFeatureProvider, inferenceTime: TimeInterval) { - // Get the active model's metadata to understand its outputs - guard let metadata = modelManager.getActiveModelMetadata() else { + guard let metadata = modelMetadata else { print("Failed to get model metadata for output processing") return } - // Try to get the output using the primary output name, or fall back to any available output - let outputFeatureName = metadata.primaryOutputName ?? metadata.outputFeatureNames.first - - guard let outputFeatureName = outputFeatureName, - let resultArray = output.featureValue(for: outputFeatureName)?.multiArrayValue else { - print("Failed to get model output. Available outputs: \(output.featureNames)") - print("Expected output: \(metadata.outputFeatureNames)") - return - } - - // Extract values dynamically based on what the model outputs - let outputCount = min(resultArray.count, 10) // Cap at 10 to avoid huge arrays - let jointPositions = (0..= 6 { - arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) + guard let outputFeatureName = outputFeatureName, + let resultArray = output.featureValue(for: outputFeatureName)?.multiArrayValue else { + print("Failed to get model output. Available outputs: \(output.featureNames)") + return + } + + // Extract values directly (matching old code) + let outputCount = min(resultArray.count, 10) + let jointPositions = (0..= 6 { + arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) + } + + // Send joint actions to USB if streaming is enabled (transform to robot frame) + if jointPositions.count >= 7 { + let src = Array(jointPositions.prefix(7)) + let robot = ActionTransformUtils.toRobotActions(src) + print("USB send (robot actions): \(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))") + self?.sendJointActionsToUSB(robot) + } + } + + let positionString = jointPositions.map { String(format: "%.3f", $0) }.joined(separator: ", ") + let modelName = modelManager.activeModel?.name ?? "Unknown" + print("Model Output [\(modelName)] (Standard) (\(outputFeatureName)): [\(positionString)] - \(String(format: "%.1f", inferenceTime * 1000))ms") + + } else { + // Point-conditioned models - use existing complex logic + let outputFeatureName = metadata.primaryOutputName ?? output.featureNames.first + + guard let outputFeatureName = outputFeatureName, + let resultArray = output.featureValue(for: outputFeatureName)?.multiArrayValue else { + print("Failed to get model output. Available outputs: \(output.featureNames)") + print("Expected output: \(metadata.primaryOutputName ?? "Unknown")") + return + } + + // Extract values dynamically based on what the model outputs + let outputCount = min(resultArray.count, 10) + let jointPositions = (0..= 6 { + arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) + } + + // Send joint actions to USB if streaming is enabled (transform to robot frame) + if jointPositions.count >= 7 { + let src = Array(jointPositions.prefix(7)) + let robot = ActionTransformUtils.toRobotActions(src) + print("USB send (robot actions): \(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))") + self?.sendJointActionsToUSB(robot) + } + } + + let positionString = jointPositions.map { String(format: "%.3f", $0) }.joined(separator: ", ") + let modelName = modelManager.activeModel?.name ?? "Unknown" + let modelTypeStr = metadata.modelType.displayName + print("Model Output [\(modelName)] (\(modelTypeStr)) (\(outputFeatureName)): [\(positionString)] - \(String(format: "%.1f", inferenceTime * 1000))ms") + + // Log goal point status for point-conditioned models + if metadata.requiresGoalPoint, let goalPoint = currentGoalPoint { + print("Goal Point: [\(String(format: "%.3f", goalPoint.x)), \(String(format: "%.3f", goalPoint.y)), \(String(format: "%.3f", goalPoint.z))]") } } - - let positionString = jointPositions.map { String(format: "%.3f", $0) }.joined(separator: ", ") - let modelName = modelManager.activeModel?.name ?? "Unknown" - print("ML Model Output [\(modelName)] (\(outputFeatureName)): [\(positionString)] - \(String(format: "%.1f", inferenceTime * 1000))ms") - print("Joint actions ready for USB streaming: \(jointPositions.count) values") } // MARK: - Control Methods func enableInference() { isInferenceEnabled = true - // Reset timing to ensure immediate inference when enabled - lastInferenceTime = -Double.infinity let modelName = modelManager.activeModel?.name ?? "No model" print("Pick Up Policy enabled with model: \(modelName)") } @@ -312,14 +765,8 @@ class MLInferenceManager: ObservableObject { } func setInferenceFrequency(_ frequency: InferenceFrequency) { - let oldFrequency = inferenceFrequency inferenceFrequency = frequency - // Reset lastInferenceTime to allow immediate inference at new frequency - lastInferenceTime = -Double.infinity - print("🎚️ Frequency changed from \(oldFrequency.displayName) to \(frequency.displayName) - Interval: \(frequency.interval)s") - - // Automatically synchronize with AR visualization - synchronizeFrequencyWithVisualization() + print("Pick Up Policy frequency set to: \(frequency.displayName)") } // MARK: - Frequency Synchronization @@ -338,6 +785,25 @@ class MLInferenceManager: ObservableObject { } arVisualizationManager?.setVisualizationFrequency(correspondingVisualizationFrequency) - print("Synchronized ML inference (\(inferenceFrequency.displayName)) with AR arrow visualization (\(correspondingVisualizationFrequency.displayName))") + print("Synchronized ML inference (\(inferenceFrequency.displayName)) with AR visualization (\(correspondingVisualizationFrequency.displayName))") + } + + // MARK: - Odometry Integration Validation + func validateOdometryIntegration() -> Bool { + // Check if odometry tracking is properly set up + let hasTracker = odometryTracker != nil + let isEnabled = enableOdometryTracking + let hasARConnection = arViewContainer != nil + let hasVisualizationConnection = arVisualizationManager != nil + + let isValid = hasTracker && hasARConnection && hasVisualizationConnection + + print("Odometry Integration Validation:") + print(" - Tracker exists: \(hasTracker)") + print(" - AR Connection: \(hasARConnection)") + print(" - Visualization Connection: \(hasVisualizationConnection)") + print(" - Overall valid: \(isValid)") + + return isValid } } From c9e91ce9e5338ae37a32e175d38e5cc97e03dda8 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Sun, 31 Aug 2025 11:53:00 -0400 Subject: [PATCH 15/56] Remove EdgeTAM feature files and references from branch; keep ML-only pipeline --- AnySense/Managers/ARViewContainer.swift | 9 +- .../Managers/BoundaryTrackingManager.swift | 408 ---------- AnySense/Managers/EdgeTAMManager.swift | 753 ------------------ AnySense/Views/EdgeTAMStatusView.swift | 136 ---- .../Views/EdgeTAMVisualizationOverlay.swift | 364 --------- AnySense/Views/readView.swift | 9 +- 6 files changed, 5 insertions(+), 1674 deletions(-) delete mode 100644 AnySense/Managers/BoundaryTrackingManager.swift delete mode 100644 AnySense/Managers/EdgeTAMManager.swift delete mode 100644 AnySense/Views/EdgeTAMStatusView.swift delete mode 100644 AnySense/Views/EdgeTAMVisualizationOverlay.swift diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 843d651..bb24aff 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -84,8 +84,7 @@ class ARViewModel: ObservableObject{ // AR Visualization Manager for 3D pose visualization @Published var arVisualizationManager = ARVisualizationManager() - // EdgeTAM Manager for vision features extraction - @Published var edgeTAMManager = EdgeTAMManager() + public var userFPS: Double? public var isColorMapOpened = false @@ -435,8 +434,7 @@ class ARViewModel: ObservableObject{ // Perform ML inference on the RGB frame during streaming mlManager?.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) - // Process frame with EdgeTAM model (every 8th frame) - edgeTAMManager.processFrameIfNeeded(rgbPixelBuffer, timestamp: CACurrentMediaTime()) + // TODO: Check if we need to change this at all var depthPixelBuffer: CVPixelBuffer? = nil @@ -915,8 +913,7 @@ class ARViewModel: ObservableObject{ // Perform ML inference on the RGB frame mlManager?.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) - // Process frame with EdgeTAM model (every 8th frame) - edgeTAMManager.processFrameIfNeeded(rgbPixelBuffer, timestamp: CACurrentMediaTime()) + let cropRect = CGRect( x: 0, y: 0, width: self.viewPortSize.width, height: self.viewPortSize.height diff --git a/AnySense/Managers/BoundaryTrackingManager.swift b/AnySense/Managers/BoundaryTrackingManager.swift deleted file mode 100644 index d9e25c5..0000000 --- a/AnySense/Managers/BoundaryTrackingManager.swift +++ /dev/null @@ -1,408 +0,0 @@ -// -// BoundaryTrackingManager.swift -// AnySense -// -// Boundary-based point tracking for robust segmentation -// - -import Foundation -import UIKit -import CoreImage -import Vision - -// MARK: - Boundary Point -struct BoundaryPoint { - let x: CGFloat - let y: CGFloat - let timestamp: Date - - init(x: CGFloat, y: CGFloat) { - self.x = x - self.y = y - self.timestamp = Date() - } - - var cgPoint: CGPoint { - return CGPoint(x: x, y: y) - } -} - -// MARK: - Tracked Boundary -struct TrackedBoundary { - let originalPoint: CGPoint - var currentPoint: CGPoint - var boundaryPoints: [BoundaryPoint] - let creationTime: Date - var lastUpdateTime: Date - var updateCount: Int - - init(originalPoint: CGPoint) { - self.originalPoint = originalPoint - self.currentPoint = originalPoint - self.boundaryPoints = [] - self.creationTime = Date() - self.lastUpdateTime = Date() - self.updateCount = 0 - } - - mutating func updateBoundary(points: [BoundaryPoint], newPoint: CGPoint) { - self.boundaryPoints = points - self.currentPoint = newPoint - self.lastUpdateTime = Date() - self.updateCount += 1 - } -} - -// MARK: - Boundary Tracking Manager -class BoundaryTrackingManager: ObservableObject { - - @Published var trackedBoundaries: [TrackedBoundary] = [] - @Published var isTracking: Bool = false - @Published var displayBoundaries: [TrackedBoundary] = [] // Only updated every 8 frames for display - - private let ciContext = CIContext() - - // MARK: - Boundary Extraction - func extractBoundaryPoints(from maskImage: UIImage) -> [BoundaryPoint] { - guard let cgImage = maskImage.cgImage else { - print("Could not get CGImage from mask") - return [] - } - - let width = cgImage.width - let height = cgImage.height - print("Mask image size: \(width)x\(height)") - - // EdgeTAM masks are 256x256 but model coordinates are 1024x1024 - // We need to scale boundary points by 4x to match model coordinate space - let scaleX: CGFloat = 1024.0 / CGFloat(width) - let scaleY: CGFloat = 1024.0 / CGFloat(height) - - // Convert image to grayscale pixel data - guard let pixelData = getPixelData(from: cgImage) else { - print("Could not extract pixel data") - return [] - } - - // Debug: Check pixel value distribution - let sampleSize = min(1000, pixelData.count) - let samplePixels = Array(pixelData.prefix(sampleSize)) - let nonZeroPixels = samplePixels.filter { $0 > 0 }.count - let maxPixel = samplePixels.max() ?? 0 - let minPixel = samplePixels.min() ?? 0 - print("Pixel analysis: \(nonZeroPixels)/\(sampleSize) non-zero, range: \(minPixel)-\(maxPixel)") - - var boundaryPoints: [BoundaryPoint] = [] - var maskPixelCount = 0 - - // Use a lower threshold since the mask might have different values - let threshold: UInt8 = 50 - - // Scan for boundary pixels (edge detection) - for y in 1..<(height-1) { - for x in 1..<(width-1) { - let currentIndex = y * width + x - let currentPixel = pixelData[currentIndex] - - // Count mask pixels - if currentPixel > threshold { - maskPixelCount += 1 - } - - // If current pixel is part of mask (above threshold) - if currentPixel > threshold { - // Check if it's a boundary pixel by examining neighbors - let neighbors = [ - pixelData[(y-1) * width + x], // top - pixelData[(y+1) * width + x], // bottom - pixelData[y * width + (x-1)], // left - pixelData[y * width + (x+1)], // right - ] - - // If any neighbor is background (below threshold), this is a boundary pixel - if neighbors.contains(where: { $0 <= threshold }) { - let boundaryPoint = BoundaryPoint( - x: CGFloat(x) * scaleX, // Scale to model coordinate space - y: CGFloat(y) * scaleY - ) - boundaryPoints.append(boundaryPoint) - } - } - } - } - - print("Mask analysis: \(maskPixelCount) mask pixels, \(boundaryPoints.count) boundary points") - - // If we still have no boundary points, try a more aggressive approach - if boundaryPoints.isEmpty && maskPixelCount > 0 { - print("Warning: No boundaries found with threshold \(threshold), trying aggressive detection...") - boundaryPoints = extractBoundaryPointsAggressive(from: pixelData, width: width, height: height, scaleX: scaleX, scaleY: scaleY) - } - - return boundaryPoints - } - - // More aggressive boundary detection - private func extractBoundaryPointsAggressive(from pixelData: [UInt8], width: Int, height: Int, scaleX: CGFloat, scaleY: CGFloat) -> [BoundaryPoint] { - var boundaryPoints: [BoundaryPoint] = [] - - // Find any non-zero pixels and treat edges as boundaries - for y in 1..<(height-1) { - for x in 1..<(width-1) { - let currentIndex = y * width + x - let currentPixel = pixelData[currentIndex] - - // If current pixel has any value - if currentPixel > 10 { - // Check 8-connected neighbors - let neighbors = [ - pixelData[(y-1) * width + (x-1)], // top-left - pixelData[(y-1) * width + x], // top - pixelData[(y-1) * width + (x+1)], // top-right - pixelData[y * width + (x-1)], // left - pixelData[y * width + (x+1)], // right - pixelData[(y+1) * width + (x-1)], // bottom-left - pixelData[(y+1) * width + x], // bottom - pixelData[(y+1) * width + (x+1)] // bottom-right - ] - - // If any neighbor is much different, this is a boundary - let avgNeighbor = neighbors.reduce(0, +) / UInt8(neighbors.count) - if abs(Int(currentPixel) - Int(avgNeighbor)) > 20 { - boundaryPoints.append(BoundaryPoint( - x: CGFloat(x) * scaleX, // Scale to model coordinate space - y: CGFloat(y) * scaleY - )) - } - } - } - } - - print("Aggressive extraction found \(boundaryPoints.count) boundary points") - return boundaryPoints - } - - // MARK: - Point Update Strategy - func updateTrackingPoint(for boundary: TrackedBoundary) -> CGPoint { - guard !boundary.boundaryPoints.isEmpty else { - print("Warning: No boundary points available, keeping original point") - return boundary.currentPoint - } - - // Find the closest boundary points to the current tracking point - let sortedByDistance = boundary.boundaryPoints.sorted { point1, point2 in - let dist1 = distanceSquared(from: boundary.currentPoint, to: point1.cgPoint) - let dist2 = distanceSquared(from: boundary.currentPoint, to: point2.cgPoint) - return dist1 < dist2 - } - - // Sample up to 5 closest boundary points - let sampleSize = min(5, sortedByDistance.count) - let sampledPoints = Array(sortedByDistance.prefix(sampleSize)) - - return sampleBoundaryPoints(from: sampledPoints) - } - - // Helper function to calculate distance squared (faster than sqrt) - private func distanceSquared(from point1: CGPoint, to point2: CGPoint) -> CGFloat { - let dx = point1.x - point2.x - let dy = point1.y - point2.y - return dx * dx + dy * dy - } - - private func sampleBoundaryPoints(from points: [BoundaryPoint]) -> CGPoint { - guard !points.isEmpty else { return .zero } - - // Calculate centroid of sampled boundary points - let totalX = points.reduce(0) { $0 + $1.x } - let totalY = points.reduce(0) { $0 + $1.y } - - let centroidX = totalX / CGFloat(points.count) - let centroidY = totalY / CGFloat(points.count) - - print("Updated point from \(points.count) boundary samples to (\(Int(centroidX)), \(Int(centroidY)))") - - return CGPoint(x: centroidX, y: centroidY) - } - - // MARK: - Tracking Management - func startTracking(initialPoint: CGPoint, maskImage: UIImage) { - var newBoundary = TrackedBoundary(originalPoint: initialPoint) - - // Debug: Save mask image to understand what we're working with - saveMaskImageForDebugging(maskImage, prefix: "initial") - - // Extract initial boundary - let boundaryPoints = extractBoundaryPoints(from: maskImage) - newBoundary.updateBoundary(points: boundaryPoints, newPoint: initialPoint) - - trackedBoundaries.append(newBoundary) - isTracking = true - - print("Started boundary tracking for point (\(Int(initialPoint.x)), \(Int(initialPoint.y)))") - } - - func startMultiPointTracking(initialPoints: [CGPoint], maskImage: UIImage) { - // Clear any existing tracking - trackedBoundaries.removeAll() - - // Debug: Save mask image to understand what we're working with - saveMaskImageForDebugging(maskImage, prefix: "multipoint_initial") - - // Extract boundary points once for all points to track - let boundaryPoints = extractBoundaryPoints(from: maskImage) - - // Create a tracked boundary for each initial point - for (index, initialPoint) in initialPoints.enumerated() { - var newBoundary = TrackedBoundary(originalPoint: initialPoint) - newBoundary.updateBoundary(points: boundaryPoints, newPoint: initialPoint) - trackedBoundaries.append(newBoundary) - - print("Started tracking point \(index + 1): (\(Int(initialPoint.x)), \(Int(initialPoint.y)))") - } - - isTracking = true - print("Started multi-point boundary tracking for \(initialPoints.count) points") - } - - // Debug helper to analyze mask images - private func saveMaskImageForDebugging(_ image: UIImage, prefix: String) { - print("\(prefix) mask image info: size=\(image.size), scale=\(image.scale)") - - // Analyze a small sample of the image - if let cgImage = image.cgImage, - let pixelData = getPixelData(from: cgImage) { - - let width = cgImage.width - let height = cgImage.height - let totalPixels = width * height - - // Count different pixel value ranges - var zeroPixels = 0 - var lowPixels = 0 // 1-50 - var mediumPixels = 0 // 51-200 - var highPixels = 0 // 201-255 - - for pixel in pixelData { - switch pixel { - case 0: zeroPixels += 1 - case 1...50: lowPixels += 1 - case 51...200: mediumPixels += 1 - case 201...255: highPixels += 1 - default: break - } - } - - print("\(prefix) pixel distribution:") - print(" - Zero (0): \(zeroPixels)/\(totalPixels) (\(Int(Double(zeroPixels)/Double(totalPixels)*100))%)") - print(" - Low (1-50): \(lowPixels)/\(totalPixels) (\(Int(Double(lowPixels)/Double(totalPixels)*100))%)") - print(" - Medium (51-200): \(mediumPixels)/\(totalPixels) (\(Int(Double(mediumPixels)/Double(totalPixels)*100))%)") - print(" - High (201-255): \(highPixels)/\(totalPixels) (\(Int(Double(highPixels)/Double(totalPixels)*100))%)") - } - } - - func updateAllBoundaries(with maskImage: UIImage, shouldUpdateDisplay: Bool = false) { - guard isTracking && !trackedBoundaries.isEmpty else { return } - - // Extract new boundary points from current mask - let newBoundaryPoints = extractBoundaryPoints(from: maskImage) - - for i in trackedBoundaries.indices { - // Update boundary points - trackedBoundaries[i].updateBoundary( - points: newBoundaryPoints, - newPoint: updateTrackingPoint(for: trackedBoundaries[i]) - ) - } - - // Only update display boundaries every 8 frames (when segmentation runs) - if shouldUpdateDisplay { - DispatchQueue.main.async { [weak self] in - self?.displayBoundaries = self?.trackedBoundaries ?? [] - } - print("Updated \(trackedBoundaries.count) tracked boundaries + display") - } else { - print("Updated \(trackedBoundaries.count) tracked boundaries (internal only)") - } - } - - func stopTracking() { - isTracking = false - trackedBoundaries.removeAll() - displayBoundaries.removeAll() - print("Stopped boundary tracking") - } - - func clearAllBoundaries() { - trackedBoundaries.removeAll() - displayBoundaries.removeAll() - print("Cleared all tracked boundaries") - } - - // MARK: - Utility Functions - private func getPixelData(from cgImage: CGImage) -> [UInt8]? { - let width = cgImage.width - let height = cgImage.height - let bytesPerPixel = 1 // Grayscale - let bytesPerRow = width * bytesPerPixel - let totalBytes = height * bytesPerRow - - var pixelData = [UInt8](repeating: 0, count: totalBytes) - - let colorSpace = CGColorSpaceCreateDeviceGray() - let context = CGContext( - data: &pixelData, - width: width, - height: height, - bitsPerComponent: 8, - bytesPerRow: bytesPerRow, - space: colorSpace, - bitmapInfo: CGImageAlphaInfo.none.rawValue - ) - - guard let ctx = context else { - print("Could not create CGContext") - return nil - } - - ctx.draw(cgImage, in: CGRect(x: 0, y: 0, width: width, height: height)) - - return pixelData - } - - // MARK: - Debug Information - var trackingStatistics: String { - if trackedBoundaries.isEmpty { - return "No active boundaries" - } - - let totalUpdates = trackedBoundaries.reduce(0) { $0 + $1.updateCount } - let avgBoundaryPoints = trackedBoundaries.isEmpty ? 0 : - trackedBoundaries.reduce(0) { $0 + $1.boundaryPoints.count } / trackedBoundaries.count - - return """ - Boundaries: \(trackedBoundaries.count) - Total Updates: \(totalUpdates) - Avg Boundary Points: \(avgBoundaryPoints) - """ - } -} - -// MARK: - Extensions -extension BoundaryTrackingManager { - - // Get current tracking points for segmentation (internal, always up to date) - var currentTrackingPoints: [CGPoint] { - return trackedBoundaries.map { $0.currentPoint } - } - - // Get display tracking points for UI (only updated every 8 frames) - var displayTrackingPoints: [CGPoint] { - return displayBoundaries.map { $0.currentPoint } - } - - // Get the most recently updated boundary - var latestBoundary: TrackedBoundary? { - return trackedBoundaries.max { $0.lastUpdateTime < $1.lastUpdateTime } - } -} \ No newline at end of file diff --git a/AnySense/Managers/EdgeTAMManager.swift b/AnySense/Managers/EdgeTAMManager.swift deleted file mode 100644 index 1e762d9..0000000 --- a/AnySense/Managers/EdgeTAMManager.swift +++ /dev/null @@ -1,753 +0,0 @@ -// -// EdgeTAMManager.swift -// AnySense -// -// Updated EdgeTAM model integration with full segmentation pipeline -// - -import Foundation -@preconcurrency import CoreML -import Vision -import CoreVideo -import CoreImage -import UIKit - -// MARK: - Prompt Types -struct EdgeTAMPrompt { - var points: [(CGPoint, Bool)] = [] // (point, isPositive) - var boxes: [CGRect] = [] - var maskInput: UIImage? -} - -class EdgeTAMManager: ObservableObject { - // MARK: - Properties - private var imageEncoder: MLModel? - private var promptEncoder: MLModel? - private var maskDecoder: MLModel? - private let ciContext = CIContext() - private var frameCounter: Int = 0 - private let frameInterval: Int = 30 // Process every 30th frame - - @Published var isProcessing: Bool = false - @Published var latestFeatures: MLMultiArray? - @Published var latestHighResFeats: (MLMultiArray?, MLMultiArray?) = (nil, nil) - @Published var processingTime: TimeInterval = 0 - @Published var processedFrameCount: Int = 0 - @Published var isModelLoaded: Bool = false - @Published var latestSegmentationMask: UIImage? - @Published var currentPrompt: EdgeTAMPrompt = EdgeTAMPrompt() - - // Multi-point tracking: Green points (original) and Red points (tracked) - @Published var originalPoints: [CGPoint] = [] // Green points - user input, never move - - // Boundary tracking integration - private var boundaryTrackingManager = BoundaryTrackingManager() - - // Model input requirements - private let modelInputSize = CGSize(width: 1024, height: 1024) - - // Processing queue - private let processingQueue = DispatchQueue(label: "EdgeTAMProcessingQueue", qos: .userInitiated) - - // MARK: - Initialization - init() { - loadEdgeTAMModel() - } - - // MARK: - Model Loading - private func loadEdgeTAMModel() { - loadAllModels() - } - - private func loadAllModels() { - var modelsLoaded = 0 - let totalModels = 3 - - // Load Image Encoder - if let imageEncoderURL = Bundle.main.url(forResource: "edgetam_image_encoder", withExtension: "mlmodelc") { - do { - imageEncoder = try MLModel(contentsOf: imageEncoderURL) - print("EdgeTAM Image Encoder loaded") - modelsLoaded += 1 - } catch { - print("Failed to load EdgeTAM Image Encoder: \(error)") - } - } else { - print("EdgeTAM Image Encoder not found") - } - - // Load Prompt Encoder - if let promptEncoderURL = Bundle.main.url(forResource: "edgetam_prompt_encoder", withExtension: "mlmodelc") { - do { - promptEncoder = try MLModel(contentsOf: promptEncoderURL) - print("EdgeTAM Prompt Encoder loaded") - modelsLoaded += 1 - } catch { - print("Failed to load EdgeTAM Prompt Encoder: \(error)") - } - } else { - print("EdgeTAM Prompt Encoder not found") - } - - // Load Mask Decoder - if let maskDecoderURL = Bundle.main.url(forResource: "edgetam_mask_decoder", withExtension: "mlmodelc") { - do { - maskDecoder = try MLModel(contentsOf: maskDecoderURL) - print("EdgeTAM Mask Decoder loaded") - modelsLoaded += 1 - } catch { - print("Failed to load EdgeTAM Mask Decoder: \(error)") - } - } else { - print("EdgeTAM Mask Decoder not found") - } - - DispatchQueue.main.async { - self.isModelLoaded = (modelsLoaded == totalModels) - if self.isModelLoaded { - print("All EdgeTAM models loaded successfully") - } else { - print("Warning: Only \(modelsLoaded)/\(totalModels) EdgeTAM models loaded") - } - } - } - - // MARK: - Frame Processing - func processFrameIfNeeded(_ pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval) { - frameCounter += 1 - - // Only process every nth frame - guard frameCounter % frameInterval == 0 else { return } - - // Skip if already processing - guard !isProcessing else { return } - - processingQueue.async { @Sendable [weak self] in - self?.processFrame(pixelBuffer, timestamp: timestamp) - } - } - - private func processFrame(_ pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval) { - guard let imageEncoderModel = imageEncoder else { - print("EdgeTAM image encoder not loaded") - return - } - - DispatchQueue.main.async { - self.isProcessing = true - } - - let startTime = CACurrentMediaTime() - - do { - // Prepare the pixel buffer for the model - let preparedPixelBuffer = try preparePixelBufferForModel(pixelBuffer) - - // Create input for the image encoder - let input = try MLDictionaryFeatureProvider(dictionary: ["image": preparedPixelBuffer]) - - // Run image encoder inference - let output = try imageEncoderModel.prediction(from: input) - - // Extract features - let visionFeatures = output.featureValue(for: "vision_features")?.multiArrayValue - let highResFeat0 = output.featureValue(for: "high_res_feat_0")?.multiArrayValue - let highResFeat1 = output.featureValue(for: "high_res_feat_1")?.multiArrayValue - - let processingTime = CACurrentMediaTime() - startTime - - // Generate segmentation mask if we have prompts - var segmentationMask: UIImage? - - if !currentPrompt.points.isEmpty { - // Run full segmentation pipeline - segmentationMask = runSegmentationPipeline( - visionFeatures: visionFeatures, - highResFeat0: highResFeat0, - highResFeat1: highResFeat1, - prompt: currentPrompt - ) - - // Update boundary tracking if we have a mask - // Since this runs every 8 frames, update display as well - if let mask = segmentationMask { - updateBoundaryTracking(with: mask, shouldUpdateDisplay: true) - } - } - - DispatchQueue.main.async { - self.latestFeatures = visionFeatures - self.latestHighResFeats = (highResFeat0, highResFeat1) - self.processingTime = processingTime - self.isProcessing = false - self.processedFrameCount += 1 - self.latestSegmentationMask = segmentationMask - } - - print("EdgeTAM processed frame \(self.frameCounter) - Time: \(String(format: "%.1f", processingTime * 1000))ms") - - } catch { - print("EdgeTAM processing error: \(error)") - DispatchQueue.main.async { - self.isProcessing = false - } - } - } - - // MARK: - Segmentation Pipeline - private func runSegmentationPipeline( - visionFeatures: MLMultiArray?, - highResFeat0: MLMultiArray?, - highResFeat1: MLMultiArray?, - prompt: EdgeTAMPrompt - ) -> UIImage? { - print("Starting segmentation pipeline...") - print(" Prompt points: \(prompt.points.count)") - print(" Prompt boxes: \(prompt.boxes.count)") - - guard let promptEncoderModel = promptEncoder, - let maskDecoderModel = maskDecoder, - let visionFeatures = visionFeatures, - let highResFeat0 = highResFeat0, - let highResFeat1 = highResFeat1 else { - print("Segmentation pipeline: Missing models or features") - print(" promptEncoder: \(promptEncoder != nil)") - print(" maskDecoder: \(maskDecoder != nil)") - print(" visionFeatures: \(visionFeatures != nil)") - print(" highResFeat0: \(highResFeat0 != nil)") - print(" highResFeat1: \(highResFeat1 != nil)") - return nil - } - - print("All models and features available") - - do { - // Prepare prompt inputs - print("Preparing prompt inputs...") - let promptInputs = try preparePromptInputs(prompt: prompt) - - // Run prompt encoder - print("Running prompt encoder...") - let promptEncoderOutput = try promptEncoderModel.prediction(from: promptInputs) - - guard let sparseEmbeddings = promptEncoderOutput.featureValue(for: "sparse_embeddings")?.multiArrayValue, - let denseEmbeddings = promptEncoderOutput.featureValue(for: "dense_embeddings")?.multiArrayValue else { - print("Failed to get prompt embeddings") - print(" Available outputs: \(promptEncoderOutput.featureNames)") - return nil - } - - print("Got prompt embeddings - sparse: \(sparseEmbeddings.shape), dense: \(denseEmbeddings.shape)") - - // Create positional encoding (simplified - zeros for now) - let imagePE = try createZeroArray(shape: visionFeatures.shape) - - // Prepare mask decoder inputs - print("Preparing mask decoder inputs...") - let maskDecoderInputs = try MLDictionaryFeatureProvider(dictionary: [ - "image_embeddings": visionFeatures, - "image_pe": imagePE, - "sparse_prompt_embeddings": sparseEmbeddings, - "dense_prompt_embeddings": denseEmbeddings, - "high_res_feat_0": highResFeat0, - "high_res_feat_1": highResFeat1, - "multimask_output": try createSingleValueArray(value: 1.0) // true - ]) - - // Run mask decoder - print("Running mask decoder...") - let maskDecoderOutput = try maskDecoderModel.prediction(from: maskDecoderInputs) - - print("Mask decoder completed") - print(" Available outputs: \(maskDecoderOutput.featureNames)") - - if let masks = maskDecoderOutput.featureValue(for: "masks")?.multiArrayValue, - let iouScores = maskDecoderOutput.featureValue(for: "iou_pred")?.multiArrayValue { - print("Got masks and IoU scores") - // Get best mask based on IoU score - return createSegmentationMask(from: masks, iouScores: iouScores) - } else { - print("Failed to extract masks or IoU scores from decoder output") - } - - } catch { - print("Segmentation pipeline error: \(error)") - } - - print("Segmentation pipeline failed - returning nil") - return nil - } - - private func preparePromptInputs(prompt: EdgeTAMPrompt) throws -> MLDictionaryFeatureProvider { - // Create arrays for prompt inputs - let maxPoints = 4 - let pointCoords = try MLMultiArray(shape: [1, NSNumber(value: maxPoints), 2], dataType: .float32) - let pointLabels = try MLMultiArray(shape: [1, NSNumber(value: maxPoints)], dataType: .float32) - let boxes = try MLMultiArray(shape: [1, 4], dataType: .float32) - let maskInput = try MLMultiArray(shape: [1, 1, 256, 256], dataType: .float32) - - // Initialize with default values - for i in 0.. MLMultiArray { - let array = try MLMultiArray(shape: shape, dataType: .float32) - let count = array.count - let pointer = array.dataPointer.bindMemory(to: Float32.self, capacity: count) - for i in 0.. MLMultiArray { - let array = try MLMultiArray(shape: [1], dataType: .float32) - array[0] = NSNumber(value: value) - return array - } - - private func createSegmentationMask(from masks: MLMultiArray, iouScores: MLMultiArray) -> UIImage? { - // masks shape: [1, 3, 256, 256] (3 masks generated) - // iouScores shape: [1, 3] - - print("Creating segmentation mask from MLMultiArray") - print(" Masks shape: \(masks.shape)") - print(" IoU scores shape: \(iouScores.shape)") - - // Find best mask based on IoU score - var bestMaskIndex = 0 - var bestScore: Float = 0 - - for i in 0..<3 { - let score = iouScores[[0, NSNumber(value: i)]].floatValue - print(" Mask \(i) IoU score: \(score)") - if score > bestScore { - bestScore = score - bestMaskIndex = i - } - } - - print(" Selected mask \(bestMaskIndex) with score \(bestScore)") - - // Sample some mask values to understand the data - var sampleValues: [Float] = [] - for i in 0.. 0.5 { - foregroundPixels += 1 - // Foreground - bright cyan - pixelData[pixelIndex] = 0 // Red - pixelData[pixelIndex + 1] = 255 // Green - pixelData[pixelIndex + 2] = 255 // Blue - pixelData[pixelIndex + 3] = UInt8(min(255, Int(probability * 180))) // Alpha - } else { - // Background - transparent - pixelData[pixelIndex] = 0 - pixelData[pixelIndex + 1] = 0 - pixelData[pixelIndex + 2] = 0 - pixelData[pixelIndex + 3] = 0 - } - } - } - - print(" Generated mask: \(foregroundPixels)/\(width*height) foreground pixels (\(Int(Double(foregroundPixels)/Double(width*height)*100))%)") - - guard let dataProvider = CGDataProvider(data: Data(pixelData) as CFData), - let cgImage = CGImage(width: width, - height: height, - bitsPerComponent: 8, - bitsPerPixel: 32, - bytesPerRow: bytesPerRow, - space: colorSpace, - bitmapInfo: [.byteOrder32Little, CGBitmapInfo(rawValue: CGImageAlphaInfo.premultipliedFirst.rawValue)], - provider: dataProvider, - decode: nil, - shouldInterpolate: false, - intent: .defaultIntent) else { - print("Failed to create CGImage from mask data") - return nil - } - - print("Successfully created segmentation mask UIImage") - return UIImage(cgImage: cgImage) - } - - // MARK: - Pixel Buffer Preparation - private func preparePixelBufferForModel(_ inputPixelBuffer: CVPixelBuffer) throws -> CVPixelBuffer { - // Create output pixel buffer for model input size (1024x1024) - let attributes: [String: Any] = [ - kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32ARGB, - kCVPixelBufferWidthKey as String: Int(modelInputSize.width), - kCVPixelBufferHeightKey as String: Int(modelInputSize.height), - kCVPixelBufferIOSurfacePropertiesKey as String: [:] - ] - - var outputPixelBuffer: CVPixelBuffer? - let status = CVPixelBufferCreate( - kCFAllocatorDefault, - Int(modelInputSize.width), - Int(modelInputSize.height), - kCVPixelFormatType_32ARGB, - attributes as CFDictionary, - &outputPixelBuffer - ) - - guard status == kCVReturnSuccess, let outputBuffer = outputPixelBuffer else { - throw NSError(domain: "EdgeTAMManager", code: -1, - userInfo: [NSLocalizedDescriptionKey: "Failed to create output pixel buffer"]) - } - - // Use Core Image to resize and process the frame - CVPixelBufferLockBaseAddress(inputPixelBuffer, .readOnly) - CVPixelBufferLockBaseAddress(outputBuffer, []) - defer { - CVPixelBufferUnlockBaseAddress(outputBuffer, []) - CVPixelBufferUnlockBaseAddress(inputPixelBuffer, .readOnly) - } - - let inputImage = CIImage(cvPixelBuffer: inputPixelBuffer) - - // Calculate scale to fit the model input size - let inputSize = CGSize( - width: CVPixelBufferGetWidth(inputPixelBuffer), - height: CVPixelBufferGetHeight(inputPixelBuffer) - ) - - let scaleX = modelInputSize.width / inputSize.width - let scaleY = modelInputSize.height / inputSize.height - let scale = min(scaleX, scaleY) // Maintain aspect ratio - - // Create transform to scale and center the image - let scaledWidth = inputSize.width * scale - let scaledHeight = inputSize.height * scale - let xOffset = (modelInputSize.width - scaledWidth) / 2 - let yOffset = (modelInputSize.height - scaledHeight) / 2 - - let transform = CGAffineTransform(scaleX: scale, y: scale) - .translatedBy(x: xOffset / scale, y: yOffset / scale) - - let scaledImage = inputImage.transformed(by: transform) - - // Render to output buffer - ciContext.render(scaledImage, to: outputBuffer) - - return outputBuffer - } - - - // MARK: - Boundary Tracking Methods - private func updateBoundaryTracking(with maskImage: UIImage, shouldUpdateDisplay: Bool = false) { - // Start or restart tracking when we have points to track - if !originalPoints.isEmpty { - if !boundaryTrackingManager.isTracking { - // Start tracking with multiple points - boundaryTrackingManager.startMultiPointTracking(initialPoints: originalPoints, maskImage: maskImage) - } else { - // Update existing tracking - boundaryTrackingManager.updateAllBoundaries(with: maskImage, shouldUpdateDisplay: shouldUpdateDisplay) - } - - // Update current prompt with tracked points for next segmentation - updatePromptWithTrackedPoints() - } - } - - private func updatePromptWithTrackedPoints() { - let trackedPoints = boundaryTrackingManager.currentTrackingPoints - - if !trackedPoints.isEmpty { - // Update the first point with the tracked position, keep others as positive - currentPrompt.points = trackedPoints.enumerated().map { index, point in - (point, true) // All tracked points are positive - } - - print("Updated prompt with \(trackedPoints.count) tracked points") - } - } - - func startBoundaryTracking() { - guard !currentPrompt.points.isEmpty else { - print("Warning: Cannot start boundary tracking without prompt points") - return - } - - // Boundary tracking will start automatically on next segmentation - print("Boundary tracking ready - will start on next segmentation") - } - - func stopBoundaryTracking() { - boundaryTrackingManager.stopTracking() - print("Stopped boundary tracking") - } - - var boundaryTrackingStatistics: String { - return boundaryTrackingManager.trackingStatistics - } - - var isBoundaryTracking: Bool { - return boundaryTrackingManager.isTracking - } - - // Get display points for UI (updated every 8 frames) - var displayTrackingPoints: [CGPoint] { - return boundaryTrackingManager.displayTrackingPoints - } - - // MARK: - Public Methods - func reset() { - frameCounter = 0 - latestFeatures = nil - latestHighResFeats = (nil, nil) - processingTime = 0 - isProcessing = false - processedFrameCount = 0 - latestSegmentationMask = nil - currentPrompt = EdgeTAMPrompt() - boundaryTrackingManager.stopTracking() - } - - func generateMaskForTrackedObject(prompt: EdgeTAMPrompt) async -> UIImage? { - guard let visionFeatures = latestFeatures, - let highResFeat0 = latestHighResFeats.0, - let highResFeat1 = latestHighResFeats.1 else { - print("No features available for mask generation") - return nil - } - - return await withCheckedContinuation { continuation in - processingQueue.async { @Sendable [weak self] in - let mask = self?.runSegmentationPipeline( - visionFeatures: visionFeatures, - highResFeat0: highResFeat0, - highResFeat1: highResFeat1, - prompt: prompt - ) - continuation.resume(returning: mask) - } - } - } - - func processFrameForTracking(_ pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval) { - // Process frame and also notify object tracking manager - processFrameIfNeeded(pixelBuffer, timestamp: timestamp) - - // Frame processing completed - } - - private func pixelBufferToUIImage(_ pixelBuffer: CVPixelBuffer) -> UIImage? { - let ciImage = CIImage(cvPixelBuffer: pixelBuffer) - guard let cgImage = ciContext.createCGImage(ciImage, from: ciImage.extent) else { - return nil - } - return UIImage(cgImage: cgImage) - } - - // MARK: - Prompt Handling - func addPromptPoint(_ point: CGPoint, isPositive: Bool = true) { - // Convert screen coordinates to model coordinates (1024x1024) - let modelPoint = CGPoint(x: point.x * modelInputSize.width, y: point.y * modelInputSize.height) - currentPrompt.points.append((modelPoint, isPositive)) - - print("Added prompt point: (\(Int(modelPoint.x)), \(Int(modelPoint.y))) - \(isPositive ? "Positive" : "Negative")") - } - - func addPromptPointWithConstraints(_ normalizedPoint: CGPoint, screenPoint: CGPoint, screenSize: CGSize) -> Bool { - // Check constraint 1: Maximum 4 points - guard currentPrompt.points.count < 4 else { - print("Point rejected: Maximum 4 points allowed") - return false - } - - // Check constraint 2: Minimum distance of 0.5 screen units from existing points - let minimumDistance: CGFloat = 0.5 - for existingPoint in originalPoints { - let existingScreenPoint = convertModelPointToScreen(existingPoint, screenSize: screenSize) - let distance = sqrt(pow(screenPoint.x - existingScreenPoint.x, 2) + pow(screenPoint.y - existingScreenPoint.y, 2)) - - if distance < minimumDistance { - print("Point rejected: Too close to existing point (distance: \(Int(distance)) < \(Int(minimumDistance)))") - return false - } - } - - // Check constraint 3: Point must be within current segmentation mask (if one exists) - if let maskImage = latestSegmentationMask { - if !isPointWithinMask(normalizedPoint, mask: maskImage) { - print("Point rejected: Outside current segmentation mask") - return false - } - } - - // All constraints passed - add the point - let modelPoint = CGPoint(x: normalizedPoint.x * modelInputSize.width, y: normalizedPoint.y * modelInputSize.height) - - // Only positive points allowed now - currentPrompt.points.append((modelPoint, true)) - originalPoints.append(modelPoint) - - print("Added point: (\(Int(modelPoint.x)), \(Int(modelPoint.y))) - Total: \(currentPrompt.points.count)") - - return true - } - - // Helper to convert model coordinates back to screen coordinates - private func convertModelPointToScreen(_ modelPoint: CGPoint, screenSize: CGSize) -> CGPoint { - let normalizedX = modelPoint.x / modelInputSize.width - let normalizedY = modelPoint.y / modelInputSize.height - return CGPoint(x: normalizedX * screenSize.width, y: normalizedY * screenSize.height) - } - - // Helper to check if point is within segmentation mask - private func isPointWithinMask(_ normalizedPoint: CGPoint, mask: UIImage) -> Bool { - guard let cgImage = mask.cgImage else { return false } - - let width = cgImage.width - let height = cgImage.height - - // Convert normalized point to mask coordinates - let maskX = Int(normalizedPoint.x * CGFloat(width)) - let maskY = Int(normalizedPoint.y * CGFloat(height)) - - // Ensure coordinates are within bounds - guard maskX >= 0 && maskX < width && maskY >= 0 && maskY < height else { return false } - - // Get pixel data and check if the point is in a mask region - guard let pixelData = getPixelData(from: cgImage) else { return false } - - let pixelIndex = maskY * width + maskX - let pixelValue = pixelData[pixelIndex] - - // Consider point valid if pixel value is above threshold (indicating mask region) - return pixelValue > 50 // Threshold for mask detection - } - - // Helper to extract pixel data from image - private func getPixelData(from cgImage: CGImage) -> [UInt8]? { - let width = cgImage.width - let height = cgImage.height - let bytesPerPixel = 4 - let bytesPerRow = width * bytesPerPixel - let totalBytes = height * bytesPerRow - - var pixelData = [UInt8](repeating: 0, count: totalBytes) - - guard let context = CGContext( - data: &pixelData, - width: width, - height: height, - bitsPerComponent: 8, - bytesPerRow: bytesPerRow, - space: CGColorSpaceCreateDeviceRGB(), - bitmapInfo: CGImageAlphaInfo.noneSkipLast.rawValue - ) else { return nil } - - context.draw(cgImage, in: CGRect(x: 0, y: 0, width: width, height: height)) - - // Convert RGBA to grayscale - var grayscaleData = [UInt8](repeating: 0, count: width * height) - for i in 0..<(width * height) { - let r = pixelData[i * 4] - let g = pixelData[i * 4 + 1] - let b = pixelData[i * 4 + 2] - grayscaleData[i] = UInt8((Int(r) + Int(g) + Int(b)) / 3) - } - - return grayscaleData - } - - func addPromptBox(_ box: CGRect) { - // Convert screen coordinates to model coordinates - let modelBox = CGRect( - x: box.origin.x * modelInputSize.width, - y: box.origin.y * modelInputSize.height, - width: box.size.width * modelInputSize.width, - height: box.size.height * modelInputSize.height - ) - currentPrompt.boxes.append(modelBox) - - print("Added prompt box: \(modelBox)") - } - - func clearPrompts() { - currentPrompt = EdgeTAMPrompt() - originalPoints.removeAll() - latestSegmentationMask = nil - boundaryTrackingManager.stopTracking() - print("Cleared all prompts and tracking") - } - - func setFrameInterval(_ interval: Int) { - guard interval > 0 else { return } - frameCounter = 0 - print("EdgeTAM frame interval set to: \(interval)") - } - - // MARK: - Status Properties - var statusText: String { - if !isModelLoaded { - return "EdgeTAM: Models not loaded" - } - - if processedFrameCount == 0 { - return "EdgeTAM: Ready" - } - - return "EdgeTAM: \(processedFrameCount) frames, \(String(format: "%.1f", processingTime * 1000))ms" - } - - var isActive: Bool { - return isModelLoaded && (processedFrameCount > 0 || isProcessing) - } -} \ No newline at end of file diff --git a/AnySense/Views/EdgeTAMStatusView.swift b/AnySense/Views/EdgeTAMStatusView.swift deleted file mode 100644 index 91c3d93..0000000 --- a/AnySense/Views/EdgeTAMStatusView.swift +++ /dev/null @@ -1,136 +0,0 @@ -// -// EdgeTAMStatusView.swift -// AnySense -// -// UI component for displaying EdgeTAM processing status -// - -import SwiftUI - -struct EdgeTAMStatusView: View { - @ObservedObject var edgeTAMManager: EdgeTAMManager - - var body: some View { - VStack(alignment: .leading, spacing: 8) { - HStack { - Circle() - .fill(statusColor) - .frame(width: 8, height: 8) - - Text(edgeTAMManager.statusText) - .font(.caption) - .foregroundColor(.primary) - } - - if edgeTAMManager.isModelLoaded && edgeTAMManager.processedFrameCount > 0 { - HStack { - Text("Processing every 8th frame") - .font(.caption2) - .foregroundColor(.secondary) - - if edgeTAMManager.isProcessing { - ProgressView() - .scaleEffect(0.5) - } - } - } - - if let features = edgeTAMManager.latestFeatures { - Text("Features: \(features.shape.map { String(describing: $0) }.joined(separator: "x"))") - .font(.caption2) - .foregroundColor(.secondary) - } - - // Show segmentation status - if !edgeTAMManager.currentPrompt.points.isEmpty { - HStack { - Text("Segmentation:") - .font(.caption2) - .foregroundColor(.secondary) - - if edgeTAMManager.latestSegmentationMask != nil { - HStack(spacing: 4) { - Image(systemName: "checkmark.circle.fill") - .foregroundColor(.green) - .font(.caption2) - Text("Mask ready") - .font(.caption2) - .foregroundColor(.green) - } - } else { - HStack(spacing: 4) { - ProgressView() - .scaleEffect(0.5) - Text("Generating...") - .font(.caption2) - .foregroundColor(.orange) - } - } - } - } - } - .padding() - .background(Color.secondary.opacity(0.1)) - .cornerRadius(8) - } - - private var statusColor: Color { - if !edgeTAMManager.isModelLoaded { - return .red - } else if edgeTAMManager.isProcessing { - return .orange - } else if edgeTAMManager.isActive { - return .green - } else { - return .gray - } - } -} - -struct EdgeTAMControlView: View { - @ObservedObject var edgeTAMManager: EdgeTAMManager - @State private var frameInterval: Double = 8 - - var body: some View { - VStack(alignment: .leading, spacing: 12) { - Text("EdgeTAM Settings") - .font(.headline) - - HStack { - Text("Process every") - Slider(value: $frameInterval, in: 1...30, step: 1) - .frame(width: 100) - Text("\(Int(frameInterval)) frames") - .frame(width: 70) - } - .font(.caption) - - Button(action: { - edgeTAMManager.setFrameInterval(Int(frameInterval)) - }) { - Text("Update Interval") - .font(.caption) - .padding(.horizontal, 12) - .padding(.vertical, 6) - .background(Color.blue) - .foregroundColor(.white) - .cornerRadius(6) - } - - Button(action: { - edgeTAMManager.reset() - }) { - Text("Reset") - .font(.caption) - .padding(.horizontal, 12) - .padding(.vertical, 6) - .background(Color.red.opacity(0.8)) - .foregroundColor(.white) - .cornerRadius(6) - } - } - .padding() - .background(Color.secondary.opacity(0.1)) - .cornerRadius(8) - } -} diff --git a/AnySense/Views/EdgeTAMVisualizationOverlay.swift b/AnySense/Views/EdgeTAMVisualizationOverlay.swift deleted file mode 100644 index c6fe1b7..0000000 --- a/AnySense/Views/EdgeTAMVisualizationOverlay.swift +++ /dev/null @@ -1,364 +0,0 @@ -// -// EdgeTAMVisualizationOverlay.swift -// AnySense -// -// Real-time EdgeTAM visualization overlay with full segmentation pipeline -// - -import SwiftUI - -struct EdgeTAMVisualizationOverlay: View { - @ObservedObject var edgeTAMManager: EdgeTAMManager - @State private var showVisualization: Bool = false - @State private var overlayOpacity: Double = 0.7 - @State private var isPromptMode: Bool = false - - var body: some View { - GeometryReader { geometry in - ZStack { - // EdgeTAM segmentation mask overlay - if showVisualization && !edgeTAMManager.currentPrompt.points.isEmpty { - if let segmentationMask = edgeTAMManager.latestSegmentationMask { - Image(uiImage: segmentationMask) - .interpolation(.none) - .resizable() - .aspectRatio(contentMode: .fit) - .opacity(overlayOpacity) - .animation(.easeInOut(duration: 0.3), value: edgeTAMManager.latestSegmentationMask) - } - } - - // Tap gesture overlay for adding prompts - if isPromptMode { - Color.clear - .contentShape(Rectangle()) - .onTapGesture { location in - addPromptPoint(at: location, in: geometry) - } - } - - // Show prompt points overlay - if edgeTAMManager.isBoundaryTracking { - // Show original green points (user input, never move) - ForEach(0.. 0 { - VStack(alignment: .trailing, spacing: 2) { - Text("EdgeTAM") - .font(.caption.bold()) - .foregroundColor(.white) - - Text("Segmentation") - .font(.caption2) - .foregroundColor(.white.opacity(0.8)) - - Text("\(edgeTAMManager.processedFrameCount) frames") - .font(.caption2) - .foregroundColor(.white.opacity(0.8)) - - Text("\(String(format: "%.0f", edgeTAMManager.processingTime * 1000))ms") - .font(.caption2) - .foregroundColor(.white.opacity(0.8)) - - if !edgeTAMManager.currentPrompt.points.isEmpty { - Text("\(edgeTAMManager.currentPrompt.points.count) points") - .font(.caption2) - .foregroundColor(.yellow.opacity(0.8)) - } - - if edgeTAMManager.isBoundaryTracking { - Text("Boundary Tracking") - .font(.caption2) - .foregroundColor(.green.opacity(0.8)) - } - } - .padding(8) - .background(Color.black.opacity(0.7)) - .cornerRadius(8) - } - } - .padding(.trailing, 20) - .padding(.bottom, 100) // Above other UI elements - } - } - - // Prompt mode instructions - if isPromptMode { - VStack { - HStack { - VStack(alignment: .leading, spacing: 4) { - Text("Prompt Mode") - .font(.headline) - .foregroundColor(.white) - - Text("Tap to add positive points") - .font(.caption) - .foregroundColor(.white.opacity(0.8)) - - Text("Long press for negative points") - .font(.caption) - .foregroundColor(.white.opacity(0.8)) - } - .padding(12) - .background(Color.black.opacity(0.8)) - .cornerRadius(8) - - Spacer() - } - .padding(.top, 50) - .padding(.leading, 20) - - Spacer() - } - .transition(.opacity.combined(with: .move(edge: .top))) - } - } - } - } - - // MARK: - Helper Functions - private func addPromptPoint(at location: CGPoint, in geometry: GeometryProxy) { - // Convert screen coordinates to normalized coordinates (0-1) - let normalizedPoint = CGPoint( - x: location.x / geometry.size.width, - y: location.y / geometry.size.height - ) - - // Try to add point with constraints - pass screen coordinates for distance checking - let success = edgeTAMManager.addPromptPointWithConstraints( - normalizedPoint, - screenPoint: location, - screenSize: geometry.size - ) - - if !success { - // Could add visual feedback here (shake animation, error message, etc.) - print("⚠️ Point rejected: outside mask or too close to existing point") - } - } - - private func convertModelPointToScreen(_ modelPoint: CGPoint, in geometry: GeometryProxy) -> CGPoint { - // Convert model coordinates (0-1024) back to screen coordinates - let normalizedX = modelPoint.x / 1024.0 - let normalizedY = modelPoint.y / 1024.0 - - return CGPoint( - x: normalizedX * geometry.size.width, - y: normalizedY * geometry.size.height - ) - } - - private func convertTuplePointToScreen(_ tuplePoint: (CGPoint, Bool), in geometry: GeometryProxy) -> CGPoint { - return convertModelPointToScreen(tuplePoint.0, in: geometry) - } -} - -// MARK: - Enhanced Controls -struct EdgeTAMVisualizationControls: View { - @ObservedObject var edgeTAMManager: EdgeTAMManager - - var body: some View { - VStack(alignment: .leading, spacing: 12) { - Text("EdgeTAM Segmentation") - .font(.headline) - - // Model status - HStack { - Image(systemName: edgeTAMManager.isModelLoaded ? "checkmark.circle.fill" : "xmark.circle.fill") - .foregroundColor(edgeTAMManager.isModelLoaded ? .green : .red) - - Text(edgeTAMManager.isModelLoaded ? "Models Loaded" : "Models Not Loaded") - .font(.caption) - } - - // Segmentation controls - if !edgeTAMManager.currentPrompt.points.isEmpty { - VStack(alignment: .leading, spacing: 8) { - Text("Active Segmentation") - .font(.subheadline.bold()) - - HStack { - Button("Clear Prompts") { - edgeTAMManager.clearPrompts() - } - .buttonStyle(.bordered) - - Spacer() - - Text("\(edgeTAMManager.currentPrompt.points.count) points") - .font(.caption) - .foregroundColor(.secondary) - } - - if edgeTAMManager.latestSegmentationMask != nil { - Text("✓ Mask generated") - .font(.caption2) - .foregroundColor(.green) - } - } - .padding(8) - .background(Color.blue.opacity(0.1)) - .cornerRadius(8) - } else { - Text("Tap screen in prompt mode to add points") - .font(.caption) - .foregroundColor(.secondary) - .italic() - } - - // Processing info - if edgeTAMManager.processedFrameCount > 0 { - VStack(alignment: .leading, spacing: 4) { - Text("Processing: \(edgeTAMManager.processedFrameCount) frames") - .font(.caption2) - .foregroundColor(.secondary) - - Text("Last update: \(String(format: "%.1f", edgeTAMManager.processingTime * 1000))ms") - .font(.caption2) - .foregroundColor(.secondary) - } - } - } - .padding() - .background(Color.secondary.opacity(0.1)) - .cornerRadius(8) - } -} diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 8d9ffe8..6d613df 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -54,15 +54,12 @@ struct ReadView : View{ .opacity(appStatus.rgbdVideoStreaming == .off ? 1 : 0) .allowsHitTesting(appStatus.rgbdVideoStreaming == .off) // Disable interaction in streaming mode - // EdgeTAM Visualization Overlay - if appStatus.rgbdVideoStreaming == .off { - EdgeTAMVisualizationOverlay(edgeTAMManager: arViewModel.edgeTAMManager) - } + } .frame(width: arViewWidth, height: arViewHeight) .padding(.bottom, arViewPadding) - // ML and EdgeTAM Status Overlay + // ML Status Overlay if appStatus.rgbdVideoStreaming == .off { VStack { HStack { @@ -74,8 +71,6 @@ struct ReadView : View{ } } - // EdgeTAM Status (always show when not streaming) - EdgeTAMStatusView(edgeTAMManager: arViewModel.edgeTAMManager) } Spacer() } From 8a0abc1e5968d9787bcda3bce557c0d90ce74e10 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Sun, 31 Aug 2025 11:57:12 -0400 Subject: [PATCH 16/56] Viz: remove 0.5m/world-origin anchor; keep camera-relative arrows only --- AnySense/Managers/ARVisualizationManager.swift | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 9d5e0ea..1a3e930 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -124,11 +124,8 @@ class ARVisualizationManager: ObservableObject { previousWorldPosition = nil hasEstablishedOrigin = true - // Create anchor at world origin - worldOriginAnchor = AnchorEntity(world: worldOrigin) - arView.scene.addAnchor(worldOriginAnchor!) - - print("🌍 World origin established at: \(worldOrigin)") + // No anchor creation needed for visualization + print("🌍 World origin set (no anchor created) at: \(worldOrigin)") } private func resetMovementTracking() { From e3628b4b861c80655e231d2b02fada788c606415 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Sun, 31 Aug 2025 12:06:43 -0400 Subject: [PATCH 17/56] Restore OdometryPointTracker.swift from history; reinstate odometry goal tracking --- AnySense/Managers/OdometryPointTracker.swift | 441 +++++++++++++++++++ 1 file changed, 441 insertions(+) create mode 100644 AnySense/Managers/OdometryPointTracker.swift diff --git a/AnySense/Managers/OdometryPointTracker.swift b/AnySense/Managers/OdometryPointTracker.swift new file mode 100644 index 0000000..a52dec2 --- /dev/null +++ b/AnySense/Managers/OdometryPointTracker.swift @@ -0,0 +1,441 @@ +// +// OdometryPointTracker.swift +// AnySense +// +// Correct odometry-based point tracking matching Python implementation +// + +import Foundation +import ARKit +import simd + +// MARK: - Tracking State +enum OdometryTrackingState { + case idle + case tracking + case lost + + var description: String { + switch self { + case .idle: return "Idle" + case .tracking: return "Tracking" + case .lost: return "Lost" + } + } +} + +// MARK: - Point Tracking Result (matches Python output) +struct OdometryTrackingResult { + let normalized2DPoint: CGPoint // [0,1] normalized coordinates for model (clicked_point equivalent) + let world3DPoint: simd_float3 // 3D point in camera coordinate system (new_3d_point equivalent) + let screenPixelPoint: CGPoint // Screen pixel coordinates for visualization + let isVisible: Bool // Whether point is visible in current view + let confidence: Float // Tracking quality +} + +// MARK: - Python-Style Odometry Point Tracker +class OdometryPointTracker: ObservableObject { + + // MARK: - Published Properties + @Published var trackingState: OdometryTrackingState = .idle + @Published var currentResult: OdometryTrackingResult? + @Published var isEnabled: Bool = true + + // MARK: - Private Properties (matching Python variables) + + // Initial state (step_n == 0 in Python) + private var startPose: simd_float4x4 = matrix_identity_float4x4 + private var startPoseMatrix: simd_float4x4 = matrix_identity_float4x4 + + // Original object position (equivalent to object_x, object_y, object_depth) + private var originalObjectPosition: simd_float3 = simd_float3(0, 0, 0) // In normalized camera coordinates + + // Camera parameters + private var cameraIntrinsics: matrix_float3x3? + private var imageSize: CGSize = CGSize(width: 256, height: 256) // Model input size + private var actualImageSize: CGSize = CGSize(width: 1920, height: 1440) // Actual camera resolution + + // Tracking quality + private var hasInitialPose: Bool = false + private var trackingHistory: [Float] = [] + private let maxHistoryLength: Int = 30 + + // Constants matching Python + let depthOffset: Float = 0.05 // DEPTH_OFFSET from Python (public for validation) + + init() { + print("OdometryPointTracker initialized (Python-compatible)") + } + + // MARK: - Public Interface (matching Python workflow) + + /// Start tracking (equivalent to step_n == 0 in Python) + func startTracking( + screenPoint: CGPoint, + in view: UIView, + arFrame: ARFrame, + session: ARSession, + depthMap: CVPixelBuffer? + ) -> Bool { + + print("Starting odometry tracking at screen point: (\(screenPoint.x), \(screenPoint.y))") + + // Store initial pose (equivalent to self.start_pose and self.start_pose_matrix) + self.startPose = arFrame.camera.transform + self.startPoseMatrix = arFrame.camera.transform + self.cameraIntrinsics = arFrame.camera.intrinsics + self.actualImageSize = CGSize( + width: CVPixelBufferGetWidth(arFrame.capturedImage), + height: CVPixelBufferGetHeight(arFrame.capturedImage) + ) + + // Convert screen point to normalized camera coordinates (equivalent to _point2d_to_3d) + guard let objectPosition = convertScreenPointTo3D( + screenPoint: screenPoint, + in: view, + frame: arFrame, + session: session, + depthMap: depthMap + ) else { + print("Failed to convert screen point to 3D") + return false + } + + self.originalObjectPosition = objectPosition + self.hasInitialPose = true + self.trackingState = .tracking + + // Create initial result (equivalent to new_3d_point = get_new_2d_point(..., None)) + let initialResult = createTrackingResult( + objectPosition: objectPosition, + currentPose: startPose, + relativePose: matrix_identity_float4x4 + ) + + self.currentResult = initialResult + + print("Started tracking object at normalized position: [\(objectPosition.x), \(objectPosition.y), \(objectPosition.z)]") + print("Initial 2D point: [\(initialResult.normalized2DPoint.x), \(initialResult.normalized2DPoint.y)]") + + return true + } + + /// Update tracking (equivalent to step_n > 0 in Python) + func updateTracking(currentFrame: ARFrame) -> OdometryTrackingResult? { + guard isEnabled && hasInitialPose && trackingState == .tracking else { + return currentResult + } + + let currentPose = currentFrame.camera.transform + + // Calculate relative transformation (equivalent to Python logic) + // relative_transformation_matrix = np.linalg.inv(self.start_pose_matrix) @ current_pose_matrix + let relativePose = simd_mul(simd_inverse(startPoseMatrix), currentPose) + + // Get new 2D point using the same logic as Python + // new_2d_point, new_3d_point = get_new_2d_point(self.object_x, self.object_y, self.object_depth, relative_transformation_matrix) + let result = createTrackingResult( + objectPosition: originalObjectPosition, + currentPose: currentPose, + relativePose: relativePose + ) + + // Update tracking quality + updateTrackingMetrics(result: result) + + self.currentResult = result + + print("Updated tracking: 2D=[\(String(format: "%.3f", result.normalized2DPoint.x)), \(String(format: "%.3f", result.normalized2DPoint.y))], 3D=[\(String(format: "%.3f", result.world3DPoint.x)), \(String(format: "%.3f", result.world3DPoint.y)), \(String(format: "%.3f", result.world3DPoint.z))]") + + return result + } + + /// Reset tracking + func resetTracking() { + hasInitialPose = false + trackingState = .idle + currentResult = nil + trackingHistory.removeAll() + print("Odometry tracking reset") + } + + /// Get current goal point for model (2D or 3D based on goal_dim) + func getGoalPointForModel(goalDimension: Int) -> [Float]? { + guard let result = currentResult else { return nil } + + if goalDimension == 3 { + // Return 3D point (new_3d_point converted to labels.json frame) + let labelPoint = convertToLabelsFrame(result.world3DPoint) + return [labelPoint.x, labelPoint.y, labelPoint.z] + } else { + // Return 2D normalized point (clicked_point equivalent) + return [Float(result.normalized2DPoint.x), Float(result.normalized2DPoint.y)] + } + } + + /// Enable/disable tracking + func setEnabled(_ enabled: Bool) { + isEnabled = enabled + if !enabled { + trackingState = .idle + } + print("Odometry tracking \(enabled ? "enabled" : "disabled")") + } + + // MARK: - Private Implementation (matching Python logic) + + /// Convert screen point to 3D with robust fallback strategies + private func convertScreenPointTo3D( + screenPoint: CGPoint, + in view: UIView, + frame: ARFrame, + session: ARSession, + depthMap: CVPixelBuffer? + ) -> simd_float3? { + + print("🎯 Converting screen point (\(screenPoint.x), \(screenPoint.y)) to 3D") + + // Normalize screen coordinates to [0,1] (matching Python: p2d[0] / 256, p2d[1] / 256) + let normalizedX = screenPoint.x / view.bounds.width + let normalizedY = screenPoint.y / view.bounds.height + + // Strategy 1: Try depth map sampling (highest accuracy) + if let depthBuffer = depthMap { + print("📡 Attempting depth map sampling...") + let sampledDepth = sampleDepthMap( + depthBuffer: depthBuffer, + normalizedX: normalizedX, + normalizedY: normalizedY + ) + + if sampledDepth > 0.1 && sampledDepth < 10.0 { // Valid depth range + let finalDepth = sampledDepth + depthOffset + print("✅ Depth map success: \(String(format: "%.3f", finalDepth))m") + return simd_float3(Float(normalizedX), Float(normalizedY), finalDepth) + } else { + print("⚠️ Depth map returned invalid depth: \(sampledDepth)m") + } + } else { + print("⚠️ No depth map provided") + } + + // Strategy 2: ARKit raycast hit testing (reliable fallback) + print("🔍 Attempting ARKit raycast...") + let normalizedPoint = CGPoint(x: normalizedX, y: normalizedY) + + // Create raycast query for existing planes or surfaces + let query = frame.raycastQuery(from: normalizedPoint, allowing: .existingPlaneGeometry, alignment: .any) + + let results = session.raycast(query) + if let result = results.first { + let hitPoint = result.worldTransform.columns.3 + let cameraPos = frame.camera.transform.columns.3 + let distance = length(simd_float3(hitPoint.x - cameraPos.x, hitPoint.y - cameraPos.y, hitPoint.z - cameraPos.z)) + + if distance > 0.1 && distance < 10.0 { + let finalDepth = distance + depthOffset + print("✅ Raycast success: \(String(format: "%.3f", finalDepth))m") + return simd_float3(Float(normalizedX), Float(normalizedY), finalDepth) + } + } + print("⚠️ Raycast failed - no surfaces detected") + + // Strategy 3: Simple fixed distance fallback + print("📊 Using fixed distance estimation...") + let fixedDepth: Float = 1.0 + depthOffset // 1 meter default + print("📊 Fixed depth: \(String(format: "%.3f", fixedDepth))m") + + return simd_float3(Float(normalizedX), Float(normalizedY), fixedDepth) + } + + + /// Sample depth map (equivalent to np_depth[int(y * 192), int(x * 256)]) + private func sampleDepthMap( + depthBuffer: CVPixelBuffer, + normalizedX: CGFloat, + normalizedY: CGFloat + ) -> Float { + + let depthWidth = CVPixelBufferGetWidth(depthBuffer) + let depthHeight = CVPixelBufferGetHeight(depthBuffer) + + // Convert to depth map coordinates (matching Python indexing) + let depthX = Int(normalizedX * CGFloat(depthWidth)) + let depthY = Int(normalizedY * CGFloat(depthHeight)) + + // Ensure coordinates are within bounds + guard depthX >= 0 && depthX < depthWidth && depthY >= 0 && depthY < depthHeight else { + return 1.0 // Default depth + } + + // Read depth value + CVPixelBufferLockBaseAddress(depthBuffer, .readOnly) + defer { CVPixelBufferUnlockBaseAddress(depthBuffer, .readOnly) } + + guard let baseAddress = CVPixelBufferGetBaseAddress(depthBuffer) else { return 1.0 } + let bytesPerRow = CVPixelBufferGetBytesPerRow(depthBuffer) + let depthPointer = baseAddress.assumingMemoryBound(to: Float32.self) + + let pixelOffset = depthY * (bytesPerRow / MemoryLayout.stride) + depthX + let depth = depthPointer[pixelOffset] + + return depth > 0.1 ? depth : 1.0 // Return valid depth or default + } + + /// Create tracking result (equivalent to get_new_2d_point with transformation) + private func createTrackingResult( + objectPosition: simd_float3, + currentPose: simd_float4x4, + relativePose: simd_float4x4 + ) -> OdometryTrackingResult { + + // Apply relative transformation to get new position + // This is the key logic from Python: get_new_2d_point with relative_transformation_matrix + var transformedPosition = objectPosition + + if relativePose != matrix_identity_float4x4 { + // Transform the original position by the relative pose change + // This keeps the object fixed in world space and calculates its new appearance + let homogeneous = simd_float4(objectPosition.x, objectPosition.y, objectPosition.z, 1.0) + let transformed = simd_mul(relativePose, homogeneous) + transformedPosition = simd_float3(transformed.x, transformed.y, transformed.z) + } + + // Convert to screen pixel coordinates for visualization + let screenPixelPoint = convertNormalizedToScreenPixels( + normalized: CGPoint(x: CGFloat(transformedPosition.x), y: CGFloat(transformedPosition.y)) + ) + + // Check visibility (equivalent to checking if point is in bounds) + let isVisible = transformedPosition.x >= 0 && transformedPosition.x <= 1.0 && + transformedPosition.y >= 0 && transformedPosition.y <= 1.0 && + transformedPosition.z > 0 + + // Calculate confidence based on visibility and position + let confidence = calculateConfidence( + position: transformedPosition, + isVisible: isVisible + ) + + // Create world 3D point (for 3D goal conditioning) + let world3DPoint = convertToWorldCoordinates( + normalizedPosition: transformedPosition, + cameraPose: currentPose + ) + + return OdometryTrackingResult( + normalized2DPoint: CGPoint(x: CGFloat(transformedPosition.x), y: CGFloat(transformedPosition.y)), + world3DPoint: world3DPoint, + screenPixelPoint: screenPixelPoint, + isVisible: isVisible, + confidence: confidence + ) + } + + /// Convert normalized coordinates to screen pixels + private func convertNormalizedToScreenPixels(normalized: CGPoint) -> CGPoint { + // Convert from [0,1] normalized coordinates to actual screen pixels + let pixelX = normalized.x * imageSize.width + let pixelY = normalized.y * imageSize.height + return CGPoint(x: pixelX, y: pixelY) + } + + /// Convert normalized position to world coordinates + private func convertToWorldCoordinates( + normalizedPosition: simd_float3, + cameraPose: simd_float4x4 + ) -> simd_float3 { + + guard let intrinsics = cameraIntrinsics else { + // Fallback to simple conversion + return simd_float3( + (normalizedPosition.x - 0.5) * normalizedPosition.z * 2.0, + (normalizedPosition.y - 0.5) * normalizedPosition.z * 2.0, + normalizedPosition.z + ) + } + + // Convert from normalized coordinates to camera space using intrinsics + let fx = intrinsics.columns.0.x + let fy = intrinsics.columns.1.y + let cx = intrinsics.columns.2.x + let cy = intrinsics.columns.2.y + + let pixelX = normalizedPosition.x * Float(actualImageSize.width) + let pixelY = normalizedPosition.y * Float(actualImageSize.height) + + let cameraX = (pixelX - cx) / fx * normalizedPosition.z + let cameraY = (pixelY - cy) / fy * normalizedPosition.z + let cameraZ = normalizedPosition.z + + let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) + + // Transform to world coordinates + let worldPoint = simd_mul(cameraPose, cameraPoint) + + return simd_float3(worldPoint.x, worldPoint.y, worldPoint.z) + } + + /// Convert world point to labels.json frame (equivalent to Python conversion) + private func convertToLabelsFrame(_ worldPoint: simd_float3) -> simd_float3 { + // Python: new_3d_point = [-x, z, y] # converting from canonical frame to labels.json frame + return simd_float3(-worldPoint.x, worldPoint.z, worldPoint.y) + } + + /// Calculate tracking confidence + private func calculateConfidence(position: simd_float3, isVisible: Bool) -> Float { + var confidence: Float = 1.0 + + // Reduce confidence if not visible + if !isVisible { + confidence *= 0.3 + } + + // Reduce confidence based on distance from center + let centerDistance = length(simd_float2(position.x - 0.5, position.y - 0.5)) + confidence *= max(0.2, 1.0 - centerDistance * 2.0) + + // Reduce confidence based on depth + if position.z > 5.0 { + confidence *= 0.5 + } + + return max(0.0, min(1.0, confidence)) + } + + /// Update tracking quality metrics + private func updateTrackingMetrics(result: OdometryTrackingResult) { + trackingHistory.append(result.confidence) + if trackingHistory.count > maxHistoryLength { + trackingHistory.removeFirst() + } + + // Update tracking state based on confidence + if result.confidence < 0.2 { + trackingState = .lost + } else if result.confidence > 0.5 && trackingState == .lost { + trackingState = .tracking + } + } + + // MARK: - Simple Test Method (to avoid compilation error) + func runAllValidationTests() -> Bool { + // Simple validation - just return true since tests are removed + return true + } + +} + +// MARK: - Matrix Utilities +extension float4x4 { + static func == (lhs: float4x4, rhs: float4x4) -> Bool { + return lhs.columns.0 == rhs.columns.0 && + lhs.columns.1 == rhs.columns.1 && + lhs.columns.2 == rhs.columns.2 && + lhs.columns.3 == rhs.columns.3 + } + + static func != (lhs: float4x4, rhs: float4x4) -> Bool { + return !(lhs == rhs) + } +} \ No newline at end of file From f76d859f1df24ef4a3da4f680ad4dab75fcc190e Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Sun, 31 Aug 2025 12:16:22 -0400 Subject: [PATCH 18/56] Viz: restore target/device pose handlers (updateActualDevicePose/updateTargetFromOdometry/set/clearTargetPose) --- .../Managers/ARVisualizationManager.swift | 22 +++++++++++++++++++ 1 file changed, 22 insertions(+) diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 1a3e930..299c5db 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -50,6 +50,10 @@ class ARVisualizationManager: ObservableObject { private var movementArrows: [DirectionalArrow] = [] private var lastVisualizationTime: CFTimeInterval = 0 + // Target/device pose state for point-conditioned flows + private var targetPose: SIMD3? + private var actualDevicePose: SIMD3 = SIMD3(0, 0, 0) + // Movement tracking private var worldOrigin: SIMD3 = SIMD3(0, 0, 0) private var currentWorldPosition: SIMD3 = SIMD3(0, 0, 0) @@ -184,6 +188,24 @@ class ARVisualizationManager: ObservableObject { print("AR Visualization frequency set to: \(frequency.displayName)") } + // MARK: - Odometry/Device Pose Integration + func updateActualDevicePose(from arFrame: ARFrame) { + let t = arFrame.camera.transform + actualDevicePose = SIMD3(t.columns.3.x, t.columns.3.y, t.columns.3.z) + } + + func updateTargetFromOdometry(_ result: OdometryTrackingResult) { + targetPose = result.world3DPoint + } + + func setTargetPose(_ worldPoint: SIMD3) { + targetPose = worldPoint + } + + func clearTargetPose() { + targetPose = nil + } + // MARK: - ML Integration Method func updatePoseFromMLOutput(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) { // Apply frequency throttling From 32ff073eddf6a03f582973219a5e8735fd1f1d4c Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Mon, 1 Sep 2025 16:15:11 -0400 Subject: [PATCH 19/56] =?UTF-8?q?Unify=20policy=E2=86=92camera=20transform?= =?UTF-8?q?s;=20orientation-aware=20viz;=20ML=20USB=20mapping;=20debug=20t?= =?UTF-8?q?ools;=20ignore=20model=20artifacts?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .gitignore | 4 + AnySense.xcodeproj/project.pbxproj | 8 ++ AnySense/MLModel+Extensions.swift | 132 +++++++++++++++++- AnySense/Managers/ARViewContainer.swift | 85 ++++++++++- .../Managers/ARVisualizationManager.swift | 107 ++++++++------ AnySense/Managers/ActionTransformUtils.swift | 128 +++++++++++++++-- AnySense/Managers/MLInferenceManager.swift | 131 +++++++++++++---- AnySense/Managers/ModelManager.swift | 107 ++++++++------ AnySense/Managers/TransformDebug.swift | 24 ++++ AnySense/Managers/USBManager.swift | 18 +++ AnySense/Views/accountView.swift | 7 +- AnySense/Views/readView.swift | 17 +++ AnySense/dataStorage.swift | 10 +- 13 files changed, 639 insertions(+), 139 deletions(-) create mode 100644 AnySense/Managers/TransformDebug.swift diff --git a/.gitignore b/.gitignore index 242fabd..80976e4 100644 --- a/.gitignore +++ b/.gitignore @@ -64,3 +64,7 @@ fastlane/report.xml fastlane/Preview.html fastlane/screenshots/**/*.png fastlane/test_output + + +# Models +Models/ diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 716bdfb..03e9004 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -10,6 +10,8 @@ 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */; }; 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */; }; 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */; }; + 01D2FDD72E64C33600F0BA98 /* OdometryPointTracker.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01D2FDD62E64C33600F0BA98 /* OdometryPointTracker.swift */; }; + 01D2FDD82E64C33600F0BA98 /* ActionTransformUtils.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */; }; 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */; }; 01F5B7C62DEA698D00061B16 /* MLInferenceResultsView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */; }; 01F5B7C82DEA6A0000061B16 /* ModelManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C72DEA6A0000061B16 /* ModelManager.swift */; }; @@ -48,6 +50,8 @@ /* Begin PBXFileReference section */ 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARVisualizationManager.swift; sourceTree = ""; }; + 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ActionTransformUtils.swift; sourceTree = ""; }; + 01D2FDD62E64C33600F0BA98 /* OdometryPointTracker.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = OdometryPointTracker.swift; sourceTree = ""; }; 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceManager.swift; sourceTree = ""; }; 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceResultsView.swift; sourceTree = ""; }; 01F5B7C72DEA6A0000061B16 /* ModelManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ModelManager.swift; sourceTree = ""; }; @@ -144,6 +148,8 @@ children = ( B9E4B2282D62A9BA0032E877 /* ARViewContainer.swift */, 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */, + 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */, + 01D2FDD62E64C33600F0BA98 /* OdometryPointTracker.swift */, 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */, 01F5B7C72DEA6A0000061B16 /* ModelManager.swift */, B9E4B2292D62A9BA0032E877 /* BluetoothManager.swift */, @@ -352,6 +358,8 @@ B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */, 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */, 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */, + 01D2FDD72E64C33600F0BA98 /* OdometryPointTracker.swift in Sources */, + 01D2FDD82E64C33600F0BA98 /* ActionTransformUtils.swift in Sources */, 01F5B7C82DEA6A0000061B16 /* ModelManager.swift in Sources */, B9E4B22D2D62A9BA0032E877 /* BluetoothManager.swift in Sources */, B9E4B22F2D62A9BA0032E877 /* ARViewContainer.swift in Sources */, diff --git a/AnySense/MLModel+Extensions.swift b/AnySense/MLModel+Extensions.swift index a1c8172..40e82ed 100644 --- a/AnySense/MLModel+Extensions.swift +++ b/AnySense/MLModel+Extensions.swift @@ -60,22 +60,54 @@ struct ModelMetadata { let expectedOutputCount: Int? let outputFeatureNames: [String] let primaryOutputName: String? + private let allInputsByName: [String: MLFeatureDescription] init(from model: MLModel) throws { let modelDescription = model.modelDescription - // Get input description (assuming single input for now) - self.inputDescription = modelDescription.inputDescriptionsByName.values.first + // Cache all inputs (local first to avoid using self during init) + let inputsByName = modelDescription.inputDescriptionsByName + + // Get first input description (legacy use) + self.inputDescription = inputsByName.values.first // Get output description self.outputDescription = modelDescription.outputDescriptionsByName.values.first self.modelDescription = modelDescription.metadata[.description] as? String ?? "No description" - // Extract input shape if available - simplified approach - if self.inputDescription != nil { - // For now, set a default shape - can be enhanced later if needed - self.requiredInputShape = [224, 224, 3] // Common image input shape + // Extract input shape if available (try to infer from first image or 4D array) + func localFirstImageLikeInput(_ inputs: [String: MLFeatureDescription]) -> (String, MLFeatureDescription)? { + if let d = inputs["camera_image"] { return ("camera_image", d) } + for (key, desc) in inputs { + switch desc.type { + case .image: return (key, desc) + case .multiArray: + if let shape = desc.multiArrayConstraint?.shape, shape.count >= 4 { return (key, desc) } + default: continue + } + } + return nil + } + if let (_, desc) = localFirstImageLikeInput(inputsByName) { + switch desc.type { + case .image: + if let c = desc.imageConstraint { + self.requiredInputShape = [Int(c.pixelsHigh), Int(c.pixelsWide), 3] + } else { + self.requiredInputShape = [224, 224, 3] + } + case .multiArray: + if let shape = desc.multiArrayConstraint?.shape, shape.count >= 4 { + let h = shape[shape.count-2].intValue + let w = shape[shape.count-1].intValue + self.requiredInputShape = [h, w, 3] + } else { + self.requiredInputShape = [224, 224, 3] + } + default: + self.requiredInputShape = [224, 224, 3] + } } else { self.requiredInputShape = nil } @@ -87,7 +119,7 @@ struct ModelMetadata { self.outputFeatureNames = Array(modelDescription.outputDescriptionsByName.keys).sorted() self.primaryOutputName = self.outputFeatureNames.first - // Check compatibility inline - avoid calling self method before initialization complete + // Check compatibility inline - avoid calling helpers before initialization complete self.isCompatible = !modelDescription.inputDescriptionsByName.isEmpty && !modelDescription.outputDescriptionsByName.isEmpty && modelDescription.inputDescriptionsByName.values.contains { desc in @@ -102,6 +134,92 @@ struct ModelMetadata { default: return false } } + + // Now that init values are ready, set cached inputs map + self.allInputsByName = inputsByName + } + + // MARK: - Dynamic helpers used by MLInferenceManager + enum ModelType { + case pointConditioned + case standard + var displayName: String { + switch self { + case .pointConditioned: return "Point-Conditioned" + case .standard: return "Standard" + } + } + } + + var modelType: ModelType { + return requiresGoalPoint ? .pointConditioned : .standard + } + + var requiresGoalPoint: Bool { + // Heuristic: presence of a second non-image input named "goal_point" or a small (1x3) array input + if allInputsByName.keys.contains("goal_point") { return true } + for (name, desc) in allInputsByName { + if name == "camera_image" { continue } + switch desc.type { + case .multiArray: + if let shape = desc.multiArrayConstraint?.shape { + // Accept 2D [1,3] or [3] or small shapes as goal vector + let dims = shape.map { $0.intValue } + if dims == [1,3] || dims == [3] || dims.suffix(1).first == 3 && dims.reduce(1,*) <= 16 { + return true + } + } + default: break + } + } + return false + } + + var imageInputSize: CGSize? { + guard let (_, desc) = firstImageLikeInput() else { return nil } + switch desc.type { + case .image: + if let c = desc.imageConstraint { return CGSize(width: Int(c.pixelsWide), height: Int(c.pixelsHigh)) } + case .multiArray: + if let shape = desc.multiArrayConstraint?.shape, shape.count >= 4 { + let h = shape[shape.count-2].intValue + let w = shape[shape.count-1].intValue + return CGSize(width: w, height: h) + } + default: break + } + return nil + } + + func getImageInputName() -> String? { + if allInputsByName.keys.contains("camera_image") { return "camera_image" } + if let (name, _) = firstImageLikeInput() { return name } + return nil + } + + func getGoalInputName() -> String? { + if allInputsByName.keys.contains("goal_point") { return "goal_point" } + for (name, desc) in allInputsByName where name != "camera_image" { + if desc.type == .multiArray, let shape = desc.multiArrayConstraint?.shape { + let dims = shape.map { $0.intValue } + if dims == [1,3] || dims == [3] || dims.reduce(1,*) <= 16 { return name } + } + } + return nil + } + + // Find the first image-like input (image or 4D array) + private func firstImageLikeInput() -> (String, MLFeatureDescription)? { + if let d = allInputsByName["camera_image"] { return ("camera_image", d) } + for (name, desc) in allInputsByName { + switch desc.type { + case .image: return (name, desc) + case .multiArray: + if let shape = desc.multiArrayConstraint?.shape, shape.count >= 4 { return (name, desc) } + default: continue + } + } + return nil } } diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index bb24aff..78e49fd 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -50,6 +50,10 @@ struct ARViewContainer: UIViewRepresentable { // Setup AR visualization with the created ARView arVisualizationManager.setupVisualization(with: arView) + // Add tap recognizer for goal setting (point-conditioned models) + let tap = UITapGestureRecognizer(target: context.coordinator, action: #selector(Coordinator.handleTap(_:))) + arView.addGestureRecognizer(tap) + return arView } func updateUIView(_ uiView: ARView, context: Context) { @@ -57,6 +61,25 @@ struct ARViewContainer: UIViewRepresentable { uiView.session = session } } + + // MARK: - Coordinator for gesture handling + func makeCoordinator() -> Coordinator { Coordinator(self) } + + class Coordinator: NSObject { + let parent: ARViewContainer + init(_ parent: ARViewContainer) { self.parent = parent } + + @objc func handleTap(_ recognizer: UITapGestureRecognizer) { + guard recognizer.state == .ended, let arView = recognizer.view as? ARView else { return } + let location = recognizer.location(in: arView) + // Convert UIKit tap to a lightweight UIView for ML manager API + let dummyView = UIView(frame: arView.bounds) + + // Access ML manager via a shared ARViewModel if available + // Here, we post a notification with tap info; the view model can subscribe and start odometry + NotificationCenter.default.post(name: NSNotification.Name("ARViewTapForGoal"), object: nil, userInfo: ["location": location, "bounds": arView.bounds]) + } + } } class DepthStatus: ObservableObject { @@ -83,8 +106,8 @@ class ARViewModel: ObservableObject{ // AR Visualization Manager for 3D pose visualization @Published var arVisualizationManager = ARVisualizationManager() - - + @Published var goalTapModeEnabled: Bool = false + public var userFPS: Double? public var isColorMapOpened = false @@ -110,7 +133,19 @@ class ARViewModel: ObservableObject{ private var rgbOutputPixelBufferUSB: CVPixelBuffer? private var depthOutputPixelBufferUSB: CVPixelBuffer? private var depthConfidenceOutputPixelBufferUSB: CVPixelBuffer? + // MARK: - Exposed helpers for MLInferenceManager + func getARSession() -> ARSession { + return session + } + func sendJointActionsUSB(_ jointActions: [Float]) { + var actions = Array(jointActions.prefix(7)) + if actions.count < 7 { + actions.append(contentsOf: Array(repeating: 0.0, count: 7 - actions.count)) + } + let data = actions.withUnsafeBytes { Data($0) } + usbManager.sendJointActions(data) + } private var poseFileHandle: FileHandle? // Control the destination of rgb images directory and depth images directory @@ -167,6 +202,42 @@ class ARViewModel: ObservableObject{ self.ciContext = CIContext() updateDemoCounter() + + // Listen for goal-tap notifications and start odometry + set goal point + NotificationCenter.default.addObserver(forName: NSNotification.Name("ARViewTapForGoal"), object: nil, queue: .main) { [weak self] notif in + guard let self = self, let ml = self.mlManager else { return } + // Only handle taps when using a point-conditioned policy and the user enabled goal-tap mode + guard ml.isPointConditioned, self.goalTapModeEnabled else { return } + guard let location = notif.userInfo?["location"] as? CGPoint, + let bounds = notif.userInfo?["bounds"] as? CGRect else { return } + let dummyView = UIView(frame: bounds) + if let frame = self.session.currentFrame { + let depth = self.depthStatus.isDepthAvailable ? (frame.sceneDepth?.depthMap) : nil + _ = ml.startOdometryTrackingWithScreenPoint(screenPoint: location, in: dummyView, arFrame: frame, depthMap: depth) + if let world = ml.convertScreenToWorld(location, in: dummyView, arSession: self.session, depthMap: depth) ?? self.raycastWithEstimatedDepth(at: location, in: dummyView, frame: frame, estimatedDepth: 2.5) { + ml.setGoalPoint(world) + self.arVisualizationManager.setTargetPose(world) + // Exit goal-tap mode after a successful set + self.goalTapModeEnabled = false + } + } + } + } + + // Fallback conversion using a constant estimated depth when depth map is unavailable + private func raycastWithEstimatedDepth(at screenPoint: CGPoint, in view: UIView, frame: ARFrame, estimatedDepth: Float) -> simd_float3? { + let cameraIntrinsics = frame.camera.intrinsics + let cameraTransform = frame.camera.transform + let fx = cameraIntrinsics.columns.0.x + let fy = cameraIntrinsics.columns.1.y + let cx = cameraIntrinsics.columns.2.x + let cy = cameraIntrinsics.columns.2.y + let cameraX = (Float(screenPoint.x) - cx) / fx * estimatedDepth + let cameraY = (Float(screenPoint.y) - cy) / fy * estimatedDepth + let cameraZ = estimatedDepth + let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) + let worldPoint = simd_mul(cameraTransform, cameraPoint) + return simd_float3(worldPoint.x, worldPoint.y, worldPoint.z) } @@ -431,8 +502,8 @@ class ARViewModel: ObservableObject{ let rgbPixelBuffer = currentFrame.capturedImage - // Perform ML inference on the RGB frame during streaming - mlManager?.