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[codex] add Mac RDK camera streaming tools #1

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61 changes: 61 additions & 0 deletions new_project/README.md
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Expand Up @@ -59,6 +59,67 @@ YOLO BPU inference node:
ros2 run camera animal_detect
```

Mac local QR -> YOLO test without ROS2/RDK dependencies:

```bash
python3 new_project/local_mission_vision.py --select-camera
```

To only list usable camera indices:

```bash
python3 new_project/local_mission_vision.py --list-cameras
```

The local script uses the selected camera first for QR recognition. After the
QR mission is stable for 3 frames, it switches the same camera stream into YOLO
recognition. If macOS blocks the camera, allow the terminal app running Python
in System Settings -> Privacy & Security -> Camera, then rerun the command.

RDK X5 camera stream to Mac over Ethernet:

```bash
# Do not change the RDK X5 eth0 static IP if it is bound to the MID360 radar.
# First check the RDK address without modifying it:
ip -br addr show eth0

# Mac side: add an address in the same subnet to the USB Ethernet adapter.
# Example if the RDK is 172.20.10.2/24:
sudo ifconfig en8 alias 172.20.10.1 netmask 255.255.255.0
ping 172.20.10.2

# Example if the RDK/radar subnet is 192.168.1.x/24:
# choose a free Mac address that does not duplicate the RDK or radar.
sudo ifconfig en8 alias 192.168.1.250 netmask 255.255.255.0
```

Start the RDK USB camera and MJPEG server:

```bash
source /opt/ros/humble/setup.bash
source /opt/tros/humble/setup.bash

ros2 launch hobot_usb_cam hobot_usb_cam.launch.py \
usb_video_device:=/dev/video0 \
usb_image_width:=1280 \
usb_image_height:=720 \
usb_pixel_format:=mjpeg \
usb_framerate:=30

# In another RDK terminal.
source /opt/ros/humble/setup.bash
source /opt/tros/humble/setup.bash
python3 /home/sunrise/project/rdk_deploy/mjpeg_view.py --port 8080 --fps 20 --quality 75
```

Then open `http://<RDK_IP>:8080` in the Mac browser, or run Mac-side QR ->
YOLO recognition from the RDK camera stream. For example, if the RDK is
`172.20.10.2`:

```bash
python3 new_project/local_mission_vision.py --source http://172.20.10.2:8080/stream
```

## AI Training

The CIFAR-100 source used by the competition picture targets:
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