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) + // Perform ML inference on the RGB frame during streaming (provide ARFrame for odometry/goal updates) + mlManager?.performInference(on: rgbPixelBuffer, arFrame: currentFrame, timestamp: CACurrentMediaTime()) @@ -910,8 +981,8 @@ class ARViewModel: ObservableObject{ depthPixelBuffer = depthBuffer } - // Perform ML inference on the RGB frame - mlManager?.performInference(on: rgbPixelBuffer, timestamp: CACurrentMediaTime()) + // Perform ML inference on the RGB frame (provide ARFrame for odometry/goal updates) + mlManager?.performInference(on: rgbPixelBuffer, arFrame: currentFrame, timestamp: CACurrentMediaTime()) @@ -959,6 +1030,8 @@ class ARViewModel: ObservableObject{ // Connect AR visualization to ML inference self.mlManager?.arVisualizationManager = self.arVisualizationManager + // Provide AR session access to ML manager for goal and odometry + self.mlManager?.setARViewContainer(self) // ML results are now accessed directly during streaming for better real-time performance diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 299c5db..fffcfd2 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -71,6 +71,10 @@ class ARVisualizationManager: ObservableObject { // Arrow lifecycle private let arrowLifetime: TimeInterval = 3.0 // Arrows fade after 3 seconds + // Debug controls + var debugLoggingEnabled: Bool = true + var debugAlwaysDrawArrow: Bool = false + // MARK: - Initialization init() { print("ARVisualizationManager initialized with delta-based movement arrows") @@ -86,7 +90,7 @@ class ARVisualizationManager: ObservableObject { func startRecordingVisualization() { print("startRecordingVisualization called") - guard let arView = arView else { + guard arView != nil else { print("ARView not available for visualization") return } @@ -116,7 +120,7 @@ class ARVisualizationManager: ObservableObject { } private func establishWorldOrigin() { - guard let arView = arView else { return } + guard let currentArView = arView else { return } guard !hasEstablishedOrigin else { print("World origin already established") return @@ -127,9 +131,15 @@ class ARVisualizationManager: ObservableObject { currentWorldPosition = SIMD3(0, 0, 0) // Start at origin previousWorldPosition = nil hasEstablishedOrigin = true - - // No anchor creation needed for visualization - print("🌍 World origin set (no anchor created) at: \(worldOrigin)") + + // Create an anchor at the chosen world origin to host visualization entities + var t = matrix_identity_float4x4 + t.columns.3 = SIMD4(worldOrigin.x, worldOrigin.y, worldOrigin.z, 1) + let anchor = AnchorEntity(world: t) + currentArView.scene.addAnchor(anchor) + worldOriginAnchor = anchor + + print("🌍 World origin set at: \(worldOrigin) and anchor created") } private func resetMovementTracking() { @@ -161,6 +171,15 @@ class ARVisualizationManager: ObservableObject { } movementArrows.removeAll() } + + // MARK: - Public helper to auto-prepare visualization + func prepareVisualizationIfNeeded() { + if !hasEstablishedOrigin { establishWorldOrigin() } + if !isVisualizationEnabled { enableVisualization() } + if debugLoggingEnabled { + print("[Viz] prepareVisualizationIfNeeded → enabled=\(isVisualizationEnabled), origin=\(hasEstablishedOrigin)") + } + } func toggleMovementArrows() { showMovementArrows.toggle() @@ -210,6 +229,9 @@ class ARVisualizationManager: ObservableObject { func updatePoseFromMLOutput(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) { // Apply frequency throttling if timestamp - lastVisualizationTime < visualizationFrequency.interval { + if debugLoggingEnabled { + print("[Viz] throttled (\(timestamp - lastVisualizationTime)s < \(visualizationFrequency.interval)s)") + } return } @@ -225,8 +247,17 @@ class ARVisualizationManager: ObservableObject { return } - // Interpret joint actions as movement deltas in ARKit coordinates - let (deltaTranslation, _, confidence) = interpretMLDirections(jointActions) + // Interpret joint actions as movement deltas in CAMERA coordinates, then rotate into world frame + let (cameraDeltaTranslation, _, confidence) = interpretMLDirections(jointActions) + let cameraTransform = getCurrentCameraTransform() + let rotationWorldFromCamera = simd_float3x3( + columns: ( + SIMD3(cameraTransform.columns.0.x, cameraTransform.columns.0.y, cameraTransform.columns.0.z), + SIMD3(cameraTransform.columns.1.x, cameraTransform.columns.1.y, cameraTransform.columns.1.z), + SIMD3(cameraTransform.columns.2.x, cameraTransform.columns.2.y, cameraTransform.columns.2.z) + ) + ) + let deltaTranslation = rotationWorldFromCamera * cameraDeltaTranslation print("📱 ML input (x=down,y=right,z=back): (\(String(format: "%.3f", jointActions[0])), \(String(format: "%.3f", jointActions[1])), \(String(format: "%.3f", jointActions[2])))") print("📲 Delta movement (x=right,y=up,z=forward): (\(String(format: "%.3f", deltaTranslation.x)), \(String(format: "%.3f", deltaTranslation.y)), \(String(format: "%.3f", deltaTranslation.z)))") @@ -238,7 +269,10 @@ class ARVisualizationManager: ObservableObject { // Only create movement arrow if there's meaningful movement and we have a previous position let movementMagnitude = length(deltaTranslation) - if movementMagnitude > 0.005 { // 5mm threshold for meaningful movement + if debugLoggingEnabled { + print("[Viz] camera delta=\(cameraDeltaTranslation), world delta=\(deltaTranslation), mag=\(movementMagnitude)") + } + if movementMagnitude > 0.005 || debugAlwaysDrawArrow { // draw even if tiny in debug createMovementArrow( from: previousPosition, to: currentWorldPosition, @@ -251,45 +285,38 @@ class ARVisualizationManager: ObservableObject { } private func interpretMLDirections(_ jointActions: [Float]) -> (translation: SIMD3, rotation: simd_quatf, confidence: Float) { + // Use unified policy→camera mapping for consistency with robot path + let action7 = Array(jointActions.prefix(7)) + let quarterTurns: Int + // Map device interface orientation to quarter turns around camera Z + if let windowScene = UIApplication.shared.connectedScenes.first as? UIWindowScene { + switch windowScene.interfaceOrientation { + case .landscapeLeft: + quarterTurns = 1 + case .landscapeRight: + quarterTurns = -1 + case .portraitUpsideDown: + quarterTurns = 2 + default: + quarterTurns = 0 + } + } else { + quarterTurns = 0 + } + let mapped = ActionTransformUtils.policyToCameraEulerAction(action7, rotationUnit: .eulerXYZ, quarterTurns: quarterTurns) + let translation = SIMD3(mapped[0], mapped[1], mapped[2]) + let rotation = eulerToQuaternion(roll: mapped[3], pitch: mapped[4], yaw: mapped[5]) - // Interpret as directional vectors (not absolute positions) - // Transform from ML coordinate system to ARKit camera-relative coordinates - let ml_x = jointActions[0] // down - let ml_y = jointActions[1] // right - let ml_z = jointActions[2] // backward (into phone) - let ml_roll = jointActions[3] - let ml_pitch = jointActions[4] - let ml_yaw = jointActions[5] - - // COORDINATE SYSTEM TRANSFORMATION: - // Phone ML: x=down, y=right, z=backward → ARKit: x=right, y=up, z=forward - // - // ML x (down) → ARKit y (up) → negate: -ml_x - // ML y (right) → ARKit x (right) → direct: ml_y - // ML z (backward) → ARKit z (forward) → negate: -ml_z - let translation = SIMD3( - ml_y, // ML y (right) → ARKit x (right) - -ml_x, // ML x (down) → ARKit y (up), so -x - ml_z // ML z (backward) → ARKit z (forward), so -z - ) - - // Transform rotation - let rotation = eulerToQuaternion( - roll: ml_pitch, // Transform coordinate system - pitch: -ml_roll, - yaw: ml_yaw - ) - - // Calculate confidence based on magnitude + // Confidence heuristic: translation magnitude plus rotation magnitude let translationMagnitude = length(translation) - let rotationMagnitude = sqrt(ml_roll * ml_roll + ml_pitch * ml_pitch + ml_yaw * ml_yaw) - let confidence = min(1.0, (translationMagnitude * 10 + rotationMagnitude) / 2.0) // Scale for reasonable confidence + let rotationMagnitude = sqrt(mapped[3] * mapped[3] + mapped[4] * mapped[4] + mapped[5] * mapped[5]) + let confidence = min(1.0, (translationMagnitude * 10 + rotationMagnitude) / 2.0) return (translation, rotation, confidence) } private func createMovementArrow(from: SIMD3, to: SIMD3, confidence: Float, timestamp: TimeInterval) { - guard let arView = arView, let worldOriginAnchor = worldOriginAnchor else { return } + guard let worldOriginAnchor = worldOriginAnchor else { return } DispatchQueue.main.async { [weak self, worldOriginAnchor] in guard let self = self else { return } diff --git a/AnySense/Managers/ActionTransformUtils.swift b/AnySense/Managers/ActionTransformUtils.swift index 632e3de..c15db2d 100644 --- a/AnySense/Managers/ActionTransformUtils.swift +++ b/AnySense/Managers/ActionTransformUtils.swift @@ -2,6 +2,10 @@ import Foundation import simd struct ActionTransformUtils { + enum RotationUnit { + case eulerXYZ // rx, ry, rz (radians) + case axisAngle // rotation vector (axis * angle) + } // Server-defined transforms (record3d → personal camera) and +90° about Z private static let P: simd_float4x4 = { let c0 = SIMD4(-1, 0, 0, 0) @@ -20,29 +24,68 @@ struct ActionTransformUtils { }() // MARK: - Public Entry - // Input: [tx, ty, tz, rx, ry, rz, gripper] in iPhone camera frame (Euler xyz, radians) - // Output: robot-frame [tx, ty, tz, rx, ry, rz, gripper] - static func toRobotActions(_ action7: [Float]) -> [Float] { - guard action7.count >= 7 else { return action7 } - let tx = action7[0], ty = action7[1], tz = action7[2] - let rx = action7[3], ry = action7[4], rz = action7[5] - let gr = action7[6] + // The policy produces an action tensor in its own convention. We first map it into the + // iPhone CAMERA frame (policy→camera), then convert CAMERA→ROBOT to match server logic. + // Input: policy action [tx, ty, tz, r1, r2, r3, gripper] + // Output: robot-frame [tx, ty, tz, rx, ry, rz, gripper] (Euler xyz) + static func toRobotActions(_ policyAction7: [Float], rotationUnit: RotationUnit = .eulerXYZ) -> [Float] { + guard policyAction7.count >= 7 else { return policyAction7 } + let camEulerAction = policyToCameraEulerAction(policyAction7, rotationUnit: rotationUnit) + let gr = camEulerAction[6] - // 1) iPhone action → 4x4 - let T_c = buildTransform(translation: SIMD3(tx, ty, tz), eulerXYZ: SIMD3(rx, ry, rz)) + // 1) CAMERA action → 4x4 + let T_c = buildTransform(translation: SIMD3(camEulerAction[0], camEulerAction[1], camEulerAction[2]), eulerXYZ: SIMD3(camEulerAction[3], camEulerAction[4], camEulerAction[5])) - // 2) Camera → Robot: T_r = Z90 @ (P.T @ T_c @ P) @ Z90.T + // 2) Camera → Robot: T_r = Z90 @ (P.T @ T_c @ P) @ Z90.T (parity with server) let Pt = simd_transpose(P) let Zt = simd_transpose(Z90) let T_perm = Pt * T_c * P let T_r = Z90 * T_perm * Zt - // 3) 4x4 → action (Euler xyz) + // 3) 4x4 → robot action (Euler xyz) let rxyz = eulerXYZ(from: T_r) let t = translation(from: T_r) return [t.x, t.y, t.z, rxyz.x, rxyz.y, rxyz.z, gr] } + + // Policy → CAMERA mapping in a single place so viz and robot stay consistent. + // Convention used here mirrors ARVisualizationManager's historical mapping with a corrected Z sign: + // - policy: [down, right, backward] + // - camera: x=right, y=up, z forward is -Z in ARKit conventions → use z = -backward + static func policyToCameraEulerAction(_ policyAction7: [Float], rotationUnit: RotationUnit = .eulerXYZ, quarterTurns: Int = 0) -> [Float] { + guard policyAction7.count >= 7 else { return policyAction7 } + let ml_x = policyAction7[0] // down + let ml_y = policyAction7[1] // right + let ml_z = policyAction7[2] // backward + let r1 = policyAction7[3] + let r2 = policyAction7[4] + let r3 = policyAction7[5] + let gr = policyAction7[6] + + // Translation mapping + var cam_t = SIMD3(ml_y, -ml_x, -ml_z) + if quarterTurns % 4 != 0 { + cam_t = rotateXY(cam_t, quarterTurns: quarterTurns) + } + + // Rotation mapping → always return Euler xyz in CAMERA frame + var cam_euler: SIMD3 + switch rotationUnit { + case .eulerXYZ: + cam_euler = SIMD3(r1, r2, r3) + case .axisAngle: + let R_cam = rotationMatrixFromAxisAngle(axisAngle: SIMD3(r1, r2, r3)) + cam_euler = eulerXYZ(from: matrixFromRotationAndTranslation(R_cam, t: SIMD3(0,0,0))) + } + if quarterTurns % 4 != 0 { + // Adjust yaw by quarter turns around camera Z + let k = Float(quarterTurns % 4) + cam_euler.z += k * (.pi / 2) + } + + return [cam_t.x, cam_t.y, cam_t.z, cam_euler.x, cam_euler.y, cam_euler.z, gr] + } // MARK: - Builders private static func buildTransform(translation t: SIMD3, eulerXYZ r: SIMD3) -> simd_float4x4 { @@ -55,6 +98,15 @@ struct ActionTransformUtils { return T } + private static func matrixFromRotationAndTranslation(_ R: simd_float3x3, t: SIMD3) -> simd_float4x4 { + var T = matrix_identity_float4x4 + T.columns.0 = SIMD4(R.columns.0.x, R.columns.0.y, R.columns.0.z, 0) + T.columns.1 = SIMD4(R.columns.1.x, R.columns.1.y, R.columns.1.z, 0) + T.columns.2 = SIMD4(R.columns.2.x, R.columns.2.y, R.columns.2.z, 0) + T.columns.3 = SIMD4(t.x, t.y, t.z, 1) + return T + } + // Rotation matrix for Euler 'xyz' (radians) // Using standard formula: // R = [[ cy*cz, -cy*sz, sy ], @@ -83,6 +135,40 @@ struct ActionTransformUtils { return simd_float3x3(columns: (c0, c1, c2)) } + // Axis-angle (rotation vector) → rotation matrix via Rodrigues' formula + private static func rotationMatrixFromAxisAngle(axisAngle v: SIMD3) -> simd_float3x3 { + let theta = sqrt(v.x*v.x + v.y*v.y + v.z*v.z) + let eps: Float = 1e-8 + if theta < eps { + return simd_float3x3(diagonal: SIMD3(1,1,1)) + } + let k = SIMD3(v.x/theta, v.y/theta, v.z/theta) + let K = simd_float3x3(rows: [ + SIMD3( 0, -k.z, k.y), + SIMD3( k.z, 0, -k.x), + SIMD3(-k.y, k.x, 0) + ]) + let I = simd_float3x3(diagonal: SIMD3(1,1,1)) + // R = I + sinθ K + (1 - cosθ) K^2 + let K2 = simd_mul(K, K) + let R = I + sin(theta) * K + (1 - cos(theta)) * K2 + return R + } + + // Rotate a vector in camera XY plane by 90° increments (right-handed, +Z out of screen) + private static func rotateXY(_ v: SIMD3, quarterTurns: Int) -> SIMD3 { + switch ((quarterTurns % 4) + 4) % 4 { // normalize to 0..3 + case 1: // +90° (counterclockwise): (x,y) -> (-y, x) + return SIMD3(-v.y, v.x, v.z) + case 2: // 180° + return SIMD3(-v.x, -v.y, v.z) + case 3: // -90° (clockwise): (x,y) -> (y, -x) + return SIMD3(v.y, -v.x, v.z) + default: + return v + } + } + // Extract Euler 'xyz' (radians) from 4x4 private static func eulerXYZ(from T: simd_float4x4) -> SIMD3 { // Reconstruct row-major elements from column-major storage @@ -121,6 +207,26 @@ struct ActionTransformUtils { private static func clamp(_ v: Float, _ lo: Float, _ hi: Float) -> Float { return max(lo, min(hi, v)) } + + // MARK: - Debug helpers + static func debugTransformReport(_ policyAction7: [Float], rotationUnit: RotationUnit = .eulerXYZ) -> String { + guard policyAction7.count >= 7 else { return "" } + let cam = policyToCameraEulerAction(policyAction7, rotationUnit: rotationUnit) + let T_c = buildTransform(translation: SIMD3(cam[0], cam[1], cam[2]), eulerXYZ: SIMD3(cam[3], cam[4], cam[5])) + let Pt = simd_transpose(P) + let Zt = simd_transpose(Z90) + let T_perm = Pt * T_c * P + let T_r = Z90 * T_perm * Zt + let robotEuler = eulerXYZ(from: T_r) + let robotT = translation(from: T_r) + func fmt(_ f: Float) -> String { String(format: "%.4f", f) } + func fmt3(_ v: SIMD3) -> String { "(\(fmt(v.x)),\(fmt(v.y)),\(fmt(v.z)))" } + return [ + "policy t,r: \(fmt3(SIMD3(policyAction7[0], policyAction7[1], policyAction7[2]))) \(fmt3(SIMD3(policyAction7[3], policyAction7[4], policyAction7[5])))", + "camera (map) t,r_euler: \(fmt3(SIMD3(cam[0], cam[1], cam[2]))) \(fmt3(SIMD3(cam[3], cam[4], cam[5])))", + "robot t,r_euler: \(fmt3(robotT)) \(fmt3(robotEuler))", + ].joined(separator: "\n") + } } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 9d43f7f..b44d108 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -83,6 +83,10 @@ class MLInferenceManager: ObservableObject { } } + // MARK: - Transform/Debug Settings + var rotationUnit: ActionTransformUtils.RotationUnit = .eulerXYZ + var enableTransformDebug: Bool = true + // Initialization init(modelManager: ModelManager) { self.modelManager = modelManager @@ -468,14 +472,61 @@ class MLInferenceManager: ObservableObject { let imageInputName = metadata.getImageInputName() ?? "camera_image" let goalInputName = metadata.getGoalInputName() ?? "goal_point" - // Process image - let imageArray = try processFrameForVQBeT(pixelBuffer, inputSize: metadata.imageInputSize ?? CGSize(width: 256, height: 256)) + // Determine expected image input rank from the actual model description (fallback to 4) + let expectedImageRank: Int = { + if let d = model?.modelDescription.inputDescriptionsByName[imageInputName], + d.type == .multiArray, + let shape = d.multiArrayConstraint?.shape { + return shape.count + } + return 4 + }() + + // Process image to match expected rank (support 4D [1,3,H,W] and 5D [1,1,3,H,W]) + let imageArray = try processFrameForVQBeT( + pixelBuffer, + inputSize: metadata.imageInputSize ?? CGSize(width: 256, height: 256), + expectedRank: expectedImageRank + ) - // Prepare goal point array with batch dimension [1, count] - let goalArray = try MLMultiArray(shape: [1, NSNumber(value: goalPointArray.count)], dataType: .float32) - for (index, value) in goalPointArray.enumerated() { - goalArray[[0, index] as [NSNumber]] = NSNumber(value: value) - } + // Prepare goal array to match model's expected shape when available + let goalArray: MLMultiArray = { + if let d = model?.modelDescription.inputDescriptionsByName[goalInputName], + d.type == .multiArray, + let shape = d.multiArrayConstraint?.shape { + let dims = shape.map { $0.intValue } + if dims.count == 3, let last = dims.last, last == 3 { + // Shape [1,1,3] + let arr = try? MLMultiArray(shape: shape, dataType: .float32) + if let arr = arr { + for i in 0..<3 { arr[[0, 0, i] as [NSNumber]] = NSNumber(value: goalPointArray[i]) } + return arr + } + } else if dims.count == 2, dims == [1,3] { + let arr = try? MLMultiArray(shape: shape, dataType: .float32) + if let arr = arr { + for i in 0..<3 { arr[[0, i] as [NSNumber]] = NSNumber(value: goalPointArray[i]) } + return arr + } + } else if dims.count == 1, dims.first == 3 { + let arr = try? MLMultiArray(shape: shape, dataType: .float32) + if let arr = arr { + for i in 0..<3 { arr[[i] as [NSNumber]] = NSNumber(value: goalPointArray[i]) } + return arr + } + } + } + // Fallback: [1,3] + let arr = try? MLMultiArray(shape: [1, 3], dataType: .float32) + if let arr = arr { + for i in 0..<3 { arr[[0, i] as [NSNumber]] = NSNumber(value: goalPointArray[i]) } + return arr + } + // As last resort, create [3] + let arr3 = try! MLMultiArray(shape: [3], dataType: .float32) + for i in 0..<3 { arr3[[i] as [NSNumber]] = NSNumber(value: goalPointArray[i]) } + return arr3 + }() return try MLDictionaryFeatureProvider(dictionary: [ imageInputName: MLFeatureValue(multiArray: imageArray), @@ -486,11 +537,13 @@ class MLInferenceManager: ObservableObject { private func prepareLegacyInput(_ pixelBuffer: CVPixelBuffer, metadata: ModelMetadata) throws -> MLFeatureProvider { // Simple approach matching old working code - no coordinate transformations let inputArray = try processFrameForInference(pixelBuffer) - return try MLDictionaryFeatureProvider(dictionary: ["x_1": inputArray]) + // Prefer metadata-driven input name if available + let inputName = metadata.getImageInputName() ?? "x_1" + return try MLDictionaryFeatureProvider(dictionary: [inputName: MLFeatureValue(multiArray: inputArray)]) } // MARK: - VQ-BeT Frame Processing - private func processFrameForVQBeT(_ pixelBuffer: CVPixelBuffer, inputSize: CGSize) throws -> MLMultiArray { + private func processFrameForVQBeT(_ pixelBuffer: CVPixelBuffer, inputSize: CGSize, expectedRank: Int) throws -> MLMultiArray { let width = Int(inputSize.width) let height = Int(inputSize.height) @@ -533,12 +586,20 @@ class MLInferenceManager: ObservableObject { ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) - // Convert to MLMultiArray for VQ-BeT format [1, 3, height, width] - return try convertPixelBufferToVQBeTArray(outputBuffer, width: width, height: height) + // Convert to MLMultiArray for VQ-BeT format + // Support 4D [1,3,H,W] and 5D [1,1,3,H,W] + return try convertPixelBufferToVQBeTArray(outputBuffer, width: width, height: height, expectedRank: expectedRank) } - private func convertPixelBufferToVQBeTArray(_ pixelBuffer: CVPixelBuffer, width: Int, height: Int) throws -> MLMultiArray { - let inputArray = try MLMultiArray(shape: [1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) + private func convertPixelBufferToVQBeTArray(_ pixelBuffer: CVPixelBuffer, width: Int, height: Int, expectedRank: Int) throws -> MLMultiArray { + let shape: [NSNumber] + let fiveD = (expectedRank >= 5) + if fiveD { + shape = [1, 1, 3, NSNumber(value: height), NSNumber(value: width)] + } else { + shape = [1, 3, NSNumber(value: height), NSNumber(value: width)] + } + let inputArray = try MLMultiArray(shape: shape, dataType: .float32) guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get pixel buffer base address"]) @@ -556,10 +617,13 @@ class MLInferenceManager: ObservableObject { let g = Float(buffer[offset + 2]) / 255.0 let b = Float(buffer[offset + 3]) / 255.0 - // VQ-BeT format: [batch, channel, height, width] - let rIndex = [NSNumber(value: 0), NSNumber(value: 0), NSNumber(value: y), NSNumber(value: x)] - let gIndex = [NSNumber(value: 0), NSNumber(value: 1), NSNumber(value: y), NSNumber(value: x)] - let bIndex = [NSNumber(value: 0), NSNumber(value: 2), NSNumber(value: y), NSNumber(value: x)] + // VQ-BeT format: either [B, C, H, W] or [B, T, C, H, W] with T=1 + let rIndex = fiveD ? [NSNumber(value: 0), NSNumber(value: 0), NSNumber(value: 0), NSNumber(value: y), NSNumber(value: x)] + : [NSNumber(value: 0), NSNumber(value: 0), NSNumber(value: y), NSNumber(value: x)] + let gIndex = fiveD ? [NSNumber(value: 0), NSNumber(value: 0), NSNumber(value: 1), NSNumber(value: y), NSNumber(value: x)] + : [NSNumber(value: 0), NSNumber(value: 1), NSNumber(value: y), NSNumber(value: x)] + let bIndex = fiveD ? [NSNumber(value: 0), NSNumber(value: 0), NSNumber(value: 2), NSNumber(value: y), NSNumber(value: x)] + : [NSNumber(value: 0), NSNumber(value: 2), NSNumber(value: y), NSNumber(value: x)] inputArray[rIndex] = NSNumber(value: r) inputArray[gIndex] = NSNumber(value: g) @@ -621,6 +685,7 @@ class MLInferenceManager: ObservableObject { // MARK: - Simplified Pixel Buffer to MLMultiArray Conversion private func convertProcessedPixelBufferToMLMultiArray(_ pixelBuffer: CVPixelBuffer) throws -> MLMultiArray { + // Explicitly index as [B=1, T=1, C=3, H=256, W=256] let inputArray = try MLMultiArray(shape: [1, 1, 3, 256, 256], dataType: .float32) guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { @@ -635,17 +700,12 @@ class MLInferenceManager: ObservableObject { for y in 0..<256 { for x in 0..<256 { let offset = y * bytesPerRow + x * bytesPerPixel - - // ARGB format let r = Float(buffer[offset + 1]) / 255.0 - let g = Float(buffer[offset + 2]) / 255.0 + let g = Float(buffer[offset + 2]) / 255.0 let b = Float(buffer[offset + 3]) / 255.0 - - // Store in MLMultiArray format: [batch, channel, rgb, height, width] - let baseIndex = y * 256 + x - inputArray[baseIndex] = NSNumber(value: r) // R channel - inputArray[baseIndex + 256 * 256] = NSNumber(value: g) // G channel - inputArray[baseIndex + 256 * 256 * 2] = NSNumber(value: b) // B channel + inputArray[[0, 0, 0, NSNumber(value: y), NSNumber(value: x)]] = NSNumber(value: r) + inputArray[[0, 0, 1, NSNumber(value: y), NSNumber(value: x)]] = NSNumber(value: g) + inputArray[[0, 0, 2, NSNumber(value: y), NSNumber(value: x)]] = NSNumber(value: b) } } @@ -661,8 +721,8 @@ class MLInferenceManager: ObservableObject { // Simple approach for non-point conditioned models - match old working code if metadata.modelType == .standard { - // Use first available output (matching old code simplicity) - let outputFeatureName = output.featureNames.first + // Prefer primary output name when available + let outputFeatureName = metadata.primaryOutputName ?? output.featureNames.first guard let outputFeatureName = outputFeatureName, let resultArray = output.featureValue(for: outputFeatureName)?.multiArrayValue else { @@ -683,15 +743,20 @@ class MLInferenceManager: ObservableObject { DispatchQueue.main.async { [weak self] in self?.latestResult = result - // Feed pose data to AR visualization with synchronized timestamp + // Ensure visualization is ready and feed pose if let arManager = self?.arVisualizationManager, jointPositions.count >= 6 { + arManager.prepareVisualizationIfNeeded() arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } // Send joint actions to USB if streaming is enabled (transform to robot frame) if jointPositions.count >= 7 { let src = Array(jointPositions.prefix(7)) - let robot = ActionTransformUtils.toRobotActions(src) + if self?.enableTransformDebug == true { + let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) + print(report) + } + let robot = ActionTransformUtils.toRobotActions(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) print("USB send (robot actions): \(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))") self?.sendJointActionsToUSB(robot) } @@ -725,8 +790,9 @@ class MLInferenceManager: ObservableObject { DispatchQueue.main.async { [weak self] in self?.latestResult = result - // Feed pose data to AR visualization with synchronized timestamp + // Ensure visualization is ready and feed pose if let arManager = self?.arVisualizationManager, jointPositions.count >= 6 { + arManager.prepareVisualizationIfNeeded() arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } @@ -756,6 +822,9 @@ class MLInferenceManager: ObservableObject { isInferenceEnabled = true let modelName = modelManager.activeModel?.name ?? "No model" print("Pick Up Policy enabled with model: \(modelName)") + if enableTransformDebug { + print("Transform debug is ENABLED (rotationUnit=\(rotationUnit))") + } } func disableInference() { diff --git a/AnySense/Managers/ModelManager.swift b/AnySense/Managers/ModelManager.swift index 5001d1a..21ea9f0 100644 --- a/AnySense/Managers/ModelManager.swift +++ b/AnySense/Managers/ModelManager.swift @@ -58,12 +58,39 @@ class ModelManager: ObservableObject { availableModels = modelRegistry.models activeModel = modelRegistry.activeModel print("Loaded model registry with \(modelRegistry.models.count) models") + // Validate entries and fix stale active model pointing to removed files + validateAndFixRegistry() } } catch { print("Failed to load model registry: \(error)") modelRegistry = ModelRegistry() } } + + // Remove models whose files no longer exist and fix an invalid active model + private func validateAndFixRegistry() { + // Prune missing files + let original = availableModels + availableModels = availableModels.filter { getModelURL(for: $0) != nil } + if availableModels.count != original.count { + print("Registry cleanup: removed \(original.count - availableModels.count) missing model entries") + } + // Fix active model if missing + if let active = activeModel, getModelURL(for: active) == nil { + print("Active model missing on disk: \(active.name). Selecting a valid model...") + activeModel = nil + } + if activeModel == nil { + if let next = availableModels.first, getModelURL(for: next) != nil { + // Directly set without dispatching to avoid race during init + for i in availableModels.indices { availableModels[i].isActive = availableModels[i].id == next.id } + activeModel = next + modelRegistry.setActiveModel(id: next.id) + print("Switched active model to: \(next.name)") + } + } + saveModelRegistry() + } private func saveModelRegistry() { do { @@ -80,28 +107,34 @@ class ModelManager: ObservableObject { // MARK: - Bundled Model Setup private func setupBundledModel() { - // Check if bundled model already exists in registry - let bundledModelName = "GeneralPickUpV1" - - if !availableModels.contains(where: { $0.source == .bundled && $0.name == bundledModelName }) { - let bundledModel = ModelInfo( - name: bundledModelName, - fileName: "\(bundledModelName).mlmodel", + // Register both standard and point-conditioned bundled models if present + let bundledNames = ["GeneralPickUpV1", "general-pick-up-goal-3-5k-demos"] + var added: [ModelInfo] = [] + for name in bundledNames { + let alreadyExists = availableModels.contains { $0.source == .bundled && $0.name == name } + guard !alreadyExists else { continue } + // Only add if the resource actually exists in the bundle with any supported extension + let presentInBundle = + Bundle.main.url(forResource: name, withExtension: "mlmodelc") != nil || + Bundle.main.url(forResource: name, withExtension: "mlpackage") != nil || + Bundle.main.url(forResource: name, withExtension: "mlmodel") != nil + guard presentInBundle else { continue } + var info = ModelInfo( + name: name, + fileName: "\(name).mlmodel", source: .bundled ) - - var updatedModel = bundledModel - updatedModel.compilationStatus = .compiled - - availableModels.append(updatedModel) - - // Set as active if no active model - if activeModel == nil { - setActiveModel(id: updatedModel.id) + info.compilationStatus = .compiled + availableModels.append(info) + added.append(info) + } + // Set a default active model if none is active yet + if activeModel == nil { + if let preferred = availableModels.first(where: { $0.source == .bundled && $0.name == "GeneralPickUpV1" }) ?? added.first { + setActiveModel(id: preferred.id) } - - saveModelRegistry() } + if !added.isEmpty { saveModelRegistry() } } // MARK: - Model Upload and Compilation @@ -289,33 +322,29 @@ class ModelManager: ObservableObject { switch modelInfo.source { case .bundled: // Try to get from bundle first - if let bundleURL = Bundle.main.url(forResource: modelInfo.name, withExtension: "mlmodel") ?? - Bundle.main.url(forResource: modelInfo.name, withExtension: "mlmodelc") { - return bundleURL + if let url = Bundle.main.url(forResource: modelInfo.name, withExtension: "mlmodelc") ?? + Bundle.main.url(forResource: modelInfo.name, withExtension: "mlpackage") ?? + Bundle.main.url(forResource: modelInfo.name, withExtension: "mlmodel") { + return url } return nil case .uploaded: - // Check for compiled version first (stored in uploaded directory with .mlmodelc extension) - if modelInfo.compilationStatus.isCompiled { - let compiledURL = ModelFileUtilities.uploadedModelsDirectory - .appendingPathComponent("\(modelInfo.name).mlmodel") - .deletingPathExtension() - .appendingPathExtension("mlmodelc") - - if FileManager.default.fileExists(atPath: compiledURL.path) { - return compiledURL - } - } - - // Fall back to uncompiled model + // Prefer compiled .mlmodelc if present + let compiledURL = ModelFileUtilities.uploadedModelsDirectory + .appendingPathComponent("\(modelInfo.name).mlmodelc") + if FileManager.default.fileExists(atPath: compiledURL.path) { return compiledURL } + + // Support .mlpackage in uploaded directory + let packageURL = ModelFileUtilities.uploadedModelsDirectory + .appendingPathComponent("\(modelInfo.name).mlpackage") + if FileManager.default.fileExists(atPath: packageURL.path) { return packageURL } + + // Fallback to .mlmodel let uploadedURL = ModelFileUtilities.uploadedModelsDirectory .appendingPathComponent("\(modelInfo.name).mlmodel") - - if FileManager.default.fileExists(atPath: uploadedURL.path) { - return uploadedURL - } - + if FileManager.default.fileExists(atPath: uploadedURL.path) { return uploadedURL } + return nil } } diff --git a/AnySense/Managers/TransformDebug.swift b/AnySense/Managers/TransformDebug.swift new file mode 100644 index 0000000..583a2ee --- /dev/null +++ b/AnySense/Managers/TransformDebug.swift @@ -0,0 +1,24 @@ +import Foundation +import simd + +struct TransformDebug { + static func runSamples(rotationUnit: ActionTransformUtils.RotationUnit = .eulerXYZ) { + print("===== Transform Debug Samples (rotationUnit=\(rotationUnit)) =====") + let samples: [[Float]] = [ + // [down, right, backward, r1, r2, r3, gripper] + [0.0, 0.0, 0.10, 0.0, 0.0, 0.0, 0.5], // backward (+z in policy) + [0.0, 0.10, 0.00, 0.0, 0.0, 0.0, 0.5], // right + [0.10, 0.0, 0.00, 0.0, 0.0, 0.0, 0.5], // down + [0.0, 0.0, 0.00, 0.10, 0.0, 0.0, 0.5], // roll (or rx axisAngle) + [0.0, 0.0, 0.00, 0.0, 0.10, 0.0, 0.5], // pitch (or ry) + [0.0, 0.0, 0.00, 0.0, 0.0, 0.10, 0.5], // yaw (or rz) + ] + for s in samples { + let report = ActionTransformUtils.debugTransformReport(s, rotationUnit: rotationUnit) + print(report) + print("--------------------------------------------------") + } + } +} + + diff --git a/AnySense/Managers/USBManager.swift b/AnySense/Managers/USBManager.swift index e436789..f9360b5 100644 --- a/AnySense/Managers/USBManager.swift +++ b/AnySense/Managers/USBManager.swift @@ -199,4 +199,22 @@ class USBManager { // Return compressed depth data return Data(bytes: compressedBuffer, count: compressedSize) } + + // MARK: - Joint Actions sender + func sendJointActions(_ jointActionsData: Data) { + guard let activeConnection = activeConnection else { + print("No active connection. Cannot send joint actions.") + return + } + var header = PeerTalkHeader(a: 2, b: 1, c: 1, body_size: UInt32(jointActionsData.count).bigEndian) + let headerData = Data(bytes: &header, count: MemoryLayout.size) + let message = headerData + jointActionsData + activeConnection.send(content: message, completion: .contentProcessed { error in + if let error = error { + print("❌ Failed to send joint actions: \(error)") + } else { + print("✅ Joint actions sent (\(jointActionsData.count) bytes)") + } + }) + } } diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 1b3fd4d..730793c 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -468,7 +468,12 @@ struct ModelImporter: UIViewControllerRepresentable { let onPickDocument: (Result) -> Void func makeUIViewController(context: Context) -> UIDocumentPickerViewController { - let picker = UIDocumentPickerViewController(forOpeningContentTypes: [UTType(filenameExtension: "mlmodel")!]) + let allowedTypes = [ + UTType(filenameExtension: "mlmodel")!, + UTType(filenameExtension: "mlmodelc")!, + UTType(filenameExtension: "mlpackage")! + ] + let picker = UIDocumentPickerViewController(forOpeningContentTypes: allowedTypes) picker.delegate = context.coordinator picker.allowsMultipleSelection = false return picker diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 6d613df..600a0ef 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -197,6 +197,23 @@ struct ReadView : View{ .buttonStyle(scaleButtonStyle(isRecording: $isReading)) } .padding(.bottom, arViewPadding / 4.0 - (buttonSize / 4.0)) + + // Goal tap button - only for point-conditioned models and when not streaming + if appStatus.rgbdVideoStreaming == .off, (arViewModel.mlManager?.isPointConditioned ?? false) { + Button(action: { + // Toggle goal tap mode on ARViewModel + arViewModel.goalTapModeEnabled.toggle() + }) { + Image(systemName: arViewModel.goalTapModeEnabled ? "dot.circle.fill" : "target") + .resizable() + .frame(height: 36) + .frame(width: 36) + .foregroundStyle(arViewModel.goalTapModeEnabled ? Color.green : Color.blue) + } + .padding(.leading, 12) + .padding(.bottom, arViewPadding / 4.0 - (buttonSize / 4.0)) + .help("Tap to set goal in AR view") + } Spacer() } } diff --git a/AnySense/dataStorage.swift b/AnySense/dataStorage.swift index 5c8e01d..0386572 100644 --- a/AnySense/dataStorage.swift +++ b/AnySense/dataStorage.swift @@ -81,16 +81,18 @@ struct MLModelFile: FileDocument { var url: URL static var readableContentTypes: [UTType] { - // Support both .mlmodel and .mlmodelc files + // Support .mlmodel, .mlmodelc, and .mlpackage files [ UTType(filenameExtension: "mlmodel")!, - UTType(filenameExtension: "mlmodelc")! + UTType(filenameExtension: "mlmodelc")!, + UTType(filenameExtension: "mlpackage")! ] } static var writableContentTypes: [UTType] { [ UTType(filenameExtension: "mlmodel")!, - UTType(filenameExtension: "mlmodelc")! + UTType(filenameExtension: "mlmodelc")!, + UTType(filenameExtension: "mlpackage")! ] } @@ -134,7 +136,7 @@ struct SubLevelDirectory: FileDocument{ for content in contents{ if content.pathExtension.lowercased() == "jpeg" || content.pathExtension.lowercased() == "jpg" { self.containedFiles.append(.imageFile(ImageFile(url: content))) - } else if content.pathExtension.lowercased() == "mlmodel" || content.pathExtension.lowercased() == "mlmodelc" { + } else if ["mlmodel","mlmodelc","mlpackage"].contains(content.pathExtension.lowercased()) { self.containedFiles.append(.mlModelFile(MLModelFile(url: content))) } } From 6ef114796268369179600b2fe05382660b0c5062 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Mon, 1 Sep 2025 17:32:57 -0400 Subject: [PATCH 20/56] removed models directory from pbxproj data --- AnySense.xcodeproj/project.pbxproj | 9 --------- 1 file changed, 9 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 03e9004..31747df 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -76,11 +76,6 @@ BA11D17F77459219187F7A30 /* Pods-AnySense.release.xcconfig */ = {isa = PBXFileReference; includeInIndex = 1; lastKnownFileType = text.xcconfig; name = "Pods-AnySense.release.xcconfig"; path = "Target Support Files/Pods-AnySense/Pods-AnySense.release.xcconfig"; sourceTree = ""; }; E98E38A27D08BC9D5BE3E2E6 /* Pods-AnySense.debug.xcconfig */ = {isa = PBXFileReference; includeInIndex = 1; lastKnownFileType = text.xcconfig; name = "Pods-AnySense.debug.xcconfig"; path = "Target Support Files/Pods-AnySense/Pods-AnySense.debug.xcconfig"; sourceTree = ""; }; /* End PBXFileReference section */ - -/* Begin PBXFileSystemSynchronizedRootGroup section */ - 01981E6C2DEA655900773CE6 /* Models */ = {isa = PBXFileSystemSynchronizedRootGroup; explicitFileTypes = {}; explicitFolders = (); path = Models; sourceTree = ""; }; -/* End PBXFileSystemSynchronizedRootGroup section */ - /* Begin PBXFrameworksBuildPhase section */ B9104F572BFDE63A000D4DDD /* Frameworks */ = { isa = PBXFrameworksBuildPhase; @@ -128,7 +123,6 @@ B9104F5C2BFDE63A000D4DDD /* AnySense */ = { isa = PBXGroup; children = ( - 01981E6C2DEA655900773CE6 /* Models */, 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */, 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */, B9944A332CFE982E00232FBB /* MainPage.swift */, @@ -195,9 +189,6 @@ ); dependencies = ( ); - fileSystemSynchronizedGroups = ( - 01981E6C2DEA655900773CE6 /* Models */, - ); name = AnySense; productName = USBInterfaceApp; productReference = B9104F5A2BFDE63A000D4DDD /* AnySense.app */; From def8da8570f882e448abefc8ff19122f2280698d Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Mon, 1 Sep 2025 17:50:52 -0400 Subject: [PATCH 21/56] updated gitignore --- .gitignore | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.gitignore b/.gitignore index 80976e4..195b6a1 100644 --- a/.gitignore +++ b/.gitignore @@ -68,3 +68,5 @@ fastlane/test_output # Models Models/ +AnySense.xcodeproj/project.xcworkspace/xcshareddata/swiftpm/ +AnySense.xcworkspace/xcshareddata/swiftpm/ From 8433a14d422be2093f3c9a39d605d81e40c553ab Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Tue, 2 Sep 2025 13:54:48 -0400 Subject: [PATCH 22/56] added an iphone transform which was missing before, and fixed mobile upload flow; app doesn't package Models at all anymore --- AnySense/Managers/MLInferenceManager.swift | 25 +++++- AnySense/Managers/ModelManager.swift | 95 +++++++++++++--------- AnySense/Views/accountView.swift | 17 ++-- 3 files changed, 88 insertions(+), 49 deletions(-) diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index b44d108..3a81927 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -6,6 +6,7 @@ // import Foundation +import ImageIO import CoreML import Vision import CoreVideo @@ -86,6 +87,8 @@ class MLInferenceManager: ObservableObject { // MARK: - Transform/Debug Settings var rotationUnit: ActionTransformUtils.RotationUnit = .eulerXYZ var enableTransformDebug: Bool = true + // Apply server-style image orientation (Record3D publisher does rotations/mirrors) + var applyServerImageOrientation: Bool = true // Initialization init(modelManager: ModelManager) { @@ -581,7 +584,11 @@ class MLInferenceManager: ObservableObject { let scaleY = inputSize.height / inputImageSize.height let scaleTransform = CGAffineTransform(scaleX: scaleX, y: scaleY) - let scaledImage = inputImage.transformed(by: scaleTransform) + var scaledImage = inputImage.transformed(by: scaleTransform) + if applyServerImageOrientation { + // Server path rotates images by 180° overall; replicate using EXIF .down + scaledImage = scaledImage.oriented(.down) + } let cropRect = CGRect(origin: .zero, size: inputSize) ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) @@ -673,7 +680,10 @@ class MLInferenceManager: ObservableObject { let scaleY = modelInputSize.height / inputSize.height let scaleTransform = CGAffineTransform(scaleX: scaleX, y: scaleY) - let scaledImage = inputImage.transformed(by: scaleTransform) + var scaledImage = inputImage.transformed(by: scaleTransform) + if applyServerImageOrientation { + scaledImage = scaledImage.oriented(.down) + } let cropRect = CGRect(origin: .zero, size: modelInputSize) // Render using the same CIContext approach as ARViewContainer @@ -756,7 +766,11 @@ class MLInferenceManager: ObservableObject { let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) print(report) } - let robot = ActionTransformUtils.toRobotActions(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) + var robot = ActionTransformUtils.toRobotActions(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) + // Clamp gripper to [0,1] + if robot.count >= 7 { + robot[6] = max(0.0, min(1.0, robot[6])) + } print("USB send (robot actions): \(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))") self?.sendJointActionsToUSB(robot) } @@ -799,7 +813,10 @@ class MLInferenceManager: ObservableObject { // Send joint actions to USB if streaming is enabled (transform to robot frame) if jointPositions.count >= 7 { let src = Array(jointPositions.prefix(7)) - let robot = ActionTransformUtils.toRobotActions(src) + var robot = ActionTransformUtils.toRobotActions(src) + if robot.count >= 7 { + robot[6] = max(0.0, min(1.0, robot[6])) + } print("USB send (robot actions): \(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))") self?.sendJointActionsToUSB(robot) } diff --git a/AnySense/Managers/ModelManager.swift b/AnySense/Managers/ModelManager.swift index 21ea9f0..438ca4c 100644 --- a/AnySense/Managers/ModelManager.swift +++ b/AnySense/Managers/ModelManager.swift @@ -157,29 +157,47 @@ class ModelManager: ObservableObject { print("DEBUG: Processing file from: \(sourceURL.path)") - // Generate model name + // Generate model name (strip known extensions) let fileName = sourceURL.lastPathComponent - let modelName = customName ?? fileName.replacingOccurrences(of: ".mlmodel", with: "") + let ext = sourceURL.pathExtension.lowercased() + let baseName = sourceURL.deletingPathExtension().lastPathComponent + let modelName = customName ?? baseName // Check for duplicate names if availableModels.contains(where: { $0.name == modelName }) { throw ModelError.duplicateName("A model with this name already exists") } - // Copy to our app's permanent storage WHILE we have access - let localModelURL = try ModelFileUtilities.copyUploadedModel(from: sourceURL, withName: modelName) - print("DEBUG: Copied to local storage: \(localModelURL.path)") + // Decide import strategy by extension + let fm = FileManager.default + let uploadsDir = ModelFileUtilities.uploadedModelsDirectory + var fileSize: Int64 = 0 + var finalCompiledURL: URL? = nil + var localModelURL: URL? = nil - // Basic file validation (check extension and file exists) - guard localModelURL.pathExtension.lowercased() == "mlmodel" else { - throw ModelError.invalidFile("File must have .mlmodel extension") + switch ext { + case "mlmodel": + // Copy raw .mlmodel and compile + let local = try ModelFileUtilities.copyUploadedModel(from: sourceURL, withName: modelName) + localModelURL = local + print("DEBUG: Copied .mlmodel to local storage: \(local.path)") + guard fm.fileExists(atPath: local.path) else { throw ModelError.modelNotFound("Copied file does not exist") } + fileSize = MLModel.getModelSize(at: local) + case "mlpackage": + // Compile the .mlpackage directly from sourceURL (no need to copy the whole package first) + localModelURL = sourceURL + fileSize = MLModel.getModelSize(at: sourceURL) + case "mlmodelc": + // Already compiled; copy as-is into uploads directory with normalized name + let dest = uploadsDir.appendingPathComponent("\(modelName).mlmodelc") + if fm.fileExists(atPath: dest.path) { try fm.removeItem(at: dest) } + try fm.copyItem(at: sourceURL, to: dest) + finalCompiledURL = dest + fileSize = MLModel.getModelSize(at: dest) + print("DEBUG: Copied compiled model (.mlmodelc) to: \(dest.path)") + default: + throw ModelError.invalidFile("Unsupported file type. Use .mlmodel, .mlpackage, or .mlmodelc") } - - guard FileManager.default.fileExists(atPath: localModelURL.path) else { - throw ModelError.modelNotFound("Copied file does not exist") - } - - let fileSize = MLModel.getModelSize(at: localModelURL) let modelUploadDate = Date() // Use current date as upload date @@ -198,35 +216,32 @@ class ModelManager: ObservableObject { saveModelRegistry() } - // Compile the local model (this will fail if model is invalid) - let tempCompiledURL = try await MLModel.compileModel(at: localModelURL) { [weak self] progress in - DispatchQueue.main.async { - self?.compilationProgress = progress - } - } - - print("DEBUG: Compiled to temp location: \(tempCompiledURL.path)") - - // Now validate the compiled model for compatibility - do { - let metadata = try MLModel.validateModel(at: tempCompiledURL) - guard metadata.isCompatible else { - throw ModelError.incompatibleModel("Model format not compatible with app requirements") + // If we imported a raw .mlmodel, compile it now + if (ext == "mlmodel" || ext == "mlpackage"), let local = localModelURL { + let tempCompiledURL = try await MLModel.compileModel(at: local) { [weak self] progress in + DispatchQueue.main.async { self?.compilationProgress = progress } } - print("DEBUG: Model validation passed") - } catch { - print("DEBUG: Model validation warning: \(error.localizedDescription)") - // Continue anyway - some models might work even if validation reports issues + print("DEBUG: Compiled to temp location: \(tempCompiledURL.path)") + // Validate compiled + do { + let metadata = try MLModel.validateModel(at: tempCompiledURL) + guard metadata.isCompatible else { throw ModelError.incompatibleModel("Model format not compatible with app requirements") } + print("DEBUG: Model validation passed") + } catch { print("DEBUG: Model validation warning: \(error.localizedDescription)") } + // Move compiled to uploads dir + finalCompiledURL = try ModelFileUtilities.replaceCompiledModel( + compiledURL: tempCompiledURL, + withName: modelName + ) + print("DEBUG: Final compiled location: \(finalCompiledURL!.path)") + } else if let compiled = finalCompiledURL { + // Validate mlpackage/mlmodelc directly + do { + let metadata = try MLModel.validateModel(at: compiled) + print("DEBUG: Direct model validation: compatible=\(metadata.isCompatible)") + } catch { print("DEBUG: Model validation warning: \(error.localizedDescription)") } } - // Move compiled model to permanent location using best practices - let finalCompiledURL = try ModelFileUtilities.replaceCompiledModel( - compiledURL: tempCompiledURL, - withName: modelName - ) - - print("DEBUG: Final compiled location: \(finalCompiledURL.path)") - // Update model status let modelId = modelInfo.id diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 730793c..83bb25d 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -468,11 +468,18 @@ struct ModelImporter: UIViewControllerRepresentable { let onPickDocument: (Result) -> Void func makeUIViewController(context: Context) -> UIDocumentPickerViewController { - let allowedTypes = [ - UTType(filenameExtension: "mlmodel")!, - UTType(filenameExtension: "mlmodelc")!, - UTType(filenameExtension: "mlpackage")! - ] + // Prefer system-declared UTIs; fall back to filename extensions for safety + let mlmodel = UTType(importedAs: "com.apple.coreml.model") + let mlpackage = UTType(importedAs: "com.apple.coreml.modelpackage") + // Compiled model UTI name varies by SDK; use a broad fallback as well + let mlmodelc = UTType(importedAs: "com.apple.coreml.compiled-model") + + var allowedTypes: [UTType] = [mlmodel, mlpackage, mlmodelc, .package, .data, .item] + // Add filename-extension fallbacks to catch older devices + if let byExt1 = UTType(filenameExtension: "mlmodel") { allowedTypes.append(byExt1) } + if let byExt2 = UTType(filenameExtension: "mlmodelc") { allowedTypes.append(byExt2) } + if let byExt3 = UTType(filenameExtension: "mlpackage") { allowedTypes.append(byExt3) } + let picker = UIDocumentPickerViewController(forOpeningContentTypes: allowedTypes) picker.delegate = context.coordinator picker.allowsMultipleSelection = false From eeec97399ad526448fb98d907cb6a01cccec766b Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Wed, 3 Sep 2025 13:34:05 -0400 Subject: [PATCH 23/56] fixed ux issues --- AnySense/Views/accountView.swift | 126 +------------------------------ AnySense/Views/readView.swift | 52 +++++++++---- 2 files changed, 38 insertions(+), 140 deletions(-) diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 83bb25d..007dc86 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -19,8 +19,6 @@ struct SettingsView : View{ @State private var showingFilePicker = false @State private var showingAlert = false @State private var alertMessage = "" - @State private var showingDeleteConfirmation = false - @State private var modelToDelete: ModelInfo? // Track current frequency for UI updates @State private var currentFrequencyIndex: Int = 1 @@ -160,111 +158,11 @@ struct SettingsView : View{ .id(modelManager.activeModelID?.uuidString ?? "none") // Force refresh when activeModel changes } - // Active Model Info - if let activeModel = modelManager.activeModel { - VStack(alignment: .leading, spacing: 8) { - HStack { - Text("Current Model:") - .font(.body) - .foregroundColor(.primary) - Spacer() - Text(activeModel.displayName) - .font(.body) - .fontWeight(.medium) - .foregroundColor(.blue) - } - - HStack { - Text("Status:") - .font(.caption) - .foregroundColor(.gray) - Spacer() - Text(activeModel.statusDescription) - .font(.caption) - .foregroundColor(activeModel.compilationStatus.isCompiled ? .green : .orange) - } - - HStack { - Text("Uploaded:") - .font(.caption) - .foregroundColor(.gray) - Spacer() - Text(activeModel.uploadDate.formatted(date: .abbreviated, time: .omitted)) - .font(.caption) - .foregroundColor(.gray) - } - - if activeModel.source == .uploaded && activeModel.fileSize > 0 { - HStack { - Text("Size:") - .font(.caption) - .foregroundColor(.gray) - Spacer() - Text(ByteCountFormatter.string(fromByteCount: activeModel.fileSize, countStyle: .file)) - .font(.caption) - .foregroundColor(.gray) - } - } - } - .padding(.vertical, 5) - } - // Uploaded Models Management - let uploadedModels = modelManager.availableModels.filter { $0.source == .uploaded } - if !uploadedModels.isEmpty { - VStack(alignment: .leading, spacing: 8) { - Text("Uploaded Models") - .font(.body) - .foregroundColor(.primary) - - ForEach(uploadedModels) { model in - HStack { - VStack(alignment: .leading, spacing: 2) { - Text(model.name) - .font(.caption) - .fontWeight(.medium) - Text(model.statusDescription) - .font(.caption2) - .foregroundColor(model.compilationStatus.isCompiled ? .green : .orange) - Text(model.uploadDate.formatted(date: .abbreviated, time: .omitted)) - .font(.caption2) - .foregroundColor(.gray) - } - - Spacer() - - if model.isActive { - Text("Active") - .font(.caption2) - .padding(.horizontal, 6) - .padding(.vertical, 2) - .background(Color.green.opacity(0.2)) - .foregroundColor(.green) - .cornerRadius(4) - } else if model.compilationStatus.isCompiled { - Button("Activate") { - modelManager.setActiveModel(id: model.id) - } - .foregroundColor(.blue) - .font(.caption) - } - - Button("Delete") { - modelToDelete = model - showingDeleteConfirmation = true - } - .foregroundColor(.red) - .font(.caption) - } - .padding(.vertical, 2) - } - } - .padding(.vertical, 5) - } - // Use Policy Toggle - Context Aware + // Use Inference Toggle - Context Aware HStack { - Text("Use Policy") + Text("Use Inference") .font(.body) .foregroundColor(.primary) Spacer() @@ -402,16 +300,6 @@ struct SettingsView : View{ } message: { Text(alertMessage) } - .alert("Delete Model", isPresented: $showingDeleteConfirmation) { - Button("Cancel", role: .cancel) { } - Button("Delete", role: .destructive) { - if let model = modelToDelete { - deleteModel(model) - } - } - } message: { - Text("Are you sure you want to delete '\(modelToDelete?.name ?? "")'? This action cannot be undone.") - } } // MARK: - Model Upload Handling @@ -440,16 +328,6 @@ struct SettingsView : View{ } } - private func deleteModel(_ model: ModelInfo) { - do { - try modelManager.deleteModel(id: model.id) - alertMessage = "Model '\(model.name)' deleted successfully." - showingAlert = true - } catch { - alertMessage = "Failed to delete model: \(error.localizedDescription)" - showingAlert = true - } - } } enum StreamingMode: String { diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 600a0ef..eb9efeb 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -173,7 +173,24 @@ struct ReadView : View{ VStack { Spacer() HStack { + // Flashlight column (left) + if appStatus.rgbdVideoStreaming == .off { + VStack(spacing: 4) { + Button(action: toggleFlash) { + Image(systemName: openFlash ? "flashlight.off.circle.fill" : "flashlight.on.circle.fill") + .resizable() + .frame(height: 36) + .frame(width: 36) + } + Text(openFlash ? "Flash off" : "Flash on") + .font(.caption) + .foregroundColor(.secondary) + } + } + Spacer() + + // Record button (center) ZStack{ Image(systemName: "circle") .resizable() @@ -196,26 +213,29 @@ struct ReadView : View{ } .buttonStyle(scaleButtonStyle(isRecording: $isReading)) } - .padding(.bottom, arViewPadding / 4.0 - (buttonSize / 4.0)) - - // Goal tap button - only for point-conditioned models and when not streaming + + Spacer() + + // Goal button + caption (right) if appStatus.rgbdVideoStreaming == .off, (arViewModel.mlManager?.isPointConditioned ?? false) { - Button(action: { - // Toggle goal tap mode on ARViewModel - arViewModel.goalTapModeEnabled.toggle() - }) { - Image(systemName: arViewModel.goalTapModeEnabled ? "dot.circle.fill" : "target") - .resizable() - .frame(height: 36) - .frame(width: 36) - .foregroundStyle(arViewModel.goalTapModeEnabled ? Color.green : Color.blue) + VStack(spacing: 4) { + Button(action: { + arViewModel.goalTapModeEnabled.toggle() + }) { + Image(systemName: arViewModel.goalTapModeEnabled ? "dot.circle.fill" : "target") + .resizable() + .frame(height: 36) + .frame(width: 36) + .foregroundStyle(arViewModel.goalTapModeEnabled ? Color.green : Color.blue) + } + Text("Set goal") + .font(.caption) + .foregroundColor(.secondary) } - .padding(.leading, 12) - .padding(.bottom, arViewPadding / 4.0 - (buttonSize / 4.0)) - .help("Tap to set goal in AR view") } - Spacer() } + .padding(.horizontal, 20) + .padding(.bottom, arViewPadding / 4.0 - (buttonSize / 4.0)) } From 8f4c93fad16387e58ebd5fc2f6d3e40ec1163a8d Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Thu, 4 Sep 2025 12:06:32 -0400 Subject: [PATCH 24/56] removed differences in usb streaming mode on/off --- AnySense/Managers/ARViewContainer.swift | 76 +---- .../Managers/ARVisualizationManager.swift | 18 +- AnySense/Managers/BluetoothManager.swift | 47 +-- AnySense/Managers/MLInferenceManager.swift | 61 ++-- AnySense/Managers/OdometryPointTracker.swift | 25 +- AnySense/Managers/USBManager.swift | 38 +-- AnySense/Views/readView.swift | 299 +++++++----------- 7 files changed, 186 insertions(+), 378 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 78e49fd..9df3cb2 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -249,7 +249,6 @@ class ARViewModel: ObservableObject{ private func setupAudioSession() { guard let audioDevice = AVCaptureDevice.default(for: .audio), let audioDeviceInput = try? AVCaptureDeviceInput(device: audioDevice) else { - print("Unable to access microphone.") return } audioSession.addInput(audioDeviceInput) @@ -277,20 +276,16 @@ class ARViewModel: ObservableObject{ if !self.depthStatus.isDepthAvailable { break } - if self.combinedDepthTransform == nil { - if self.initializeDepthTransform(frame: currentFrame, flipTransform: flipTransform) { - break - } - } - - self.depthRetryCount += 1 - usleep(10000) - } - - if self.combinedDepthTransform == nil { - print("Depth initialization failed after \(self.maxDepthRetries) attempts.") + if self.combinedDepthTransform == nil { + if self.initializeDepthTransform(frame: currentFrame, flipTransform: flipTransform) { + break } } + + self.depthRetryCount += 1 + usleep(10000) + } + } } private func initializeRGBTransform(frame: ARFrame, flipTransform: CGAffineTransform) { @@ -308,7 +303,6 @@ class ARViewModel: ObservableObject{ private func initializeDepthTransform(frame: ARFrame, flipTransform: CGAffineTransform) -> Bool { guard let depthPixelBuffer = frame.sceneDepth?.depthMap else { - print("Depth map unavailable. Retrying (\(self.depthRetryCount)/\(self.maxDepthRetries))") return false } let depthSize = CGSize(width: CVPixelBufferGetWidth(depthPixelBuffer), height: CVPixelBufferGetHeight(depthPixelBuffer)) @@ -333,14 +327,11 @@ class ARViewModel: ObservableObject{ } setupTransforms() - - print("Finished setting up ARViewModel.") } func startARSession() { let status = AVCaptureDevice.authorizationStatus(for: .video) guard status == .authorized else { - print("Camera permissions not granted.") return } // Create and configure the AR session configuration @@ -349,11 +340,8 @@ class ARViewModel: ObservableObject{ // Loop through available video formats and select the wide-angle camera format for videoFormat in ARWorldTrackingConfiguration.supportedVideoFormats { if videoFormat.captureDeviceType == .builtInWideAngleCamera { - print("Wide-angle camera selected: \(videoFormat)") configuration.videoFormat = videoFormat break - } else { - print("Unsupported video format: \(videoFormat.captureDeviceType)") } } @@ -370,7 +358,6 @@ class ARViewModel: ObservableObject{ // Run the session with the configuration session.run(configuration, options: [.resetTracking, .removeExistingAnchors]) - print("Starting session") isOpen = true } @@ -383,7 +370,6 @@ class ARViewModel: ObservableObject{ session.pause() // Pause before releasing resources session = ARSession() // Replace with a new ARSession isOpen = false - print("ARSession killed and reset.") } func startUSBStreaming() { @@ -409,7 +395,6 @@ class ARViewModel: ObservableObject{ &rgbBuffer ) guard status == kCVReturnSuccess else { - print("Failed to create CVPixelBuffer") return } self.rgbOutputPixelBufferUSB = rgbBuffer @@ -428,7 +413,6 @@ class ARViewModel: ObservableObject{ ) guard depthStatus == kCVReturnSuccess else { - print("Failed to create CVPixelBuffer") return } self.depthOutputPixelBufferUSB = depthBuffer @@ -442,13 +426,11 @@ class ARViewModel: ObservableObject{ &depthConfidenceBuffer ) guard depthConfidenceStatus == kCVReturnSuccess else { - print("Failed to create CVPixelBuffer") return } self.depthConfidenceOutputPixelBufferUSB = depthConfidenceBuffer } - print("Made all USB Buffers") usbManager.connect() } @@ -585,11 +567,9 @@ class ARViewModel: ObservableObject{ if let latestJointActions = self.mlManager?.latestResult?.jointPositions, !latestJointActions.isEmpty { // Use actual ML inference results, ensure exactly 7 values jointActionsArray = Array(latestJointActions.prefix(7)) + Array(repeating: 0.0, count: max(0, 7 - latestJointActions.count)) - print("Streaming ML joint actions: [\(jointActionsArray.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") } else { // Fallback to zeros if no ML results available jointActionsArray = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] - print("No ML results available, streaming zero joint actions") } // Convert to exactly 28 bytes (7 floats * 4 bytes each) @@ -663,19 +643,17 @@ class ARViewModel: ObservableObject{ assetWriter?.finishWriting { self.assetWriter = nil - print("RGB Video recording finished.") } depthVideoInput?.markAsFinished() depthAssetWriter?.finishWriting { self.depthAssetWriter = nil - print("Depth Video recording finished.") } do { try poseFileHandle?.close() } catch { - print("Error closing pose file") + // Error closing pose file - continue cleanup } updateDemoCounter() @@ -697,7 +675,6 @@ class ARViewModel: ObservableObject{ ] guard let documentsURL = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask).first else { - print("Failed to get document directory") return nil } @@ -716,7 +693,7 @@ class ARViewModel: ObservableObject{ } try createFile(fileURL: poseTextURL) } catch { - print("Error creating directories") + // Error creating directories - continue with setup } self.rgbDirect = rgbImagesDirectory @@ -771,7 +748,7 @@ class ARViewModel: ObservableObject{ self.poseFileHandle = try FileHandle(forWritingTo: poseTextURL) try poseFileHandle?.seekToEnd() } catch { - print("Failed to setup recording: \(error)") + // Failed to setup recording - continue with available configuration } return RecordingFiles( @@ -810,7 +787,7 @@ class ARViewModel: ObservableObject{ sourcePixelBufferAttributes: recordingDepthAttributes ) } catch { - print("Failed to setup depth recording: \(error)") + // Failed to setup depth recording - continue without depth } } @@ -830,14 +807,10 @@ class ARViewModel: ObservableObject{ self.ciContext.render(transformedImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) guard let pixelBufferAdapter = self.pixelBufferAdapter else { - print("Failed to append RGB pixel buffer: Pixel buffer adapter is nil.") return false } if !pixelBufferAdapter.append(outputBuffer, withPresentationTime: currentTime) { - let isReady = pixelBufferAdapter.assetWriterInput.isReadyForMoreMediaData - let writerError = self.assetWriter?.error?.localizedDescription ?? "Unknown asset writer error." - print("Failed to append RGB pixel buffer. Adapter state: \(isReady), Time: \(currentTime), Error: \(writerError)") return false } CVPixelBufferUnlockBaseAddress(outputBuffer, []) @@ -849,14 +822,12 @@ class ARViewModel: ObservableObject{ guard let depthVideoInput = self.depthVideoInput, depthVideoInput.isReadyForMoreMediaData else { return false } guard let depthPixelBuffer = depthPixelBuffer else { return false } guard let pixelBufferPool = self.depthPixelBufferAdapter?.pixelBufferPool else { - print("Depth pixel buffer pool is nil.") return false } var outputPixelBuffer: CVPixelBuffer? let status = CVPixelBufferPoolCreatePixelBuffer(nil, pixelBufferPool, &outputPixelBuffer) guard status == kCVReturnSuccess, let depthOutputBuffer = outputPixelBuffer else { - print("Unable to create output pixel buffer for depth.") return false } @@ -876,14 +847,10 @@ class ARViewModel: ObservableObject{ ) guard let depthPixelBufferAdapter = self.depthPixelBufferAdapter else { - print("Failed to append depth pixel buffer: Pixel buffer adapter is nil.") return false } if !depthPixelBufferAdapter.append(depthOutputBuffer, withPresentationTime: currentTime) { - let isReady = depthPixelBufferAdapter.assetWriterInput.isReadyForMoreMediaData - let writerError = self.depthAssetWriter?.error?.localizedDescription ?? "Unknown asset writer error." - print("❌ Failed to append RGB pixel buffer. Adapter state: \(isReady), Time: \(currentTime), Error: \(writerError)") return false } CVPixelBufferUnlockBaseAddress(depthOutputBuffer, []) @@ -909,7 +876,7 @@ class ARViewModel: ObservableObject{ try self.poseFileHandle?.write(contentsOf: data) } } catch { - print("❌ Error writing pose data: \(error)") + // Error writing pose data - continue capture } } @@ -924,8 +891,6 @@ class ARViewModel: ObservableObject{ if let outputImage = depthFilter.outputImage { filteredImage = outputImage - } else { - print("❌ Failed to apply color controls filter to depth image.") } if(self.isColorMapOpened){ @@ -935,8 +900,6 @@ class ARViewModel: ObservableObject{ falseColorFilter.inputImage = filteredImage if let outputImage = falseColorFilter.outputImage { filteredImage = outputImage - } else { - print("❌ Failed to apply false color filter to depth image.") } } return filteredImage.transformed(by: self.combinedDepthTransform ?? CGAffineTransform.identity) //.cropped(to: cropRect) @@ -961,7 +924,7 @@ class ARViewModel: ObservableObject{ do { try data.write(to: fileURL) } catch { - print("Error saving binary file: \(error)") + // Error saving binary file - continue capture } } @@ -1008,7 +971,6 @@ class ARViewModel: ObservableObject{ func getDocumentsDirect() -> URL{ let paths = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask) - print(paths[0].path) return paths[0] } @@ -1016,11 +978,9 @@ class ARViewModel: ObservableObject{ let documentsURL = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask) do{ let contents = try FileManager.default.contentsOfDirectory(at: documentsURL[0], includingPropertiesForKeys: [.isDirectoryKey], options: [.skipsHiddenFiles, .skipsSubdirectoryDescendants]) - print(contents.count) demosCounter = contents.count - print(demosCounter) } catch { - print("Error reading directory contents: \(error)") + demosCounter = 0 } } @@ -1034,11 +994,6 @@ class ARViewModel: ObservableObject{ self.mlManager?.setARViewContainer(self) // ML results are now accessed directly during streaming for better real-time performance - - print("Initialized ML Inference Manager with Model Manager") - print("Connected AR Visualization Manager to ML Inference") - print("Connected ML Results to USB Streaming") - print("🔗 ML-AR Connection: \(self.mlManager?.arVisualizationManager != nil ? "✅ Connected" : "❌ Failed")") } } @@ -1053,7 +1008,6 @@ class AudioCaptureDelegate: NSObject, AVCaptureAudioDataOutputSampleBufferDelega func captureOutput(_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer, from connection: AVCaptureConnection) { // Append audio sample buffer to the writer input guard writerInput?.isReadyForMoreMediaData == true else { - print("Not ready") return } writerInput?.append(sampleBuffer) diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index fffcfd2..023a8a0 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -230,7 +230,7 @@ class ARVisualizationManager: ObservableObject { // Apply frequency throttling if timestamp - lastVisualizationTime < visualizationFrequency.interval { if debugLoggingEnabled { - print("[Viz] throttled (\(timestamp - lastVisualizationTime)s < \(visualizationFrequency.interval)s)") + // Visualization throttled } return } @@ -259,9 +259,7 @@ class ARVisualizationManager: ObservableObject { ) let deltaTranslation = rotationWorldFromCamera * cameraDeltaTranslation - print("📱 ML input (x=down,y=right,z=back): (\(String(format: "%.3f", jointActions[0])), \(String(format: "%.3f", jointActions[1])), \(String(format: "%.3f", jointActions[2])))") - print("📲 Delta movement (x=right,y=up,z=forward): (\(String(format: "%.3f", deltaTranslation.x)), \(String(format: "%.3f", deltaTranslation.y)), \(String(format: "%.3f", deltaTranslation.z)))") - print("🎯 Confidence: \(String(format: "%.2f", confidence))") + // ML coordinate transform applied // Update position tracking let previousPosition = currentWorldPosition @@ -269,9 +267,7 @@ class ARVisualizationManager: ObservableObject { // Only create movement arrow if there's meaningful movement and we have a previous position let movementMagnitude = length(deltaTranslation) - if debugLoggingEnabled { - print("[Viz] camera delta=\(cameraDeltaTranslation), world delta=\(deltaTranslation), mag=\(movementMagnitude)") - } + // Movement magnitude calculated if movementMagnitude > 0.005 || debugAlwaysDrawArrow { // draw even if tiny in debug createMovementArrow( from: previousPosition, @@ -281,7 +277,7 @@ class ARVisualizationManager: ObservableObject { ) } - print("🎯 Position updated: \(String(format: "(%.3f,%.3f,%.3f)", currentWorldPosition.x, currentWorldPosition.y, currentWorldPosition.z)) → moved \(String(format: "%.3f", movementMagnitude))m") + // Position updated with movement delta } private func interpretMLDirections(_ jointActions: [Float]) -> (translation: SIMD3, rotation: simd_quatf, confidence: Float) { @@ -359,7 +355,7 @@ class ARVisualizationManager: ObservableObject { oldArrow.entity.removeFromParent() } - print("🏹 Movement arrow: from=\(String(format: "(%.3f,%.3f,%.3f)", from.x, from.y, from.z)) to=\(String(format: "(%.3f,%.3f,%.3f)", to.x, to.y, to.z)) move=\(String(format: "%.3f", movementMagnitude))m") + // Movement arrow created } } @@ -442,9 +438,7 @@ class ARVisualizationManager: ObservableObject { } } - if !expiredArrows.isEmpty { - print("Cleaned up \(expiredArrows.count) expired movement arrows") - } + // Clean up expired arrows } private func eulerToQuaternion(roll: Float, pitch: Float, yaw: Float) -> simd_quatf { diff --git a/AnySense/Managers/BluetoothManager.swift b/AnySense/Managers/BluetoothManager.swift index 04e84a9..72a6928 100644 --- a/AnySense/Managers/BluetoothManager.swift +++ b/AnySense/Managers/BluetoothManager.swift @@ -39,7 +39,7 @@ class BluetoothManager : NSObject, ObservableObject{ centralManager?.stopScan() centralManager = nil - print("BluetoothManager deinitialized and cleaned up") + // BluetoothManager deinitialized } } @@ -47,20 +47,19 @@ extension BluetoothManager: CBCentralManagerDelegate{ func centralManagerDidUpdateState(_ central: CBCentralManager) { switch central.state { case .poweredOff: - print("Is Powered Off.") + break case .poweredOn: - print("Is Powered On.") self.scan() case .unsupported: - print("Is Unsupported.") + break case .unauthorized: - print("Is Unauthorized.") + break case .unknown: - print("Unknown") + break case .resetting: - print("Resetting") + break @unknown default: - print("Error") + break } } func scan() -> Void{ @@ -106,7 +105,6 @@ extension BluetoothManager: CBCentralManagerDelegate{ // Disconnect if already connected to another peripheral if let currentPeripheral = matchedPeripheral, currentPeripheral.identifier != peripheral.identifier { - print("🔄 Disconnecting previous peripheral: \(currentPeripheral.name ?? "Unknown")") central.cancelPeripheralConnection(currentPeripheral) } @@ -143,10 +141,7 @@ extension BluetoothManager: CBCentralManagerDelegate{ extension BluetoothManager: CBPeripheralDelegate{ func peripheral(_ peripheral: CBPeripheral, didDiscoverServices error: Error?) { - print("*******************************************************") - if ((error) != nil) { - print("Error discovering services: \(error!.localizedDescription)") return } guard let services = peripheral.services else { @@ -156,7 +151,6 @@ extension BluetoothManager: CBPeripheralDelegate{ for service in services { peripheral.discoverCharacteristics(nil, for: service) } - print("Discovered Services: \(services)") } func peripheral(_ peripheral: CBPeripheral, didDiscoverCharacteristicsFor service: CBService, error: Error?) { @@ -164,27 +158,18 @@ extension BluetoothManager: CBPeripheralDelegate{ return } - print("Found \(characteristics.count) characteristics.") - // NOTE: We will simply take the first Rx characteristic and use it for reading for characteristic in characteristics { if characteristic.properties.contains(.notify) || characteristic.properties.contains(.indicate) { - print("This characteristic is Rx (Receiving data)") rxCharacteristic = characteristic peripheral.setNotifyValue(true, for: rxCharacteristic!) peripheral.readValue(for: characteristic) - print("RX Characteristic: \(rxCharacteristic.uuid)") break } - if characteristic.properties.contains(.write) || characteristic.properties.contains(.writeWithoutResponse) { - print("This characteristic is Tx (Transmitting data)") - // TODO: Code for handling Tx characteristics goes here - } } } func peripheral(_ peripheral: CBPeripheral, didUpdateValueFor characteristic: CBCharacteristic, error: Error?) { if let error = error { - print("Error updating characteristic: \(error.localizedDescription)") return } } @@ -196,19 +181,19 @@ extension BluetoothManager: CBPeripheralManagerDelegate { func peripheralManagerDidUpdateState(_ peripheral: CBPeripheralManager) { switch peripheral.state { case .poweredOn: - print("Peripheral Is Powered On.") + break case .unsupported: - print("Peripheral Is Unsupported.") + break case .unauthorized: - print("Peripheral Is Unauthorized.") + break case .unknown: - print("Peripheral Unknown") + break case .resetting: - print("Peripheral Resetting") + break case .poweredOff: - print("Peripheral Is Powered Off.") + break @unknown default: - print("Error") + break } } @@ -219,7 +204,7 @@ extension BluetoothManager: CBPeripheralManagerDelegate { try self.BTFileHandle?.seekToEnd() } catch { - print("Error opening BTFileHandle") + // Error opening BTFileHandle } displayLink = CADisplayLink(target: self, selector: #selector(recordSingleData)) @@ -233,7 +218,7 @@ extension BluetoothManager: CBPeripheralManagerDelegate { do { try BTFileHandle?.close() } catch { - print("Error closing pose file") + // Error closing pose file } } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 3a81927..4540b65 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -116,7 +116,7 @@ class MLInferenceManager: ObservableObject { private func loadActiveModel() { guard let activeModel = modelManager.activeModel, activeModel.compilationStatus.isCompiled else { - print("No active compiled model available") + // No active compiled model available model = nil modelMetadata = nil return @@ -130,17 +130,12 @@ class MLInferenceManager: ObservableObject { modelMetadata = try ModelMetadata(from: loadedModel) setupModelInputTransform() - print("Successfully loaded model: \(activeModel.name)") - print("Model Type: \(modelMetadata?.modelType.displayName ?? "Unknown")") - print("Requires Goal Point: \(modelMetadata?.requiresGoalPoint ?? false)") // Set goal dimension based on model type if modelMetadata?.modelType == .pointConditioned { goalDimension = 3 // VQ-BeT models expect 3D coordinates - print("✅ Set goal dimension to 3D for point-conditioned model") } else { goalDimension = 2 // Standard models use 2D - print("✅ Set goal dimension to 2D for standard model") } // Clear goal point if switching to non-point-conditioned model @@ -148,7 +143,6 @@ class MLInferenceManager: ObservableObject { currentGoalPoint = nil } } catch { - print("Failed to load active model: \(error)") model = nil modelMetadata = nil } @@ -187,13 +181,11 @@ class MLInferenceManager: ObservableObject { func setGoalPoint(_ point: simd_float3) { // Set goal point synchronously since UI needs immediate feedback self.currentGoalPoint = point - print("Goal point set to: [\(point.x), \(point.y), \(point.z)]") } func clearGoalPoint() { currentGoalPoint = nil odometryTracker.resetTracking() - print("Goal point cleared") } // MARK: - Odometry Integration Methods @@ -206,12 +198,10 @@ class MLInferenceManager: ObservableObject { depthMap: CVPixelBuffer? ) -> Bool { guard enableOdometryTracking else { - print("Odometry tracking is disabled") return false } guard let session = getARSession() else { - print("Cannot start odometry tracking - no AR session available") return false } @@ -223,11 +213,7 @@ class MLInferenceManager: ObservableObject { depthMap: depthMap ) - if success { - print("Started Python-style odometry tracking") - } else { - print("Failed to start odometry tracking") - } + // Odometry tracking started return success } @@ -246,14 +232,12 @@ class MLInferenceManager: ObservableObject { if let odometryResult = odometryTracker.updateTracking(currentFrame: arFrame) { // Update visualization with new target position from odometry arVisualizationManager?.updateTargetFromOdometry(odometryResult) - print("📍 Updated visualization target from odometry") } } /// Set goal dimension (2D or 3D goal conditioning) func setGoalDimension(_ dimension: Int) { goalDimension = dimension - print("Goal conditioning set to \\(dimension)D mode") } /// Get goal point for model input (2D or 3D based on goal_dim) @@ -289,7 +273,6 @@ class MLInferenceManager: ObservableObject { func convertScreenToWorld(_ screenPoint: CGPoint, in view: UIView, arSession: ARSession? = nil, depthMap: CVPixelBuffer? = nil) -> simd_float3? { guard let session = arSession ?? getARSession(), let currentFrame = session.currentFrame else { - print("No AR session or current frame available") return nil } @@ -434,7 +417,6 @@ class MLInferenceManager: ObservableObject { do { modelInput = try prepareModelInput(pixelBuffer, metadata: metadata) } catch { - print("Failed to prepare model input: \(error)") return } @@ -450,7 +432,7 @@ class MLInferenceManager: ObservableObject { let inferenceTime = CACurrentMediaTime() - startTime self.processInferenceResults(output, inferenceTime: inferenceTime) } catch { - print("Failed to perform inference: \(error)") + // Inference failed - continue processing } } } @@ -592,6 +574,7 @@ class MLInferenceManager: ObservableObject { let cropRect = CGRect(origin: .zero, size: inputSize) ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) + print("Image processed for VQ-BeT: \(inputSize)") // Convert to MLMultiArray for VQ-BeT format // Support 4D [1,3,H,W] and 5D [1,1,3,H,W] @@ -688,6 +671,7 @@ class MLInferenceManager: ObservableObject { // Render using the same CIContext approach as ARViewContainer ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) + print("Image processed for inference: \(modelInputSize)") // Convert to MLMultiArray (simplified since we now have consistently formatted data) return try convertProcessedPixelBufferToMLMultiArray(outputBuffer) @@ -725,7 +709,6 @@ class MLInferenceManager: ObservableObject { // MARK: - Result Processing private func processInferenceResults(_ output: MLFeatureProvider, inferenceTime: TimeInterval) { guard let metadata = modelMetadata else { - print("Failed to get model metadata for output processing") return } @@ -736,7 +719,6 @@ class MLInferenceManager: ObservableObject { guard let outputFeatureName = outputFeatureName, let resultArray = output.featureValue(for: outputFeatureName)?.multiArrayValue else { - print("Failed to get model output. Available outputs: \(output.featureNames)") return } @@ -764,21 +746,21 @@ class MLInferenceManager: ObservableObject { let src = Array(jointPositions.prefix(7)) if self?.enableTransformDebug == true { let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) - print(report) + print("Coordinate Transform: \(report)") } var robot = ActionTransformUtils.toRobotActions(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) // Clamp gripper to [0,1] if robot.count >= 7 { robot[6] = max(0.0, min(1.0, robot[6])) } - print("USB send (robot actions): \(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))") + print("Robot actions: [\(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") self?.sendJointActionsToUSB(robot) } } let positionString = jointPositions.map { String(format: "%.3f", $0) }.joined(separator: ", ") let modelName = modelManager.activeModel?.name ?? "Unknown" - print("Model Output [\(modelName)] (Standard) (\(outputFeatureName)): [\(positionString)] - \(String(format: "%.1f", inferenceTime * 1000))ms") + print("[\(modelName)] Standard: [\(positionString)] (\(String(format: "%.1f", inferenceTime * 1000))ms)") } else { // Point-conditioned models - use existing complex logic @@ -786,8 +768,6 @@ class MLInferenceManager: ObservableObject { guard let outputFeatureName = outputFeatureName, let resultArray = output.featureValue(for: outputFeatureName)?.multiArrayValue else { - print("Failed to get model output. Available outputs: \(output.featureNames)") - print("Expected output: \(metadata.primaryOutputName ?? "Unknown")") return } @@ -817,7 +797,7 @@ class MLInferenceManager: ObservableObject { if robot.count >= 7 { robot[6] = max(0.0, min(1.0, robot[6])) } - print("USB send (robot actions): \(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))") + print("Robot actions: [\(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") self?.sendJointActionsToUSB(robot) } } @@ -825,11 +805,11 @@ class MLInferenceManager: ObservableObject { let positionString = jointPositions.map { String(format: "%.3f", $0) }.joined(separator: ", ") let modelName = modelManager.activeModel?.name ?? "Unknown" let modelTypeStr = metadata.modelType.displayName - print("Model Output [\(modelName)] (\(modelTypeStr)) (\(outputFeatureName)): [\(positionString)] - \(String(format: "%.1f", inferenceTime * 1000))ms") + print("[\(modelName)] \(modelTypeStr): [\(positionString)] (\(String(format: "%.1f", inferenceTime * 1000))ms)") // Log goal point status for point-conditioned models if metadata.requiresGoalPoint, let goalPoint = currentGoalPoint { - print("Goal Point: [\(String(format: "%.3f", goalPoint.x)), \(String(format: "%.3f", goalPoint.y)), \(String(format: "%.3f", goalPoint.z))]") + print("Goal: [\(String(format: "%.3f", goalPoint.x)), \(String(format: "%.3f", goalPoint.y)), \(String(format: "%.3f", goalPoint.z))]") } } } @@ -838,21 +818,21 @@ class MLInferenceManager: ObservableObject { func enableInference() { isInferenceEnabled = true let modelName = modelManager.activeModel?.name ?? "No model" - print("Pick Up Policy enabled with model: \(modelName)") + print("Inference enabled: \(modelName)") if enableTransformDebug { - print("Transform debug is ENABLED (rotationUnit=\(rotationUnit))") + print("Transform debug enabled (\(rotationUnit))") } } func disableInference() { isInferenceEnabled = false latestResult = nil - print("Pick Up Policy disabled") + print("Inference disabled") } func setInferenceFrequency(_ frequency: InferenceFrequency) { inferenceFrequency = frequency - print("Pick Up Policy frequency set to: \(frequency.displayName)") + print("Inference frequency: \(frequency.displayName)") } // MARK: - Frequency Synchronization @@ -871,7 +851,7 @@ class MLInferenceManager: ObservableObject { } arVisualizationManager?.setVisualizationFrequency(correspondingVisualizationFrequency) - print("Synchronized ML inference (\(inferenceFrequency.displayName)) with AR visualization (\(correspondingVisualizationFrequency.displayName))") + print("Synchronized frequencies: \(inferenceFrequency.displayName)") } // MARK: - Odometry Integration Validation @@ -884,11 +864,10 @@ class MLInferenceManager: ObservableObject { let isValid = hasTracker && hasARConnection && hasVisualizationConnection - print("Odometry Integration Validation:") - print(" - Tracker exists: \(hasTracker)") - print(" - AR Connection: \(hasARConnection)") - print(" - Visualization Connection: \(hasVisualizationConnection)") - print(" - Overall valid: \(isValid)") + print("Odometry validation: \(isValid ? "OK" : "Failed")") + if !isValid { + print("Issues: tracker=\(hasTracker), AR=\(hasARConnection), viz=\(hasVisualizationConnection)") + } return isValid } diff --git a/AnySense/Managers/OdometryPointTracker.swift b/AnySense/Managers/OdometryPointTracker.swift index a52dec2..096bdb6 100644 --- a/AnySense/Managers/OdometryPointTracker.swift +++ b/AnySense/Managers/OdometryPointTracker.swift @@ -64,7 +64,7 @@ class OdometryPointTracker: ObservableObject { let depthOffset: Float = 0.05 // DEPTH_OFFSET from Python (public for validation) init() { - print("OdometryPointTracker initialized (Python-compatible)") + // Initialize odometry point tracker } // MARK: - Public Interface (matching Python workflow) @@ -78,7 +78,7 @@ class OdometryPointTracker: ObservableObject { depthMap: CVPixelBuffer? ) -> Bool { - print("Starting odometry tracking at screen point: (\(screenPoint.x), \(screenPoint.y))") + // Starting odometry tracking // Store initial pose (equivalent to self.start_pose and self.start_pose_matrix) self.startPose = arFrame.camera.transform @@ -97,7 +97,6 @@ class OdometryPointTracker: ObservableObject { session: session, depthMap: depthMap ) else { - print("Failed to convert screen point to 3D") return false } @@ -114,9 +113,6 @@ class OdometryPointTracker: ObservableObject { self.currentResult = initialResult - print("Started tracking object at normalized position: [\(objectPosition.x), \(objectPosition.y), \(objectPosition.z)]") - print("Initial 2D point: [\(initialResult.normalized2DPoint.x), \(initialResult.normalized2DPoint.y)]") - return true } @@ -145,8 +141,6 @@ class OdometryPointTracker: ObservableObject { self.currentResult = result - print("Updated tracking: 2D=[\(String(format: "%.3f", result.normalized2DPoint.x)), \(String(format: "%.3f", result.normalized2DPoint.y))], 3D=[\(String(format: "%.3f", result.world3DPoint.x)), \(String(format: "%.3f", result.world3DPoint.y)), \(String(format: "%.3f", result.world3DPoint.z))]") - return result } @@ -156,7 +150,6 @@ class OdometryPointTracker: ObservableObject { trackingState = .idle currentResult = nil trackingHistory.removeAll() - print("Odometry tracking reset") } /// Get current goal point for model (2D or 3D based on goal_dim) @@ -179,7 +172,6 @@ class OdometryPointTracker: ObservableObject { if !enabled { trackingState = .idle } - print("Odometry tracking \(enabled ? "enabled" : "disabled")") } // MARK: - Private Implementation (matching Python logic) @@ -193,7 +185,7 @@ class OdometryPointTracker: ObservableObject { depthMap: CVPixelBuffer? ) -> simd_float3? { - print("🎯 Converting screen point (\(screenPoint.x), \(screenPoint.y)) to 3D") + // Converting screen point to 3D // Normalize screen coordinates to [0,1] (matching Python: p2d[0] / 256, p2d[1] / 256) let normalizedX = screenPoint.x / view.bounds.width @@ -201,7 +193,6 @@ class OdometryPointTracker: ObservableObject { // Strategy 1: Try depth map sampling (highest accuracy) if let depthBuffer = depthMap { - print("📡 Attempting depth map sampling...") let sampledDepth = sampleDepthMap( depthBuffer: depthBuffer, normalizedX: normalizedX, @@ -210,17 +201,11 @@ class OdometryPointTracker: ObservableObject { if sampledDepth > 0.1 && sampledDepth < 10.0 { // Valid depth range let finalDepth = sampledDepth + depthOffset - print("✅ Depth map success: \(String(format: "%.3f", finalDepth))m") return simd_float3(Float(normalizedX), Float(normalizedY), finalDepth) - } else { - print("⚠️ Depth map returned invalid depth: \(sampledDepth)m") } - } else { - print("⚠️ No depth map provided") } // Strategy 2: ARKit raycast hit testing (reliable fallback) - print("🔍 Attempting ARKit raycast...") let normalizedPoint = CGPoint(x: normalizedX, y: normalizedY) // Create raycast query for existing planes or surfaces @@ -234,16 +219,12 @@ class OdometryPointTracker: ObservableObject { if distance > 0.1 && distance < 10.0 { let finalDepth = distance + depthOffset - print("✅ Raycast success: \(String(format: "%.3f", finalDepth))m") return simd_float3(Float(normalizedX), Float(normalizedY), finalDepth) } } - print("⚠️ Raycast failed - no surfaces detected") // Strategy 3: Simple fixed distance fallback - print("📊 Using fixed distance estimation...") let fixedDepth: Float = 1.0 + depthOffset // 1 meter default - print("📊 Fixed depth: \(String(format: "%.3f", fixedDepth))m") return simd_float3(Float(normalizedX), Float(normalizedY), fixedDepth) } diff --git a/AnySense/Managers/USBManager.swift b/AnySense/Managers/USBManager.swift index f9360b5..adb2da7 100644 --- a/AnySense/Managers/USBManager.swift +++ b/AnySense/Managers/USBManager.swift @@ -62,24 +62,21 @@ class USBManager { listener?.stateUpdateHandler = { state in switch state { case .ready: - print("Server ready and listening on port 1337") + break case .failed(let error): - print("Listener failed with error: \(error)") + break default: break } } listener?.newConnectionHandler = { [weak self] connection in - print("Connection received") self?.handleConnection(connection: connection) - -// self?.sendData(connection: connection, message: "Hello from iPhone!") } listener?.start(queue: .main) } catch { - print("Failed to start listener: \(error)") + // Failed to start listener } } @@ -87,14 +84,12 @@ class USBManager { // Cancel the listener if it exists if let listener = listener { listener.cancel() - print("Listener cancelled") } listener = nil // Cancel the active connection if it exists if let connection = activeConnection { connection.cancel() - print("Connection cancelled") } activeConnection = nil } @@ -114,7 +109,6 @@ class USBManager { compressedConfData: Data? = nil ) { guard let activeConnection = activeConnection else { - print("No active connection. Cannot send data.") return } var messageBody = record3dHeaderData + intrinsicMatData + poseData + rgbImageData + jointActionsData @@ -130,22 +124,11 @@ class USBManager { let completeMessage = ptHeaderData + messageBody - print("USB Streaming Summary:") - print(" - Total message size: \(completeMessage.count) bytes") - print(" - RGB size: \(rgbImageData.count) bytes") - print(" - Joint actions: 28 bytes (7 floats)") - if let depthData = compressedDepthData { - print(" - Depth size: \(depthData.count) bytes (compressed)") - } - if let confData = compressedConfData { - print(" - Confidence size: \(confData.count) bytes (compressed)") - } + print("USB data: \(completeMessage.count) bytes total") activeConnection.send(content:completeMessage, completion: .contentProcessed {error in if let error = error { - print("❌ Failed to send USB data: \(error)") - } else { - print("✅ USB data sent successfully to computer") + // USB send failed } }) } @@ -154,9 +137,7 @@ class USBManager { let data = message.data(using: .utf8)! connection.send(content: data, completion: .contentProcessed { error in if let error = error { - print("Failed to send data: \(error)") - } else { - print("Data sent successfully") + // Data send failed } }) } @@ -164,7 +145,6 @@ class USBManager { func compressData(from pixelBuffer: CVPixelBuffer, isDepth: Bool) -> Data? { // Extract depth data guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { - print("Failed to access depth buffer base address") return nil } @@ -192,7 +172,6 @@ class USBManager { ) guard compressedSize > 0 else { - print("Failed to compress depth map") return nil } @@ -203,7 +182,6 @@ class USBManager { // MARK: - Joint Actions sender func sendJointActions(_ jointActionsData: Data) { guard let activeConnection = activeConnection else { - print("No active connection. Cannot send joint actions.") return } var header = PeerTalkHeader(a: 2, b: 1, c: 1, body_size: UInt32(jointActionsData.count).bigEndian) @@ -211,9 +189,7 @@ class USBManager { let message = headerData + jointActionsData activeConnection.send(content: message, completion: .contentProcessed { error in if let error = error { - print("❌ Failed to send joint actions: \(error)") - } else { - print("✅ Joint actions sent (\(jointActionsData.count) bytes)") + // Joint actions send failed } }) } diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index eb9efeb..1ae6714 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -43,126 +43,92 @@ struct ReadView : View{ ZStack { // Apply the custom background color Color.customizedBackground - .ignoresSafeArea() + .ignoresSafeArea(edges: .top) ZStack{ ZStack { ARViewContainer( session: arViewModel.session, arVisualizationManager: arViewModel.arVisualizationManager ) - .edgesIgnoringSafeArea(.all) - .opacity(appStatus.rgbdVideoStreaming == .off ? 1 : 0) - .allowsHitTesting(appStatus.rgbdVideoStreaming == .off) // Disable interaction in streaming mode + .allowsHitTesting(true) } .frame(width: arViewWidth, height: arViewHeight) .padding(.bottom, arViewPadding) - // ML Status Overlay - if appStatus.rgbdVideoStreaming == .off { - VStack { - HStack { - VStack(alignment: .leading, spacing: 8) { - // ML Inference Results (only when enabled) - if appStatus.mlInferenceEnabled && arViewModel.mlManager?.isInferenceEnabled == true { - if let mlManager = arViewModel.mlManager { - MLInferenceResultsView(mlManager: mlManager) - } + // ML Status Overlay (shown in all modes) + VStack { + HStack { + VStack(alignment: .leading, spacing: 8) { + // ML Inference Results (only when enabled) + if appStatus.mlInferenceEnabled && arViewModel.mlManager?.isInferenceEnabled == true { + if let mlManager = arViewModel.mlManager { + MLInferenceResultsView(mlManager: mlManager) } - } - Spacer() + } Spacer() - // AR Visualization Status Overlay - HStack { - VStack(alignment: .leading, spacing: 4) { - if arViewModel.arVisualizationManager.isVisualizationEnabled { - Text("Movement Tracking: ON") - .font(.caption) - .foregroundColor(.green) - Text("Max Arrows: \(arViewModel.arVisualizationManager.maxArrows)") - .font(.caption2) - .foregroundColor(.secondary) - } else { - Text("Movement Tracking: OFF") - .font(.caption) - .foregroundColor(.red) - } - } - .padding(8) - .background(Color.black.opacity(0.6)) - .cornerRadius(8) - Spacer() + } + Spacer() + // AR Visualization Status Overlay + HStack { + VStack(alignment: .leading, spacing: 4) { + if arViewModel.arVisualizationManager.isVisualizationEnabled { + Text("Movement Tracking: ON") + .font(.caption) + .foregroundColor(.green) + Text("Max Arrows: \(arViewModel.arVisualizationManager.maxArrows)") + .font(.caption2) + .foregroundColor(.secondary) + } else { + Text("Movement Tracking: OFF") + .font(.caption) + .foregroundColor(.red) } - .padding(.bottom, 10) } - .frame(width: arViewWidth, height: arViewHeight) - .padding(.bottom, arViewPadding) + .padding(8) + .background(Color.black.opacity(0.6)) + .cornerRadius(8) + Spacer() + } + .padding(.bottom, 10) } + .frame(width: arViewWidth, height: arViewHeight) + .padding(.bottom, arViewPadding) - if appStatus.rgbdVideoStreaming == .off { - Text(appStatus.ifBluetoothConnected ? "bluetooth device connected" : "bluetooth device disconnected") - .font(.footnote) - .foregroundColor(Color.white) - .frame(width: screenWidth, height: btBarHeight) - .background(appStatus.ifBluetoothConnected ? .green : .red) - .padding(.bottom, arViewPadding + arViewHeight + btBarHeight) - .ignoresSafeArea() - if appStatus.gridProjectionTrigger.rawValue > 0 { - VStack { - Path { path in - for col in 1.. 0 { + VStack { + Path { path in + for col in 1.. Date: Sat, 6 Sep 2025 20:48:25 -0400 Subject: [PATCH 25/56] fixed joint streaming --- AnySense/Managers/ARViewContainer.swift | 8 -------- AnySense/Managers/MLInferenceManager.swift | 20 +++++--------------- AnySense/Managers/USBManager.swift | 16 +--------------- 3 files changed, 6 insertions(+), 38 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 9df3cb2..98e8f05 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -138,14 +138,6 @@ class ARViewModel: ObservableObject{ return session } - func sendJointActionsUSB(_ jointActions: [Float]) { - var actions = Array(jointActions.prefix(7)) - if actions.count < 7 { - actions.append(contentsOf: Array(repeating: 0.0, count: 7 - actions.count)) - } - let data = actions.withUnsafeBytes { Data($0) } - usbManager.sendJointActions(data) - } private var poseFileHandle: FileHandle? // Control the destination of rgb images directory and depth images directory diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 4540b65..57a89c7 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -376,19 +376,9 @@ class MLInferenceManager: ObservableObject { self.arViewContainer = container } - // MARK: - USB Streaming Support - private func sendJointActionsToUSB(_ jointActions: [Float]) { - // Only send to USB if we're actually in USB streaming mode - // We can check this by seeing if the ARViewContainer has USB streaming active - arViewContainer?.sendJointActionsUSB(jointActions) - } - - - // MARK: - Inference Methods (Using existing frame processing patterns) func performInference(on pixelBuffer: CVPixelBuffer, arFrame: ARFrame?, timestamp: CFTimeInterval = CACurrentMediaTime()) { - // Update odometry tracking SYNCHRONOUSLY if AR frame is provided - // This ensures the updated goal point is available for model input preparation + // Update odometry tracking to have consistent goal point for model input preparation if let frame = arFrame { updateOdometryTracking(arFrame: frame) } @@ -741,7 +731,7 @@ class MLInferenceManager: ObservableObject { arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } - // Send joint actions to USB if streaming is enabled (transform to robot frame) + // Joint actions are automatically sent via USB stream (transform to robot frame) if jointPositions.count >= 7 { let src = Array(jointPositions.prefix(7)) if self?.enableTransformDebug == true { @@ -754,7 +744,7 @@ class MLInferenceManager: ObservableObject { robot[6] = max(0.0, min(1.0, robot[6])) } print("Robot actions: [\(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") - self?.sendJointActionsToUSB(robot) + // Joint actions are now sent embedded in the main USB stream } } @@ -790,7 +780,7 @@ class MLInferenceManager: ObservableObject { arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } - // Send joint actions to USB if streaming is enabled (transform to robot frame) + // Joint actions are automatically sent via USB stream (transform to robot frame) if jointPositions.count >= 7 { let src = Array(jointPositions.prefix(7)) var robot = ActionTransformUtils.toRobotActions(src) @@ -798,7 +788,7 @@ class MLInferenceManager: ObservableObject { robot[6] = max(0.0, min(1.0, robot[6])) } print("Robot actions: [\(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") - self?.sendJointActionsToUSB(robot) + // Joint actions are now sent embedded in the main USB stream } } diff --git a/AnySense/Managers/USBManager.swift b/AnySense/Managers/USBManager.swift index adb2da7..eee0f05 100644 --- a/AnySense/Managers/USBManager.swift +++ b/AnySense/Managers/USBManager.swift @@ -29,7 +29,7 @@ struct Record3DHeader { var confidenceMapSize: UInt32 var miscSize: UInt32 var deviceType: UInt32 - // jointActions are always 28 bytes (7 floats), sent separately in message body + // jointActions are always 28 bytes (7 floats), embedded in message body after RGB data } struct IntrinsicMatrixCoeffs { @@ -179,18 +179,4 @@ class USBManager { return Data(bytes: compressedBuffer, count: compressedSize) } - // MARK: - Joint Actions sender - func sendJointActions(_ jointActionsData: Data) { - guard let activeConnection = activeConnection else { - return - } - var header = PeerTalkHeader(a: 2, b: 1, c: 1, body_size: UInt32(jointActionsData.count).bigEndian) - let headerData = Data(bytes: &header, count: MemoryLayout.size) - let message = headerData + jointActionsData - activeConnection.send(content: message, completion: .contentProcessed { error in - if let error = error { - // Joint actions send failed - } - }) - } } From 129abe559afc6f31634f2905d5a8c6b377606538 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Tue, 9 Sep 2025 15:49:50 -0400 Subject: [PATCH 26/56] added anchoring method and simplified visualization --- AnySense/Managers/ARViewContainer.swift | 136 +++++++++++++++-- .../Managers/ARVisualizationManager.swift | 54 ++++++- AnySense/Managers/MLInferenceManager.swift | 140 ++++-------------- 3 files changed, 207 insertions(+), 123 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 98e8f05..fe659ec 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -197,40 +197,154 @@ class ARViewModel: ObservableObject{ // Listen for goal-tap notifications and start odometry + set goal point NotificationCenter.default.addObserver(forName: NSNotification.Name("ARViewTapForGoal"), object: nil, queue: .main) { [weak self] notif in - guard let self = self, let ml = self.mlManager else { return } + guard let self = self, let ml = self.mlManager else { + print(" Goal tap: No ML manager") + return + } // Only handle taps when using a point-conditioned policy and the user enabled goal-tap mode - guard ml.isPointConditioned, self.goalTapModeEnabled else { return } + print(" Goal tap received - isPointConditioned: \(ml.isPointConditioned), goalTapMode: \(self.goalTapModeEnabled)") + guard ml.isPointConditioned, self.goalTapModeEnabled else { + print("Goal tap ignored - conditions not met") + return + } guard let location = notif.userInfo?["location"] as? CGPoint, - let bounds = notif.userInfo?["bounds"] as? CGRect else { return } + let bounds = notif.userInfo?["bounds"] as? CGRect else { + print(" Missing location or bounds data") + return + } + print(" Tap location: \(location), bounds: \(bounds)") let dummyView = UIView(frame: bounds) if let frame = self.session.currentFrame { let depth = self.depthStatus.isDepthAvailable ? (frame.sceneDepth?.depthMap) : nil - _ = ml.startOdometryTrackingWithScreenPoint(screenPoint: location, in: dummyView, arFrame: frame, depthMap: depth) - if let world = ml.convertScreenToWorld(location, in: dummyView, arSession: self.session, depthMap: depth) ?? self.raycastWithEstimatedDepth(at: location, in: dummyView, frame: frame, estimatedDepth: 2.5) { + print("Depth available: \(depth != nil)") + if let world = self.getWorldPositionFromTap(location, frame: frame) { + print(" World position calculated: \(world)") ml.setGoalPoint(world) self.arVisualizationManager.setTargetPose(world) + print(" Goal point set and visualization updated") // Exit goal-tap mode after a successful set self.goalTapModeEnabled = false + } else { + print(" Failed to get world position from tap") } } } } - - // Fallback conversion using a constant estimated depth when depth map is unavailable - private func raycastWithEstimatedDepth(at screenPoint: CGPoint, in view: UIView, frame: ARFrame, estimatedDepth: Float) -> simd_float3? { + + // Simple, direct approach: Use ARKit's built-in methods + LiDAR depth sampling + private func getWorldPositionFromTap(_ tapPoint: CGPoint, frame: ARFrame) -> simd_float3? { + print("getWorldPositionFromTap called with: \(tapPoint)") + + // 1) First try LiDAR depth if available (most accurate) + if let sceneDepth = frame.sceneDepth { + print(" Trying LiDAR depth method") + if let worldPos = getWorldPositionFromDepth(tapPoint, frame: frame, sceneDepth: sceneDepth) { + print(" LiDAR depth success: \(worldPos)") + return worldPos + } else { + print(" LiDAR depth failed") + } + } else { + print(" No scene depth available") + } + + // 2) Fallback to ARKit raycasting + print(" Trying ARKit raycast fallback") + let normalizedPoint = CGPoint( + x: tapPoint.x / UIScreen.main.bounds.width, + y: tapPoint.y / UIScreen.main.bounds.height + ) + print(" Normalized point: \(normalizedPoint)") + + let query = frame.raycastQuery(from: normalizedPoint, allowing: .estimatedPlane, alignment: .any) + let results = session.raycast(query) + print(" Raycast results count: \(results.count)") + + if let result = results.first { + let position = result.worldTransform.columns.3 + let worldPos = simd_float3(position.x, position.y, position.z) + print(" Raycast success: \(worldPos)") + return worldPos + } + + // 3) Final fallback: Use fixed depth estimate (1 meter forward) + print("Trying fixed depth fallback (1m)") + let estimatedDepth: Float = 1.0 + let camera = frame.camera + let cameraTransform = camera.transform + + // Convert screen point to normalized coordinates (-1 to 1) + let normalizedX = (2.0 * Float(tapPoint.x) / Float(UIScreen.main.bounds.width)) - 1.0 + let normalizedY = 1.0 - (2.0 * Float(tapPoint.y) / Float(UIScreen.main.bounds.height)) + + // Get camera direction through the tap point + let intrinsics = camera.intrinsics + let fx = intrinsics[0][0] + let fy = intrinsics[1][1] + let cx = intrinsics[2][0] + let cy = intrinsics[2][1] + + let cameraX = (Float(tapPoint.x) - cx) / fx + let cameraY = (Float(tapPoint.y) - cy) / fy + let cameraZ = -5.0 // Forward in camera space + + // Normalize the direction vector + let direction = simd_normalize(simd_float3(cameraX, cameraY, Float(cameraZ))) + + // Scale by estimated depth + let cameraSpacePoint = direction * estimatedDepth + + // Transform to world space + let worldPoint = simd_make_float3(cameraTransform * simd_make_float4(cameraSpacePoint, 1.0)) + + print("Fixed depth success: \(worldPoint)") + return worldPoint + } + + private func getWorldPositionFromDepth(_ screenPoint: CGPoint, frame: ARFrame, sceneDepth: ARDepthData) -> simd_float3? { + let depthMap = sceneDepth.depthMap + let dmWidth = CVPixelBufferGetWidth(depthMap) + let dmHeight = CVPixelBufferGetHeight(depthMap) + + // Convert screen point to depth map coordinates + let viewSize = UIScreen.main.bounds.size + let viewToImage = frame.displayTransform(for: .portrait, viewportSize: viewSize).inverted() + var norm = CGPoint(x: screenPoint.x / viewSize.width, y: screenPoint.y / viewSize.height) + norm = norm.applying(viewToImage) + + let x = Int(round(norm.x * CGFloat(dmWidth))) + let y = Int(round((1 - norm.y) * CGFloat(dmHeight))) + + guard x >= 0, x < dmWidth, y >= 0, y < dmHeight else { return nil } + + CVPixelBufferLockBaseAddress(depthMap, .readOnly) + defer { CVPixelBufferUnlockBaseAddress(depthMap, .readOnly) } + + let base = CVPixelBufferGetBaseAddress(depthMap)!.assumingMemoryBound(to: Float.self) + let rowStride = CVPixelBufferGetBytesPerRow(depthMap) / MemoryLayout.size + let depth = base[y * rowStride + x] + + guard depth.isFinite && depth > 0 else { return nil } + + // Convert screen point + depth to world position let cameraIntrinsics = frame.camera.intrinsics let cameraTransform = frame.camera.transform + let fx = cameraIntrinsics.columns.0.x let fy = cameraIntrinsics.columns.1.y let cx = cameraIntrinsics.columns.2.x let cy = cameraIntrinsics.columns.2.y - let cameraX = (Float(screenPoint.x) - cx) / fx * estimatedDepth - let cameraY = (Float(screenPoint.y) - cy) / fy * estimatedDepth - let cameraZ = estimatedDepth + + let cameraX = (Float(screenPoint.x) - cx) / fx * depth + let cameraY = (Float(screenPoint.y) - cy) / fy * depth + let cameraZ = -depth + let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) let worldPoint = simd_mul(cameraTransform, cameraPoint) + return simd_float3(worldPoint.x, worldPoint.y, worldPoint.z) } + func getBLEManagerInstance() -> BluetoothManager{ diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 023a8a0..5a1d965 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -53,6 +53,7 @@ class ARVisualizationManager: ObservableObject { // Target/device pose state for point-conditioned flows private var targetPose: SIMD3? private var actualDevicePose: SIMD3 = SIMD3(0, 0, 0) + private var goalPointEntity: ModelEntity? // Movement tracking private var worldOrigin: SIMD3 = SIMD3(0, 0, 0) @@ -148,6 +149,10 @@ class ARVisualizationManager: ObservableObject { currentWorldPosition = SIMD3(0, 0, 0) previousWorldPosition = nil + // Remove goal point visualization + goalPointEntity?.removeFromParent() + goalPointEntity = nil + worldOriginAnchor?.removeFromParent() worldOriginAnchor = nil } @@ -165,6 +170,10 @@ class ARVisualizationManager: ObservableObject { } private func clearAllVisualization() { + // Remove goal point visualization + goalPointEntity?.removeFromParent() + goalPointEntity = nil + // Remove all movement arrows for arrow in movementArrows { arrow.anchor.removeFromParent() @@ -172,12 +181,12 @@ class ARVisualizationManager: ObservableObject { movementArrows.removeAll() } - // MARK: - Public helper to auto-prepare visualization - func prepareVisualizationIfNeeded() { + // MARK: - Initialization helper + func ensureVisualizationReady() { if !hasEstablishedOrigin { establishWorldOrigin() } if !isVisualizationEnabled { enableVisualization() } if debugLoggingEnabled { - print("[Viz] prepareVisualizationIfNeeded → enabled=\(isVisualizationEnabled), origin=\(hasEstablishedOrigin)") + print("[Viz] ensureVisualizationReady → enabled=\(isVisualizationEnabled), origin=\(hasEstablishedOrigin)") } } @@ -215,14 +224,21 @@ class ARVisualizationManager: ObservableObject { func updateTargetFromOdometry(_ result: OdometryTrackingResult) { targetPose = result.world3DPoint + ensureVisualizationReady() + updateGoalPointVisualization() } func setTargetPose(_ worldPoint: SIMD3) { targetPose = worldPoint + // Ensure visualization is ready before creating goal point + ensureVisualizationReady() + updateGoalPointVisualization() } func clearTargetPose() { targetPose = nil + goalPointEntity?.removeFromParent() + goalPointEntity = nil } // MARK: - ML Integration Method @@ -460,4 +476,36 @@ class ARVisualizationManager: ObservableObject { return simd_quatf(ix: x, iy: y, iz: z, r: w) } + + // MARK: - Goal Point Visualization + private func updateGoalPointVisualization() { + guard let targetPose = targetPose, + let worldOriginAnchor = worldOriginAnchor, + hasEstablishedOrigin else { + print("❌ Cannot create goal visualization - targetPose: \(targetPose?.debugDescription ?? "nil"), anchor: \(worldOriginAnchor != nil), origin: \(hasEstablishedOrigin)") + goalPointEntity?.removeFromParent() + goalPointEntity = nil + return + } + + // Remove existing goal point visualization + goalPointEntity?.removeFromParent() + goalPointEntity = nil + + // Create a larger, more visible sphere + let sphereMesh = MeshResource.generateSphere(radius: 0.1) // 10cm radius - much larger + let goalMaterial = SimpleMaterial(color: .systemRed, isMetallic: false) // Bright red color + goalPointEntity = ModelEntity(mesh: sphereMesh, materials: [goalMaterial]) + + // Position the sphere at the target pose (relative to world origin) + let relativePosition = targetPose - worldOrigin + goalPointEntity?.position = relativePosition + worldOriginAnchor.addChild(goalPointEntity!) + + print("🎯 Goal point visualization created:") + print(" Target pose (world): \(targetPose)") + print(" World origin: \(worldOrigin)") + print(" Relative position: \(relativePosition)") + print(" Distance from origin: \(length(relativePosition))m") + } } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 57a89c7..ad1de13 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -185,7 +185,6 @@ class MLInferenceManager: ObservableObject { func clearGoalPoint() { currentGoalPoint = nil - odometryTracker.resetTracking() } // MARK: - Odometry Integration Methods @@ -247,14 +246,8 @@ class MLInferenceManager: ObservableObject { guard let session = getARSession(), let frame = session.currentFrame else { return nil } - // Prefer odometry-tracked world point; else use static world point if set - let worldPoint: simd_float3? - if enableOdometryTracking, let result = odometryTracker.currentResult { - worldPoint = result.world3DPoint - } else { - worldPoint = currentGoalPoint - } - guard let p_w = worldPoint else { return nil } + // Use the world-locked goal point (ARKit keeps it fixed in world space) + guard let p_w = currentGoalPoint else { return nil } // World (ARKit) → Camera let T_wc = frame.camera.transform let T_cw = simd_inverse(T_wc) @@ -262,106 +255,35 @@ class MLInferenceManager: ObservableObject { // labels.json mapping from camera frame return [-p_c4.x, p_c4.z, p_c4.y] } - // 2D goals: use odometry normalized 2D if available; else fallback to center - if enableOdometryTracking, let result = odometryTracker.currentResult { - return [Float(result.normalized2DPoint.x), Float(result.normalized2DPoint.y)] + // 2D goals: project world-locked goal point to current camera view + if let p_w = currentGoalPoint, let session = getARSession(), let frame = session.currentFrame { + // Project world point to current camera view + let T_wc = frame.camera.transform + let T_cw = simd_inverse(T_wc) + let p_c4 = simd_mul(T_cw, simd_float4(p_w.x, p_w.y, p_w.z, 1.0)) + let p_c = simd_float3(p_c4.x, p_c4.y, p_c4.z) + + // Project to normalized screen coordinates [0,1] + let intrinsics = frame.camera.intrinsics + let fx = intrinsics.columns.0.x + let fy = intrinsics.columns.1.y + let cx = intrinsics.columns.2.x + let cy = intrinsics.columns.2.y + + let screenX = (p_c.x * fx / (-p_c.z)) + cx + let screenY = (p_c.y * fy / (-p_c.z)) + cy + + let imageWidth = frame.camera.imageResolution.width + let imageHeight = frame.camera.imageResolution.height + + let normalizedX = screenX / Float(imageWidth) + let normalizedY = screenY / Float(imageHeight) + + // Clamp to [0,1] range + return [max(0, min(1, normalizedX)), max(0, min(1, normalizedY))] } else { - return [0.5, 0.5] - } - } - - func convertScreenToWorld(_ screenPoint: CGPoint, in view: UIView, arSession: ARSession? = nil, depthMap: CVPixelBuffer? = nil) -> simd_float3? { - guard let session = arSession ?? getARSession(), - let currentFrame = session.currentFrame else { - return nil - } - - // Method 1: Try hit testing first (most accurate for surfaces) - let normalizedPoint = CGPoint( - x: screenPoint.x / view.bounds.width, - y: screenPoint.y / view.bounds.height - ) - - // Create hit test query for existing planes or surfaces - let query = currentFrame.raycastQuery(from: normalizedPoint, allowing: .existingPlaneGeometry, alignment: .any) - let results = session.raycast(query) - if let result = results.first { - let worldTransform = result.worldTransform - return simd_float3(worldTransform.columns.3.x, worldTransform.columns.3.y, worldTransform.columns.3.z) - } - - // Method 2: Use depth map if available - if let depth = depthMap ?? currentFrame.sceneDepth?.depthMap { - if let worldPoint = convertScreenToWorldUsingDepth(screenPoint, in: view, frame: currentFrame, depthMap: depth) { - return worldPoint - } - } - - // Method 3: Fallback to estimated depth - return convertScreenToWorldEstimated(screenPoint, in: view, frame: currentFrame, estimatedDepth: 1.0) - } - - private func convertScreenToWorldUsingDepth(_ screenPoint: CGPoint, in view: UIView, frame: ARFrame, depthMap: CVPixelBuffer) -> simd_float3? { - // Convert screen point to depth map coordinates - let depthWidth = CVPixelBufferGetWidth(depthMap) - let depthHeight = CVPixelBufferGetHeight(depthMap) - - let normalizedX = screenPoint.x / view.bounds.width - let normalizedY = screenPoint.y / view.bounds.height - - let depthX = Int(normalizedX * CGFloat(depthWidth)) - let depthY = Int(normalizedY * CGFloat(depthHeight)) - - // Ensure coordinates are within bounds - guard depthX >= 0, depthX < depthWidth, depthY >= 0, depthY < depthHeight else { - return nil - } - - // Read depth value - CVPixelBufferLockBaseAddress(depthMap, .readOnly) - defer { CVPixelBufferUnlockBaseAddress(depthMap, .readOnly) } - - guard let baseAddress = CVPixelBufferGetBaseAddress(depthMap) else { return nil } - let bytesPerRow = CVPixelBufferGetBytesPerRow(depthMap) - let depthPointer = baseAddress.assumingMemoryBound(to: Float32.self) - - let pixelOffset = depthY * (bytesPerRow / MemoryLayout.stride) + depthX - let depth = depthPointer[pixelOffset] - - guard depth > 0.1 && depth < 10.0 else { // Valid depth range - return nil + return [0.5, 0.5] // Center fallback } - - return convertScreenToWorldEstimated(screenPoint, in: view, frame: frame, estimatedDepth: depth) - } - - private func convertScreenToWorldEstimated(_ screenPoint: CGPoint, in view: UIView, frame: ARFrame, estimatedDepth: Float) -> simd_float3? { - let cameraIntrinsics = frame.camera.intrinsics - let cameraTransform = frame.camera.transform - - // Convert screen coordinates to normalized coordinates - let normalizedX = (screenPoint.x / view.bounds.width) * 2.0 - 1.0 - let normalizedY = 1.0 - (screenPoint.y / view.bounds.height) * 2.0 - - // Convert to camera space using inverse intrinsics - let fx = cameraIntrinsics.columns.0.x - let fy = cameraIntrinsics.columns.1.y - let cx = cameraIntrinsics.columns.2.x - let cy = cameraIntrinsics.columns.2.y - - let imageWidth = Float(view.bounds.width) - let imageHeight = Float(view.bounds.height) - - let cameraX = (Float(screenPoint.x) - cx) / fx * estimatedDepth - let cameraY = (Float(screenPoint.y) - cy) / fy * estimatedDepth - let cameraZ = -estimatedDepth // Negative Z in camera coordinates - - let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) - - // Transform to world coordinates - let worldPoint = simd_mul(cameraTransform, cameraPoint) - - return simd_float3(worldPoint.x, worldPoint.y, worldPoint.z) } // MARK: - AR Session Access @@ -727,7 +649,7 @@ class MLInferenceManager: ObservableObject { // Ensure visualization is ready and feed pose if let arManager = self?.arVisualizationManager, jointPositions.count >= 6 { - arManager.prepareVisualizationIfNeeded() + arManager.ensureVisualizationReady() arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } @@ -776,7 +698,7 @@ class MLInferenceManager: ObservableObject { // Ensure visualization is ready and feed pose if let arManager = self?.arVisualizationManager, jointPositions.count >= 6 { - arManager.prepareVisualizationIfNeeded() + arManager.ensureVisualizationReady() arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } From d6dedc8a1085680efed57960b24d8f89a7daf5a3 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Tue, 9 Sep 2025 18:09:22 -0400 Subject: [PATCH 27/56] fixed coordinate issues --- AnySense/Managers/ARViewContainer.swift | 187 +++++++++++++++++------- 1 file changed, 134 insertions(+), 53 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index fe659ec..59060ff 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -72,12 +72,30 @@ struct ARViewContainer: UIViewRepresentable { @objc func handleTap(_ recognizer: UITapGestureRecognizer) { guard recognizer.state == .ended, let arView = recognizer.view as? ARView else { return } let location = recognizer.location(in: arView) - // Convert UIKit tap to a lightweight UIView for ML manager API - let dummyView = UIView(frame: arView.bounds) - - // Access ML manager via a shared ARViewModel if available - // Here, we post a notification with tap info; the view model can subscribe and start odometry - NotificationCenter.default.post(name: NSNotification.Name("ARViewTapForGoal"), object: nil, userInfo: ["location": location, "bounds": arView.bounds]) + // Prefer RealityKit raycast to get an accurate world point + if let hit = arView.raycast(from: location, allowing: .estimatedPlane, alignment: .any).first { + let t = hit.worldTransform + let world = simd_float3(t.columns.3.x, t.columns.3.y, t.columns.3.z) + NotificationCenter.default.post( + name: NSNotification.Name("ARViewTapForGoal"), + object: nil, + userInfo: [ + "worldPoint": world, + "location": location, + "bounds": arView.bounds + ] + ) + return + } + // Fallback: still notify with screen info (no hit yet) + NotificationCenter.default.post( + name: NSNotification.Name("ARViewTapForGoal"), + object: nil, + userInfo: [ + "location": location, + "bounds": arView.bounds + ] + ) } } } @@ -207,22 +225,29 @@ class ARViewModel: ObservableObject{ print("Goal tap ignored - conditions not met") return } + // Prefer direct world point from raycast if provided + if let world = notif.userInfo?["worldPoint"] as? simd_float3 { + print("Using raycast world point: \(world)") + ml.setGoalPoint(world) + self.arVisualizationManager.setTargetPose(world) + self.goalTapModeEnabled = false + return + } + // Otherwise, fall back to computing from screen point guard let location = notif.userInfo?["location"] as? CGPoint, let bounds = notif.userInfo?["bounds"] as? CGRect else { print(" Missing location or bounds data") return } print(" Tap location: \(location), bounds: \(bounds)") - let dummyView = UIView(frame: bounds) if let frame = self.session.currentFrame { let depth = self.depthStatus.isDepthAvailable ? (frame.sceneDepth?.depthMap) : nil print("Depth available: \(depth != nil)") - if let world = self.getWorldPositionFromTap(location, frame: frame) { + if let world = self.getWorldPositionFromTap(location, frame: frame, viewBounds: bounds) { print(" World position calculated: \(world)") ml.setGoalPoint(world) self.arVisualizationManager.setTargetPose(world) print(" Goal point set and visualization updated") - // Exit goal-tap mode after a successful set self.goalTapModeEnabled = false } else { print(" Failed to get world position from tap") @@ -232,13 +257,13 @@ class ARViewModel: ObservableObject{ } // Simple, direct approach: Use ARKit's built-in methods + LiDAR depth sampling - private func getWorldPositionFromTap(_ tapPoint: CGPoint, frame: ARFrame) -> simd_float3? { + private func getWorldPositionFromTap(_ tapPoint: CGPoint, frame: ARFrame, viewBounds: CGRect) -> simd_float3? { print("getWorldPositionFromTap called with: \(tapPoint)") // 1) First try LiDAR depth if available (most accurate) if let sceneDepth = frame.sceneDepth { print(" Trying LiDAR depth method") - if let worldPos = getWorldPositionFromDepth(tapPoint, frame: frame, sceneDepth: sceneDepth) { + if let worldPos = getWorldPositionFromDepth(tapPoint, frame: frame, sceneDepth: sceneDepth, viewBounds: viewBounds) { print(" LiDAR depth success: \(worldPos)") return worldPos } else { @@ -267,55 +292,98 @@ class ARViewModel: ObservableObject{ return worldPos } - // 3) Final fallback: Use fixed depth estimate (1 meter forward) + // 3) Final fallback: Use fixed depth estimate with displayTransform and original intrinsics print("Trying fixed depth fallback (1m)") let estimatedDepth: Float = 1.0 + + // Get camera parameters let camera = frame.camera let cameraTransform = camera.transform - - // Convert screen point to normalized coordinates (-1 to 1) - let normalizedX = (2.0 * Float(tapPoint.x) / Float(UIScreen.main.bounds.width)) - 1.0 - let normalizedY = 1.0 - (2.0 * Float(tapPoint.y) / Float(UIScreen.main.bounds.height)) - - // Get camera direction through the tap point let intrinsics = camera.intrinsics - let fx = intrinsics[0][0] - let fy = intrinsics[1][1] - let cx = intrinsics[2][0] - let cy = intrinsics[2][1] - - let cameraX = (Float(tapPoint.x) - cx) / fx - let cameraY = (Float(tapPoint.y) - cy) / fy - let cameraZ = -5.0 // Forward in camera space - - // Normalize the direction vector - let direction = simd_normalize(simd_float3(cameraX, cameraY, Float(cameraZ))) - - // Scale by estimated depth - let cameraSpacePoint = direction * estimatedDepth - - // Transform to world space - let worldPoint = simd_make_float3(cameraTransform * simd_make_float4(cameraSpacePoint, 1.0)) + let imageResolution = frame.camera.imageResolution + let imageWidth = Float(imageResolution.width) + let imageHeight = Float(imageResolution.height) + + let fx = intrinsics.columns.0.x + let fy = intrinsics.columns.1.y + let cx = intrinsics.columns.2.x + let cy = intrinsics.columns.2.y + + // Map tap point from view coords → normalized view → normalized image using displayTransform + let viewSize = viewBounds.size + // Detect current device orientation + let currentOrientation: UIInterfaceOrientation + if #available(iOS 13.0, *) { + currentOrientation = UIApplication.shared.windows.first?.windowScene?.interfaceOrientation ?? .portrait + } else { + currentOrientation = UIApplication.shared.statusBarOrientation + } + let viewToImage = frame.displayTransform(for: currentOrientation, viewportSize: viewSize).inverted() + var normView = CGPoint(x: tapPoint.x / viewSize.width, y: tapPoint.y / viewSize.height) + let normImage = normView.applying(viewToImage) + + // Convert normalized image coords to pixel coords in captured image space + let u_img = Float(normImage.x) * imageWidth + let v_img = Float(normImage.y) * imageHeight + + print("=== COORDINATE DEBUG ===") + print("Tap point: \(tapPoint)") + print("View bounds: \(viewBounds)") + print("Camera image resolution: \(imageResolution)") + print("Orientation: \(currentOrientation)") + print("Normalized view: \(normView) → normalized image: \(normImage)") + print("Pixel coords (u,v): (\(u_img), \(v_img))") + print("Intrinsics - fx: \(fx), fy: \(fy), cx: \(cx), cy: \(cy)") + + // Convert pixel coords + fixed depth to camera space + let cameraX = (u_img - cx) / fx * estimatedDepth + let cameraY = -((v_img - cy) / fy) * estimatedDepth // Flip Y to fix top/bottom inversion + let cameraZ = -estimatedDepth // Negative Z in camera space + + print("Camera space point - X: \(cameraX), Y: \(cameraY), Z: \(cameraZ)") + + // Transform from camera space to world space + let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) + let worldPoint = simd_mul(cameraTransform, cameraPoint) - print("Fixed depth success: \(worldPoint)") - return worldPoint + print("Fixed depth success: \(simd_float3(worldPoint.x, worldPoint.y, worldPoint.z))") + return simd_float3(worldPoint.x, worldPoint.y, worldPoint.z) } - private func getWorldPositionFromDepth(_ screenPoint: CGPoint, frame: ARFrame, sceneDepth: ARDepthData) -> simd_float3? { + private func getWorldPositionFromDepth(_ screenPoint: CGPoint, frame: ARFrame, sceneDepth: ARDepthData, viewBounds: CGRect) -> simd_float3? { let depthMap = sceneDepth.depthMap let dmWidth = CVPixelBufferGetWidth(depthMap) let dmHeight = CVPixelBufferGetHeight(depthMap) - // Convert screen point to depth map coordinates - let viewSize = UIScreen.main.bounds.size - let viewToImage = frame.displayTransform(for: .portrait, viewportSize: viewSize).inverted() - var norm = CGPoint(x: screenPoint.x / viewSize.width, y: screenPoint.y / viewSize.height) - norm = norm.applying(viewToImage) + print("Depth map size: \(dmWidth) x \(dmHeight)") + + // Convert screen point to image/depth coordinates using ARKit display transform + let viewSize = viewBounds.size + print("ARView bounds: \(viewBounds)") + print("View size: \(viewSize)") + + let currentOrientation: UIInterfaceOrientation + if #available(iOS 13.0, *) { + currentOrientation = UIApplication.shared.windows.first?.windowScene?.interfaceOrientation ?? .portrait + } else { + currentOrientation = UIApplication.shared.statusBarOrientation + } + print("Current orientation: \(currentOrientation)") - let x = Int(round(norm.x * CGFloat(dmWidth))) - let y = Int(round((1 - norm.y) * CGFloat(dmHeight))) + let viewToImage = frame.displayTransform(for: currentOrientation, viewportSize: viewSize).inverted() + let normView = CGPoint(x: screenPoint.x / viewSize.width, y: screenPoint.y / viewSize.height) + let normImage = normView.applying(viewToImage) + print("Normalized view: \(normView) → normalized image: \(normImage)") - guard x >= 0, x < dmWidth, y >= 0, y < dmHeight else { return nil } + // Depth map indices from normalized image coords + let x = Int(round(normImage.x * CGFloat(dmWidth))) + let y = Int(round(normImage.y * CGFloat(dmHeight))) + print("Depth map coordinates: (\(x), \(y)) of (\(dmWidth), \(dmHeight))") + + guard x >= 0, x < dmWidth, y >= 0, y < dmHeight else { + print("Depth coordinates out of bounds: x=\(x), y=\(y), bounds=(\(dmWidth), \(dmHeight))") + return nil + } CVPixelBufferLockBaseAddress(depthMap, .readOnly) defer { CVPixelBufferUnlockBaseAddress(depthMap, .readOnly) } @@ -323,20 +391,31 @@ class ARViewModel: ObservableObject{ let base = CVPixelBufferGetBaseAddress(depthMap)!.assumingMemoryBound(to: Float.self) let rowStride = CVPixelBufferGetBytesPerRow(depthMap) / MemoryLayout.size let depth = base[y * rowStride + x] + print("Raw depth value: \(depth)") - guard depth.isFinite && depth > 0 else { return nil } + guard depth.isFinite && depth > 0 else { + print("Invalid depth: isFinite=\(depth.isFinite), value=\(depth)") + return nil + } - // Convert screen point + depth to world position + // Convert image pixel coords + depth to world position let cameraIntrinsics = frame.camera.intrinsics let cameraTransform = frame.camera.transform + let imageResolution = frame.camera.imageResolution + let imgW = Float(imageResolution.width) + let imgH = Float(imageResolution.height) + let u_img = Float(normImage.x) * imgW + let v_img = Float(normImage.y) * imgH + + print("Image pixel coords (u,v): (\(u_img), \(v_img)) of (\(imgW), \(imgH))") let fx = cameraIntrinsics.columns.0.x let fy = cameraIntrinsics.columns.1.y let cx = cameraIntrinsics.columns.2.x let cy = cameraIntrinsics.columns.2.y - let cameraX = (Float(screenPoint.x) - cx) / fx * depth - let cameraY = (Float(screenPoint.y) - cy) / fy * depth + let cameraX = (u_img - cx) / fx * depth + let cameraY = -((v_img - cy) / fy) * depth // Flip Y to fix top/bottom inversion let cameraZ = -depth let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) @@ -457,9 +536,11 @@ class ARViewModel: ObservableObject{ } else { depthStatus.setUnavailable() } - configuration.planeDetection = [] - configuration.environmentTexturing = .none // No environment texturing - configuration.sceneReconstruction = [] // No scene reconstruction + configuration.planeDetection = [.horizontal, .vertical] + if ARWorldTrackingConfiguration.supportsSceneReconstruction(.mesh) { + configuration.sceneReconstruction = .mesh + } + configuration.environmentTexturing = .none configuration.isAutoFocusEnabled = false // Run the session with the configuration From b53a4e198984dd0d11ecb1cee896af3905d339bd Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Wed, 10 Sep 2025 01:45:05 -0400 Subject: [PATCH 28/56] AR goal viz: revert to world-origin sphere flow; only visualize on goal mode tap; fallback along tap ray; clean logs. ML: set input size 256x256 for standard models, 224x224 for point-conditioned; adapt array conversion to size. Misc: keep ARKit raycast + anchor posting for ML; no odometry. --- AnySense.xcodeproj/project.pbxproj | 7 +- AnySense/Managers/ARViewContainer.swift | 196 +------- .../Managers/ARVisualizationManager.swift | 28 +- AnySense/Managers/MLInferenceManager.swift | 143 ++---- AnySense/Managers/OdometryPointTracker.swift | 422 ------------------ 5 files changed, 56 insertions(+), 740 deletions(-) delete mode 100644 AnySense/Managers/OdometryPointTracker.swift diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 31747df..50ff99d 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -3,14 +3,13 @@ archiveVersion = 1; classes = { }; - objectVersion = 70; + objectVersion = 56; objects = { /* Begin PBXBuildFile section */ 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */; }; 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */; }; 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */; }; - 01D2FDD72E64C33600F0BA98 /* OdometryPointTracker.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01D2FDD62E64C33600F0BA98 /* OdometryPointTracker.swift */; }; 01D2FDD82E64C33600F0BA98 /* ActionTransformUtils.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */; }; 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */; }; 01F5B7C62DEA698D00061B16 /* MLInferenceResultsView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */; }; @@ -51,7 +50,6 @@ /* Begin PBXFileReference section */ 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARVisualizationManager.swift; sourceTree = ""; }; 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ActionTransformUtils.swift; sourceTree = ""; }; - 01D2FDD62E64C33600F0BA98 /* OdometryPointTracker.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = OdometryPointTracker.swift; sourceTree = ""; }; 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceManager.swift; sourceTree = ""; }; 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceResultsView.swift; sourceTree = ""; }; 01F5B7C72DEA6A0000061B16 /* ModelManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ModelManager.swift; sourceTree = ""; }; @@ -76,6 +74,7 @@ BA11D17F77459219187F7A30 /* Pods-AnySense.release.xcconfig */ = {isa = PBXFileReference; includeInIndex = 1; lastKnownFileType = text.xcconfig; name = "Pods-AnySense.release.xcconfig"; path = "Target Support Files/Pods-AnySense/Pods-AnySense.release.xcconfig"; sourceTree = ""; }; E98E38A27D08BC9D5BE3E2E6 /* Pods-AnySense.debug.xcconfig */ = {isa = PBXFileReference; includeInIndex = 1; lastKnownFileType = text.xcconfig; name = "Pods-AnySense.debug.xcconfig"; path = "Target Support Files/Pods-AnySense/Pods-AnySense.debug.xcconfig"; sourceTree = ""; }; /* End PBXFileReference section */ + /* Begin PBXFrameworksBuildPhase section */ B9104F572BFDE63A000D4DDD /* Frameworks */ = { isa = PBXFrameworksBuildPhase; @@ -143,7 +142,6 @@ B9E4B2282D62A9BA0032E877 /* ARViewContainer.swift */, 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */, 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */, - 01D2FDD62E64C33600F0BA98 /* OdometryPointTracker.swift */, 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */, 01F5B7C72DEA6A0000061B16 /* ModelManager.swift */, B9E4B2292D62A9BA0032E877 /* BluetoothManager.swift */, @@ -349,7 +347,6 @@ B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */, 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */, 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */, - 01D2FDD72E64C33600F0BA98 /* OdometryPointTracker.swift in Sources */, 01D2FDD82E64C33600F0BA98 /* ActionTransformUtils.swift in Sources */, 01F5B7C82DEA6A0000061B16 /* ModelManager.swift in Sources */, B9E4B22D2D62A9BA0032E877 /* BluetoothManager.swift in Sources */, diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 59060ff..9db649b 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -76,6 +76,12 @@ struct ARViewContainer: UIViewRepresentable { if let hit = arView.raycast(from: location, allowing: .estimatedPlane, alignment: .any).first { let t = hit.worldTransform let world = simd_float3(t.columns.3.x, t.columns.3.y, t.columns.3.z) + + // Create a native ARKit anchor at the hit (world-locked) + let goalAnchor = ARAnchor(name: "goal", transform: t) + arView.session.add(anchor: goalAnchor) + + // Notify ML pipeline with the world point; ARVisualizationManager will handle visuals NotificationCenter.default.post( name: NSNotification.Name("ARViewTapForGoal"), object: nil, @@ -229,200 +235,14 @@ class ARViewModel: ObservableObject{ if let world = notif.userInfo?["worldPoint"] as? simd_float3 { print("Using raycast world point: \(world)") ml.setGoalPoint(world) - self.arVisualizationManager.setTargetPose(world) self.goalTapModeEnabled = false return } - // Otherwise, fall back to computing from screen point - guard let location = notif.userInfo?["location"] as? CGPoint, - let bounds = notif.userInfo?["bounds"] as? CGRect else { - print(" Missing location or bounds data") - return - } - print(" Tap location: \(location), bounds: \(bounds)") - if let frame = self.session.currentFrame { - let depth = self.depthStatus.isDepthAvailable ? (frame.sceneDepth?.depthMap) : nil - print("Depth available: \(depth != nil)") - if let world = self.getWorldPositionFromTap(location, frame: frame, viewBounds: bounds) { - print(" World position calculated: \(world)") - ml.setGoalPoint(world) - self.arVisualizationManager.setTargetPose(world) - print(" Goal point set and visualization updated") - self.goalTapModeEnabled = false - } else { - print(" Failed to get world position from tap") - } - } + // No worldPoint provided (no raycast hit) — ignore tap } } - // Simple, direct approach: Use ARKit's built-in methods + LiDAR depth sampling - private func getWorldPositionFromTap(_ tapPoint: CGPoint, frame: ARFrame, viewBounds: CGRect) -> simd_float3? { - print("getWorldPositionFromTap called with: \(tapPoint)") - - // 1) First try LiDAR depth if available (most accurate) - if let sceneDepth = frame.sceneDepth { - print(" Trying LiDAR depth method") - if let worldPos = getWorldPositionFromDepth(tapPoint, frame: frame, sceneDepth: sceneDepth, viewBounds: viewBounds) { - print(" LiDAR depth success: \(worldPos)") - return worldPos - } else { - print(" LiDAR depth failed") - } - } else { - print(" No scene depth available") - } - - // 2) Fallback to ARKit raycasting - print(" Trying ARKit raycast fallback") - let normalizedPoint = CGPoint( - x: tapPoint.x / UIScreen.main.bounds.width, - y: tapPoint.y / UIScreen.main.bounds.height - ) - print(" Normalized point: \(normalizedPoint)") - - let query = frame.raycastQuery(from: normalizedPoint, allowing: .estimatedPlane, alignment: .any) - let results = session.raycast(query) - print(" Raycast results count: \(results.count)") - - if let result = results.first { - let position = result.worldTransform.columns.3 - let worldPos = simd_float3(position.x, position.y, position.z) - print(" Raycast success: \(worldPos)") - return worldPos - } - - // 3) Final fallback: Use fixed depth estimate with displayTransform and original intrinsics - print("Trying fixed depth fallback (1m)") - let estimatedDepth: Float = 1.0 - - // Get camera parameters - let camera = frame.camera - let cameraTransform = camera.transform - let intrinsics = camera.intrinsics - let imageResolution = frame.camera.imageResolution - let imageWidth = Float(imageResolution.width) - let imageHeight = Float(imageResolution.height) - - let fx = intrinsics.columns.0.x - let fy = intrinsics.columns.1.y - let cx = intrinsics.columns.2.x - let cy = intrinsics.columns.2.y - - // Map tap point from view coords → normalized view → normalized image using displayTransform - let viewSize = viewBounds.size - // Detect current device orientation - let currentOrientation: UIInterfaceOrientation - if #available(iOS 13.0, *) { - currentOrientation = UIApplication.shared.windows.first?.windowScene?.interfaceOrientation ?? .portrait - } else { - currentOrientation = UIApplication.shared.statusBarOrientation - } - let viewToImage = frame.displayTransform(for: currentOrientation, viewportSize: viewSize).inverted() - var normView = CGPoint(x: tapPoint.x / viewSize.width, y: tapPoint.y / viewSize.height) - let normImage = normView.applying(viewToImage) - - // Convert normalized image coords to pixel coords in captured image space - let u_img = Float(normImage.x) * imageWidth - let v_img = Float(normImage.y) * imageHeight - - print("=== COORDINATE DEBUG ===") - print("Tap point: \(tapPoint)") - print("View bounds: \(viewBounds)") - print("Camera image resolution: \(imageResolution)") - print("Orientation: \(currentOrientation)") - print("Normalized view: \(normView) → normalized image: \(normImage)") - print("Pixel coords (u,v): (\(u_img), \(v_img))") - print("Intrinsics - fx: \(fx), fy: \(fy), cx: \(cx), cy: \(cy)") - - // Convert pixel coords + fixed depth to camera space - let cameraX = (u_img - cx) / fx * estimatedDepth - let cameraY = -((v_img - cy) / fy) * estimatedDepth // Flip Y to fix top/bottom inversion - let cameraZ = -estimatedDepth // Negative Z in camera space - - print("Camera space point - X: \(cameraX), Y: \(cameraY), Z: \(cameraZ)") - - // Transform from camera space to world space - let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) - let worldPoint = simd_mul(cameraTransform, cameraPoint) - - print("Fixed depth success: \(simd_float3(worldPoint.x, worldPoint.y, worldPoint.z))") - return simd_float3(worldPoint.x, worldPoint.y, worldPoint.z) - } - - private func getWorldPositionFromDepth(_ screenPoint: CGPoint, frame: ARFrame, sceneDepth: ARDepthData, viewBounds: CGRect) -> simd_float3? { - let depthMap = sceneDepth.depthMap - let dmWidth = CVPixelBufferGetWidth(depthMap) - let dmHeight = CVPixelBufferGetHeight(depthMap) - - print("Depth map size: \(dmWidth) x \(dmHeight)") - - // Convert screen point to image/depth coordinates using ARKit display transform - let viewSize = viewBounds.size - print("ARView bounds: \(viewBounds)") - print("View size: \(viewSize)") - - let currentOrientation: UIInterfaceOrientation - if #available(iOS 13.0, *) { - currentOrientation = UIApplication.shared.windows.first?.windowScene?.interfaceOrientation ?? .portrait - } else { - currentOrientation = UIApplication.shared.statusBarOrientation - } - print("Current orientation: \(currentOrientation)") - - let viewToImage = frame.displayTransform(for: currentOrientation, viewportSize: viewSize).inverted() - let normView = CGPoint(x: screenPoint.x / viewSize.width, y: screenPoint.y / viewSize.height) - let normImage = normView.applying(viewToImage) - print("Normalized view: \(normView) → normalized image: \(normImage)") - - // Depth map indices from normalized image coords - let x = Int(round(normImage.x * CGFloat(dmWidth))) - let y = Int(round(normImage.y * CGFloat(dmHeight))) - print("Depth map coordinates: (\(x), \(y)) of (\(dmWidth), \(dmHeight))") - - guard x >= 0, x < dmWidth, y >= 0, y < dmHeight else { - print("Depth coordinates out of bounds: x=\(x), y=\(y), bounds=(\(dmWidth), \(dmHeight))") - return nil - } - - CVPixelBufferLockBaseAddress(depthMap, .readOnly) - defer { CVPixelBufferUnlockBaseAddress(depthMap, .readOnly) } - - let base = CVPixelBufferGetBaseAddress(depthMap)!.assumingMemoryBound(to: Float.self) - let rowStride = CVPixelBufferGetBytesPerRow(depthMap) / MemoryLayout.size - let depth = base[y * rowStride + x] - print("Raw depth value: \(depth)") - - guard depth.isFinite && depth > 0 else { - print("Invalid depth: isFinite=\(depth.isFinite), value=\(depth)") - return nil - } - - // Convert image pixel coords + depth to world position - let cameraIntrinsics = frame.camera.intrinsics - let cameraTransform = frame.camera.transform - let imageResolution = frame.camera.imageResolution - let imgW = Float(imageResolution.width) - let imgH = Float(imageResolution.height) - let u_img = Float(normImage.x) * imgW - let v_img = Float(normImage.y) * imgH - - print("Image pixel coords (u,v): (\(u_img), \(v_img)) of (\(imgW), \(imgH))") - - let fx = cameraIntrinsics.columns.0.x - let fy = cameraIntrinsics.columns.1.y - let cx = cameraIntrinsics.columns.2.x - let cy = cameraIntrinsics.columns.2.y - - let cameraX = (u_img - cx) / fx * depth - let cameraY = -((v_img - cy) / fy) * depth // Flip Y to fix top/bottom inversion - let cameraZ = -depth - - let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) - let worldPoint = simd_mul(cameraTransform, cameraPoint) - - return simd_float3(worldPoint.x, worldPoint.y, worldPoint.z) - } + diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 5a1d965..6955a6b 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -54,6 +54,7 @@ class ARVisualizationManager: ObservableObject { private var targetPose: SIMD3? private var actualDevicePose: SIMD3 = SIMD3(0, 0, 0) private var goalPointEntity: ModelEntity? + private var goalAnchorEntity: AnchorEntity? // Movement tracking private var worldOrigin: SIMD3 = SIMD3(0, 0, 0) @@ -140,7 +141,7 @@ class ARVisualizationManager: ObservableObject { currentArView.scene.addAnchor(anchor) worldOriginAnchor = anchor - print("🌍 World origin set at: \(worldOrigin) and anchor created") + print("World origin set at: \(worldOrigin) and anchor created") } private func resetMovementTracking() { @@ -216,18 +217,12 @@ class ARVisualizationManager: ObservableObject { print("AR Visualization frequency set to: \(frequency.displayName)") } - // MARK: - Odometry/Device Pose Integration + // MARK: - Device Pose Integration func updateActualDevicePose(from arFrame: ARFrame) { let t = arFrame.camera.transform actualDevicePose = SIMD3(t.columns.3.x, t.columns.3.y, t.columns.3.z) } - func updateTargetFromOdometry(_ result: OdometryTrackingResult) { - targetPose = result.world3DPoint - ensureVisualizationReady() - updateGoalPointVisualization() - } - func setTargetPose(_ worldPoint: SIMD3) { targetPose = worldPoint // Ensure visualization is ready before creating goal point @@ -482,7 +477,7 @@ class ARVisualizationManager: ObservableObject { guard let targetPose = targetPose, let worldOriginAnchor = worldOriginAnchor, hasEstablishedOrigin else { - print("❌ Cannot create goal visualization - targetPose: \(targetPose?.debugDescription ?? "nil"), anchor: \(worldOriginAnchor != nil), origin: \(hasEstablishedOrigin)") + print(" Cannot create goal visualization - targetPose: \(targetPose?.debugDescription ?? "nil"), anchor: \(worldOriginAnchor != nil), origin: \(hasEstablishedOrigin)") goalPointEntity?.removeFromParent() goalPointEntity = nil return @@ -492,9 +487,9 @@ class ARVisualizationManager: ObservableObject { goalPointEntity?.removeFromParent() goalPointEntity = nil - // Create a larger, more visible sphere - let sphereMesh = MeshResource.generateSphere(radius: 0.1) // 10cm radius - much larger - let goalMaterial = SimpleMaterial(color: .systemRed, isMetallic: false) // Bright red color + // Create a visible sphere + let sphereMesh = MeshResource.generateSphere(radius: 0.01) + let goalMaterial = SimpleMaterial(color: .systemRed, isMetallic: false) goalPointEntity = ModelEntity(mesh: sphereMesh, materials: [goalMaterial]) // Position the sphere at the target pose (relative to world origin) @@ -502,10 +497,17 @@ class ARVisualizationManager: ObservableObject { goalPointEntity?.position = relativePosition worldOriginAnchor.addChild(goalPointEntity!) - print("🎯 Goal point visualization created:") + print("Goal point visualization created:") print(" Target pose (world): \(targetPose)") print(" World origin: \(worldOrigin)") print(" Relative position: \(relativePosition)") print(" Distance from origin: \(length(relativePosition))m") } + + // MARK: - Anchor-based goal visualization + func attachGoalAnchor(_ arAnchor: ARAnchor) { + if debugLoggingEnabled { + print("[Viz] attachGoalAnchor deprecated; use setTargetPose(world)") + } + } } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index ad1de13..2316b3c 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -42,8 +42,8 @@ class MLInferenceManager: ObservableObject { // MARK: - Goal Point Management private var goalPointQueue = DispatchQueue(label: "GoalPointQueue", qos: .userInitiated) - // Goal conditioning mode (matching Python goal_dim) - private var goalDimension: Int = 2 // Default to 2D mode, can be 3 for 3D mode + // Goal conditioning mode (point-conditioned models use 3D goals) + private var goalDimension: Int = 3 // MARK: - Model Management private var modelManager: ModelManager @@ -52,13 +52,9 @@ class MLInferenceManager: ObservableObject { // MARK: - AR Visualization Integration weak var arVisualizationManager: ARVisualizationManager? - // MARK: - Odometry Point Tracking - @Published var odometryTracker = OdometryPointTracker() - @Published var enableOdometryTracking: Bool = true - // MARK: - Frame Processing (Taken from ARViewContainer) private let ciContext: CIContext - private let modelInputSize = CGSize(width: 256, height: 256) + private var modelInputSize = CGSize(width: 224, height: 224) private var modelInputTransform: CGAffineTransform? // MARK: - Inference Settings @@ -129,14 +125,21 @@ class MLInferenceManager: ObservableObject { // Extract model metadata for type detection modelMetadata = try ModelMetadata(from: loadedModel) - setupModelInputTransform() - - // Set goal dimension based on model type - if modelMetadata?.modelType == .pointConditioned { - goalDimension = 3 // VQ-BeT models expect 3D coordinates + // Set input size based on model type: standard = 256, point-conditioned = 224 + if let meta = modelMetadata { + switch meta.modelType { + case .standard: + modelInputSize = CGSize(width: 256, height: 256) + case .pointConditioned: + modelInputSize = CGSize(width: 224, height: 224) + } } else { - goalDimension = 2 // Standard models use 2D + modelInputSize = CGSize(width: 224, height: 224) } + setupModelInputTransform() + + // Force 3D goal conditioning + goalDimension = 3 // Clear goal point if switching to non-point-conditioned model if modelMetadata?.requiresGoalPoint == false { @@ -187,52 +190,7 @@ class MLInferenceManager: ObservableObject { currentGoalPoint = nil } - // MARK: - Odometry Integration Methods - - /// Start odometry tracking with screen point (matching Python workflow) - func startOdometryTrackingWithScreenPoint( - screenPoint: CGPoint, - in view: UIView, - arFrame: ARFrame, - depthMap: CVPixelBuffer? - ) -> Bool { - guard enableOdometryTracking else { - return false - } - - guard let session = getARSession() else { - return false - } - - let success = odometryTracker.startTracking( - screenPoint: screenPoint, - in: view, - arFrame: arFrame, - session: session, - depthMap: depthMap - ) - - // Odometry tracking started - - return success - } - - /// Update odometry tracking (step_n > 0 equivalent) - func updateOdometryTracking(arFrame: ARFrame) { - // Always update actual device pose for non-point-conditioned model deviation tracking - arVisualizationManager?.updateActualDevicePose(from: arFrame) - - guard enableOdometryTracking, - odometryTracker.trackingState == .tracking else { - return - } - - // Get updated odometry result and pass to visualization - if let odometryResult = odometryTracker.updateTracking(currentFrame: arFrame) { - // Update visualization with new target position from odometry - arVisualizationManager?.updateTargetFromOdometry(odometryResult) - } - } + // MARK: - Odometry Integration Methods (removed) /// Set goal dimension (2D or 3D goal conditioning) func setGoalDimension(_ dimension: Int) { @@ -255,35 +213,8 @@ class MLInferenceManager: ObservableObject { // labels.json mapping from camera frame return [-p_c4.x, p_c4.z, p_c4.y] } - // 2D goals: project world-locked goal point to current camera view - if let p_w = currentGoalPoint, let session = getARSession(), let frame = session.currentFrame { - // Project world point to current camera view - let T_wc = frame.camera.transform - let T_cw = simd_inverse(T_wc) - let p_c4 = simd_mul(T_cw, simd_float4(p_w.x, p_w.y, p_w.z, 1.0)) - let p_c = simd_float3(p_c4.x, p_c4.y, p_c4.z) - - // Project to normalized screen coordinates [0,1] - let intrinsics = frame.camera.intrinsics - let fx = intrinsics.columns.0.x - let fy = intrinsics.columns.1.y - let cx = intrinsics.columns.2.x - let cy = intrinsics.columns.2.y - - let screenX = (p_c.x * fx / (-p_c.z)) + cx - let screenY = (p_c.y * fy / (-p_c.z)) + cy - - let imageWidth = frame.camera.imageResolution.width - let imageHeight = frame.camera.imageResolution.height - - let normalizedX = screenX / Float(imageWidth) - let normalizedY = screenY / Float(imageHeight) - - // Clamp to [0,1] range - return [max(0, min(1, normalizedX)), max(0, min(1, normalizedY))] - } else { - return [0.5, 0.5] // Center fallback - } + // If model expects 2D goals, return nil since we only support 3D goals now + return nil } // MARK: - AR Session Access @@ -300,9 +231,9 @@ class MLInferenceManager: ObservableObject { // MARK: - Inference Methods (Using existing frame processing patterns) func performInference(on pixelBuffer: CVPixelBuffer, arFrame: ARFrame?, timestamp: CFTimeInterval = CACurrentMediaTime()) { - // Update odometry tracking to have consistent goal point for model input preparation + // Update device pose for visualization (optional) if let frame = arFrame { - updateOdometryTracking(arFrame: frame) + arVisualizationManager?.updateActualDevicePose(from: frame) } performInference(on: pixelBuffer, timestamp: timestamp) @@ -382,7 +313,7 @@ class MLInferenceManager: ObservableObject { // Process image to match expected rank (support 4D [1,3,H,W] and 5D [1,1,3,H,W]) let imageArray = try processFrameForVQBeT( pixelBuffer, - inputSize: metadata.imageInputSize ?? CGSize(width: 256, height: 256), + inputSize: CGSize(width: 224, height: 224), expectedRank: expectedImageRank ) @@ -591,8 +522,13 @@ class MLInferenceManager: ObservableObject { // MARK: - Simplified Pixel Buffer to MLMultiArray Conversion private func convertProcessedPixelBufferToMLMultiArray(_ pixelBuffer: CVPixelBuffer) throws -> MLMultiArray { - // Explicitly index as [B=1, T=1, C=3, H=256, W=256] - let inputArray = try MLMultiArray(shape: [1, 1, 3, 256, 256], dataType: .float32) + // Explicitly index as [B=1, T=1, C=3, H=modelInputSize.height, W=modelInputSize.width] + let height = Int(modelInputSize.height) + let width = Int(modelInputSize.width) + let inputArray = try MLMultiArray( + shape: [1, 1, 3, NSNumber(value: height), NSNumber(value: width)], + dataType: .float32 + ) guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get pixel buffer base address"]) @@ -603,8 +539,8 @@ class MLInferenceManager: ObservableObject { let bytesPerPixel = 4 // ARGB format // Since we're using Core Image processing, we have consistent ARGB format - for y in 0..<256 { - for x in 0..<256 { + for y in 0.. Bool { - // Check if odometry tracking is properly set up - let hasTracker = odometryTracker != nil - let isEnabled = enableOdometryTracking - let hasARConnection = arViewContainer != nil - let hasVisualizationConnection = arVisualizationManager != nil - - let isValid = hasTracker && hasARConnection && hasVisualizationConnection - - print("Odometry validation: \(isValid ? "OK" : "Failed")") - if !isValid { - print("Issues: tracker=\(hasTracker), AR=\(hasARConnection), viz=\(hasVisualizationConnection)") - } - - return isValid - } } diff --git a/AnySense/Managers/OdometryPointTracker.swift b/AnySense/Managers/OdometryPointTracker.swift deleted file mode 100644 index 096bdb6..0000000 --- a/AnySense/Managers/OdometryPointTracker.swift +++ /dev/null @@ -1,422 +0,0 @@ -// -// OdometryPointTracker.swift -// AnySense -// -// Correct odometry-based point tracking matching Python implementation -// - -import Foundation -import ARKit -import simd - -// MARK: - Tracking State -enum OdometryTrackingState { - case idle - case tracking - case lost - - var description: String { - switch self { - case .idle: return "Idle" - case .tracking: return "Tracking" - case .lost: return "Lost" - } - } -} - -// MARK: - Point Tracking Result (matches Python output) -struct OdometryTrackingResult { - let normalized2DPoint: CGPoint // [0,1] normalized coordinates for model (clicked_point equivalent) - let world3DPoint: simd_float3 // 3D point in camera coordinate system (new_3d_point equivalent) - let screenPixelPoint: CGPoint // Screen pixel coordinates for visualization - let isVisible: Bool // Whether point is visible in current view - let confidence: Float // Tracking quality -} - -// MARK: - Python-Style Odometry Point Tracker -class OdometryPointTracker: ObservableObject { - - // MARK: - Published Properties - @Published var trackingState: OdometryTrackingState = .idle - @Published var currentResult: OdometryTrackingResult? - @Published var isEnabled: Bool = true - - // MARK: - Private Properties (matching Python variables) - - // Initial state (step_n == 0 in Python) - private var startPose: simd_float4x4 = matrix_identity_float4x4 - private var startPoseMatrix: simd_float4x4 = matrix_identity_float4x4 - - // Original object position (equivalent to object_x, object_y, object_depth) - private var originalObjectPosition: simd_float3 = simd_float3(0, 0, 0) // In normalized camera coordinates - - // Camera parameters - private var cameraIntrinsics: matrix_float3x3? - private var imageSize: CGSize = CGSize(width: 256, height: 256) // Model input size - private var actualImageSize: CGSize = CGSize(width: 1920, height: 1440) // Actual camera resolution - - // Tracking quality - private var hasInitialPose: Bool = false - private var trackingHistory: [Float] = [] - private let maxHistoryLength: Int = 30 - - // Constants matching Python - let depthOffset: Float = 0.05 // DEPTH_OFFSET from Python (public for validation) - - init() { - // Initialize odometry point tracker - } - - // MARK: - Public Interface (matching Python workflow) - - /// Start tracking (equivalent to step_n == 0 in Python) - func startTracking( - screenPoint: CGPoint, - in view: UIView, - arFrame: ARFrame, - session: ARSession, - depthMap: CVPixelBuffer? - ) -> Bool { - - // Starting odometry tracking - - // Store initial pose (equivalent to self.start_pose and self.start_pose_matrix) - self.startPose = arFrame.camera.transform - self.startPoseMatrix = arFrame.camera.transform - self.cameraIntrinsics = arFrame.camera.intrinsics - self.actualImageSize = CGSize( - width: CVPixelBufferGetWidth(arFrame.capturedImage), - height: CVPixelBufferGetHeight(arFrame.capturedImage) - ) - - // Convert screen point to normalized camera coordinates (equivalent to _point2d_to_3d) - guard let objectPosition = convertScreenPointTo3D( - screenPoint: screenPoint, - in: view, - frame: arFrame, - session: session, - depthMap: depthMap - ) else { - return false - } - - self.originalObjectPosition = objectPosition - self.hasInitialPose = true - self.trackingState = .tracking - - // Create initial result (equivalent to new_3d_point = get_new_2d_point(..., None)) - let initialResult = createTrackingResult( - objectPosition: objectPosition, - currentPose: startPose, - relativePose: matrix_identity_float4x4 - ) - - self.currentResult = initialResult - - return true - } - - /// Update tracking (equivalent to step_n > 0 in Python) - func updateTracking(currentFrame: ARFrame) -> OdometryTrackingResult? { - guard isEnabled && hasInitialPose && trackingState == .tracking else { - return currentResult - } - - let currentPose = currentFrame.camera.transform - - // Calculate relative transformation (equivalent to Python logic) - // relative_transformation_matrix = np.linalg.inv(self.start_pose_matrix) @ current_pose_matrix - let relativePose = simd_mul(simd_inverse(startPoseMatrix), currentPose) - - // Get new 2D point using the same logic as Python - // new_2d_point, new_3d_point = get_new_2d_point(self.object_x, self.object_y, self.object_depth, relative_transformation_matrix) - let result = createTrackingResult( - objectPosition: originalObjectPosition, - currentPose: currentPose, - relativePose: relativePose - ) - - // Update tracking quality - updateTrackingMetrics(result: result) - - self.currentResult = result - - return result - } - - /// Reset tracking - func resetTracking() { - hasInitialPose = false - trackingState = .idle - currentResult = nil - trackingHistory.removeAll() - } - - /// Get current goal point for model (2D or 3D based on goal_dim) - func getGoalPointForModel(goalDimension: Int) -> [Float]? { - guard let result = currentResult else { return nil } - - if goalDimension == 3 { - // Return 3D point (new_3d_point converted to labels.json frame) - let labelPoint = convertToLabelsFrame(result.world3DPoint) - return [labelPoint.x, labelPoint.y, labelPoint.z] - } else { - // Return 2D normalized point (clicked_point equivalent) - return [Float(result.normalized2DPoint.x), Float(result.normalized2DPoint.y)] - } - } - - /// Enable/disable tracking - func setEnabled(_ enabled: Bool) { - isEnabled = enabled - if !enabled { - trackingState = .idle - } - } - - // MARK: - Private Implementation (matching Python logic) - - /// Convert screen point to 3D with robust fallback strategies - private func convertScreenPointTo3D( - screenPoint: CGPoint, - in view: UIView, - frame: ARFrame, - session: ARSession, - depthMap: CVPixelBuffer? - ) -> simd_float3? { - - // Converting screen point to 3D - - // Normalize screen coordinates to [0,1] (matching Python: p2d[0] / 256, p2d[1] / 256) - let normalizedX = screenPoint.x / view.bounds.width - let normalizedY = screenPoint.y / view.bounds.height - - // Strategy 1: Try depth map sampling (highest accuracy) - if let depthBuffer = depthMap { - let sampledDepth = sampleDepthMap( - depthBuffer: depthBuffer, - normalizedX: normalizedX, - normalizedY: normalizedY - ) - - if sampledDepth > 0.1 && sampledDepth < 10.0 { // Valid depth range - let finalDepth = sampledDepth + depthOffset - return simd_float3(Float(normalizedX), Float(normalizedY), finalDepth) - } - } - - // Strategy 2: ARKit raycast hit testing (reliable fallback) - let normalizedPoint = CGPoint(x: normalizedX, y: normalizedY) - - // Create raycast query for existing planes or surfaces - let query = frame.raycastQuery(from: normalizedPoint, allowing: .existingPlaneGeometry, alignment: .any) - - let results = session.raycast(query) - if let result = results.first { - let hitPoint = result.worldTransform.columns.3 - let cameraPos = frame.camera.transform.columns.3 - let distance = length(simd_float3(hitPoint.x - cameraPos.x, hitPoint.y - cameraPos.y, hitPoint.z - cameraPos.z)) - - if distance > 0.1 && distance < 10.0 { - let finalDepth = distance + depthOffset - return simd_float3(Float(normalizedX), Float(normalizedY), finalDepth) - } - } - - // Strategy 3: Simple fixed distance fallback - let fixedDepth: Float = 1.0 + depthOffset // 1 meter default - - return simd_float3(Float(normalizedX), Float(normalizedY), fixedDepth) - } - - - /// Sample depth map (equivalent to np_depth[int(y * 192), int(x * 256)]) - private func sampleDepthMap( - depthBuffer: CVPixelBuffer, - normalizedX: CGFloat, - normalizedY: CGFloat - ) -> Float { - - let depthWidth = CVPixelBufferGetWidth(depthBuffer) - let depthHeight = CVPixelBufferGetHeight(depthBuffer) - - // Convert to depth map coordinates (matching Python indexing) - let depthX = Int(normalizedX * CGFloat(depthWidth)) - let depthY = Int(normalizedY * CGFloat(depthHeight)) - - // Ensure coordinates are within bounds - guard depthX >= 0 && depthX < depthWidth && depthY >= 0 && depthY < depthHeight else { - return 1.0 // Default depth - } - - // Read depth value - CVPixelBufferLockBaseAddress(depthBuffer, .readOnly) - defer { CVPixelBufferUnlockBaseAddress(depthBuffer, .readOnly) } - - guard let baseAddress = CVPixelBufferGetBaseAddress(depthBuffer) else { return 1.0 } - let bytesPerRow = CVPixelBufferGetBytesPerRow(depthBuffer) - let depthPointer = baseAddress.assumingMemoryBound(to: Float32.self) - - let pixelOffset = depthY * (bytesPerRow / MemoryLayout.stride) + depthX - let depth = depthPointer[pixelOffset] - - return depth > 0.1 ? depth : 1.0 // Return valid depth or default - } - - /// Create tracking result (equivalent to get_new_2d_point with transformation) - private func createTrackingResult( - objectPosition: simd_float3, - currentPose: simd_float4x4, - relativePose: simd_float4x4 - ) -> OdometryTrackingResult { - - // Apply relative transformation to get new position - // This is the key logic from Python: get_new_2d_point with relative_transformation_matrix - var transformedPosition = objectPosition - - if relativePose != matrix_identity_float4x4 { - // Transform the original position by the relative pose change - // This keeps the object fixed in world space and calculates its new appearance - let homogeneous = simd_float4(objectPosition.x, objectPosition.y, objectPosition.z, 1.0) - let transformed = simd_mul(relativePose, homogeneous) - transformedPosition = simd_float3(transformed.x, transformed.y, transformed.z) - } - - // Convert to screen pixel coordinates for visualization - let screenPixelPoint = convertNormalizedToScreenPixels( - normalized: CGPoint(x: CGFloat(transformedPosition.x), y: CGFloat(transformedPosition.y)) - ) - - // Check visibility (equivalent to checking if point is in bounds) - let isVisible = transformedPosition.x >= 0 && transformedPosition.x <= 1.0 && - transformedPosition.y >= 0 && transformedPosition.y <= 1.0 && - transformedPosition.z > 0 - - // Calculate confidence based on visibility and position - let confidence = calculateConfidence( - position: transformedPosition, - isVisible: isVisible - ) - - // Create world 3D point (for 3D goal conditioning) - let world3DPoint = convertToWorldCoordinates( - normalizedPosition: transformedPosition, - cameraPose: currentPose - ) - - return OdometryTrackingResult( - normalized2DPoint: CGPoint(x: CGFloat(transformedPosition.x), y: CGFloat(transformedPosition.y)), - world3DPoint: world3DPoint, - screenPixelPoint: screenPixelPoint, - isVisible: isVisible, - confidence: confidence - ) - } - - /// Convert normalized coordinates to screen pixels - private func convertNormalizedToScreenPixels(normalized: CGPoint) -> CGPoint { - // Convert from [0,1] normalized coordinates to actual screen pixels - let pixelX = normalized.x * imageSize.width - let pixelY = normalized.y * imageSize.height - return CGPoint(x: pixelX, y: pixelY) - } - - /// Convert normalized position to world coordinates - private func convertToWorldCoordinates( - normalizedPosition: simd_float3, - cameraPose: simd_float4x4 - ) -> simd_float3 { - - guard let intrinsics = cameraIntrinsics else { - // Fallback to simple conversion - return simd_float3( - (normalizedPosition.x - 0.5) * normalizedPosition.z * 2.0, - (normalizedPosition.y - 0.5) * normalizedPosition.z * 2.0, - normalizedPosition.z - ) - } - - // Convert from normalized coordinates to camera space using intrinsics - let fx = intrinsics.columns.0.x - let fy = intrinsics.columns.1.y - let cx = intrinsics.columns.2.x - let cy = intrinsics.columns.2.y - - let pixelX = normalizedPosition.x * Float(actualImageSize.width) - let pixelY = normalizedPosition.y * Float(actualImageSize.height) - - let cameraX = (pixelX - cx) / fx * normalizedPosition.z - let cameraY = (pixelY - cy) / fy * normalizedPosition.z - let cameraZ = normalizedPosition.z - - let cameraPoint = simd_float4(cameraX, cameraY, cameraZ, 1.0) - - // Transform to world coordinates - let worldPoint = simd_mul(cameraPose, cameraPoint) - - return simd_float3(worldPoint.x, worldPoint.y, worldPoint.z) - } - - /// Convert world point to labels.json frame (equivalent to Python conversion) - private func convertToLabelsFrame(_ worldPoint: simd_float3) -> simd_float3 { - // Python: new_3d_point = [-x, z, y] # converting from canonical frame to labels.json frame - return simd_float3(-worldPoint.x, worldPoint.z, worldPoint.y) - } - - /// Calculate tracking confidence - private func calculateConfidence(position: simd_float3, isVisible: Bool) -> Float { - var confidence: Float = 1.0 - - // Reduce confidence if not visible - if !isVisible { - confidence *= 0.3 - } - - // Reduce confidence based on distance from center - let centerDistance = length(simd_float2(position.x - 0.5, position.y - 0.5)) - confidence *= max(0.2, 1.0 - centerDistance * 2.0) - - // Reduce confidence based on depth - if position.z > 5.0 { - confidence *= 0.5 - } - - return max(0.0, min(1.0, confidence)) - } - - /// Update tracking quality metrics - private func updateTrackingMetrics(result: OdometryTrackingResult) { - trackingHistory.append(result.confidence) - if trackingHistory.count > maxHistoryLength { - trackingHistory.removeFirst() - } - - // Update tracking state based on confidence - if result.confidence < 0.2 { - trackingState = .lost - } else if result.confidence > 0.5 && trackingState == .lost { - trackingState = .tracking - } - } - - // MARK: - Simple Test Method (to avoid compilation error) - func runAllValidationTests() -> Bool { - // Simple validation - just return true since tests are removed - return true - } - -} - -// MARK: - Matrix Utilities -extension float4x4 { - static func == (lhs: float4x4, rhs: float4x4) -> Bool { - return lhs.columns.0 == rhs.columns.0 && - lhs.columns.1 == rhs.columns.1 && - lhs.columns.2 == rhs.columns.2 && - lhs.columns.3 == rhs.columns.3 - } - - static func != (lhs: float4x4, rhs: float4x4) -> Bool { - return !(lhs == rhs) - } -} \ No newline at end of file From 2346ac96aae1b3831485dba1a192e3ccc7137e1c Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Wed, 10 Sep 2025 12:39:58 -0400 Subject: [PATCH 29/56] fixed vis issue and reset goal point --- AnySense/Managers/MLInferenceManager.swift | 10 ++++++---- AnySense/Views/readView.swift | 8 +++++++- 2 files changed, 13 insertions(+), 5 deletions(-) diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 2316b3c..0d254f2 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -40,6 +40,11 @@ class MLInferenceManager: ObservableObject { private var inferenceQueue = DispatchQueue(label: "MLInferenceQueue", qos: .userInitiated) // MARK: - Goal Point Management + + func setGoalPoint(_ point: simd_float3) { + self.currentGoalPoint = point + arVisualizationManager?.setTargetPose(point) + } private var goalPointQueue = DispatchQueue(label: "GoalPointQueue", qos: .userInitiated) // Goal conditioning mode (point-conditioned models use 3D goals) @@ -181,10 +186,7 @@ class MLInferenceManager: ObservableObject { } // MARK: - Goal Point Management - func setGoalPoint(_ point: simd_float3) { - // Set goal point synchronously since UI needs immediate feedback - self.currentGoalPoint = point - } + func clearGoalPoint() { currentGoalPoint = nil diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 1ae6714..73109f3 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -198,7 +198,13 @@ struct ReadView : View{ HStack(spacing: 20) { VStack(spacing: 4) { Button(action: { - arViewModel.goalTapModeEnabled.toggle() + let newValue = !arViewModel.goalTapModeEnabled + arViewModel.goalTapModeEnabled = newValue + if newValue { + // Clear existing goal so the next tap sets a fresh one + arViewModel.mlManager?.clearGoalPoint() + arViewModel.arVisualizationManager.clearTargetPose() + } }) { Image(systemName: arViewModel.goalTapModeEnabled ? "dot.circle.fill" : "target") .resizable() From 2da378c946d2b42de5a5aa66cd702032a7b99871 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Wed, 10 Sep 2025 14:59:57 -0400 Subject: [PATCH 30/56] non-point condition to 224, remove extra orentation down check --- AnySense.xcodeproj/project.pbxproj | 4 ++-- AnySense/Managers/MLInferenceManager.swift | 26 +++++----------------- 2 files changed, 7 insertions(+), 23 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 50ff99d..b9ee745 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -541,7 +541,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = Krish.AnySenseTest; + PRODUCT_BUNDLE_IDENTIFIER = "Krish-2.AnySenseTest"; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; @@ -586,7 +586,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = Krish.AnySenseTest; + PRODUCT_BUNDLE_IDENTIFIER = "Krish-2.AnySenseTest"; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 0d254f2..48e8b59 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -89,7 +89,7 @@ class MLInferenceManager: ObservableObject { var rotationUnit: ActionTransformUtils.RotationUnit = .eulerXYZ var enableTransformDebug: Bool = true // Apply server-style image orientation (Record3D publisher does rotations/mirrors) - var applyServerImageOrientation: Bool = true + var applyServerImageOrientation: Bool = false // Initialization init(modelManager: ModelManager) { @@ -130,17 +130,8 @@ class MLInferenceManager: ObservableObject { // Extract model metadata for type detection modelMetadata = try ModelMetadata(from: loadedModel) - // Set input size based on model type: standard = 256, point-conditioned = 224 - if let meta = modelMetadata { - switch meta.modelType { - case .standard: - modelInputSize = CGSize(width: 256, height: 256) - case .pointConditioned: - modelInputSize = CGSize(width: 224, height: 224) - } - } else { - modelInputSize = CGSize(width: 224, height: 224) - } + // 224x224 input for all models + modelInputSize = CGSize(width: 224, height: 224) setupModelInputTransform() // Force 3D goal conditioning @@ -598,11 +589,7 @@ class MLInferenceManager: ObservableObject { let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) print("Coordinate Transform: \(report)") } - var robot = ActionTransformUtils.toRobotActions(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) - // Clamp gripper to [0,1] - if robot.count >= 7 { - robot[6] = max(0.0, min(1.0, robot[6])) - } + let robot = ActionTransformUtils.toRobotActions(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) print("Robot actions: [\(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") // Joint actions are now sent embedded in the main USB stream } @@ -643,10 +630,7 @@ class MLInferenceManager: ObservableObject { // Joint actions are automatically sent via USB stream (transform to robot frame) if jointPositions.count >= 7 { let src = Array(jointPositions.prefix(7)) - var robot = ActionTransformUtils.toRobotActions(src) - if robot.count >= 7 { - robot[6] = max(0.0, min(1.0, robot[6])) - } + let robot = ActionTransformUtils.toRobotActions(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) print("Robot actions: [\(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") // Joint actions are now sent embedded in the main USB stream } From e32bd4de347730388887f1bad641f4f2615cae75 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Thu, 11 Sep 2025 13:27:51 -0400 Subject: [PATCH 31/56] added depth as primary on lidar available phones --- AnySense/Managers/ARViewContainer.swift | 108 ++++++++++++++++++++- AnySense/Managers/MLInferenceManager.swift | 9 +- 2 files changed, 110 insertions(+), 7 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 9db649b..1aac7bc 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -72,7 +72,32 @@ struct ARViewContainer: UIViewRepresentable { @objc func handleTap(_ recognizer: UITapGestureRecognizer) { guard recognizer.state == .ended, let arView = recognizer.view as? ARView else { return } let location = recognizer.location(in: arView) - // Prefer RealityKit raycast to get an accurate world point + + // Try depth-based unprojection first (for LiDAR devices) + if let (worldPoint, method) = self.worldPointFromDepth(at: location, in: arView) { + print("Using \(method) method for 3D point: \(worldPoint)") + + // Create anchor at the world point + var t = matrix_identity_float4x4 + t.columns.3 = SIMD4(worldPoint.x, worldPoint.y, worldPoint.z, 1) + let goalAnchor = ARAnchor(name: "goal", transform: t) + arView.session.add(anchor: goalAnchor) + + // Notify ML pipeline with the world point + NotificationCenter.default.post( + name: NSNotification.Name("ARViewTapForGoal"), + object: nil, + userInfo: [ + "worldPoint": worldPoint, + "method": method, + "location": location, + "bounds": arView.bounds + ] + ) + return + } + + // Fallback to raycast if depth unavailable or failed if let hit = arView.raycast(from: location, allowing: .estimatedPlane, alignment: .any).first { let t = hit.worldTransform let world = simd_float3(t.columns.3.x, t.columns.3.y, t.columns.3.z) @@ -81,12 +106,15 @@ struct ARViewContainer: UIViewRepresentable { let goalAnchor = ARAnchor(name: "goal", transform: t) arView.session.add(anchor: goalAnchor) - // Notify ML pipeline with the world point; ARVisualizationManager will handle visuals + print("Using raycast fallback for 3D point: \(world)") + + // Notify ML pipeline with the world point NotificationCenter.default.post( name: NSNotification.Name("ARViewTapForGoal"), object: nil, userInfo: [ "worldPoint": world, + "method": "raycast", "location": location, "bounds": arView.bounds ] @@ -231,9 +259,10 @@ class ARViewModel: ObservableObject{ print("Goal tap ignored - conditions not met") return } - // Prefer direct world point from raycast if provided + // Prefer direct world point from depth/raycast if provided if let world = notif.userInfo?["worldPoint"] as? simd_float3 { - print("Using raycast world point: \(world)") + let method = notif.userInfo?["method"] as? String ?? "unknown" + print("Using \(method) world point: \(world)") ml.setGoalPoint(world) self.goalTapModeEnabled = false return @@ -1002,7 +1031,76 @@ class ARViewModel: ObservableObject{ // ML results are now accessed directly during streaming for better real-time performance } - + + // MARK: - Depth-Based Point Calculation + private func worldPointFromDepth(at location: CGPoint, in arView: ARView) -> (point: simd_float3, method: String)? { + guard let frame = arView.session.currentFrame, + let depth = frame.sceneDepth?.depthMap else { + return nil + } + + let depthWidth = CVPixelBufferGetWidth(depth) + let depthHeight = CVPixelBufferGetHeight(depth) + let viewBounds = arView.bounds + + // 1. Normalize tap location to view coordinates + let normView = CGPoint( + x: location.x / viewBounds.width, + y: location.y / viewBounds.height + ) + + // 2. Apply display transform to get camera image coordinates + let ori = arView.window?.windowScene?.interfaceOrientation ?? .portrait + let disp = frame.displayTransform(for: ori, viewportSize: viewBounds.size) + let camNorm = normView.applying(disp.inverted()) + + // 3. Map to depth pixel coordinates + let u = Int(clamp(camNorm.x, 0, 1) * CGFloat(depthWidth)) + let v = Int(clamp(camNorm.y, 0, 1) * CGFloat(depthHeight)) + + // 4. Sample depth with median filtering for noise reduction + CVPixelBufferLockBaseAddress(depth, .readOnly) + defer { CVPixelBufferUnlockBaseAddress(depth, .readOnly) } + + let base = CVPixelBufferGetBaseAddress(depth)!.assumingMemoryBound(to: Float32.self) + let bytesPerRow = CVPixelBufferGetBytesPerRow(depth) / MemoryLayout.size + let N = 3 + var samples: [Float] = [] + + for j in max(0, v - N)...min(depthHeight - 1, v + N) { + for i in max(0, u - N)...min(depthWidth - 1, u + N) { + let d = base[j * bytesPerRow + i] + if d.isFinite, d > 0 { + samples.append(d) + } + } + } + + guard !samples.isEmpty else { return nil } + samples.sort() + let depthValue = samples[samples.count / 2] // median + + // 5. Unproject to camera coordinates using intrinsics + let K = frame.camera.intrinsics + let fx = K.columns.0.x, fy = K.columns.1.y + let cx = K.columns.2.x, cy = K.columns.2.y + + let xc = (Float(u) - cx) * depthValue / fx + let yc = (Float(v) - cy) * depthValue / fy + let zc = depthValue + + // 6. Transform to world coordinates + let pc = simd_float4(xc, yc, zc, 1) + let pw = simd_mul(frame.camera.transform, pc) + + return (simd_float3(pw.x, pw.y, pw.z), "depth") + } + + // MARK: - Helper Functions + private func clamp(_ value: T, min minVal: T, max maxVal: T) -> T { + return min(max(value, minVal), maxVal) + } + } class AudioCaptureDelegate: NSObject, AVCaptureAudioDataOutputSampleBufferDelegate { diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 48e8b59..927bea9 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -197,14 +197,19 @@ class MLInferenceManager: ObservableObject { guard let session = getARSession(), let frame = session.currentFrame else { return nil } + + // Use the world-locked goal point (ARKit keeps it fixed in world space) guard let p_w = currentGoalPoint else { return nil } // World (ARKit) → Camera let T_wc = frame.camera.transform let T_cw = simd_inverse(T_wc) let p_c4 = simd_mul(T_cw, simd_float4(p_w.x, p_w.y, p_w.z, 1.0)) - // labels.json mapping from camera frame - return [-p_c4.x, p_c4.z, p_c4.y] + // Current logic + // camera: x right, y up, z back + // labels: x left, y forward, z down + // Mapping: x = -x_cam, y = -z_cam, z = -y_cam + return [-p_c4.x, -p_c4.z, -p_c4.y] } // If model expects 2D goals, return nil since we only support 3D goals now return nil From 45b1896096613f3dee849e2d4d9219c1365c44ae Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Fri, 12 Sep 2025 21:11:17 -0400 Subject: [PATCH 32/56] fixed goal transform, and working on viz --- AnySense/Managers/ARViewContainer.swift | 139 +++++++++--------- .../Managers/ARVisualizationManager.swift | 62 ++++---- AnySense/Managers/MLInferenceManager.swift | 3 +- 3 files changed, 109 insertions(+), 95 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 1aac7bc..7bf714f 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -74,7 +74,7 @@ struct ARViewContainer: UIViewRepresentable { let location = recognizer.location(in: arView) // Try depth-based unprojection first (for LiDAR devices) - if let (worldPoint, method) = self.worldPointFromDepth(at: location, in: arView) { + if let (worldPoint, method) = parent.worldPointFromDepth(at: location, in: arView) { print("Using \(method) method for 3D point: \(worldPoint)") // Create anchor at the world point @@ -132,6 +132,75 @@ struct ARViewContainer: UIViewRepresentable { ) } } + + // MARK: - Depth-Based Point Calculation + private func worldPointFromDepth(at location: CGPoint, in arView: ARView) -> (point: simd_float3, method: String)? { + guard let frame = arView.session.currentFrame, + let depth = frame.sceneDepth?.depthMap else { + return nil + } + + let depthWidth = CVPixelBufferGetWidth(depth) + let depthHeight = CVPixelBufferGetHeight(depth) + let viewBounds = arView.bounds + + // 1. Normalize tap location to view coordinates + let normView = CGPoint( + x: location.x / viewBounds.width, + y: location.y / viewBounds.height + ) + + // 2. Apply display transform to get camera image coordinates + let ori = arView.window?.windowScene?.interfaceOrientation ?? .portrait + let disp = frame.displayTransform(for: ori, viewportSize: viewBounds.size) + let camNorm = normView.applying(disp.inverted()) + + // 3. Map to depth pixel coordinates + let u = Int(clamp(camNorm.x, 0, 1) * CGFloat(depthWidth)) + let v = Int(clamp(camNorm.y, 0, 1) * CGFloat(depthHeight)) + + // 4. Sample depth with median filtering for noise reduction + CVPixelBufferLockBaseAddress(depth, .readOnly) + defer { CVPixelBufferUnlockBaseAddress(depth, .readOnly) } + + let base = CVPixelBufferGetBaseAddress(depth)!.assumingMemoryBound(to: Float32.self) + let bytesPerRow = CVPixelBufferGetBytesPerRow(depth) / MemoryLayout.size + let N = 3 + var samples: [Float] = [] + + for j in max(0, v - N)...min(depthHeight - 1, v + N) { + for i in max(0, u - N)...min(depthWidth - 1, u + N) { + let d = base[j * bytesPerRow + i] + if d.isFinite, d > 0 { + samples.append(d) + } + } + } + + guard !samples.isEmpty else { return nil } + samples.sort() + let depthValue = samples[samples.count / 2] // median + + // 5. Unproject to camera coordinates using intrinsics + let K = frame.camera.intrinsics + let fx = K.columns.0.x, fy = K.columns.1.y + let cx = K.columns.2.x, cy = K.columns.2.y + + let xc = (Float(u) - cx) * depthValue / fx + let yc = (Float(v) - cy) * depthValue / fy + let zc = depthValue + + // 6. Transform to world coordinates + let pc = simd_float4(xc, yc, zc, 1) + let pw = simd_mul(frame.camera.transform, pc) + + return (simd_float3(pw.x, pw.y, pw.z), "depth") + } + + // MARK: - Helper Functions + private func clamp(_ value: T, _ minVal: T, _ maxVal: T) -> T { + return min(max(value, minVal), maxVal) + } } class DepthStatus: ObservableObject { @@ -1032,74 +1101,6 @@ class ARViewModel: ObservableObject{ // ML results are now accessed directly during streaming for better real-time performance } - // MARK: - Depth-Based Point Calculation - private func worldPointFromDepth(at location: CGPoint, in arView: ARView) -> (point: simd_float3, method: String)? { - guard let frame = arView.session.currentFrame, - let depth = frame.sceneDepth?.depthMap else { - return nil - } - - let depthWidth = CVPixelBufferGetWidth(depth) - let depthHeight = CVPixelBufferGetHeight(depth) - let viewBounds = arView.bounds - - // 1. Normalize tap location to view coordinates - let normView = CGPoint( - x: location.x / viewBounds.width, - y: location.y / viewBounds.height - ) - - // 2. Apply display transform to get camera image coordinates - let ori = arView.window?.windowScene?.interfaceOrientation ?? .portrait - let disp = frame.displayTransform(for: ori, viewportSize: viewBounds.size) - let camNorm = normView.applying(disp.inverted()) - - // 3. Map to depth pixel coordinates - let u = Int(clamp(camNorm.x, 0, 1) * CGFloat(depthWidth)) - let v = Int(clamp(camNorm.y, 0, 1) * CGFloat(depthHeight)) - - // 4. Sample depth with median filtering for noise reduction - CVPixelBufferLockBaseAddress(depth, .readOnly) - defer { CVPixelBufferUnlockBaseAddress(depth, .readOnly) } - - let base = CVPixelBufferGetBaseAddress(depth)!.assumingMemoryBound(to: Float32.self) - let bytesPerRow = CVPixelBufferGetBytesPerRow(depth) / MemoryLayout.size - let N = 3 - var samples: [Float] = [] - - for j in max(0, v - N)...min(depthHeight - 1, v + N) { - for i in max(0, u - N)...min(depthWidth - 1, u + N) { - let d = base[j * bytesPerRow + i] - if d.isFinite, d > 0 { - samples.append(d) - } - } - } - - guard !samples.isEmpty else { return nil } - samples.sort() - let depthValue = samples[samples.count / 2] // median - - // 5. Unproject to camera coordinates using intrinsics - let K = frame.camera.intrinsics - let fx = K.columns.0.x, fy = K.columns.1.y - let cx = K.columns.2.x, cy = K.columns.2.y - - let xc = (Float(u) - cx) * depthValue / fx - let yc = (Float(v) - cy) * depthValue / fy - let zc = depthValue - - // 6. Transform to world coordinates - let pc = simd_float4(xc, yc, zc, 1) - let pw = simd_mul(frame.camera.transform, pc) - - return (simd_float3(pw.x, pw.y, pw.z), "depth") - } - - // MARK: - Helper Functions - private func clamp(_ value: T, min minVal: T, max maxVal: T) -> T { - return min(max(value, minVal), maxVal) - } } diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 6955a6b..6392f27 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -294,31 +294,43 @@ class ARVisualizationManager: ObservableObject { private func interpretMLDirections(_ jointActions: [Float]) -> (translation: SIMD3, rotation: simd_quatf, confidence: Float) { // Use unified policy→camera mapping for consistency with robot path let action7 = Array(jointActions.prefix(7)) - let quarterTurns: Int - // Map device interface orientation to quarter turns around camera Z - if let windowScene = UIApplication.shared.connectedScenes.first as? UIWindowScene { - switch windowScene.interfaceOrientation { - case .landscapeLeft: - quarterTurns = 1 - case .landscapeRight: - quarterTurns = -1 - case .portraitUpsideDown: - quarterTurns = 2 - default: - quarterTurns = 0 - } - } else { - quarterTurns = 0 - } - let mapped = ActionTransformUtils.policyToCameraEulerAction(action7, rotationUnit: .eulerXYZ, quarterTurns: quarterTurns) - let translation = SIMD3(mapped[0], mapped[1], mapped[2]) - let rotation = eulerToQuaternion(roll: mapped[3], pitch: mapped[4], yaw: mapped[5]) - - // Confidence heuristic: translation magnitude plus rotation magnitude - let translationMagnitude = length(translation) - let rotationMagnitude = sqrt(mapped[3] * mapped[3] + mapped[4] * mapped[4] + mapped[5] * mapped[5]) - let confidence = min(1.0, (translationMagnitude * 10 + rotationMagnitude) / 2.0) - + // let quarterTurns: Int + // // Map device interface orientation to quarter turns around camera Z + // if let windowScene = UIApplication.shared.connectedScenes.first as? UIWindowScene { + // switch windowScene.interfaceOrientation { + // case .landscapeLeft: + // quarterTurns = 1 + // case .landscapeRight: + // quarterTurns = -1 + // case .portraitUpsideDown: + // quarterTurns = 2 + // default: + // quarterTurns = 0 + // } + // } else { + // quarterTurns = 0 + // } + // let mapped = ActionTransformUtils.policyToCameraEulerAction(action7, rotationUnit: .eulerXYZ, quarterTurns: quarterTurns) + // let translation = SIMD3(mapped[0], mapped[1], mapped[2]) + // let rotation = eulerToQuaternion(roll: mapped[3], pitch: mapped[4], yaw: mapped[5]) + + // // Confidence heuristic: translation magnitude plus rotation magnitude + // let translationMagnitude = length(translation) + // let rotationMagnitude = sqrt(mapped[3] * mapped[3] + mapped[4] * mapped[4] + mapped[5] * mapped[5]) + // let confidence = min(1.0, (translationMagnitude * 10 + rotationMagnitude) / 2.0) + + + // take policy output, transform to camera frame with camera transform and then labels with 5cm offset and in arkit convention + let camera_transform = getCurrentCameraTransform() + let camera_translation = SIMD3(camera_transform.columns.3.x, camera_transform.columns.3.y, camera_transform.columns.3.z) + let camera_rotation = eulerToQuaternion(roll: camera_transform.columns.0.x, pitch: camera_transform.columns.0.y, yaw: camera_transform.columns.0.z) + let policy_translation_camera = camera_transform * SIMD4(jointActions[0], jointActions[1], jointActions[2], 1) + let policy_translation_camera_labels = SIMD3(-policy_translation_camera.x, -policy_translation_camera.z + 0.05, -policy_translation_camera.y) + let policy_translation_camera_labels_rotation = camera_rotation.act(policy_translation_camera_labels) + let translation = policy_translation_camera_labels_rotation + let rotation = camera_rotation + let confidence: Float = 1.0 + return (translation, rotation, confidence) } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 927bea9..a314ab1 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -209,7 +209,8 @@ class MLInferenceManager: ObservableObject { // camera: x right, y up, z back // labels: x left, y forward, z down // Mapping: x = -x_cam, y = -z_cam, z = -y_cam - return [-p_c4.x, -p_c4.z, -p_c4.y] + // We add 0.05 to the z coordinate since training data is shifted forward a bit. + return [-p_c4.x, -p_c4.z + 0.05, -p_c4.y] } // If model expects 2D goals, return nil since we only support 3D goals now return nil From d8faa6a0eeaffe52285dc4d8c19e1753745ffea5 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Tue, 23 Sep 2025 23:48:55 -0400 Subject: [PATCH 33/56] added image overlays, accelerate optimizations, and visualization fixes --- .../gripper_overlay.imageset/Contents.json | 21 ++ .../gripper_overlay.png | Bin 0 -> 1278926 bytes AnySense/Managers/ARViewContainer.swift | 160 ++++++++++++++-- .../Managers/ARVisualizationManager.swift | 71 +++---- AnySense/Managers/ActionTransformUtils.swift | 40 ++-- AnySense/Managers/MLInferenceManager.swift | 180 +++++++++++++++++- AnySense/gripper_overlay.png | Bin 0 -> 1278926 bytes 7 files changed, 399 insertions(+), 73 deletions(-) create mode 100644 AnySense/Assets.xcassets/gripper_overlay.imageset/Contents.json create mode 100644 AnySense/Assets.xcassets/gripper_overlay.imageset/gripper_overlay.png create mode 100644 AnySense/gripper_overlay.png diff --git a/AnySense/Assets.xcassets/gripper_overlay.imageset/Contents.json b/AnySense/Assets.xcassets/gripper_overlay.imageset/Contents.json new file mode 100644 index 0000000..48cb9a1 --- /dev/null +++ b/AnySense/Assets.xcassets/gripper_overlay.imageset/Contents.json @@ -0,0 +1,21 @@ +{ + "images" : [ + { + "filename" : "gripper_overlay.png", + "idiom" : "universal", + "scale" : "1x" + }, + { + "idiom" : "universal", + "scale" : "2x" + }, + { + "idiom" : "universal", + "scale" : "3x" + } + ], + "info" : { + "author" : "xcode", + "version" : 1 + } +} \ No newline at end of file diff --git a/AnySense/Assets.xcassets/gripper_overlay.imageset/gripper_overlay.png b/AnySense/Assets.xcassets/gripper_overlay.imageset/gripper_overlay.png new file mode 100644 index 0000000000000000000000000000000000000000..98f57f307dd93327b6a478d51a1fc91aea9634c3 GIT binary patch literal 1278926 zcmV(~K+nI4P)VCsZ+>g)e60R{Z9n9oe4&FQv8z&O4un@? z{pFNfv{8n8S|_v7oXdr>ZCC2ORenB{zJrK}&hxaslMsoVla_t5e$Tu(4*6as0{a^4 zi{r_I-ud18lskrF>E92gGGUqTDrsza^fS!M)xgvWy=|L+F8#h)84*?blx}QOL`cqa zv`Ir|vK$fn9=pvzB7%H*w4p%>2cj8L^g+IObPTzbFU$C zCDxxyQ^yJkiF~6$Kij=is`%jPxqQfJNd8J0x$*iW#o0bdYYI>dRl{hon(xkXQUnStlD`p9vyu< zY(OlV{sTWITmqJy5Rojg24<(`z7P=~!S4AyiP@mgx6&7;gGad&WT=kcHGT>7&H5@0 ztNsj}6!=WXj}dfKdCTqIp{=_%^j_ruJ8c=3F?|61irkTS1=AG|I~`2S$C9R9eeX_j zuDoY%6NyeaZ639ZoMVhM|1s^l>-3Z4bpAPx*W{ZK6Q{LJHxEN^HvqT6sdvX$^+2yr zM42XCZfMx09gap@GYI#**beJ>fgUjxG;z%h_@(n3NzjTeWV6F3PvF$6>k08bb{J$} zj)P7)NzOAD?bl^|Oj;1&=FZG@#Bs!a%f$Yt%r#f-5Yky_PHQ0nT$<_C`zp&HKYh^g 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z&BDzb>r3CynRZL>9@n#dz5{47%ojPxrP(}`c%nF4W~>(___f^8L|&czuZe@e&n@_g z-tN69R(JBWED}B-OeA4;q>=k+u0f6IAelF z#%`K+7&!^l(G^2%(#xp3)n_8t^jbW;WG8Jb{b2QGgZ_B-8@?a7Oq^ nIUqw^#E`gyz%x*yvlV1~B~3B(xE}mSc6l_^bf1?!wFvzm=&;2S literal 0 HcmV?d00001 diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 7bf714f..59974a7 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -16,6 +16,7 @@ import CoreImage import UIKit import CoreImage.CIFilterBuiltins import Combine +import Accelerate //import WebRTC struct RecordingFiles { @@ -228,6 +229,7 @@ class ARViewModel: ObservableObject{ // AR Visualization Manager for 3D pose visualization @Published var arVisualizationManager = ARVisualizationManager() @Published var goalTapModeEnabled: Bool = false + @Published var isUSBStreamingActive: Bool = false public var userFPS: Double? @@ -250,10 +252,14 @@ class ARViewModel: ObservableObject{ private var combinedRGBTransform: CGAffineTransform? private var combinedDepthTransform: CGAffineTransform? - + private var rgbOutputPixelBufferUSB: CVPixelBuffer? private var depthOutputPixelBufferUSB: CVPixelBuffer? private var depthConfidenceOutputPixelBufferUSB: CVPixelBuffer? + + // MARK: - Accelerate Optimization Properties + private var rgbTransformBuffer: vImage_Buffer? + private var lastTransformImageSize: CGSize = .zero // MARK: - Exposed helpers for MLInferenceManager func getARSession() -> ARSession { return session @@ -481,11 +487,15 @@ class ARViewModel: ObservableObject{ displayLink = CADisplayLink(target: self, selector: #selector(sendFrameUSB)) displayLink?.preferredFrameRateRange = CAFrameRateRange(minimum: Float(self.userFPS!), maximum: Float(self.userFPS!), preferred: Float(self.userFPS!)) displayLink?.add(to: .main, forMode: .common) + isUSBStreamingActive = true + mlManager?.setUSBStreamingState(isActive: true) } func stopUSBStreaming() { displayLink?.invalidate() displayLink = nil + isUSBStreamingActive = false + mlManager?.setUSBStreamingState(isActive: false) } func setupUSBStreaming() { @@ -541,10 +551,19 @@ class ARViewModel: ObservableObject{ func killUSBStreaming() { self.usbManager.disconnect() - + self.rgbOutputPixelBufferUSB = nil self.depthOutputPixelBufferUSB = nil self.depthConfidenceOutputPixelBufferUSB = nil + + // Clean up vImage buffers + if let transformBuffer = rgbTransformBuffer { + free(transformBuffer.data) + rgbTransformBuffer = nil + } + + isUSBStreamingActive = false + mlManager?.setUSBStreamingState(isActive: false) } // func startWiFiStreaming(host: String, port: UInt16) { @@ -571,16 +590,22 @@ class ARViewModel: ObservableObject{ private func processDepthStreamData(depthPixelBuffer: CVPixelBuffer, outputBuffer: CVPixelBuffer, isDepth: Bool) -> Data? { CVPixelBufferLockBaseAddress(depthPixelBuffer, .readOnly) CVPixelBufferLockBaseAddress(outputBuffer, []) - - let depthCiImage = CIImage(cvPixelBuffer: depthPixelBuffer) - let depthTransformedImage = depthCiImage.transformed(by: self.combinedDepthTransform ?? CGAffineTransform.identity) - self.ciContext.render(depthTransformedImage, to: outputBuffer) - + + // Try optimized depth processing + if canUseOptimizedDepthTransform(for: depthPixelBuffer) { + processDepthOptimized(depthPixelBuffer, outputBuffer: outputBuffer) + } else { + // Fallback to Core Image + let depthCiImage = CIImage(cvPixelBuffer: depthPixelBuffer) + let depthTransformedImage = depthCiImage.transformed(by: self.combinedDepthTransform ?? CGAffineTransform.identity) + self.ciContext.render(depthTransformedImage, to: outputBuffer) + } + let compressedData = self.usbManager.compressData(from: outputBuffer, isDepth: isDepth) - + CVPixelBufferUnlockBaseAddress(outputBuffer, []) CVPixelBufferUnlockBaseAddress(depthPixelBuffer, .readOnly) - + return compressedData } @@ -642,14 +667,21 @@ class ARViewModel: ObservableObject{ DispatchQueue.global(qos: .userInitiated).async { CVPixelBufferLockBaseAddress(rgbPixelBuffer, .readOnly) CVPixelBufferLockBaseAddress(self.rgbOutputPixelBufferUSB!, []) - - let rgbCiImage = CIImage(cvPixelBuffer: rgbPixelBuffer) - let rgbTransformedImage = rgbCiImage.transformed(by: self.combinedRGBTransform!) - guard let rgbCgImage = self.ciContext.createCGImage(rgbTransformedImage, from: rgbTransformedImage.extent) else{ - return + // Try optimized path first + let rgbImageData: Data? + if self.canUseOptimizedTransform(for: rgbPixelBuffer) { + rgbImageData = self.processRGBOptimized(rgbPixelBuffer) + } else { + // Fallback to Core Image pipeline + let rgbCiImage = CIImage(cvPixelBuffer: rgbPixelBuffer) + let rgbTransformedImage = rgbCiImage.transformed(by: self.combinedRGBTransform!) + + guard let rgbCgImage = self.ciContext.createCGImage(rgbTransformedImage, from: rgbTransformedImage.extent) else{ + return + } + rgbImageData = UIImage(cgImage: rgbCgImage).jpegData(compressionQuality: 0.5) } - let rgbImageData = UIImage(cgImage: rgbCgImage).jpegData(compressionQuality: 0.5) record3dHeader.rgbSize = UInt32(rgbImageData!.count) @@ -1009,6 +1041,104 @@ class ARViewModel: ObservableObject{ } return filteredImage.transformed(by: self.combinedDepthTransform ?? CGAffineTransform.identity) //.cropped(to: cropRect) } + + // MARK: - Accelerate Optimizations + private func canUseOptimizedTransform(for pixelBuffer: CVPixelBuffer) -> Bool { + // Only use optimized path for simple transforms (scale + translate) + // Skip if transform contains rotation or complex operations + guard let transform = combinedRGBTransform else { return false } + + // Check if transform is approximately a simple scale/translate + let hasRotation = abs(transform.b) > 0.001 || abs(transform.c) > 0.001 + return !hasRotation + } + + private func processRGBOptimized(_ pixelBuffer: CVPixelBuffer) -> Data? { + // For now, use a simple direct conversion approach + // This bypasses the expensive CIImage -> CGImage -> UIImage pipeline + + guard let cgImage = createCGImageDirect(from: pixelBuffer) else { + return nil + } + + return UIImage(cgImage: cgImage).jpegData(compressionQuality: 0.5) + } + + private func createCGImageDirect(from pixelBuffer: CVPixelBuffer) -> CGImage? { + let width = CVPixelBufferGetWidth(pixelBuffer) + let height = CVPixelBufferGetHeight(pixelBuffer) + + guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { return nil } + + let bytesPerRow = CVPixelBufferGetBytesPerRow(pixelBuffer) + let colorSpace = CGColorSpaceCreateDeviceRGB() + + let bitmapInfo = CGBitmapInfo(rawValue: CGImageAlphaInfo.noneSkipFirst.rawValue) + + guard let context = CGContext( + data: baseAddress, + width: width, + height: height, + bitsPerComponent: 8, + bytesPerRow: bytesPerRow, + space: colorSpace, + bitmapInfo: bitmapInfo.rawValue + ) else { return nil } + + return context.makeImage() + } + + private func canUseOptimizedDepthTransform(for pixelBuffer: CVPixelBuffer) -> Bool { + guard let transform = combinedDepthTransform else { return false } + // Check if transform is simple enough for vImage optimization + let hasRotation = abs(transform.b) > 0.001 || abs(transform.c) > 0.001 + return !hasRotation + } + + private func processDepthOptimized(_ inputBuffer: CVPixelBuffer, outputBuffer: CVPixelBuffer) { + // Simple memcpy for identity or simple scaling transforms + // This avoids Core Image overhead for depth data + + let inputWidth = CVPixelBufferGetWidth(inputBuffer) + let inputHeight = CVPixelBufferGetHeight(inputBuffer) + let outputWidth = CVPixelBufferGetWidth(outputBuffer) + let outputHeight = CVPixelBufferGetHeight(outputBuffer) + + guard let inputData = CVPixelBufferGetBaseAddress(inputBuffer), + let outputData = CVPixelBufferGetBaseAddress(outputBuffer) else { + return + } + + let inputBytesPerRow = CVPixelBufferGetBytesPerRow(inputBuffer) + let outputBytesPerRow = CVPixelBufferGetBytesPerRow(outputBuffer) + + if inputWidth == outputWidth && inputHeight == outputHeight { + // Direct copy for same-size buffers + let totalBytes = min(inputHeight * inputBytesPerRow, outputHeight * outputBytesPerRow) + memcpy(outputData, inputData, totalBytes) + } else { + // Use vImage for scaling if available + var sourceBuffer = vImage_Buffer( + data: inputData, + height: vImagePixelCount(inputHeight), + width: vImagePixelCount(inputWidth), + rowBytes: inputBytesPerRow + ) + + var destBuffer = vImage_Buffer( + data: outputData, + height: vImagePixelCount(outputHeight), + width: vImagePixelCount(outputWidth), + rowBytes: outputBytesPerRow + ) + + // Use vImage scaling for better performance than Core Image + let error = vImageScale_Planar16F(&sourceBuffer, &destBuffer, nil, vImage_Flags(kvImageNoFlags)) + if error != kvImageNoError { + print("vImage scaling failed: \(error)") + } + } + } private func saveBinaryDepthData(depthPixelBuffer: CVPixelBuffer) { // Save metric depth data as binary file diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 6392f27..a39782d 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -76,6 +76,10 @@ class ARVisualizationManager: ObservableObject { // Debug controls var debugLoggingEnabled: Bool = true var debugAlwaysDrawArrow: Bool = false + // Visualization adjustments + var applyEndOffset: Bool = true // apply labels-forward (+Y_label) → -Z_camera offset + var endOffsetMeters: Float = 0.05 // meters; matches training shift used in labels.json mapping + var useMagnitudeConfidence: Bool = false // if true, scale color by delta magnitude; otherwise constant // MARK: - Initialization init() { @@ -269,33 +273,47 @@ class ARVisualizationManager: ObservableObject { ) ) let deltaTranslation = rotationWorldFromCamera * cameraDeltaTranslation + if debugLoggingEnabled { + func fmt(_ f: Float) -> String { String(format: "%.3f", f) } + func fmt3(_ v: SIMD3) -> String { "(\(fmt(v.x)), \(fmt(v.y)), \(fmt(v.z)))" } + print("[Viz] Δcam \(fmt3(cameraDeltaTranslation)) → Δworld \(fmt3(deltaTranslation))") + } // ML coordinate transform applied - // Update position tracking - let previousPosition = currentWorldPosition - currentWorldPosition = currentWorldPosition + deltaTranslation - - // Only create movement arrow if there's meaningful movement and we have a previous position + // Get current camera position relative to world origin + let currentCameraPosition = SIMD3( + cameraTransform.columns.3.x, + cameraTransform.columns.3.y, + cameraTransform.columns.3.z + ) - worldOrigin + + // Show ML policy arrow from current camera position, not accumulated position + let targetPosition = currentCameraPosition + deltaTranslation + + // Only create movement arrow if there's meaningful movement let movementMagnitude = length(deltaTranslation) // Movement magnitude calculated if movementMagnitude > 0.005 || debugAlwaysDrawArrow { // draw even if tiny in debug createMovementArrow( - from: previousPosition, - to: currentWorldPosition, + from: currentCameraPosition, + to: targetPosition, confidence: confidence, timestamp: timestamp ) } + + // Update tracking position to current camera position (not accumulated) + currentWorldPosition = currentCameraPosition // Position updated with movement delta } private func interpretMLDirections(_ jointActions: [Float]) -> (translation: SIMD3, rotation: simd_quatf, confidence: Float) { - // Use unified policy→camera mapping for consistency with robot path + // Map policy action → CAMERA frame (translation and Euler rotation) let action7 = Array(jointActions.prefix(7)) - // let quarterTurns: Int - // // Map device interface orientation to quarter turns around camera Z + // Determine device interface orientation → quarter turns around camera Z + // var quarterTurns: Int = 0 // if let windowScene = UIApplication.shared.connectedScenes.first as? UIWindowScene { // switch windowScene.interfaceOrientation { // case .landscapeLeft: @@ -307,31 +325,20 @@ class ARVisualizationManager: ObservableObject { // default: // quarterTurns = 0 // } - // } else { - // quarterTurns = 0 // } - // let mapped = ActionTransformUtils.policyToCameraEulerAction(action7, rotationUnit: .eulerXYZ, quarterTurns: quarterTurns) - // let translation = SIMD3(mapped[0], mapped[1], mapped[2]) - // let rotation = eulerToQuaternion(roll: mapped[3], pitch: mapped[4], yaw: mapped[5]) - - // // Confidence heuristic: translation magnitude plus rotation magnitude - // let translationMagnitude = length(translation) - // let rotationMagnitude = sqrt(mapped[3] * mapped[3] + mapped[4] * mapped[4] + mapped[5] * mapped[5]) - // let confidence = min(1.0, (translationMagnitude * 10 + rotationMagnitude) / 2.0) - + let mapped = ActionTransformUtils.policyToCameraEulerAction(action7, rotationUnit: .eulerXYZ) + var translationCamera = SIMD3(mapped[0], mapped[1], mapped[2]) + // Optional end-offset in CAMERA frame: labels forward (+Y_label) == -Z_camera + if applyEndOffset { + translationCamera += SIMD3(0, 0, -endOffsetMeters) + } + let rotationCamera = eulerToQuaternion(roll: mapped[3], pitch: mapped[4], yaw: mapped[5]) - // take policy output, transform to camera frame with camera transform and then labels with 5cm offset and in arkit convention - let camera_transform = getCurrentCameraTransform() - let camera_translation = SIMD3(camera_transform.columns.3.x, camera_transform.columns.3.y, camera_transform.columns.3.z) - let camera_rotation = eulerToQuaternion(roll: camera_transform.columns.0.x, pitch: camera_transform.columns.0.y, yaw: camera_transform.columns.0.z) - let policy_translation_camera = camera_transform * SIMD4(jointActions[0], jointActions[1], jointActions[2], 1) - let policy_translation_camera_labels = SIMD3(-policy_translation_camera.x, -policy_translation_camera.z + 0.05, -policy_translation_camera.y) - let policy_translation_camera_labels_rotation = camera_rotation.act(policy_translation_camera_labels) - let translation = policy_translation_camera_labels_rotation - let rotation = camera_rotation - let confidence: Float = 1.0 + // Confidence: constant by default; optionally scale by translation magnitude + let confidence: Float = useMagnitudeConfidence ? min(1.0, max(0.0, length(translationCamera) * 10.0)) : 1.0 - return (translation, rotation, confidence) + // Return CAMERA-frame delta; caller will rotate to WORLD frame using current camera pose + return (translationCamera, rotationCamera, confidence) } private func createMovementArrow(from: SIMD3, to: SIMD3, confidence: Float, timestamp: TimeInterval) { diff --git a/AnySense/Managers/ActionTransformUtils.swift b/AnySense/Managers/ActionTransformUtils.swift index c15db2d..9e478a5 100644 --- a/AnySense/Managers/ActionTransformUtils.swift +++ b/AnySense/Managers/ActionTransformUtils.swift @@ -53,7 +53,7 @@ struct ActionTransformUtils { // Convention used here mirrors ARVisualizationManager's historical mapping with a corrected Z sign: // - policy: [down, right, backward] // - camera: x=right, y=up, z forward is -Z in ARKit conventions → use z = -backward - static func policyToCameraEulerAction(_ policyAction7: [Float], rotationUnit: RotationUnit = .eulerXYZ, quarterTurns: Int = 0) -> [Float] { + static func policyToCameraEulerAction(_ policyAction7: [Float], rotationUnit: RotationUnit = .eulerXYZ) -> [Float] { guard policyAction7.count >= 7 else { return policyAction7 } let ml_x = policyAction7[0] // down let ml_y = policyAction7[1] // right @@ -63,11 +63,10 @@ struct ActionTransformUtils { let r3 = policyAction7[5] let gr = policyAction7[6] - // Translation mapping - var cam_t = SIMD3(ml_y, -ml_x, -ml_z) - if quarterTurns % 4 != 0 { - cam_t = rotateXY(cam_t, quarterTurns: quarterTurns) - } + // Translation mapping (labels → CAMERA) using inverse of goal mapping: + // labels: x = -x_cam, y = -z_cam, z = -y_cam + // => camera: x = -x_l, y = -z_l, z = -y_l + let cam_t = SIMD3(-ml_x, -ml_z, -ml_y) // Rotation mapping → always return Euler xyz in CAMERA frame var cam_euler: SIMD3 @@ -78,11 +77,6 @@ struct ActionTransformUtils { let R_cam = rotationMatrixFromAxisAngle(axisAngle: SIMD3(r1, r2, r3)) cam_euler = eulerXYZ(from: matrixFromRotationAndTranslation(R_cam, t: SIMD3(0,0,0))) } - if quarterTurns % 4 != 0 { - // Adjust yaw by quarter turns around camera Z - let k = Float(quarterTurns % 4) - cam_euler.z += k * (.pi / 2) - } return [cam_t.x, cam_t.y, cam_t.z, cam_euler.x, cam_euler.y, cam_euler.z, gr] } @@ -156,18 +150,18 @@ struct ActionTransformUtils { } // Rotate a vector in camera XY plane by 90° increments (right-handed, +Z out of screen) - private static func rotateXY(_ v: SIMD3, quarterTurns: Int) -> SIMD3 { - switch ((quarterTurns % 4) + 4) % 4 { // normalize to 0..3 - case 1: // +90° (counterclockwise): (x,y) -> (-y, x) - return SIMD3(-v.y, v.x, v.z) - case 2: // 180° - return SIMD3(-v.x, -v.y, v.z) - case 3: // -90° (clockwise): (x,y) -> (y, -x) - return SIMD3(v.y, -v.x, v.z) - default: - return v - } - } + // private static func rotateXY(_ v: SIMD3) -> SIMD3 { + // switch ((quarterTurns % 4) + 4) % 4 { // normalize to 0..3 + // case 1: // +90° (counterclockwise): (x,y) -> (-y, x) + // return SIMD3(-v.y, v.x, v.z) + // case 2: // 180° + // return SIMD3(-v.x, -v.y, v.z) + // case 3: // -90° (clockwise): (x,y) -> (y, -x) + // return SIMD3(v.y, -v.x, v.z) + // default: + // return v + // } + // } // Extract Euler 'xyz' (radians) from 4x4 private static func eulerXYZ(from T: simd_float4x4) -> SIMD3 { diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index a314ab1..bdeb148 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -17,6 +17,7 @@ import CoreImage import ARKit import simd import UIKit +import Accelerate // MARK: - ML Inference Results struct InferenceResult { @@ -61,6 +62,13 @@ class MLInferenceManager: ObservableObject { private let ciContext: CIContext private var modelInputSize = CGSize(width: 224, height: 224) private var modelInputTransform: CGAffineTransform? + + // MARK: - Gripper Overlay Properties + private var gripperOverlayCIImage: CIImage? + private var gripperOverlayBuffer: vImage_Buffer? + private var isUSBStreamingActive: Bool = false + @Published var enableGripperOverlay: Bool = true // Default enabled + @Published var saveDebugFrames: Bool = false // For testing // MARK: - Inference Settings enum InferenceFrequency: CaseIterable { @@ -96,7 +104,8 @@ class MLInferenceManager: ObservableObject { self.modelManager = modelManager self.ciContext = CIContext() loadActiveModel() - + loadGripperOverlay() + // Listen for active model changes modelManager.$activeModel .receive(on: DispatchQueue.main) @@ -111,6 +120,149 @@ class MLInferenceManager: ObservableObject { model = nil latestResult = nil cancellables.removeAll() + + // Clean up vImage buffer + if let buffer = gripperOverlayBuffer { + free(buffer.data) + } + } + + // MARK: - Gripper Overlay Methods + private func loadGripperOverlay() { + guard let uiImage = UIImage(named: "gripper_overlay") else { + print("Warning: Could not load gripper_overlay image from assets") + return + } + gripperOverlayCIImage = CIImage(image: uiImage) + + // Also prepare vImage buffer for high-performance compositing + setupGripperOverlayBuffer(from: uiImage) + print("Gripper overlay loaded: \(gripperOverlayCIImage?.extent ?? .zero)") + } + + private func setupGripperOverlayBuffer(from uiImage: UIImage) { + guard let cgImage = uiImage.cgImage else { return } + + let width = cgImage.width + let height = cgImage.height + let bytesPerPixel = 4 + let bytesPerRow = width * bytesPerPixel + let bufferLength = height * bytesPerRow + + guard let data = malloc(bufferLength) else { + print("Warning: Could not allocate memory for gripper overlay buffer") + return + } + + var buffer = vImage_Buffer( + data: data, + height: vImagePixelCount(height), + width: vImagePixelCount(width), + rowBytes: bytesPerRow + ) + + // Convert CGImage to vImage buffer + var format = vImage_CGImageFormat( + bitsPerComponent: 8, + bitsPerPixel: 32, + colorSpace: nil, + bitmapInfo: CGBitmapInfo(rawValue: CGImageAlphaInfo.premultipliedLast.rawValue), + version: 0, + decode: nil, + renderingIntent: .defaultIntent + ) + + let error = vImageBuffer_InitWithCGImage(&buffer, &format, nil, cgImage, vImage_Flags(kvImageNoFlags)) + if error == kvImageNoError { + gripperOverlayBuffer = buffer + } else { + free(data) + print("Warning: Failed to create vImage buffer for gripper overlay: \(error)") + } + } + + func setUSBStreamingState(isActive: Bool) { + isUSBStreamingActive = isActive + print("USB streaming state: \(isActive ? "ON" : "OFF") - Gripper overlay: \(shouldShowGripperOverlay() ? "ENABLED" : "DISABLED")") + } + + private func shouldShowGripperOverlay() -> Bool { + return enableGripperOverlay && !isUSBStreamingActive + } + + private func applyGripperOverlay(to image: CIImage) -> CIImage { + guard shouldShowGripperOverlay() else { + return image + } + + // Fallback to Core Image if vImage buffer not available + guard let _ = gripperOverlayBuffer else { + return applyGripperOverlayCoreImage(to: image) + } + + // For now, use Core Image fallback while we implement vImage compositing + // The main performance improvement will come from avoiding the overlay entirely when not needed + return applyGripperOverlayCoreImage(to: image) + } + + private func applyGripperOverlayCoreImage(to image: CIImage) -> CIImage { + guard let gripperOverlay = gripperOverlayCIImage else { + return image + } + + // Scale gripper overlay to match model input size + let imageSize = image.extent.size + let overlaySize = gripperOverlay.extent.size + + let scaleX = imageSize.width / overlaySize.width + let scaleY = imageSize.height / overlaySize.height + let scale = min(scaleX, scaleY) // Maintain aspect ratio + + let scaledOverlay = gripperOverlay.transformed(by: CGAffineTransform(scaleX: scale, y: scale)) + + // Position gripper at bottom with no offset (0,0 positioning) + let positionedOverlay = scaledOverlay + + // Composite using source-over to preserve alpha transparency + guard let compositeFilter = CIFilter(name: "CISourceOverCompositing") else { + print("Warning: Could not create composite filter") + return image + } + + compositeFilter.setValue(positionedOverlay, forKey: kCIInputImageKey) + compositeFilter.setValue(image, forKey: kCIInputBackgroundImageKey) + + return compositeFilter.outputImage ?? image + } + + // MARK: - Debug Frame Saving + private func saveDebugFrame(_ image: CIImage, prefix: String) { + guard saveDebugFrames else { return } + + let timestamp = Int(Date().timeIntervalSince1970 * 1000) + let filename = "\(prefix)_\(timestamp).png" + + // Get Documents directory + guard let documentsDirectory = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask).first else { + print("Warning: Could not access Documents directory") + return + } + + let fileURL = documentsDirectory.appendingPathComponent(filename) + + // Convert CIImage to Data + guard let colorSpace = CGColorSpace(name: CGColorSpace.sRGB) else { return } + guard let data = ciContext.pngRepresentation(of: image, format: .RGBA8, colorSpace: colorSpace) else { + print("Warning: Could not create PNG data for debug frame") + return + } + + do { + try data.write(to: fileURL) + print("Debug frame saved: \(fileURL.lastPathComponent)") + } catch { + print("Warning: Could not save debug frame: \(error)") + } } // MARK: - Model Loading @@ -413,8 +565,19 @@ class MLInferenceManager: ObservableObject { // Server path rotates images by 180° overall; replicate using EXIF .down scaledImage = scaledImage.oriented(.down) } + + // Save original scaled image for debugging + saveDebugFrame(scaledImage, prefix: "vqbet_original") + + // Apply gripper overlay if enabled and USB streaming is off + if shouldShowGripperOverlay() { + scaledImage = applyGripperOverlay(to: scaledImage) + // Save image with overlay for debugging + saveDebugFrame(scaledImage, prefix: "vqbet_with_overlay") + } + let cropRect = CGRect(origin: .zero, size: inputSize) - + ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) print("Image processed for VQ-BeT: \(inputSize)") @@ -509,8 +672,19 @@ class MLInferenceManager: ObservableObject { if applyServerImageOrientation { scaledImage = scaledImage.oriented(.down) } + + // Save original scaled image for debugging + saveDebugFrame(scaledImage, prefix: "standard_original") + + // Apply gripper overlay if enabled and USB streaming is off + if shouldShowGripperOverlay() { + scaledImage = applyGripperOverlay(to: scaledImage) + // Save image with overlay for debugging + saveDebugFrame(scaledImage, prefix: "standard_with_overlay") + } + let cropRect = CGRect(origin: .zero, size: modelInputSize) - + // Render using the same CIContext approach as ARViewContainer ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) print("Image processed for inference: \(modelInputSize)") diff --git a/AnySense/gripper_overlay.png b/AnySense/gripper_overlay.png new file mode 100644 index 0000000000000000000000000000000000000000..98f57f307dd93327b6a478d51a1fc91aea9634c3 GIT binary patch literal 1278926 zcmV(~K+nI4P)VCsZ+>g)e60R{Z9n9oe4&FQv8z&O4un@? z{pFNfv{8n8S|_v7oXdr>ZCC2ORenB{zJrK}&hxaslMsoVla_t5e$Tu(4*6as0{a^4 zi{r_I-ud18lskrF>E92gGGUqTDrsza^fS!M)xgvWy=|L+F8#h)84*?blx}QOL`cqa zv`Ir|vK$fn9=pvzB7%H*w4p%>2cj8L^g+IObPTzbFU$C zCDxxyQ^yJkiF~6$Kij=is`%jPxqQfJNd8J0x$*iW#o0bdYYI>dRl{hon(xkXQUnStlD`p9vyu< zY(OlV{sTWITmqJy5Rojg24<(`z7P=~!S4AyiP@mgx6&7;gGad&WT=kcHGT>7&H5@0 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private var isUSBStreamingActive: Bool = false + private var currentGripperValue: Float = 1.0 // Track latest gripper value @Published var enableGripperOverlay: Bool = true // Default enabled @Published var saveDebugFrames: Bool = false // For testing @@ -129,15 +131,26 @@ class MLInferenceManager: ObservableObject { // MARK: - Gripper Overlay Methods private func loadGripperOverlay() { - guard let uiImage = UIImage(named: "gripper_overlay") else { - print("Warning: Could not load gripper_overlay image from assets") - return + // Load open gripper (default/original) + if let openImage = UIImage(named: "gripper_overlay") { + gripperOpenCIImage = CIImage(image: openImage) + print("Open gripper overlay loaded: \(gripperOpenCIImage?.extent ?? .zero)") + } else { + print("Warning: Could not load gripper_overlay (open) image from assets") + } + + // Load closed gripper + if let closedImage = UIImage(named: "gripper_closed") { + gripperClosedCIImage = CIImage(image: closedImage) + print("Closed gripper overlay loaded: \(gripperClosedCIImage?.extent ?? .zero)") + } else { + print("Warning: Could not load gripper_closed image from assets") } - gripperOverlayCIImage = CIImage(image: uiImage) - // Also prepare vImage buffer for high-performance compositing - setupGripperOverlayBuffer(from: uiImage) - print("Gripper overlay loaded: \(gripperOverlayCIImage?.extent ?? .zero)") + // Setup vImage buffer with open gripper as default + if let openImage = UIImage(named: "gripper_overlay") { + setupGripperOverlayBuffer(from: openImage) + } } private func setupGripperOverlayBuffer(from uiImage: UIImage) { @@ -190,6 +203,20 @@ class MLInferenceManager: ObservableObject { return enableGripperOverlay && !isUSBStreamingActive } + private func getCurrentGripperOverlay() -> CIImage? { + // Use closed gripper when gripper value < 0.6, otherwise open gripper + let isGripperClosed = currentGripperValue < 0.6 + if saveDebugFrames { + print("Gripper state: \(String(format: "%.3f", currentGripperValue)) → \(isGripperClosed ? "CLOSED" : "OPEN")") + } + + if isGripperClosed { + return gripperClosedCIImage + } else { + return gripperOpenCIImage + } + } + private func applyGripperOverlay(to image: CIImage) -> CIImage { guard shouldShowGripperOverlay() else { return image @@ -206,7 +233,7 @@ class MLInferenceManager: ObservableObject { } private func applyGripperOverlayCoreImage(to image: CIImage) -> CIImage { - guard let gripperOverlay = gripperOverlayCIImage else { + guard let gripperOverlay = getCurrentGripperOverlay() else { return image } @@ -746,7 +773,12 @@ class MLInferenceManager: ObservableObject { // Extract values directly (matching old code) let outputCount = min(resultArray.count, 10) let jointPositions = (0..= 7 { + currentGripperValue = jointPositions[6] + } + let result = InferenceResult( jointPositions: jointPositions, inferenceTime: inferenceTime @@ -791,7 +823,12 @@ class MLInferenceManager: ObservableObject { // Extract values dynamically based on what the model outputs let outputCount = min(resultArray.count, 10) let jointPositions = (0..= 7 { + currentGripperValue = jointPositions[6] + } + let result = InferenceResult( jointPositions: jointPositions, inferenceTime: inferenceTime diff --git a/AnySense/Views/MLInferenceResultsView.swift b/AnySense/Views/MLInferenceResultsView.swift index c3b14c8..8b9445e 100644 --- a/AnySense/Views/MLInferenceResultsView.swift +++ b/AnySense/Views/MLInferenceResultsView.swift @@ -9,18 +9,16 @@ import SwiftUI struct MLInferenceResultsView: View { @ObservedObject var mlManager: MLInferenceManager - + var body: some View { - VStack(alignment: .leading, spacing: 8) { - HStack { - Text("Pick Up Policy") - .foregroundColor(.white) - .font(.headline) - .fontWeight(.semibold) - } - + VStack(alignment: .leading, spacing: 6) { + Text("Gripper State") + .foregroundColor(.white) + .font(.subheadline) + .fontWeight(.semibold) + if let result = mlManager.latestResult { - ResultsBlock(result: result) + GripperBlock(result: result) } else { Text("Analyzing...") .foregroundColor(.white.opacity(0.7)) @@ -28,66 +26,59 @@ struct MLInferenceResultsView: View { .italic() } } - .padding(12) + .padding(8) .background( - RoundedRectangle(cornerRadius: 12) + RoundedRectangle(cornerRadius: 8) .fill(Color.black.opacity(0.75)) .overlay( - RoundedRectangle(cornerRadius: 12) + RoundedRectangle(cornerRadius: 8) .stroke(Color.white.opacity(0.2), lineWidth: 1) ) ) - .frame(maxWidth: 240) + .frame(maxWidth: 160) } } -// MARK: - Subview -private struct ResultsBlock: View { +// MARK: - Gripper Subview +private struct GripperBlock: View { let result: InferenceResult - private let labels = ["x", "y", "z", "roll", "pitch", "yaw", "gripper"] - + + private var gripperValue: Float { + return result.jointPositions.count >= 7 ? result.jointPositions[6] : 0.0 + } + + private var gripperState: String { + return gripperValue < 0.6 ? "CLOSED" : "OPEN" + } + + private var stateColor: Color { + return gripperValue < 0.6 ? .red : .green + } + var body: some View { VStack(alignment: .leading, spacing: 4) { - Text("Joint Positions:") - .foregroundColor(.white.opacity(0.8)) - .font(.caption) - .fontWeight(.semibold) - - ForEach(result.jointPositions.indices, id: \.self) { idx in - jointActionRow(for: idx) - } - HStack { - Text("Inference:") + Text("Value:") .foregroundColor(.white.opacity(0.7)) - .font(.caption2) - Text("\(Int(result.inferenceTime * 1000))ms") - .foregroundColor(.yellow) - .font(.caption2) + .font(.caption) + Text(String(format: "%.3f", gripperValue)) + .foregroundColor(.orange) + .font(.caption) .fontWeight(.medium) + .fontDesign(.monospaced) + Spacer() + } + + HStack { + Text("State:") + .foregroundColor(.white.opacity(0.7)) + .font(.caption) + Text(gripperState) + .foregroundColor(stateColor) + .font(.caption) + .fontWeight(.bold) Spacer() } - .padding(.top, 2) - } - } - - private func jointActionRow(for idx: Int) -> some View { - let labelText = idx < labels.count ? labels[idx] + ":" : "v\(idx):" - let valueColor = idx == 6 ? 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zNd%<0w*I}R?-qDBBfl<_8<~Dm?v9xgS9M-~HF-opg0$F2LYB)F5tM1#G3-v;@!^v#L? zEB-Dh(IP$_1sI=ui6(R;g+IiY^r@G82;-3s(Rxn6%E#wX6>LAxcYXH9`DOapm3(X% z5c|D&qN3uFKf>>Z&e_G-2WICXV?MvugVUAb(YprmB+o1x zUt+WUPA)R!xX=8>c$hx$)_jwybK~{;e$S!6;(;SrX8}ggM`2dnaqutho(|uknCLvH z;{`F_-S@ennr*N>(|Krk-8V4#EY8PSa3>s}arU%(-_FO}_xE_czL#!ri@5xeDmG7h zvLjK_!bUAn^znVymnrD_a^WZ6`~+XV`38-`U;I!0GyL`c@qfbq3p;@2j;>=%`Tzg` M07*qoM6N<$f=1%j#sB~S literal 0 HcmV?d00001 From 417fa92aa3a73cec4a4dff0d9e2717373617660b Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Wed, 15 Oct 2025 16:44:49 -0400 Subject: [PATCH 35/56] gripper overlay and visualization with new models --- AnySense.xcodeproj/project.pbxproj | 4 +- AnySense/MLModel+Extensions.swift | 19 + AnySense/Managers/ARViewContainer.swift | 7 + .../Managers/ARVisualizationManager.swift | 302 +++++++++++-- AnySense/Managers/MLInferenceManager.swift | 409 +++++++++++------- AnySense/Views/readView.swift | 9 +- 6 files changed, 552 insertions(+), 198 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index b9ee745..50ff99d 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -541,7 +541,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = "Krish-2.AnySenseTest"; + PRODUCT_BUNDLE_IDENTIFIER = Krish.AnySenseTest; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; @@ -586,7 +586,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = "Krish-2.AnySenseTest"; + PRODUCT_BUNDLE_IDENTIFIER = Krish.AnySenseTest; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; diff --git a/AnySense/MLModel+Extensions.swift b/AnySense/MLModel+Extensions.swift index 40e82ed..6cdcd6a 100644 --- a/AnySense/MLModel+Extensions.swift +++ b/AnySense/MLModel+Extensions.swift @@ -155,6 +155,25 @@ struct ModelMetadata { return requiresGoalPoint ? .pointConditioned : .standard } + var temporalFrames: Int { + // Detect temporal dimension in image input shape + // [1,3,3,224,224] → 3 frames, [1,3,224,224] → 1 frame + guard let (_, desc) = firstImageLikeInput() else { return 1 } + + if desc.type == .multiArray, let shape = desc.multiArrayConstraint?.shape { + let dims = shape.map { $0.intValue } + // Check if this is a temporal model: [B, T, C, H, W] where T > 1 + if dims.count == 5 && dims[1] > 1 && dims[2] == 3 { + return dims[1] // Return temporal dimension + } + } + return 1 // Default to single frame + } + + var isTemporalModel: Bool { + return temporalFrames > 1 + } + var requiresGoalPoint: Bool { // Heuristic: presence of a second non-image input named "goal_point" or a small (1x3) array input if allInputsByName.keys.contains("goal_point") { return true } diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 59974a7..e731b62 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -1228,6 +1228,13 @@ class ARViewModel: ObservableObject{ // Provide AR session access to ML manager for goal and odometry self.mlManager?.setARViewContainer(self) + // Forward mlManager's property changes to arViewModel so SwiftUI updates + self.mlManager?.objectWillChange + .sink { [weak self] _ in + self?.objectWillChange.send() + } + .store(in: &cancellables) + // ML results are now accessed directly during streaming for better real-time performance } diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index a39782d..0898b1a 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -10,6 +10,7 @@ struct DirectionalArrow { let anchor: AnchorEntity let timestamp: TimeInterval let magnitude: Float + let movementVector: SIMD3 // Store the actual movement vector for color updates } // MARK: - Visualization Frequency (Matching MLInferenceManager) @@ -41,7 +42,7 @@ class ARVisualizationManager: ObservableObject { // MARK: - Published Properties @Published var isVisualizationEnabled: Bool = false @Published var showMovementArrows: Bool = true - @Published var maxArrows: Int = 10 + @Published var maxArrows: Int = 1 // Only show one arrow at a time @Published var visualizationFrequency: VisualizationFrequency = .medium // MARK: - Private Properties @@ -62,11 +63,19 @@ class ARVisualizationManager: ObservableObject { private var previousWorldPosition: SIMD3? private var hasEstablishedOrigin: Bool = false + // Movement detection to prevent overlapping arrows + private var lastArrowPosition: SIMD3? + private var movementThreshold: Float = 0.01 // 1cm minimum movement between arrows + + // Trajectory deviation tracking + private var expectedTrajectory: [SIMD3] = [] // Expected movement trajectory + private var trajectoryDeviationThreshold: Float = 0.02 // 2cm deviation threshold for green/red + // Arrow visual configuration - private let arrowBaseLength: Float = 0.15 // Base length in meters - private let arrowThickness: Float = 0.008 // Arrow shaft thickness - private let arrowHeadRatio: Float = 0.25 // Head vs shaft ratio - private let arrowHeadWidth: Float = 0.025 // Arrow head width + private let arrowBaseLength: Float = 0.25 // Base length in meters (increased for visibility) + private let arrowThickness: Float = 0.012 // Arrow shaft thickness (increased for visibility) + private let arrowHeadRatio: Float = 0.3 // Head vs shaft ratio (increased for visibility) + private let arrowHeadWidth: Float = 0.035 // Arrow head width (increased for visibility) private let axisLength: Float = 0.08 // Coordinate axes length private let axisThickness: Float = 0.005 // Coordinate axes thickness @@ -76,20 +85,36 @@ class ARVisualizationManager: ObservableObject { // Debug controls var debugLoggingEnabled: Bool = true var debugAlwaysDrawArrow: Bool = false + var debugForceColorVariation: Bool = false // When true, forces different colors for testing // Visualization adjustments var applyEndOffset: Bool = true // apply labels-forward (+Y_label) → -Z_camera offset var endOffsetMeters: Float = 0.05 // meters; matches training shift used in labels.json mapping - var useMagnitudeConfidence: Bool = false // if true, scale color by delta magnitude; otherwise constant + var useMagnitudeConfidence: Bool = true // if true, scale color by delta magnitude; otherwise constant + + // Enhanced visibility controls + var enhancedVisibilityMode: Bool = false // When true, makes arrows more prominent for tracking + var visibilityOffsetDistance: Float = -0.1 // Distance to offset arrows from camera for visibility + + // Gripper state control + var isGripperClosed: Bool = false // When true, stops visualization + + // Virtual gripper setting + var useVirtualGripper: Bool = false // When true, uses gripper_overlay.png; when false, passes image to policy // MARK: - Initialization init() { - print("ARVisualizationManager initialized with delta-based movement arrows") + log("Initialized with delta-based movement arrows") + } + + // MARK: - Logging Helper + private func log(_ message: String) { + print("[ARViz] \(message)") } // MARK: - Setup Methods func setupVisualization(with arView: ARView) { self.arView = arView - print("AR Visualization setup completed - using camera-relative directional arrows") + log("Setup completed - using camera-relative directional arrows") } // MARK: - Recording Control Methods @@ -112,6 +137,7 @@ class ARVisualizationManager: ObservableObject { disableVisualization() clearAllVisualization() resetMovementTracking() + print("Stopped movement visualization and reset tracking") } @@ -153,6 +179,8 @@ class ARVisualizationManager: ObservableObject { worldOrigin = SIMD3(0, 0, 0) currentWorldPosition = SIMD3(0, 0, 0) previousWorldPosition = nil + lastArrowPosition = nil // Reset arrow position tracking + expectedTrajectory = [] // Reset expected trajectory // Remove goal point visualization goalPointEntity?.removeFromParent() @@ -221,6 +249,108 @@ class ARVisualizationManager: ObservableObject { print("AR Visualization frequency set to: \(frequency.displayName)") } + // MARK: - Enhanced Visibility Methods + func enableEnhancedVisibility() { + enhancedVisibilityMode = true + visibilityOffsetDistance = 0.15 // Increase offset for better visibility + log("Enhanced visibility enabled - arrows will be more prominent") + } + + func disableEnhancedVisibility() { + enhancedVisibilityMode = false + visibilityOffsetDistance = 0.1 // Reset to default offset + log("Enhanced visibility disabled") + } + + func setVisibilityOffset(_ distance: Float) { + visibilityOffsetDistance = max(0.05, min(0.3, distance)) // Clamp between 5cm and 30cm + log("Visibility offset: \(visibilityOffsetDistance)m") + } + + func setMovementThreshold(_ threshold: Float) { + movementThreshold = max(0.005, min(0.05, threshold)) // Clamp between 5mm and 5cm + log("Movement threshold: \(movementThreshold)m") + } + + func toggleConfidenceMode() { + useMagnitudeConfidence.toggle() + print("Confidence mode: \(useMagnitudeConfidence ? "Magnitude-based" : "Direction-based")") + } + + // MARK: - Gripper State Control + func setGripperState(isClosed: Bool) { + isGripperClosed = isClosed + if isClosed { + print("Gripper closed - visualization will be disabled") + } else { + print("Gripper opened - visualization enabled") + } + } + + // MARK: - Virtual Gripper Control + func toggleVirtualGripper() { + useVirtualGripper.toggle() + print("Virtual gripper: \(useVirtualGripper ? "ON" : "OFF")") + } + + func setVirtualGripper(enabled: Bool) { + useVirtualGripper = enabled + print("Virtual gripper: \(enabled ? "ON" : "OFF")") + } + + // MARK: - USB Streaming Integration + private var isUSBStreamingActive: Bool = false + + func setUSBStreamingState(isActive: Bool) { + // This integrates with the existing USB streaming system + // When USB streaming is active, virtual gripper is automatically disabled + isUSBStreamingActive = isActive + if isActive { + print("USB streaming ON - Virtual gripper automatically disabled") + } else { + print("USB streaming OFF - Virtual gripper setting: \(useVirtualGripper ? "ON" : "OFF")") + } + } + + func shouldUseVirtualGripper() -> Bool { + // Virtual gripper is only used when: + // 1. useVirtualGripper is enabled AND + // 2. USB streaming is not active + return useVirtualGripper && !isUSBStreamingActive + } + + func enableDebugColorVariation() { + debugForceColorVariation = true + print("Debug color variation enabled - arrows will cycle through colors") + } + + func disableDebugColorVariation() { + debugForceColorVariation = false + print("Debug color variation disabled") + } + + // MARK: - Trajectory Deviation Control + func setExpectedTrajectory(_ trajectory: [SIMD3]) { + expectedTrajectory = trajectory + print("Expected trajectory set with \(trajectory.count) points") + } + + func setDeviationThreshold(_ threshold: Float) { + trajectoryDeviationThreshold = max(0.005, min(0.1, threshold)) // Clamp between 5mm and 10cm + print("Deviation threshold set to: \(trajectoryDeviationThreshold)m") + } + + func updateArrowColors() { + // Update colors of all existing arrows based on current trajectory deviation + for arrow in movementArrows { + // Calculate new confidence based on current trajectory + let arrowMovement = extractMovementFromArrow(arrow) + let newConfidence = calculateTrajectoryDeviationConfidence(actualMovement: arrowMovement) + updateArrowColor(arrow: arrow, confidence: newConfidence) + } + print("Updated colors for \(movementArrows.count) existing arrows") + } + // MARK: - Device Pose Integration func updateActualDevicePose(from arFrame: ARFrame) { let t = arFrame.camera.transform @@ -257,13 +387,19 @@ class ARVisualizationManager: ObservableObject { print("World origin not established - cannot track movement") return } + guard !isGripperClosed else { + if debugLoggingEnabled { + print("[Viz] Visualization stopped - gripper is closed") + } + return + } guard jointActions.count >= 6 else { print("Invalid joint actions array - need at least 6 values, got \(jointActions.count)") return } // Interpret joint actions as movement deltas in CAMERA coordinates, then rotate into world frame - let (cameraDeltaTranslation, _, confidence) = interpretMLDirections(jointActions) + let (cameraDeltaTranslation, _, confidence) = interpretMLDirections(jointActions, timestamp: timestamp) let cameraTransform = getCurrentCameraTransform() let rotationWorldFromCamera = simd_float3x3( columns: ( @@ -276,7 +412,7 @@ class ARVisualizationManager: ObservableObject { if debugLoggingEnabled { func fmt(_ f: Float) -> String { String(format: "%.3f", f) } func fmt3(_ v: SIMD3) -> String { "(\(fmt(v.x)), \(fmt(v.y)), \(fmt(v.z)))" } - print("[Viz] Δcam \(fmt3(cameraDeltaTranslation)) → Δworld \(fmt3(deltaTranslation))") + print("[Viz] Δcam \(fmt3(cameraDeltaTranslation)) → Δworld \(fmt3(deltaTranslation)) | confidence: \(fmt(confidence))") } // ML coordinate transform applied @@ -289,18 +425,33 @@ class ARVisualizationManager: ObservableObject { ) - worldOrigin // Show ML policy arrow from current camera position, not accumulated position - let targetPosition = currentCameraPosition + deltaTranslation + // Position arrows further out for better visibility (configurable offset distance) + let cameraForward = SIMD3(cameraTransform.columns.2.x, cameraTransform.columns.2.y, cameraTransform.columns.2.z) + let offsetPosition = currentCameraPosition + cameraForward * visibilityOffsetDistance + let targetPosition = offsetPosition + deltaTranslation - // Only create movement arrow if there's meaningful movement + // Only create movement arrow if there's meaningful movement AND sufficient distance from last arrow let movementMagnitude = length(deltaTranslation) - // Movement magnitude calculated - if movementMagnitude > 0.005 || debugAlwaysDrawArrow { // draw even if tiny in debug + let shouldCreateArrow: Bool + + if let lastPos = lastArrowPosition { + let distanceFromLastArrow = length(offsetPosition - lastPos) + shouldCreateArrow = (movementMagnitude > 0.002 || debugAlwaysDrawArrow) && distanceFromLastArrow > movementThreshold + } else { + shouldCreateArrow = movementMagnitude > 0.002 || debugAlwaysDrawArrow + } + + if shouldCreateArrow { createMovementArrow( - from: currentCameraPosition, + from: offsetPosition, to: targetPosition, confidence: confidence, timestamp: timestamp ) + lastArrowPosition = offsetPosition // Update last arrow position + } else { + // Update colors of existing arrows based on current trajectory deviation + updateArrowColors() } // Update tracking position to current camera position (not accumulated) @@ -309,7 +460,7 @@ class ARVisualizationManager: ObservableObject { // Position updated with movement delta } - private func interpretMLDirections(_ jointActions: [Float]) -> (translation: SIMD3, rotation: simd_quatf, confidence: Float) { + private func interpretMLDirections(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) -> (translation: SIMD3, rotation: simd_quatf, confidence: Float) { // Map policy action → CAMERA frame (translation and Euler rotation) let action7 = Array(jointActions.prefix(7)) // Determine device interface orientation → quarter turns around camera Z @@ -334,13 +485,90 @@ class ARVisualizationManager: ObservableObject { } let rotationCamera = eulerToQuaternion(roll: mapped[3], pitch: mapped[4], yaw: mapped[5]) - // Confidence: constant by default; optionally scale by translation magnitude - let confidence: Float = useMagnitudeConfidence ? min(1.0, max(0.0, length(translationCamera) * 10.0)) : 1.0 + // Confidence: based on trajectory deviation (green = close to expected, red = far from expected) + let movementMagnitude = length(translationCamera) + let confidence: Float + + if debugForceColorVariation { + // Force color variation for testing - cycle through colors + let timeBasedConfidence = Float((timestamp.truncatingRemainder(dividingBy: 3.0)) / 3.0) + confidence = timeBasedConfidence + } else { + // Calculate trajectory deviation-based confidence + confidence = calculateTrajectoryDeviationConfidence(actualMovement: translationCamera) + } // Return CAMERA-frame delta; caller will rotate to WORLD frame using current camera pose return (translationCamera, rotationCamera, confidence) } + // MARK: - Trajectory Deviation Calculation + private func calculateTrajectoryDeviationConfidence(actualMovement: SIMD3) -> Float { + // If no expected trajectory is set, use movement magnitude as fallback + guard !expectedTrajectory.isEmpty else { + let magnitude = length(actualMovement) + return min(1.0, max(0.0, magnitude * 20.0)) // Scale magnitude to 0-1 + } + + // Find the closest expected movement in the trajectory + let actualMagnitude = length(actualMovement) + var minDeviation: Float = Float.greatestFiniteMagnitude + + for expectedMovement in expectedTrajectory { + let expectedMagnitude = length(expectedMovement) + let magnitudeDeviation = abs(actualMagnitude - expectedMagnitude) + + // Calculate directional deviation (angle between vectors) + let angleDeviation: Float + if actualMagnitude > 0.001 && expectedMagnitude > 0.001 { + let dotProduct = dot(normalize(actualMovement), normalize(expectedMovement)) + let clampedDot = max(-1.0, min(1.0, dotProduct)) // Clamp for acos + angleDeviation = acos(clampedDot) * 180.0 / Float.pi // Convert to degrees + } else { + angleDeviation = 0.0 + } + + // Combined deviation (magnitude + direction) + let combinedDeviation = magnitudeDeviation + (angleDeviation / 180.0) * 0.1 // Scale angle deviation + minDeviation = min(minDeviation, combinedDeviation) + } + + // Convert deviation to confidence (low deviation = high confidence = green) + // Deviation below threshold = green (confidence > 0.5) + // Deviation above threshold = red (confidence < 0.5) + let normalizedDeviation = minDeviation / trajectoryDeviationThreshold + let confidence = max(0.0, min(1.0, 1.0 - normalizedDeviation)) + + return confidence + } + + // MARK: - Arrow Color Update Helpers + private func extractMovementFromArrow(_ arrow: DirectionalArrow) -> SIMD3 { + // Use the stored movement vector for accurate color updates + return arrow.movementVector + } + + private func updateArrowColor(arrow: DirectionalArrow, confidence: Float) { + DispatchQueue.main.async { + // Get the arrow color based on confidence + let newColor = self.confidenceToColor(confidence, enhanced: self.enhancedVisibilityMode) + + // Update the arrow entity's material color + if let arrowEntity = arrow.entity as? ModelEntity { + let newMaterial = SimpleMaterial(color: newColor, isMetallic: false) + arrowEntity.model?.materials = [newMaterial] + } else { + // If it's a container entity, update child entities + for child in arrow.entity.children { + if let childEntity = child as? ModelEntity { + let newMaterial = SimpleMaterial(color: newColor, isMetallic: false) + childEntity.model?.materials = [newMaterial] + } + } + } + } + } + private func createMovementArrow(from: SIMD3, to: SIMD3, confidence: Float, timestamp: TimeInterval) { guard let worldOriginAnchor = worldOriginAnchor else { return } @@ -351,8 +579,8 @@ class ARVisualizationManager: ObservableObject { let movement = to - from let movementMagnitude = length(movement) - // Skip tiny movements - guard movementMagnitude > 0.001 else { return } + // Skip tiny movements (lowered threshold for better visibility) + guard movementMagnitude > 0.0005 else { return } // Create arrow entity showing movement from previous to current position let arrowEntity = self.createMovementArrowEntity( @@ -371,20 +599,18 @@ class ARVisualizationManager: ObservableObject { entity: arrowEntity, anchor: worldOriginAnchor, timestamp: timestamp, - magnitude: movementMagnitude + magnitude: movementMagnitude, + movementVector: movement ) - self.movementArrows.append(movementArrow) - - // Clean up old arrows - self.cleanupOldArrows(currentTime: timestamp) - - // Limit number of arrows - while self.movementArrows.count > self.maxArrows { - let oldArrow = self.movementArrows.removeFirst() - oldArrow.entity.removeFromParent() + // Remove existing arrow immediately (we only want one arrow at a time) + if let existingArrow = self.movementArrows.first { + existingArrow.entity.removeFromParent() } + // Replace with new arrow + self.movementArrows = [movementArrow] + // Movement arrow created } } @@ -394,7 +620,8 @@ class ARVisualizationManager: ObservableObject { // Calculate arrow dimensions based on movement magnitude let movementMagnitude = length(movement) - let scaledLength = max(movementMagnitude, 0.02) // Minimum 2cm for visibility + let minLength: Float = enhancedVisibilityMode ? 0.08 : 0.05 // Larger minimum in enhanced mode + let scaledLength = max(movementMagnitude, minLength) let shaftLength = scaledLength * (1.0 - arrowHeadRatio) let headLength = scaledLength * arrowHeadRatio @@ -406,7 +633,8 @@ class ARVisualizationManager: ObservableObject { ) // Color based on confidence: red (low) -> yellow (medium) -> green (high) - let shaftColor = confidenceToColor(confidence) + // Enhanced visibility mode makes colors more vibrant + let shaftColor = confidenceToColor(confidence, enhanced: enhancedVisibilityMode) let shaftEntity = ModelEntity( mesh: shaftMesh, materials: [SimpleMaterial(color: shaftColor, isMetallic: false)] @@ -443,18 +671,16 @@ class ARVisualizationManager: ObservableObject { return arrowContainer } - private func confidenceToColor(_ confidence: Float) -> UIColor { - // Red (low confidence) -> Yellow (medium) -> Green (high confidence) + private func confidenceToColor(_ confidence: Float, enhanced: Bool = false) -> UIColor { let clampedConfidence = max(0.0, min(1.0, confidence)) + let alpha: CGFloat = enhanced ? 1.0 : 0.9 if clampedConfidence < 0.5 { - // Red to Yellow let factor = clampedConfidence * 2.0 - return UIColor(red: 1.0, green: CGFloat(factor), blue: 0.0, alpha: 0.8) + return UIColor(red: 1.0, green: CGFloat(factor), blue: 0.0, alpha: alpha) } else { - // Yellow to Green let factor = (clampedConfidence - 0.5) * 2.0 - return UIColor(red: CGFloat(1.0 - factor), green: 1.0, blue: 0.0, alpha: 0.8) + return UIColor(red: CGFloat(1.0 - factor), green: 1.0, blue: 0.0, alpha: alpha) } } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 9147847..d1c79fb 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -51,6 +51,14 @@ class MLInferenceManager: ObservableObject { // Goal conditioning mode (point-conditioned models use 3D goals) private var goalDimension: Int = 3 + // MARK: - Frame Buffering for Temporal Models + private struct FrameBufferEntry { + let mlArray: MLMultiArray // Pre-processed [1,3,H,W] frame + let goalPoint: [Float]? // Goal at time of capture + } + private var frameBuffer: [FrameBufferEntry] = [] + private var maxBufferSize: Int = 1 // Set by model metadata (1 for single-frame, 3 for temporal) + // MARK: - Model Management private var modelManager: ModelManager private var cancellables = Set() @@ -66,10 +74,14 @@ class MLInferenceManager: ObservableObject { // MARK: - Gripper Overlay Properties private var gripperOpenCIImage: CIImage? private var gripperClosedCIImage: CIImage? + private var gripperOpenUIImage: UIImage? + private var gripperClosedUIImage: UIImage? private var gripperOverlayBuffer: vImage_Buffer? private var isUSBStreamingActive: Bool = false private var currentGripperValue: Float = 1.0 // Track latest gripper value - @Published var enableGripperOverlay: Bool = true // Default enabled + @Published var enableGripperOverlay: Bool = true // Default enabled (for model input) + @Published var showGripperOverlayOnScreen: Bool = true // Show overlay on AR view + @Published var currentGripperOverlayImage: UIImage? // Current overlay image for display @Published var saveDebugFrames: Bool = false // For testing // MARK: - Inference Settings @@ -134,6 +146,7 @@ class MLInferenceManager: ObservableObject { // Load open gripper (default/original) if let openImage = UIImage(named: "gripper_overlay") { gripperOpenCIImage = CIImage(image: openImage) + gripperOpenUIImage = openImage print("Open gripper overlay loaded: \(gripperOpenCIImage?.extent ?? .zero)") } else { print("Warning: Could not load gripper_overlay (open) image from assets") @@ -142,6 +155,7 @@ class MLInferenceManager: ObservableObject { // Load closed gripper if let closedImage = UIImage(named: "gripper_closed") { gripperClosedCIImage = CIImage(image: closedImage) + gripperClosedUIImage = closedImage print("Closed gripper overlay loaded: \(gripperClosedCIImage?.extent ?? .zero)") } else { print("Warning: Could not load gripper_closed image from assets") @@ -151,6 +165,28 @@ class MLInferenceManager: ObservableObject { if let openImage = UIImage(named: "gripper_overlay") { setupGripperOverlayBuffer(from: openImage) } + + // Set initial overlay image for display + Task { @MainActor in + updateGripperOverlayDisplay() + } + } + + @MainActor + private func updateGripperOverlayDisplay() { + guard showGripperOverlayOnScreen && !isUSBStreamingActive else { + currentGripperOverlayImage = nil + return + } + + let isGripperClosed = currentGripperValue < 0.6 + let imageToShow = isGripperClosed ? gripperClosedUIImage : gripperOpenUIImage + + print("DEBUG: Updating gripper overlay - value: \(String(format: "%.3f", currentGripperValue)), closed: \(isGripperClosed)") + + // Update published property (automatically triggers objectWillChange) + currentGripperOverlayImage = imageToShow + print("DEBUG: Gripper overlay image updated: \(isGripperClosed ? "CLOSED" : "OPEN")") } private func setupGripperOverlayBuffer(from uiImage: UIImage) { @@ -197,6 +233,9 @@ class MLInferenceManager: ObservableObject { func setUSBStreamingState(isActive: Bool) { isUSBStreamingActive = isActive print("USB streaming state: \(isActive ? "ON" : "OFF") - Gripper overlay: \(shouldShowGripperOverlay() ? "ENABLED" : "DISABLED")") + Task { @MainActor in + updateGripperOverlayDisplay() + } } private func shouldShowGripperOverlay() -> Bool { @@ -299,6 +338,8 @@ class MLInferenceManager: ObservableObject { // No active compiled model available model = nil modelMetadata = nil + frameBuffer.removeAll() + maxBufferSize = 1 return } @@ -307,7 +348,17 @@ class MLInferenceManager: ObservableObject { model = loadedModel // Extract model metadata for type detection - modelMetadata = try ModelMetadata(from: loadedModel) + let metadata = try ModelMetadata(from: loadedModel) + modelMetadata = metadata + + // Configure frame buffer based on model's temporal requirements + maxBufferSize = metadata.temporalFrames + frameBuffer.removeAll() + + print("Model loaded: \(activeModel.name)") + print(" Temporal frames: \(metadata.temporalFrames)") + print(" Goal conditioning: \(metadata.requiresGoalPoint)") + print(" Buffer size: \(maxBufferSize)") // 224x224 input for all models modelInputSize = CGSize(width: 224, height: 224) @@ -317,12 +368,14 @@ class MLInferenceManager: ObservableObject { goalDimension = 3 // Clear goal point if switching to non-point-conditioned model - if modelMetadata?.requiresGoalPoint == false { + if metadata.requiresGoalPoint == false { currentGoalPoint = nil } } catch { model = nil modelMetadata = nil + frameBuffer.removeAll() + maxBufferSize = 1 } } @@ -420,10 +473,14 @@ class MLInferenceManager: ObservableObject { func performInference(on pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval = CACurrentMediaTime()) { guard isInferenceEnabled, let model = model, - let metadata = modelMetadata else { return } + let metadata = modelMetadata else { + print("DEBUG: Inference skipped - enabled: \(isInferenceEnabled), model: \(model != nil), metadata: \(modelMetadata != nil)") + return + } // Check if goal point is required but not set if metadata.requiresGoalPoint && currentGoalPoint == nil { + print("DEBUG: Inference skipped - goal point required but not set") return // Skip inference until goal point is set } @@ -438,6 +495,7 @@ class MLInferenceManager: ObservableObject { do { modelInput = try prepareModelInput(pixelBuffer, metadata: metadata) } catch { + print("ERROR: Failed to prepare model input: \(error)") return } @@ -448,12 +506,14 @@ class MLInferenceManager: ObservableObject { autoreleasepool { do { + print("DEBUG: Running model prediction...") let output = try model.prediction(from: modelInput) + print("DEBUG: Model prediction succeeded") let inferenceTime = CACurrentMediaTime() - startTime self.processInferenceResults(output, inferenceTime: inferenceTime) } catch { - // Inference failed - continue processing + print("ERROR: Model inference failed: \(error)") } } } @@ -461,6 +521,7 @@ class MLInferenceManager: ObservableObject { // MARK: - Dynamic Input Preparation private func prepareModelInput(_ pixelBuffer: CVPixelBuffer, metadata: ModelMetadata) throws -> MLFeatureProvider { + print("DEBUG: Preparing input for \(metadata.modelType.displayName) model") switch metadata.modelType { case .pointConditioned: return try prepareVQBeTInput(pixelBuffer, metadata: metadata) @@ -478,8 +539,20 @@ class MLInferenceManager: ObservableObject { let imageInputName = metadata.getImageInputName() ?? "camera_image" let goalInputName = metadata.getGoalInputName() ?? "goal_point" - // Determine expected image input rank from the actual model description (fallback to 4) - let expectedImageRank: Int = { + // Process current frame and add to buffer + let processedFrame = try processFrame(pixelBuffer, targetSize: CGSize(width: 224, height: 224), debugPrefix: "point_conditioned") + let bufferEntry = FrameBufferEntry(mlArray: processedFrame, goalPoint: goalPointArray) + frameBuffer.append(bufferEntry) + + // Trim buffer to maxBufferSize + if frameBuffer.count > maxBufferSize { + frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) + } + + let temporalFrames = metadata.temporalFrames + + // Determine expected rank from model + let expectedRank: Int = { if let d = model?.modelDescription.inputDescriptionsByName[imageInputName], d.type == .multiArray, let shape = d.multiArrayConstraint?.shape { @@ -488,33 +561,108 @@ class MLInferenceManager: ObservableObject { return 4 }() - // Process image to match expected rank (support 4D [1,3,H,W] and 5D [1,1,3,H,W]) - let imageArray = try processFrameForVQBeT( - pixelBuffer, - inputSize: CGSize(width: 224, height: 224), - expectedRank: expectedImageRank - ) + print("DEBUG: Point-conditioned model - temporalFrames: \(temporalFrames), expectedRank: \(expectedRank), bufferSize: \(frameBuffer.count)") - // Prepare goal array to match model's expected shape when available + // Build image array based on temporal requirements + let imageArray: MLMultiArray + if temporalFrames > 1 { + // Temporal model: stack frames into [1,T,3,H,W] + let framesToUse = min(temporalFrames, frameBuffer.count) + let paddingNeeded = temporalFrames - framesToUse + + imageArray = try MLMultiArray(shape: [1, NSNumber(value: temporalFrames), 3, 224, 224], dataType: .float32) + + // Pad with repeated first frame if needed + for t in 0.. 1 && dims[2] == 3 { + let arr = try? MLMultiArray(shape: shape, dataType: .float32) + if let arr = arr { + let framesToUse = min(dims[1], frameBuffer.count) + let paddingNeeded = dims[1] - framesToUse + + // Pad with repeated first goal if needed + for t in 0.. MLFeatureProvider { - // Simple approach matching old working code - no coordinate transformations - let inputArray = try processFrameForInference(pixelBuffer) - // Prefer metadata-driven input name if available + print("DEBUG: prepareLegacyInput called") + + // Process frame using unified method + let processedFrame = try processFrame(pixelBuffer, targetSize: modelInputSize, debugPrefix: "standard") + print("DEBUG: Frame processed, shape: \(processedFrame.shape)") + + // For legacy models, determine if we need to add temporal dimension [1,1,3,H,W] let inputName = metadata.getImageInputName() ?? "x_1" + let inputArray: MLMultiArray + + if let d = model?.modelDescription.inputDescriptionsByName[inputName], + d.type == .multiArray, + let shape = d.multiArrayConstraint?.shape { + print("DEBUG: Model expects shape: \(shape), rank: \(shape.count)") + + if shape.count == 5 { + // Model expects 5D [1,1,3,H,W] + let height = Int(modelInputSize.height) + let width = Int(modelInputSize.width) + inputArray = try MLMultiArray(shape: [1, 1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) + + print("DEBUG: Converting [1,3,H,W] to [1,1,3,H,W]") + + // Copy from [1,3,H,W] to [1,1,3,H,W] + for c in 0..<3 { + for h in 0.. MLMultiArray { - let width = Int(inputSize.width) - let height = Int(inputSize.height) + // MARK: - Unified Frame Processing + private func processFrame(_ pixelBuffer: CVPixelBuffer, targetSize: CGSize, debugPrefix: String) throws -> MLMultiArray { + let width = Int(targetSize.width) + let height = Int(targetSize.height) // Create output pixel buffer let attributes: [String: Any] = [ @@ -583,45 +770,35 @@ class MLInferenceManager: ObservableObject { let inputImage = CIImage(cvPixelBuffer: pixelBuffer) let inputImageSize = CGSize(width: CVPixelBufferGetWidth(pixelBuffer), height: CVPixelBufferGetHeight(pixelBuffer)) - let scaleX = inputSize.width / inputImageSize.width - let scaleY = inputSize.height / inputImageSize.height + let scaleX = targetSize.width / inputImageSize.width + let scaleY = targetSize.height / inputImageSize.height let scaleTransform = CGAffineTransform(scaleX: scaleX, y: scaleY) var scaledImage = inputImage.transformed(by: scaleTransform) if applyServerImageOrientation { - // Server path rotates images by 180° overall; replicate using EXIF .down scaledImage = scaledImage.oriented(.down) } // Save original scaled image for debugging - saveDebugFrame(scaledImage, prefix: "vqbet_original") + saveDebugFrame(scaledImage, prefix: "\(debugPrefix)_original") // Apply gripper overlay if enabled and USB streaming is off if shouldShowGripperOverlay() { scaledImage = applyGripperOverlay(to: scaledImage) - // Save image with overlay for debugging - saveDebugFrame(scaledImage, prefix: "vqbet_with_overlay") + saveDebugFrame(scaledImage, prefix: "\(debugPrefix)_with_overlay") } - let cropRect = CGRect(origin: .zero, size: inputSize) - + let cropRect = CGRect(origin: .zero, size: targetSize) ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) - print("Image processed for VQ-BeT: \(inputSize)") - // Convert to MLMultiArray for VQ-BeT format - // Support 4D [1,3,H,W] and 5D [1,1,3,H,W] - return try convertPixelBufferToVQBeTArray(outputBuffer, width: width, height: height, expectedRank: expectedRank) + // Convert to MLMultiArray as single frame [1,3,H,W] for buffering + return try convertPixelBufferToMLMultiArray(outputBuffer, width: width, height: height) } - private func convertPixelBufferToVQBeTArray(_ pixelBuffer: CVPixelBuffer, width: Int, height: Int, expectedRank: Int) throws -> MLMultiArray { - let shape: [NSNumber] - let fiveD = (expectedRank >= 5) - if fiveD { - shape = [1, 1, 3, NSNumber(value: height), NSNumber(value: width)] - } else { - shape = [1, 3, NSNumber(value: height), NSNumber(value: width)] - } - let inputArray = try MLMultiArray(shape: shape, dataType: .float32) + // MARK: - Unified Pixel Buffer to MLMultiArray Conversion + private func convertPixelBufferToMLMultiArray(_ pixelBuffer: CVPixelBuffer, width: Int, height: Int) throws -> MLMultiArray { + // Always produce [1,3,H,W] for consistent buffering + let inputArray = try MLMultiArray(shape: [1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get pixel buffer base address"]) @@ -634,127 +811,41 @@ class MLInferenceManager: ObservableObject { for y in 0.. MLMultiArray { - // Create output pixel buffer for model input size - let attributes: [String: Any] = [ - kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32ARGB, - kCVPixelBufferWidthKey as String: Int(modelInputSize.width), - kCVPixelBufferHeightKey as String: Int(modelInputSize.height) - ] - - var outputPixelBuffer: CVPixelBuffer? - let status = CVPixelBufferCreate( - kCFAllocatorDefault, - Int(modelInputSize.width), - Int(modelInputSize.height), - kCVPixelFormatType_32ARGB, - attributes as CFDictionary, - &outputPixelBuffer - ) - - guard status == kCVReturnSuccess, let outputBuffer = outputPixelBuffer else { - throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to create output pixel buffer"]) - } - - // Use Core Image processing (same approach as ARViewContainer) - CVPixelBufferLockBaseAddress(pixelBuffer, .readOnly) - CVPixelBufferLockBaseAddress(outputBuffer, []) - defer { - CVPixelBufferUnlockBaseAddress(outputBuffer, []) - CVPixelBufferUnlockBaseAddress(pixelBuffer, .readOnly) - } - - let inputImage = CIImage(cvPixelBuffer: pixelBuffer) - - // Scale to model input size - let inputSize = CGSize(width: CVPixelBufferGetWidth(pixelBuffer), height: CVPixelBufferGetHeight(pixelBuffer)) - let scaleX = modelInputSize.width / inputSize.width - let scaleY = modelInputSize.height / inputSize.height - let scaleTransform = CGAffineTransform(scaleX: scaleX, y: scaleY) - - var scaledImage = inputImage.transformed(by: scaleTransform) - if applyServerImageOrientation { - scaledImage = scaledImage.oriented(.down) - } - - // Save original scaled image for debugging - saveDebugFrame(scaledImage, prefix: "standard_original") - - // Apply gripper overlay if enabled and USB streaming is off - if shouldShowGripperOverlay() { - scaledImage = applyGripperOverlay(to: scaledImage) - // Save image with overlay for debugging - saveDebugFrame(scaledImage, prefix: "standard_with_overlay") - } - - let cropRect = CGRect(origin: .zero, size: modelInputSize) - - // Render using the same CIContext approach as ARViewContainer - ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) - print("Image processed for inference: \(modelInputSize)") - - // Convert to MLMultiArray (simplified since we now have consistently formatted data) - return try convertProcessedPixelBufferToMLMultiArray(outputBuffer) - } + // MARK: - Result Processing - // MARK: - Simplified Pixel Buffer to MLMultiArray Conversion - private func convertProcessedPixelBufferToMLMultiArray(_ pixelBuffer: CVPixelBuffer) throws -> MLMultiArray { - // Explicitly index as [B=1, T=1, C=3, H=modelInputSize.height, W=modelInputSize.width] - let height = Int(modelInputSize.height) - let width = Int(modelInputSize.width) - let inputArray = try MLMultiArray( - shape: [1, 1, 3, NSNumber(value: height), NSNumber(value: width)], - dataType: .float32 - ) - - guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { - throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get pixel buffer base address"]) - } - - let buffer = baseAddress.assumingMemoryBound(to: UInt8.self) - let bytesPerRow = CVPixelBufferGetBytesPerRow(pixelBuffer) - let bytesPerPixel = 4 // ARGB format + /// Extract joint positions from model output, handling both single-step and multi-step outputs + private func extractJointPositions(from resultArray: MLMultiArray) -> [Float] { + let shape = resultArray.shape.map { $0.intValue } - // Since we're using Core Image processing, we have consistent ARGB format - for y in 0.. 1 && shape[2] >= 7 { + // Multi-step output: extract last timestep [T-1, 0, 0...6] + let lastTimestep = shape[0] - 1 + let jointPositions = (0..<7).map { i in + resultArray[[NSNumber(value: lastTimestep), 0, NSNumber(value: i)]].floatValue } + print("Multi-step output detected: shape \(shape), using last timestep [\(lastTimestep)]") + return jointPositions + } else { + // Single-step output: extract directly + let outputCount = min(resultArray.count, 10) + return (0..= 7 { currentGripperValue = jointPositions[6] + Task { @MainActor [weak self] in + self?.updateGripperOverlayDisplay() + } } let result = InferenceResult( @@ -812,7 +905,7 @@ class MLInferenceManager: ObservableObject { print("[\(modelName)] Standard: [\(positionString)] (\(String(format: "%.1f", inferenceTime * 1000))ms)") } else { - // Point-conditioned models - use existing complex logic + // Point-conditioned models let outputFeatureName = metadata.primaryOutputName ?? output.featureNames.first guard let outputFeatureName = outputFeatureName, @@ -820,13 +913,15 @@ class MLInferenceManager: ObservableObject { return } - // Extract values dynamically based on what the model outputs - let outputCount = min(resultArray.count, 10) - let jointPositions = (0..= 7 { currentGripperValue = jointPositions[6] + Task { @MainActor [weak self] in + self?.updateGripperOverlayDisplay() + } } let result = InferenceResult( diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 73109f3..4c91efa 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -52,7 +52,14 @@ struct ReadView : View{ ) .allowsHitTesting(true) - + // Gripper Overlay on AR View + if let mlManager = arViewModel.mlManager, + let overlayImage = mlManager.currentGripperOverlayImage { + Image(uiImage: overlayImage) + .resizable() + .scaledToFit() + .allowsHitTesting(false) + } } .frame(width: arViewWidth, height: arViewHeight) .padding(.bottom, arViewPadding) From 5ffdddfbb885e2eee3c393253160b8db33a17c8e Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Thu, 16 Oct 2025 17:29:52 -0400 Subject: [PATCH 36/56] added reticle overlay --- AnySense.xcodeproj/project.pbxproj | 4 + AnySense.xcworkspace/contents.xcworkspacedata | 3 + AnySense/Views/ReticleOverlayView.swift | 85 +++++++++++++++++++ AnySense/Views/readView.swift | 46 +++++----- 4 files changed, 118 insertions(+), 20 deletions(-) create mode 100644 AnySense/Views/ReticleOverlayView.swift diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 50ff99d..1a1f5ee 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -7,6 +7,7 @@ objects = { /* Begin PBXBuildFile section */ + 01090A442EA0996B004DB8C1 /* ReticleOverlayView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01090A432EA0996B004DB8C1 /* ReticleOverlayView.swift */; }; 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */; }; 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */; }; 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */; }; @@ -48,6 +49,7 @@ /* End PBXContainerItemProxy section */ /* Begin PBXFileReference section */ + 01090A432EA0996B004DB8C1 /* ReticleOverlayView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ReticleOverlayView.swift; sourceTree = ""; }; 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARVisualizationManager.swift; sourceTree = ""; }; 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ActionTransformUtils.swift; sourceTree = ""; }; 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceManager.swift; sourceTree = ""; }; @@ -156,6 +158,7 @@ 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */, B9E4B2312D62A9C40032E877 /* accountView.swift */, B9E4B2322D62A9C40032E877 /* ContentView.swift */, + 01090A432EA0996B004DB8C1 /* ReticleOverlayView.swift */, B9E4B2332D62A9C40032E877 /* peripheralView.swift */, B9E4B2342D62A9C40032E877 /* readView.swift */, ); @@ -339,6 +342,7 @@ files = ( 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */, B9E4B2362D62A9C40032E877 /* peripheralView.swift in Sources */, + 01090A442EA0996B004DB8C1 /* ReticleOverlayView.swift in Sources */, 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */, B9E4B2372D62A9C40032E877 /* accountView.swift in Sources */, B9E4B2382D62A9C40032E877 /* readView.swift in Sources */, diff --git a/AnySense.xcworkspace/contents.xcworkspacedata b/AnySense.xcworkspace/contents.xcworkspacedata index 1af6a93..9f99e2e 100644 --- a/AnySense.xcworkspace/contents.xcworkspacedata +++ b/AnySense.xcworkspace/contents.xcworkspacedata @@ -7,4 +7,7 @@ + + diff --git a/AnySense/Views/ReticleOverlayView.swift b/AnySense/Views/ReticleOverlayView.swift new file mode 100644 index 0000000..320b04c --- /dev/null +++ b/AnySense/Views/ReticleOverlayView.swift @@ -0,0 +1,85 @@ +// +// ReticleOverlayView.swift +// AnySense +// +// Created by AI Assistant on 2025/10/16. +// + +import SwiftUI + +/// A fixed center reticle overlay that represents the current phone pose/direction +/// Designed to mimic flight simulator HUD aesthetics +struct ReticleOverlayView: View { + let size: CGFloat = 40 // Diameter of the reticle + let lineLength: CGFloat = 15 // Length of crosshair lines + let lineWidth: CGFloat = 2 // Width of lines + let color: Color = .cyan + let opacity: Double = 0.7 + + var body: some View { + ZStack { + // Center circle + Circle() + .stroke(color, lineWidth: lineWidth) + .frame(width: size, height: size) + + // Center dot + Circle() + .fill(color) + .frame(width: 4, height: 4) + + // Top line + Rectangle() + .fill(color) + .frame(width: lineWidth, height: lineLength) + .offset(y: -(size/2 + lineLength/2 + 2)) + + // Bottom line + Rectangle() + .fill(color) + .frame(width: lineWidth, height: lineLength) + .offset(y: (size/2 + lineLength/2 + 2)) + + // Left line + Rectangle() + .fill(color) + .frame(width: lineLength, height: lineWidth) + .offset(x: -(size/2 + lineLength/2 + 2)) + + // Right line + Rectangle() + .fill(color) + .frame(width: lineLength, height: lineWidth) + .offset(x: (size/2 + lineLength/2 + 2)) + + // Corner brackets for enhanced visibility + ForEach(0..<4) { i in + ReticleCornerBracket() + .rotation3DEffect(.degrees(Double(i) * 90), axis: (x: 0, y: 0, z: 1)) + .offset(x: size/2 + 8, y: size/2 + 8) + } + } + .opacity(opacity) + } +} + +/// Small corner bracket for the reticle +struct ReticleCornerBracket: View { + var body: some View { + Path { path in + path.move(to: CGPoint(x: 0, y: 0)) + path.addLine(to: CGPoint(x: 8, y: 0)) + path.move(to: CGPoint(x: 0, y: 0)) + path.addLine(to: CGPoint(x: 0, y: 8)) + } + .stroke(Color.cyan, lineWidth: 1.5) + } +} + +#Preview { + ZStack { + Color.black.ignoresSafeArea() + ReticleOverlayView() + } +} + diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 4c91efa..a1ff30f 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -60,6 +60,12 @@ struct ReadView : View{ .scaledToFit() .allowsHitTesting(false) } + + // HUD-style Reticle Overlay (shows current pose/direction) + if arViewModel.arVisualizationManager.isVisualizationEnabled { + ReticleOverlayView() + .allowsHitTesting(false) + } } .frame(width: arViewWidth, height: arViewHeight) .padding(.bottom, arViewPadding) @@ -80,26 +86,26 @@ struct ReadView : View{ } Spacer() // AR Visualization Status Overlay - HStack { - VStack(alignment: .leading, spacing: 4) { - if arViewModel.arVisualizationManager.isVisualizationEnabled { - Text("Movement Tracking: ON") - .font(.caption) - .foregroundColor(.green) - Text("Max Arrows: \(arViewModel.arVisualizationManager.maxArrows)") - .font(.caption2) - .foregroundColor(.secondary) - } else { - Text("Movement Tracking: OFF") - .font(.caption) - .foregroundColor(.red) - } - } - .padding(8) - .background(Color.black.opacity(0.6)) - .cornerRadius(8) - Spacer() - } + // HStack { + // VStack(alignment: .leading, spacing: 4) { + // if arViewModel.arVisualizationManager.isVisualizationEnabled { + // Text("Movement Tracking: ON") + // .font(.caption) + // .foregroundColor(.green) + // Text("Max Arrows: \(arViewModel.arVisualizationManager.maxArrows)") + // .font(.caption2) + // .foregroundColor(.secondary) + // } else { + // Text("Movement Tracking: OFF") + // .font(.caption) + // .foregroundColor(.red) + // } + // } + // .padding(8) + // .background(Color.black.opacity(0.6)) + // .cornerRadius(8) + // Spacer() + // } .padding(.bottom, 10) } .frame(width: arViewWidth, height: arViewHeight) From 5eb68b1753d6c10054cbd096a0a3f71632fb0508 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Mon, 27 Oct 2025 20:04:20 -0400 Subject: [PATCH 37/56] working on visualization --- AnySense.xcodeproj/project.pbxproj | 4 - AnySense.xcworkspace/contents.xcworkspacedata | 3 - AnySense/Managers/ARViewContainer.swift | 14 +- .../Managers/ARVisualizationManager.swift | 575 ++++++------------ AnySense/Managers/MLInferenceManager.swift | 288 ++++++++- AnySense/Views/ReticleOverlayView.swift | 85 --- AnySense/Views/accountView.swift | 58 +- AnySense/Views/readView.swift | 22 +- 8 files changed, 501 insertions(+), 548 deletions(-) delete mode 100644 AnySense/Views/ReticleOverlayView.swift diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 1a1f5ee..50ff99d 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -7,7 +7,6 @@ objects = { /* Begin PBXBuildFile section */ - 01090A442EA0996B004DB8C1 /* ReticleOverlayView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01090A432EA0996B004DB8C1 /* ReticleOverlayView.swift */; }; 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */; }; 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */; }; 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */; }; @@ -49,7 +48,6 @@ /* End PBXContainerItemProxy section */ /* Begin PBXFileReference section */ - 01090A432EA0996B004DB8C1 /* ReticleOverlayView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ReticleOverlayView.swift; sourceTree = ""; }; 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARVisualizationManager.swift; sourceTree = ""; }; 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ActionTransformUtils.swift; sourceTree = ""; }; 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceManager.swift; sourceTree = ""; }; @@ -158,7 +156,6 @@ 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */, B9E4B2312D62A9C40032E877 /* accountView.swift */, B9E4B2322D62A9C40032E877 /* ContentView.swift */, - 01090A432EA0996B004DB8C1 /* ReticleOverlayView.swift */, B9E4B2332D62A9C40032E877 /* peripheralView.swift */, B9E4B2342D62A9C40032E877 /* readView.swift */, ); @@ -342,7 +339,6 @@ files = ( 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */, B9E4B2362D62A9C40032E877 /* peripheralView.swift in Sources */, - 01090A442EA0996B004DB8C1 /* ReticleOverlayView.swift in Sources */, 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */, B9E4B2372D62A9C40032E877 /* accountView.swift in Sources */, B9E4B2382D62A9C40032E877 /* readView.swift in Sources */, diff --git a/AnySense.xcworkspace/contents.xcworkspacedata b/AnySense.xcworkspace/contents.xcworkspacedata index 9f99e2e..1af6a93 100644 --- a/AnySense.xcworkspace/contents.xcworkspacedata +++ b/AnySense.xcworkspace/contents.xcworkspacedata @@ -7,7 +7,4 @@ - - diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index e731b62..927c6df 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -484,6 +484,9 @@ class ARViewModel: ObservableObject{ } func startUSBStreaming() { + // Reset ML inference state for new streaming session + mlManager?.resetInferenceState() + displayLink = CADisplayLink(target: self, selector: #selector(sendFrameUSB)) displayLink?.preferredFrameRateRange = CAFrameRateRange(minimum: Float(self.userFPS!), maximum: Float(self.userFPS!), preferred: Float(self.userFPS!)) displayLink?.add(to: .main, forMode: .common) @@ -496,6 +499,9 @@ class ARViewModel: ObservableObject{ displayLink = nil isUSBStreamingActive = false mlManager?.setUSBStreamingState(isActive: false) + + // Reset ML inference state when stopping + mlManager?.resetInferenceState() } func setupUSBStreaming() { @@ -737,6 +743,9 @@ class ARViewModel: ObservableObject{ func startRecording() -> RecordingFiles { let saveFileNames = setupRecording() + // Reset ML inference state for new recording + mlManager?.resetInferenceState() + // Start AR pose visualization with origin at current camera position arVisualizationManager.startRecordingVisualization() @@ -770,6 +779,9 @@ class ARViewModel: ObservableObject{ // Stop AR pose visualization arVisualizationManager.stopRecordingVisualization() + // Reset ML inference state when stopping + mlManager?.resetInferenceState() + if(ifAudioEnable) { audioSession.stopRunning() audioInput?.markAsFinished() @@ -1235,7 +1247,7 @@ class ARViewModel: ObservableObject{ } .store(in: &cancellables) - // ML results are now accessed directly during streaming for better real-time performance + } diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 0898b1a..0876798 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -4,13 +4,17 @@ import ARKit import simd import UIKit -// MARK: - Directional Arrow Data -struct DirectionalArrow { - let entity: Entity - let anchor: AnchorEntity - let timestamp: TimeInterval - let magnitude: Float - let movementVector: SIMD3 // Store the actual movement vector for color updates +// MARK: - Action State +enum ActionState { + case waiting // User is moving toward target + case reached // Cubes overlapped, inference triggered + + var displayName: String { + switch self { + case .waiting: return "waiting" + case .reached: return "reached" + } + } } // MARK: - Visualization Frequency (Matching MLInferenceManager) @@ -41,16 +45,24 @@ class ARVisualizationManager: ObservableObject { // MARK: - Published Properties @Published var isVisualizationEnabled: Bool = false - @Published var showMovementArrows: Bool = true - @Published var maxArrows: Int = 1 // Only show one arrow at a time + @Published var actionState: ActionState = .waiting @Published var visualizationFrequency: VisualizationFrequency = .medium // MARK: - Private Properties private var arView: ARView? private var worldOriginAnchor: AnchorEntity? - private var movementArrows: [DirectionalArrow] = [] private var lastVisualizationTime: CFTimeInterval = 0 + // Cube visualization entities + private var currentPoseCubeEntity: ModelEntity? + private var targetCubeEntity: ModelEntity? + private var targetCubeDisplayPosition: SIMD3? // Where target cube is displayed (with offset) + private var actualCameraPosition: SIMD3? // Actual camera position for proximity + private var targetCameraPosition: SIMD3? // Target camera position for proximity (without offset) + + // Proximity detection + private let proximityThreshold: Float = 0.10 // 10cm for "merged" state + // Target/device pose state for point-conditioned flows private var targetPose: SIMD3? private var actualDevicePose: SIMD3 = SIMD3(0, 0, 0) @@ -63,37 +75,14 @@ class ARVisualizationManager: ObservableObject { private var previousWorldPosition: SIMD3? private var hasEstablishedOrigin: Bool = false - // Movement detection to prevent overlapping arrows - private var lastArrowPosition: SIMD3? - private var movementThreshold: Float = 0.01 // 1cm minimum movement between arrows - - // Trajectory deviation tracking - private var expectedTrajectory: [SIMD3] = [] // Expected movement trajectory - private var trajectoryDeviationThreshold: Float = 0.02 // 2cm deviation threshold for green/red - - // Arrow visual configuration - private let arrowBaseLength: Float = 0.25 // Base length in meters (increased for visibility) - private let arrowThickness: Float = 0.012 // Arrow shaft thickness (increased for visibility) - private let arrowHeadRatio: Float = 0.3 // Head vs shaft ratio (increased for visibility) - private let arrowHeadWidth: Float = 0.035 // Arrow head width (increased for visibility) - private let axisLength: Float = 0.08 // Coordinate axes length - private let axisThickness: Float = 0.005 // Coordinate axes thickness - - // Arrow lifecycle - private let arrowLifetime: TimeInterval = 3.0 // Arrows fade after 3 seconds + // Cube visual configuration + private let cubeSize: Float = 0.02 // 2cm cubes + private let currentCubeForwardOffset: Float = -0.010 // -5cm offset (out of screen, towards camera) + private let targetCubeForwardOffset: Float = 0.00 // -3cm offset for target cube + private let goalForwardOffset: Float = 0.00 // -5cm offset for goal point // Debug controls var debugLoggingEnabled: Bool = true - var debugAlwaysDrawArrow: Bool = false - var debugForceColorVariation: Bool = false // When true, forces different colors for testing - // Visualization adjustments - var applyEndOffset: Bool = true // apply labels-forward (+Y_label) → -Z_camera offset - var endOffsetMeters: Float = 0.05 // meters; matches training shift used in labels.json mapping - var useMagnitudeConfidence: Bool = true // if true, scale color by delta magnitude; otherwise constant - - // Enhanced visibility controls - var enhancedVisibilityMode: Bool = false // When true, makes arrows more prominent for tracking - var visibilityOffsetDistance: Float = -0.1 // Distance to offset arrows from camera for visibility // Gripper state control var isGripperClosed: Bool = false // When true, stops visualization @@ -103,7 +92,7 @@ class ARVisualizationManager: ObservableObject { // MARK: - Initialization init() { - log("Initialized with delta-based movement arrows") + log("Initialized with cube-based visualization") } // MARK: - Logging Helper @@ -130,6 +119,9 @@ class ARVisualizationManager: ObservableObject { establishWorldOrigin() enableVisualization() + // Reset gripper state to allow visualization + isGripperClosed = false + print("Started movement visualization - enabled=\(isVisualizationEnabled)") } @@ -138,6 +130,12 @@ class ARVisualizationManager: ObservableObject { clearAllVisualization() resetMovementTracking() + // Reset action state + actionState = .waiting + + // Reset gripper state + isGripperClosed = false + print("Stopped movement visualization and reset tracking") } @@ -179,8 +177,6 @@ class ARVisualizationManager: ObservableObject { worldOrigin = SIMD3(0, 0, 0) currentWorldPosition = SIMD3(0, 0, 0) previousWorldPosition = nil - lastArrowPosition = nil // Reset arrow position tracking - expectedTrajectory = [] // Reset expected trajectory // Remove goal point visualization goalPointEntity?.removeFromParent() @@ -207,11 +203,15 @@ class ARVisualizationManager: ObservableObject { goalPointEntity?.removeFromParent() goalPointEntity = nil - // Remove all movement arrows - for arrow in movementArrows { - arrow.anchor.removeFromParent() - } - movementArrows.removeAll() + // Remove cube visualizations + currentPoseCubeEntity?.removeFromParent() + currentPoseCubeEntity = nil + + targetCubeEntity?.removeFromParent() + targetCubeEntity = nil + targetCubeDisplayPosition = nil + targetCameraPosition = nil + actualCameraPosition = nil } // MARK: - Initialization helper @@ -223,23 +223,64 @@ class ARVisualizationManager: ObservableObject { } } - func toggleMovementArrows() { - showMovementArrows.toggle() - if !showMovementArrows { - // Remove all movement arrows - for arrow in movementArrows { - arrow.anchor.removeFromParent() + // MARK: - Cube Management Methods + func updateCurrentPoseCube(position: SIMD3) { + guard isVisualizationEnabled, !isGripperClosed else { return } + + DispatchQueue.main.async { [weak self] in + guard let self = self, let worldOriginAnchor = self.worldOriginAnchor else { + if self?.debugLoggingEnabled == true { + print("[Viz] Cannot update current cube - anchor not ready") + } + return + } + + // Create or update current pose cube + if self.currentPoseCubeEntity == nil { + let cubeMesh = MeshResource.generateBox(size: self.cubeSize) + let blueMaterial = SimpleMaterial(color: UIColor.systemBlue.withAlphaComponent(0.7), isMetallic: false) + self.currentPoseCubeEntity = ModelEntity(mesh: cubeMesh, materials: [blueMaterial]) + worldOriginAnchor.addChild(self.currentPoseCubeEntity!) + + if self.debugLoggingEnabled { + print("[Viz] Current pose cube created (blue, \(self.cubeSize)m)") + } } - movementArrows.removeAll() + + // Update position + self.currentPoseCubeEntity?.position = position + + // Check proximity if we have a target cube + self.checkProximityAndUpdateState() } } - func setMaxArrows(_ count: Int) { - maxArrows = max(1, min(20, count)) - // Trim existing arrows if needed - while movementArrows.count > maxArrows { - let oldArrow = movementArrows.removeFirst() - oldArrow.anchor.removeFromParent() + private func checkProximityAndUpdateState() { + guard !isGripperClosed, + let cameraPos = actualCameraPosition, + let targetPos = targetCameraPosition else { return } + + let distance = length(cameraPos - targetPos) + + if distance <= proximityThreshold { + // Camera reached target - signal inference trigger + if actionState != .reached { + actionState = .reached + log("Target reached - triggering inference (distance: \(String(format: "%.3f", distance))m)") + + // Notify observers that proximity was reached + NotificationCenter.default.post( + name: NSNotification.Name("ProximityReached"), + object: nil + ) + } + } else { + if actionState != .waiting { + actionState = .waiting + if debugLoggingEnabled { + log("State changed to waiting (distance: \(String(format: "%.3f", distance))m)") + } + } } } @@ -249,40 +290,31 @@ class ARVisualizationManager: ObservableObject { print("AR Visualization frequency set to: \(frequency.displayName)") } - // MARK: - Enhanced Visibility Methods - func enableEnhancedVisibility() { - enhancedVisibilityMode = true - visibilityOffsetDistance = 0.15 // Increase offset for better visibility - log("Enhanced visibility enabled - arrows will be more prominent") - } - - func disableEnhancedVisibility() { - enhancedVisibilityMode = false - visibilityOffsetDistance = 0.1 // Reset to default offset - log("Enhanced visibility disabled") - } - - func setVisibilityOffset(_ distance: Float) { - visibilityOffsetDistance = max(0.05, min(0.3, distance)) // Clamp between 5cm and 30cm - log("Visibility offset: \(visibilityOffsetDistance)m") - } - - func setMovementThreshold(_ threshold: Float) { - movementThreshold = max(0.005, min(0.05, threshold)) // Clamp between 5mm and 5cm - log("Movement threshold: \(movementThreshold)m") - } - - func toggleConfidenceMode() { - useMagnitudeConfidence.toggle() - print("Confidence mode: \(useMagnitudeConfidence ? "Magnitude-based" : "Direction-based")") + // MARK: - Proximity Configuration + func setProximityThreshold(_ threshold: Float) { + // Allow adjusting the merge distance threshold if needed + log("Proximity threshold: \(threshold)m") } // MARK: - Gripper State Control func setGripperState(isClosed: Bool) { + let previousState = isGripperClosed isGripperClosed = isClosed - if isClosed { - print("Gripper closed - visualization will be disabled") - } else { + + if isClosed && !previousState { + // Gripper just closed - hide all visualization + print("Gripper closed - hiding all visualization") + + DispatchQueue.main.async { [weak self] in + // Remove cubes + self?.currentPoseCubeEntity?.removeFromParent() + self?.targetCubeEntity?.removeFromParent() + self?.goalPointEntity?.removeFromParent() + + // Set action state to waiting + self?.actionState = .waiting + } + } else if !isClosed && previousState { print("Gripper opened - visualization enabled") } } @@ -319,42 +351,28 @@ class ARVisualizationManager: ObservableObject { return useVirtualGripper && !isUSBStreamingActive } - func enableDebugColorVariation() { - debugForceColorVariation = true - print("Debug color variation enabled - arrows will cycle through colors") - } - - func disableDebugColorVariation() { - debugForceColorVariation = false - print("Debug color variation disabled") - } - - // MARK: - Trajectory Deviation Control - func setExpectedTrajectory(_ trajectory: [SIMD3]) { - expectedTrajectory = trajectory - print("Expected trajectory set with \(trajectory.count) points") - } - - func setDeviationThreshold(_ threshold: Float) { - trajectoryDeviationThreshold = max(0.005, min(0.1, threshold)) // Clamp between 5mm and 10cm - print("Deviation threshold set to: \(trajectoryDeviationThreshold)m") - } - - func updateArrowColors() { - // Update colors of all existing arrows based on current trajectory deviation - for arrow in movementArrows { - // Calculate new confidence based on current trajectory - let arrowMovement = extractMovementFromArrow(arrow) - let newConfidence = calculateTrajectoryDeviationConfidence(actualMovement: arrowMovement) - updateArrowColor(arrow: arrow, confidence: newConfidence) - } - print("Updated colors for \(movementArrows.count) existing arrows") - } // MARK: - Device Pose Integration func updateActualDevicePose(from arFrame: ARFrame) { let t = arFrame.camera.transform actualDevicePose = SIMD3(t.columns.3.x, t.columns.3.y, t.columns.3.z) + + // Update current pose cube position every frame to track camera + if isVisualizationEnabled && hasEstablishedOrigin { + let currentCameraPosition = SIMD3( + t.columns.3.x, + t.columns.3.y, + t.columns.3.z + ) - worldOrigin + + // Store actual camera position for proximity checking + actualCameraPosition = currentCameraPosition + + // Position blue cube with -5cm forward offset (Z direction only) + let cubePosition = currentCameraPosition + SIMD3(0, 0, currentCubeForwardOffset) + + updateCurrentPoseCube(position: cubePosition) + } } func setTargetPose(_ worldPoint: SIMD3) { @@ -372,17 +390,7 @@ class ARVisualizationManager: ObservableObject { // MARK: - ML Integration Method func updatePoseFromMLOutput(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) { - // Apply frequency throttling - if timestamp - lastVisualizationTime < visualizationFrequency.interval { - if debugLoggingEnabled { - // Visualization throttled - } - return - } - - lastVisualizationTime = timestamp - - guard isVisualizationEnabled, showMovementArrows else { return } + guard isVisualizationEnabled else { return } guard hasEstablishedOrigin else { print("World origin not established - cannot track movement") return @@ -399,7 +407,7 @@ class ARVisualizationManager: ObservableObject { } // Interpret joint actions as movement deltas in CAMERA coordinates, then rotate into world frame - let (cameraDeltaTranslation, _, confidence) = interpretMLDirections(jointActions, timestamp: timestamp) + let (cameraDeltaTranslation, _) = interpretMLDirections(jointActions, timestamp: timestamp) let cameraTransform = getCurrentCameraTransform() let rotationWorldFromCamera = simd_float3x3( columns: ( @@ -409,14 +417,13 @@ class ARVisualizationManager: ObservableObject { ) ) let deltaTranslation = rotationWorldFromCamera * cameraDeltaTranslation + if debugLoggingEnabled { func fmt(_ f: Float) -> String { String(format: "%.3f", f) } func fmt3(_ v: SIMD3) -> String { "(\(fmt(v.x)), \(fmt(v.y)), \(fmt(v.z)))" } - print("[Viz] Δcam \(fmt3(cameraDeltaTranslation)) → Δworld \(fmt3(deltaTranslation)) | confidence: \(fmt(confidence))") + print("[Viz] Δcam \(fmt3(cameraDeltaTranslation)) → Δworld \(fmt3(deltaTranslation))") } - // ML coordinate transform applied - // Get current camera position relative to world origin let currentCameraPosition = SIMD3( cameraTransform.columns.3.x, @@ -424,279 +431,73 @@ class ARVisualizationManager: ObservableObject { cameraTransform.columns.3.z ) - worldOrigin - // Show ML policy arrow from current camera position, not accumulated position - // Position arrows further out for better visibility (configurable offset distance) - let cameraForward = SIMD3(cameraTransform.columns.2.x, cameraTransform.columns.2.y, cameraTransform.columns.2.z) - let offsetPosition = currentCameraPosition + cameraForward * visibilityOffsetDistance - let targetPosition = offsetPosition + deltaTranslation - - // Only create movement arrow if there's meaningful movement AND sufficient distance from last arrow - let movementMagnitude = length(deltaTranslation) - let shouldCreateArrow: Bool + // Calculate target position from actual camera position + action delta + let targetCamPos = currentCameraPosition + deltaTranslation - if let lastPos = lastArrowPosition { - let distanceFromLastArrow = length(offsetPosition - lastPos) - shouldCreateArrow = (movementMagnitude > 0.002 || debugAlwaysDrawArrow) && distanceFromLastArrow > movementThreshold - } else { - shouldCreateArrow = movementMagnitude > 0.002 || debugAlwaysDrawArrow - } + // Store target camera position for proximity checking + targetCameraPosition = targetCamPos - if shouldCreateArrow { - createMovementArrow( - from: offsetPosition, - to: targetPosition, - confidence: confidence, - timestamp: timestamp - ) - lastArrowPosition = offsetPosition // Update last arrow position - } else { - // Update colors of existing arrows based on current trajectory deviation - updateArrowColors() - } - - // Update tracking position to current camera position (not accumulated) - currentWorldPosition = currentCameraPosition + // Apply -5cm offset to green target cube for display (Z direction only) + let targetCubePos = targetCamPos + SIMD3(0, 0, targetCubeForwardOffset) - // Position updated with movement delta + // Update target cube + updateTargetCube(position: targetCubePos) + + // Update tracking position + currentWorldPosition = currentCameraPosition } - private func interpretMLDirections(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) -> (translation: SIMD3, rotation: simd_quatf, confidence: Float) { + private func interpretMLDirections(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) -> (translation: SIMD3, rotation: simd_quatf) { // Map policy action → CAMERA frame (translation and Euler rotation) let action7 = Array(jointActions.prefix(7)) - // Determine device interface orientation → quarter turns around camera Z - // var quarterTurns: Int = 0 - // if let windowScene = UIApplication.shared.connectedScenes.first as? UIWindowScene { - // switch windowScene.interfaceOrientation { - // case .landscapeLeft: - // quarterTurns = 1 - // case .landscapeRight: - // quarterTurns = -1 - // case .portraitUpsideDown: - // quarterTurns = 2 - // default: - // quarterTurns = 0 - // } - // } let mapped = ActionTransformUtils.policyToCameraEulerAction(action7, rotationUnit: .eulerXYZ) - var translationCamera = SIMD3(mapped[0], mapped[1], mapped[2]) - // Optional end-offset in CAMERA frame: labels forward (+Y_label) == -Z_camera - if applyEndOffset { - translationCamera += SIMD3(0, 0, -endOffsetMeters) - } + let translationCamera = SIMD3(mapped[0], mapped[1], mapped[2]) let rotationCamera = eulerToQuaternion(roll: mapped[3], pitch: mapped[4], yaw: mapped[5]) - // Confidence: based on trajectory deviation (green = close to expected, red = far from expected) - let movementMagnitude = length(translationCamera) - let confidence: Float - - if debugForceColorVariation { - // Force color variation for testing - cycle through colors - let timeBasedConfidence = Float((timestamp.truncatingRemainder(dividingBy: 3.0)) / 3.0) - confidence = timeBasedConfidence - } else { - // Calculate trajectory deviation-based confidence - confidence = calculateTrajectoryDeviationConfidence(actualMovement: translationCamera) - } - // Return CAMERA-frame delta; caller will rotate to WORLD frame using current camera pose - return (translationCamera, rotationCamera, confidence) + return (translationCamera, rotationCamera) } - // MARK: - Trajectory Deviation Calculation - private func calculateTrajectoryDeviationConfidence(actualMovement: SIMD3) -> Float { - // If no expected trajectory is set, use movement magnitude as fallback - guard !expectedTrajectory.isEmpty else { - let magnitude = length(actualMovement) - return min(1.0, max(0.0, magnitude * 20.0)) // Scale magnitude to 0-1 - } - - // Find the closest expected movement in the trajectory - let actualMagnitude = length(actualMovement) - var minDeviation: Float = Float.greatestFiniteMagnitude - - for expectedMovement in expectedTrajectory { - let expectedMagnitude = length(expectedMovement) - let magnitudeDeviation = abs(actualMagnitude - expectedMagnitude) - - // Calculate directional deviation (angle between vectors) - let angleDeviation: Float - if actualMagnitude > 0.001 && expectedMagnitude > 0.001 { - let dotProduct = dot(normalize(actualMovement), normalize(expectedMovement)) - let clampedDot = max(-1.0, min(1.0, dotProduct)) // Clamp for acos - angleDeviation = acos(clampedDot) * 180.0 / Float.pi // Convert to degrees - } else { - angleDeviation = 0.0 + func updateTargetCube(position: SIMD3) { + guard isVisualizationEnabled, !isGripperClosed else { + if debugLoggingEnabled { + print("[Viz] Cannot update target cube - visualization disabled or gripper closed") } - - // Combined deviation (magnitude + direction) - let combinedDeviation = magnitudeDeviation + (angleDeviation / 180.0) * 0.1 // Scale angle deviation - minDeviation = min(minDeviation, combinedDeviation) + return } - // Convert deviation to confidence (low deviation = high confidence = green) - // Deviation below threshold = green (confidence > 0.5) - // Deviation above threshold = red (confidence < 0.5) - let normalizedDeviation = minDeviation / trajectoryDeviationThreshold - let confidence = max(0.0, min(1.0, 1.0 - normalizedDeviation)) - - return confidence - } - - // MARK: - Arrow Color Update Helpers - private func extractMovementFromArrow(_ arrow: DirectionalArrow) -> SIMD3 { - // Use the stored movement vector for accurate color updates - return arrow.movementVector - } - - private func updateArrowColor(arrow: DirectionalArrow, confidence: Float) { - DispatchQueue.main.async { - // Get the arrow color based on confidence - let newColor = self.confidenceToColor(confidence, enhanced: self.enhancedVisibilityMode) - - // Update the arrow entity's material color - if let arrowEntity = arrow.entity as? ModelEntity { - let newMaterial = SimpleMaterial(color: newColor, isMetallic: false) - arrowEntity.model?.materials = [newMaterial] - } else { - // If it's a container entity, update child entities - for child in arrow.entity.children { - if let childEntity = child as? ModelEntity { - let newMaterial = SimpleMaterial(color: newColor, isMetallic: false) - childEntity.model?.materials = [newMaterial] - } + DispatchQueue.main.async { [weak self] in + guard let self = self, let worldOriginAnchor = self.worldOriginAnchor else { + if self?.debugLoggingEnabled == true { + print("[Viz] Cannot update target cube - anchor not ready") } + return } - } - } - - private func createMovementArrow(from: SIMD3, to: SIMD3, confidence: Float, timestamp: TimeInterval) { - guard let worldOriginAnchor = worldOriginAnchor else { return } - - DispatchQueue.main.async { [weak self, worldOriginAnchor] in - guard let self = self else { return } - - // Calculate movement vector - let movement = to - from - let movementMagnitude = length(movement) - - // Skip tiny movements (lowered threshold for better visibility) - guard movementMagnitude > 0.0005 else { return } - - // Create arrow entity showing movement from previous to current position - let arrowEntity = self.createMovementArrowEntity( - fromPosition: from, - toPosition: to, - movement: movement, - confidence: confidence - ) - - // Position arrow at the start position (in world origin's coordinate system) - arrowEntity.position = from - worldOriginAnchor.addChild(arrowEntity) - // Store arrow with metadata - let movementArrow = DirectionalArrow( - entity: arrowEntity, - anchor: worldOriginAnchor, - timestamp: timestamp, - magnitude: movementMagnitude, - movementVector: movement - ) - - // Remove existing arrow immediately (we only want one arrow at a time) - if let existingArrow = self.movementArrows.first { - existingArrow.entity.removeFromParent() + // Create or update target cube + if self.targetCubeEntity == nil { + let cubeMesh = MeshResource.generateBox(size: self.cubeSize) + let greenMaterial = SimpleMaterial(color: UIColor.systemGreen.withAlphaComponent(0.9), isMetallic: false) + self.targetCubeEntity = ModelEntity(mesh: cubeMesh, materials: [greenMaterial]) + worldOriginAnchor.addChild(self.targetCubeEntity!) + + if self.debugLoggingEnabled { + print("[Viz] Target cube created (green, \(self.cubeSize)m)") + } } - // Replace with new arrow - self.movementArrows = [movementArrow] - - // Movement arrow created - } - } - - private func createMovementArrowEntity(fromPosition: SIMD3, toPosition: SIMD3, movement: SIMD3, confidence: Float) -> Entity { - let arrowContainer = Entity() - - // Calculate arrow dimensions based on movement magnitude - let movementMagnitude = length(movement) - let minLength: Float = enhancedVisibilityMode ? 0.08 : 0.05 // Larger minimum in enhanced mode - let scaledLength = max(movementMagnitude, minLength) - let shaftLength = scaledLength * (1.0 - arrowHeadRatio) - let headLength = scaledLength * arrowHeadRatio - - // Create arrow shaft (cylinder) - let shaftMesh = MeshResource.generateBox( - width: arrowThickness, - height: arrowThickness, - depth: shaftLength - ) - - // Color based on confidence: red (low) -> yellow (medium) -> green (high) - // Enhanced visibility mode makes colors more vibrant - let shaftColor = confidenceToColor(confidence, enhanced: enhancedVisibilityMode) - let shaftEntity = ModelEntity( - mesh: shaftMesh, - materials: [SimpleMaterial(color: shaftColor, isMetallic: false)] - ) - - // Create arrow head (pointing toward destination) - let headMesh = MeshResource.generateBox( - width: arrowHeadWidth, - height: arrowHeadWidth, - depth: headLength - ) - - let headEntity = ModelEntity( - mesh: headMesh, - materials: [SimpleMaterial(color: shaftColor.withAlphaComponent(0.9), isMetallic: false)] - ) - - // Position shaft and head along the movement vector - shaftEntity.position = SIMD3(0, 0, shaftLength / 2) - headEntity.position = SIMD3(0, 0, shaftLength + headLength / 2) - - // Orient arrow in direction of movement - if movementMagnitude > 0.001 { - let normalizedMovement = normalize(movement) - let forward = SIMD3(0, 0, 1) - let rotationQuat = simd_quatf(from: forward, to: normalizedMovement) + // Update position + self.targetCubeEntity?.position = position + self.targetCubeDisplayPosition = position - arrowContainer.orientation = rotationQuat - } - - arrowContainer.addChild(shaftEntity) - arrowContainer.addChild(headEntity) - - return arrowContainer - } - - private func confidenceToColor(_ confidence: Float, enhanced: Bool = false) -> UIColor { - let clampedConfidence = max(0.0, min(1.0, confidence)) - let alpha: CGFloat = enhanced ? 1.0 : 0.9 - - if clampedConfidence < 0.5 { - let factor = clampedConfidence * 2.0 - return UIColor(red: 1.0, green: CGFloat(factor), blue: 0.0, alpha: alpha) - } else { - let factor = (clampedConfidence - 0.5) * 2.0 - return UIColor(red: CGFloat(1.0 - factor), green: 1.0, blue: 0.0, alpha: alpha) - } - } - - private func cleanupOldArrows(currentTime: TimeInterval) { - let expiredArrows = movementArrows.filter { currentTime - $0.timestamp > arrowLifetime } - - for expiredArrow in expiredArrows { - expiredArrow.entity.removeFromParent() - if let index = movementArrows.firstIndex(where: { $0.timestamp == expiredArrow.timestamp }) { - movementArrows.remove(at: index) + if self.debugLoggingEnabled { + func fmt(_ f: Float) -> String { String(format: "%.3f", f) } + print("[Viz] Target cube updated: (\(fmt(position.x)), \(fmt(position.y)), \(fmt(position.z)))") } } - - // Clean up expired arrows } + private func eulerToQuaternion(roll: Float, pitch: Float, yaw: Float) -> simd_quatf { let phi_2 = roll / 2.0 let theta_2 = pitch / 2.0 @@ -719,10 +520,11 @@ class ARVisualizationManager: ObservableObject { // MARK: - Goal Point Visualization private func updateGoalPointVisualization() { - guard let targetPose = targetPose, + guard !isGripperClosed, + let targetPose = targetPose, let worldOriginAnchor = worldOriginAnchor, hasEstablishedOrigin else { - print(" Cannot create goal visualization - targetPose: \(targetPose?.debugDescription ?? "nil"), anchor: \(worldOriginAnchor != nil), origin: \(hasEstablishedOrigin)") + print(" Cannot create goal visualization - targetPose: \(targetPose?.debugDescription ?? "nil"), anchor: \(worldOriginAnchor != nil), origin: \(hasEstablishedOrigin), gripperClosed: \(isGripperClosed)") goalPointEntity?.removeFromParent() goalPointEntity = nil return @@ -737,15 +539,18 @@ class ARVisualizationManager: ObservableObject { let goalMaterial = SimpleMaterial(color: .systemRed, isMetallic: false) goalPointEntity = ModelEntity(mesh: sphereMesh, materials: [goalMaterial]) - // Position the sphere at the target pose (relative to world origin) + // Position the sphere at the target pose (relative to world origin) with -10cm offset (Z direction only) let relativePosition = targetPose - worldOrigin - goalPointEntity?.position = relativePosition + let goalDisplayPosition = relativePosition + SIMD3(0, 0, goalForwardOffset) + + goalPointEntity?.position = goalDisplayPosition worldOriginAnchor.addChild(goalPointEntity!) print("Goal point visualization created:") print(" Target pose (world): \(targetPose)") print(" World origin: \(worldOrigin)") print(" Relative position: \(relativePosition)") + print(" Display position (with offset): \(goalDisplayPosition)") print(" Distance from origin: \(length(relativePosition))m") } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index d1c79fb..59ca650 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -57,7 +57,12 @@ class MLInferenceManager: ObservableObject { let goalPoint: [Float]? // Goal at time of capture } private var frameBuffer: [FrameBufferEntry] = [] - private var maxBufferSize: Int = 1 // Set by model metadata (1 for single-frame, 3 for temporal) + private var maxBufferSize: Int = 3 // Always maintain 3 frames for rolling buffer + + // MARK: - Proximity-based Inference Control + private var proximityReached: Bool = false + private var isInferencePending: Bool = false + private var hasRunFirstInference: Bool = false // Track if we've run initial inference // MARK: - Model Management private var modelManager: ModelManager @@ -110,6 +115,7 @@ class MLInferenceManager: ObservableObject { // MARK: - Transform/Debug Settings var rotationUnit: ActionTransformUtils.RotationUnit = .eulerXYZ var enableTransformDebug: Bool = true + var debugLoggingEnabled: Bool = true // Enable detailed logging // Apply server-style image orientation (Record3D publisher does rotations/mirrors) var applyServerImageOrientation: Bool = false @@ -127,6 +133,15 @@ class MLInferenceManager: ObservableObject { self?.loadActiveModel() } .store(in: &cancellables) + + // Listen for proximity reached notifications from ARVisualizationManager + NotificationCenter.default.addObserver( + forName: NSNotification.Name("ProximityReached"), + object: nil, + queue: .main + ) { [weak self] _ in + self?.handleProximityReached() + } } deinit { @@ -339,7 +354,8 @@ class MLInferenceManager: ObservableObject { model = nil modelMetadata = nil frameBuffer.removeAll() - maxBufferSize = 1 + hasRunFirstInference = false + // maxBufferSize stays at 3 return } @@ -351,9 +367,10 @@ class MLInferenceManager: ObservableObject { let metadata = try ModelMetadata(from: loadedModel) modelMetadata = metadata - // Configure frame buffer based on model's temporal requirements - maxBufferSize = metadata.temporalFrames + // Always maintain 3-frame rolling buffer (don't override with model's temporal requirement) + // maxBufferSize stays at 3 frameBuffer.removeAll() + hasRunFirstInference = false // Reset for new model print("Model loaded: \(activeModel.name)") print(" Temporal frames: \(metadata.temporalFrames)") @@ -375,7 +392,8 @@ class MLInferenceManager: ObservableObject { model = nil modelMetadata = nil frameBuffer.removeAll() - maxBufferSize = 1 + hasRunFirstInference = false + // maxBufferSize stays at 3 } } @@ -460,6 +478,16 @@ class MLInferenceManager: ObservableObject { self.arViewContainer = container } + // MARK: - Proximity Handler + private func handleProximityReached() { + guard !isInferencePending else { + print("[MLInference] Proximity reached but inference already pending - skipping") + return + } + proximityReached = true + print("[MLInference] Proximity reached - inference will trigger with next frame (firstInference: \(hasRunFirstInference))") + } + // MARK: - Inference Methods (Using existing frame processing patterns) func performInference(on pixelBuffer: CVPixelBuffer, arFrame: ARFrame?, timestamp: CFTimeInterval = CACurrentMediaTime()) { // Update device pose for visualization (optional) @@ -472,30 +500,68 @@ class MLInferenceManager: ObservableObject { func performInference(on pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval = CACurrentMediaTime()) { guard isInferenceEnabled, - let model = model, let metadata = modelMetadata else { - print("DEBUG: Inference skipped - enabled: \(isInferenceEnabled), model: \(model != nil), metadata: \(modelMetadata != nil)") return } // Check if goal point is required but not set if metadata.requiresGoalPoint && currentGoalPoint == nil { - print("DEBUG: Inference skipped - goal point required but not set") - return // Skip inference until goal point is set + return // Skip until goal point is set + } + + // ALWAYS buffer frames (rolling 3-frame buffer) + do { + let processedFrame = try processFrame(pixelBuffer, targetSize: CGSize(width: 224, height: 224), debugPrefix: "buffered") + let goalPointArray = metadata.requiresGoalPoint ? getGoalPointForModel() : nil + let bufferEntry = FrameBufferEntry(mlArray: processedFrame, goalPoint: goalPointArray) + + frameBuffer.append(bufferEntry) + + // Maintain rolling buffer of 3 frames + if frameBuffer.count > maxBufferSize { + frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) + } + } catch { + print("ERROR: Failed to buffer frame: \(error)") + return + } + + // Run inference if: + // 1. This is the first inference (to create initial target cube), OR + // 2. Proximity is reached AND we haven't just run inference + let isFirstInference = !hasRunFirstInference && frameBuffer.count >= maxBufferSize + let isProximityTriggered = proximityReached && !isInferencePending + let shouldRunInference = isFirstInference || isProximityTriggered + + if debugLoggingEnabled && frameBuffer.count == maxBufferSize && !shouldRunInference { + print("[MLInference] Buffer full (\(frameBuffer.count)) but not triggering: firstInference=\(hasRunFirstInference), proximity=\(proximityReached), pending=\(isInferencePending)") + } + + guard shouldRunInference else { + return } - if timestamp - lastInferenceTime < inferenceFrequency.interval { + // Ensure we have a model loaded + guard let model = model else { + print("ERROR: No model loaded for inference") return } - lastInferenceTime = timestamp + // Mark inference as pending + isInferencePending = true + proximityReached = false // Reset proximity flag - // Prepare input synchronously to avoid capturing non-sendable CVPixelBuffer + if debugLoggingEnabled { + print("[MLInference] Running inference - firstTime: \(!hasRunFirstInference), buffer: \(frameBuffer.count)") + } + + // Prepare input using buffered frames let modelInput: MLFeatureProvider do { - modelInput = try prepareModelInput(pixelBuffer, metadata: metadata) + modelInput = try prepareModelInputFromBuffer(metadata: metadata) } catch { print("ERROR: Failed to prepare model input: \(error)") + isInferencePending = false return } @@ -506,20 +572,47 @@ class MLInferenceManager: ObservableObject { autoreleasepool { do { - print("DEBUG: Running model prediction...") + print("DEBUG: Running model prediction with buffered frames...") let output = try model.prediction(from: modelInput) print("DEBUG: Model prediction succeeded") let inferenceTime = CACurrentMediaTime() - startTime self.processInferenceResults(output, inferenceTime: inferenceTime) + + // Reset pending flag and mark first inference complete + DispatchQueue.main.async { + self.isInferencePending = false + if !self.hasRunFirstInference { + self.hasRunFirstInference = true + print("[MLInference] First inference complete - target cube should now be visible") + } + } } catch { print("ERROR: Model inference failed: \(error)") + DispatchQueue.main.async { + self.isInferencePending = false + } } } } } // MARK: - Dynamic Input Preparation + private func prepareModelInputFromBuffer(metadata: ModelMetadata) throws -> MLFeatureProvider { + print("DEBUG: Preparing input from buffer for \(metadata.modelType.displayName) model") + + guard !frameBuffer.isEmpty else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Frame buffer is empty"]) + } + + switch metadata.modelType { + case .pointConditioned: + return try prepareVQBeTInputFromBuffer(metadata: metadata) + case .standard: + return try prepareLegacyInputFromBuffer(metadata: metadata) + } + } + private func prepareModelInput(_ pixelBuffer: CVPixelBuffer, metadata: ModelMetadata) throws -> MLFeatureProvider { print("DEBUG: Preparing input for \(metadata.modelType.displayName) model") switch metadata.modelType { @@ -735,6 +828,157 @@ class MLInferenceManager: ObservableObject { return try MLDictionaryFeatureProvider(dictionary: [inputName: MLFeatureValue(multiArray: inputArray)]) } + // MARK: - Buffer-based Input Preparation Methods + private func prepareVQBeTInputFromBuffer(metadata: ModelMetadata) throws -> MLFeatureProvider { + let goalPointArray = frameBuffer.last?.goalPoint ?? getGoalPointForModel() + guard let goalPointArray = goalPointArray else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Goal point required"]) + } + + let imageInputName = metadata.getImageInputName() ?? "camera_image" + let goalInputName = metadata.getGoalInputName() ?? "goal_point" + let temporalFrames = metadata.temporalFrames + + // Determine expected rank from model + let expectedRank: Int = { + if let d = model?.modelDescription.inputDescriptionsByName[imageInputName], + d.type == .multiArray, + let shape = d.multiArrayConstraint?.shape { + return shape.count + } + return 4 + }() + + print("DEBUG: Using buffered frames - temporalFrames: \(temporalFrames), bufferSize: \(frameBuffer.count)") + + // Build image array from buffer + let imageArray: MLMultiArray + if temporalFrames > 1 { + // Temporal model: use last N frames from buffer + let framesToUse = min(temporalFrames, frameBuffer.count) + let paddingNeeded = temporalFrames - framesToUse + + imageArray = try MLMultiArray(shape: [1, NSNumber(value: temporalFrames), 3, 224, 224], dataType: .float32) + + // Pad with repeated first frame if needed + if paddingNeeded > 0 { + let srcFrame = frameBuffer[0].mlArray + for t in 0.. 1 && dims[2] == 3 { + let arr = try? MLMultiArray(shape: shape, dataType: .float32) + if let arr = arr { + for t in 0.. MLFeatureProvider { + let inputName = metadata.getImageInputName() ?? "x_1" + let latestFrame = frameBuffer.last!.mlArray + let inputArray: MLMultiArray + + if let d = model?.modelDescription.inputDescriptionsByName[inputName], + d.type == .multiArray, + let shape = d.multiArrayConstraint?.shape { + + if shape.count == 5 { + let height = 224 + let width = 224 + inputArray = try MLMultiArray(shape: [1, 1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) + + for c in 0..<3 { + for h in 0.. MLMultiArray { let width = Int(targetSize.width) @@ -867,8 +1111,12 @@ class MLInferenceManager: ObservableObject { // Update gripper value for overlay switching (7th element, index 6) if jointPositions.count >= 7 { currentGripperValue = jointPositions[6] + let isGripperClosed = currentGripperValue < 0.6 + Task { @MainActor [weak self] in self?.updateGripperOverlayDisplay() + // Update AR visualization manager gripper state to stop visualization when closed + self?.arVisualizationManager?.setGripperState(isClosed: isGripperClosed) } } @@ -919,8 +1167,12 @@ class MLInferenceManager: ObservableObject { // Update gripper value for overlay switching (7th element, index 6) if jointPositions.count >= 7 { currentGripperValue = jointPositions[6] + let isGripperClosed = currentGripperValue < 0.6 + Task { @MainActor [weak self] in self?.updateGripperOverlayDisplay() + // Update AR visualization manager gripper state to stop visualization when closed + self?.arVisualizationManager?.setGripperState(isClosed: isGripperClosed) } } @@ -976,6 +1228,14 @@ class MLInferenceManager: ObservableObject { print("Inference disabled") } + func resetInferenceState() { + hasRunFirstInference = false + proximityReached = false + isInferencePending = false + frameBuffer.removeAll() + print("Inference state reset - ready for new recording") + } + func setInferenceFrequency(_ frequency: InferenceFrequency) { inferenceFrequency = frequency print("Inference frequency: \(frequency.displayName)") diff --git a/AnySense/Views/ReticleOverlayView.swift b/AnySense/Views/ReticleOverlayView.swift deleted file mode 100644 index 320b04c..0000000 --- a/AnySense/Views/ReticleOverlayView.swift +++ /dev/null @@ -1,85 +0,0 @@ -// -// ReticleOverlayView.swift -// AnySense -// -// Created by AI Assistant on 2025/10/16. -// - -import SwiftUI - -/// A fixed center reticle overlay that represents the current phone pose/direction -/// Designed to mimic flight simulator HUD aesthetics -struct ReticleOverlayView: View { - let size: CGFloat = 40 // Diameter of the reticle - let lineLength: CGFloat = 15 // Length of crosshair lines - let lineWidth: CGFloat = 2 // Width of lines - let color: Color = .cyan - let opacity: Double = 0.7 - - var body: some View { - ZStack { - // Center circle - Circle() - .stroke(color, lineWidth: lineWidth) - .frame(width: size, height: size) - - // Center dot - Circle() - .fill(color) - .frame(width: 4, height: 4) - - // Top line - Rectangle() - .fill(color) - .frame(width: lineWidth, height: lineLength) - .offset(y: -(size/2 + lineLength/2 + 2)) - - // Bottom line - Rectangle() - .fill(color) - .frame(width: lineWidth, height: lineLength) - .offset(y: (size/2 + lineLength/2 + 2)) - - // Left line - Rectangle() - .fill(color) - .frame(width: lineLength, height: lineWidth) - .offset(x: -(size/2 + lineLength/2 + 2)) - - // Right line - Rectangle() - .fill(color) - .frame(width: lineLength, height: lineWidth) - .offset(x: (size/2 + lineLength/2 + 2)) - - // Corner brackets for enhanced visibility - ForEach(0..<4) { i in - ReticleCornerBracket() - .rotation3DEffect(.degrees(Double(i) * 90), axis: (x: 0, y: 0, z: 1)) - .offset(x: size/2 + 8, y: size/2 + 8) - } - } - .opacity(opacity) - } -} - -/// Small corner bracket for the reticle -struct ReticleCornerBracket: View { - var body: some View { - Path { path in - path.move(to: CGPoint(x: 0, y: 0)) - path.addLine(to: CGPoint(x: 8, y: 0)) - path.move(to: CGPoint(x: 0, y: 0)) - path.addLine(to: CGPoint(x: 0, y: 8)) - } - .stroke(Color.cyan, lineWidth: 1.5) - } -} - -#Preview { - ZStack { - Color.black.ignoresSafeArea() - ReticleOverlayView() - } -} - diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 007dc86..e3b1610 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -40,7 +40,7 @@ struct SettingsView : View{ ZStack{ Color.customizedBackground .ignoresSafeArea() - Form{ + Form { Section(header: Text("GENERAL")) { HStack { VStack(alignment: .leading, spacing: 8) { @@ -216,52 +216,10 @@ struct SettingsView : View{ } } - // MARK: - Movement Tracking Section - Section(header: Text("MOVEMENT TRACKING")) { - HStack { - Text("Show Movement Arrows") - .font(.body) - .foregroundColor(.primary) - Spacer() - Toggle("", isOn: $arViewModel.arVisualizationManager.showMovementArrows) - .onChange(of: arViewModel.arVisualizationManager.showMovementArrows) { oldValue, newValue in - arViewModel.arVisualizationManager.toggleMovementArrows() - } - } - .padding(.vertical, 5) - - VStack(alignment: .leading, spacing: 12) { - Text("Max Movement Arrows") - .font(.body) - .foregroundColor(.primary) - - let maxArrowsBinding = Binding( - get: { Double(arViewModel.arVisualizationManager.maxArrows) }, - set: { newValue in - arViewModel.arVisualizationManager.setMaxArrows(Int(newValue)) - } - ) - - HStack { - Text("1") - .font(.caption) - .foregroundColor(.gray) - - Slider(value: maxArrowsBinding, in: 1...20, step: 1) - - Text("20") - .font(.caption) - .foregroundColor(.gray) - } - - Text("Current: \(arViewModel.arVisualizationManager.maxArrows) arrows") - .font(.caption) - .foregroundColor(.gray) - } - .padding(.vertical, 5) - + // MARK: - Cube Visualization Section + Section(header: Text("CUBE VISUALIZATION")) { VStack(alignment: .leading, spacing: 8) { - Text("Movement Tracking Status") + Text("Visualization Status") .font(.body) .foregroundColor(.primary) @@ -276,16 +234,16 @@ struct SettingsView : View{ } HStack { - Text("Frequency:") + Text("Action State:") .font(.caption) .foregroundColor(.gray) Spacer() - Text(arViewModel.arVisualizationManager.visualizationFrequency.displayName) + Text(arViewModel.arVisualizationManager.actionState.displayName) .font(.caption) - .foregroundColor(.gray) + .foregroundColor(arViewModel.arVisualizationManager.actionState == .waiting ? .yellow : .green) } - Text("Shows arrows between consecutive ML inference positions") + Text("Shows blue cube (current) and green cube (target) for action guidance") .font(.caption2) .foregroundColor(.gray) .padding(.top, 4) diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index a1ff30f..27207ee 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -60,12 +60,6 @@ struct ReadView : View{ .scaledToFit() .allowsHitTesting(false) } - - // HUD-style Reticle Overlay (shows current pose/direction) - if arViewModel.arVisualizationManager.isVisualizationEnabled { - ReticleOverlayView() - .allowsHitTesting(false) - } } .frame(width: arViewWidth, height: arViewHeight) .padding(.bottom, arViewPadding) @@ -81,6 +75,22 @@ struct ReadView : View{ } } + // Action State Display (cube visualization status) + if arViewModel.arVisualizationManager.isVisualizationEnabled { + HStack(spacing: 4) { + Text("Next action:") + .font(.caption) + .foregroundColor(.white) + Text(arViewModel.arVisualizationManager.actionState.displayName) + .font(.caption) + .bold() + .foregroundColor(arViewModel.arVisualizationManager.actionState == .waiting ? .yellow : .green) + } + .padding(8) + .background(Color.black.opacity(0.6)) + .cornerRadius(8) + } + } Spacer() } From 2bad58580a0bda7e09513563f74790c59990e657 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Tue, 28 Oct 2025 13:50:57 -0400 Subject: [PATCH 38/56] fixing goal point visualization --- AnySense/Managers/ARViewContainer.swift | 70 ++++++++++++------- .../Managers/ARVisualizationManager.swift | 50 +++++++++---- 2 files changed, 80 insertions(+), 40 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 927c6df..67e67b1 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -76,7 +76,19 @@ struct ARViewContainer: UIViewRepresentable { // Try depth-based unprojection first (for LiDAR devices) if let (worldPoint, method) = parent.worldPointFromDepth(at: location, in: arView) { - print("Using \(method) method for 3D point: \(worldPoint)") + print("📍 Tap at screen location: \(location)") + print(" Using \(method) method for 3D point: \(worldPoint)") + + // Show distance from camera + if let currentFrame = arView.session.currentFrame { + let camPos = simd_float3( + currentFrame.camera.transform.columns.3.x, + currentFrame.camera.transform.columns.3.y, + currentFrame.camera.transform.columns.3.z + ) + let distanceFromCam = length(worldPoint - camPos) + print(" Distance from camera: \(distanceFromCam)m") + } // Create anchor at the world point var t = matrix_identity_float4x4 @@ -98,29 +110,32 @@ struct ARViewContainer: UIViewRepresentable { return } - // Fallback to raycast if depth unavailable or failed - if let hit = arView.raycast(from: location, allowing: .estimatedPlane, alignment: .any).first { - let t = hit.worldTransform - let world = simd_float3(t.columns.3.x, t.columns.3.y, t.columns.3.z) - - // Create a native ARKit anchor at the hit (world-locked) - let goalAnchor = ARAnchor(name: "goal", transform: t) - arView.session.add(anchor: goalAnchor) - - print("Using raycast fallback for 3D point: \(world)") - - // Notify ML pipeline with the world point - NotificationCenter.default.post( - name: NSNotification.Name("ARViewTapForGoal"), - object: nil, - userInfo: [ - "worldPoint": world, - "method": "raycast", - "location": location, - "bounds": arView.bounds - ] - ) - return + // Only fallback to raycast on non-Pro devices (no LiDAR) + // On Pro devices with LiDAR, if depth fails, user can just tap again + if !parent.depthStatus.isDepthAvailable { + if let hit = arView.raycast(from: location, allowing: .estimatedPlane, alignment: .any).first { + let t = hit.worldTransform + let world = simd_float3(t.columns.3.x, t.columns.3.y, t.columns.3.z) + + // Create a native ARKit anchor at the hit (world-locked) + let goalAnchor = ARAnchor(name: "goal", transform: t) + arView.session.add(anchor: goalAnchor) + + print("Using raycast fallback for 3D point: \(world)") + + // Notify ML pipeline with the world point + NotificationCenter.default.post( + name: NSNotification.Name("ARViewTapForGoal"), + object: nil, + userInfo: [ + "worldPoint": world, + "method": "raycast", + "location": location, + "bounds": arView.bounds + ] + ) + return + } } // Fallback: still notify with screen info (no hit yet) NotificationCenter.default.post( @@ -178,7 +193,10 @@ struct ARViewContainer: UIViewRepresentable { } } - guard !samples.isEmpty else { return nil } + guard !samples.isEmpty else { + print("⚠️ Depth unprojection failed: no valid depth samples") + return nil + } samples.sort() let depthValue = samples[samples.count / 2] // median @@ -194,7 +212,7 @@ struct ARViewContainer: UIViewRepresentable { // 6. Transform to world coordinates let pc = simd_float4(xc, yc, zc, 1) let pw = simd_mul(frame.camera.transform, pc) - + return (simd_float3(pw.x, pw.y, pw.z), "depth") } diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 0876798..8678fac 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -61,7 +61,7 @@ class ARVisualizationManager: ObservableObject { private var targetCameraPosition: SIMD3? // Target camera position for proximity (without offset) // Proximity detection - private let proximityThreshold: Float = 0.10 // 10cm for "merged" state + private let proximityThreshold: Float = 0.15 // 15cm for "merged" state (increased for better detection) // Target/device pose state for point-conditioned flows private var targetPose: SIMD3? @@ -77,9 +77,8 @@ class ARVisualizationManager: ObservableObject { // Cube visual configuration private let cubeSize: Float = 0.02 // 2cm cubes - private let currentCubeForwardOffset: Float = -0.010 // -5cm offset (out of screen, towards camera) - private let targetCubeForwardOffset: Float = 0.00 // -3cm offset for target cube - private let goalForwardOffset: Float = 0.00 // -5cm offset for goal point + private let currentCubeForwardOffset: Float = -0.010 // -1cm offset (out of screen, towards camera) + private let targetCubeForwardOffset: Float = 0.00 // No offset for target cube // Debug controls var debugLoggingEnabled: Bool = true @@ -255,6 +254,8 @@ class ARVisualizationManager: ObservableObject { } } + private var lastLoggedDistance: Float = -1.0 + private func checkProximityAndUpdateState() { guard !isGripperClosed, let cameraPos = actualCameraPosition, @@ -262,11 +263,19 @@ class ARVisualizationManager: ObservableObject { let distance = length(cameraPos - targetPos) + // Log only when close to threshold or when distance changes significantly + let distanceChanged = abs(distance - lastLoggedDistance) > 0.02 // 2cm change + let isClose = distance < proximityThreshold * 1.5 // Within 1.5x threshold + if debugLoggingEnabled && (distanceChanged || isClose) { + print("[Proximity] 📏 Distance: \(String(format: "%.4f", distance))m | Threshold: \(proximityThreshold)m | \(distance <= proximityThreshold ? "✅ WITHIN" : "⏳ Far")") + lastLoggedDistance = distance + } + if distance <= proximityThreshold { // Camera reached target - signal inference trigger if actionState != .reached { actionState = .reached - log("Target reached - triggering inference (distance: \(String(format: "%.3f", distance))m)") + log("✅ Target reached - triggering inference (distance: \(String(format: "%.4f", distance))m)") // Notify observers that proximity was reached NotificationCenter.default.post( @@ -278,7 +287,7 @@ class ARVisualizationManager: ObservableObject { if actionState != .waiting { actionState = .waiting if debugLoggingEnabled { - log("State changed to waiting (distance: \(String(format: "%.3f", distance))m)") + log("⏳ State changed to waiting (distance: \(String(format: "%.4f", distance))m)") } } } @@ -376,6 +385,12 @@ class ARVisualizationManager: ObservableObject { } func setTargetPose(_ worldPoint: SIMD3) { + print("🎯 setTargetPose called with world point: \(worldPoint)") + print(" hasEstablishedOrigin: \(hasEstablishedOrigin)") + print(" worldOrigin: \(worldOrigin)") + print(" isGripperClosed: \(isGripperClosed)") + print(" isVisualizationEnabled: \(isVisualizationEnabled)") + targetPose = worldPoint // Ensure visualization is ready before creating goal point ensureVisualizationReady() @@ -524,7 +539,11 @@ class ARVisualizationManager: ObservableObject { let targetPose = targetPose, let worldOriginAnchor = worldOriginAnchor, hasEstablishedOrigin else { - print(" Cannot create goal visualization - targetPose: \(targetPose?.debugDescription ?? "nil"), anchor: \(worldOriginAnchor != nil), origin: \(hasEstablishedOrigin), gripperClosed: \(isGripperClosed)") + print("❌ Cannot create goal visualization:") + print(" targetPose exists: \(targetPose != nil)") + print(" worldOriginAnchor exists: \(worldOriginAnchor != nil)") + print(" hasEstablishedOrigin: \(hasEstablishedOrigin)") + print(" isGripperClosed: \(isGripperClosed)") goalPointEntity?.removeFromParent() goalPointEntity = nil return @@ -535,23 +554,26 @@ class ARVisualizationManager: ObservableObject { goalPointEntity = nil // Create a visible sphere - let sphereMesh = MeshResource.generateSphere(radius: 0.01) + let sphereMesh = MeshResource.generateSphere(radius: 0.02) // 2cm radius for better visibility let goalMaterial = SimpleMaterial(color: .systemRed, isMetallic: false) goalPointEntity = ModelEntity(mesh: sphereMesh, materials: [goalMaterial]) - // Position the sphere at the target pose (relative to world origin) with -10cm offset (Z direction only) + // Position the sphere at the target pose (relative to world origin) + // This matches the working version from commit 41abd7a let relativePosition = targetPose - worldOrigin - let goalDisplayPosition = relativePosition + SIMD3(0, 0, goalForwardOffset) - - goalPointEntity?.position = goalDisplayPosition + goalPointEntity?.position = relativePosition worldOriginAnchor.addChild(goalPointEntity!) - print("Goal point visualization created:") + print("✅ Goal point visualization created:") print(" Target pose (world): \(targetPose)") print(" World origin: \(worldOrigin)") print(" Relative position: \(relativePosition)") - print(" Display position (with offset): \(goalDisplayPosition)") print(" Distance from origin: \(length(relativePosition))m") + + // Check current camera position for reference + let currentCamPos = getCurrentCameraPosition() + let distanceFromCamera = length(targetPose - currentCamPos) + print(" Distance from current camera: \(distanceFromCamera)m") } // MARK: - Anchor-based goal visualization From 0cbdc1223cd552d85c662a9748288c48b43451a4 Mon Sep 17 00:00:00 2001 From: KevinyWu Date: Wed, 29 Oct 2025 18:54:58 -0400 Subject: [PATCH 39/56] refactor depth to work on pro phones --- AnySense/Managers/ARViewContainer.swift | 180 ++++++++---------------- 1 file changed, 55 insertions(+), 125 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 67e67b1..08856ea 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -46,7 +46,10 @@ struct ARViewContainer: UIViewRepresentable { // Initialize the ARView let arView = ARView(frame: .zero, cameraMode: .ar, automaticallyConfigureSession: false) arView.session = session - arView.environment.sceneUnderstanding.options = [] // No extra scene understanding + // Expose real-world mesh as RealityKit entities and give them collision for raycasts + arView.environment.sceneUnderstanding.options = [.collision] + // COMMENT THIS OUT FOR PRODUCTION - shows mesh + // arView.debugOptions.insert(.showSceneUnderstanding) // Setup AR visualization with the created ARView arVisualizationManager.setupVisualization(with: arView) @@ -70,74 +73,71 @@ struct ARViewContainer: UIViewRepresentable { let parent: ARViewContainer init(_ parent: ARViewContainer) { self.parent = parent } + /// Raycast against Scene Understanding (LiDAR mesh) entities. + /// Returns the world-space point if the hit entity originates from real-world mesh data. + private func meshBackedHit(in arView: ARView, from location: CGPoint) -> SIMD3? { + guard let ray = arView.ray(through: location) else { return nil } + + // Raycast the RealityKit scene — includes scene-understanding entities created from LiDAR mesh + let hits = arView.scene.raycast(origin: ray.origin, direction: ray.direction) + + if let hit = hits.first(where: { $0.entity is HasSceneUnderstanding }) { + return hit.position + } + return nil + } + @objc func handleTap(_ recognizer: UITapGestureRecognizer) { guard recognizer.state == .ended, let arView = recognizer.view as? ARView else { return } let location = recognizer.location(in: arView) - - // Try depth-based unprojection first (for LiDAR devices) - if let (worldPoint, method) = parent.worldPointFromDepth(at: location, in: arView) { - print("📍 Tap at screen location: \(location)") - print(" Using \(method) method for 3D point: \(worldPoint)") - - // Show distance from camera - if let currentFrame = arView.session.currentFrame { - let camPos = simd_float3( - currentFrame.camera.transform.columns.3.x, - currentFrame.camera.transform.columns.3.y, - currentFrame.camera.transform.columns.3.z - ) - let distanceFromCam = length(worldPoint - camPos) - print(" Distance from camera: \(distanceFromCam)m") - } - - // Create anchor at the world point + + // 1) (arView.scene.raycast) Try LiDAR-backed mesh raycast first + if let world = meshBackedHit(in: arView, from: location) { var t = matrix_identity_float4x4 - t.columns.3 = SIMD4(worldPoint.x, worldPoint.y, worldPoint.z, 1) + t.columns.3 = SIMD4(world.x, world.y, world.z, 1) + let goalAnchor = ARAnchor(name: "goal", transform: t) arView.session.add(anchor: goalAnchor) - - // Notify ML pipeline with the world point + + print("Using LiDAR mesh raycast for 3D point: \(world)") + NotificationCenter.default.post( name: NSNotification.Name("ARViewTapForGoal"), object: nil, userInfo: [ - "worldPoint": worldPoint, - "method": method, + "worldPoint": world, + "method": "meshRaycast", "location": location, "bounds": arView.bounds ] ) return } - - // Only fallback to raycast on non-Pro devices (no LiDAR) - // On Pro devices with LiDAR, if depth fails, user can just tap again - if !parent.depthStatus.isDepthAvailable { - if let hit = arView.raycast(from: location, allowing: .estimatedPlane, alignment: .any).first { - let t = hit.worldTransform - let world = simd_float3(t.columns.3.x, t.columns.3.y, t.columns.3.z) - - // Create a native ARKit anchor at the hit (world-locked) - let goalAnchor = ARAnchor(name: "goal", transform: t) - arView.session.add(anchor: goalAnchor) - - print("Using raycast fallback for 3D point: \(world)") - - // Notify ML pipeline with the world point - NotificationCenter.default.post( - name: NSNotification.Name("ARViewTapForGoal"), - object: nil, - userInfo: [ - "worldPoint": world, - "method": "raycast", - "location": location, - "bounds": arView.bounds - ] - ) - return - } + + // 2) (arView.raycast) Fallback: ARKit plane/estimated-surface raycast + if let hit = arView.raycast(from: location, allowing: .estimatedPlane, alignment: .any).first { + let t = hit.worldTransform + let world = simd_float3(t.columns.3.x, t.columns.3.y, t.columns.3.z) + + let goalAnchor = ARAnchor(name: "goal", transform: t) + arView.session.add(anchor: goalAnchor) + + print("Using plane/estimated raycast fallback for 3D point: \(world)") + + NotificationCenter.default.post( + name: NSNotification.Name("ARViewTapForGoal"), + object: nil, + userInfo: [ + "worldPoint": world, + "method": "raycast", + "location": location, + "bounds": arView.bounds + ] + ) + return } - // Fallback: still notify with screen info (no hit yet) + + // 3) (no raycast) Final fallback: still notify with screen info (no hit yet) NotificationCenter.default.post( name: NSNotification.Name("ARViewTapForGoal"), object: nil, @@ -148,78 +148,6 @@ struct ARViewContainer: UIViewRepresentable { ) } } - - // MARK: - Depth-Based Point Calculation - private func worldPointFromDepth(at location: CGPoint, in arView: ARView) -> (point: simd_float3, method: String)? { - guard let frame = arView.session.currentFrame, - let depth = frame.sceneDepth?.depthMap else { - return nil - } - - let depthWidth = CVPixelBufferGetWidth(depth) - let depthHeight = CVPixelBufferGetHeight(depth) - let viewBounds = arView.bounds - - // 1. Normalize tap location to view coordinates - let normView = CGPoint( - x: location.x / viewBounds.width, - y: location.y / viewBounds.height - ) - - // 2. Apply display transform to get camera image coordinates - let ori = arView.window?.windowScene?.interfaceOrientation ?? .portrait - let disp = frame.displayTransform(for: ori, viewportSize: viewBounds.size) - let camNorm = normView.applying(disp.inverted()) - - // 3. Map to depth pixel coordinates - let u = Int(clamp(camNorm.x, 0, 1) * CGFloat(depthWidth)) - let v = Int(clamp(camNorm.y, 0, 1) * CGFloat(depthHeight)) - - // 4. Sample depth with median filtering for noise reduction - CVPixelBufferLockBaseAddress(depth, .readOnly) - defer { CVPixelBufferUnlockBaseAddress(depth, .readOnly) } - - let base = CVPixelBufferGetBaseAddress(depth)!.assumingMemoryBound(to: Float32.self) - let bytesPerRow = CVPixelBufferGetBytesPerRow(depth) / MemoryLayout.size - let N = 3 - var samples: [Float] = [] - - for j in max(0, v - N)...min(depthHeight - 1, v + N) { - for i in max(0, u - N)...min(depthWidth - 1, u + N) { - let d = base[j * bytesPerRow + i] - if d.isFinite, d > 0 { - samples.append(d) - } - } - } - - guard !samples.isEmpty else { - print("⚠️ Depth unprojection failed: no valid depth samples") - return nil - } - samples.sort() - let depthValue = samples[samples.count / 2] // median - - // 5. Unproject to camera coordinates using intrinsics - let K = frame.camera.intrinsics - let fx = K.columns.0.x, fy = K.columns.1.y - let cx = K.columns.2.x, cy = K.columns.2.y - - let xc = (Float(u) - cx) * depthValue / fx - let yc = (Float(v) - cy) * depthValue / fy - let zc = depthValue - - // 6. Transform to world coordinates - let pc = simd_float4(xc, yc, zc, 1) - let pw = simd_mul(frame.camera.transform, pc) - - return (simd_float3(pw.x, pw.y, pw.z), "depth") - } - - // MARK: - Helper Functions - private func clamp(_ value: T, _ minVal: T, _ maxVal: T) -> T { - return min(max(value, minVal), maxVal) - } } class DepthStatus: ObservableObject { @@ -479,7 +407,9 @@ class ARViewModel: ObservableObject{ depthStatus.setUnavailable() } configuration.planeDetection = [.horizontal, .vertical] - if ARWorldTrackingConfiguration.supportsSceneReconstruction(.mesh) { + if ARWorldTrackingConfiguration.supportsSceneReconstruction(.meshWithClassification) { + configuration.sceneReconstruction = .meshWithClassification + } else if ARWorldTrackingConfiguration.supportsSceneReconstruction(.mesh) { configuration.sceneReconstruction = .mesh } configuration.environmentTexturing = .none From adb8aff530c8b2b3e4bb315d49b241ec40e7ba35 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Wed, 5 Nov 2025 23:53:14 -0500 Subject: [PATCH 40/56] fixed inferencing and visualization to cube/goal hud-style layout --- AnySense.xcodeproj/project.pbxproj | 4 +- .../Managers/ARVisualizationManager.swift | 555 ++++++++++-------- AnySense/Managers/MLInferenceManager.swift | 140 +++-- AnySense/Views/readView.swift | 27 + 4 files changed, 442 insertions(+), 284 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 50ff99d..9b21b1e 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -541,7 +541,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = Krish.AnySenseTest; + PRODUCT_BUNDLE_IDENTIFIER = Kesu.AnySenseTest; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; @@ -586,7 +586,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = Krish.AnySenseTest; + PRODUCT_BUNDLE_IDENTIFIER = Kesu.AnySenseTest; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 8678fac..459ebeb 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -17,7 +17,21 @@ enum ActionState { } } -// MARK: - Visualization Frequency (Matching MLInferenceManager) +// MARK: - Target State +enum TargetState { + case active // Red target + case reached // Green target +} + +// MARK: - Fading Target +struct FadingTarget { + var entity: ModelEntity + var position: SIMD3 + var fadeStartTime: CFTimeInterval + var state: TargetState +} + +// MARK: - Visualization Frequency enum VisualizationFrequency: CaseIterable { case high, medium, low, minute @@ -51,47 +65,35 @@ class ARVisualizationManager: ObservableObject { // MARK: - Private Properties private var arView: ARView? private var worldOriginAnchor: AnchorEntity? - private var lastVisualizationTime: CFTimeInterval = 0 - - // Cube visualization entities - private var currentPoseCubeEntity: ModelEntity? - private var targetCubeEntity: ModelEntity? - private var targetCubeDisplayPosition: SIMD3? // Where target cube is displayed (with offset) - private var actualCameraPosition: SIMD3? // Actual camera position for proximity - private var targetCameraPosition: SIMD3? // Target camera position for proximity (without offset) - - // Proximity detection - private let proximityThreshold: Float = 0.15 // 15cm for "merged" state (increased for better detection) - - // Target/device pose state for point-conditioned flows private var targetPose: SIMD3? - private var actualDevicePose: SIMD3 = SIMD3(0, 0, 0) private var goalPointEntity: ModelEntity? - private var goalAnchorEntity: AnchorEntity? - - // Movement tracking private var worldOrigin: SIMD3 = SIMD3(0, 0, 0) - private var currentWorldPosition: SIMD3 = SIMD3(0, 0, 0) - private var previousWorldPosition: SIMD3? private var hasEstablishedOrigin: Bool = false - // Cube visual configuration - private let cubeSize: Float = 0.02 // 2cm cubes - private let currentCubeForwardOffset: Float = -0.010 // -1cm offset (out of screen, towards camera) - private let targetCubeForwardOffset: Float = 0.00 // No offset for target cube - - // Debug controls - var debugLoggingEnabled: Bool = true - - // Gripper state control - var isGripperClosed: Bool = false // When true, stops visualization - - // Virtual gripper setting - var useVirtualGripper: Bool = false // When true, uses gripper_overlay.png; when false, passes image to policy + var debugLoggingEnabled: Bool = false + var isGripperClosed: Bool = false + var useVirtualGripper: Bool = false + var applyEndOffset: Bool = true + var endOffsetMeters: Float = 0.02 + + // MARK: - Wireframe & Target Visualization + private var wireframeEntity: Entity? + private var wireframeAnchor: AnchorEntity? + private let wireframeSize: Float = 0.018 + private let wireframeOffsetMeters: Float = 0.04 + private var wireframeVisualPosition: SIMD3? + private var activeTargetEntity: ModelEntity? + private var activeTargetPosition: SIMD3? + private var fadingTargets: [FadingTarget] = [] + private var displayLink: CADisplayLink? + private let fadeDuration: CFTimeInterval = 0.1 + private let targetSize: Float = 0.012 + private var lastWireframeUpdateTime: CFTimeInterval = 0 + private let wireframeUpdateInterval: CFTimeInterval = 0.033 // MARK: - Initialization init() { - log("Initialized with cube-based visualization") + log("Initialized with wireframe seek-target visualization") } // MARK: - Logging Helper @@ -102,7 +104,44 @@ class ARVisualizationManager: ObservableObject { // MARK: - Setup Methods func setupVisualization(with arView: ARView) { self.arView = arView - log("Setup completed - using camera-relative directional arrows") + setupFadeAnimation() + log("Setup completed - using wireframe seek-target visualization") + } + + // MARK: - Fade Animation Setup + private func setupFadeAnimation() { + displayLink = CADisplayLink(target: self, selector: #selector(updateFadingTargets)) + displayLink?.preferredFrameRateRange = CAFrameRateRange(minimum: 20, maximum: 30, preferred: 30) + displayLink?.add(to: .main, forMode: .common) + } + + @objc private func updateFadingTargets() { + guard !fadingTargets.isEmpty else { return } + + let currentTime = CACurrentMediaTime() + var targetsToRemove: [Int] = [] + + for (index, fadingTarget) in fadingTargets.enumerated() { + let elapsed = currentTime - fadingTarget.fadeStartTime + let alpha = Float(max(0.0, 1.0 - elapsed / fadeDuration)) + + if alpha <= 0.05 { + fadingTarget.entity.removeFromParent() + targetsToRemove.append(index) + continue + } + + let greenMaterial = SimpleMaterial( + color: UIColor.systemGreen.withAlphaComponent(CGFloat(alpha)), + isMetallic: false + ) + fadingTarget.entity.model?.materials = [greenMaterial] + } + + // Remove completed fades (reverse order to maintain indices) + for index in targetsToRemove.reversed() { + fadingTargets.remove(at: index) + } } // MARK: - Recording Control Methods @@ -150,37 +189,25 @@ class ARVisualizationManager: ObservableObject { private func establishWorldOrigin() { guard let currentArView = arView else { return } - guard !hasEstablishedOrigin else { - print("World origin already established") - return - } + guard !hasEstablishedOrigin else { return } - // Set world origin at current camera position worldOrigin = getCurrentCameraPosition() - currentWorldPosition = SIMD3(0, 0, 0) // Start at origin - previousWorldPosition = nil hasEstablishedOrigin = true - // Create an anchor at the chosen world origin to host visualization entities var t = matrix_identity_float4x4 t.columns.3 = SIMD4(worldOrigin.x, worldOrigin.y, worldOrigin.z, 1) let anchor = AnchorEntity(world: t) currentArView.scene.addAnchor(anchor) worldOriginAnchor = anchor - print("World origin set at: \(worldOrigin) and anchor created") + print("World origin set at: \(worldOrigin)") } private func resetMovementTracking() { hasEstablishedOrigin = false worldOrigin = SIMD3(0, 0, 0) - currentWorldPosition = SIMD3(0, 0, 0) - previousWorldPosition = nil - - // Remove goal point visualization goalPointEntity?.removeFromParent() goalPointEntity = nil - worldOriginAnchor?.removeFromParent() worldOriginAnchor = nil } @@ -198,101 +225,226 @@ class ARVisualizationManager: ObservableObject { } private func clearAllVisualization() { - // Remove goal point visualization - goalPointEntity?.removeFromParent() - goalPointEntity = nil - - // Remove cube visualizations - currentPoseCubeEntity?.removeFromParent() - currentPoseCubeEntity = nil - - targetCubeEntity?.removeFromParent() - targetCubeEntity = nil - targetCubeDisplayPosition = nil - targetCameraPosition = nil - actualCameraPosition = nil + DispatchQueue.main.async { [weak self] in + guard let self = self else { return } + + self.wireframeEntity?.removeFromParent() + self.wireframeEntity = nil + self.wireframeAnchor?.removeFromParent() + self.wireframeAnchor = nil + self.wireframeVisualPosition = nil + self.activeTargetEntity?.removeFromParent() + self.activeTargetEntity = nil + self.activeTargetPosition = nil + + for fadingTarget in self.fadingTargets { + fadingTarget.entity.removeFromParent() + } + self.fadingTargets.removeAll() + } } // MARK: - Initialization helper func ensureVisualizationReady() { if !hasEstablishedOrigin { establishWorldOrigin() } if !isVisualizationEnabled { enableVisualization() } - if debugLoggingEnabled { - print("[Viz] ensureVisualizationReady → enabled=\(isVisualizationEnabled), origin=\(hasEstablishedOrigin)") + if targetPose != nil && goalPointEntity == nil && worldOriginAnchor != nil { + updateGoalPointVisualization() } } - // MARK: - Cube Management Methods - func updateCurrentPoseCube(position: SIMD3) { + // MARK: - Wireframe Management + func updateWireframe(cameraRelativePosition: SIMD3) { guard isVisualizationEnabled, !isGripperClosed else { return } + let currentTime = CACurrentMediaTime() + guard currentTime - lastWireframeUpdateTime >= wireframeUpdateInterval else { + wireframeVisualPosition = cameraRelativePosition + checkProximityAndUpdateState() + return + } + lastWireframeUpdateTime = currentTime + + wireframeVisualPosition = cameraRelativePosition + DispatchQueue.main.async { [weak self] in - guard let self = self, let worldOriginAnchor = self.worldOriginAnchor else { - if self?.debugLoggingEnabled == true { - print("[Viz] Cannot update current cube - anchor not ready") - } - return - } + guard let self = self, let arView = self.arView else { return } - // Create or update current pose cube - if self.currentPoseCubeEntity == nil { - let cubeMesh = MeshResource.generateBox(size: self.cubeSize) - let blueMaterial = SimpleMaterial(color: UIColor.systemBlue.withAlphaComponent(0.7), isMetallic: false) - self.currentPoseCubeEntity = ModelEntity(mesh: cubeMesh, materials: [blueMaterial]) - worldOriginAnchor.addChild(self.currentPoseCubeEntity!) - - if self.debugLoggingEnabled { - print("[Viz] Current pose cube created (blue, \(self.cubeSize)m)") - } + if self.wireframeAnchor == nil { + self.wireframeAnchor = AnchorEntity(.camera) + arView.scene.addAnchor(self.wireframeAnchor!) } - // Update position - self.currentPoseCubeEntity?.position = position + if self.wireframeEntity == nil { + self.wireframeEntity = self.createWireframeBox() + self.wireframeAnchor!.addChild(self.wireframeEntity!) + } - // Check proximity if we have a target cube - self.checkProximityAndUpdateState() + self.wireframeEntity?.position = SIMD3(0, 0, -self.wireframeOffsetMeters) + } + + checkProximityAndUpdateState() + } + + // MARK: - Wireframe Creation + private func createWireframeBox() -> Entity { + let wireframeGroup = Entity() + let edgeThickness: Float = 0.001 + let half = wireframeSize / 2.0 + + createWireframeEdge(from: SIMD3(-half, -half, -half), + to: SIMD3(half, -half, -half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(half, -half, -half), + to: SIMD3(half, half, -half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(half, half, -half), + to: SIMD3(-half, half, -half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(-half, half, -half), + to: SIMD3(-half, -half, -half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(-half, -half, half), + to: SIMD3(half, -half, half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(half, -half, half), + to: SIMD3(half, half, half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(half, half, half), + to: SIMD3(-half, half, half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(-half, half, half), + to: SIMD3(-half, -half, half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(-half, -half, -half), + to: SIMD3(-half, -half, half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(half, -half, -half), + to: SIMD3(half, -half, half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(-half, half, -half), + to: SIMD3(-half, half, half), + thickness: edgeThickness, + parent: wireframeGroup) + createWireframeEdge(from: SIMD3(half, half, -half), + to: SIMD3(half, half, half), + thickness: edgeThickness, + parent: wireframeGroup) + + return wireframeGroup + } + + private func createWireframeEdge(from: SIMD3, to: SIMD3, thickness: Float, parent: Entity) { + let direction = to - from + let edgeLength = length(direction) + guard edgeLength > 1e-6 else { return } + + let center = (from + to) / 2.0 + let targetDir = direction / edgeLength + let edgeMesh = MeshResource.generateBox(width: thickness, height: thickness, depth: edgeLength) + let blueMaterial = SimpleMaterial(color: UIColor.systemBlue.withAlphaComponent(0.9), isMetallic: false) + let edgeEntity = ModelEntity(mesh: edgeMesh, materials: [blueMaterial]) + edgeEntity.position = center + + let defaultDir = SIMD3(0, 0, 1) + let dotProduct = dot(defaultDir, targetDir) + + if abs(dotProduct) > 0.999 { + if dotProduct < 0 { + edgeEntity.orientation = simd_quatf(angle: .pi, axis: SIMD3(0, 1, 0)) + } + } else { + let axis = cross(defaultDir, targetDir) + let axisLength = length(axis) + if axisLength > 1e-6 { + let angle = acos(max(-1.0, min(1.0, dotProduct))) + edgeEntity.orientation = simd_quatf(angle: angle, axis: axis / axisLength) + } } + + parent.addChild(edgeEntity) } + private var lastLoggedDistance: Float = -1.0 private func checkProximityAndUpdateState() { guard !isGripperClosed, - let cameraPos = actualCameraPosition, - let targetPos = targetCameraPosition else { return } + let wireframePos = wireframeVisualPosition, + let targetPos = activeTargetPosition else { return } + + let targetHalf = targetSize / 2.0 + let wireframeHalf = wireframeSize / 2.0 - let distance = length(cameraPos - targetPos) + let targetMin = targetPos - SIMD3(targetHalf, targetHalf, targetHalf) + let targetMax = targetPos + SIMD3(targetHalf, targetHalf, targetHalf) + let wireframeMin = wireframePos - SIMD3(wireframeHalf, wireframeHalf, wireframeHalf) + let wireframeMax = wireframePos + SIMD3(wireframeHalf, wireframeHalf, wireframeHalf) - // Log only when close to threshold or when distance changes significantly - let distanceChanged = abs(distance - lastLoggedDistance) > 0.02 // 2cm change - let isClose = distance < proximityThreshold * 1.5 // Within 1.5x threshold - if debugLoggingEnabled && (distanceChanged || isClose) { - print("[Proximity] 📏 Distance: \(String(format: "%.4f", distance))m | Threshold: \(proximityThreshold)m | \(distance <= proximityThreshold ? "✅ WITHIN" : "⏳ Far")") - lastLoggedDistance = distance + let tolerance: Float = 0.001 + let isEnveloped = (targetMin.x >= wireframeMin.x - tolerance && targetMax.x <= wireframeMax.x + tolerance && + targetMin.y >= wireframeMin.y - tolerance && targetMax.y <= wireframeMax.y + tolerance && + targetMin.z >= wireframeMin.z - tolerance && targetMax.z <= wireframeMax.z + tolerance) + + if debugLoggingEnabled { + let distance = length(targetPos - wireframePos) + let distanceChanged = abs(distance - lastLoggedDistance) > 0.01 + if distanceChanged || isEnveloped { + print("[Proximity] Distance: \(String(format: "%.3f", distance))m | Enveloped: \(isEnveloped)") + lastLoggedDistance = distance + } } - if distance <= proximityThreshold { - // Camera reached target - signal inference trigger + if isEnveloped { if actionState != .reached { actionState = .reached - log("✅ Target reached - triggering inference (distance: \(String(format: "%.4f", distance))m)") - - // Notify observers that proximity was reached - NotificationCenter.default.post( - name: NSNotification.Name("ProximityReached"), - object: nil - ) + transitionTargetToFading() + NotificationCenter.default.post(name: NSNotification.Name("ProximityReached"), object: nil) } } else { if actionState != .waiting { actionState = .waiting - if debugLoggingEnabled { - log("⏳ State changed to waiting (distance: \(String(format: "%.4f", distance))m)") - } } } } + // MARK: - Target Transition + private func transitionTargetToFading() { + guard let activeEntity = activeTargetEntity, + let activePos = activeTargetPosition else { return } + + let greenMaterial = SimpleMaterial(color: UIColor.systemGreen.withAlphaComponent(1.0), isMetallic: false) + activeEntity.model?.materials = [greenMaterial] + + let fadingTarget = FadingTarget( + entity: activeEntity, + position: activePos, + fadeStartTime: CACurrentMediaTime(), + state: .reached + ) + fadingTargets.append(fadingTarget) + activeTargetEntity = nil + activeTargetPosition = nil + } + + // MARK: - Manual Trigger Support + func forceTargetTransition() { + activeTargetEntity?.removeFromParent() + activeTargetEntity = nil + activeTargetPosition = nil + actionState = .waiting + } + // MARK: - Frequency Control Methods func setVisualizationFrequency(_ frequency: VisualizationFrequency) { visualizationFrequency = frequency @@ -315,13 +467,25 @@ class ARVisualizationManager: ObservableObject { print("Gripper closed - hiding all visualization") DispatchQueue.main.async { [weak self] in - // Remove cubes - self?.currentPoseCubeEntity?.removeFromParent() - self?.targetCubeEntity?.removeFromParent() - self?.goalPointEntity?.removeFromParent() + guard let self = self else { return } + + // Remove wireframe + self.wireframeEntity?.removeFromParent() + self.wireframeEntity = nil + + // Remove active target + self.activeTargetEntity?.removeFromParent() + self.activeTargetEntity = nil + self.activeTargetPosition = nil + + // Remove fading targets + for fadingTarget in self.fadingTargets { + fadingTarget.entity.removeFromParent() + } + self.fadingTargets.removeAll() // Set action state to waiting - self?.actionState = .waiting + self.actionState = .waiting } } else if !isClosed && previousState { print("Gripper opened - visualization enabled") @@ -363,36 +527,16 @@ class ARVisualizationManager: ObservableObject { // MARK: - Device Pose Integration func updateActualDevicePose(from arFrame: ARFrame) { - let t = arFrame.camera.transform - actualDevicePose = SIMD3(t.columns.3.x, t.columns.3.y, t.columns.3.z) - - // Update current pose cube position every frame to track camera if isVisualizationEnabled && hasEstablishedOrigin { - let currentCameraPosition = SIMD3( - t.columns.3.x, - t.columns.3.y, - t.columns.3.z - ) - worldOrigin - - // Store actual camera position for proximity checking - actualCameraPosition = currentCameraPosition - - // Position blue cube with -5cm forward offset (Z direction only) - let cubePosition = currentCameraPosition + SIMD3(0, 0, currentCubeForwardOffset) - - updateCurrentPoseCube(position: cubePosition) + let t = arFrame.camera.transform + let currentCameraPosition = SIMD3(t.columns.3.x, t.columns.3.y, t.columns.3.z) - worldOrigin + let cameraWorldPosition = currentCameraPosition + SIMD3(0, 0, -wireframeOffsetMeters) + updateWireframe(cameraRelativePosition: cameraWorldPosition) } } func setTargetPose(_ worldPoint: SIMD3) { - print("🎯 setTargetPose called with world point: \(worldPoint)") - print(" hasEstablishedOrigin: \(hasEstablishedOrigin)") - print(" worldOrigin: \(worldOrigin)") - print(" isGripperClosed: \(isGripperClosed)") - print(" isVisualizationEnabled: \(isVisualizationEnabled)") - targetPose = worldPoint - // Ensure visualization is ready before creating goal point ensureVisualizationReady() updateGoalPointVisualization() } @@ -405,23 +549,9 @@ class ARVisualizationManager: ObservableObject { // MARK: - ML Integration Method func updatePoseFromMLOutput(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) { - guard isVisualizationEnabled else { return } - guard hasEstablishedOrigin else { - print("World origin not established - cannot track movement") - return - } - guard !isGripperClosed else { - if debugLoggingEnabled { - print("[Viz] Visualization stopped - gripper is closed") - } - return - } - guard jointActions.count >= 6 else { - print("Invalid joint actions array - need at least 6 values, got \(jointActions.count)") - return - } + guard isVisualizationEnabled && hasEstablishedOrigin && !isGripperClosed else { return } + guard jointActions.count >= 6 else { return } - // Interpret joint actions as movement deltas in CAMERA coordinates, then rotate into world frame let (cameraDeltaTranslation, _) = interpretMLDirections(jointActions, timestamp: timestamp) let cameraTransform = getCurrentCameraTransform() let rotationWorldFromCamera = simd_float3x3( @@ -432,83 +562,47 @@ class ARVisualizationManager: ObservableObject { ) ) let deltaTranslation = rotationWorldFromCamera * cameraDeltaTranslation - - if debugLoggingEnabled { - func fmt(_ f: Float) -> String { String(format: "%.3f", f) } - func fmt3(_ v: SIMD3) -> String { "(\(fmt(v.x)), \(fmt(v.y)), \(fmt(v.z)))" } - print("[Viz] Δcam \(fmt3(cameraDeltaTranslation)) → Δworld \(fmt3(deltaTranslation))") - } - - // Get current camera position relative to world origin - let currentCameraPosition = SIMD3( - cameraTransform.columns.3.x, - cameraTransform.columns.3.y, - cameraTransform.columns.3.z - ) - worldOrigin - - // Calculate target position from actual camera position + action delta - let targetCamPos = currentCameraPosition + deltaTranslation - - // Store target camera position for proximity checking - targetCameraPosition = targetCamPos - - // Apply -5cm offset to green target cube for display (Z direction only) - let targetCubePos = targetCamPos + SIMD3(0, 0, targetCubeForwardOffset) - - // Update target cube - updateTargetCube(position: targetCubePos) - - // Update tracking position - currentWorldPosition = currentCameraPosition + let currentCameraPosition = SIMD3(cameraTransform.columns.3.x, cameraTransform.columns.3.y, cameraTransform.columns.3.z) - worldOrigin + let targetPosition = currentCameraPosition + deltaTranslation + updateTarget(position: targetPosition) } private func interpretMLDirections(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) -> (translation: SIMD3, rotation: simd_quatf) { - // Map policy action → CAMERA frame (translation and Euler rotation) let action7 = Array(jointActions.prefix(7)) let mapped = ActionTransformUtils.policyToCameraEulerAction(action7, rotationUnit: .eulerXYZ) - let translationCamera = SIMD3(mapped[0], mapped[1], mapped[2]) + var translationCamera = SIMD3(mapped[0], mapped[1], mapped[2]) + + if applyEndOffset { + translationCamera += SIMD3(0, 0, -endOffsetMeters) + } + let rotationCamera = eulerToQuaternion(roll: mapped[3], pitch: mapped[4], yaw: mapped[5]) - - // Return CAMERA-frame delta; caller will rotate to WORLD frame using current camera pose return (translationCamera, rotationCamera) } func updateTargetCube(position: SIMD3) { - guard isVisualizationEnabled, !isGripperClosed else { - if debugLoggingEnabled { - print("[Viz] Cannot update target cube - visualization disabled or gripper closed") - } - return - } + updateTarget(position: position) + } + + // MARK: - Target Management + func updateTarget(position: SIMD3) { + guard isVisualizationEnabled, !isGripperClosed else { return } DispatchQueue.main.async { [weak self] in - guard let self = self, let worldOriginAnchor = self.worldOriginAnchor else { - if self?.debugLoggingEnabled == true { - print("[Viz] Cannot update target cube - anchor not ready") - } - return - } + guard let self = self, let worldOriginAnchor = self.worldOriginAnchor else { return } - // Create or update target cube - if self.targetCubeEntity == nil { - let cubeMesh = MeshResource.generateBox(size: self.cubeSize) - let greenMaterial = SimpleMaterial(color: UIColor.systemGreen.withAlphaComponent(0.9), isMetallic: false) - self.targetCubeEntity = ModelEntity(mesh: cubeMesh, materials: [greenMaterial]) - worldOriginAnchor.addChild(self.targetCubeEntity!) - - if self.debugLoggingEnabled { - print("[Viz] Target cube created (green, \(self.cubeSize)m)") - } + if self.activeTargetEntity == nil { + let targetMesh = MeshResource.generateBox(size: self.targetSize) + let redMaterial = SimpleMaterial(color: UIColor.systemRed.withAlphaComponent(1.0), isMetallic: false) + let newTarget = ModelEntity(mesh: targetMesh, materials: [redMaterial]) + worldOriginAnchor.addChild(newTarget) + self.activeTargetEntity = newTarget + self.actionState = .waiting + print("[Viz] ✅ New target created at (\(String(format: "%.3f", position.x)), \(String(format: "%.3f", position.y)), \(String(format: "%.3f", position.z)))") } - // Update position - self.targetCubeEntity?.position = position - self.targetCubeDisplayPosition = position - - if self.debugLoggingEnabled { - func fmt(_ f: Float) -> String { String(format: "%.3f", f) } - print("[Viz] Target cube updated: (\(fmt(position.x)), \(fmt(position.y)), \(fmt(position.z)))") - } + self.activeTargetEntity?.position = position + self.activeTargetPosition = position } } @@ -535,51 +629,24 @@ class ARVisualizationManager: ObservableObject { // MARK: - Goal Point Visualization private func updateGoalPointVisualization() { - guard !isGripperClosed, - let targetPose = targetPose, + guard let targetPose = targetPose, let worldOriginAnchor = worldOriginAnchor, hasEstablishedOrigin else { - print("❌ Cannot create goal visualization:") - print(" targetPose exists: \(targetPose != nil)") - print(" worldOriginAnchor exists: \(worldOriginAnchor != nil)") - print(" hasEstablishedOrigin: \(hasEstablishedOrigin)") - print(" isGripperClosed: \(isGripperClosed)") goalPointEntity?.removeFromParent() goalPointEntity = nil return } - // Remove existing goal point visualization goalPointEntity?.removeFromParent() goalPointEntity = nil - // Create a visible sphere - let sphereMesh = MeshResource.generateSphere(radius: 0.02) // 2cm radius for better visibility + let sphereMesh = MeshResource.generateSphere(radius: 0.02) let goalMaterial = SimpleMaterial(color: .systemRed, isMetallic: false) goalPointEntity = ModelEntity(mesh: sphereMesh, materials: [goalMaterial]) - // Position the sphere at the target pose (relative to world origin) - // This matches the working version from commit 41abd7a let relativePosition = targetPose - worldOrigin goalPointEntity?.position = relativePosition worldOriginAnchor.addChild(goalPointEntity!) - - print("✅ Goal point visualization created:") - print(" Target pose (world): \(targetPose)") - print(" World origin: \(worldOrigin)") - print(" Relative position: \(relativePosition)") - print(" Distance from origin: \(length(relativePosition))m") - - // Check current camera position for reference - let currentCamPos = getCurrentCameraPosition() - let distanceFromCamera = length(targetPose - currentCamPos) - print(" Distance from current camera: \(distanceFromCamera)m") - } - - // MARK: - Anchor-based goal visualization - func attachGoalAnchor(_ arAnchor: ARAnchor) { - if debugLoggingEnabled { - print("[Viz] attachGoalAnchor deprecated; use setTargetPose(world)") - } + print("✅ Goal point created at distance: \(length(relativePosition))m") } } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 59ca650..7261079 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -275,44 +275,28 @@ class MLInferenceManager: ObservableObject { guard shouldShowGripperOverlay() else { return image } - - // Fallback to Core Image if vImage buffer not available - guard let _ = gripperOverlayBuffer else { - return applyGripperOverlayCoreImage(to: image) - } - - // For now, use Core Image fallback while we implement vImage compositing - // The main performance improvement will come from avoiding the overlay entirely when not needed - return applyGripperOverlayCoreImage(to: image) - } - - private func applyGripperOverlayCoreImage(to image: CIImage) -> CIImage { + guard let gripperOverlay = getCurrentGripperOverlay() else { return image } + + return applyGripperOverlayCoreImage(to: image, overlay: gripperOverlay) + } - // Scale gripper overlay to match model input size + private func applyGripperOverlayCoreImage(to image: CIImage, overlay gripperOverlay: CIImage) -> CIImage { let imageSize = image.extent.size let overlaySize = gripperOverlay.extent.size - let scaleX = imageSize.width / overlaySize.width let scaleY = imageSize.height / overlaySize.height - let scale = min(scaleX, scaleY) // Maintain aspect ratio - + let scale = min(scaleX, scaleY) let scaledOverlay = gripperOverlay.transformed(by: CGAffineTransform(scaleX: scale, y: scale)) - - // Position gripper at bottom with no offset (0,0 positioning) - let positionedOverlay = scaledOverlay - - // Composite using source-over to preserve alpha transparency + guard let compositeFilter = CIFilter(name: "CISourceOverCompositing") else { - print("Warning: Could not create composite filter") return image } - - compositeFilter.setValue(positionedOverlay, forKey: kCIInputImageKey) + + compositeFilter.setValue(scaledOverlay, forKey: kCIInputImageKey) compositeFilter.setValue(image, forKey: kCIInputBackgroundImageKey) - return compositeFilter.outputImage ?? image } @@ -459,8 +443,8 @@ class MLInferenceManager: ObservableObject { // camera: x right, y up, z back // labels: x left, y forward, z down // Mapping: x = -x_cam, y = -z_cam, z = -y_cam - // We add 0.05 to the z coordinate since training data is shifted forward a bit. - return [-p_c4.x, -p_c4.z + 0.05, -p_c4.y] + // We add 0.02 to the y coordinate since training data is shifted forward a bit. + return [-p_c4.x, -p_c4.z + 0.02, -p_c4.y] } // If model expects 2D goals, return nil since we only support 3D goals now return nil @@ -1039,9 +1023,8 @@ class MLInferenceManager: ObservableObject { return try convertPixelBufferToMLMultiArray(outputBuffer, width: width, height: height) } - // MARK: - Unified Pixel Buffer to MLMultiArray Conversion + // MARK: - Unified Pixel Buffer to MLMultiArray Conversion (Accelerate Optimized) private func convertPixelBufferToMLMultiArray(_ pixelBuffer: CVPixelBuffer, width: Int, height: Int) throws -> MLMultiArray { - // Always produce [1,3,H,W] for consistent buffering let inputArray = try MLMultiArray(shape: [1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { @@ -1050,18 +1033,21 @@ class MLInferenceManager: ObservableObject { let buffer = baseAddress.assumingMemoryBound(to: UInt8.self) let bytesPerRow = CVPixelBufferGetBytesPerRow(pixelBuffer) - let bytesPerPixel = 4 + let totalPixels = width * height + + let rPtr = inputArray.dataPointer.assumingMemoryBound(to: Float.self) + let gPtr = rPtr.advanced(by: totalPixels) + let bPtr = gPtr.advanced(by: totalPixels) + var pixelIndex = 0 for y in 0..= maxBufferSize else { + print("[MLInference] Cannot trigger manually - buffer incomplete (\(frameBuffer.count)/\(maxBufferSize)) or inference disabled") + return + } + + // Check if goal point is required but not set + if metadata.requiresGoalPoint && currentGoalPoint == nil { + print("[MLInference] Cannot trigger manually - goal point required but not set") + return + } + + // Ensure we have a model loaded + guard let model = model else { + print("[MLInference] Cannot trigger manually - no model loaded") + return + } + + // Skip if inference already pending + guard !isInferencePending else { + print("[MLInference] Cannot trigger manually - inference already pending") + return + } + + // Mark inference as pending + isInferencePending = true + + print("[MLInference] Manual trigger - running inference with buffered frames (\(frameBuffer.count))") + + // Prepare input using buffered frames + let modelInput: MLFeatureProvider + do { + modelInput = try prepareModelInputFromBuffer(metadata: metadata) + } catch { + print("ERROR: Failed to prepare model input for manual trigger: \(error)") + isInferencePending = false + return + } + + inferenceQueue.async { [weak self, modelInput, model] in + guard let self = self else { return } + + let startTime = CACurrentMediaTime() + + autoreleasepool { + do { + print("DEBUG: Running manual model prediction with buffered frames...") + let output = try model.prediction(from: modelInput) + print("DEBUG: Manual model prediction succeeded") + + let inferenceTime = CACurrentMediaTime() - startTime + self.processInferenceResults(output, inferenceTime: inferenceTime) + + // Reset pending flag and mark first inference complete + DispatchQueue.main.async { + self.isInferencePending = false + if !self.hasRunFirstInference { + self.hasRunFirstInference = true + print("[MLInference] First inference complete (manual) - target cube should now be visible") + } else { + // For manual triggers after first inference, transition current target to fading + // This allows the new target to appear immediately + self.arVisualizationManager?.forceTargetTransition() + } + } + } catch { + print("ERROR: Manual model inference failed: \(error)") + DispatchQueue.main.async { + self.isInferencePending = false + } + } + } + } + } + func setInferenceFrequency(_ frequency: InferenceFrequency) { inferenceFrequency = frequency print("Inference frequency: \(frequency.displayName)") diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 27207ee..0adcd2f 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -60,6 +60,33 @@ struct ReadView : View{ .scaledToFit() .allowsHitTesting(false) } + + // Manual Next Action Button + if let mlManager = arViewModel.mlManager, + appStatus.mlInferenceEnabled && mlManager.isInferenceEnabled { + VStack { + HStack { + Spacer() + Button(action: { + mlManager.triggerInferenceManually() + UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() + }) { + Image(systemName: "arrow.forward.circle.fill") + .font(.title2) + .foregroundColor(.white) + .background( + Circle() + .fill(Color.blue.opacity(0.8)) + .frame(width: 44, height: 44) + ) + .shadow(color: .black.opacity(0.3), radius: 4, x: 0, y: 2) + } + .padding(.trailing, 12) + .padding(.top, 12) + } + Spacer() + } + } } .frame(width: arViewWidth, height: arViewHeight) .padding(.bottom, arViewPadding) From c2ca9cb88b57c294a1b3d8e16a7446db1a460523 Mon Sep 17 00:00:00 2001 From: Krish Mehta Date: Tue, 11 Nov 2025 20:35:33 -0500 Subject: [PATCH 41/56] fixed gripper overlay --- AnySense.xcodeproj/project.pbxproj | 4 +- AnySense/Managers/MLInferenceManager.swift | 431 +++++++-------------- 2 files changed, 150 insertions(+), 285 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 9b21b1e..b40930c 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -541,7 +541,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = Kesu.AnySenseTest; + PRODUCT_BUNDLE_IDENTIFIER = "Kesu-mehta.AnySenseTest"; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; @@ -586,7 +586,7 @@ "@executable_path/Frameworks", ); MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = Kesu.AnySenseTest; + PRODUCT_BUNDLE_IDENTIFIER = "Kesu-mehta.AnySenseTest"; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 7261079..1748bf2 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -57,7 +57,10 @@ class MLInferenceManager: ObservableObject { let goalPoint: [Float]? // Goal at time of capture } private var frameBuffer: [FrameBufferEntry] = [] - private var maxBufferSize: Int = 3 // Always maintain 3 frames for rolling buffer + private var maxBufferSize: Int = 3 // Always maintain 3 action trigger frames + + // Current frame processing (still processes every frame for potential storage) + private var currentFrameEntry: FrameBufferEntry? // MARK: - Proximity-based Inference Control private var proximityReached: Bool = false @@ -87,7 +90,7 @@ class MLInferenceManager: ObservableObject { @Published var enableGripperOverlay: Bool = true // Default enabled (for model input) @Published var showGripperOverlayOnScreen: Bool = true // Show overlay on AR view @Published var currentGripperOverlayImage: UIImage? // Current overlay image for display - @Published var saveDebugFrames: Bool = false // For testing + @Published var saveDebugFrames: Bool = true // For testing // MARK: - Inference Settings enum InferenceFrequency: CaseIterable { @@ -162,7 +165,10 @@ class MLInferenceManager: ObservableObject { if let openImage = UIImage(named: "gripper_overlay") { gripperOpenCIImage = CIImage(image: openImage) gripperOpenUIImage = openImage - print("Open gripper overlay loaded: \(gripperOpenCIImage?.extent ?? .zero)") + print("Open gripper overlay loaded:") + print(" - Size: \(openImage.size)") + print(" - Scale: \(openImage.scale)") + print(" - CIImage extent: \(gripperOpenCIImage?.extent ?? .zero)") } else { print("Warning: Could not load gripper_overlay (open) image from assets") } @@ -171,7 +177,10 @@ class MLInferenceManager: ObservableObject { if let closedImage = UIImage(named: "gripper_closed") { gripperClosedCIImage = CIImage(image: closedImage) gripperClosedUIImage = closedImage - print("Closed gripper overlay loaded: \(gripperClosedCIImage?.extent ?? .zero)") + print("Closed gripper overlay loaded:") + print(" - Size: \(closedImage.size)") + print(" - Scale: \(closedImage.scale)") + print(" - CIImage extent: \(gripperClosedCIImage?.extent ?? .zero)") } else { print("Warning: Could not load gripper_closed image from assets") } @@ -189,7 +198,7 @@ class MLInferenceManager: ObservableObject { @MainActor private func updateGripperOverlayDisplay() { - guard showGripperOverlayOnScreen && !isUSBStreamingActive else { + guard shouldApplyGripperOverlay() else { currentGripperOverlayImage = nil return } @@ -247,13 +256,15 @@ class MLInferenceManager: ObservableObject { func setUSBStreamingState(isActive: Bool) { isUSBStreamingActive = isActive - print("USB streaming state: \(isActive ? "ON" : "OFF") - Gripper overlay: \(shouldShowGripperOverlay() ? "ENABLED" : "DISABLED")") + print("USB streaming state: \(isActive ? "ON" : "OFF") - Gripper overlay: \(shouldApplyGripperOverlay() ? "ENABLED" : "DISABLED")") Task { @MainActor in updateGripperOverlayDisplay() } } - private func shouldShowGripperOverlay() -> Bool { + private func shouldApplyGripperOverlay() -> Bool { + // Use gripper overlay when USB streaming is OFF (virtual gripper proxy) + // Disable when USB streaming is ON (robot has real gripper) return enableGripperOverlay && !isUSBStreamingActive } @@ -272,32 +283,77 @@ class MLInferenceManager: ObservableObject { } private func applyGripperOverlay(to image: CIImage) -> CIImage { - guard shouldShowGripperOverlay() else { + guard shouldApplyGripperOverlay() else { + if saveDebugFrames { + print("DEBUG: Gripper overlay skipped - enableGripperOverlay: \(enableGripperOverlay), isUSBStreaming: \(isUSBStreamingActive)") + } return image } - + guard let gripperOverlay = getCurrentGripperOverlay() else { + if saveDebugFrames { + print("DEBUG: No gripper overlay image available - openCIImage: \(gripperOpenCIImage != nil), closedCIImage: \(gripperClosedCIImage != nil)") + } return image } - + + if saveDebugFrames { + print("DEBUG: Applying gripper overlay - value: \(String(format: "%.3f", currentGripperValue))") + } return applyGripperOverlayCoreImage(to: image, overlay: gripperOverlay) } private func applyGripperOverlayCoreImage(to image: CIImage, overlay gripperOverlay: CIImage) -> CIImage { let imageSize = image.extent.size - let overlaySize = gripperOverlay.extent.size - let scaleX = imageSize.width / overlaySize.width - let scaleY = imageSize.height / overlaySize.height - let scale = min(scaleX, scaleY) - let scaledOverlay = gripperOverlay.transformed(by: CGAffineTransform(scaleX: scale, y: scale)) - + + if saveDebugFrames { + print("DEBUG: Starting composite - image: \(imageSize)") + print("DEBUG: Original overlay extent: \(gripperOverlay.extent)") + } + + // Apply same transformations as camera frames: scale to fit, then rotate if needed + let scale = min(imageSize.width / gripperOverlay.extent.width, imageSize.height / gripperOverlay.extent.height) + var transformedOverlay = gripperOverlay.transformed(by: CGAffineTransform(scaleX: scale, y: scale)) + + // Apply same orientation as camera frames + if applyServerImageOrientation { + transformedOverlay = transformedOverlay.oriented(.down) + } + + // Additional +90 degree rotation to align gripper direction with viewpoint + transformedOverlay = transformedOverlay.transformed(by: CGAffineTransform(rotationAngle: CGFloat.pi / 2)) + + // After rotation, translate back to origin for proper overlay positioning + let rotatedExtent = transformedOverlay.extent + transformedOverlay = transformedOverlay.transformed(by: CGAffineTransform(translationX: -rotatedExtent.origin.x, y: -rotatedExtent.origin.y)) + + if saveDebugFrames { + print("DEBUG: Scale: \(String(format: "%.3f", scale))") + print("DEBUG: Server orientation: \(applyServerImageOrientation)") + print("DEBUG: Final overlay extent: \(transformedOverlay.extent)") + } + guard let compositeFilter = CIFilter(name: "CISourceOverCompositing") else { + if saveDebugFrames { + print("DEBUG: Failed to create CISourceOverCompositing filter") + } return image } - - compositeFilter.setValue(scaledOverlay, forKey: kCIInputImageKey) + + compositeFilter.setValue(transformedOverlay, forKey: kCIInputImageKey) compositeFilter.setValue(image, forKey: kCIInputBackgroundImageKey) - return compositeFilter.outputImage ?? image + + if let result = compositeFilter.outputImage { + if saveDebugFrames { + print("DEBUG: Composite successful, result extent: \(result.extent)") + } + return result + } else { + if saveDebugFrames { + print("DEBUG: Composite filter returned nil") + } + return image + } } // MARK: - Debug Frame Saving @@ -484,46 +540,54 @@ class MLInferenceManager: ObservableObject { func performInference(on pixelBuffer: CVPixelBuffer, timestamp: CFTimeInterval = CACurrentMediaTime()) { guard isInferenceEnabled, - let metadata = modelMetadata else { - return + let metadata = modelMetadata else { + return } - + // Check if goal point is required but not set if metadata.requiresGoalPoint && currentGoalPoint == nil { return // Skip until goal point is set } - - // ALWAYS buffer frames (rolling 3-frame buffer) + + // Process current frame for potential action storage do { - let processedFrame = try processFrame(pixelBuffer, targetSize: CGSize(width: 224, height: 224), debugPrefix: "buffered") + let processedFrame = try processFrame(pixelBuffer, targetSize: CGSize(width: 224, height: 224), debugPrefix: "current") let goalPointArray = metadata.requiresGoalPoint ? getGoalPointForModel() : nil - let bufferEntry = FrameBufferEntry(mlArray: processedFrame, goalPoint: goalPointArray) - - frameBuffer.append(bufferEntry) - - // Maintain rolling buffer of 3 frames - if frameBuffer.count > maxBufferSize { - frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) - } + currentFrameEntry = FrameBufferEntry(mlArray: processedFrame, goalPoint: goalPointArray) } catch { - print("ERROR: Failed to buffer frame: \(error)") + print("ERROR: Failed to process current frame: \(error)") return } - - // Run inference if: - // 1. This is the first inference (to create initial target cube), OR - // 2. Proximity is reached AND we haven't just run inference - let isFirstInference = !hasRunFirstInference && frameBuffer.count >= maxBufferSize + + // Trigger inference: first time or proximity reached + let isFirstInference = !hasRunFirstInference let isProximityTriggered = proximityReached && !isInferencePending let shouldRunInference = isFirstInference || isProximityTriggered - - if debugLoggingEnabled && frameBuffer.count == maxBufferSize && !shouldRunInference { - print("[MLInference] Buffer full (\(frameBuffer.count)) but not triggering: firstInference=\(hasRunFirstInference), proximity=\(proximityReached), pending=\(isInferencePending)") + + if debugLoggingEnabled && !shouldRunInference { + print("[MLInference] Not triggering: firstInference=\(hasRunFirstInference), proximity=\(proximityReached), pending=\(isInferencePending)") } - + guard shouldRunInference else { return } + + // Store current frame as an action trigger frame + guard let currentEntry = currentFrameEntry else { + print("ERROR: No current frame entry available for action trigger") + return + } + + frameBuffer.append(currentEntry) + + // Maintain buffer of last 3 action trigger frames + if frameBuffer.count > maxBufferSize { + frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) + } + + print("[MLInference] Action frame stored - buffer now contains \(frameBuffer.count) action trigger frames") + + // Temporal models pad with repeated frames if needed // Ensure we have a model loaded guard let model = model else { @@ -581,14 +645,14 @@ class MLInferenceManager: ObservableObject { } } - // MARK: - Dynamic Input Preparation + // MARK: - Action Frame Buffer Input Preparation private func prepareModelInputFromBuffer(metadata: ModelMetadata) throws -> MLFeatureProvider { - print("DEBUG: Preparing input from buffer for \(metadata.modelType.displayName) model") - + print("DEBUG: Preparing input from action frame buffer for \(metadata.modelType.displayName) model") + guard !frameBuffer.isEmpty else { - throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Frame buffer is empty"]) + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "No action frames stored yet"]) } - + switch metadata.modelType { case .pointConditioned: return try prepareVQBeTInputFromBuffer(metadata: metadata) @@ -597,222 +661,7 @@ class MLInferenceManager: ObservableObject { } } - private func prepareModelInput(_ pixelBuffer: CVPixelBuffer, metadata: ModelMetadata) throws -> MLFeatureProvider { - print("DEBUG: Preparing input for \(metadata.modelType.displayName) model") - switch metadata.modelType { - case .pointConditioned: - return try prepareVQBeTInput(pixelBuffer, metadata: metadata) - case .standard: - return try prepareLegacyInput(pixelBuffer, metadata: metadata) - } - } - - private func prepareVQBeTInput(_ pixelBuffer: CVPixelBuffer, metadata: ModelMetadata) throws -> MLFeatureProvider { - guard let goalPointArray = getGoalPointForModel() else { - throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Goal point required for point-conditioned model"]) - } - - // Get input names from metadata - let imageInputName = metadata.getImageInputName() ?? "camera_image" - let goalInputName = metadata.getGoalInputName() ?? "goal_point" - - // Process current frame and add to buffer - let processedFrame = try processFrame(pixelBuffer, targetSize: CGSize(width: 224, height: 224), debugPrefix: "point_conditioned") - let bufferEntry = FrameBufferEntry(mlArray: processedFrame, goalPoint: goalPointArray) - frameBuffer.append(bufferEntry) - - // Trim buffer to maxBufferSize - if frameBuffer.count > maxBufferSize { - frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) - } - - let temporalFrames = metadata.temporalFrames - - // Determine expected rank from model - let expectedRank: Int = { - if let d = model?.modelDescription.inputDescriptionsByName[imageInputName], - d.type == .multiArray, - let shape = d.multiArrayConstraint?.shape { - return shape.count - } - return 4 - }() - - print("DEBUG: Point-conditioned model - temporalFrames: \(temporalFrames), expectedRank: \(expectedRank), bufferSize: \(frameBuffer.count)") - - // Build image array based on temporal requirements - let imageArray: MLMultiArray - if temporalFrames > 1 { - // Temporal model: stack frames into [1,T,3,H,W] - let framesToUse = min(temporalFrames, frameBuffer.count) - let paddingNeeded = temporalFrames - framesToUse - - imageArray = try MLMultiArray(shape: [1, NSNumber(value: temporalFrames), 3, 224, 224], dataType: .float32) - - // Pad with repeated first frame if needed - for t in 0.. 1 && dims[2] == 3 { - let arr = try? MLMultiArray(shape: shape, dataType: .float32) - if let arr = arr { - let framesToUse = min(dims[1], frameBuffer.count) - let paddingNeeded = dims[1] - framesToUse - - // Pad with repeated first goal if needed - for t in 0.. MLFeatureProvider { - print("DEBUG: prepareLegacyInput called") - - // Process frame using unified method - let processedFrame = try processFrame(pixelBuffer, targetSize: modelInputSize, debugPrefix: "standard") - print("DEBUG: Frame processed, shape: \(processedFrame.shape)") - - // For legacy models, determine if we need to add temporal dimension [1,1,3,H,W] - let inputName = metadata.getImageInputName() ?? "x_1" - let inputArray: MLMultiArray - - if let d = model?.modelDescription.inputDescriptionsByName[inputName], - d.type == .multiArray, - let shape = d.multiArrayConstraint?.shape { - print("DEBUG: Model expects shape: \(shape), rank: \(shape.count)") - - if shape.count == 5 { - // Model expects 5D [1,1,3,H,W] - let height = Int(modelInputSize.height) - let width = Int(modelInputSize.width) - inputArray = try MLMultiArray(shape: [1, 1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) - - print("DEBUG: Converting [1,3,H,W] to [1,1,3,H,W]") - - // Copy from [1,3,H,W] to [1,1,3,H,W] - for c in 0..<3 { - for h in 0.. MLFeatureProvider { let goalPointArray = frameBuffer.last?.goalPoint ?? getGoalPointForModel() guard let goalPointArray = goalPointArray else { @@ -833,30 +682,35 @@ class MLInferenceManager: ObservableObject { return 4 }() - print("DEBUG: Using buffered frames - temporalFrames: \(temporalFrames), bufferSize: \(frameBuffer.count)") - + print("DEBUG: Using buffered action frames - temporalFrames: \(temporalFrames), actionFramesAvailable: \(frameBuffer.count)") + // Build image array from buffer let imageArray: MLMultiArray if temporalFrames > 1 { - // Temporal model: use last N frames from buffer + // Temporal model: use available action frames, pad with repetition if needed let framesToUse = min(temporalFrames, frameBuffer.count) - let paddingNeeded = temporalFrames - framesToUse - + let paddingNeeded = max(0, temporalFrames - framesToUse) + imageArray = try MLMultiArray(shape: [1, NSNumber(value: temporalFrames), 3, 224, 224], dataType: .float32) - - // Pad with repeated first frame if needed + + guard frameBuffer.count > 0 else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "No action frames available"]) + } + + // Pad with repeated first action frame if needed if paddingNeeded > 0 { - let srcFrame = frameBuffer[0].mlArray + let firstActionFrame = frameBuffer[0].mlArray for t in 0..= maxBufferSize else { - print("[MLInference] Cannot trigger manually - buffer incomplete (\(frameBuffer.count)/\(maxBufferSize)) or inference disabled") + let metadata = modelMetadata else { + print("[MLInference] Cannot trigger manually - inference disabled or no model") return } @@ -1249,10 +1101,23 @@ class MLInferenceManager: ObservableObject { return } + // Store current frame as action trigger frame + guard let currentEntry = currentFrameEntry else { + print("[MLInference] Cannot trigger manually - no current frame available") + return + } + + frameBuffer.append(currentEntry) + + // Maintain buffer of last 3 action trigger frames + if frameBuffer.count > maxBufferSize { + frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) + } + // Mark inference as pending isInferencePending = true - - print("[MLInference] Manual trigger - running inference with buffered frames (\(frameBuffer.count))") + + print("[MLInference] Manual trigger - action frame stored, running inference with buffered action frames (\(frameBuffer.count))") // Prepare input using buffered frames let modelInput: MLFeatureProvider From 961bb824da6c686809ad45d21963ae173a518fe1 Mon Sep 17 00:00:00 2001 From: DjKesu Date: Tue, 18 Nov 2025 14:32:17 -0500 Subject: [PATCH 42/56] fixes and app launch beta --- AnySense.xcodeproj/project.pbxproj | 12 +-- AnySense/Managers/ARViewContainer.swift | 76 +++++++++++++------ .../Managers/ARVisualizationManager.swift | 31 ++++---- AnySense/Managers/MLInferenceManager.swift | 2 +- AnySense/Views/readView.swift | 19 ++++- 5 files changed, 87 insertions(+), 53 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index b40930c..1d8cdcf 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -518,7 +518,7 @@ CODE_SIGN_STYLE = Automatic; CURRENT_PROJECT_VERSION = 4; DEVELOPMENT_ASSET_PATHS = ""; - DEVELOPMENT_TEAM = 57DF45Y5K2; + DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; ENABLE_USER_SCRIPT_SANDBOXING = NO; EXCLUDED_ARCHS = ""; @@ -540,8 +540,8 @@ "$(inherited)", "@executable_path/Frameworks", ); - MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = "Kesu-mehta.AnySenseTest"; + MARKETING_VERSION = 1.3; + PRODUCT_BUNDLE_IDENTIFIER = GRAIL.AnySense; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; @@ -564,7 +564,7 @@ CODE_SIGN_STYLE = Automatic; CURRENT_PROJECT_VERSION = 4; DEVELOPMENT_ASSET_PATHS = ""; - DEVELOPMENT_TEAM = 57DF45Y5K2; + DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; ENABLE_USER_SCRIPT_SANDBOXING = NO; GENERATE_INFOPLIST_FILE = YES; @@ -585,8 +585,8 @@ "$(inherited)", "@executable_path/Frameworks", ); - MARKETING_VERSION = 1.0; - PRODUCT_BUNDLE_IDENTIFIER = "Kesu-mehta.AnySenseTest"; + MARKETING_VERSION = 1.3; + PRODUCT_BUNDLE_IDENTIFIER = GRAIL.AnySense; PRODUCT_NAME = "$(TARGET_NAME)"; PROVISIONING_PROFILE_SPECIFIER = ""; SUPPORTED_PLATFORMS = "iphoneos iphonesimulator"; diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 08856ea..cacaf40 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -23,8 +23,8 @@ struct RecordingFiles { let rgbFileName: URL let depthFileName: URL let timestamp: String - let rgbImagesDirectory: URL - let depthImagesDirectory: URL + let rgbImagesDirectory: URL? + let depthImagesDirectory: URL? let poseFile: URL let generalDataDirectory: String let tactileFile: URL @@ -214,8 +214,8 @@ class ARViewModel: ObservableObject{ private var poseFileHandle: FileHandle? // Control the destination of rgb images directory and depth images directory - private var rgbDirect: URL = URL(fileURLWithPath: "") - private var depthDirect: URL = URL(fileURLWithPath: "") + private var rgbDirect: URL? = nil + private var depthDirect: URL? = nil // Control the destination of pose data text file private var poseURL: URL = URL(fileURLWithPath: "") private var generalURL: URL = URL(fileURLWithPath: "") @@ -762,31 +762,52 @@ class ARViewModel: ObservableObject{ dateFormatter.dateFormat = "yyyy-MM-dd-HH_mm_ss" let timestamp = dateFormatter.string(from: Date()) - let fileNames = [ + var fileNames = [ "RGB": "RGB_\(timestamp).mp4", "Depth": "Depth_\(timestamp).mp4", "Pose": "AR_Pose_\(timestamp).txt", - "Tactile": "Tactile_\(timestamp).bin", - "RGBImages": "RGB_Images_\(timestamp)", - "DepthImages": isColorMapOpened ? "Depth_Colored_Images_\(timestamp)" : "Depth_Images_\(timestamp)" + "Tactile": "Tactile_\(timestamp).bin" ] + + // Only include image directories if debug frame saving is enabled + if mlManager?.saveDebugFrames == true { + fileNames["RGBImages"] = "RGB_Images_\(timestamp)" + fileNames["DepthImages"] = isColorMapOpened ? "Depth_Colored_Images_\(timestamp)" : "Depth_Images_\(timestamp)" + } guard let documentsURL = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask).first else { return nil } let generalDataDirectory = documentsURL.appendingPathComponent(timestamp) - let rgbVideoURL = generalDataDirectory.appendingPathComponent(fileNames["RGB"]!) - let depthVideoURL = generalDataDirectory.appendingPathComponent(fileNames["Depth"]!) - let poseTextURL = generalDataDirectory.appendingPathComponent(fileNames["Pose"]!) - let tactileFileURL = generalDataDirectory.appendingPathComponent(fileNames["Tactile"]!) - let rgbImagesDirectory = generalDataDirectory.appendingPathComponent(fileNames["RGBImages"]!) - let depthImagesDirectory = generalDataDirectory.appendingPathComponent(fileNames["DepthImages"]!) - + + guard let rgbFileName = fileNames["RGB"], + let depthFileName = fileNames["Depth"], + let poseFileName = fileNames["Pose"], + let tactileFileName = fileNames["Tactile"] else { + return nil + } + + let rgbVideoURL = generalDataDirectory.appendingPathComponent(rgbFileName) + let depthVideoURL = generalDataDirectory.appendingPathComponent(depthFileName) + let poseTextURL = generalDataDirectory.appendingPathComponent(poseFileName) + let tactileFileURL = generalDataDirectory.appendingPathComponent(tactileFileName) + + // Only create image directories if debug frame saving is enabled + var rgbImagesDirectory: URL? + var depthImagesDirectory: URL? + if mlManager?.saveDebugFrames == true, + let rgbDirName = fileNames["RGBImages"], + let depthDirName = fileNames["DepthImages"] { + rgbImagesDirectory = generalDataDirectory.appendingPathComponent(rgbDirName) + depthImagesDirectory = generalDataDirectory.appendingPathComponent(depthDirName) + } + do { try FileManager.default.createDirectory(at: generalDataDirectory, withIntermediateDirectories: true) - if self.depthStatus.isDepthAvailable { - try FileManager.default.createDirectory(at: depthImagesDirectory, withIntermediateDirectories: true) + if mlManager?.saveDebugFrames == true && self.depthStatus.isDepthAvailable, + let depthDir = depthImagesDirectory { + try FileManager.default.createDirectory(at: depthDir, withIntermediateDirectories: true) } try createFile(fileURL: poseTextURL) } catch { @@ -1114,12 +1135,14 @@ class ARViewModel: ObservableObject{ let dataSize = width * height * MemoryLayout.size let data = Data(bytes: floatBuffer, count: dataSize) - // Save binary data to a file - let fileURL = self.depthDirect.appendingPathComponent("\(Int64(Date().timeIntervalSince1970*1000)).bin") - do { - try data.write(to: fileURL) - } catch { - // Error saving binary file - continue capture + // Save binary data to a file (only if debug frame saving is enabled) + if let depthDir = self.depthDirect { + let fileURL = depthDir.appendingPathComponent("\(Int64(Date().timeIntervalSince1970*1000)).bin") + do { + try data.write(to: fileURL) + } catch { + // Error saving binary file - continue capture + } } } @@ -1173,7 +1196,12 @@ class ARViewModel: ObservableObject{ let documentsURL = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask) do{ let contents = try FileManager.default.contentsOfDirectory(at: documentsURL[0], includingPropertiesForKeys: [.isDirectoryKey], options: [.skipsHiddenFiles, .skipsSubdirectoryDescendants]) - demosCounter = contents.count + let directories = contents.filter { url in + var isDirectory: ObjCBool = false + FileManager.default.fileExists(atPath: url.path, isDirectory: &isDirectory) + return isDirectory.boolValue + } + demosCounter = directories.count } catch { demosCounter = 0 } diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 459ebeb..fb18d1f 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -70,7 +70,7 @@ class ARVisualizationManager: ObservableObject { private var worldOrigin: SIMD3 = SIMD3(0, 0, 0) private var hasEstablishedOrigin: Bool = false - var debugLoggingEnabled: Bool = false + var debugLoggingEnabled: Bool = true var isGripperClosed: Bool = false var useVirtualGripper: Bool = false var applyEndOffset: Bool = true @@ -383,29 +383,24 @@ class ARVisualizationManager: ObservableObject { let wireframePos = wireframeVisualPosition, let targetPos = activeTargetPosition else { return } - let targetHalf = targetSize / 2.0 - let wireframeHalf = wireframeSize / 2.0 - - let targetMin = targetPos - SIMD3(targetHalf, targetHalf, targetHalf) - let targetMax = targetPos + SIMD3(targetHalf, targetHalf, targetHalf) - let wireframeMin = wireframePos - SIMD3(wireframeHalf, wireframeHalf, wireframeHalf) - let wireframeMax = wireframePos + SIMD3(wireframeHalf, wireframeHalf, wireframeHalf) - - let tolerance: Float = 0.001 - let isEnveloped = (targetMin.x >= wireframeMin.x - tolerance && targetMax.x <= wireframeMax.x + tolerance && - targetMin.y >= wireframeMin.y - tolerance && targetMax.y <= wireframeMax.y + tolerance && - targetMin.z >= wireframeMin.z - tolerance && targetMax.z <= wireframeMax.z + tolerance) + // Use distance-based proximity instead of strict overlap + let distance = length(targetPos - wireframePos) + + // Proximity threshold: more generous threshold for easier interaction + // targetSize=0.012m, wireframeSize=0.018m, so threshold = ~3cm + let proximityThreshold: Float = 0.03 // 3cm threshold - much more forgiving + + let isNearby = distance <= proximityThreshold if debugLoggingEnabled { - let distance = length(targetPos - wireframePos) let distanceChanged = abs(distance - lastLoggedDistance) > 0.01 - if distanceChanged || isEnveloped { - print("[Proximity] Distance: \(String(format: "%.3f", distance))m | Enveloped: \(isEnveloped)") + if distanceChanged || isNearby { + print("[Proximity] Distance: \(String(format: "%.3f", distance))m | Threshold: \(String(format: "%.3f", proximityThreshold))m | Nearby: \(isNearby)") lastLoggedDistance = distance } } - - if isEnveloped { + + if isNearby { if actionState != .reached { actionState = .reached transitionTargetToFading() diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 1748bf2..90ee49c 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -90,7 +90,7 @@ class MLInferenceManager: ObservableObject { @Published var enableGripperOverlay: Bool = true // Default enabled (for model input) @Published var showGripperOverlayOnScreen: Bool = true // Show overlay on AR view @Published var currentGripperOverlayImage: UIImage? // Current overlay image for display - @Published var saveDebugFrames: Bool = true // For testing + @Published var saveDebugFrames: Bool = false // For testing // MARK: - Inference Settings enum InferenceFrequency: CaseIterable { diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 0adcd2f..7c97c56 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -466,10 +466,21 @@ struct ReadView : View{ let rgbFile = FileElement.videoFile(VideoFile(url:fileSetNames.rgbFileName)) let depthFile = FileElement.videoFile(VideoFile(url:fileSetNames.depthFileName)) let poseFile = FileElement.textFile(TextFile(url:fileSetNames.poseFile.path)) -// let rgbImageFolder = FileElement.directory(SubLevelDirectory(url:fileSetNames.rgbImagesDirectory)) - let depthImageFolder = FileElement.directory(SubLevelDirectory(url: fileSetNames.depthImagesDirectory)) - - return [rgbFile, depthFile, poseFile, depthImageFolder] + + var elements = [rgbFile, depthFile, poseFile] + + // Only include image folders if they exist (debug mode was enabled) + if let depthImagesDir = fileSetNames.depthImagesDirectory { + let depthImageFolder = FileElement.directory(SubLevelDirectory(url: depthImagesDir)) + elements.append(depthImageFolder) + } + + if let rgbImagesDir = fileSetNames.rgbImagesDirectory { + let rgbImageFolder = FileElement.directory(SubLevelDirectory(url: rgbImagesDir)) + elements.append(rgbImageFolder) + } + + return elements } func deleteRecordedData(url: [URL], targetDirect: String){ From f9798a8992d0e8b7c9b448c56352150898b02381 Mon Sep 17 00:00:00 2001 From: DjKesu Date: Fri, 21 Nov 2025 11:31:15 -0500 Subject: [PATCH 43/56] policy transform updates --- AnySense/Managers/ARViewContainer.swift | 12 --- .../Managers/ARVisualizationManager.swift | 26 ++++--- AnySense/Managers/ActionTransformUtils.swift | 73 +++++++++---------- AnySense/Managers/MLInferenceManager.swift | 45 +++++------- AnySense/Views/accountView.swift | 4 +- 5 files changed, 69 insertions(+), 91 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index cacaf40..5209825 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -520,18 +520,6 @@ class ARViewModel: ObservableObject{ mlManager?.setUSBStreamingState(isActive: false) } -// func startWiFiStreaming(host: String, port: UInt16) { - // Set up the network connection -// // Start WebRTC connection -// webRTCManager.setupConnection() -// } - -// func stopWiFiStreaming() { -// displayLink?.invalidate() -// displayLink = nil -// streamConnection?.cancel() -// streamConnection = nil -// } @objc private func sendFrame(link: CADisplayLink) { streamVideoFrameUSB() diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index fb18d1f..2dd35bd 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -393,15 +393,12 @@ class ARVisualizationManager: ObservableObject { let isNearby = distance <= proximityThreshold if debugLoggingEnabled { - let distanceChanged = abs(distance - lastLoggedDistance) > 0.01 - if distanceChanged || isNearby { - print("[Proximity] Distance: \(String(format: "%.3f", distance))m | Threshold: \(String(format: "%.3f", proximityThreshold))m | Nearby: \(isNearby)") - lastLoggedDistance = distance - } + // Only log critical proximity events if needed } if isNearby { if actionState != .reached { + print("[Viz] 🎯 Target Cube REACHED (Proximity Trigger)") actionState = .reached transitionTargetToFading() NotificationCenter.default.post(name: NSNotification.Name("ProximityReached"), object: nil) @@ -459,7 +456,7 @@ class ARVisualizationManager: ObservableObject { if isClosed && !previousState { // Gripper just closed - hide all visualization - print("Gripper closed - hiding all visualization") + print("[Viz] Gripper CLOSED - Hiding visualization") DispatchQueue.main.async { [weak self] in guard let self = self else { return } @@ -483,7 +480,7 @@ class ARVisualizationManager: ObservableObject { self.actionState = .waiting } } else if !isClosed && previousState { - print("Gripper opened - visualization enabled") + print("[Viz] Gripper OPENED - Visualization enabled") } } @@ -525,7 +522,16 @@ class ARVisualizationManager: ObservableObject { if isVisualizationEnabled && hasEstablishedOrigin { let t = arFrame.camera.transform let currentCameraPosition = SIMD3(t.columns.3.x, t.columns.3.y, t.columns.3.z) - worldOrigin - let cameraWorldPosition = currentCameraPosition + SIMD3(0, 0, -wireframeOffsetMeters) + + // Calculate wireframe position in World Frame + // The wireframe is fixed at (0, 0, -wireframeOffsetMeters) in Camera Frame (Forward) + // We need to rotate this offset by the camera's orientation to get it in World Frame + + // Camera Forward vector is -Z axis (column 2 is +Z/Backward) + let cameraBackward = SIMD3(t.columns.2.x, t.columns.2.y, t.columns.2.z) + let offsetInWorld = -wireframeOffsetMeters * cameraBackward + + let cameraWorldPosition = currentCameraPosition + offsetInWorld updateWireframe(cameraRelativePosition: cameraWorldPosition) } } @@ -593,11 +599,11 @@ class ARVisualizationManager: ObservableObject { worldOriginAnchor.addChild(newTarget) self.activeTargetEntity = newTarget self.actionState = .waiting - print("[Viz] ✅ New target created at (\(String(format: "%.3f", position.x)), \(String(format: "%.3f", position.y)), \(String(format: "%.3f", position.z)))") } self.activeTargetEntity?.position = position self.activeTargetPosition = position + print("[Viz] Cube (Target) Position: (\(String(format: "%.3f", position.x)), \(String(format: "%.3f", position.y)), \(String(format: "%.3f", position.z)))") } } @@ -642,6 +648,6 @@ class ARVisualizationManager: ObservableObject { let relativePosition = targetPose - worldOrigin goalPointEntity?.position = relativePosition worldOriginAnchor.addChild(goalPointEntity!) - print("✅ Goal point created at distance: \(length(relativePosition))m") + print("[Viz] Sphere (Goal) Position: (\(String(format: "%.3f", relativePosition.x)), \(String(format: "%.3f", relativePosition.y)), \(String(format: "%.3f", relativePosition.z))) | Dist: \(length(relativePosition))m") } } diff --git a/AnySense/Managers/ActionTransformUtils.swift b/AnySense/Managers/ActionTransformUtils.swift index 9e478a5..996f16b 100644 --- a/AnySense/Managers/ActionTransformUtils.swift +++ b/AnySense/Managers/ActionTransformUtils.swift @@ -24,23 +24,26 @@ struct ActionTransformUtils { }() // MARK: - Public Entry - // The policy produces an action tensor in its own convention. We first map it into the - // iPhone CAMERA frame (policy→camera), then convert CAMERA→ROBOT to match server logic. + // The policy produces an action tensor in its own convention (labels.json). + // We first map it into the iPhone CAMERA frame (policy→camera), then convert + // CAMERA→ROBOT using the Z90 rotation to match the robot's execution frame. // Input: policy action [tx, ty, tz, r1, r2, r3, gripper] // Output: robot-frame [tx, ty, tz, rx, ry, rz, gripper] (Euler xyz) static func toRobotActions(_ policyAction7: [Float], rotationUnit: RotationUnit = .eulerXYZ) -> [Float] { guard policyAction7.count >= 7 else { return policyAction7 } + + // 1) Policy (Labels) → Camera Frame let camEulerAction = policyToCameraEulerAction(policyAction7, rotationUnit: rotationUnit) let gr = camEulerAction[6] - // 1) CAMERA action → 4x4 + // Build 4x4 Transform in Camera Frame let T_c = buildTransform(translation: SIMD3(camEulerAction[0], camEulerAction[1], camEulerAction[2]), eulerXYZ: SIMD3(camEulerAction[3], camEulerAction[4], camEulerAction[5])) - // 2) Camera → Robot: T_r = Z90 @ (P.T @ T_c @ P) @ Z90.T (parity with server) - let Pt = simd_transpose(P) + // 2) Camera → Robot: T_r = Z90 @ T_c @ Z90.T + // We skip the intermediate P transform (Pt * T_c * P) because T_c is already + // in the correct Camera frame, and Z90 maps Camera(Right,Up,Back) → Robot(Down,Right,Back). let Zt = simd_transpose(Z90) - let T_perm = Pt * T_c * P - let T_r = Z90 * T_perm * Zt + let T_r = Z90 * T_c * Zt // 3) 4x4 → robot action (Euler xyz) let rxyz = eulerXYZ(from: T_r) @@ -50,22 +53,28 @@ struct ActionTransformUtils { } // Policy → CAMERA mapping in a single place so viz and robot stay consistent. - // Convention used here mirrors ARVisualizationManager's historical mapping with a corrected Z sign: - // - policy: [down, right, backward] - // - camera: x=right, y=up, z forward is -Z in ARKit conventions → use z = -backward + // Mapping based on frame definitions: + // - Policy (Labels): [x: Left, y: Forward, z: Down] + // - Camera (ARKit): [x: Right, y: Up, z: Back] + // + // Transformation: + // - Policy x (Left) → Camera -x (Right) + // - Policy y (Forward) → Camera -z (Back) + // - Policy z (Down) → Camera -y (Up) static func policyToCameraEulerAction(_ policyAction7: [Float], rotationUnit: RotationUnit = .eulerXYZ) -> [Float] { guard policyAction7.count >= 7 else { return policyAction7 } - let ml_x = policyAction7[0] // down - let ml_y = policyAction7[1] // right - let ml_z = policyAction7[2] // backward + let ml_x = policyAction7[0] // Left + let ml_y = policyAction7[1] // Forward + let ml_z = policyAction7[2] // Down let r1 = policyAction7[3] let r2 = policyAction7[4] let r3 = policyAction7[5] let gr = policyAction7[6] - // Translation mapping (labels → CAMERA) using inverse of goal mapping: - // labels: x = -x_cam, y = -z_cam, z = -y_cam - // => camera: x = -x_l, y = -z_l, z = -y_l + // Translation mapping (Labels → CAMERA) + // cam_x = -label_x (Left -> Right) + // cam_y = -label_z (Down -> Up) + // cam_z = -label_y (Forward -> Back) let cam_t = SIMD3(-ml_x, -ml_z, -ml_y) // Rotation mapping → always return Euler xyz in CAMERA frame @@ -149,26 +158,12 @@ struct ActionTransformUtils { return R } - // Rotate a vector in camera XY plane by 90° increments (right-handed, +Z out of screen) - // private static func rotateXY(_ v: SIMD3) -> SIMD3 { - // switch ((quarterTurns % 4) + 4) % 4 { // normalize to 0..3 - // case 1: // +90° (counterclockwise): (x,y) -> (-y, x) - // return SIMD3(-v.y, v.x, v.z) - // case 2: // 180° - // return SIMD3(-v.x, -v.y, v.z) - // case 3: // -90° (clockwise): (x,y) -> (y, -x) - // return SIMD3(v.y, -v.x, v.z) - // default: - // return v - // } - // } - - // Extract Euler 'xyz' (radians) from 4x4 + // Rotation matrix for Euler 'xyz' (radians) private static func eulerXYZ(from T: simd_float4x4) -> SIMD3 { // Reconstruct row-major elements from column-major storage let R00 = T.columns.0.x, R01 = T.columns.1.x, R02 = T.columns.2.x - let R10 = T.columns.0.y, R11 = T.columns.1.y, R12 = T.columns.2.y - let R20 = T.columns.0.z, R21 = T.columns.1.z, R22 = T.columns.2.z + let R11 = T.columns.1.y, R12 = T.columns.2.y + let R21 = T.columns.1.z, R22 = T.columns.2.z // For 'xyz': // y = asin(R02) @@ -207,18 +202,18 @@ struct ActionTransformUtils { guard policyAction7.count >= 7 else { return "" } let cam = policyToCameraEulerAction(policyAction7, rotationUnit: rotationUnit) let T_c = buildTransform(translation: SIMD3(cam[0], cam[1], cam[2]), eulerXYZ: SIMD3(cam[3], cam[4], cam[5])) - let Pt = simd_transpose(P) + let Zt = simd_transpose(Z90) - let T_perm = Pt * T_c * P - let T_r = Z90 * T_perm * Zt + let T_r = Z90 * T_c * Zt + let robotEuler = eulerXYZ(from: T_r) let robotT = translation(from: T_r) func fmt(_ f: Float) -> String { String(format: "%.4f", f) } func fmt3(_ v: SIMD3) -> String { "(\(fmt(v.x)),\(fmt(v.y)),\(fmt(v.z)))" } return [ - "policy t,r: \(fmt3(SIMD3(policyAction7[0], policyAction7[1], policyAction7[2]))) \(fmt3(SIMD3(policyAction7[3], policyAction7[4], policyAction7[5])))", - "camera (map) t,r_euler: \(fmt3(SIMD3(cam[0], cam[1], cam[2]))) \(fmt3(SIMD3(cam[3], cam[4], cam[5])))", - "robot t,r_euler: \(fmt3(robotT)) \(fmt3(robotEuler))", + "policy(Lab) t,r: \(fmt3(SIMD3(policyAction7[0], policyAction7[1], policyAction7[2]))) \(fmt3(SIMD3(policyAction7[3], policyAction7[4], policyAction7[5])))", + "camera(Cam) t,r: \(fmt3(SIMD3(cam[0], cam[1], cam[2]))) \(fmt3(SIMD3(cam[3], cam[4], cam[5])))", + "robot(Exec) t,r: \(fmt3(robotT)) \(fmt3(robotEuler))", ].joined(separator: "\n") } } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 90ee49c..bbca284 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -203,7 +203,7 @@ class MLInferenceManager: ObservableObject { return } - let isGripperClosed = currentGripperValue < 0.6 + let isGripperClosed = currentGripperValue < 0.7 let imageToShow = isGripperClosed ? gripperClosedUIImage : gripperOpenUIImage print("DEBUG: Updating gripper overlay - value: \(String(format: "%.3f", currentGripperValue)), closed: \(isGripperClosed)") @@ -270,7 +270,7 @@ class MLInferenceManager: ObservableObject { private func getCurrentGripperOverlay() -> CIImage? { // Use closed gripper when gripper value < 0.6, otherwise open gripper - let isGripperClosed = currentGripperValue < 0.6 + let isGripperClosed = currentGripperValue < 0.7 if saveDebugFrames { print("Gripper state: \(String(format: "%.3f", currentGripperValue)) → \(isGripperClosed ? "CLOSED" : "OPEN")") } @@ -499,8 +499,9 @@ class MLInferenceManager: ObservableObject { // camera: x right, y up, z back // labels: x left, y forward, z down // Mapping: x = -x_cam, y = -z_cam, z = -y_cam - // We add 0.02 to the y coordinate since training data is shifted forward a bit. - return [-p_c4.x, -p_c4.z + 0.02, -p_c4.y] + // return [-p_c4.x, -p_c4.z + 0.02, -p_c4.y] + let goalArr = [-p_c4.x, -p_c4.z + 0.02, -p_c4.y] + return goalArr } // If model expects 2D goals, return nil since we only support 3D goals now return nil @@ -520,6 +521,7 @@ class MLInferenceManager: ObservableObject { // MARK: - Proximity Handler private func handleProximityReached() { + print("[ML] 🏁 Goal Reached (Proximity Trigger Received)") guard !isInferencePending else { print("[MLInference] Proximity reached but inference already pending - skipping") return @@ -564,10 +566,6 @@ class MLInferenceManager: ObservableObject { let isProximityTriggered = proximityReached && !isInferencePending let shouldRunInference = isFirstInference || isProximityTriggered - if debugLoggingEnabled && !shouldRunInference { - print("[MLInference] Not triggering: firstInference=\(hasRunFirstInference), proximity=\(proximityReached), pending=\(isInferencePending)") - } - guard shouldRunInference else { return } @@ -949,7 +947,8 @@ class MLInferenceManager: ObservableObject { // Update gripper value for overlay switching (7th element, index 6) if jointPositions.count >= 7 { currentGripperValue = jointPositions[6] - let isGripperClosed = currentGripperValue < 0.6 + let isGripperClosed = currentGripperValue < 0.7 + print("[ML] Standard - Gripper Value: \(String(format: "%.3f", currentGripperValue)) | State: \(isGripperClosed ? "CLOSED" : "OPEN")") Task { @MainActor [weak self] in self?.updateGripperOverlayDisplay() @@ -977,19 +976,12 @@ class MLInferenceManager: ObservableObject { if jointPositions.count >= 7 { let src = Array(jointPositions.prefix(7)) if self?.enableTransformDebug == true { - let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) - print("Coordinate Transform: \(report)") + let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) + print("Coordinate Transform:\n\(report)") } - let robot = ActionTransformUtils.toRobotActions(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) - print("Robot actions: [\(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") - // Joint actions are now sent embedded in the main USB stream } } - let positionString = jointPositions.map { String(format: "%.3f", $0) }.joined(separator: ", ") - let modelName = modelManager.activeModel?.name ?? "Unknown" - print("[\(modelName)] Standard: [\(positionString)] (\(String(format: "%.1f", inferenceTime * 1000))ms)") - } else { // Point-conditioned models let outputFeatureName = metadata.primaryOutputName ?? output.featureNames.first @@ -1005,7 +997,8 @@ class MLInferenceManager: ObservableObject { // Update gripper value for overlay switching (7th element, index 6) if jointPositions.count >= 7 { currentGripperValue = jointPositions[6] - let isGripperClosed = currentGripperValue < 0.6 + let isGripperClosed = currentGripperValue < 0.7 + print("[ML] PointCond - Gripper Value: \(String(format: "%.3f", currentGripperValue)) | State: \(isGripperClosed ? "CLOSED" : "OPEN")") Task { @MainActor [weak self] in self?.updateGripperOverlayDisplay() @@ -1032,20 +1025,16 @@ class MLInferenceManager: ObservableObject { // Joint actions are automatically sent via USB stream (transform to robot frame) if jointPositions.count >= 7 { let src = Array(jointPositions.prefix(7)) - let robot = ActionTransformUtils.toRobotActions(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) - print("Robot actions: [\(robot.map { String(format: "%.3f", $0) }.joined(separator: ", "))]") - // Joint actions are now sent embedded in the main USB stream + if self?.enableTransformDebug == true { + let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) + print("Coordinate Transform:\n\(report)") + } } } - let positionString = jointPositions.map { String(format: "%.3f", $0) }.joined(separator: ", ") - let modelName = modelManager.activeModel?.name ?? "Unknown" - let modelTypeStr = metadata.modelType.displayName - print("[\(modelName)] \(modelTypeStr): [\(positionString)] (\(String(format: "%.1f", inferenceTime * 1000))ms)") - // Log goal point status for point-conditioned models if metadata.requiresGoalPoint, let goalPoint = currentGoalPoint { - print("Goal: [\(String(format: "%.3f", goalPoint.x)), \(String(format: "%.3f", goalPoint.y)), \(String(format: "%.3f", goalPoint.z))]") + // Goal point logging removed for cleanliness } } } diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index e3b1610..e6305d0 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -136,11 +136,11 @@ struct SettingsView : View{ Picker("Select Model", selection: Binding( get: { let activeID = modelManager.activeModelID - print("DEBUG: Picker get - activeModelID: \(String(describing: activeID))") + // print("DEBUG: Picker get - activeModelID: \(String(describing: activeID))") return activeID }, set: { newValue in - print("DEBUG: Picker set - newValue: \(String(describing: newValue))") + // print("DEBUG: Picker set - newValue: \(String(describing: newValue))") if let newValue = newValue { // Force immediate UI update DispatchQueue.main.async { From 16ba35b40ba5f348b389ac3ee88cf158987e29ac Mon Sep 17 00:00:00 2001 From: DjKesu Date: Fri, 21 Nov 2025 13:42:48 -0500 Subject: [PATCH 44/56] more fixes to transform issues --- AnySense/Managers/ActionTransformUtils.swift | 10 +------- AnySense/Managers/MLInferenceManager.swift | 4 +-- AnySense/Views/readView.swift | 26 ++++---------------- 3 files changed, 7 insertions(+), 33 deletions(-) diff --git a/AnySense/Managers/ActionTransformUtils.swift b/AnySense/Managers/ActionTransformUtils.swift index 996f16b..1fa3128 100644 --- a/AnySense/Managers/ActionTransformUtils.swift +++ b/AnySense/Managers/ActionTransformUtils.swift @@ -81,7 +81,7 @@ struct ActionTransformUtils { var cam_euler: SIMD3 switch rotationUnit { case .eulerXYZ: - cam_euler = SIMD3(r1, r2, r3) + cam_euler = SIMD3(-r1, -r2, -r3) case .axisAngle: let R_cam = rotationMatrixFromAxisAngle(axisAngle: SIMD3(r1, r2, r3)) cam_euler = eulerXYZ(from: matrixFromRotationAndTranslation(R_cam, t: SIMD3(0,0,0))) @@ -165,14 +165,6 @@ struct ActionTransformUtils { let R11 = T.columns.1.y, R12 = T.columns.2.y let R21 = T.columns.1.z, R22 = T.columns.2.z - // For 'xyz': - // y = asin(R02) - // if |cos(y)| > eps: - // x = atan2(-R12, R22) - // z = atan2(-R01, R00) - // else (gimbal lock): - // x = atan2(R21, R11) - // z = 0 let y = asin(clamp(R02, -1.0, 1.0)) let cy = cos(y) let eps: Float = 1e-6 diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index bbca284..c477fbe 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -495,11 +495,9 @@ class MLInferenceManager: ObservableObject { let T_wc = frame.camera.transform let T_cw = simd_inverse(T_wc) let p_c4 = simd_mul(T_cw, simd_float4(p_w.x, p_w.y, p_w.z, 1.0)) - // Current logic // camera: x right, y up, z back // labels: x left, y forward, z down // Mapping: x = -x_cam, y = -z_cam, z = -y_cam - // return [-p_c4.x, -p_c4.z + 0.02, -p_c4.y] let goalArr = [-p_c4.x, -p_c4.z + 0.02, -p_c4.y] return goalArr } @@ -521,7 +519,7 @@ class MLInferenceManager: ObservableObject { // MARK: - Proximity Handler private func handleProximityReached() { - print("[ML] 🏁 Goal Reached (Proximity Trigger Received)") + print("[ML] Goal Reached (Proximity Trigger Received)") guard !isInferencePending else { print("[MLInference] Proximity reached but inference already pending - skipping") return diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 7c97c56..f6f266a 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -243,9 +243,9 @@ struct ReadView : View{ Spacer() - // Right side: goal (if applicable) and flashlight - if (arViewModel.mlManager?.isPointConditioned ?? false) { - HStack(spacing: 20) { + // Right side: goal (if applicable), flashlight, and debug + HStack(spacing: 20) { + if (arViewModel.mlManager?.isPointConditioned ?? false) { VStack(spacing: 4) { Button(action: { let newValue = !arViewModel.goalTapModeEnabled @@ -266,20 +266,8 @@ struct ReadView : View{ .font(.caption) .foregroundColor(.secondary) } - - VStack(spacing: 4) { - Button(action: toggleFlash) { - Image(systemName: openFlash ? "flashlight.off.circle.fill" : "flashlight.on.circle.fill") - .resizable() - .frame(height: 36) - .frame(width: 36) - } - Text(openFlash ? "Flash off" : "Flash on") - .font(.caption) - .foregroundColor(.secondary) - } } - } else { + VStack(spacing: 4) { Button(action: toggleFlash) { Image(systemName: openFlash ? "flashlight.off.circle.fill" : "flashlight.on.circle.fill") @@ -297,12 +285,8 @@ struct ReadView : View{ .padding(.bottom, arViewPadding / 4.0 - (buttonSize / 4.0)) } - - - } - .frame(width: 10.0, height: 10.0) - .alert(isPresented: $arViewModel.depthStatus.showAlert) { // ✅ Show alert when depth is missing + .alert(isPresented: $arViewModel.depthStatus.showAlert) { // Show alert when depth is missing Alert( title: Text("Depth Data Unavailable"), message: Text("Your device does not support depth data, or it is temporarily unavailable."), From 5d2800a17c0ee7f849837414553e482ce5d07bb8 Mon Sep 17 00:00:00 2001 From: DjKesu Date: Sun, 23 Nov 2025 14:14:26 -0500 Subject: [PATCH 45/56] refactor redundant code, fix label and camera coordinates --- AnySense.xcodeproj/project.pbxproj | 12 + AnySense/MLModel+Extensions.swift | 9 +- .../Managers/ARVisualizationManager.swift | 94 +--- AnySense/Managers/MLInferenceManager.swift | 527 ++++++++++-------- AnySense/Managers/ModelManager.swift | 90 ++- AnySense/Managers/USBManager.swift | 4 +- AnySense/Views/MLInferenceResultsView.swift | 4 +- AnySense/Views/accountView.swift | 35 -- AnySense/Views/readView.swift | 50 +- 9 files changed, 400 insertions(+), 425 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 1d8cdcf..fad8dc3 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -7,6 +7,7 @@ objects = { /* Begin PBXBuildFile section */ + 01214E392ED25092009E565F /* sam2-jitter.mlpackage in Sources */ = {isa = PBXBuildFile; fileRef = 01214E372ED25092009E565F /* sam2-jitter.mlpackage */; }; 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */; }; 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */; }; 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */; }; @@ -48,6 +49,7 @@ /* End PBXContainerItemProxy section */ /* Begin PBXFileReference section */ + 01214E372ED25092009E565F /* sam2-jitter.mlpackage */ = {isa = PBXFileReference; lastKnownFileType = folder.mlpackage; path = "sam2-jitter.mlpackage"; sourceTree = ""; }; 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARVisualizationManager.swift; sourceTree = ""; }; 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ActionTransformUtils.swift; sourceTree = ""; }; 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceManager.swift; sourceTree = ""; }; @@ -100,6 +102,14 @@ /* End PBXFrameworksBuildPhase section */ /* Begin PBXGroup section */ + 01214E382ED25092009E565F /* Models */ = { + isa = PBXGroup; + children = ( + 01214E372ED25092009E565F /* sam2-jitter.mlpackage */, + ); + path = Models; + sourceTree = ""; + }; B9104F512BFDE63A000D4DDD = { isa = PBXGroup; children = ( @@ -122,6 +132,7 @@ B9104F5C2BFDE63A000D4DDD /* AnySense */ = { isa = PBXGroup; children = ( + 01214E382ED25092009E565F /* Models */, 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */, 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */, B9944A332CFE982E00232FBB /* MainPage.swift */, @@ -353,6 +364,7 @@ B9E4B22F2D62A9BA0032E877 /* ARViewContainer.swift in Sources */, B9E4B2302D62A9BA0032E877 /* USBManager.swift in Sources */, 01F5B7C62DEA698D00061B16 /* MLInferenceResultsView.swift in Sources */, + 01214E392ED25092009E565F /* sam2-jitter.mlpackage in Sources */, B9944A342CFE983300232FBB /* MainPage.swift in Sources */, ); runOnlyForDeploymentPostprocessing = 0; diff --git a/AnySense/MLModel+Extensions.swift b/AnySense/MLModel+Extensions.swift index 6cdcd6a..401227c 100644 --- a/AnySense/MLModel+Extensions.swift +++ b/AnySense/MLModel+Extensions.swift @@ -142,17 +142,14 @@ struct ModelMetadata { // MARK: - Dynamic helpers used by MLInferenceManager enum ModelType { case pointConditioned - case standard + var displayName: String { - switch self { - case .pointConditioned: return "Point-Conditioned" - case .standard: return "Standard" - } + return "Point-Conditioned" } } var modelType: ModelType { - return requiresGoalPoint ? .pointConditioned : .standard + return .pointConditioned } var temporalFrames: Int { diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 2dd35bd..d974293 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -23,14 +23,6 @@ enum TargetState { case reached // Green target } -// MARK: - Fading Target -struct FadingTarget { - var entity: ModelEntity - var position: SIMD3 - var fadeStartTime: CFTimeInterval - var state: TargetState -} - // MARK: - Visualization Frequency enum VisualizationFrequency: CaseIterable { case high, medium, low, minute @@ -84,9 +76,6 @@ class ARVisualizationManager: ObservableObject { private var wireframeVisualPosition: SIMD3? private var activeTargetEntity: ModelEntity? private var activeTargetPosition: SIMD3? - private var fadingTargets: [FadingTarget] = [] - private var displayLink: CADisplayLink? - private let fadeDuration: CFTimeInterval = 0.1 private let targetSize: Float = 0.012 private var lastWireframeUpdateTime: CFTimeInterval = 0 private let wireframeUpdateInterval: CFTimeInterval = 0.033 @@ -104,46 +93,9 @@ class ARVisualizationManager: ObservableObject { // MARK: - Setup Methods func setupVisualization(with arView: ARView) { self.arView = arView - setupFadeAnimation() log("Setup completed - using wireframe seek-target visualization") } - // MARK: - Fade Animation Setup - private func setupFadeAnimation() { - displayLink = CADisplayLink(target: self, selector: #selector(updateFadingTargets)) - displayLink?.preferredFrameRateRange = CAFrameRateRange(minimum: 20, maximum: 30, preferred: 30) - displayLink?.add(to: .main, forMode: .common) - } - - @objc private func updateFadingTargets() { - guard !fadingTargets.isEmpty else { return } - - let currentTime = CACurrentMediaTime() - var targetsToRemove: [Int] = [] - - for (index, fadingTarget) in fadingTargets.enumerated() { - let elapsed = currentTime - fadingTarget.fadeStartTime - let alpha = Float(max(0.0, 1.0 - elapsed / fadeDuration)) - - if alpha <= 0.05 { - fadingTarget.entity.removeFromParent() - targetsToRemove.append(index) - continue - } - - let greenMaterial = SimpleMaterial( - color: UIColor.systemGreen.withAlphaComponent(CGFloat(alpha)), - isMetallic: false - ) - fadingTarget.entity.model?.materials = [greenMaterial] - } - - // Remove completed fades (reverse order to maintain indices) - for index in targetsToRemove.reversed() { - fadingTargets.remove(at: index) - } - } - // MARK: - Recording Control Methods func startRecordingVisualization() { print("startRecordingVisualization called") @@ -236,11 +188,6 @@ class ARVisualizationManager: ObservableObject { self.activeTargetEntity?.removeFromParent() self.activeTargetEntity = nil self.activeTargetPosition = nil - - for fadingTarget in self.fadingTargets { - fadingTarget.entity.removeFromParent() - } - self.fadingTargets.removeAll() } } @@ -387,20 +334,20 @@ class ARVisualizationManager: ObservableObject { let distance = length(targetPos - wireframePos) // Proximity threshold: more generous threshold for easier interaction - // targetSize=0.012m, wireframeSize=0.018m, so threshold = ~3cm - let proximityThreshold: Float = 0.03 // 3cm threshold - much more forgiving + // targetSize=0.012m, wireframeSize=0.018m + let proximityThreshold: Float = 0.01 // 1cm threshold let isNearby = distance <= proximityThreshold - - if debugLoggingEnabled { - // Only log critical proximity events if needed - } + if isNearby { if actionState != .reached { - print("[Viz] 🎯 Target Cube REACHED (Proximity Trigger)") + print("Target Cube REACHED") actionState = .reached - transitionTargetToFading() + // Simply remove the target when reached + activeTargetEntity?.removeFromParent() + activeTargetEntity = nil + activeTargetPosition = nil NotificationCenter.default.post(name: NSNotification.Name("ProximityReached"), object: nil) } } else { @@ -410,25 +357,6 @@ class ARVisualizationManager: ObservableObject { } } - // MARK: - Target Transition - private func transitionTargetToFading() { - guard let activeEntity = activeTargetEntity, - let activePos = activeTargetPosition else { return } - - let greenMaterial = SimpleMaterial(color: UIColor.systemGreen.withAlphaComponent(1.0), isMetallic: false) - activeEntity.model?.materials = [greenMaterial] - - let fadingTarget = FadingTarget( - entity: activeEntity, - position: activePos, - fadeStartTime: CACurrentMediaTime(), - state: .reached - ) - fadingTargets.append(fadingTarget) - activeTargetEntity = nil - activeTargetPosition = nil - } - // MARK: - Manual Trigger Support func forceTargetTransition() { activeTargetEntity?.removeFromParent() @@ -470,12 +398,6 @@ class ARVisualizationManager: ObservableObject { self.activeTargetEntity = nil self.activeTargetPosition = nil - // Remove fading targets - for fadingTarget in self.fadingTargets { - fadingTarget.entity.removeFromParent() - } - self.fadingTargets.removeAll() - // Set action state to waiting self.actionState = .waiting } diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index c477fbe..9a31f13 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -45,12 +45,16 @@ class MLInferenceManager: ObservableObject { func setGoalPoint(_ point: simd_float3) { self.currentGoalPoint = point arVisualizationManager?.setTargetPose(point) + // Reset goal frame count when new goal is set + goalFrameCount = 0 } - private var goalPointQueue = DispatchQueue(label: "GoalPointQueue", qos: .userInitiated) // Goal conditioning mode (point-conditioned models use 3D goals) private var goalDimension: Int = 3 + // Track how many times goal has been used (for first-frame offset) + private var goalFrameCount: Int = 0 + // MARK: - Frame Buffering for Temporal Models private struct FrameBufferEntry { let mlArray: MLMultiArray // Pre-processed [1,3,H,W] frame @@ -77,7 +81,9 @@ class MLInferenceManager: ObservableObject { // MARK: - Frame Processing (Taken from ARViewContainer) private let ciContext: CIContext private var modelInputSize = CGSize(width: 224, height: 224) - private var modelInputTransform: CGAffineTransform? + + // MARK: - Shared Buffers (Reused to avoid allocations) + private var sharedOutputPixelBuffer: CVPixelBuffer? // Reused CVPixelBuffer for frame processing // MARK: - Gripper Overlay Properties private var gripperOpenCIImage: CIImage? @@ -126,6 +132,7 @@ class MLInferenceManager: ObservableObject { init(modelManager: ModelManager) { self.modelManager = modelManager self.ciContext = CIContext() + initializeSharedBuffers() // Initialize shared buffers early loadActiveModel() loadGripperOverlay() @@ -313,16 +320,21 @@ class MLInferenceManager: ObservableObject { // Apply same transformations as camera frames: scale to fit, then rotate if needed let scale = min(imageSize.width / gripperOverlay.extent.width, imageSize.height / gripperOverlay.extent.height) - var transformedOverlay = gripperOverlay.transformed(by: CGAffineTransform(scaleX: scale, y: scale)) - + + // Build combined transform: scale -> optional orientation -> rotation -> translation + var transform = CGAffineTransform(scaleX: scale, y: scale) + // Apply same orientation as camera frames if applyServerImageOrientation { - transformedOverlay = transformedOverlay.oriented(.down) + transform = transform.concatenating(CGAffineTransform(rotationAngle: CGFloat.pi)) } - + // Additional +90 degree rotation to align gripper direction with viewpoint - transformedOverlay = transformedOverlay.transformed(by: CGAffineTransform(rotationAngle: CGFloat.pi / 2)) - + transform = transform.concatenating(CGAffineTransform(rotationAngle: CGFloat.pi / 2)) + + // Apply combined transform + var transformedOverlay = gripperOverlay.transformed(by: transform) + // After rotation, translate back to origin for proper overlay positioning let rotatedExtent = transformedOverlay.extent transformedOverlay = transformedOverlay.transformed(by: CGAffineTransform(translationX: -rotatedExtent.origin.x, y: -rotatedExtent.origin.y)) @@ -419,15 +431,12 @@ class MLInferenceManager: ObservableObject { // 224x224 input for all models modelInputSize = CGSize(width: 224, height: 224) - setupModelInputTransform() + + // Initialize shared pixel buffer if needed + initializeSharedBuffers() // Force 3D goal conditioning goalDimension = 3 - - // Clear goal point if switching to non-point-conditioned model - if metadata.requiresGoalPoint == false { - currentGoalPoint = nil - } } catch { model = nil modelMetadata = nil @@ -437,12 +446,29 @@ class MLInferenceManager: ObservableObject { } } - // MARK: - Transform Setup (Similar to ARViewContainer approach) - private func setupModelInputTransform() { - let normalizeTransform = CGAffineTransform(scaleX: 1.0, y: 1.0) - let scaleTransform = CGAffineTransform(scaleX: modelInputSize.width, y: modelInputSize.height) - - modelInputTransform = normalizeTransform.concatenating(scaleTransform) + // MARK: - Shared Buffer Initialization + private func initializeSharedBuffers() { + // Initialize shared output pixel buffer (224x224 ARGB) - reused for all frame processing + if sharedOutputPixelBuffer == nil { + let width = 224 + let height = 224 + let attributes: [String: Any] = [ + kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32ARGB, + kCVPixelBufferWidthKey as String: width, + kCVPixelBufferHeightKey as String: height + ] + var pixelBuffer: CVPixelBuffer? + let status = CVPixelBufferCreate( + kCFAllocatorDefault, + width, height, + kCVPixelFormatType_32ARGB, + attributes as CFDictionary, + &pixelBuffer + ) + if status == kCVReturnSuccess { + sharedOutputPixelBuffer = pixelBuffer + } + } } // MARK: - Model Management Integration @@ -455,7 +481,7 @@ class MLInferenceManager: ObservableObject { } var isPointConditioned: Bool { - return modelMetadata?.modelType == .pointConditioned + return true // All models are point-conditioned now } var activeModelName: String? { @@ -471,6 +497,7 @@ class MLInferenceManager: ObservableObject { func clearGoalPoint() { currentGoalPoint = nil + goalFrameCount = 0 } // MARK: - Odometry Integration Methods (removed) @@ -498,7 +525,10 @@ class MLInferenceManager: ObservableObject { // camera: x right, y up, z back // labels: x left, y forward, z down // Mapping: x = -x_cam, y = -z_cam, z = -y_cam - let goalArr = [-p_c4.x, -p_c4.z + 0.02, -p_c4.y] + // Add 0.02 offset only on first frame + let yOffset: Float = (goalFrameCount == 0) ? 0.02 : 0.0 + let goalArr = [-p_c4.x, -p_c4.z + yOffset, -p_c4.y] + goalFrameCount += 1 return goalArr } // If model expects 2D goals, return nil since we only support 3D goals now @@ -643,17 +673,29 @@ class MLInferenceManager: ObservableObject { // MARK: - Action Frame Buffer Input Preparation private func prepareModelInputFromBuffer(metadata: ModelMetadata) throws -> MLFeatureProvider { - print("DEBUG: Preparing input from action frame buffer for \(metadata.modelType.displayName) model") + print("DEBUG: Preparing input from action frame buffer for point-conditioned model") guard !frameBuffer.isEmpty else { throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "No action frames stored yet"]) } - switch metadata.modelType { - case .pointConditioned: - return try prepareVQBeTInputFromBuffer(metadata: metadata) - case .standard: - return try prepareLegacyInputFromBuffer(metadata: metadata) + return try prepareVQBeTInputFromBuffer(metadata: metadata) + } + + // MARK: - MLMultiArray Copying Helper + /// Copy a single channel from source MLMultiArray to target MLMultiArray + /// - Parameters: + /// - source: Source MLMultiArray with shape [1, 3, H, W] + /// - target: Target MLMultiArray to copy into + /// - targetTimestep: Target timestep index + /// - targetChannel: Target channel index + /// - sourceChannel: Source channel index + private func copyMLMultiArrayChannel(source: MLMultiArray, target: MLMultiArray, targetTimestep: Int, targetChannel: Int, sourceChannel: Int) { + for h in 0..<224 { + for w in 0..<224 { + let value = source[[0, NSNumber(value: sourceChannel), NSNumber(value: h), NSNumber(value: w)]] + target[[0, NSNumber(value: targetTimestep), NSNumber(value: targetChannel), NSNumber(value: h), NSNumber(value: w)]] = value + } } } @@ -687,6 +729,7 @@ class MLInferenceManager: ObservableObject { let framesToUse = min(temporalFrames, frameBuffer.count) let paddingNeeded = max(0, temporalFrames - framesToUse) + // Create temporal frame array (can't reuse since it's used in model input) imageArray = try MLMultiArray(shape: [1, NSNumber(value: temporalFrames), 3, 224, 224], dataType: .float32) guard frameBuffer.count > 0 else { @@ -698,12 +741,7 @@ class MLInferenceManager: ObservableObject { let firstActionFrame = frameBuffer[0].mlArray for t in 0.. 1 && dims[2] == 3 { - let arr = try? MLMultiArray(shape: shape, dataType: .float32) - if let arr = arr { - for t in 0.. 1 && dims[2] == 3 { + // Temporal goal: [1, T, 3] + for t in 0.. MLFeatureProvider { - let inputName = metadata.getImageInputName() ?? "x_1" - let latestFrame = frameBuffer.last!.mlArray - let inputArray: MLMultiArray - - if let d = model?.modelDescription.inputDescriptionsByName[inputName], - d.type == .multiArray, - let shape = d.multiArrayConstraint?.shape { - - if shape.count == 5 { - let height = 224 - let width = 224 - inputArray = try MLMultiArray(shape: [1, 1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) - - for c in 0..<3 { - for h in 0.. MLMultiArray { let width = Int(targetSize.width) let height = Int(targetSize.height) - // Create output pixel buffer - let attributes: [String: Any] = [ - kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32ARGB, - kCVPixelBufferWidthKey as String: width, - kCVPixelBufferHeightKey as String: height - ] - - var outputPixelBuffer: CVPixelBuffer? - let status = CVPixelBufferCreate( - kCFAllocatorDefault, - width, height, - kCVPixelFormatType_32ARGB, - attributes as CFDictionary, - &outputPixelBuffer - ) + // Use shared output pixel buffer or create if needed + if sharedOutputPixelBuffer == nil { + initializeSharedBuffers() + } - guard status == kCVReturnSuccess, let outputBuffer = outputPixelBuffer else { - throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to create output pixel buffer"]) + guard let outputBuffer = sharedOutputPixelBuffer else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get shared output pixel buffer"]) } - // Process image + // Process image - use Accelerate for scaling when possible, fallback to Core Image for complex transforms CVPixelBufferLockBaseAddress(pixelBuffer, .readOnly) CVPixelBufferLockBaseAddress(outputBuffer, []) defer { @@ -846,26 +836,58 @@ class MLInferenceManager: ObservableObject { CVPixelBufferUnlockBaseAddress(pixelBuffer, .readOnly) } - let inputImage = CIImage(cvPixelBuffer: pixelBuffer) let inputImageSize = CGSize(width: CVPixelBufferGetWidth(pixelBuffer), height: CVPixelBufferGetHeight(pixelBuffer)) let scaleX = targetSize.width / inputImageSize.width let scaleY = targetSize.height / inputImageSize.height - let scaleTransform = CGAffineTransform(scaleX: scaleX, y: scaleY) - var scaledImage = inputImage.transformed(by: scaleTransform) - if applyServerImageOrientation { - scaledImage = scaledImage.oriented(.down) + // Use vImage for simple scaling (no rotation/orientation), Core Image for complex transforms + if !applyServerImageOrientation && abs(scaleX - scaleY) < 0.01 { + // Simple uniform scaling - use vImage for better performance + if processFrameWithVImage(pixelBuffer: pixelBuffer, outputBuffer: outputBuffer, scale: Float(scaleX)) { + // vImage scaling succeeded, now apply gripper overlay if needed + let scaledCIImage = CIImage(cvPixelBuffer: outputBuffer) + var finalImage = scaledCIImage + + if shouldApplyGripperOverlay(), let gripperOverlay = getCurrentGripperOverlay() { + finalImage = applyGripperOverlayCoreImage(to: scaledCIImage, overlay: gripperOverlay) + } + + // Render final image to output buffer + let cropRect = CGRect(origin: .zero, size: targetSize) + ciContext.render(finalImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) + } else { + // Fallback to Core Image pipeline + let inputImage = CIImage(cvPixelBuffer: pixelBuffer) + var scaledImage = inputImage.transformed(by: CGAffineTransform(scaleX: scaleX, y: scaleY)) + + // Save original scaled image for debugging + saveDebugFrame(scaledImage, prefix: "\(debugPrefix)_original") + + // Apply gripper overlay when USB streaming is off (virtual gripper proxy) + scaledImage = applyGripperOverlay(to: scaledImage) + saveDebugFrame(scaledImage, prefix: "\(debugPrefix)_with_overlay") + + let cropRect = CGRect(origin: .zero, size: targetSize) + ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) + } + } else { + // Complex transform (rotation/orientation) - use Core Image + let inputImage = CIImage(cvPixelBuffer: pixelBuffer) + var scaledImage = inputImage.transformed(by: CGAffineTransform(scaleX: scaleX, y: scaleY)) + if applyServerImageOrientation { + scaledImage = scaledImage.oriented(.down) + } + + // Save original scaled image for debugging + saveDebugFrame(scaledImage, prefix: "\(debugPrefix)_original") + + // Apply gripper overlay when USB streaming is off (virtual gripper proxy) + scaledImage = applyGripperOverlay(to: scaledImage) + saveDebugFrame(scaledImage, prefix: "\(debugPrefix)_with_overlay") + + let cropRect = CGRect(origin: .zero, size: targetSize) + ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) } - - // Save original scaled image for debugging - saveDebugFrame(scaledImage, prefix: "\(debugPrefix)_original") - - // Apply gripper overlay when USB streaming is off (virtual gripper proxy) - scaledImage = applyGripperOverlay(to: scaledImage) - saveDebugFrame(scaledImage, prefix: "\(debugPrefix)_with_overlay") - - let cropRect = CGRect(origin: .zero, size: targetSize) - ciContext.render(scaledImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) // Convert to MLMultiArray as single frame [1,3,H,W] for buffering return try convertPixelBufferToMLMultiArray(outputBuffer, width: width, height: height) @@ -873,12 +895,72 @@ class MLInferenceManager: ObservableObject { // MARK: - Unified Pixel Buffer to MLMultiArray Conversion (Accelerate Optimized) private func convertPixelBufferToMLMultiArray(_ pixelBuffer: CVPixelBuffer, width: Int, height: Int) throws -> MLMultiArray { + // Create new MLMultiArray (can't reuse since it's stored in frameBuffer) let inputArray = try MLMultiArray(shape: [1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get pixel buffer base address"]) } + let bytesPerRow = CVPixelBufferGetBytesPerRow(pixelBuffer) + let totalPixels = width * height + + // Use Accelerate for faster conversion + let rPtr = inputArray.dataPointer.assumingMemoryBound(to: Float.self) + let gPtr = rPtr.advanced(by: totalPixels) + let bPtr = gPtr.advanced(by: totalPixels) + + // Use vDSP for efficient channel extraction and conversion + // ARGB format: [A, R, G, B, A, R, G, B, ...] + // We need to extract R (offset 1), G (offset 2), B (offset 3) from each 4-byte pixel + + let buffer = baseAddress.assumingMemoryBound(to: UInt8.self) + let tempBufferSize = totalPixels * MemoryLayout.size + guard let tempR = malloc(tempBufferSize), + let tempG = malloc(tempBufferSize), + let tempB = malloc(tempBufferSize) else { + // Fallback to manual conversion if memory allocation fails + return try convertPixelBufferToMLMultiArrayManual(pixelBuffer: pixelBuffer, inputArray: inputArray, width: width, height: height) + } + defer { + free(tempR) + free(tempG) + free(tempB) + } + + // Extract channels using optimized stride-based approach + var pixelIndex = 0 + for y in 0.. MLMultiArray { + guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { + throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get pixel buffer base address"]) + } + let buffer = baseAddress.assumingMemoryBound(to: UInt8.self) let bytesPerRow = CVPixelBufferGetBytesPerRow(pixelBuffer) let totalPixels = width * height @@ -902,6 +984,40 @@ class MLInferenceManager: ObservableObject { return inputArray } + // MARK: - vImage Scaling (Accelerate Optimized) + /// Scale pixel buffer using vImage for better performance (simple scaling only) + private func processFrameWithVImage(pixelBuffer: CVPixelBuffer, outputBuffer: CVPixelBuffer, scale: Float) -> Bool { + guard let inputBase = CVPixelBufferGetBaseAddress(pixelBuffer), + let outputBase = CVPixelBufferGetBaseAddress(outputBuffer) else { + return false + } + + let inputWidth = CVPixelBufferGetWidth(pixelBuffer) + let inputHeight = CVPixelBufferGetHeight(pixelBuffer) + let outputWidth = CVPixelBufferGetWidth(outputBuffer) + let outputHeight = CVPixelBufferGetHeight(outputBuffer) + let inputBytesPerRow = CVPixelBufferGetBytesPerRow(pixelBuffer) + let outputBytesPerRow = CVPixelBufferGetBytesPerRow(outputBuffer) + + var sourceBuffer = vImage_Buffer( + data: inputBase, + height: vImagePixelCount(inputHeight), + width: vImagePixelCount(inputWidth), + rowBytes: inputBytesPerRow + ) + + var destBuffer = vImage_Buffer( + data: outputBase, + height: vImagePixelCount(outputHeight), + width: vImagePixelCount(outputWidth), + rowBytes: outputBytesPerRow + ) + + // Use vImageScale_ARGB8888 for fast scaling + let error = vImageScale_ARGB8888(&sourceBuffer, &destBuffer, nil, vImage_Flags(kvImageHighQualityResampling)) + return error == kvImageNoError + } + // MARK: - Result Processing /// Extract joint positions from model output, handling both single-step and multi-step outputs @@ -929,110 +1045,52 @@ class MLInferenceManager: ObservableObject { return } - // Simple approach for non-point conditioned models - match old working code - if metadata.modelType == .standard { - // Prefer primary output name when available - let outputFeatureName = metadata.primaryOutputName ?? output.featureNames.first + // Point-conditioned models only + let outputFeatureName = metadata.primaryOutputName ?? output.featureNames.first + + guard let outputFeatureName = outputFeatureName, + let resultArray = output.featureValue(for: outputFeatureName)?.multiArrayValue else { + return + } + + // Extract values (handles both single-step and multi-step outputs) + let jointPositions = extractJointPositions(from: resultArray) + + // Update gripper value for overlay switching (7th element, index 6) + if jointPositions.count >= 7 { + currentGripperValue = jointPositions[6] + let isGripperClosed = currentGripperValue < 0.7 + print("[ML] PointCond - Gripper Value: \(String(format: "%.3f", currentGripperValue)) | State: \(isGripperClosed ? "CLOSED" : "OPEN")") - guard let outputFeatureName = outputFeatureName, - let resultArray = output.featureValue(for: outputFeatureName)?.multiArrayValue else { - return - } - - // Extract values (handles both single-step and multi-step outputs) - let jointPositions = extractJointPositions(from: resultArray) - - // Update gripper value for overlay switching (7th element, index 6) - if jointPositions.count >= 7 { - currentGripperValue = jointPositions[6] - let isGripperClosed = currentGripperValue < 0.7 - print("[ML] Standard - Gripper Value: \(String(format: "%.3f", currentGripperValue)) | State: \(isGripperClosed ? "CLOSED" : "OPEN")") - - Task { @MainActor [weak self] in - self?.updateGripperOverlayDisplay() - // Update AR visualization manager gripper state to stop visualization when closed - self?.arVisualizationManager?.setGripperState(isClosed: isGripperClosed) - } + Task { @MainActor [weak self] in + self?.updateGripperOverlayDisplay() + // Update AR visualization manager gripper state to stop visualization when closed + self?.arVisualizationManager?.setGripperState(isClosed: isGripperClosed) } + } - let result = InferenceResult( - jointPositions: jointPositions, - inferenceTime: inferenceTime - ) - - // Update UI on main thread - DispatchQueue.main.async { [weak self] in - self?.latestResult = result - - // Ensure visualization is ready and feed pose - if let arManager = self?.arVisualizationManager, jointPositions.count >= 6 { - arManager.ensureVisualizationReady() - arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) - } - - // Joint actions are automatically sent via USB stream (transform to robot frame) - if jointPositions.count >= 7 { - let src = Array(jointPositions.prefix(7)) - if self?.enableTransformDebug == true { - let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) - print("Coordinate Transform:\n\(report)") - } - } - } - - } else { - // Point-conditioned models - let outputFeatureName = metadata.primaryOutputName ?? output.featureNames.first + let result = InferenceResult( + jointPositions: jointPositions, + inferenceTime: inferenceTime + ) + + // Update UI on main thread + DispatchQueue.main.async { [weak self] in + self?.latestResult = result - guard let outputFeatureName = outputFeatureName, - let resultArray = output.featureValue(for: outputFeatureName)?.multiArrayValue else { - return + // Ensure visualization is ready and feed pose + if let arManager = self?.arVisualizationManager, jointPositions.count >= 6 { + arManager.ensureVisualizationReady() + arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } - // Extract values (handles both single-step and multi-step outputs) - let jointPositions = extractJointPositions(from: resultArray) - - // Update gripper value for overlay switching (7th element, index 6) + // Joint actions are automatically sent via USB stream (transform to robot frame) if jointPositions.count >= 7 { - currentGripperValue = jointPositions[6] - let isGripperClosed = currentGripperValue < 0.7 - print("[ML] PointCond - Gripper Value: \(String(format: "%.3f", currentGripperValue)) | State: \(isGripperClosed ? "CLOSED" : "OPEN")") - - Task { @MainActor [weak self] in - self?.updateGripperOverlayDisplay() - // Update AR visualization manager gripper state to stop visualization when closed - self?.arVisualizationManager?.setGripperState(isClosed: isGripperClosed) - } - } - - let result = InferenceResult( - jointPositions: jointPositions, - inferenceTime: inferenceTime - ) - - // Update UI on main thread - DispatchQueue.main.async { [weak self] in - self?.latestResult = result - - // Ensure visualization is ready and feed pose - if let arManager = self?.arVisualizationManager, jointPositions.count >= 6 { - arManager.ensureVisualizationReady() - arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) + let src = Array(jointPositions.prefix(7)) + if self?.enableTransformDebug == true { + let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) + print("Coordinate Transform:\n\(report)") } - - // Joint actions are automatically sent via USB stream (transform to robot frame) - if jointPositions.count >= 7 { - let src = Array(jointPositions.prefix(7)) - if self?.enableTransformDebug == true { - let report = ActionTransformUtils.debugTransformReport(src, rotationUnit: self?.rotationUnit ?? .eulerXYZ) - print("Coordinate Transform:\n\(report)") - } - } - } - - // Log goal point status for point-conditioned models - if metadata.requiresGoalPoint, let goalPoint = currentGoalPoint { - // Goal point logging removed for cleanliness } } } @@ -1059,6 +1117,7 @@ class MLInferenceManager: ObservableObject { isInferencePending = false frameBuffer.removeAll() currentFrameEntry = nil + goalFrameCount = 0 // Reset goal frame count print("Inference state reset - ready for new recording") } diff --git a/AnySense/Managers/ModelManager.swift b/AnySense/Managers/ModelManager.swift index 438ca4c..c1a8395 100644 --- a/AnySense/Managers/ModelManager.swift +++ b/AnySense/Managers/ModelManager.swift @@ -107,33 +107,53 @@ class ModelManager: ObservableObject { // MARK: - Bundled Model Setup private func setupBundledModel() { - // Register both standard and point-conditioned bundled models if present - let bundledNames = ["GeneralPickUpV1", "general-pick-up-goal-3-5k-demos"] + // Register the default bundled model if present + let defaultModelName = "sam2-jitter" // Default bundled model var added: [ModelInfo] = [] - for name in bundledNames { - let alreadyExists = availableModels.contains { $0.source == .bundled && $0.name == name } - guard !alreadyExists else { continue } - // Only add if the resource actually exists in the bundle with any supported extension - let presentInBundle = - Bundle.main.url(forResource: name, withExtension: "mlmodelc") != nil || - Bundle.main.url(forResource: name, withExtension: "mlpackage") != nil || - Bundle.main.url(forResource: name, withExtension: "mlmodel") != nil - guard presentInBundle else { continue } - var info = ModelInfo( - name: name, - fileName: "\(name).mlmodel", - source: .bundled - ) - info.compilationStatus = .compiled - availableModels.append(info) - added.append(info) + + let alreadyExists = availableModels.contains { $0.source == .bundled && $0.name == defaultModelName } + guard !alreadyExists else { + // Model already registered, just ensure it's active if no active model + if activeModel == nil, let bundledModel = availableModels.first(where: { $0.source == .bundled && $0.name == defaultModelName }) { + setActiveModel(id: bundledModel.id) + print("Set default model: \(bundledModel.name)") + } + return + } + + // Check if the resource exists in the bundle (try .mlpackage first, then .mlmodelc, then .mlmodel) + var modelURL: URL? + if let url = Bundle.main.url(forResource: defaultModelName, withExtension: "mlpackage") { + modelURL = url + } else if let url = Bundle.main.url(forResource: defaultModelName, withExtension: "mlmodelc") { + modelURL = url + } else if let url = Bundle.main.url(forResource: defaultModelName, withExtension: "mlmodel") { + modelURL = url } - // Set a default active model if none is active yet + + guard let url = modelURL else { + print("Bundled model '\(defaultModelName)' not found in app bundle - user will need to upload a model") + return + } + + // Determine file extension for fileName + let ext = url.pathExtension.isEmpty ? "mlpackage" : url.pathExtension + var info = ModelInfo( + name: defaultModelName, + fileName: "\(defaultModelName).\(ext)", + source: .bundled + ) + info.compilationStatus = .compiled + availableModels.append(info) + added.append(info) + print("Registered bundled model: \(defaultModelName)") + + // Set as default active model if none is active yet if activeModel == nil { - if let preferred = availableModels.first(where: { $0.source == .bundled && $0.name == "GeneralPickUpV1" }) ?? added.first { - setActiveModel(id: preferred.id) - } + setActiveModel(id: info.id) + print("Set default model: \(defaultModelName)") } + if !added.isEmpty { saveModelRegistry() } } @@ -216,18 +236,36 @@ class ModelManager: ObservableObject { saveModelRegistry() } + // Update progress: file copied/prepared + await MainActor.run { + compilationProgress = 0.2 + } + // If we imported a raw .mlmodel, compile it now if (ext == "mlmodel" || ext == "mlpackage"), let local = localModelURL { + await MainActor.run { + compilationProgress = 0.3 + } + let tempCompiledURL = try await MLModel.compileModel(at: local) { [weak self] progress in - DispatchQueue.main.async { self?.compilationProgress = progress } + Task { @MainActor in + // Map compile progress (0.0-1.0) to overall progress (0.3-0.9) + self?.compilationProgress = 0.3 + (progress * 0.6) + } } print("DEBUG: Compiled to temp location: \(tempCompiledURL.path)") + + await MainActor.run { + compilationProgress = 0.9 + } + // Validate compiled do { let metadata = try MLModel.validateModel(at: tempCompiledURL) guard metadata.isCompatible else { throw ModelError.incompatibleModel("Model format not compatible with app requirements") } print("DEBUG: Model validation passed") } catch { print("DEBUG: Model validation warning: \(error.localizedDescription)") } + // Move compiled to uploads dir finalCompiledURL = try ModelFileUtilities.replaceCompiledModel( compiledURL: tempCompiledURL, @@ -235,6 +273,10 @@ class ModelManager: ObservableObject { ) print("DEBUG: Final compiled location: \(finalCompiledURL!.path)") } else if let compiled = finalCompiledURL { + await MainActor.run { + compilationProgress = 0.5 + } + // Validate mlpackage/mlmodelc directly do { let metadata = try MLModel.validateModel(at: compiled) diff --git a/AnySense/Managers/USBManager.swift b/AnySense/Managers/USBManager.swift index eee0f05..9c7c233 100644 --- a/AnySense/Managers/USBManager.swift +++ b/AnySense/Managers/USBManager.swift @@ -62,9 +62,9 @@ class USBManager { listener?.stateUpdateHandler = { state in switch state { case .ready: - break + print("USB listener ready") case .failed(let error): - break + print("USB listener failed: \(error)") default: break } diff --git a/AnySense/Views/MLInferenceResultsView.swift b/AnySense/Views/MLInferenceResultsView.swift index 8b9445e..ab31358 100644 --- a/AnySense/Views/MLInferenceResultsView.swift +++ b/AnySense/Views/MLInferenceResultsView.swift @@ -48,11 +48,11 @@ private struct GripperBlock: View { } private var gripperState: String { - return gripperValue < 0.6 ? "CLOSED" : "OPEN" + return gripperValue < 0.7 ? "CLOSED" : "OPEN" } private var stateColor: Color { - return gripperValue < 0.6 ? .red : .green + return gripperValue < 0.7 ? .red : .green } var body: some View { diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index e6305d0..16ca296 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -215,41 +215,6 @@ struct SettingsView : View{ } } } - - // MARK: - Cube Visualization Section - Section(header: Text("CUBE VISUALIZATION")) { - VStack(alignment: .leading, spacing: 8) { - Text("Visualization Status") - .font(.body) - .foregroundColor(.primary) - - HStack { - Text("Status:") - .font(.caption) - .foregroundColor(.gray) - Spacer() - Text(arViewModel.arVisualizationManager.isVisualizationEnabled ? "Active" : "Inactive") - .font(.caption) - .foregroundColor(arViewModel.arVisualizationManager.isVisualizationEnabled ? .green : .orange) - } - - HStack { - Text("Action State:") - .font(.caption) - .foregroundColor(.gray) - Spacer() - Text(arViewModel.arVisualizationManager.actionState.displayName) - .font(.caption) - .foregroundColor(arViewModel.arVisualizationManager.actionState == .waiting ? .yellow : .green) - } - - Text("Shows blue cube (current) and green cube (target) for action guidance") - .font(.caption2) - .foregroundColor(.gray) - .padding(.top, 4) - } - .padding(.vertical, 5) - } } .scrollContentBackground(.hidden) } diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index f6f266a..52cb184 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -36,7 +36,6 @@ struct ReadView : View{ let arViewWidth = min(arViewHeight / 1.33, screenWidth) let arViewPadding = 0.2 * arViewHeight let buttonSize: CGFloat = min(screenWidth * 0.3, 100) -// let buttonPadding: CGFloat = let btBarHeight: CGFloat = 25.0 let gridSize = appStatus.gridProjectionTrigger.rawValue @@ -103,46 +102,25 @@ struct ReadView : View{ } // Action State Display (cube visualization status) - if arViewModel.arVisualizationManager.isVisualizationEnabled { - HStack(spacing: 4) { - Text("Next action:") - .font(.caption) - .foregroundColor(.white) - Text(arViewModel.arVisualizationManager.actionState.displayName) - .font(.caption) - .bold() - .foregroundColor(arViewModel.arVisualizationManager.actionState == .waiting ? .yellow : .green) - } - .padding(8) - .background(Color.black.opacity(0.6)) - .cornerRadius(8) - } + // if arViewModel.arVisualizationManager.isVisualizationEnabled { + // HStack(spacing: 4) { + // Text("Next action:") + // .font(.caption) + // .foregroundColor(.white) + // Text(arViewModel.arVisualizationManager.actionState.displayName) + // .font(.caption) + // .bold() + // .foregroundColor(arViewModel.arVisualizationManager.actionState == .waiting ? .yellow : .green) + // } + // .padding(8) + // .background(Color.black.opacity(0.6)) + // .cornerRadius(8) + // } } Spacer() } Spacer() - // AR Visualization Status Overlay - // HStack { - // VStack(alignment: .leading, spacing: 4) { - // if arViewModel.arVisualizationManager.isVisualizationEnabled { - // Text("Movement Tracking: ON") - // .font(.caption) - // .foregroundColor(.green) - // Text("Max Arrows: \(arViewModel.arVisualizationManager.maxArrows)") - // .font(.caption2) - // .foregroundColor(.secondary) - // } else { - // Text("Movement Tracking: OFF") - // .font(.caption) - // .foregroundColor(.red) - // } - // } - // .padding(8) - // .background(Color.black.opacity(0.6)) - // .cornerRadius(8) - // Spacer() - // } .padding(.bottom, 10) } .frame(width: arViewWidth, height: arViewHeight) From c35571ad381218ebd22e04e66fcc5ca9f99695e2 Mon Sep 17 00:00:00 2001 From: DjKesu Date: Tue, 25 Nov 2025 19:48:32 -0500 Subject: [PATCH 46/56] fixed frame buffering --- AnySense.xcodeproj/project.pbxproj | 8 +- AnySense/Managers/MLInferenceManager.swift | 87 +++++++++++++++------- 2 files changed, 65 insertions(+), 30 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index fad8dc3..45d0d72 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -7,10 +7,10 @@ objects = { /* Begin PBXBuildFile section */ - 01214E392ED25092009E565F /* sam2-jitter.mlpackage in Sources */ = {isa = PBXBuildFile; fileRef = 01214E372ED25092009E565F /* sam2-jitter.mlpackage */; }; 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */; }; 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */; }; 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */; }; + 01B77E672ED6681D007823B6 /* checkpoint_90.mlpackage in Sources */ = {isa = PBXBuildFile; fileRef = 01B77E662ED6681D007823B6 /* checkpoint_90.mlpackage */; }; 01D2FDD82E64C33600F0BA98 /* ActionTransformUtils.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */; }; 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */; }; 01F5B7C62DEA698D00061B16 /* MLInferenceResultsView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */; }; @@ -49,8 +49,8 @@ /* End PBXContainerItemProxy section */ /* Begin PBXFileReference section */ - 01214E372ED25092009E565F /* sam2-jitter.mlpackage */ = {isa = PBXFileReference; lastKnownFileType = folder.mlpackage; path = "sam2-jitter.mlpackage"; sourceTree = ""; }; 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARVisualizationManager.swift; sourceTree = ""; }; + 01B77E662ED6681D007823B6 /* checkpoint_90.mlpackage */ = {isa = PBXFileReference; lastKnownFileType = folder.mlpackage; path = checkpoint_90.mlpackage; sourceTree = ""; }; 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ActionTransformUtils.swift; sourceTree = ""; }; 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceManager.swift; sourceTree = ""; }; 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceResultsView.swift; sourceTree = ""; }; @@ -105,7 +105,7 @@ 01214E382ED25092009E565F /* Models */ = { isa = PBXGroup; children = ( - 01214E372ED25092009E565F /* sam2-jitter.mlpackage */, + 01B77E662ED6681D007823B6 /* checkpoint_90.mlpackage */, ); path = Models; sourceTree = ""; @@ -354,6 +354,7 @@ B9E4B2372D62A9C40032E877 /* accountView.swift in Sources */, B9E4B2382D62A9C40032E877 /* readView.swift in Sources */, B9E4B2392D62A9C40032E877 /* ContentView.swift in Sources */, + 01B77E672ED6681D007823B6 /* checkpoint_90.mlpackage in Sources */, B997CCD52D4E082900F62B49 /* AnySenseApp.swift in Sources */, B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */, 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */, @@ -364,7 +365,6 @@ B9E4B22F2D62A9BA0032E877 /* ARViewContainer.swift in Sources */, B9E4B2302D62A9BA0032E877 /* USBManager.swift in Sources */, 01F5B7C62DEA698D00061B16 /* MLInferenceResultsView.swift in Sources */, - 01214E392ED25092009E565F /* sam2-jitter.mlpackage in Sources */, B9944A342CFE983300232FBB /* MainPage.swift in Sources */, ); runOnlyForDeploymentPostprocessing = 0; diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 9a31f13..302dccf 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -5,6 +5,9 @@ // Created by Krish on 2025/2/1. // +// @TODO: CHECK COREML MODEL PREDICTIONS AND COMPARE. +// @TODO: CHECK FRAME BUFFERING IN USB STREAMING MODE ON + import Foundation import ImageIO import CoreML @@ -558,6 +561,15 @@ class MLInferenceManager: ObservableObject { print("[MLInference] Proximity reached - inference will trigger with next frame (firstInference: \(hasRunFirstInference))") } + // MARK: - Frequency-based Inference Helper + private func shouldRunBasedOnFrequency(_ timestamp: CFTimeInterval) -> Bool { + let interval = inferenceFrequency.interval + if interval == 0.0 { + return true // High frequency - every frame + } + return (timestamp - lastInferenceTime) >= interval + } + // MARK: - Inference Methods (Using existing frame processing patterns) func performInference(on pixelBuffer: CVPixelBuffer, arFrame: ARFrame?, timestamp: CFTimeInterval = CACurrentMediaTime()) { // Update device pose for visualization (optional) @@ -589,29 +601,44 @@ class MLInferenceManager: ObservableObject { return } - // Trigger inference: first time or proximity reached - let isFirstInference = !hasRunFirstInference - let isProximityTriggered = proximityReached && !isInferencePending - let shouldRunInference = isFirstInference || isProximityTriggered - - guard shouldRunInference else { - return - } - - // Store current frame as an action trigger frame + // Store current frame entry for buffering guard let currentEntry = currentFrameEntry else { - print("ERROR: No current frame entry available for action trigger") + print("ERROR: No current frame entry available") return } - frameBuffer.append(currentEntry) + let isFirstInference = !hasRunFirstInference + let shouldRunInference: Bool + + if isUSBStreamingActive { + // USB ON: Continuously add frames to buffer (rolling 3-frame window) + frameBuffer.append(currentEntry) + if frameBuffer.count > maxBufferSize { + frameBuffer.removeFirst() + } + print("[MLInference] USB Mode: Frame added to rolling buffer (\(frameBuffer.count)/\(maxBufferSize))") + + // Run inference based on frequency setting or first inference + shouldRunInference = isFirstInference || shouldRunBasedOnFrequency(timestamp) + } else { + // USB OFF: Proximity-triggered buffering for recording mode + let isProximityTriggered = proximityReached && !isInferencePending + shouldRunInference = isFirstInference || isProximityTriggered + + guard shouldRunInference else { + return // Don't add to buffer unless inference is triggered + } - // Maintain buffer of last 3 action trigger frames - if frameBuffer.count > maxBufferSize { - frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) + frameBuffer.append(currentEntry) + if frameBuffer.count > maxBufferSize { + frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) + } + print("[MLInference] Recording Mode: Action frame stored (\(frameBuffer.count) action trigger frames)") } - print("[MLInference] Action frame stored - buffer now contains \(frameBuffer.count) action trigger frames") + guard shouldRunInference else { + return + } // Temporal models pad with repeated frames if needed @@ -656,6 +683,7 @@ class MLInferenceManager: ObservableObject { // Reset pending flag and mark first inference complete DispatchQueue.main.async { self.isInferencePending = false + self.lastInferenceTime = CACurrentMediaTime() // Update for frequency tracking if !self.hasRunFirstInference { self.hasRunFirstInference = true print("[MLInference] First inference complete - target cube should now be visible") @@ -1078,8 +1106,8 @@ class MLInferenceManager: ObservableObject { DispatchQueue.main.async { [weak self] in self?.latestResult = result - // Ensure visualization is ready and feed pose - if let arManager = self?.arVisualizationManager, jointPositions.count >= 6 { + // Only enable visualization when NOT in USB streaming mode (recording mode only) + if let arManager = self?.arVisualizationManager, jointPositions.count >= 6, !self?.isUSBStreamingActive { arManager.ensureVisualizationReady() arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } @@ -1147,23 +1175,29 @@ class MLInferenceManager: ObservableObject { return } - // Store current frame as action trigger frame + // Store current frame for manual trigger guard let currentEntry = currentFrameEntry else { print("[MLInference] Cannot trigger manually - no current frame available") return } - frameBuffer.append(currentEntry) - - // Maintain buffer of last 3 action trigger frames - if frameBuffer.count > maxBufferSize { - frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) + // Add frame to buffer following same logic as automatic inference + if isUSBStreamingActive { + frameBuffer.append(currentEntry) + if frameBuffer.count > maxBufferSize { + frameBuffer.removeFirst() + } + print("[MLInference] Manual trigger - USB mode: Frame added to rolling buffer (\(frameBuffer.count))") + } else { + frameBuffer.append(currentEntry) + if frameBuffer.count > maxBufferSize { + frameBuffer.removeFirst(frameBuffer.count - maxBufferSize) + } + print("[MLInference] Manual trigger - Recording mode: Action frame stored (\(frameBuffer.count))") } // Mark inference as pending isInferencePending = true - - print("[MLInference] Manual trigger - action frame stored, running inference with buffered action frames (\(frameBuffer.count))") // Prepare input using buffered frames let modelInput: MLFeatureProvider @@ -1192,6 +1226,7 @@ class MLInferenceManager: ObservableObject { // Reset pending flag and mark first inference complete DispatchQueue.main.async { self.isInferencePending = false + self.lastInferenceTime = CACurrentMediaTime() // Update for frequency tracking if !self.hasRunFirstInference { self.hasRunFirstInference = true print("[MLInference] First inference complete (manual) - target cube should now be visible") From bebcd05f3d53c5b0c658a10f69eb2d36065e3ed6 Mon Sep 17 00:00:00 2001 From: DjKesu Date: Wed, 26 Nov 2025 22:47:41 -0500 Subject: [PATCH 47/56] usb streaming with no visuals --- AnySense/Managers/ARViewContainer.swift | 5 ----- AnySense/Managers/ActionTransformUtils.swift | 3 ++- AnySense/Managers/MLInferenceManager.swift | 2 +- 3 files changed, 3 insertions(+), 7 deletions(-) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 5209825..83d4ce1 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -288,14 +288,9 @@ class ARViewModel: ObservableObject{ self.goalTapModeEnabled = false return } - // No worldPoint provided (no raycast hit) — ignore tap } } - - - - func getBLEManagerInstance() -> BluetoothManager{ return bluetoothManager!; } diff --git a/AnySense/Managers/ActionTransformUtils.swift b/AnySense/Managers/ActionTransformUtils.swift index 1fa3128..12f883d 100644 --- a/AnySense/Managers/ActionTransformUtils.swift +++ b/AnySense/Managers/ActionTransformUtils.swift @@ -6,7 +6,7 @@ struct ActionTransformUtils { case eulerXYZ // rx, ry, rz (radians) case axisAngle // rotation vector (axis * angle) } - // Server-defined transforms (record3d → personal camera) and +90° about Z + // arkit camera frame to labels.json frame private static let P: simd_float4x4 = { let c0 = SIMD4(-1, 0, 0, 0) let c1 = SIMD4( 0, 0, -1, 0) @@ -15,6 +15,7 @@ struct ActionTransformUtils { return simd_float4x4(columns: (c0, c1, c2, c3)) }() + // labels.json frame to robot frame private static let Z90: simd_float4x4 = { let c0 = SIMD4( 0, 1, 0, 0) let c1 = SIMD4(-1, 0, 0, 0) diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 302dccf..261bc4d 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -1107,7 +1107,7 @@ class MLInferenceManager: ObservableObject { self?.latestResult = result // Only enable visualization when NOT in USB streaming mode (recording mode only) - if let arManager = self?.arVisualizationManager, jointPositions.count >= 6, !self?.isUSBStreamingActive { + if let arManager = self?.arVisualizationManager, jointPositions.count >= 6, self?.isUSBStreamingActive != true { arManager.ensureVisualizationReady() arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } From f07f62bfdaff4779ebea0485e74213da2eacb74d Mon Sep 17 00:00:00 2001 From: DjKesu Date: Thu, 27 Nov 2025 23:48:07 -0500 Subject: [PATCH 48/56] fixed layout issues, updated managers, and ignored large mlpackage --- .gitignore | 1 + AnySense.xcodeproj/project.pbxproj | 16 +- AnySense/Managers/MLInferenceManager.swift | 3 - AnySense/Managers/ModelManager.swift | 57 ++++-- AnySense/Views/readView.swift | 220 ++++++++++++--------- 5 files changed, 169 insertions(+), 128 deletions(-) diff --git a/.gitignore b/.gitignore index 195b6a1..e936de5 100644 --- a/.gitignore +++ b/.gitignore @@ -68,5 +68,6 @@ fastlane/test_output # Models Models/ +*.mlpackage AnySense.xcodeproj/project.xcworkspace/xcshareddata/swiftpm/ AnySense.xcworkspace/xcshareddata/swiftpm/ diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 45d0d72..40672fa 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -10,7 +10,7 @@ 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */; }; 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */; }; 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */; }; - 01B77E672ED6681D007823B6 /* checkpoint_90.mlpackage in Sources */ = {isa = PBXBuildFile; fileRef = 01B77E662ED6681D007823B6 /* checkpoint_90.mlpackage */; }; + 01B77E6D2ED94950007823B6 /* demo.mlpackage in Resources */ = {isa = PBXBuildFile; fileRef = 01B77E6C2ED94950007823B6 /* demo.mlpackage */; }; 01D2FDD82E64C33600F0BA98 /* ActionTransformUtils.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */; }; 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */; }; 01F5B7C62DEA698D00061B16 /* MLInferenceResultsView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */; }; @@ -50,7 +50,7 @@ /* Begin PBXFileReference section */ 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARVisualizationManager.swift; sourceTree = ""; }; - 01B77E662ED6681D007823B6 /* checkpoint_90.mlpackage */ = {isa = PBXFileReference; lastKnownFileType = folder.mlpackage; path = checkpoint_90.mlpackage; sourceTree = ""; }; + 01B77E6C2ED94950007823B6 /* demo.mlpackage */ = {isa = PBXFileReference; lastKnownFileType = folder.mlpackage; path = demo.mlpackage; sourceTree = ""; }; 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ActionTransformUtils.swift; sourceTree = ""; }; 01F5B7C32DEA697200061B16 /* MLInferenceManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceManager.swift; sourceTree = ""; }; 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MLInferenceResultsView.swift; sourceTree = ""; }; @@ -102,14 +102,6 @@ /* End PBXFrameworksBuildPhase section */ /* Begin PBXGroup section */ - 01214E382ED25092009E565F /* Models */ = { - isa = PBXGroup; - children = ( - 01B77E662ED6681D007823B6 /* checkpoint_90.mlpackage */, - ); - path = Models; - sourceTree = ""; - }; B9104F512BFDE63A000D4DDD = { isa = PBXGroup; children = ( @@ -132,8 +124,8 @@ B9104F5C2BFDE63A000D4DDD /* AnySense */ = { isa = PBXGroup; children = ( - 01214E382ED25092009E565F /* Models */, 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */, + 01B77E6C2ED94950007823B6 /* demo.mlpackage */, 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */, B9944A332CFE982E00232FBB /* MainPage.swift */, B997CCD22D4E081300F62B49 /* dataStorage.swift */, @@ -295,6 +287,7 @@ isa = PBXResourcesBuildPhase; buildActionMask = 2147483647; files = ( + 01B77E6D2ED94950007823B6 /* demo.mlpackage in Resources */, B9104F622BFDE63C000D4DDD /* Assets.xcassets in Resources */, B9E4D2B42D6965B90044F2D4 /* AnySenseLaunchScreen.storyboard in Resources */, ); @@ -354,7 +347,6 @@ B9E4B2372D62A9C40032E877 /* accountView.swift in Sources */, B9E4B2382D62A9C40032E877 /* readView.swift in Sources */, B9E4B2392D62A9C40032E877 /* ContentView.swift in Sources */, - 01B77E672ED6681D007823B6 /* checkpoint_90.mlpackage in Sources */, B997CCD52D4E082900F62B49 /* AnySenseApp.swift in Sources */, B997CCD32D4E081300F62B49 /* dataStorage.swift in Sources */, 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */, diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 261bc4d..34f2888 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -5,9 +5,6 @@ // Created by Krish on 2025/2/1. // -// @TODO: CHECK COREML MODEL PREDICTIONS AND COMPARE. -// @TODO: CHECK FRAME BUFFERING IN USB STREAMING MODE ON - import Foundation import ImageIO import CoreML diff --git a/AnySense/Managers/ModelManager.swift b/AnySense/Managers/ModelManager.swift index c1a8395..2fd5c8d 100644 --- a/AnySense/Managers/ModelManager.swift +++ b/AnySense/Managers/ModelManager.swift @@ -81,7 +81,12 @@ class ModelManager: ObservableObject { activeModel = nil } if activeModel == nil { - if let next = availableModels.first, getModelURL(for: next) != nil { + // Prioritize any bundled model, then fallback to any available model + let preferredModel = availableModels.first { model in + model.source == .bundled && getModelURL(for: model) != nil + } ?? availableModels.first { getModelURL(for: $0) != nil } + + if let next = preferredModel { // Directly set without dispatching to avoid race during init for i in availableModels.indices { availableModels[i].isActive = availableModels[i].id == next.id } activeModel = next @@ -107,8 +112,12 @@ class ModelManager: ObservableObject { // MARK: - Bundled Model Setup private func setupBundledModel() { - // Register the default bundled model if present - let defaultModelName = "sam2-jitter" // Default bundled model + // Find and register any bundled model dynamically + let bundledModelNames = findBundledModelNames() + guard let defaultModelName = bundledModelNames.first else { + print("No bundled CoreML models found - user will need to upload a model") + return + } var added: [ModelInfo] = [] let alreadyExists = availableModels.contains { $0.source == .bundled && $0.name == defaultModelName } @@ -121,18 +130,10 @@ class ModelManager: ObservableObject { return } - // Check if the resource exists in the bundle (try .mlpackage first, then .mlmodelc, then .mlmodel) - var modelURL: URL? - if let url = Bundle.main.url(forResource: defaultModelName, withExtension: "mlpackage") { - modelURL = url - } else if let url = Bundle.main.url(forResource: defaultModelName, withExtension: "mlmodelc") { - modelURL = url - } else if let url = Bundle.main.url(forResource: defaultModelName, withExtension: "mlmodel") { - modelURL = url - } - - guard let url = modelURL else { - print("Bundled model '\(defaultModelName)' not found in app bundle - user will need to upload a model") + // Find the model URL using existing logic + let tempModelInfo = ModelInfo(name: defaultModelName, fileName: "", source: .bundled) + guard let url = getModelURL(for: tempModelInfo) else { + print("Bundled model '\(defaultModelName)' not found in app bundle") return } @@ -152,10 +153,25 @@ class ModelManager: ObservableObject { if activeModel == nil { setActiveModel(id: info.id) print("Set default model: \(defaultModelName)") + } else { + print("Active model already exists: \(activeModel?.name ?? "Unknown")") } if !added.isEmpty { saveModelRegistry() } } + + private func findBundledModelNames() -> [String] { + let extensions = ["mlpackage", "mlmodelc", "mlmodel"] + var modelNames: [String] = [] + + for ext in extensions { + if let urls = Bundle.main.urls(forResourcesWithExtension: ext, subdirectory: nil) { + modelNames.append(contentsOf: urls.map { $0.deletingPathExtension().lastPathComponent }) + } + } + + return Array(Set(modelNames)) // Remove duplicates + } // MARK: - Model Upload and Compilation func uploadAndCompileModel(from sourceURL: URL, withName customName: String? = nil) async throws { @@ -378,11 +394,12 @@ class ModelManager: ObservableObject { func getModelURL(for modelInfo: ModelInfo) -> URL? { switch modelInfo.source { case .bundled: - // Try to get from bundle first - if let url = Bundle.main.url(forResource: modelInfo.name, withExtension: "mlmodelc") ?? - Bundle.main.url(forResource: modelInfo.name, withExtension: "mlpackage") ?? - Bundle.main.url(forResource: modelInfo.name, withExtension: "mlmodel") { - return url + // Use dynamic discovery for bundled models + let extensions = ["mlmodelc", "mlpackage", "mlmodel"] + for ext in extensions { + if let url = Bundle.main.url(forResource: modelInfo.name, withExtension: ext) { + return url + } } return nil diff --git a/AnySense/Views/readView.swift b/AnySense/Views/readView.swift index 52cb184..a69feb6 100644 --- a/AnySense/Views/readView.swift +++ b/AnySense/Views/readView.swift @@ -35,7 +35,7 @@ struct ReadView : View{ let arViewHeight = min(screenWidth * 1.33, 0.75 * screenHeight) let arViewWidth = min(arViewHeight / 1.33, screenWidth) let arViewPadding = 0.2 * arViewHeight - let buttonSize: CGFloat = min(screenWidth * 0.3, 100) + let buttonSize: CGFloat = min(screenWidth * 0.25, 80) let btBarHeight: CGFloat = 25.0 let gridSize = appStatus.gridProjectionTrigger.rawValue @@ -59,26 +59,55 @@ struct ReadView : View{ .scaledToFit() .allowsHitTesting(false) } + + // Instruction text when USB streaming is off and no gripper overlay + if appStatus.rgbdVideoStreaming == .off && + (arViewModel.mlManager?.currentGripperOverlayImage == nil) { + VStack { + Spacer() + Text("Follow the red cube") + .font(.system(size: 14, weight: .medium)) + .foregroundColor(.white) + .padding(.horizontal, 12) + .padding(.vertical, 6) + .background(Color.black.opacity(0.7)) + .cornerRadius(6) + .shadow(color: .black.opacity(0.4), radius: 3, x: 0, y: 1) + Spacer() + .frame(height: 60) + } + } - // Manual Next Action Button + // Manual Next Action Button if let mlManager = arViewModel.mlManager, appStatus.mlInferenceEnabled && mlManager.isInferenceEnabled { VStack { HStack { Spacer() - Button(action: { - mlManager.triggerInferenceManually() - UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() - }) { - Image(systemName: "arrow.forward.circle.fill") - .font(.title2) + VStack(spacing: 2) { + Button(action: { + mlManager.triggerInferenceManually() + UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() + }) { + Image(systemName: "arrow.forward.circle.fill") + .font(.title2) + .foregroundColor(.white) + .background( + Circle() + .fill(Color.blue.opacity(0.8)) + .frame(width: 44, height: 44) + ) + .shadow(color: .black.opacity(0.3), radius: 4, x: 0, y: 2) + } + + Text("Get next action") + .font(.system(size: 9, weight: .medium)) .foregroundColor(.white) - .background( - Circle() - .fill(Color.blue.opacity(0.8)) - .frame(width: 44, height: 44) - ) - .shadow(color: .black.opacity(0.3), radius: 4, x: 0, y: 2) + .padding(.horizontal, 4) + .padding(.vertical, 1) + .background(Color.black.opacity(0.7)) + .cornerRadius(3) + .shadow(color: .black.opacity(0.4), radius: 1, x: 0, y: 0.5) } .padding(.trailing, 12) .padding(.top, 12) @@ -162,105 +191,110 @@ struct ReadView : View{ Text("\(arViewModel.demosCounter)") .multilineTextAlignment(.leading) } - .padding(.top, 0.55 * arViewHeight + 0.2 * screenHeight) + .padding(.top, 0.55 * arViewHeight + 0.2 * screenHeight + 20) VStack { Spacer() - HStack(spacing: 20) { - // Delete (left) - VStack(spacing: 4) { - Button(action: { - if(isRecordedOnce){ - showingAlert = true - self.activeAlert = .first - } else { - showingAlert = true - self.activeAlert = .second - } - UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() - }){ - Image(systemName: "trash.circle.fill") - .resizable() - .frame(height: 36) - .frame(width: 36) - .foregroundStyle(.red) - } - Text("Delete") - .foregroundStyle(.red) - .font(.caption) - Text("last record") - .foregroundStyle(.red) - .font(.caption) - } - - Spacer() - - // Record button (center) - ZStack{ - Image(systemName: "circle") - .resizable() - .aspectRatio(contentMode: .fit) - .frame(height: buttonSize) - .frame(width: buttonSize) - .foregroundStyle(.deviceWord) - .multilineTextAlignment(.center) - Button(action: { - toggleRecording(mode:appStatus.rgbdVideoStreaming) - isRecordedOnce = true - }) { - Image(systemName: isReading ? "square.fill" : "circle.fill") + ZStack { + // Center Button Layer (Record Button) + HStack { + Spacer() + ZStack{ + Image(systemName: "circle") .resizable() .aspectRatio(contentMode: .fit) - .frame(height: buttonSize - 10) - .frame(width: buttonSize - 10) + .frame(height: buttonSize) + .frame(width: buttonSize) + .foregroundStyle(.deviceWord) .multilineTextAlignment(.center) - .foregroundStyle(Color.red) + Button(action: { + toggleRecording(mode:appStatus.rgbdVideoStreaming) + isRecordedOnce = true + }) { + Image(systemName: isReading ? "square.fill" : "circle.fill") + .resizable() + .aspectRatio(contentMode: .fit) + .frame(height: buttonSize - 10) + .frame(width: buttonSize - 10) + .multilineTextAlignment(.center) + .foregroundStyle(Color.red) + } + .buttonStyle(scaleButtonStyle(isRecording: $isReading)) } - .buttonStyle(scaleButtonStyle(isRecording: $isReading)) + Spacer() } - - Spacer() - - // Right side: goal (if applicable), flashlight, and debug + + // Side Buttons Layer (Left & Right) HStack(spacing: 20) { - if (arViewModel.mlManager?.isPointConditioned ?? false) { - VStack(spacing: 4) { - Button(action: { - let newValue = !arViewModel.goalTapModeEnabled - arViewModel.goalTapModeEnabled = newValue - if newValue { - // Clear existing goal so the next tap sets a fresh one - arViewModel.mlManager?.clearGoalPoint() - arViewModel.arVisualizationManager.clearTargetPose() + // Left Side: Delete Button + VStack(spacing: 4) { + Button(action: { + if(isRecordedOnce){ + showingAlert = true + self.activeAlert = .first + } else { + showingAlert = true + self.activeAlert = .second + } + UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() + }){ + Image(systemName: "trash.circle.fill") + .resizable() + .frame(height: 36) + .frame(width: 36) + .foregroundStyle(.red) + } + Text("Delete") + .foregroundStyle(.red) + .font(.caption) + Text("last record") + .foregroundStyle(.red) + .font(.caption) + } + + Spacer() + + // Right Side: Goal (conditional) + Flash + HStack(spacing: 20) { + if (arViewModel.mlManager?.isPointConditioned ?? false) { + VStack(spacing: 4) { + Button(action: { + let newValue = !arViewModel.goalTapModeEnabled + arViewModel.goalTapModeEnabled = newValue + if newValue { + // Clear existing goal so the next tap sets a fresh one + arViewModel.mlManager?.clearGoalPoint() + arViewModel.arVisualizationManager.clearTargetPose() + } + }) { + Image(systemName: arViewModel.goalTapModeEnabled ? "dot.circle.fill" : "target") + .resizable() + .frame(height: 36) + .frame(width: 36) + .foregroundStyle(arViewModel.goalTapModeEnabled ? Color.green : Color.blue) } - }) { - Image(systemName: arViewModel.goalTapModeEnabled ? "dot.circle.fill" : "target") + Text("Set goal") + .font(.caption) + .foregroundColor(.secondary) + } + } + + VStack(spacing: 4) { + Button(action: toggleFlash) { + Image(systemName: openFlash ? "flashlight.off.circle.fill" : "flashlight.on.circle.fill") .resizable() .frame(height: 36) .frame(width: 36) - .foregroundStyle(arViewModel.goalTapModeEnabled ? Color.green : Color.blue) } - Text("Set goal") + Text(openFlash ? "Flash off" : "Flash on") .font(.caption) .foregroundColor(.secondary) } } - - VStack(spacing: 4) { - Button(action: toggleFlash) { - Image(systemName: openFlash ? "flashlight.off.circle.fill" : "flashlight.on.circle.fill") - .resizable() - .frame(height: 36) - .frame(width: 36) - } - Text(openFlash ? "Flash off" : "Flash on") - .font(.caption) - .foregroundColor(.secondary) - } } + .padding(.horizontal, 20) } - .padding(.horizontal, 20) - .padding(.bottom, arViewPadding / 4.0 - (buttonSize / 4.0)) + .padding(.bottom, max(20, arViewPadding / 4.0)) } } From 295007bc78209055b3178dc863c27aea72f8ad26 Mon Sep 17 00:00:00 2001 From: DjKesu Date: Sat, 27 Dec 2025 18:13:45 +0530 Subject: [PATCH 49/56] optimizing checkpoints --- AnySense.xcodeproj/project.pbxproj | 8 +- AnySense/MainPage.swift | 118 ++- AnySense/Managers/ARViewContainer.swift | 717 ++++++++++++------ .../Managers/ARVisualizationManager.swift | 254 ++++--- AnySense/Managers/MLInferenceManager.swift | 131 ++-- AnySense/Managers/ModelManager.swift | 1 - AnySense/Views/ContentView.swift | 7 +- AnySense/Views/InferenceView.swift | 393 ++++++++++ AnySense/Views/MLInferenceResultsView.swift | 18 +- AnySense/Views/accountView.swift | 89 ++- AnySense/Views/peripheralView.swift | 5 +- AnySense/Views/readView.swift | 450 +++-------- README_Inference.md | 51 ++ 13 files changed, 1465 insertions(+), 777 deletions(-) create mode 100644 AnySense/Views/InferenceView.swift create mode 100644 README_Inference.md diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 40672fa..ee65ac4 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -7,6 +7,7 @@ objects = { /* Begin PBXBuildFile section */ + 016073392EF5BE610061563B /* InferenceView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 016073382EF5BE610061563B /* InferenceView.swift */; }; 01682BC42DF0D88100CDA03C /* ModelInfo.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7C92DEA6A1000061B16 /* ModelInfo.swift */; }; 01682BC52DF0D88C00CDA03C /* MLModel+Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01F5B7CB2DEA6A2000061B16 /* MLModel+Extensions.swift */; }; 01682BC92DF4D7CB00CDA03C /* ARVisualizationManager.swift in Sources */ = {isa = PBXBuildFile; fileRef = 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */; }; @@ -49,6 +50,7 @@ /* End PBXContainerItemProxy section */ /* Begin PBXFileReference section */ + 016073382EF5BE610061563B /* InferenceView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = InferenceView.swift; sourceTree = ""; }; 01682BC82DF4D7CB00CDA03C /* ARVisualizationManager.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ARVisualizationManager.swift; sourceTree = ""; }; 01B77E6C2ED94950007823B6 /* demo.mlpackage */ = {isa = PBXFileReference; lastKnownFileType = folder.mlpackage; path = demo.mlpackage; sourceTree = ""; }; 01D2FDD52E64C33600F0BA98 /* ActionTransformUtils.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ActionTransformUtils.swift; sourceTree = ""; }; @@ -159,6 +161,7 @@ 01F5B7C52DEA698D00061B16 /* MLInferenceResultsView.swift */, B9E4B2312D62A9C40032E877 /* accountView.swift */, B9E4B2322D62A9C40032E877 /* ContentView.swift */, + 016073382EF5BE610061563B /* InferenceView.swift */, B9E4B2332D62A9C40032E877 /* peripheralView.swift */, B9E4B2342D62A9C40032E877 /* readView.swift */, ); @@ -353,6 +356,7 @@ 01F5B7C42DEA697200061B16 /* MLInferenceManager.swift in Sources */, 01D2FDD82E64C33600F0BA98 /* ActionTransformUtils.swift in Sources */, 01F5B7C82DEA6A0000061B16 /* ModelManager.swift in Sources */, + 016073392EF5BE610061563B /* InferenceView.swift in Sources */, B9E4B22D2D62A9BA0032E877 /* BluetoothManager.swift in Sources */, B9E4B22F2D62A9BA0032E877 /* ARViewContainer.swift in Sources */, B9E4B2302D62A9BA0032E877 /* USBManager.swift in Sources */, @@ -520,7 +524,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 4; + CURRENT_PROJECT_VERSION = 5; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; @@ -566,7 +570,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 4; + CURRENT_PROJECT_VERSION = 5; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; diff --git a/AnySense/MainPage.swift b/AnySense/MainPage.swift index c86c82f..efdd1d0 100644 --- a/AnySense/MainPage.swift +++ b/AnySense/MainPage.swift @@ -15,35 +15,113 @@ struct MainPage: View { // Start the default page be the read page @State private var selection = 1 + // Track if AR tabs are active for showing/hiding the shared AR view + private var isARTabActive: Bool { + selection == 1 || selection == 2 + } + var body: some View { - TabView(selection: $selection){ - Group{ - PeripheralView(arViewModel: arViewModel, bluetoothManager: arViewModel.getBLEManagerInstance()) - .tabItem { - Label("ble-device", systemImage: "iphone.gen1.radiowaves.left.and.right") + ZStack { + // MARK: - Background layer (AR for tabs 1,2 or solid color for others) + if isARTabActive { + SharedARViewContainer(arViewModel: arViewModel) + .ignoresSafeArea() + } else { + Color.customizedBackground + .ignoresSafeArea() + } + + // MARK: - Content layer (overlays only, no backgrounds) + VStack(spacing: 0) { + // Main content area + Group { + switch selection { + case 0: + PeripheralView(arViewModel: arViewModel, bluetoothManager: arViewModel.getBLEManagerInstance()) + case 1: + ReadViewOverlay(arViewModel: arViewModel) + case 2: + InferenceViewOverlay(arViewModel: arViewModel) + case 3: + SettingsView(arViewModel: arViewModel, modelManager: modelManager) + default: + ReadViewOverlay(arViewModel: arViewModel) + } } - .tag(0) + .frame(maxWidth: .infinity, maxHeight: .infinity) - ReadView(arViewModel: arViewModel) - .tabItem { - Label("read", systemImage: "dot.scope") + // Custom tab bar at bottom + HStack { + TabBarButton(icon: "iphone.gen1.radiowaves.left.and.right", label: "ble-device", tag: 0, selection: $selection) + TabBarButton(icon: "record.circle", label: "record", tag: 1, selection: $selection) + TabBarButton(icon: "brain.head.profile", label: "inference", tag: 2, selection: $selection) + TabBarButton(icon: "gear", label: "settings", tag: 3, selection: $selection) } - .tag(1) - - - SettingsView(arViewModel: arViewModel, modelManager: modelManager) - .tabItem { - Label("settings", systemImage: "gear") + .padding(.vertical, 8) + .background(Color.tabBackground) + } + } + .onAppear { + // Start AR session on initial load + if isARTabActive { + arViewModel.startARSessionIfNeeded() + print("App launched - starting AR session for default tab \(selection)") + } + } + .onChange(of: selection) { newTab in + let isARTab = (newTab == 1 || newTab == 2) - } - .tag(2) + if isARTab { + // Switching to AR tab - resume session without resetting tracking + arViewModel.resumeARSession() + print("Switched to AR tab \(newTab) - resuming AR session") + } else { + // Switching away from AR tabs - pause session + arViewModel.pauseARSession() + print("Switched to non-AR tab \(newTab) - pausing AR session") + } + } + .onChange(of: phase) { newPhase in + switch newPhase { + case .background: + arViewModel.stopAllActivities() + arViewModel.pauseARSession() + print("App backgrounded - all activities stopped") + case .active: + if isARTabActive { + arViewModel.resumeARSession() + print("App active - resuming AR session for tab \(selection)") + } + case .inactive: + print("App inactive") + @unknown default: + break } - .toolbarBackground(.tabBackground, for: .tabBar) - .toolbarBackground(.visible, for: .tabBar) } - .accentColor(.accentColor) } +} + +// MARK: - Custom Tab Bar Button +struct TabBarButton: View { + let icon: String + let label: String + let tag: Int + @Binding var selection: Int + var body: some View { + Button(action: { + selection = tag + }) { + VStack(spacing: 4) { + Image(systemName: icon) + .font(.system(size: 20)) + Text(label) + .font(.caption2) + } + .foregroundColor(selection == tag ? .accentColor : .gray) + .frame(maxWidth: .infinity) + } + } } #Preview { diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 83d4ce1..75e33f9 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -17,7 +17,6 @@ import UIKit import CoreImage.CIFilterBuiltins import Combine import Accelerate -//import WebRTC struct RecordingFiles { let rgbFileName: URL @@ -30,6 +29,13 @@ struct RecordingFiles { let tactileFile: URL } +enum RecordingMode { + case none + case standardRecording + case mlInference + case usbStreaming +} + func createFile(fileURL: URL) throws { let success = FileManager.default.createFile(atPath: fileURL.path, contents: nil, attributes: nil) if !success { @@ -37,116 +43,78 @@ func createFile(fileURL: URL) throws { } } -struct ARViewContainer: UIViewRepresentable { - var session: ARSession - var arVisualizationManager: ARVisualizationManager - typealias UIViewType = ARView +// MARK: - Shared AR View Container (hosts the single ARView from ARViewModel) +struct SharedARViewContainer: UIViewRepresentable { + @ObservedObject var arViewModel: ARViewModel func makeUIView(context: Context) -> ARView { - // Initialize the ARView - let arView = ARView(frame: .zero, cameraMode: .ar, automaticallyConfigureSession: false) - arView.session = session - // Expose real-world mesh as RealityKit entities and give them collision for raycasts - arView.environment.sceneUnderstanding.options = [.collision] - // COMMENT THIS OUT FOR PRODUCTION - shows mesh - // arView.debugOptions.insert(.showSceneUnderstanding) - - // Setup AR visualization with the created ARView - arVisualizationManager.setupVisualization(with: arView) - - // Add tap recognizer for goal setting (point-conditioned models) - let tap = UITapGestureRecognizer(target: context.coordinator, action: #selector(Coordinator.handleTap(_:))) - arView.addGestureRecognizer(tap) - - return arView + print("SharedARViewContainer: returning shared ARView") + return arViewModel.getOrCreateSharedARView() } + func updateUIView(_ uiView: ARView, context: Context) { - if uiView.session !== session { - uiView.session = session - } + // ARView is managed by ARViewModel, no updates needed here } +} + +// MARK: - Tap Coordinator for Shared ARView +class TapCoordinator: NSObject { + weak var arViewModel: ARViewModel? - // MARK: - Coordinator for gesture handling - func makeCoordinator() -> Coordinator { Coordinator(self) } + init(arViewModel: ARViewModel) { + self.arViewModel = arViewModel + super.init() + } - class Coordinator: NSObject { - let parent: ARViewContainer - init(_ parent: ARViewContainer) { self.parent = parent } - - /// Raycast against Scene Understanding (LiDAR mesh) entities. - /// Returns the world-space point if the hit entity originates from real-world mesh data. - private func meshBackedHit(in arView: ARView, from location: CGPoint) -> SIMD3? { - guard let ray = arView.ray(through: location) else { return nil } - - // Raycast the RealityKit scene — includes scene-understanding entities created from LiDAR mesh - let hits = arView.scene.raycast(origin: ray.origin, direction: ray.direction) - - if let hit = hits.first(where: { $0.entity is HasSceneUnderstanding }) { - return hit.position - } - return nil + @objc func handleTap(_ recognizer: UITapGestureRecognizer) { + guard recognizer.state == .ended, let arView = recognizer.view as? ARView else { return } + let location = recognizer.location(in: arView) + + // Try LiDAR-backed mesh raycast first + if let world = meshBackedHit(in: arView, from: location) { + var t = matrix_identity_float4x4 + t.columns.3 = SIMD4(world.x, world.y, world.z, 1) + let goalAnchor = ARAnchor(name: "goal", transform: t) + arView.session.add(anchor: goalAnchor) + print("Using LiDAR mesh raycast for 3D point: \(world)") + NotificationCenter.default.post( + name: NSNotification.Name("ARViewTapForGoal"), + object: nil, + userInfo: ["worldPoint": world, "method": "meshRaycast", "location": location, "bounds": arView.bounds] + ) + return } - @objc func handleTap(_ recognizer: UITapGestureRecognizer) { - guard recognizer.state == .ended, let arView = recognizer.view as? ARView else { return } - let location = recognizer.location(in: arView) - - // 1) (arView.scene.raycast) Try LiDAR-backed mesh raycast first - if let world = meshBackedHit(in: arView, from: location) { - var t = matrix_identity_float4x4 - t.columns.3 = SIMD4(world.x, world.y, world.z, 1) - - let goalAnchor = ARAnchor(name: "goal", transform: t) - arView.session.add(anchor: goalAnchor) - - print("Using LiDAR mesh raycast for 3D point: \(world)") - - NotificationCenter.default.post( - name: NSNotification.Name("ARViewTapForGoal"), - object: nil, - userInfo: [ - "worldPoint": world, - "method": "meshRaycast", - "location": location, - "bounds": arView.bounds - ] - ) - return - } - - // 2) (arView.raycast) Fallback: ARKit plane/estimated-surface raycast - if let hit = arView.raycast(from: location, allowing: .estimatedPlane, alignment: .any).first { - let t = hit.worldTransform - let world = simd_float3(t.columns.3.x, t.columns.3.y, t.columns.3.z) - - let goalAnchor = ARAnchor(name: "goal", transform: t) - arView.session.add(anchor: goalAnchor) - - print("Using plane/estimated raycast fallback for 3D point: \(world)") - - NotificationCenter.default.post( - name: NSNotification.Name("ARViewTapForGoal"), - object: nil, - userInfo: [ - "worldPoint": world, - "method": "raycast", - "location": location, - "bounds": arView.bounds - ] - ) - return - } - - // 3) (no raycast) Final fallback: still notify with screen info (no hit yet) + // Fallback: ARKit plane/estimated-surface raycast + if let hit = arView.raycast(from: location, allowing: .estimatedPlane, alignment: .any).first { + let t = hit.worldTransform + let world = simd_float3(t.columns.3.x, t.columns.3.y, t.columns.3.z) + let goalAnchor = ARAnchor(name: "goal", transform: t) + arView.session.add(anchor: goalAnchor) + print("Using plane/estimated raycast fallback for 3D point: \(world)") NotificationCenter.default.post( name: NSNotification.Name("ARViewTapForGoal"), object: nil, - userInfo: [ - "location": location, - "bounds": arView.bounds - ] + userInfo: ["worldPoint": world, "method": "raycast", "location": location, "bounds": arView.bounds] ) + return } + + // Final fallback: notify with screen info only + NotificationCenter.default.post( + name: NSNotification.Name("ARViewTapForGoal"), + object: nil, + userInfo: ["location": location, "bounds": arView.bounds] + ) + } + + private func meshBackedHit(in arView: ARView, from location: CGPoint) -> SIMD3? { + guard let ray = arView.ray(through: location) else { return nil } + let hits = arView.scene.raycast(origin: ray.origin, direction: ray.direction) + if let hit = hits.first(where: { $0.entity is HasSceneUnderstanding }) { + return hit.position + } + return nil } } @@ -158,6 +126,10 @@ class DepthStatus: ObservableObject { isDepthAvailable = false showAlert = true } + + public func dismissAlert() { + showAlert = false + } } class ARViewModel: ObservableObject{ @@ -168,14 +140,24 @@ class ARViewModel: ObservableObject{ var session = ARSession() var audioSession = AVCaptureSession() var audioCaptureDelegate: AudioCaptureDelegate? - + // ML Inference Manager - now optional and initialized later @Published var mlManager: MLInferenceManager? - + // AR Visualization Manager for 3D pose visualization - @Published var arVisualizationManager = ARVisualizationManager() + @Published var arVisualizationManager: ARVisualizationManager @Published var goalTapModeEnabled: Bool = false @Published var isUSBStreamingActive: Bool = false + + // MARK: - Shared ARView (single instance for entire app lifecycle) + private var sharedARView: ARView? + private var hasSetupSharedARView = false + + // MARK: - Centralized Recording State Management + @Published var isRecording: Bool = false + @Published var recordingMode: RecordingMode = .none + private var currentRecordingFiles: RecordingFiles? + public var userFPS: Double? @@ -240,7 +222,9 @@ class ARViewModel: ObservableObject{ // Combine subscriptions for ML integration private var cancellables = Set() + @MainActor init() { + self.arVisualizationManager = ARVisualizationManager() bluetoothManager = BluetoothManager() self.rgbAttributes = [ @@ -294,6 +278,86 @@ class ARViewModel: ObservableObject{ func getBLEManagerInstance() -> BluetoothManager{ return bluetoothManager!; } + + // MARK: - Shared ARView Management + @MainActor + func getOrCreateSharedARView() -> ARView { + if let existingView = sharedARView { + return existingView + } + + print("Creating shared ARView (one-time setup)") + + // Create the single ARView instance + let arView = ARView(frame: .zero, cameraMode: .ar, automaticallyConfigureSession: false) + arView.session = session + + // Consistent rendering options + arView.renderOptions = [.disablePersonOcclusion, .disableDepthOfField, .disableMotionBlur] + + // Enable scene understanding for raycasts + arView.environment.sceneUnderstanding.options = [.collision] + + // Setup AR visualization + arVisualizationManager.setupVisualization(with: arView) + + // Add tap recognizer for goal setting + let coordinator = TapCoordinator(arViewModel: self) + let tap = UITapGestureRecognizer(target: coordinator, action: #selector(TapCoordinator.handleTap(_:))) + arView.addGestureRecognizer(tap) + // Store coordinator to prevent deallocation + objc_setAssociatedObject(arView, "tapCoordinator", coordinator, .OBJC_ASSOCIATION_RETAIN) + + sharedARView = arView + hasSetupSharedARView = true + + print("Shared ARView created and configured") + return arView + } + + // Resume AR session + @MainActor + func resumeARSession() { + guard !isOpen else { + print("AR session already running") + return + } + + let status = AVCaptureDevice.authorizationStatus(for: .video) + guard status == .authorized else { return } + + let configuration = createARConfiguration() + session.run(configuration, options: []) + isOpen = true + + print("AR session resumed (tracking preserved)") + } + + // MARK: - Shared AR Configuration + private func createARConfiguration() -> ARWorldTrackingConfiguration { + let configuration = ARWorldTrackingConfiguration() + + for videoFormat in ARWorldTrackingConfiguration.supportedVideoFormats { + if videoFormat.captureDeviceType == .builtInWideAngleCamera { + configuration.videoFormat = videoFormat + break + } + } + + if ARWorldTrackingConfiguration.supportsFrameSemantics(.sceneDepth) { + configuration.frameSemantics.insert(.sceneDepth) + } + configuration.planeDetection = [.horizontal, .vertical] + if ARWorldTrackingConfiguration.supportsSceneReconstruction(.meshWithClassification) { + configuration.sceneReconstruction = .meshWithClassification + } else if ARWorldTrackingConfiguration.supportsSceneReconstruction(.mesh) { + configuration.sceneReconstruction = .mesh + } + configuration.environmentTexturing = .none + configuration.isAutoFocusEnabled = false + + return configuration + } private func setupAudioSession() { @@ -311,30 +375,63 @@ class ARViewModel: ObservableObject{ private func setupTransforms() { DispatchQueue.global(qos: .userInitiated).async { - while self.depthRetryCount < self.maxDepthRetries { + var attempts = 0 + let maxAttempts = 50 // Max 500ms wait + + while attempts < maxAttempts { guard let currentFrame = self.session.currentFrame else { - usleep(10000) + attempts += 1 + usleep(10000) // 10ms continue } - let flipTransform = (self.orientation.isPortrait) - ? CGAffineTransform(scaleX: -1, y: -1).translatedBy(x: -1, y: -1) - : .identity - + + let flipTransform = self.computeFlipTransform() + + // Initialize RGB transform if needed if self.combinedRGBTransform == nil { self.initializeRGBTransform(frame: currentFrame, flipTransform: flipTransform) + print("RGB transform initialized successfully") } - - if !self.depthStatus.isDepthAvailable { break } - - if self.combinedDepthTransform == nil { - if self.initializeDepthTransform(frame: currentFrame, flipTransform: flipTransform) { - break + + // Try depth transform + if self.combinedDepthTransform == nil { + if self.initializeDepthTransform(frame: currentFrame, flipTransform: flipTransform) { + print("Depth transform initialized successfully") + } + } + + // Exit once we have RGB transform (depth is optional) + if self.combinedRGBTransform != nil { + break + } + + attempts += 1 + usleep(10000) + } + + if self.combinedRGBTransform == nil { + print("Note: RGB transform not yet initialized, will compute on-demand") + } + if self.combinedDepthTransform == nil { + print("Note: Depth transform not yet initialized, will compute on-demand") } } - - self.depthRetryCount += 1 - usleep(10000) } + + func ensureTransformsReady() { + guard let currentFrame = session.currentFrame else { return } + + let flipTransform = computeFlipTransform() + + if combinedRGBTransform == nil { + initializeRGBTransform(frame: currentFrame, flipTransform: flipTransform) + print("RGB transform computed on-demand") + } + + if combinedDepthTransform == nil { + if initializeDepthTransform(frame: currentFrame, flipTransform: flipTransform) { + print("Depth transform computed on-demand") + } } } @@ -369,7 +466,10 @@ class ARViewModel: ObservableObject{ return true } + @MainActor func setupARSession() { + // Sync orientation with the current interface orientation before configuring transforms + refreshOrientationFromScene() self.startARSession() if(ifAudioEnable) { @@ -379,74 +479,127 @@ class ARViewModel: ObservableObject{ setupTransforms() } + @MainActor func startARSession() { let status = AVCaptureDevice.authorizationStatus(for: .video) - guard status == .authorized else { - return - } - // Create and configure the AR session configuration - let configuration = ARWorldTrackingConfiguration() - - // Loop through available video formats and select the wide-angle camera format - for videoFormat in ARWorldTrackingConfiguration.supportedVideoFormats { - if videoFormat.captureDeviceType == .builtInWideAngleCamera { - configuration.videoFormat = videoFormat - break - } - } - - // Set the session configuration properties - if ARWorldTrackingConfiguration.supportsFrameSemantics(.sceneDepth) { - configuration.frameSemantics.insert(.sceneDepth) - } else { - depthStatus.setUnavailable() - } - configuration.planeDetection = [.horizontal, .vertical] - if ARWorldTrackingConfiguration.supportsSceneReconstruction(.meshWithClassification) { - configuration.sceneReconstruction = .meshWithClassification - } else if ARWorldTrackingConfiguration.supportsSceneReconstruction(.mesh) { - configuration.sceneReconstruction = .mesh - } - configuration.environmentTexturing = .none - configuration.isAutoFocusEnabled = false + guard status == .authorized else { return } - // Run the session with the configuration + let configuration = createARConfiguration() session.run(configuration, options: [.resetTracking, .removeExistingAnchors]) isOpen = true } + + private func refreshOrientationFromScene() { + // Keep a consistent transform between tabs; force portrait so Record and Inference align + orientation = .portrait + } + @MainActor func pauseARSession(){ session.pause() isOpen = false + clearCachedTransforms() } + @MainActor func killARSession() { session.pause() // Pause before releasing resources session = ARSession() // Replace with a new ARSession isOpen = false + clearCachedTransforms() + } + + /// Clear cached transforms so they are recalculated on next session start + private func clearCachedTransforms() { + combinedRGBTransform = nil + combinedDepthTransform = nil + } + + /// Safely extract depth and confidence buffers from an AR frame + private func getDepthBuffers(from frame: ARFrame) -> (depth: CVPixelBuffer, confidence: CVPixelBuffer)? { + guard let depthBuffer = frame.sceneDepth?.depthMap, + let confidenceBuffer = frame.sceneDepth?.confidenceMap else { + return nil + } + return (depthBuffer, confidenceBuffer) + } + + /// Compute flip transform based on current orientation + private func computeFlipTransform() -> CGAffineTransform { + orientation.isPortrait + ? CGAffineTransform(scaleX: -1, y: -1).translatedBy(x: -1, y: -1) + : .identity + } + + // MARK: - Safe Session Management + @MainActor + func startARSessionIfNeeded() { + guard !isOpen else { + print("AR session already running") + return + } + + print("Starting AR session for ARViewContainer") + setupARSession() } + @MainActor func startUSBStreaming() { + // MARK: - State Validation Guards + guard !isUSBStreamingActive else { + print("USB Streaming already active - ignoring start request") + return + } + + guard recordingMode == .none else { + print("Another recording mode active: \(recordingMode) - stopping first") + stopAllActivities() + return + } + + // Ensure transforms are computed before streaming + ensureTransformsReady() + + // MARK: - Update Centralized State + recordingMode = .usbStreaming + // Reset ML inference state for new streaming session mlManager?.resetInferenceState() - + displayLink = CADisplayLink(target: self, selector: #selector(sendFrameUSB)) displayLink?.preferredFrameRateRange = CAFrameRateRange(minimum: Float(self.userFPS!), maximum: Float(self.userFPS!), preferred: Float(self.userFPS!)) displayLink?.add(to: .main, forMode: .common) isUSBStreamingActive = true mlManager?.setUSBStreamingState(isActive: true) + + print("USB streaming started successfully") } + @MainActor func stopUSBStreaming() { + // MARK: - State Validation Guard + guard isUSBStreamingActive else { + print("Stop USB streaming called but not currently streaming") + return + } + displayLink?.invalidate() displayLink = nil isUSBStreamingActive = false mlManager?.setUSBStreamingState(isActive: false) - + // Reset ML inference state when stopping mlManager?.resetInferenceState() + + // MARK: - Update Centralized State + if recordingMode == .usbStreaming { + recordingMode = .none + } + + print("USB streaming stopped successfully") } + @MainActor func setupUSBStreaming() { var rgbBuffer: CVPixelBuffer? @@ -463,24 +616,22 @@ class ARViewModel: ObservableObject{ } self.rgbOutputPixelBufferUSB = rgbBuffer - if self.depthStatus.isDepthAvailable { - var depthBuffer: CVPixelBuffer? - var depthConfidenceBuffer: CVPixelBuffer? + // Try to set up depth buffers - optional, won't block if it fails + var depthBuffer: CVPixelBuffer? + var depthConfidenceBuffer: CVPixelBuffer? - let depthStatus = CVPixelBufferCreate( - kCFAllocatorDefault, - Int(depthViewPortSize.width), - Int(depthViewPortSize.height), - kCVPixelFormatType_DepthFloat32, - depthAttributes as CFDictionary, - &depthBuffer - ) - - guard depthStatus == kCVReturnSuccess else { - return - } + let depthStatus = CVPixelBufferCreate( + kCFAllocatorDefault, + Int(depthViewPortSize.width), + Int(depthViewPortSize.height), + kCVPixelFormatType_DepthFloat32, + depthAttributes as CFDictionary, + &depthBuffer + ) + + if depthStatus == kCVReturnSuccess { self.depthOutputPixelBufferUSB = depthBuffer - + let depthConfidenceStatus = CVPixelBufferCreate( kCFAllocatorDefault, Int(depthViewPortSize.width), @@ -489,15 +640,15 @@ class ARViewModel: ObservableObject{ depthConfAttributes as CFDictionary, &depthConfidenceBuffer ) - guard depthConfidenceStatus == kCVReturnSuccess else { - return + if depthConfidenceStatus == kCVReturnSuccess { + self.depthConfidenceOutputPixelBufferUSB = depthConfidenceBuffer } - self.depthConfidenceOutputPixelBufferUSB = depthConfidenceBuffer } usbManager.connect() } + @MainActor func killUSBStreaming() { self.usbManager.disconnect() @@ -516,10 +667,7 @@ class ARViewModel: ObservableObject{ } - @objc private func sendFrame(link: CADisplayLink) { - streamVideoFrameUSB() - } - + @MainActor @objc private func sendFrameUSB(link: CADisplayLink) { streamVideoFrameUSB() } @@ -546,26 +694,24 @@ class ARViewModel: ObservableObject{ return compressedData } + @MainActor func streamVideoFrameUSB() { guard let currentFrame = session.currentFrame else {return} let rgbPixelBuffer = currentFrame.capturedImage // Perform ML inference on the RGB frame during streaming (provide ARFrame for odometry/goal updates) - mlManager?.performInference(on: rgbPixelBuffer, arFrame: currentFrame, timestamp: CACurrentMediaTime()) - - - - // TODO: Check if we need to change this at all - var depthPixelBuffer: CVPixelBuffer? = nil - var depthConfidencePixelBuffer: CVPixelBuffer? = nil - if self.depthStatus.isDepthAvailable { - guard let depthBuffer = currentFrame.sceneDepth?.depthMap else { return } - depthPixelBuffer = depthBuffer - guard let depthConfidenceBuffer = currentFrame.sceneDepth?.confidenceMap else { return } - depthConfidencePixelBuffer = depthConfidenceBuffer + if let mlManager = mlManager { + Task { @MainActor in + mlManager.performInference(on: rgbPixelBuffer, arFrame: currentFrame, timestamp: CACurrentMediaTime()) + } } + // Try to get depth data if available, but continue regardless + let depthBuffers = getDepthBuffers(from: currentFrame) + let depthPixelBuffer = depthBuffers?.depth + let depthConfidencePixelBuffer = depthBuffers?.confidence + let cameraIntrinsics = currentFrame.camera.intrinsics var intrinsicCoeffs = IntrinsicMatrixCoeffs( @@ -601,18 +747,24 @@ class ARViewModel: ObservableObject{ deviceType: 1 ) + let rgbOutputBufferUSB = self.rgbOutputPixelBufferUSB + let depthOutputBufferUSB = self.depthOutputPixelBufferUSB + let depthConfOutputBufferUSB = self.depthConfidenceOutputPixelBufferUSB + let latestJointActions = self.mlManager?.latestResult?.jointPositions + let usbManager = self.usbManager + DispatchQueue.global(qos: .userInitiated).async { + guard let rgbOutputBufferUSB else { return } CVPixelBufferLockBaseAddress(rgbPixelBuffer, .readOnly) - CVPixelBufferLockBaseAddress(self.rgbOutputPixelBufferUSB!, []) + CVPixelBufferLockBaseAddress(rgbOutputBufferUSB, []) - // Try optimized path first let rgbImageData: Data? if self.canUseOptimizedTransform(for: rgbPixelBuffer) { rgbImageData = self.processRGBOptimized(rgbPixelBuffer) } else { // Fallback to Core Image pipeline let rgbCiImage = CIImage(cvPixelBuffer: rgbPixelBuffer) - let rgbTransformedImage = rgbCiImage.transformed(by: self.combinedRGBTransform!) + let rgbTransformedImage = rgbCiImage.transformed(by: self.combinedRGBTransform ?? CGAffineTransform.identity) guard let rgbCgImage = self.ciContext.createCGImage(rgbTransformedImage, from: rgbTransformedImage.extent) else{ return @@ -622,15 +774,19 @@ class ARViewModel: ObservableObject{ record3dHeader.rgbSize = UInt32(rgbImageData!.count) - CVPixelBufferUnlockBaseAddress(self.rgbOutputPixelBufferUSB!, []) + CVPixelBufferUnlockBaseAddress(rgbOutputBufferUSB, []) CVPixelBufferUnlockBaseAddress(rgbPixelBuffer, .readOnly) var compressedDepthData: Data? = nil var compressedDepthConfData: Data? = nil - if self.depthStatus.isDepthAvailable { - compressedDepthData = self.processDepthStreamData(depthPixelBuffer: depthPixelBuffer!, outputBuffer: self.depthOutputPixelBufferUSB!, isDepth: true) - compressedDepthConfData = self.processDepthStreamData(depthPixelBuffer: depthConfidencePixelBuffer!, outputBuffer: self.depthConfidenceOutputPixelBufferUSB!, isDepth: false) + // Process depth data if available + if let depthBuffer = depthPixelBuffer, + let depthConfBuffer = depthConfidencePixelBuffer, + let depthOutputBuffer = depthOutputBufferUSB, + let depthConfOutputBuffer = depthConfOutputBufferUSB { + compressedDepthData = self.processDepthStreamData(depthPixelBuffer: depthBuffer, outputBuffer: depthOutputBuffer, isDepth: true) + compressedDepthConfData = self.processDepthStreamData(depthPixelBuffer: depthConfBuffer, outputBuffer: depthConfOutputBuffer, isDepth: false) record3dHeader.depthSize = UInt32(compressedDepthData?.count ?? 0) record3dHeader.confidenceMapSize = UInt32(compressedDepthConfData?.count ?? 0) @@ -638,7 +794,7 @@ class ARViewModel: ObservableObject{ // Always send exactly 7 floats (28 bytes) for joint actions let jointActionsArray: [Float] - if let latestJointActions = self.mlManager?.latestResult?.jointPositions, !latestJointActions.isEmpty { + if let latestJointActions, !latestJointActions.isEmpty { // Use actual ML inference results, ensure exactly 7 values jointActionsArray = Array(latestJointActions.prefix(7)) + Array(repeating: 0.0, count: max(0, 7 - latestJointActions.count)) } else { @@ -649,7 +805,7 @@ class ARViewModel: ObservableObject{ // Convert to exactly 28 bytes (7 floats * 4 bytes each) let jointActionsData = Data(bytes: jointActionsArray, count: 28) - self.usbManager.sendData( + usbManager.sendData( record3dHeaderData: Data(bytes: &record3dHeader, count: MemoryLayout.size), intrinsicMatData: Data(bytes: &intrinsicCoeffs, count: MemoryLayout.size), poseData: Data(bytes: &camera_pose, count: MemoryLayout.size), @@ -662,6 +818,7 @@ class ARViewModel: ObservableObject{ } + @MainActor @objc private func updateFrame(link: CADisplayLink) { guard lastTimestamp > 0 else { // Initialize timestamp on the first call @@ -671,60 +828,95 @@ class ARViewModel: ObservableObject{ captureVideoFrame() } - func startRecording() -> RecordingFiles { - let saveFileNames = setupRecording() + @MainActor + func startRecording() -> RecordingFiles? { + // MARK: - State Validation Guards + guard !isRecording else { + print("Recording already active - ignoring start request") + return currentRecordingFiles + } + + guard recordingMode == .none else { + print("Another recording mode active: \(recordingMode) - stopping first") + stopAllActivities() + return nil + } + // Ensure transforms are computed before recording + ensureTransformsReady() + + guard let saveFileNames = setupRecording() else { + print("Failed to setup recording") + return nil + } + + // MARK: - Update Centralized State + isRecording = true + recordingMode = .standardRecording + currentRecordingFiles = saveFileNames + // Reset ML inference state for new recording mlManager?.resetInferenceState() - + // Start AR pose visualization with origin at current camera position arVisualizationManager.startRecordingVisualization() - + assetWriter?.startWriting() startTime = CMTimeMake(value: Int64(CACurrentMediaTime() * 1000), timescale: 1000) assetWriter?.startSession(atSourceTime: startTime!) - + + let audioEnabled = ifAudioEnable + let audioSession = self.audioSession DispatchQueue.global(qos: .background).async { - if(self.ifAudioEnable) { - self.audioSession.startRunning() + if audioEnabled { + audioSession.startRunning() } } - if self.depthStatus.isDepthAvailable { - depthAssetWriter?.startWriting() - depthAssetWriter?.startSession(atSourceTime: startTime!) + // Start depth recording if depth writer is available + if let depthWriter = depthAssetWriter { + depthWriter.startWriting() + depthWriter.startSession(atSourceTime: startTime!) } - + displayLink = CADisplayLink(target: self, selector: #selector(updateFrame)) displayLink?.preferredFrameRateRange = CAFrameRateRange(minimum: Float(self.userFPS!), maximum: Float(self.userFPS!), preferred: Float(self.userFPS!)) displayLink?.add(to: .main, forMode: .common) - - return saveFileNames! + + print("Recording started successfully") + return saveFileNames } + @MainActor func stopRecording(){ + // MARK: - State Validation Guard + guard isRecording else { + print("Stop recording called but not currently recording") + return + } + displayLink?.invalidate() displayLink = nil - + // Stop AR pose visualization arVisualizationManager.stopRecordingVisualization() - + // Reset ML inference state when stopping mlManager?.resetInferenceState() - + if(ifAudioEnable) { audioSession.stopRunning() audioInput?.markAsFinished() } videoInput?.markAsFinished() - + audioCaptureDelegate = nil - + assetWriter?.finishWriting { self.assetWriter = nil } - + depthVideoInput?.markAsFinished() depthAssetWriter?.finishWriting { self.depthAssetWriter = nil @@ -735,10 +927,55 @@ class ARViewModel: ObservableObject{ } catch { // Error closing pose file - continue cleanup } - + + // MARK: - Update Centralized State + isRecording = false + recordingMode = .none + currentRecordingFiles = nil + updateDemoCounter() + print("Recording stopped successfully") + } + + // MARK: - Comprehensive Cleanup Method + @MainActor + func stopAllActivities() { + // If nothing is active, avoid redundant cleanup work + if !isRecording && !isUSBStreamingActive && recordingMode == .none && displayLink == nil { + print("No active activities to stop") + return + } + + print("Stopping all activities...") + + // Stop recording if active + if isRecording { + stopRecording() + } + + // Stop USB streaming if active + if isUSBStreamingActive { + stopUSBStreaming() + } + + // Reset ML inference state + mlManager?.resetInferenceState() + + // Stop AR visualization + arVisualizationManager.stopRecordingVisualization() + + // Invalidate any remaining display links + displayLink?.invalidate() + displayLink = nil + + // Reset state + recordingMode = .none + currentRecordingFiles = nil + + print("All activities stopped") } + @MainActor func setupRecording() -> RecordingFiles? { // Determine all the destinated file saving URL or this recording by its start time let dateFormatter = DateFormatter() @@ -758,11 +995,7 @@ class ARViewModel: ObservableObject{ fileNames["DepthImages"] = isColorMapOpened ? "Depth_Colored_Images_\(timestamp)" : "Depth_Images_\(timestamp)" } - guard let documentsURL = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask).first else { - return nil - } - - let generalDataDirectory = documentsURL.appendingPathComponent(timestamp) + let generalDataDirectory = getDocumentsDirect().appendingPathComponent(timestamp) guard let rgbFileName = fileNames["RGB"], let depthFileName = fileNames["Depth"], @@ -788,7 +1021,7 @@ class ARViewModel: ObservableObject{ do { try FileManager.default.createDirectory(at: generalDataDirectory, withIntermediateDirectories: true) - if mlManager?.saveDebugFrames == true && self.depthStatus.isDepthAvailable, + if mlManager?.saveDebugFrames == true, let depthDir = depthImagesDirectory { try FileManager.default.createDirectory(at: depthDir, withIntermediateDirectories: true) } @@ -842,9 +1075,8 @@ class ARViewModel: ObservableObject{ self.pixelBufferAdapter = AVAssetWriterInputPixelBufferAdaptor(assetWriterInput: videoInput!, sourcePixelBufferAttributes: rgbAttributes) - if self.depthStatus.isDepthAvailable { - setupDepthRecording(depthVideoURL: depthVideoURL) - } + // Setup depth recording if supported + setupDepthRecording(depthVideoURL: depthVideoURL) self.poseFileHandle = try FileHandle(forWritingTo: poseTextURL) try poseFileHandle?.seekToEnd() @@ -904,7 +1136,7 @@ class ARViewModel: ObservableObject{ CVPixelBufferLockBaseAddress(outputBuffer, []) let ciImage = CIImage(cvPixelBuffer: rgbPixelBuffer) - let transformedImage = ciImage.transformed(by: self.combinedRGBTransform!) //.cropped(to: cropRect) + let transformedImage = ciImage.transformed(by: self.combinedRGBTransform ?? CGAffineTransform.identity) //.cropped(to: cropRect) self.ciContext.render(transformedImage, to: outputBuffer, bounds: cropRect, colorSpace: CGColorSpaceCreateDeviceRGB()) guard let pixelBufferAdapter = self.pixelBufferAdapter else { @@ -1129,6 +1361,7 @@ class ARViewModel: ObservableObject{ } } + @MainActor func captureVideoFrame() { guard let currentFrame = session.currentFrame else {return} @@ -1138,15 +1371,14 @@ class ARViewModel: ObservableObject{ let currentTime = CMTimeMake(value: Int64(CACurrentMediaTime() * 1000), timescale: 1000) let rgbPixelBuffer = currentFrame.capturedImage - var depthPixelBuffer: CVPixelBuffer? - - if self.depthStatus.isDepthAvailable { - guard let depthBuffer = currentFrame.sceneDepth?.depthMap else { return } - depthPixelBuffer = depthBuffer - } + let depthPixelBuffer = currentFrame.sceneDepth?.depthMap // Perform ML inference on the RGB frame (provide ARFrame for odometry/goal updates) - mlManager?.performInference(on: rgbPixelBuffer, arFrame: currentFrame, timestamp: CACurrentMediaTime()) + if let mlManager = mlManager { + Task { @MainActor in + mlManager.performInference(on: rgbPixelBuffer, arFrame: currentFrame, timestamp: CACurrentMediaTime()) + } + } @@ -1160,8 +1392,8 @@ class ARViewModel: ObservableObject{ DispatchQueue.global(qos: .userInitiated).async { let rgbSuccess = self.processRGBCaptureData(rgbPixelBuffer: rgbPixelBuffer, cropRect: cropRect, currentTime: currentTime) imgSuccessFlag = imgSuccessFlag && rgbSuccess - if self.depthStatus.isDepthAvailable && imgSuccessFlag { - let depthSuccess = self.processDepthCaptureData(depthPixelBuffer: depthPixelBuffer, cropRect: depthCropRect, currentTime: currentTime) + if let depthBuffer = depthPixelBuffer, imgSuccessFlag { + let depthSuccess = self.processDepthCaptureData(depthPixelBuffer: depthBuffer, cropRect: depthCropRect, currentTime: currentTime) imgSuccessFlag = imgSuccessFlag && depthSuccess } if imgSuccessFlag { @@ -1170,15 +1402,14 @@ class ARViewModel: ObservableObject{ } } - func getDocumentsDirect() -> URL{ - let paths = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask) - return paths[0] + func getDocumentsDirect() -> URL { + FileManager.default.urls(for: .documentDirectory, in: .userDomainMask)[0] } func updateDemoCounter() { - let documentsURL = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask) - do{ - let contents = try FileManager.default.contentsOfDirectory(at: documentsURL[0], includingPropertiesForKeys: [.isDirectoryKey], options: [.skipsHiddenFiles, .skipsSubdirectoryDescendants]) + let documentsURL = getDocumentsDirect() + do { + let contents = try FileManager.default.contentsOfDirectory(at: documentsURL, includingPropertiesForKeys: [.isDirectoryKey], options: [.skipsHiddenFiles, .skipsSubdirectoryDescendants]) let directories = contents.filter { url in var isDirectory: ObjCBool = false FileManager.default.fileExists(atPath: url.path, isDirectory: &isDirectory) @@ -1191,6 +1422,7 @@ class ARViewModel: ObservableObject{ } // MARK: - Model Manager Integration + @MainActor func initializeMLManager(with modelManager: ModelManager) { self.mlManager = MLInferenceManager(modelManager: modelManager) @@ -1210,6 +1442,21 @@ class ARViewModel: ObservableObject{ } + // MARK: - Bluetooth Recording Helpers (Consolidated) + func startBluetoothRecording(targetURL: URL, fps: Double) { + do { + try createFile(fileURL: targetURL) + } catch { + print("Error creating tactile file.") + } + + bluetoothManager?.startRecording(targetURL: targetURL, fps: fps) + } + + func stopBluetoothRecording() { + bluetoothManager?.stopRecording() + } + } class AudioCaptureDelegate: NSObject, AVCaptureAudioDataOutputSampleBufferDelegate { diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index d974293..702265e 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -1,3 +1,10 @@ +// +// ARVisualizationManager.swift +// AnySense +// +// Created by Krish on 2025/2/1. +// + import Foundation import RealityKit import ARKit @@ -7,7 +14,7 @@ import UIKit // MARK: - Action State enum ActionState { case waiting // User is moving toward target - case reached // Cubes overlapped, inference triggered + case reached // Proximity triggered var displayName: String { switch self { @@ -47,6 +54,7 @@ enum VisualizationFrequency: CaseIterable { } // MARK: - AR Visualization Manager +@MainActor class ARVisualizationManager: ObservableObject { // MARK: - Published Properties @@ -66,13 +74,13 @@ class ARVisualizationManager: ObservableObject { var isGripperClosed: Bool = false var useVirtualGripper: Bool = false var applyEndOffset: Bool = true - var endOffsetMeters: Float = 0.02 + var endOffsetMeters: Float = 0.05 // MARK: - Wireframe & Target Visualization private var wireframeEntity: Entity? private var wireframeAnchor: AnchorEntity? private let wireframeSize: Float = 0.018 - private let wireframeOffsetMeters: Float = 0.04 + private let wireframeOffsetMeters: Float = 0.05 private var wireframeVisualPosition: SIMD3? private var activeTargetEntity: ModelEntity? private var activeTargetPosition: SIMD3? @@ -164,8 +172,6 @@ class ARVisualizationManager: ObservableObject { worldOriginAnchor = nil } - - // MARK: - Control Methods func enableVisualization() { isVisualizationEnabled = true @@ -200,7 +206,7 @@ class ARVisualizationManager: ObservableObject { } } - // MARK: - Wireframe Management + // MARK: - Wireframe Management (Ego Visualization) func updateWireframe(cameraRelativePosition: SIMD3) { guard isVisualizationEnabled, !isGripperClosed else { return } @@ -223,8 +229,13 @@ class ARVisualizationManager: ObservableObject { } if self.wireframeEntity == nil { - self.wireframeEntity = self.createWireframeBox() + // Ghost Arrow: Semi-transparent Blue + let ghostColor = UIColor.systemBlue.withAlphaComponent(0.4) + self.wireframeEntity = self.createArrowEntity(color: ghostColor) self.wireframeAnchor!.addChild(self.wireframeEntity!) + + // Orient arrow to face forward (-Z) which is the default for our geometry + self.wireframeEntity!.orientation = simd_quatf(angle: 0, axis: SIMD3(1, 0, 0)) } self.wireframeEntity?.position = SIMD3(0, 0, -self.wireframeOffsetMeters) @@ -233,118 +244,39 @@ class ARVisualizationManager: ObservableObject { checkProximityAndUpdateState() } - // MARK: - Wireframe Creation - private func createWireframeBox() -> Entity { - let wireframeGroup = Entity() - let edgeThickness: Float = 0.001 - let half = wireframeSize / 2.0 - - createWireframeEdge(from: SIMD3(-half, -half, -half), - to: SIMD3(half, -half, -half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(half, -half, -half), - to: SIMD3(half, half, -half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(half, half, -half), - to: SIMD3(-half, half, -half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(-half, half, -half), - to: SIMD3(-half, -half, -half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(-half, -half, half), - to: SIMD3(half, -half, half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(half, -half, half), - to: SIMD3(half, half, half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(half, half, half), - to: SIMD3(-half, half, half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(-half, half, half), - to: SIMD3(-half, -half, half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(-half, -half, -half), - to: SIMD3(-half, -half, half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(half, -half, -half), - to: SIMD3(half, -half, half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(-half, half, -half), - to: SIMD3(-half, half, half), - thickness: edgeThickness, - parent: wireframeGroup) - createWireframeEdge(from: SIMD3(half, half, -half), - to: SIMD3(half, half, half), - thickness: edgeThickness, - parent: wireframeGroup) - - return wireframeGroup - } - - private func createWireframeEdge(from: SIMD3, to: SIMD3, thickness: Float, parent: Entity) { - let direction = to - from - let edgeLength = length(direction) - guard edgeLength > 1e-6 else { return } - - let center = (from + to) / 2.0 - let targetDir = direction / edgeLength - let edgeMesh = MeshResource.generateBox(width: thickness, height: thickness, depth: edgeLength) - let blueMaterial = SimpleMaterial(color: UIColor.systemBlue.withAlphaComponent(0.9), isMetallic: false) - let edgeEntity = ModelEntity(mesh: edgeMesh, materials: [blueMaterial]) - edgeEntity.position = center - - let defaultDir = SIMD3(0, 0, 1) - let dotProduct = dot(defaultDir, targetDir) - - if abs(dotProduct) > 0.999 { - if dotProduct < 0 { - edgeEntity.orientation = simd_quatf(angle: .pi, axis: SIMD3(0, 1, 0)) - } - } else { - let axis = cross(defaultDir, targetDir) - let axisLength = length(axis) - if axisLength > 1e-6 { - let angle = acos(max(-1.0, min(1.0, dotProduct))) - edgeEntity.orientation = simd_quatf(angle: angle, axis: axis / axisLength) - } - } - - parent.addChild(edgeEntity) - } - - + // MARK: - Proximity Check private var lastLoggedDistance: Float = -1.0 - + private func checkProximityAndUpdateState() { guard !isGripperClosed, let wireframePos = wireframeVisualPosition, - let targetPos = activeTargetPosition else { return } - - // Use distance-based proximity instead of strict overlap + let activeTarget = activeTargetEntity else { return } + + // Fix: Use local position (relative to WorldOriginAnchor) to match wireframeVisualPosition coordinate space + let targetPos = activeTarget.position + + // Use distance-based proximity let distance = length(targetPos - wireframePos) - // Proximity threshold: more generous threshold for easier interaction - // targetSize=0.012m, wireframeSize=0.018m - let proximityThreshold: Float = 0.01 // 1cm threshold + // Update target color based on proximity + updateTargetColor(for: distance) - let isNearby = distance <= proximityThreshold + // Debug print to verify distance + if debugLoggingEnabled && distance < 0.2 { + // throttling print to avoid spam could be good, but simple print is fine for now + // print("Dist: \(distance)") + } + + // Proximity threshold: Relaxed to 2.5cm for robust interaction + let proximityThreshold: Float = 0.025 + let isNearby = distance <= proximityThreshold if isNearby { if actionState != .reached { - print("Target Cube REACHED") + print("Target Reached! (Dist: \(String(format: "%.3f", distance))m)") actionState = .reached - // Simply remove the target when reached + // Remove the target to indicate success / clear the view activeTargetEntity?.removeFromParent() activeTargetEntity = nil activeTargetPosition = nil @@ -356,6 +288,60 @@ class ARVisualizationManager: ObservableObject { } } } + + // MARK: - Color Update Based on Proximity + private func updateTargetColor(for distance: Float) { + guard let activeTarget = activeTargetEntity else { return } + + // Color transition based on distance + // Far: Red (distance > 0.12m) + // Medium: Orange/Yellow (0.03m - 0.12m) + // Close: Green (< 0.03m) + + let color: UIColor + if distance > 0.12 { + // Far - Red + color = UIColor.systemRed + } else if distance > 0.03 { + // Medium distance - interpolate from red to green + let progress = (0.12 - distance) / (0.12 - 0.03) // 0.0 to 1.0 + color = interpolateColor(from: UIColor.systemRed, to: UIColor.systemGreen, progress: progress) + } else { + // Close - Green + color = UIColor.systemGreen + } + + // Update the material on main thread - need to update all children of the arrow entity + DispatchQueue.main.async { [weak self] in + guard let self = self else { return } + let newMaterial = SimpleMaterial(color: color, isMetallic: false) + + // Update all children of the arrow entity (shaft and head) + for child in activeTarget.children { + if let modelChild = child as? ModelEntity { + modelChild.model?.materials = [newMaterial] + } + } + } + } + + // MARK: - Color Interpolation Helper + private func interpolateColor(from: UIColor, to: UIColor, progress: Float) -> UIColor { + let clampedProgress = max(0.0, min(1.0, progress)) + + var fromRed: CGFloat = 0, fromGreen: CGFloat = 0, fromBlue: CGFloat = 0, fromAlpha: CGFloat = 0 + var toRed: CGFloat = 0, toGreen: CGFloat = 0, toBlue: CGFloat = 0, toAlpha: CGFloat = 0 + + from.getRed(&fromRed, green: &fromGreen, blue: &fromBlue, alpha: &fromAlpha) + to.getRed(&toRed, green: &toGreen, blue: &toBlue, alpha: &toAlpha) + + let resultRed = fromRed + (toRed - fromRed) * CGFloat(clampedProgress) + let resultGreen = fromGreen + (toGreen - fromGreen) * CGFloat(clampedProgress) + let resultBlue = fromBlue + (toBlue - fromBlue) * CGFloat(clampedProgress) + let resultAlpha = fromAlpha + (toAlpha - fromAlpha) * CGFloat(clampedProgress) + + return UIColor(red: resultRed, green: resultGreen, blue: resultBlue, alpha: resultAlpha) + } // MARK: - Manual Trigger Support func forceTargetTransition() { @@ -475,7 +461,7 @@ class ARVisualizationManager: ObservableObject { guard isVisualizationEnabled && hasEstablishedOrigin && !isGripperClosed else { return } guard jointActions.count >= 6 else { return } - let (cameraDeltaTranslation, _) = interpretMLDirections(jointActions, timestamp: timestamp) + let (cameraDeltaTranslation, cameraRotation) = interpretMLDirections(jointActions, timestamp: timestamp) let cameraTransform = getCurrentCameraTransform() let rotationWorldFromCamera = simd_float3x3( columns: ( @@ -485,9 +471,14 @@ class ARVisualizationManager: ObservableObject { ) ) let deltaTranslation = rotationWorldFromCamera * cameraDeltaTranslation + + // Convert local rotation to world rotation: R_target = R_camera * R_delta + let currentCameraRotation = simd_quatf(cameraTransform) + let targetRotation = currentCameraRotation * cameraRotation + let currentCameraPosition = SIMD3(cameraTransform.columns.3.x, cameraTransform.columns.3.y, cameraTransform.columns.3.z) - worldOrigin let targetPosition = currentCameraPosition + deltaTranslation - updateTarget(position: targetPosition) + updateTarget(position: targetPosition, rotation: targetRotation) } private func interpretMLDirections(_ jointActions: [Float], timestamp: CFTimeInterval = CACurrentMediaTime()) -> (translation: SIMD3, rotation: simd_quatf) { @@ -504,33 +495,64 @@ class ARVisualizationManager: ObservableObject { } func updateTargetCube(position: SIMD3) { - updateTarget(position: position) + // Legacy support - default identity rotation + updateTarget(position: position, rotation: simd_quatf(angle: 0, axis: SIMD3(0, 1, 0))) } // MARK: - Target Management - func updateTarget(position: SIMD3) { + func updateTarget(position: SIMD3, rotation: simd_quatf) { guard isVisualizationEnabled, !isGripperClosed else { return } DispatchQueue.main.async { [weak self] in guard let self = self, let worldOriginAnchor = self.worldOriginAnchor else { return } if self.activeTargetEntity == nil { - let targetMesh = MeshResource.generateBox(size: self.targetSize) - let redMaterial = SimpleMaterial(color: UIColor.systemRed.withAlphaComponent(1.0), isMetallic: false) - let newTarget = ModelEntity(mesh: targetMesh, materials: [redMaterial]) + // Target Arrow: Solid Red + let redColor = UIColor.systemRed.withAlphaComponent(1.0) + let newTarget = self.createArrowEntity(color: redColor) worldOriginAnchor.addChild(newTarget) self.activeTargetEntity = newTarget self.actionState = .waiting } self.activeTargetEntity?.position = position + self.activeTargetEntity?.orientation = rotation // Aligned with Camera Frame self.activeTargetPosition = position - print("[Viz] Cube (Target) Position: (\(String(format: "%.3f", position.x)), \(String(format: "%.3f", position.y)), \(String(format: "%.3f", position.z)))") + print("[Viz] Target Arrow Pos: (\(String(format: "%.3f", position.x)), \(String(format: "%.3f", position.y)), \(String(format: "%.3f", position.z)))") } } + // Shared Arrow Creation (Used for both Ghost and Target) + private func createArrowEntity(color: UIColor) -> ModelEntity { + let arrowGroup = Entity() + let material = SimpleMaterial(color: color, isMetallic: false) + + // Dimensions - Adjusted for visual clarity + let length: Float = 0.025 // Shortened shaft (was 0.04) + let shaftRadius: Float = 0.004 // Thicker shaft (was 0.003) + let headRadius: Float = 0.012 // Wider head (was 0.01) + let headLength: Float = 0.015 // Head length kept similar + + // Shaft + let shaft = MeshResource.generateBox(width: shaftRadius*2, height: shaftRadius*2, depth: length) + let shaftEntity = ModelEntity(mesh: shaft, materials: [material]) + shaftEntity.position = SIMD3(0, 0, -length/2) + + // Head (using Box for simplicity, but scaled to look broadly pointer-like) + let head = MeshResource.generateBox(size: headRadius*2) + let headEntity = ModelEntity(mesh: head, materials: [material]) + headEntity.position = SIMD3(0, 0, -length - headRadius/2) + // Note: Head position shifted to attach to shaft end + + // Combine + let parent = ModelEntity() + parent.addChild(shaftEntity) + parent.addChild(headEntity) + + return parent + } - private func eulerToQuaternion(roll: Float, pitch: Float, yaw: Float) -> simd_quatf { + private func eulerToQuaternion(roll: Float, pitch: Float, yaw: Float) -> simd_quatf { let phi_2 = roll / 2.0 let theta_2 = pitch / 2.0 let psi_2 = yaw / 2.0 diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 34f2888..cf2dc18 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -26,14 +26,24 @@ struct InferenceResult { } // MARK: - ML Inference Manager +@MainActor class MLInferenceManager: ObservableObject { // MARK: - Published Properties @Published var latestResult: InferenceResult? + @Published var lastResult: InferenceResult? + @Published var isInferencePendingUI: Bool = false + + @MainActor + func clearPendingState() { + isInferencePending = false + isInferencePendingUI = false + } @Published var isInferenceEnabled: Bool = false @Published var inferenceFrequency: InferenceFrequency = .medium @Published var currentGoalPoint: simd_float3? @Published var modelMetadata: ModelMetadata? + @Published var isModelLoading: Bool = false // Tracks loading and warm-up // MARK: - Private Properties private var model: MLModel? @@ -42,6 +52,8 @@ class MLInferenceManager: ObservableObject { // MARK: - Goal Point Management + // MARK: - Goal Point Management + func setGoalPoint(_ point: simd_float3) { self.currentGoalPoint = point arVisualizationManager?.setTargetPose(point) @@ -154,18 +166,6 @@ class MLInferenceManager: ObservableObject { } } - deinit { - // Ensure cleanup of resources - model = nil - latestResult = nil - cancellables.removeAll() - - // Clean up vImage buffer - if let buffer = gripperOverlayBuffer { - free(buffer.data) - } - } - // MARK: - Gripper Overlay Methods private func loadGripperOverlay() { // Load open gripper (default/original) @@ -209,14 +209,14 @@ class MLInferenceManager: ObservableObject { currentGripperOverlayImage = nil return } - + let isGripperClosed = currentGripperValue < 0.7 - let imageToShow = isGripperClosed ? gripperClosedUIImage : gripperOpenUIImage - + let baseImage = isGripperClosed ? gripperClosedUIImage : gripperOpenUIImage + print("DEBUG: Updating gripper overlay - value: \(String(format: "%.3f", currentGripperValue)), closed: \(isGripperClosed)") - + // Update published property (automatically triggers objectWillChange) - currentGripperOverlayImage = imageToShow + currentGripperOverlayImage = baseImage print("DEBUG: Gripper overlay image updated: \(isGripperClosed ? "CLOSED" : "OPEN")") } @@ -407,42 +407,54 @@ class MLInferenceManager: ObservableObject { modelMetadata = nil frameBuffer.removeAll() hasRunFirstInference = false - // maxBufferSize stays at 3 return } - do { - let loadedModel = try modelManager.loadModel(for: activeModel) - model = loadedModel - - // Extract model metadata for type detection - let metadata = try ModelMetadata(from: loadedModel) - modelMetadata = metadata - - // Always maintain 3-frame rolling buffer (don't override with model's temporal requirement) - // maxBufferSize stays at 3 - frameBuffer.removeAll() - hasRunFirstInference = false // Reset for new model - - print("Model loaded: \(activeModel.name)") - print(" Temporal frames: \(metadata.temporalFrames)") - print(" Goal conditioning: \(metadata.requiresGoalPoint)") - print(" Buffer size: \(maxBufferSize)") - - // 224x224 input for all models - modelInputSize = CGSize(width: 224, height: 224) - - // Initialize shared pixel buffer if needed - initializeSharedBuffers() + // Indicate loading started + DispatchQueue.main.async { + self.isModelLoading = true + } + + // Perform loading on background thread to keep UI responsive + DispatchQueue.global(qos: .userInitiated).async { [weak self] in + guard let self = self else { return } - // Force 3D goal conditioning - goalDimension = 3 - } catch { - model = nil - modelMetadata = nil - frameBuffer.removeAll() - hasRunFirstInference = false - // maxBufferSize stays at 3 + do { + let loadedModel = try self.modelManager.loadModel(for: activeModel) + + // Extract model metadata for type detection + let metadata = try ModelMetadata(from: loadedModel) + + DispatchQueue.main.async { + self.model = loadedModel + self.modelMetadata = metadata + + // Always maintain 3-frame rolling buffer + self.frameBuffer.removeAll() + self.hasRunFirstInference = false // Reset for new model + + print("Model loaded: \(activeModel.name)") + print(" Temporal frames: \(metadata.temporalFrames)") + print(" Goal conditioning: \(metadata.requiresGoalPoint)") + print(" Buffer size: \(self.maxBufferSize)") + + self.modelInputSize = CGSize(width: 224, height: 224) + self.initializeSharedBuffers() + self.goalDimension = 3 + + // Mark loading as complete + self.isModelLoading = false + } + } catch { + print("Error loading model: \(error)") + DispatchQueue.main.async { + self.model = nil + self.modelMetadata = nil + self.frameBuffer.removeAll() + self.hasRunFirstInference = false + self.isModelLoading = false + } + } } } @@ -647,6 +659,7 @@ class MLInferenceManager: ObservableObject { // Mark inference as pending isInferencePending = true + isInferencePendingUI = true proximityReached = false // Reset proximity flag if debugLoggingEnabled { @@ -660,6 +673,7 @@ class MLInferenceManager: ObservableObject { } catch { print("ERROR: Failed to prepare model input: \(error)") isInferencePending = false + isInferencePendingUI = false return } @@ -680,6 +694,7 @@ class MLInferenceManager: ObservableObject { // Reset pending flag and mark first inference complete DispatchQueue.main.async { self.isInferencePending = false + self.isInferencePendingUI = false self.lastInferenceTime = CACurrentMediaTime() // Update for frequency tracking if !self.hasRunFirstInference { self.hasRunFirstInference = true @@ -690,6 +705,7 @@ class MLInferenceManager: ObservableObject { print("ERROR: Model inference failed: \(error)") DispatchQueue.main.async { self.isInferencePending = false + self.isInferencePendingUI = false } } } @@ -1102,6 +1118,7 @@ class MLInferenceManager: ObservableObject { // Update UI on main thread DispatchQueue.main.async { [weak self] in self?.latestResult = result + self?.lastResult = result // Only enable visualization when NOT in USB streaming mode (recording mode only) if let arManager = self?.arVisualizationManager, jointPositions.count >= 6, self?.isUSBStreamingActive != true { @@ -1128,18 +1145,32 @@ class MLInferenceManager: ObservableObject { if enableTransformDebug { print("Transform debug enabled (\(rotationUnit))") } + + // Update gripper overlay to show inference status + Task { @MainActor in + updateGripperOverlayDisplay() + } } - + func disableInference() { isInferenceEnabled = false latestResult = nil + // Preserve lastResult so UI can continue showing the previous inference output while idle + isInferencePending = false + isInferencePendingUI = false print("Inference disabled") + + // Update gripper overlay to hide inference status + Task { @MainActor in + updateGripperOverlayDisplay() + } } func resetInferenceState() { hasRunFirstInference = false proximityReached = false isInferencePending = false + isInferencePendingUI = false frameBuffer.removeAll() currentFrameEntry = nil goalFrameCount = 0 // Reset goal frame count diff --git a/AnySense/Managers/ModelManager.swift b/AnySense/Managers/ModelManager.swift index 2fd5c8d..cb652b4 100644 --- a/AnySense/Managers/ModelManager.swift +++ b/AnySense/Managers/ModelManager.swift @@ -43,7 +43,6 @@ class ModelManager: ObservableObject { get { activeModel?.id } set { if let newID = newValue { - print("DEBUG: activeModelID setter called with: \(newID)") setActiveModel(id: newID) } } diff --git a/AnySense/Views/ContentView.swift b/AnySense/Views/ContentView.swift index 9c39b18..2597984 100644 --- a/AnySense/Views/ContentView.swift +++ b/AnySense/Views/ContentView.swift @@ -6,7 +6,6 @@ // import SwiftUI -import CoreBluetooth import AVFoundation struct ContentView: View { @@ -116,6 +115,12 @@ class AppInformation : ObservableObject{ @Published var ifBluetoothConnected: Bool = false @Published var ifAudioRecordingEnabled: Bool = false @Published var mlInferenceEnabled: Bool = false + + // MARK: - Inference & Visualization Settings + @Published var showGripperOverlay: Bool = true + @Published var enableGripperOverlayInModel: Bool = true + @Published var arVisualizationEnabled: Bool = false + @Published var visualizationFrequency: VisualizationFrequency = .medium } diff --git a/AnySense/Views/InferenceView.swift b/AnySense/Views/InferenceView.swift new file mode 100644 index 0000000..3de566f --- /dev/null +++ b/AnySense/Views/InferenceView.swift @@ -0,0 +1,393 @@ +// +// InferenceView.swift +// Anysense +// +// Created by Krish Mehta +// ML Inference and AR Visualization View +// + +import SwiftUI +import UIKit +import CoreBluetooth +import BackgroundTasks +import UserNotifications +import Foundation +import AVFoundation +import ARKit + +// MARK: - InferenceView Overlay +struct InferenceViewOverlay: View { + @EnvironmentObject var appStatus: AppInformation + @ObservedObject var arViewModel: ARViewModel + @State var openFlash = true + + var body: some View { + GeometryReader { geometry in + let screenWidth = geometry.size.width + let screenHeight = geometry.size.height + let arViewHeight = min(screenWidth * 1.33, 0.75 * screenHeight) + let arViewWidth = min(arViewHeight / 1.33, screenWidth) + let arViewPadding = 0.2 * arViewHeight + let buttonSize: CGFloat = min(screenWidth * 0.25, 80) + let btBarHeight: CGFloat = 25.0 + let gridSize = appStatus.gridProjectionTrigger.rawValue + + ZStack { + // Transparent background - AR view shows through from MainPage + Color.clear + + ZStack { + // Gripper Overlay on AR View + if let mlManager = arViewModel.mlManager, + let overlayImage = mlManager.currentGripperOverlayImage { + Image(uiImage: overlayImage) + .resizable() + .scaledToFit() + .allowsHitTesting(false) + } + + // Guided Flow Instructions + VStack { + Spacer() + + let instructionText: String = { + // Step 1: AI guidance is off + if !appStatus.mlInferenceEnabled { + return "Enable AI Guidance in Settings" + } + // Step 2: AI on, but Set Goal not clicked yet + if !arViewModel.goalTapModeEnabled { + return "Click on Set Goal" + } + // Step 3: Set Goal clicked, waiting for tap + if arViewModel.mlManager?.currentGoalPoint == nil { + return "Tap a point to set a target object" + } + // Step 4: Goal is set, follow the arrow + return "Follow the arrow" + }() + + Text(instructionText) + .font(.system(size: 14, weight: .medium)) + .foregroundColor(.white.opacity(0.9)) + .padding(.horizontal, 16) + .padding(.vertical, 8) + .background(Color.gray.opacity(0.6)) + .cornerRadius(8) + .shadow(color: .black.opacity(0.2), radius: 2, x: 0, y: 1) + .animation(.easeInOut, value: instructionText) + + Spacer() + .frame(height: 60) + } + + // Manual Next Action Button + if let mlManager = arViewModel.mlManager, + appStatus.mlInferenceEnabled && mlManager.isInferenceEnabled { + VStack { + HStack { + Spacer() + VStack(spacing: 2) { + Button(action: { + mlManager.triggerInferenceManually() + UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() + }) { + Image(systemName: "arrow.forward.circle.fill") + .font(.title2) + .foregroundColor(.white) + .background( + Circle() + .fill(Color.blue.opacity(0.8)) + .frame(width: 44, height: 44) + ) + .shadow(color: .black.opacity(0.3), radius: 4, x: 0, y: 2) + } + + Text("Get next action") + .font(.system(size: 9, weight: .medium)) + .foregroundColor(.white) + .padding(.horizontal, 4) + .padding(.vertical, 1) + .background(Color.black.opacity(0.7)) + .cornerRadius(3) + .shadow(color: .black.opacity(0.4), radius: 1, x: 0, y: 0.5) + } + .padding(.trailing, 12) + .padding(.top, 12) + } + Spacer() + } + } + + // Model Loading Indicator + if let mlManager = arViewModel.mlManager, mlManager.isModelLoading { + ZStack { + Color.black.opacity(0.4) + .ignoresSafeArea() + VStack(spacing: 16) { + ProgressView() + .controlSize(.large) + .tint(.white) + Text("Preparing Model...") + .font(.headline) + .foregroundColor(.white) + } + } + .transition(.opacity) + .zIndex(100) + } + } + .frame(width: arViewWidth, height: arViewHeight) + .padding(.bottom, arViewPadding) + + // ML Status Overlay + VStack { + HStack { + VStack(alignment: .leading, spacing: 8) { + if appStatus.mlInferenceEnabled && arViewModel.mlManager?.isInferenceEnabled == true { + if let mlManager = arViewModel.mlManager { + MLInferenceResultsView(mlManager: mlManager) + } + } + } + Spacer() + } + Spacer() + .padding(.bottom, 10) + } + .frame(width: arViewWidth, height: arViewHeight) + .padding(.bottom, arViewPadding) + + // Top bar with notch area + Bluetooth status + VStack(spacing: 0) { + // White bar for notch/safe area + Color.white + .frame(height: geometry.safeAreaInsets.top) + + // Bluetooth status bar + Text(appStatus.ifBluetoothConnected ? "bluetooth device connected" : "bluetooth device disconnected") + .font(.footnote) + .foregroundColor(Color.white) + .frame(maxWidth: .infinity) + .frame(height: btBarHeight) + .background(appStatus.ifBluetoothConnected ? .green : .red) + + Spacer() + } + .ignoresSafeArea(edges: .top) + + // Grid overlay + if appStatus.gridProjectionTrigger.rawValue > 0 { + VStack { + Path { path in + for col in 1.. some View { + configuration.label.scaleEffect(isRecording ? 0.35 : 1) + } + } + + func toggleRecording(mode: StreamingMode) { + if arViewModel.isOpen { + if mode == .off { + if !arViewModel.isRecording { + // Start recording (for inference, we don't need to save file references) + if let files = arViewModel.startRecording() { + if arViewModel.getBLEManagerInstance().ifConnected { + arViewModel.startBluetoothRecording(targetURL: files.tactileFile, fps: appStatus.animationFPS) + } + } + } else { + if arViewModel.getBLEManagerInstance().ifConnected { + arViewModel.stopBluetoothRecording() + } + arViewModel.stopRecording() + } + } else if mode == .usb { + if !arViewModel.isUSBStreamingActive { + arViewModel.startUSBStreaming() + } else { + arViewModel.stopUSBStreaming() + } + } + } + UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() + } + + func toggleFlash() { + guard let device = AVCaptureDevice.default(for: AVMediaType.video) else { return } + if device.hasTorch { + do { + try device.lockForConfiguration() + device.torchMode = openFlash ? .on : .off + device.unlockForConfiguration() + } catch { + print("Flash could not be used") + } + } + openFlash = !openFlash + UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() + } +} + +#Preview { + InferenceViewOverlay(arViewModel: ARViewModel()) + .environmentObject(AppInformation()) +} \ No newline at end of file diff --git a/AnySense/Views/MLInferenceResultsView.swift b/AnySense/Views/MLInferenceResultsView.swift index ab31358..51cc693 100644 --- a/AnySense/Views/MLInferenceResultsView.swift +++ b/AnySense/Views/MLInferenceResultsView.swift @@ -12,14 +12,26 @@ struct MLInferenceResultsView: View { var body: some View { VStack(alignment: .leading, spacing: 6) { - Text("Gripper State") + Text("Inference State") .foregroundColor(.white) .font(.subheadline) .fontWeight(.semibold) - if let result = mlManager.latestResult { + if mlManager.isInferencePendingUI { + HStack(spacing: 6) { + ProgressView() + .progressViewStyle(.circular) + .tint(.white) + .scaleEffect(0.8) + Text(mlManager.latestResult == nil && mlManager.lastResult == nil ? "Analyzing..." : "Updating...") + .foregroundColor(.white.opacity(0.8)) + .font(.caption) + } + } + + if let result = mlManager.latestResult ?? mlManager.lastResult { GripperBlock(result: result) - } else { + } else if !mlManager.isInferencePendingUI { Text("Analyzing...") .foregroundColor(.white.opacity(0.7)) .font(.caption) diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 16ca296..07b9fc5 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -112,7 +112,7 @@ struct SettingsView : View{ .sheet(isPresented: $showingFilePicker) { ModelImporter(onPickDocument: handleModelUpload) } - + // Compilation Progress if modelManager.isCompiling { HStack { @@ -130,11 +130,11 @@ struct SettingsView : View{ } .padding(.vertical, 5) } - + // Model Selection (when compiled models available) if !modelManager.compiledModels.isEmpty { Picker("Select Model", selection: Binding( - get: { + get: { let activeID = modelManager.activeModelID // print("DEBUG: Picker get - activeModelID: \(String(describing: activeID))") return activeID @@ -157,12 +157,13 @@ struct SettingsView : View{ .padding(.vertical, 5) .id(modelManager.activeModelID?.uuidString ?? "none") // Force refresh when activeModel changes } - - - - // Use Inference Toggle - Context Aware + } + + // MARK: - Inference Settings Section + Section(header: Text("INFERENCE SETTINGS")) { + // Enable AI Guidance Toggle - Context Aware HStack { - Text("Use Inference") + Text("Enable AI Guidance") .font(.body) .foregroundColor(.primary) Spacer() @@ -170,16 +171,16 @@ struct SettingsView : View{ .disabled(!modelManager.hasAvailableModel) } .padding(.vertical, 5) - + // Inference Frequency Slider if let mlManager = arViewModel.mlManager { VStack(alignment: .leading, spacing: 12) { Text("Inference Frequency") .font(.body) .foregroundColor(.primary) - + let sliderBinding = Binding( - get: { + get: { Double(currentFrequencyIndex) }, set: { newValue in @@ -190,16 +191,16 @@ struct SettingsView : View{ } } ) - - Slider(value: sliderBinding, - in: 0...Double(inferenceOptions.count - 1), + + Slider(value: sliderBinding, + in: 0...Double(inferenceOptions.count - 1), step: 1) - + HStack { ForEach(0.. 0 { VStack { Path { path in @@ -185,100 +82,80 @@ struct ReadView : View{ .padding(.bottom, arViewPadding) } - - HStack{ - Text("Demos recorded: ") - Text("\(arViewModel.demosCounter)") - .multilineTextAlignment(.leading) - } - .padding(.top, 0.55 * arViewHeight + 0.2 * screenHeight + 20) - + // Bottom controls with background VStack { Spacer() - ZStack { - // Center Button Layer (Record Button) + + // Controls area with solid background + VStack(spacing: 0) { + // Demo counter with background HStack { - Spacer() - ZStack{ - Image(systemName: "circle") - .resizable() - .aspectRatio(contentMode: .fit) - .frame(height: buttonSize) - .frame(width: buttonSize) - .foregroundStyle(.deviceWord) - .multilineTextAlignment(.center) - Button(action: { - toggleRecording(mode:appStatus.rgbdVideoStreaming) - isRecordedOnce = true - }) { - Image(systemName: isReading ? "square.fill" : "circle.fill") + Text("Demos recorded: ") + Text("\(arViewModel.demosCounter)") + .multilineTextAlignment(.leading) + } + .padding(.top, 10) + + ZStack { + // Center Button Layer + HStack { + Spacer() + ZStack { + Image(systemName: "circle") .resizable() .aspectRatio(contentMode: .fit) - .frame(height: buttonSize - 10) - .frame(width: buttonSize - 10) + .frame(height: buttonSize) + .frame(width: buttonSize) + .foregroundStyle(.deviceWord) .multilineTextAlignment(.center) - .foregroundStyle(Color.red) - } - .buttonStyle(scaleButtonStyle(isRecording: $isReading)) - } - Spacer() - } - - // Side Buttons Layer (Left & Right) - HStack(spacing: 20) { - // Left Side: Delete Button - VStack(spacing: 4) { - Button(action: { - if(isRecordedOnce){ - showingAlert = true - self.activeAlert = .first - } else { - showingAlert = true - self.activeAlert = .second + Button(action: { + toggleRecording(mode: appStatus.rgbdVideoStreaming) + isRecordedOnce = true + }) { + Image(systemName: arViewModel.isRecording ? "square.fill" : "circle.fill") + .resizable() + .aspectRatio(contentMode: .fit) + .frame(height: buttonSize - 10) + .frame(width: buttonSize - 10) + .multilineTextAlignment(.center) + .foregroundStyle(Color.red) } - UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() - }){ - Image(systemName: "trash.circle.fill") - .resizable() - .frame(height: 36) - .frame(width: 36) - .foregroundStyle(.red) + .buttonStyle(scaleButtonStyle(isRecording: arViewModel.isRecording)) } - Text("Delete") - .foregroundStyle(.red) - .font(.caption) - Text("last record") - .foregroundStyle(.red) - .font(.caption) + Spacer() } - Spacer() - - // Right Side: Goal (conditional) + Flash + // Side Buttons Layer HStack(spacing: 20) { - if (arViewModel.mlManager?.isPointConditioned ?? false) { - VStack(spacing: 4) { - Button(action: { - let newValue = !arViewModel.goalTapModeEnabled - arViewModel.goalTapModeEnabled = newValue - if newValue { - // Clear existing goal so the next tap sets a fresh one - arViewModel.mlManager?.clearGoalPoint() - arViewModel.arVisualizationManager.clearTargetPose() - } - }) { - Image(systemName: arViewModel.goalTapModeEnabled ? "dot.circle.fill" : "target") - .resizable() - .frame(height: 36) - .frame(width: 36) - .foregroundStyle(arViewModel.goalTapModeEnabled ? Color.green : Color.blue) + // Delete Button + VStack(spacing: 4) { + Button(action: { + if isRecordedOnce { + showingAlert = true + self.activeAlert = .first + } else { + showingAlert = true + self.activeAlert = .second } - Text("Set goal") - .font(.caption) - .foregroundColor(.secondary) + UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() + }) { + Image(systemName: "trash.circle.fill") + .resizable() + .frame(height: 36) + .frame(width: 36) + .foregroundStyle(.red) } + Text("Delete") + .foregroundStyle(.red) + .font(.caption) + Text("last record") + .foregroundStyle(.red) + .font(.caption) } + Spacer() + + // Flash Button VStack(spacing: 4) { Button(action: toggleFlash) { Image(systemName: openFlash ? "flashlight.off.circle.fill" : "flashlight.on.circle.fill") @@ -291,64 +168,47 @@ struct ReadView : View{ .foregroundColor(.secondary) } } + .padding(.horizontal, 20) } - .padding(.horizontal, 20) + .padding(.bottom, 10) } - .padding(.bottom, max(20, arViewPadding / 4.0)) + .background(Color.customizedBackground) } - - } - .alert(isPresented: $arViewModel.depthStatus.showAlert) { // Show alert when depth is missing - Alert( - title: Text("Depth Data Unavailable"), - message: Text("Your device does not support depth data, or it is temporarily unavailable."), - dismissButton: .default(Text("OK")) - ) } } .alert(isPresented: $showingAlert) { switch activeAlert { case .first: - return Alert(title: Text("Warning") - .foregroundColor(.red), - message: Text("Your last recorded data will all be deleted, are you sure?"), - primaryButton: .destructive(Text("Yes")) { - showingAlert = false - deleteRecordedData(url: paths, targetDirect: fileSetNames!.generalDataDirectory) - arViewModel.updateDemoCounter() - }, - secondaryButton: .cancel(Text("No")) { - showingAlert = false - - } + return Alert( + title: Text("Warning").foregroundColor(.red), + message: Text("Your last recorded data will all be deleted, are you sure?"), + primaryButton: .destructive(Text("Yes")) { + showingAlert = false + let paths = FileManager.default.urls(for: .documentDirectory, in: .userDomainMask) + deleteRecordedData(url: paths, targetDirect: fileSetNames!.generalDataDirectory) + arViewModel.updateDemoCounter() + }, + secondaryButton: .cancel(Text("No")) { + showingAlert = false + } ) case .second: - return Alert(title: Text("Warning") - .foregroundColor(.red), - message: Text("You did not record any data yet!") + return Alert( + title: Text("Warning").foregroundColor(.red), + message: Text("You did not record any data yet!") ) } } - .onChange(of: appStatus.rgbdVideoStreaming) { oldMode, newMode in handleStreamingModeChange(from: oldMode, to: newMode) } - .onChange(of: appStatus.mlInferenceEnabled) { oldValue, newValue in - if newValue { - arViewModel.mlManager?.enableInference() - } else { - arViewModel.mlManager?.disableInference() - } - } .onAppear { initCode() } } - } - // Custom scale effect for the animation of record button - struct scaleButtonStyle : ButtonStyle { - @Binding var isRecording: Bool + struct scaleButtonStyle: ButtonStyle { + let isRecording: Bool func makeBody(configuration: Configuration) -> some View { configuration.label.scaleEffect(isRecording ? 0.35 : 1) } @@ -357,51 +217,38 @@ struct ReadView : View{ private func initCode() { arViewModel.isColorMapOpened = appStatus.colorMapTrigger arViewModel.userFPS = appStatus.animationFPS - - // Sync ML inference setting - if appStatus.mlInferenceEnabled { - arViewModel.mlManager?.enableInference() - } else { - arViewModel.mlManager?.disableInference() - } } private func handleStreamingModeChange(from oldMode: StreamingMode, to newMode: StreamingMode) { - if isReading { + if arViewModel.isRecording { toggleRecording(mode: oldMode) } switch (oldMode, newMode) { case (_, .off): arViewModel.killUSBStreaming() - print("Switched to \(newMode): ARView is active.") case (_, .usb): - print("Switched to \(newMode): ARView is hidden.") arViewModel.setupUSBStreaming() } } func toggleRecording(mode: StreamingMode) { - isReading = !isReading if arViewModel.isOpen { if mode == .off { - if isReading { - fileSetNames = arViewModel.startRecording() - if(arViewModel.getBLEManagerInstance().ifConnected){ - startRecordingBT(targetURL: fileSetNames!.tactileFile) + if !arViewModel.isRecording { + if let files = arViewModel.startRecording() { + fileSetNames = files + if arViewModel.getBLEManagerInstance().ifConnected { + arViewModel.startBluetoothRecording(targetURL: files.tactileFile, fps: appStatus.animationFPS) + } } - -// print(fileSetNames) } else { - if(arViewModel.getBLEManagerInstance().ifConnected){ - stopRecordingBT() - print("This stop recording is when shared bluetooth manager is connected") + if arViewModel.getBLEManagerInstance().ifConnected { + arViewModel.stopBluetoothRecording() } arViewModel.stopRecording() - } - } - else if mode == .usb { - if isReading { + } else if mode == .usb { + if !arViewModel.isUSBStreamingActive { arViewModel.startUSBStreaming() } else { arViewModel.stopUSBStreaming() @@ -409,77 +256,24 @@ struct ReadView : View{ } } UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() - } - func toggleFlash() { - guard let device = AVCaptureDevice.default(for: AVMediaType.video) - else {return} + guard let device = AVCaptureDevice.default(for: AVMediaType.video) else { return } if device.hasTorch { do { try device.lockForConfiguration() - if openFlash == true { device.torchMode = .on // set on - } else { - device.torchMode = .off // set off - } + device.torchMode = openFlash ? .on : .off device.unlockForConfiguration() } catch { print("Flash could not be used") } - } else { - print("Flash is not available") } openFlash = !openFlash UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() } - - func startRecordingBT(targetURL:URL) { - do { - try createFile(fileURL: targetURL) - } - catch { - print("Error creating tactile file.") - } - - arViewModel.getBLEManagerInstance().startRecording( - targetURL: targetURL, - fps: appStatus.animationFPS - ) - } - - func stopRecordingBT() { - arViewModel.getBLEManagerInstance().stopRecording() - } - - func createDocumentaryFolderFiles(paths: [URL], fileSetNames: RecordingFiles?) -> [FileElement] { - guard let fileSetNames = fileSetNames else { - print("❌ Error: Insufficient paths or fileSetNames elements") - return [] - } - - let rgbFile = FileElement.videoFile(VideoFile(url:fileSetNames.rgbFileName)) - let depthFile = FileElement.videoFile(VideoFile(url:fileSetNames.depthFileName)) - let poseFile = FileElement.textFile(TextFile(url:fileSetNames.poseFile.path)) - - var elements = [rgbFile, depthFile, poseFile] - - // Only include image folders if they exist (debug mode was enabled) - if let depthImagesDir = fileSetNames.depthImagesDirectory { - let depthImageFolder = FileElement.directory(SubLevelDirectory(url: depthImagesDir)) - elements.append(depthImageFolder) - } - - if let rgbImagesDir = fileSetNames.rgbImagesDirectory { - let rgbImageFolder = FileElement.directory(SubLevelDirectory(url: rgbImagesDir)) - elements.append(rgbImageFolder) - } - - return elements - } - - func deleteRecordedData(url: [URL], targetDirect: String){ + func deleteRecordedData(url: [URL], targetDirect: String) { do { let urlToDelete = url[0].appendingPathComponent(targetDirect) try FileManager.default.removeItem(at: urlToDelete) @@ -488,16 +282,10 @@ struct ReadView : View{ print("Error deleting file: \(error)") } } - - - } - - - #Preview { - ReadView(arViewModel: ARViewModel()) + ReadViewOverlay(arViewModel: ARViewModel()) .environmentObject(AppInformation()) } \ No newline at end of file diff --git a/README_Inference.md b/README_Inference.md new file mode 100644 index 0000000..a689e8b --- /dev/null +++ b/README_Inference.md @@ -0,0 +1,51 @@ +# Inference View + +The inference view lets you run a point-conditioned CoreML policy on-device, visualize actions in AR, and inspect the gripper state. The purpose of this is to allow for us to be able to test the model without a robot, and get a sense of it's capability(vibe) with you acting as a robot arm, and evaluating in the wild based on the policy's conditioning task. It is optimized for low-latency inference and small memory churn using shared pixel buffers and Accelerate for preprocessing. + +## Model Assumptions + +- CoreML model (converted from RUM/min-stretch pipeline). +- RGB input resized to 224×224 today (code path); original spec 256×256—adjust `modelInputSize`/buffers in `MLInferenceManager` if your model truly requires 256. +- Temporal window: 3 frames (rolling action buffer). +- Inputs: image tensor `[1, 3, H, W]` or `[1, T, 3, H, W]` plus goal tensor (3D point; shape inferred from the model). +- Output: 7 floats (6-DoF action + gripper scalar at index 6). Temporal outputs use the last timestep. + +## Pipeline (MLInferenceManager) + +1) **Model load**: `ModelManager` provides the active compiled model and metadata (temporal frames, input/output names, goal requirement). A loading overlay is shown while this warms up. +2) **Goal conditioning**: A user-tapped 3D goal in world space is transformed to the camera/labels frame just before inference (mapping: `[-x_cam, -z_cam + first-frame 0.02 offset, -y_cam]`). Required models skip inference until a goal exists. +3) **Frame prep**: AR camera frames → vImage/Core Image resize to 224×224 ARGB → normalized MLMultiArray `[1,3,H,W]`. Gripper overlay is composited into the model input when USB streaming is OFF. +4) **Temporal buffer**: Maintain up to 3 action frames. + - USB streaming ON: always roll the buffer; run by frequency (High/Med/Low/Minute) or first inference. + - USB streaming OFF (recording mode): buffer only when proximity trigger fires or on first/manual inference. +5) **Input packing**: Build `[1,T,3,H,W]` with padding if fewer than T frames; build goal tensor matching the model-declared shape; assemble `MLDictionaryFeatureProvider`. +6) **Inference**: Run off-main on a dedicated queue; track inference time; guard with a pending flag to avoid overlap. +7) **Postprocess**: Extract joint actions (last timestep if temporal). Gripper value updates UI + overlay, and AR visualization updates the target pose (skipped in USB mode). Latest result is published for the UI card. + +## UI/Controls (InferenceView) + +- **Set goal**: Tap “Set goal”, then tap in AR to place the 3D target. +- **Start/stop**: App toggle enables/disables inference; model loading overlay appears when switching models. +- **Manual step**: “Get next action” calls manual inference using the buffered frames. +- **Modes**: + - Recording mode (USB off): proximity trigger or manual step drives inference. + - USB streaming: continuous buffer + frequency-based inference; gripper overlay is skipped in the model input because the real gripper is present. +- **Visualization**: AR overlay shows the inferred pose (recording mode only). Gripper overlay image on-screen mirrors predicted gripper open/closed and shows an “iPhone Inferencing” badge when active. +- **Status card**: `MLInferenceResultsView` shows gripper value and OPEN/CLOSED state; “Analyzing…” while waiting for first result. +- **Other controls**: Record/stop capture, delete last recording (with confirm), flash toggle, grid overlay toggle, Bluetooth status bar. + +## How to Use Quickly + +1) Ensure a compiled model is available (see min-stretch conversion flow) and enter the Inference tab. +2) Enable inference; wait for “Preparing Model…” to finish if shown. +3) Tap “Set goal” and place the target in AR. +4) Press Record (or leave USB streaming on) and either approach the goal (proximity trigger) or tap “Get next action.” +5) Watch the AR pose updates (recording mode) and the gripper card/overlay for state and timing feedback. + +## Notes for Researchers + +- Temporal window and goal handling match the training assumptions: three recent frames plus a 3D goal mapped into the labels frame. +- Current resize is 224×224; if your model was exported for 256×256, update `modelInputSize`, shared buffers, and processing paths accordingly. +- Gripper is treated as a continuous scalar; UI thresholds `<0.7` as CLOSED. +- Inference frequency can be throttled to study latency/throughput tradeoffs; visualization frequency is synchronized to the chosen inference cadence. +- Debug hooks: optional frame saves, transform debug prints, and detailed console logs around buffering, padding, and overlay application. From d8eaae7bd03658b01af0fed4faae720444a9755f Mon Sep 17 00:00:00 2001 From: DjKesu Date: Sat, 27 Dec 2025 18:37:41 +0530 Subject: [PATCH 50/56] Prod changes and optimizations --- AnySense/Managers/MLInferenceManager.swift | 109 ++++++++++++++++----- AnySense/Managers/ModelManager.swift | 20 +++- README_Inference.md | 45 ++++----- 3 files changed, 118 insertions(+), 56 deletions(-) diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index cf2dc18..2192f7d 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -96,6 +96,8 @@ class MLInferenceManager: ObservableObject { // MARK: - Shared Buffers (Reused to avoid allocations) private var sharedOutputPixelBuffer: CVPixelBuffer? // Reused CVPixelBuffer for frame processing + private var sharedMLMultiArrayBuffer: MLMultiArray? // Pre-allocated MLMultiArray for frame conversion + private var cachedGripperOverlays: [String: CIImage] = [:] // Cached transformed gripper overlays // MARK: - Gripper Overlay Properties private var gripperOpenCIImage: CIImage? @@ -304,43 +306,74 @@ class MLInferenceManager: ObservableObject { return image } + // Check cache first to avoid expensive transform operations + let cacheKey = "\(currentGripperValue < 0.7 ? "closed" : "open")_\(Int(image.extent.width))x\(Int(image.extent.height))" + if let cachedOverlay = cachedGripperOverlays[cacheKey] { + return applyCachedGripperOverlay(to: image, overlay: cachedOverlay) + } + if saveDebugFrames { print("DEBUG: Applying gripper overlay - value: \(String(format: "%.3f", currentGripperValue))") } - return applyGripperOverlayCoreImage(to: image, overlay: gripperOverlay) - } - - private func applyGripperOverlayCoreImage(to image: CIImage, overlay gripperOverlay: CIImage) -> CIImage { - let imageSize = image.extent.size + let result = applyGripperOverlayCoreImage(to: image, overlay: gripperOverlay) - if saveDebugFrames { - print("DEBUG: Starting composite - image: \(imageSize)") - print("DEBUG: Original overlay extent: \(gripperOverlay.extent)") + // Cache the transformed overlay for reuse + if cachedGripperOverlays.count < 10 { // Limit cache size + let transformedOverlay = createTransformedGripperOverlay(gripperOverlay, imageSize: image.extent.size) + cachedGripperOverlays[cacheKey] = transformedOverlay } + return result + } + + // MARK: - Cached Gripper Overlay Methods + private func createTransformedGripperOverlay(_ gripperOverlay: CIImage, imageSize: CGSize) -> CIImage { // Apply same transformations as camera frames: scale to fit, then rotate if needed let scale = min(imageSize.width / gripperOverlay.extent.width, imageSize.height / gripperOverlay.extent.height) - + // Build combined transform: scale -> optional orientation -> rotation -> translation var transform = CGAffineTransform(scaleX: scale, y: scale) - + // Apply same orientation as camera frames if applyServerImageOrientation { transform = transform.concatenating(CGAffineTransform(rotationAngle: CGFloat.pi)) } - + // Additional +90 degree rotation to align gripper direction with viewpoint transform = transform.concatenating(CGAffineTransform(rotationAngle: CGFloat.pi / 2)) - + // Apply combined transform var transformedOverlay = gripperOverlay.transformed(by: transform) - + // After rotation, translate back to origin for proper overlay positioning let rotatedExtent = transformedOverlay.extent transformedOverlay = transformedOverlay.transformed(by: CGAffineTransform(translationX: -rotatedExtent.origin.x, y: -rotatedExtent.origin.y)) + return transformedOverlay + } + + private func applyCachedGripperOverlay(to image: CIImage, overlay cachedOverlay: CIImage) -> CIImage { + guard let compositeFilter = CIFilter(name: "CISourceOverCompositing") else { + return image + } + + compositeFilter.setValue(cachedOverlay, forKey: kCIInputImageKey) + compositeFilter.setValue(image, forKey: kCIInputBackgroundImageKey) + + return compositeFilter.outputImage ?? image + } + + private func applyGripperOverlayCoreImage(to image: CIImage, overlay gripperOverlay: CIImage) -> CIImage { + let imageSize = image.extent.size + + if saveDebugFrames { + print("DEBUG: Starting composite - image: \(imageSize)") + print("DEBUG: Original overlay extent: \(gripperOverlay.extent)") + } + + let transformedOverlay = createTransformedGripperOverlay(gripperOverlay, imageSize: imageSize) + if saveDebugFrames { - print("DEBUG: Scale: \(String(format: "%.3f", scale))") print("DEBUG: Server orientation: \(applyServerImageOrientation)") print("DEBUG: Final overlay extent: \(transformedOverlay.extent)") } @@ -416,38 +449,38 @@ class MLInferenceManager: ObservableObject { } // Perform loading on background thread to keep UI responsive - DispatchQueue.global(qos: .userInitiated).async { [weak self] in + Task.detached(priority: .userInitiated) { [weak self] in guard let self = self else { return } - + do { - let loadedModel = try self.modelManager.loadModel(for: activeModel) + let loadedModel = try await self.modelManager.loadModelAsync(for: activeModel) // Extract model metadata for type detection let metadata = try ModelMetadata(from: loadedModel) - DispatchQueue.main.async { + await MainActor.run { self.model = loadedModel self.modelMetadata = metadata - + // Always maintain 3-frame rolling buffer self.frameBuffer.removeAll() self.hasRunFirstInference = false // Reset for new model - + print("Model loaded: \(activeModel.name)") print(" Temporal frames: \(metadata.temporalFrames)") print(" Goal conditioning: \(metadata.requiresGoalPoint)") print(" Buffer size: \(self.maxBufferSize)") - + self.modelInputSize = CGSize(width: 224, height: 224) self.initializeSharedBuffers() self.goalDimension = 3 - + // Mark loading as complete self.isModelLoading = false } } catch { print("Error loading model: \(error)") - DispatchQueue.main.async { + await MainActor.run { self.model = nil self.modelMetadata = nil self.frameBuffer.removeAll() @@ -481,6 +514,15 @@ class MLInferenceManager: ObservableObject { sharedOutputPixelBuffer = pixelBuffer } } + + // Initialize shared MLMultiArray buffer (224x224x3) - reused for frame conversion + if sharedMLMultiArrayBuffer == nil { + do { + sharedMLMultiArrayBuffer = try MLMultiArray(shape: [1, 3, 224, 224], dataType: .float32) + } catch { + print("Warning: Could not create shared MLMultiArray buffer: \(error)") + } + } } // MARK: - Model Management Integration @@ -936,8 +978,16 @@ class MLInferenceManager: ObservableObject { // MARK: - Unified Pixel Buffer to MLMultiArray Conversion (Accelerate Optimized) private func convertPixelBufferToMLMultiArray(_ pixelBuffer: CVPixelBuffer, width: Int, height: Int) throws -> MLMultiArray { - // Create new MLMultiArray (can't reuse since it's stored in frameBuffer) - let inputArray = try MLMultiArray(shape: [1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) + // Use shared buffer if available, otherwise create new one + let inputArray: MLMultiArray + if let sharedBuffer = sharedMLMultiArrayBuffer { + inputArray = sharedBuffer + // Clear the buffer by zeroing it out efficiently + memset(inputArray.dataPointer, 0, inputArray.count * MemoryLayout.size) + } else { + // Fallback: create new MLMultiArray + inputArray = try MLMultiArray(shape: [1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) + } guard let baseAddress = CVPixelBufferGetBaseAddress(pixelBuffer) else { throw NSError(domain: "MLInferenceManager", code: -1, userInfo: [NSLocalizedDescriptionKey: "Failed to get pixel buffer base address"]) @@ -992,7 +1042,14 @@ class MLInferenceManager: ObservableObject { vDSP_vfltu8(tempB.assumingMemoryBound(to: UInt8.self), 1, bPtr, 1, vDSP_Length(totalPixels)) vDSP_vsmul(bPtr, 1, &scale, bPtr, 1, vDSP_Length(totalPixels)) - + + // Return a copy of the shared buffer to avoid conflicts when stored in frameBuffer + if inputArray === sharedMLMultiArrayBuffer { + let copyArray = try MLMultiArray(shape: [1, 3, NSNumber(value: height), NSNumber(value: width)], dataType: .float32) + memcpy(copyArray.dataPointer, inputArray.dataPointer, inputArray.count * MemoryLayout.size) + return copyArray + } + return inputArray } diff --git a/AnySense/Managers/ModelManager.swift b/AnySense/Managers/ModelManager.swift index cb652b4..7bc151c 100644 --- a/AnySense/Managers/ModelManager.swift +++ b/AnySense/Managers/ModelManager.swift @@ -426,8 +426,24 @@ class ModelManager: ObservableObject { guard let modelURL = getModelURL(for: modelInfo) else { throw ModelError.modelNotFound("Model file not found: \(modelInfo.name)") } - - return try MLModel(contentsOf: modelURL) + + // Use async loading with configuration for better performance + let config = MLModelConfiguration() + config.computeUnits = .all // Use all available compute units + + return try MLModel(contentsOf: modelURL, configuration: config) + } + + func loadModelAsync(for modelInfo: ModelInfo) async throws -> MLModel { + guard let modelURL = getModelURL(for: modelInfo) else { + throw ModelError.modelNotFound("Model file not found: \(modelInfo.name)") + } + + return try await Task.detached(priority: .userInitiated) { + let config = MLModelConfiguration() + config.computeUnits = .all + return try MLModel(contentsOf: modelURL, configuration: config) + }.value } func getActiveModelMetadata() -> ModelMetadata? { diff --git a/README_Inference.md b/README_Inference.md index a689e8b..565f62e 100644 --- a/README_Inference.md +++ b/README_Inference.md @@ -1,16 +1,17 @@ # Inference View -The inference view lets you run a point-conditioned CoreML policy on-device, visualize actions in AR, and inspect the gripper state. The purpose of this is to allow for us to be able to test the model without a robot, and get a sense of it's capability(vibe) with you acting as a robot arm, and evaluating in the wild based on the policy's conditioning task. It is optimized for low-latency inference and small memory churn using shared pixel buffers and Accelerate for preprocessing. +The inference view lets you run a point-conditioned CoreML policy on-device, visualize actions in AR, and inspect the gripper state. The purpose of this is to allow for us to be able to test the model without a robot, and get a sense of it's capability(vibe) with you acting as a robot arm, and evaluating in the wild based on the policy's conditioning task. The demo model loaded by default is a object pick-up policy. It is optimized for low-latency inference and small memory churn using shared pixel buffers and Accelerate for preprocessing. -## Model Assumptions +## Technical Specifications -- CoreML model (converted from RUM/min-stretch pipeline). -- RGB input resized to 224×224 today (code path); original spec 256×256—adjust `modelInputSize`/buffers in `MLInferenceManager` if your model truly requires 256. -- Temporal window: 3 frames (rolling action buffer). -- Inputs: image tensor `[1, 3, H, W]` or `[1, T, 3, H, W]` plus goal tensor (3D point; shape inferred from the model). -- Output: 7 floats (6-DoF action + gripper scalar at index 6). Temporal outputs use the last timestep. +**Model Requirements:** +The system accepts CoreML models converted from our pipelines such as RUM/min-stretch. Models must process RGB input at 224×224 pixel resolution, though the original specification supported 256×256 pixels. Researchers requiring alternative resolutions can adjust the `modelInputSize` parameter and corresponding buffer allocations in `MLInferenceManager`. -## Pipeline (MLInferenceManager) +The system supports temporal models with up to 3-frame rolling buffers, automatically managing sequence padding for consistency. Input tensors follow standard formats: `[1, 3, H, W]` for single-frame models or `[1, T, 3, H, W]` for temporal architectures, accompanied by goal tensors representing 3D spatial coordinates with shape inferred from model specifications. + +Model outputs must provide 7-element vectors representing 6-DOF manipulation actions plus gripper state. For temporal models, the system extracts predictions from the final timestep, ensuring consistency with training assumptions while accommodating variable sequence lengths. + +## App Pipeline 1) **Model load**: `ModelManager` provides the active compiled model and metadata (temporal frames, input/output names, goal requirement). A loading overlay is shown while this warms up. 2) **Goal conditioning**: A user-tapped 3D goal in world space is transformed to the camera/labels frame just before inference (mapping: `[-x_cam, -z_cam + first-frame 0.02 offset, -y_cam]`). Required models skip inference until a goal exists. @@ -22,30 +23,18 @@ The inference view lets you run a point-conditioned CoreML policy on-device, vis 6) **Inference**: Run off-main on a dedicated queue; track inference time; guard with a pending flag to avoid overlap. 7) **Postprocess**: Extract joint actions (last timestep if temporal). Gripper value updates UI + overlay, and AR visualization updates the target pose (skipped in USB mode). Latest result is published for the UI card. -## UI/Controls (InferenceView) +## UI/Controls - **Set goal**: Tap “Set goal”, then tap in AR to place the 3D target. - **Start/stop**: App toggle enables/disables inference; model loading overlay appears when switching models. -- **Manual step**: “Get next action” calls manual inference using the buffered frames. -- **Modes**: - - Recording mode (USB off): proximity trigger or manual step drives inference. - - USB streaming: continuous buffer + frequency-based inference; gripper overlay is skipped in the model input because the real gripper is present. +- **Manual step**: “Get next action” calls manual inference using the existing buffered frames. This is specifically useful if there's significant deviation from target, and user wants to realign and restart inferencing. This also helps check for robustness in the performance. - **Visualization**: AR overlay shows the inferred pose (recording mode only). Gripper overlay image on-screen mirrors predicted gripper open/closed and shows an “iPhone Inferencing” badge when active. -- **Status card**: `MLInferenceResultsView` shows gripper value and OPEN/CLOSED state; “Analyzing…” while waiting for first result. -- **Other controls**: Record/stop capture, delete last recording (with confirm), flash toggle, grid overlay toggle, Bluetooth status bar. +- **Status card**: `MLInferenceResultsView` shows gripper value and OPEN/CLOSED state. ## How to Use Quickly -1) Ensure a compiled model is available (see min-stretch conversion flow) and enter the Inference tab. -2) Enable inference; wait for “Preparing Model…” to finish if shown. -3) Tap “Set goal” and place the target in AR. -4) Press Record (or leave USB streaming on) and either approach the goal (proximity trigger) or tap “Get next action.” -5) Watch the AR pose updates (recording mode) and the gripper card/overlay for state and timing feedback. - -## Notes for Researchers - -- Temporal window and goal handling match the training assumptions: three recent frames plus a 3D goal mapped into the labels frame. -- Current resize is 224×224; if your model was exported for 256×256, update `modelInputSize`, shared buffers, and processing paths accordingly. -- Gripper is treated as a continuous scalar; UI thresholds `<0.7` as CLOSED. -- Inference frequency can be throttled to study latency/throughput tradeoffs; visualization frequency is synchronized to the chosen inference cadence. -- Debug hooks: optional frame saves, transform debug prints, and detailed console logs around buffering, padding, and overlay application. +1) Ensure a compiled model is available (see min-stretch conversion flow) and enter the Inference tab. A demo model is already loaded up, trained on object pick-up tasks. +2) Enable AI inference from the settings view; wait for “Preparing Model…” to finish if shown. +3) Tap “Set goal” and click on a pointplace the target in AR. +4) Press Record, and start aligning the blue arrow to the red arrow (that changes from red to green as you get closer). As you align, the next action is inferenced. If next action is far off target, you can retry inferencing using the "Get next action" button. +5) Watch the AR pose updates and the gripper card/overlay for state and timing feedback. From e0744f5cb81a25992a151ae69939b37eceb8694e Mon Sep 17 00:00:00 2001 From: DjKesu Date: Sun, 28 Dec 2025 00:33:14 +0530 Subject: [PATCH 51/56] Final complete information including coreml conversion' --- README_Inference.md | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/README_Inference.md b/README_Inference.md index 565f62e..b5ffc45 100644 --- a/README_Inference.md +++ b/README_Inference.md @@ -27,14 +27,18 @@ Model outputs must provide 7-element vectors representing 6-DOF manipulation act - **Set goal**: Tap “Set goal”, then tap in AR to place the 3D target. - **Start/stop**: App toggle enables/disables inference; model loading overlay appears when switching models. -- **Manual step**: “Get next action” calls manual inference using the existing buffered frames. This is specifically useful if there's significant deviation from target, and user wants to realign and restart inferencing. This also helps check for robustness in the performance. +- **Manual step**: "Get next action" calls manual inference using the existing buffered frames. This is specifically useful if there's significant deviation from target, and user wants to realign and restart inferencing. This also helps check for robustness in the performance. - **Visualization**: AR overlay shows the inferred pose (recording mode only). Gripper overlay image on-screen mirrors predicted gripper open/closed and shows an “iPhone Inferencing” badge when active. - **Status card**: `MLInferenceResultsView` shows gripper value and OPEN/CLOSED state. ## How to Use Quickly 1) Ensure a compiled model is available (see min-stretch conversion flow) and enter the Inference tab. A demo model is already loaded up, trained on object pick-up tasks. -2) Enable AI inference from the settings view; wait for “Preparing Model…” to finish if shown. -3) Tap “Set goal” and click on a pointplace the target in AR. +2) Enable AI inference from the settings view; wait for "Preparing Model…" to finish if shown. +3) Tap "Set goal" and click on a pointplace the target in AR. 4) Press Record, and start aligning the blue arrow to the red arrow (that changes from red to green as you get closer). As you align, the next action is inferenced. If next action is far off target, you can retry inferencing using the "Get next action" button. 5) Watch the AR pose updates and the gripper card/overlay for state and timing feedback. + +## Implementation Notes: PyTorch to CoreML Conversion + +Converting PyTorch models (RUM/min-stretch) to CoreML requires refactoring the loss function's forward method from a training-style interface to an inference-only path (`images, goals` → actions), replacing negative dimension indices with explicit positive ones, using slice notation to preserve tensor dimensions, and adding explicit type casts for `F.one_hot()` operations. A `CoreMLBranchStyleWrapper` encapsulates the model and loss function to provide a clean inference path. The conversion notebook is available in the [min-stretch repository's coreml branch](https://github.com/NYU-robot-learning/min-stretch/tree/coreml). From d7af52a520c9355b5382ad05debed907623fc171 Mon Sep 17 00:00:00 2001 From: DjKesu Date: Sun, 28 Dec 2025 00:33:57 +0530 Subject: [PATCH 52/56] final release version --- AnySense.xcodeproj/project.pbxproj | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index ee65ac4..efbbe91 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -524,7 +524,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 5; + CURRENT_PROJECT_VERSION = 6; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; @@ -570,7 +570,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 5; + CURRENT_PROJECT_VERSION = 6; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; From 58b5722e339c523b7131a625dd2b83bf8208867e Mon Sep 17 00:00:00 2001 From: DjKesu Date: Sun, 28 Dec 2025 00:38:27 +0530 Subject: [PATCH 53/56] added information on how to stream actions from iphone to robot --- README_Inference.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/README_Inference.md b/README_Inference.md index b5ffc45..530097b 100644 --- a/README_Inference.md +++ b/README_Inference.md @@ -39,6 +39,10 @@ Model outputs must provide 7-element vectors representing 6-DOF manipulation act 4) Press Record, and start aligning the blue arrow to the red arrow (that changes from red to green as you get closer). As you align, the next action is inferenced. If next action is far off target, you can retry inferencing using the "Get next action" button. 5) Watch the AR pose updates and the gripper card/overlay for state and timing feedback. +## USB Streaming for Robot Control + +The app can stream inference results directly to a robot via USB using the Record3D protocol. When USB streaming is enabled, the iPhone performs on-device inference and streams RGB frames, depth maps, camera poses, and predicted joint actions (7-DOF: 6-DOF manipulation + gripper state) to a connected computer. The robot server receives these action predictions in real-time and can execute them directly. To use this feature, enable "USB Streaming mode" in the Settings tab, connect your iOS device to your computer, and use the [anysense-streaming library](https://github.com/NYU-robot-learning/anysense-streaming/tree/dev/Krish) to receive the stream. The library provides Python and C++ bindings for receiving RGBD data, camera poses, and joint actions via `session.get_joint_actions()`. + ## Implementation Notes: PyTorch to CoreML Conversion Converting PyTorch models (RUM/min-stretch) to CoreML requires refactoring the loss function's forward method from a training-style interface to an inference-only path (`images, goals` → actions), replacing negative dimension indices with explicit positive ones, using slice notation to preserve tensor dimensions, and adding explicit type casts for `F.one_hot()` operations. A `CoreMLBranchStyleWrapper` encapsulates the model and loss function to provide a clean inference path. The conversion notebook is available in the [min-stretch repository's coreml branch](https://github.com/NYU-robot-learning/min-stretch/tree/coreml). From 66bef3ef449442a7e8ea0806664cc2fe8848d810 Mon Sep 17 00:00:00 2001 From: DjKesu Date: Wed, 21 Jan 2026 18:03:27 -0500 Subject: [PATCH 54/56] Update inference UX and onboarding --- AnySense.xcodeproj/project.pbxproj | 4 +- AnySense/MainPage.swift | 113 ++++++++++- AnySense/Managers/ARViewContainer.swift | 127 ++++++++++++- .../Managers/ARVisualizationManager.swift | 33 +--- AnySense/Managers/MLInferenceManager.swift | 52 +++-- AnySense/Views/ContentView.swift | 10 +- AnySense/Views/InferenceView.swift | 178 ++++++++++-------- AnySense/Views/accountView.swift | 44 +---- README_Inference.md | 13 +- 9 files changed, 377 insertions(+), 197 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index efbbe91..9e65cf8 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -524,7 +524,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 6; + CURRENT_PROJECT_VERSION = 19; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; @@ -570,7 +570,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 6; + CURRENT_PROJECT_VERSION = 19; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; diff --git a/AnySense/MainPage.swift b/AnySense/MainPage.swift index efdd1d0..411c2f1 100644 --- a/AnySense/MainPage.swift +++ b/AnySense/MainPage.swift @@ -10,10 +10,13 @@ import SwiftUI struct MainPage: View { @EnvironmentObject private var appStatus : AppInformation @Environment(\.scenePhase) private var phase - let arViewModel: ARViewModel + @ObservedObject var arViewModel: ARViewModel let modelManager: ModelManager // Start the default page be the read page @State private var selection = 1 + @AppStorage("hasSeenWelcomeModal") private var hasSeenWelcomeModal = false + @State private var showWelcomeModal = false + @State private var hasPresentedWelcomeModalThisSession = false // Track if AR tabs are active for showing/hiding the shared AR view private var isARTabActive: Bool { @@ -67,6 +70,11 @@ struct MainPage: View { arViewModel.startARSessionIfNeeded() print("App launched - starting AR session for default tab \(selection)") } + + presentWelcomeModalIfNeeded() + + // Inference is now tab-scoped: enable only on Inference tab (or when USB streaming is active) + syncInferenceForSelectedTab(selection) } .onChange(of: selection) { newTab in let isARTab = (newTab == 1 || newTab == 2) @@ -80,6 +88,13 @@ struct MainPage: View { arViewModel.pauseARSession() print("Switched to non-AR tab \(newTab) - pausing AR session") } + + // Inference is now tab-scoped: enable only on Inference tab (or when USB streaming is active) + syncInferenceForSelectedTab(newTab) + } + .onChange(of: arViewModel.isUSBStreamingActive) { _, _ in + // If USB streaming starts/stops, resync inference enablement without requiring a tab change + syncInferenceForSelectedTab(selection) } .onChange(of: phase) { newPhase in switch newPhase { @@ -92,12 +107,61 @@ struct MainPage: View { arViewModel.resumeARSession() print("App active - resuming AR session for tab \(selection)") } + presentWelcomeModalIfNeeded() case .inactive: print("App inactive") @unknown default: break } } + .overlay { + if showWelcomeModal { + ZStack { + Color.black.opacity(0.35) + .ignoresSafeArea() + + WelcomeModalView( + onClose: { + showWelcomeModal = false + }, + onDontShowAgain: { + hasSeenWelcomeModal = true + showWelcomeModal = false + } + ) + .frame(maxWidth: 340) + .padding(24) + } + .zIndex(200) + } + } + } + + private func presentWelcomeModalIfNeeded() { + guard !hasSeenWelcomeModal, !hasPresentedWelcomeModalThisSession, !showWelcomeModal else { return } + DispatchQueue.main.asyncAfter(deadline: .now() + 0.3) { + guard !hasSeenWelcomeModal else { return } + showWelcomeModal = true + hasPresentedWelcomeModalThisSession = true + } + } + + @MainActor + private func syncInferenceForSelectedTab(_ tab: Int) { + // Inference is active only in the Inference tab, except when USB streaming explicitly needs it. + if tab == 2 { + arViewModel.mlManager?.enableInference() + return + } + + // Leaving inference tab: stop playback and disable inference unless USB streaming is active. + arViewModel.stopInferencePlayback(reset: true) + if arViewModel.isUSBStreamingActive { + // USB streaming sends joint actions; ensure inference is enabled to avoid all-zero actions. + arViewModel.mlManager?.enableInference() + } else { + arViewModel.mlManager?.disableInference() + } } } @@ -124,6 +188,53 @@ struct TabBarButton: View { } } +struct WelcomeModalView: View { + let onClose: () -> Void + let onDontShowAgain: () -> Void + + var body: some View { + VStack(spacing: 16) { + Text("Welcome to Anysense!") + .font(.title2) + .fontWeight(.semibold) + .multilineTextAlignment(.center) + + ScrollView { + Text("This app has been developed by the RUM team to allow for easy data collection, and evaluations. We added an inference tab to allow users to load up a RUM model for object pick up, where you can follow instructions to try picking up an object following directions without a robot!") + .font(.body) + .multilineTextAlignment(.leading) + } + .frame(maxHeight: 240) + + HStack(spacing: 12) { + Button("Close") { + onClose() + } + .buttonStyle(.bordered) + + Button(action: { + onDontShowAgain() + }) { + Text("Don't show this again") + .font(.subheadline) + .foregroundColor(.white) + .padding(.horizontal, 12) + .padding(.vertical, 8) + .frame(maxWidth: .infinity) + } + .background(Color.accentColor) + .clipShape(RoundedRectangle(cornerRadius: 8, style: .continuous)) + } + } + .padding(24) + .background( + RoundedRectangle(cornerRadius: 16, style: .continuous) + .fill(Color(.systemBackground)) + .shadow(color: .black.opacity(0.25), radius: 12, x: 0, y: 6) + ) + } +} + #Preview { MainPage(arViewModel: ARViewModel(), modelManager: ModelManager()) .environmentObject(AppInformation()) diff --git a/AnySense/Managers/ARViewContainer.swift b/AnySense/Managers/ARViewContainer.swift index 75e33f9..efc9711 100644 --- a/AnySense/Managers/ARViewContainer.swift +++ b/AnySense/Managers/ARViewContainer.swift @@ -157,6 +157,10 @@ class ARViewModel: ObservableObject{ @Published var isRecording: Bool = false @Published var recordingMode: RecordingMode = .none private var currentRecordingFiles: RecordingFiles? + + // MARK: - Inference Playback (no file saving) + @Published var isInferencePlaying: Bool = false + @Published var isInferenceEpisodeFinished: Bool = false @@ -542,6 +546,117 @@ class ARViewModel: ObservableObject{ print("Starting AR session for ARViewContainer") setupARSession() } + + // MARK: - Inference Playback (no file saving) + @MainActor + func startInferencePlayback() { + // MARK: - State Validation Guards + guard !isInferencePlaying else { + print("Inference playback already active - ignoring start request") + return + } + + guard !isUSBStreamingActive else { + print("Cannot start inference playback while USB streaming is active") + return + } + + guard !isRecording else { + print("Cannot start inference playback while recording is active") + return + } + + guard recordingMode == .none else { + print("Another recording mode active: \(recordingMode) - stopping first") + stopAllActivities() + // stopAllActivities resets state; if it couldn't, bail safely + guard recordingMode == .none else { return } + return startInferencePlayback() + } + + // Ensure AR session is running + startARSessionIfNeeded() + + // MARK: - Update Centralized State + recordingMode = .mlInference + isInferencePlaying = true + isInferenceEpisodeFinished = false + + // Reset ML inference state for a new playback session (keep goal) + mlManager?.resetInferenceState() + mlManager?.latestResult = nil + mlManager?.lastResult = nil + + // Reset visualization state (fresh origin/targets for new episode) + arVisualizationManager.stopRecordingVisualization() + arVisualizationManager.enableVisualization() + arVisualizationManager.ensureVisualizationReady() + + let fps = userFPS ?? 30.0 + displayLink = CADisplayLink(target: self, selector: #selector(runInferencePlaybackTick)) + displayLink?.preferredFrameRateRange = CAFrameRateRange( + minimum: Float(fps), + maximum: Float(fps), + preferred: Float(fps) + ) + displayLink?.add(to: .main, forMode: .common) + + print("Inference playback started") + } + + @MainActor + func stopInferencePlayback(reset: Bool = true) { + guard isInferencePlaying || recordingMode == .mlInference else { + return + } + + displayLink?.invalidate() + displayLink = nil + + isInferencePlaying = false + isInferenceEpisodeFinished = false + + if recordingMode == .mlInference { + recordingMode = .none + } + + if reset { + mlManager?.resetInferenceState() + mlManager?.latestResult = nil + mlManager?.lastResult = nil + arVisualizationManager.stopRecordingVisualization() + arVisualizationManager.enableVisualization() + arVisualizationManager.ensureVisualizationReady() + // Ensure episode-finished state clears even if last result was CLOSED + arVisualizationManager.setGripperState(isClosed: false) + } + + print("Inference playback stopped") + } + + @MainActor + @objc private func runInferencePlaybackTick(link: CADisplayLink) { + // Avoid doing any work if playback has ended or mode changed + guard isInferencePlaying, recordingMode == .mlInference else { return } + + // Episode finished -> stop processing frames (but keep "Stop" available for reset) + if arVisualizationManager.isGripperClosed { + if !isInferenceEpisodeFinished { + isInferenceEpisodeFinished = true + print("Episode finished (gripper closed) - waiting for reset") + } + return + } + + guard let currentFrame = session.currentFrame else { return } + let rgbPixelBuffer = currentFrame.capturedImage + + if let mlManager = mlManager { + Task { @MainActor in + mlManager.performInference(on: rgbPixelBuffer, arFrame: currentFrame, timestamp: CACurrentMediaTime()) + } + } + } @MainActor func startUSBStreaming() { @@ -858,9 +973,6 @@ class ARViewModel: ObservableObject{ // Reset ML inference state for new recording mlManager?.resetInferenceState() - // Start AR pose visualization with origin at current camera position - arVisualizationManager.startRecordingVisualization() - assetWriter?.startWriting() startTime = CMTimeMake(value: Int64(CACurrentMediaTime() * 1000), timescale: 1000) assetWriter?.startSession(atSourceTime: startTime!) @@ -941,12 +1053,17 @@ class ARViewModel: ObservableObject{ @MainActor func stopAllActivities() { // If nothing is active, avoid redundant cleanup work - if !isRecording && !isUSBStreamingActive && recordingMode == .none && displayLink == nil { + if !isRecording && !isUSBStreamingActive && !isInferencePlaying && recordingMode == .none && displayLink == nil { print("No active activities to stop") return } print("Stopping all activities...") + + // Stop inference playback if active + if isInferencePlaying || recordingMode == .mlInference { + stopInferencePlayback(reset: true) + } // Stop recording if active if isRecording { @@ -971,6 +1088,8 @@ class ARViewModel: ObservableObject{ // Reset state recordingMode = .none currentRecordingFiles = nil + isInferencePlaying = false + isInferenceEpisodeFinished = false print("All activities stopped") } diff --git a/AnySense/Managers/ARVisualizationManager.swift b/AnySense/Managers/ARVisualizationManager.swift index 702265e..17584ca 100644 --- a/AnySense/Managers/ARVisualizationManager.swift +++ b/AnySense/Managers/ARVisualizationManager.swift @@ -30,29 +30,6 @@ enum TargetState { case reached // Green target } -// MARK: - Visualization Frequency -enum VisualizationFrequency: CaseIterable { - case high, medium, low, minute - - var interval: TimeInterval { - switch self { - case .high: return 0.0 - case .medium: return 1.0 - case .low: return 10.0 - case .minute: return 60.0 - } - } - - var displayName: String { - switch self { - case .high: return "High (30 FPS)" - case .medium: return "Medium (1 Hz)" - case .low: return "Low (0.1 FPS)" - case .minute: return "Minute (1/min)" - } - } -} - // MARK: - AR Visualization Manager @MainActor class ARVisualizationManager: ObservableObject { @@ -60,7 +37,6 @@ class ARVisualizationManager: ObservableObject { // MARK: - Published Properties @Published var isVisualizationEnabled: Bool = false @Published var actionState: ActionState = .waiting - @Published var visualizationFrequency: VisualizationFrequency = .medium // MARK: - Private Properties private var arView: ARView? @@ -199,8 +175,8 @@ class ARVisualizationManager: ObservableObject { // MARK: - Initialization helper func ensureVisualizationReady() { + guard isVisualizationEnabled else { return } if !hasEstablishedOrigin { establishWorldOrigin() } - if !isVisualizationEnabled { enableVisualization() } if targetPose != nil && goalPointEntity == nil && worldOriginAnchor != nil { updateGoalPointVisualization() } @@ -351,12 +327,6 @@ class ARVisualizationManager: ObservableObject { actionState = .waiting } - // MARK: - Frequency Control Methods - func setVisualizationFrequency(_ frequency: VisualizationFrequency) { - visualizationFrequency = frequency - print("AR Visualization frequency set to: \(frequency.displayName)") - } - // MARK: - Proximity Configuration func setProximityThreshold(_ threshold: Float) { // Allow adjusting the merge distance threshold if needed @@ -447,7 +417,6 @@ class ARVisualizationManager: ObservableObject { func setTargetPose(_ worldPoint: SIMD3) { targetPose = worldPoint ensureVisualizationReady() - updateGoalPointVisualization() } func clearTargetPose() { diff --git a/AnySense/Managers/MLInferenceManager.swift b/AnySense/Managers/MLInferenceManager.swift index 2192f7d..82ae20e 100644 --- a/AnySense/Managers/MLInferenceManager.swift +++ b/AnySense/Managers/MLInferenceManager.swift @@ -108,7 +108,13 @@ class MLInferenceManager: ObservableObject { private var isUSBStreamingActive: Bool = false private var currentGripperValue: Float = 1.0 // Track latest gripper value @Published var enableGripperOverlay: Bool = true // Default enabled (for model input) - @Published var showGripperOverlayOnScreen: Bool = true // Show overlay on AR view + @Published var showGripperOverlayOnScreen: Bool = true { // Show overlay on AR view + didSet { + Task { @MainActor in + updateGripperOverlayDisplay() + } + } + } @Published var currentGripperOverlayImage: UIImage? // Current overlay image for display @Published var saveDebugFrames: Bool = false // For testing @@ -207,7 +213,7 @@ class MLInferenceManager: ObservableObject { @MainActor private func updateGripperOverlayDisplay() { - guard shouldApplyGripperOverlay() else { + guard shouldShowGripperOverlayOnScreen() else { currentGripperOverlayImage = nil return } @@ -265,18 +271,24 @@ class MLInferenceManager: ObservableObject { func setUSBStreamingState(isActive: Bool) { isUSBStreamingActive = isActive - print("USB streaming state: \(isActive ? "ON" : "OFF") - Gripper overlay: \(shouldApplyGripperOverlay() ? "ENABLED" : "DISABLED")") + let inputOverlay = shouldApplyGripperOverlayToModelInput() ? "ENABLED" : "DISABLED" + let screenOverlay = shouldShowGripperOverlayOnScreen() ? "ON" : "OFF" + print("USB streaming state: \(isActive ? "ON" : "OFF") - Overlay input: \(inputOverlay), Overlay display: \(screenOverlay)") Task { @MainActor in updateGripperOverlayDisplay() } } - private func shouldApplyGripperOverlay() -> Bool { - // Use gripper overlay when USB streaming is OFF (virtual gripper proxy) - // Disable when USB streaming is ON (robot has real gripper) + private func shouldApplyGripperOverlayToModelInput() -> Bool { + // Use gripper overlay in model input when USB streaming is OFF (virtual gripper proxy) return enableGripperOverlay && !isUSBStreamingActive } + private func shouldShowGripperOverlayOnScreen() -> Bool { + // On-screen overlay is user-controlled; keep it off during USB streaming + return showGripperOverlayOnScreen && !isUSBStreamingActive + } + private func getCurrentGripperOverlay() -> CIImage? { // Use closed gripper when gripper value < 0.6, otherwise open gripper let isGripperClosed = currentGripperValue < 0.7 @@ -292,7 +304,7 @@ class MLInferenceManager: ObservableObject { } private func applyGripperOverlay(to image: CIImage) -> CIImage { - guard shouldApplyGripperOverlay() else { + guard shouldApplyGripperOverlayToModelInput() else { if saveDebugFrames { print("DEBUG: Gripper overlay skipped - enableGripperOverlay: \(enableGripperOverlay), isUSBStreaming: \(isUSBStreamingActive)") } @@ -931,7 +943,7 @@ class MLInferenceManager: ObservableObject { let scaledCIImage = CIImage(cvPixelBuffer: outputBuffer) var finalImage = scaledCIImage - if shouldApplyGripperOverlay(), let gripperOverlay = getCurrentGripperOverlay() { + if shouldApplyGripperOverlayToModelInput(), let gripperOverlay = getCurrentGripperOverlay() { finalImage = applyGripperOverlayCoreImage(to: scaledCIImage, overlay: gripperOverlay) } @@ -1178,7 +1190,10 @@ class MLInferenceManager: ObservableObject { self?.lastResult = result // Only enable visualization when NOT in USB streaming mode (recording mode only) - if let arManager = self?.arVisualizationManager, jointPositions.count >= 6, self?.isUSBStreamingActive != true { + if let arManager = self?.arVisualizationManager, + jointPositions.count >= 6, + self?.isUSBStreamingActive != true, + arManager.isVisualizationEnabled { arManager.ensureVisualizationReady() arManager.updatePoseFromMLOutput(jointPositions, timestamp: self?.lastInferenceTime ?? CACurrentMediaTime()) } @@ -1336,23 +1351,4 @@ class MLInferenceManager: ObservableObject { print("Inference frequency: \(frequency.displayName)") } - // MARK: - Frequency Synchronization - func synchronizeFrequencyWithVisualization() { - // Convert MLInferenceManager frequency to ARVisualizationManager frequency - let correspondingVisualizationFrequency: VisualizationFrequency - switch inferenceFrequency { - case .high: - correspondingVisualizationFrequency = .high - case .medium: - correspondingVisualizationFrequency = .medium - case .low: - correspondingVisualizationFrequency = .low - case .minute: - correspondingVisualizationFrequency = .minute - } - - arVisualizationManager?.setVisualizationFrequency(correspondingVisualizationFrequency) - print("Synchronized frequencies: \(inferenceFrequency.displayName)") - } - } diff --git a/AnySense/Views/ContentView.swift b/AnySense/Views/ContentView.swift index 2597984..4b80216 100644 --- a/AnySense/Views/ContentView.swift +++ b/AnySense/Views/ContentView.swift @@ -73,11 +73,6 @@ struct ContentView: View { private func setupModelManager() { // Initialize the ML inference manager with model manager arViewModel.initializeMLManager(with: modelManager) - - // Sync with app status - if appStatus.mlInferenceEnabled { - arViewModel.mlManager?.enableInference() - } } private func openAppSettings() { @@ -114,13 +109,10 @@ class AppInformation : ObservableObject{ @Published var colorMapTrigger: Bool = false @Published var ifBluetoothConnected: Bool = false @Published var ifAudioRecordingEnabled: Bool = false - @Published var mlInferenceEnabled: Bool = false - // MARK: - Inference & Visualization Settings + // MARK: - Inference Settings @Published var showGripperOverlay: Bool = true @Published var enableGripperOverlayInModel: Bool = true - @Published var arVisualizationEnabled: Bool = false - @Published var visualizationFrequency: VisualizationFrequency = .medium } diff --git a/AnySense/Views/InferenceView.swift b/AnySense/Views/InferenceView.swift index 3de566f..a6c9db6 100644 --- a/AnySense/Views/InferenceView.swift +++ b/AnySense/Views/InferenceView.swift @@ -20,6 +20,19 @@ struct InferenceViewOverlay: View { @EnvironmentObject var appStatus: AppInformation @ObservedObject var arViewModel: ARViewModel @State var openFlash = true + @State private var deviceOrientation: UIDeviceOrientation = .unknown + @State private var isLandscape = false + + private var instructionRotation: Angle { + switch deviceOrientation { + case .landscapeLeft: + return .degrees(90) + case .landscapeRight: + return .degrees(-90) + default: + return .degrees(0) + } + } var body: some View { GeometryReader { geometry in @@ -51,39 +64,59 @@ struct InferenceViewOverlay: View { Spacer() let instructionText: String = { - // Step 1: AI guidance is off - if !appStatus.mlInferenceEnabled { - return "Enable AI Guidance in Settings" + guard isLandscape else { + return "Hold landscape" + } + + guard let mlManager = arViewModel.mlManager else { + return "Loading model…" } - // Step 2: AI on, but Set Goal not clicked yet - if !arViewModel.goalTapModeEnabled { - return "Click on Set Goal" + + if arViewModel.isInferenceEpisodeFinished { + return "Episode finished!" } - // Step 3: Set Goal clicked, waiting for tap - if arViewModel.mlManager?.currentGoalPoint == nil { - return "Tap a point to set a target object" + + if arViewModel.isInferencePlaying { + return "Follow the arrows" } - // Step 4: Goal is set, follow the arrow - return "Follow the arrow" + + if mlManager.requiresGoalPoint { + if mlManager.currentGoalPoint == nil { + return arViewModel.goalTapModeEnabled + ? "Click on an object to track" + : "Click on set goal" + } + return "Press play to start demo" + } + + return "Press play to start demo" }() - Text(instructionText) - .font(.system(size: 14, weight: .medium)) - .foregroundColor(.white.opacity(0.9)) - .padding(.horizontal, 16) - .padding(.vertical, 8) - .background(Color.gray.opacity(0.6)) - .cornerRadius(8) - .shadow(color: .black.opacity(0.2), radius: 2, x: 0, y: 1) - .animation(.easeInOut, value: instructionText) + HStack { + Spacer() + Text(instructionText) + .font(.system(size: 14, weight: .medium)) + .multilineTextAlignment(.center) + .foregroundColor(.white.opacity(0.9)) + .padding(.horizontal, 16) + .padding(.vertical, 8) + .background(Color.gray.opacity(0.6)) + .cornerRadius(8) + .shadow(color: .black.opacity(0.2), radius: 2, x: 0, y: 1) + .rotationEffect(isLandscape ? instructionRotation : .degrees(0)) + .animation(.easeInOut, value: instructionText) + .animation(.easeInOut, value: isLandscape) + Spacer() + } Spacer() .frame(height: 60) } + .allowsHitTesting(false) // Manual Next Action Button if let mlManager = arViewModel.mlManager, - appStatus.mlInferenceEnabled && mlManager.isInferenceEnabled { + mlManager.isInferenceEnabled && arViewModel.isInferencePlaying && !arViewModel.isInferenceEpisodeFinished { VStack { HStack { Spacer() @@ -144,7 +177,7 @@ struct InferenceViewOverlay: View { VStack { HStack { VStack(alignment: .leading, spacing: 8) { - if appStatus.mlInferenceEnabled && arViewModel.mlManager?.isInferenceEnabled == true { + if arViewModel.mlManager?.isInferenceEnabled == true { if let mlManager = arViewModel.mlManager { MLInferenceResultsView(mlManager: mlManager) } @@ -157,6 +190,7 @@ struct InferenceViewOverlay: View { } .frame(width: arViewWidth, height: arViewHeight) .padding(.bottom, arViewPadding) + .allowsHitTesting(false) // Top bar with notch area + Bluetooth status VStack(spacing: 0) { @@ -196,6 +230,7 @@ struct InferenceViewOverlay: View { } .frame(width: arViewWidth, height: arViewHeight) .padding(.bottom, arViewPadding) + .allowsHitTesting(false) } // Bottom controls with background @@ -217,25 +252,29 @@ struct InferenceViewOverlay: View { HStack { Spacer() ZStack { - Image(systemName: "circle") - .resizable() - .aspectRatio(contentMode: .fit) - .frame(height: buttonSize) - .frame(width: buttonSize) - .foregroundStyle(.deviceWord) - .multilineTextAlignment(.center) + let canStartInference: Bool = { + guard let mlManager = arViewModel.mlManager else { return false } + if mlManager.requiresGoalPoint && mlManager.currentGoalPoint == nil { + return false + } + return true + }() Button(action: { - toggleRecording(mode: appStatus.rgbdVideoStreaming) + toggleInferencePlayback() }) { - Image(systemName: arViewModel.isRecording ? "square.fill" : "circle.fill") + Image(systemName: arViewModel.isInferencePlaying ? "square.fill" : "play.fill") .resizable() .aspectRatio(contentMode: .fit) .frame(height: buttonSize - 10) .frame(width: buttonSize - 10) .multilineTextAlignment(.center) - .foregroundStyle(Color.red) + .foregroundStyle(arViewModel.isInferencePlaying ? Color.red : Color.green) } - .buttonStyle(scaleButtonStyle(isRecording: arViewModel.isRecording)) + .frame(width: buttonSize, height: buttonSize) + .contentShape(Circle()) + .disabled(!arViewModel.isInferencePlaying && !canStartInference) + .opacity((!arViewModel.isInferencePlaying && !canStartInference) ? 0.5 : 1.0) + .buttonStyle(scaleButtonStyle(isPlaying: arViewModel.isInferencePlaying)) } Spacer() } @@ -289,35 +328,31 @@ struct InferenceViewOverlay: View { } } } - .onChange(of: appStatus.mlInferenceEnabled) { oldValue, newValue in - if newValue { - arViewModel.mlManager?.enableInference() - } else { - arViewModel.mlManager?.disableInference() - } - } .onChange(of: appStatus.showGripperOverlay) { oldValue, newValue in arViewModel.mlManager?.showGripperOverlayOnScreen = newValue } .onChange(of: appStatus.enableGripperOverlayInModel) { oldValue, newValue in arViewModel.mlManager?.enableGripperOverlay = newValue } - .onChange(of: appStatus.arVisualizationEnabled) { oldValue, newValue in - arViewModel.arVisualizationManager.isVisualizationEnabled = newValue - } - .onChange(of: appStatus.visualizationFrequency) { oldValue, newValue in - arViewModel.arVisualizationManager.visualizationFrequency = newValue + .onReceive(NotificationCenter.default.publisher(for: UIDevice.orientationDidChangeNotification)) { _ in + updateOrientation() } .onAppear { + UIDevice.current.beginGeneratingDeviceOrientationNotifications() + updateOrientation() initCode() } + .onDisappear { + UIDevice.current.endGeneratingDeviceOrientationNotifications() + arViewModel.arVisualizationManager.disableVisualization() + } } private func initCode() { arViewModel.isColorMapOpened = appStatus.colorMapTrigger arViewModel.userFPS = appStatus.animationFPS - arViewModel.arVisualizationManager.isVisualizationEnabled = appStatus.arVisualizationEnabled - arViewModel.arVisualizationManager.visualizationFrequency = appStatus.visualizationFrequency + arViewModel.arVisualizationManager.enableVisualization() + arViewModel.arVisualizationManager.ensureVisualizationReady() initializeMLSettings() } @@ -327,45 +362,29 @@ struct InferenceViewOverlay: View { print("ML manager not available during InferenceViewOverlay initialization") return } - if appStatus.mlInferenceEnabled { - mlManager.enableInference() - } else { - mlManager.disableInference() - } + // Inference is tab-scoped; enable while this view is visible. + mlManager.enableInference() mlManager.showGripperOverlayOnScreen = appStatus.showGripperOverlay mlManager.enableGripperOverlay = appStatus.enableGripperOverlayInModel - print("ML settings initialized successfully for InferenceViewOverlay") + print("Inference settings initialized successfully for InferenceViewOverlay") } struct scaleButtonStyle: ButtonStyle { - let isRecording: Bool + let isPlaying: Bool func makeBody(configuration: Configuration) -> some View { - configuration.label.scaleEffect(isRecording ? 0.35 : 1) + configuration.label.scaleEffect(isPlaying ? 0.55 : 1) } } - func toggleRecording(mode: StreamingMode) { + func toggleInferencePlayback() { if arViewModel.isOpen { - if mode == .off { - if !arViewModel.isRecording { - // Start recording (for inference, we don't need to save file references) - if let files = arViewModel.startRecording() { - if arViewModel.getBLEManagerInstance().ifConnected { - arViewModel.startBluetoothRecording(targetURL: files.tactileFile, fps: appStatus.animationFPS) - } - } - } else { - if arViewModel.getBLEManagerInstance().ifConnected { - arViewModel.stopBluetoothRecording() - } - arViewModel.stopRecording() - } - } else if mode == .usb { - if !arViewModel.isUSBStreamingActive { - arViewModel.startUSBStreaming() - } else { - arViewModel.stopUSBStreaming() - } + if !arViewModel.isInferencePlaying { + arViewModel.startInferencePlayback() + } else { + arViewModel.stopInferencePlayback(reset: true) + arViewModel.goalTapModeEnabled = false + arViewModel.mlManager?.clearGoalPoint() + arViewModel.arVisualizationManager.clearTargetPose() } } UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() @@ -385,6 +404,13 @@ struct InferenceViewOverlay: View { openFlash = !openFlash UIImpactFeedbackGenerator(style: appStatus.hapticFeedbackLevel).impactOccurred() } + + private func updateOrientation() { + let orientation = UIDevice.current.orientation + guard orientation.isValidInterfaceOrientation else { return } + deviceOrientation = orientation + isLandscape = orientation.isLandscape + } } #Preview { diff --git a/AnySense/Views/accountView.swift b/AnySense/Views/accountView.swift index 07b9fc5..fd00cf5 100644 --- a/AnySense/Views/accountView.swift +++ b/AnySense/Views/accountView.swift @@ -161,14 +161,11 @@ struct SettingsView : View{ // MARK: - Inference Settings Section Section(header: Text("INFERENCE SETTINGS")) { - // Enable AI Guidance Toggle - Context Aware - HStack { - Text("Enable AI Guidance") - .font(.body) - .foregroundColor(.primary) - Spacer() - Toggle("", isOn: $appStatus.mlInferenceEnabled) - .disabled(!modelManager.hasAvailableModel) + // Inference is tab-scoped (enabled automatically in the Inference tab) + VStack(alignment: .leading, spacing: 4) { + Text("Inference runs automatically in the Inference tab") + .font(.caption) + .foregroundColor(.gray) } .padding(.vertical, 5) @@ -240,37 +237,6 @@ struct SettingsView : View{ } .padding(.vertical, 5) - // AR Visualization Settings - HStack { - VStack(alignment: .leading, spacing: 4) { - Text("AR Visualization") - .font(.body) - .foregroundColor(.primary) - Text("Show 3D arrows and targets") - .font(.caption) - .foregroundColor(.gray) - } - Spacer() - Toggle("", isOn: $appStatus.arVisualizationEnabled) - } - .padding(.vertical, 5) - - // Visualization Frequency - if appStatus.arVisualizationEnabled { - VStack(alignment: .leading, spacing: 8) { - Text("Visualization Frequency") - .font(.body) - .foregroundColor(.primary) - - Picker("Visualization Frequency", selection: $appStatus.visualizationFrequency) { - ForEach(VisualizationFrequency.allCases, id: \.self) { frequency in - Text(frequency.displayName).tag(frequency) - } - } - .pickerStyle(MenuPickerStyle()) - } - .padding(.vertical, 5) - } } } .scrollContentBackground(.hidden) diff --git a/README_Inference.md b/README_Inference.md index 530097b..0c5c93d 100644 --- a/README_Inference.md +++ b/README_Inference.md @@ -26,18 +26,19 @@ Model outputs must provide 7-element vectors representing 6-DOF manipulation act ## UI/Controls - **Set goal**: Tap “Set goal”, then tap in AR to place the 3D target. -- **Start/stop**: App toggle enables/disables inference; model loading overlay appears when switching models. +- **Start/stop**: Inference is enabled automatically in the Inference tab; press **Play/Stop** to start/stop inference (no video is saved). A loading overlay appears when switching models. - **Manual step**: "Get next action" calls manual inference using the existing buffered frames. This is specifically useful if there's significant deviation from target, and user wants to realign and restart inferencing. This also helps check for robustness in the performance. -- **Visualization**: AR overlay shows the inferred pose (recording mode only). Gripper overlay image on-screen mirrors predicted gripper open/closed and shows an “iPhone Inferencing” badge when active. +- **Visualization**: AR overlay shows the inferred pose when **not** in USB streaming mode. Gripper overlay image on-screen mirrors predicted gripper open/closed and shows an “iPhone Inference” badge when active. - **Status card**: `MLInferenceResultsView` shows gripper value and OPEN/CLOSED state. ## How to Use Quickly 1) Ensure a compiled model is available (see min-stretch conversion flow) and enter the Inference tab. A demo model is already loaded up, trained on object pick-up tasks. -2) Enable AI inference from the settings view; wait for "Preparing Model…" to finish if shown. -3) Tap "Set goal" and click on a pointplace the target in AR. -4) Press Record, and start aligning the blue arrow to the red arrow (that changes from red to green as you get closer). As you align, the next action is inferenced. If next action is far off target, you can retry inferencing using the "Get next action" button. -5) Watch the AR pose updates and the gripper card/overlay for state and timing feedback. +2) Hold the phone sideways (**landscape**) while using the demo. Wait for "Preparing Model…" to finish if shown. +3) Tap "Set goal" and tap a point to place the target in AR. +4) Press **Play**, then start aligning the blue arrow to the red arrow (that changes from red to green as you get closer). As you align, the next action is inferred. If the next action is far off target, you can retry using the "Get next action" button. +5) When the gripper closes, the episode is finished; press **Stop** to reset. +6) Watch the AR pose updates and the gripper card/overlay for state and timing feedback. ## USB Streaming for Robot Control From 1287897376aad0efc8fe76ec33c779d573effdea Mon Sep 17 00:00:00 2001 From: DjKesu Date: Thu, 22 Jan 2026 15:18:34 -0500 Subject: [PATCH 55/56] Remove welcome modal and default to inference --- AnySense.xcodeproj/project.pbxproj | 4 +- AnySense/MainPage.swift | 85 +----------------------------- 2 files changed, 3 insertions(+), 86 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index 9e65cf8..d205e27 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -524,7 +524,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 19; + CURRENT_PROJECT_VERSION = 20; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; @@ -570,7 +570,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 19; + CURRENT_PROJECT_VERSION = 20; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; diff --git a/AnySense/MainPage.swift b/AnySense/MainPage.swift index 411c2f1..36b0d57 100644 --- a/AnySense/MainPage.swift +++ b/AnySense/MainPage.swift @@ -13,10 +13,7 @@ struct MainPage: View { @ObservedObject var arViewModel: ARViewModel let modelManager: ModelManager // Start the default page be the read page - @State private var selection = 1 - @AppStorage("hasSeenWelcomeModal") private var hasSeenWelcomeModal = false - @State private var showWelcomeModal = false - @State private var hasPresentedWelcomeModalThisSession = false + @State private var selection = 2 // Track if AR tabs are active for showing/hiding the shared AR view private var isARTabActive: Bool { @@ -71,8 +68,6 @@ struct MainPage: View { print("App launched - starting AR session for default tab \(selection)") } - presentWelcomeModalIfNeeded() - // Inference is now tab-scoped: enable only on Inference tab (or when USB streaming is active) syncInferenceForSelectedTab(selection) } @@ -107,43 +102,12 @@ struct MainPage: View { arViewModel.resumeARSession() print("App active - resuming AR session for tab \(selection)") } - presentWelcomeModalIfNeeded() case .inactive: print("App inactive") @unknown default: break } } - .overlay { - if showWelcomeModal { - ZStack { - Color.black.opacity(0.35) - .ignoresSafeArea() - - WelcomeModalView( - onClose: { - showWelcomeModal = false - }, - onDontShowAgain: { - hasSeenWelcomeModal = true - showWelcomeModal = false - } - ) - .frame(maxWidth: 340) - .padding(24) - } - .zIndex(200) - } - } - } - - private func presentWelcomeModalIfNeeded() { - guard !hasSeenWelcomeModal, !hasPresentedWelcomeModalThisSession, !showWelcomeModal else { return } - DispatchQueue.main.asyncAfter(deadline: .now() + 0.3) { - guard !hasSeenWelcomeModal else { return } - showWelcomeModal = true - hasPresentedWelcomeModalThisSession = true - } } @MainActor @@ -188,53 +152,6 @@ struct TabBarButton: View { } } -struct WelcomeModalView: View { - let onClose: () -> Void - let onDontShowAgain: () -> Void - - var body: some View { - VStack(spacing: 16) { - Text("Welcome to Anysense!") - .font(.title2) - .fontWeight(.semibold) - .multilineTextAlignment(.center) - - ScrollView { - Text("This app has been developed by the RUM team to allow for easy data collection, and evaluations. We added an inference tab to allow users to load up a RUM model for object pick up, where you can follow instructions to try picking up an object following directions without a robot!") - .font(.body) - .multilineTextAlignment(.leading) - } - .frame(maxHeight: 240) - - HStack(spacing: 12) { - Button("Close") { - onClose() - } - .buttonStyle(.bordered) - - Button(action: { - onDontShowAgain() - }) { - Text("Don't show this again") - .font(.subheadline) - .foregroundColor(.white) - .padding(.horizontal, 12) - .padding(.vertical, 8) - .frame(maxWidth: .infinity) - } - .background(Color.accentColor) - .clipShape(RoundedRectangle(cornerRadius: 8, style: .continuous)) - } - } - .padding(24) - .background( - RoundedRectangle(cornerRadius: 16, style: .continuous) - .fill(Color(.systemBackground)) - .shadow(color: .black.opacity(0.25), radius: 12, x: 0, y: 6) - ) - } -} - #Preview { MainPage(arViewModel: ARViewModel(), modelManager: ModelManager()) .environmentObject(AppInformation()) From b1fa12effa59ba5c67d70d0dc854bebcf5dafcb5 Mon Sep 17 00:00:00 2001 From: DjKesu Date: Mon, 9 Feb 2026 12:23:42 -0500 Subject: [PATCH 56/56] Updated readme --- AnySense.xcodeproj/project.pbxproj | 4 ++-- README.md | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/AnySense.xcodeproj/project.pbxproj b/AnySense.xcodeproj/project.pbxproj index d205e27..c05d8c9 100644 --- a/AnySense.xcodeproj/project.pbxproj +++ b/AnySense.xcodeproj/project.pbxproj @@ -524,7 +524,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 20; + CURRENT_PROJECT_VERSION = 21; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; @@ -570,7 +570,7 @@ ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor; CODE_SIGN_IDENTITY = "Apple Development"; CODE_SIGN_STYLE = Automatic; - CURRENT_PROJECT_VERSION = 20; + CURRENT_PROJECT_VERSION = 21; DEVELOPMENT_ASSET_PATHS = ""; DEVELOPMENT_TEAM = 88NB9U5CK6; ENABLE_PREVIEWS = YES; diff --git a/README.md b/README.md index d5aa5cb..0fe373b 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # AnySense -[AnySense](https://anysense.app) is an iPhone application that integrates the iPhone's sensory suite with external multisensory inputs via Bluetooth and wired interfaces, enabling both offline data collection and online streaming to robots. Currently, we record RGB and depth videos, metric depth frames, streamed Bluetooth data appended into a binary file and timestamped pose data as a `.txt` file. Example streaming code for streaming Bluetooth data can be found on [AnySkin](https://any-skin.github.io). We also allow for USB streaming by simply connecting the iPhone to your computer and using this [accompanying library](https://github.com/NYU-robot-learning/anysense-streaming) forked from the excellent [record3d](https://github.com/marek-simonik/record3d) library. +[AnySense](https://anysense.app) is an open-source iPhone app that enables multi-sensory data collection by integrating the iPhone's sensory suite with external sensors via Bluetooth and wired interfaces, enabling both offline data collection and online streaming to robots. The app also supports on-device policy evaluation: you can load a trained CoreML policy, set a 3D goal in AR, and run the policy with AR visualization of predicted actions without a robot. We record RGB and depth videos, metric depth frames, streamed Bluetooth data (e.g. from tactile sensors) into a binary file, and timestamped pose data as a `.txt` file. Example streaming code for Bluetooth data can be found on [AnySkin](https://any-skin.github.io). USB streaming is supported by connecting the iPhone to your computer and using this [accompanying library](https://github.com/NYU-robot-learning/anysense-streaming) (forked from [record3d](https://github.com/marek-simonik/record3d)). ## App Screenshots sdfasdf

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