From a4e3bf381e222fee92cc232255eee371d4f37172 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:21:51 +0800
Subject: [PATCH 01/30] Create image_object_detection

---
 src/image_object_detection | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 src/image_object_detection

diff --git a/src/image_object_detection b/src/image_object_detection
new file mode 100644
index 0000000000..8b13789179
--- /dev/null
+++ b/src/image_object_detection
@@ -0,0 +1 @@
+

From 12a6503d4e26ea17678c8f9c0bea6ec4a5e834fc Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:24:47 +0800
Subject: [PATCH 02/30] Delete src/image_object_detection

---
 src/image_object_detection | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 src/image_object_detection

diff --git a/src/image_object_detection b/src/image_object_detection
deleted file mode 100644
index 8b13789179..0000000000
--- a/src/image_object_detection
+++ /dev/null
@@ -1 +0,0 @@
-

From 0a15c3fcba88b16ab70b1adf3aa2636c1e61f772 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:25:29 +0800
Subject: [PATCH 03/30] Create image_object_detection

---
 src/image_object_detection | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 src/image_object_detection

diff --git a/src/image_object_detection b/src/image_object_detection
new file mode 100644
index 0000000000..8b13789179
--- /dev/null
+++ b/src/image_object_detection
@@ -0,0 +1 @@
+

From 42d02ade9541f864960b9ac2482bcca3c3a09f3b Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:26:24 +0800
Subject: [PATCH 04/30] Delete src/image_object_detection

---
 src/image_object_detection | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 src/image_object_detection

diff --git a/src/image_object_detection b/src/image_object_detection
deleted file mode 100644
index 8b13789179..0000000000
--- a/src/image_object_detection
+++ /dev/null
@@ -1 +0,0 @@
-

From acb8b4de9012476c5ab6f5de962a339c3285868b Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:27:06 +0800
Subject: [PATCH 05/30] Create Image_object_detection

---
 src/Image_object_detection | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 src/Image_object_detection

diff --git a/src/Image_object_detection b/src/Image_object_detection
new file mode 100644
index 0000000000..8b13789179
--- /dev/null
+++ b/src/Image_object_detection
@@ -0,0 +1 @@
+

From 7e0dcb83b37450272fa7cd51a78dacd7b5a8a9cc Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:27:30 +0800
Subject: [PATCH 06/30] Delete src/Image_object_detection

---
 src/Image_object_detection | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 src/Image_object_detection

diff --git a/src/Image_object_detection b/src/Image_object_detection
deleted file mode 100644
index 8b13789179..0000000000
--- a/src/Image_object_detection
+++ /dev/null
@@ -1 +0,0 @@
-

From 7e26f7d825fdee07fc2f5afa070be48156f0259f Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:28:19 +0800
Subject: [PATCH 07/30] Create Image_object_detection

---
 src/Image_object_detection | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 src/Image_object_detection

diff --git a/src/Image_object_detection b/src/Image_object_detection
new file mode 100644
index 0000000000..8b13789179
--- /dev/null
+++ b/src/Image_object_detection
@@ -0,0 +1 @@
+

From 17f5843806decb84cc2b2651887d2dc84027cf16 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:28:34 +0800
Subject: [PATCH 08/30] Delete src/Image_object_detection

---
 src/Image_object_detection | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 src/Image_object_detection

diff --git a/src/Image_object_detection b/src/Image_object_detection
deleted file mode 100644
index 8b13789179..0000000000
--- a/src/Image_object_detection
+++ /dev/null
@@ -1 +0,0 @@
-

From b7a579aa472f17d6ac477ec5419e33a9f7baa657 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:29:25 +0800
Subject: [PATCH 09/30] Create Image_object_detection

---
 src/Image_object_detection | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 src/Image_object_detection

diff --git a/src/Image_object_detection b/src/Image_object_detection
new file mode 100644
index 0000000000..8b13789179
--- /dev/null
+++ b/src/Image_object_detection
@@ -0,0 +1 @@
+

From d093821e28c339cf92cbb1d3ab0f262ccbaf643c Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:30:10 +0800
Subject: [PATCH 10/30] Delete src/Image_object_detection

---
 src/Image_object_detection | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 src/Image_object_detection

diff --git a/src/Image_object_detection b/src/Image_object_detection
deleted file mode 100644
index 8b13789179..0000000000
--- a/src/Image_object_detection
+++ /dev/null
@@ -1 +0,0 @@
-

From e96466ea7e95238027fb804dd5f9c366299e60c6 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:31:18 +0800
Subject: [PATCH 11/30] Create Image_object_detection

---
 src/Image_object_detection | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 src/Image_object_detection

diff --git a/src/Image_object_detection b/src/Image_object_detection
new file mode 100644
index 0000000000..8b13789179
--- /dev/null
+++ b/src/Image_object_detection
@@ -0,0 +1 @@
+

From 044ac8f205d8d5c6ddc2f1051a7d80205abebaf4 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 09:35:33 +0800
Subject: [PATCH 12/30] Delete src/Image_object_detection

---
 src/Image_object_detection | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 src/Image_object_detection

diff --git a/src/Image_object_detection b/src/Image_object_detection
deleted file mode 100644
index 8b13789179..0000000000
--- a/src/Image_object_detection
+++ /dev/null
@@ -1 +0,0 @@
-

From 456f8b1faaa80dbff133e3dda18a3e6120a0e60e Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 8 Dec 2025 11:03:17 +0800
Subject: [PATCH 13/30] Add files via upload

---
 src/image_object_detection/README.md | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 src/image_object_detection/README.md

diff --git a/src/image_object_detection/README.md b/src/image_object_detection/README.md
new file mode 100644
index 0000000000..e0c4b707ee
--- /dev/null
+++ b/src/image_object_detection/README.md
@@ -0,0 +1 @@
+这是一个使用 YOLO 训练模型来进行图像对象检测的系统
\ No newline at end of file

From 989791c09d95db8a8dfec48f637c34ea2658befe Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 09:21:50 +0800
Subject: [PATCH 14/30] Add files via upload

---
 src/image_object_detection/main.py          | 110 ++++++++++++++++++++
 src/image_object_detection/requirements.txt |  15 +++
 2 files changed, 125 insertions(+)
 create mode 100644 src/image_object_detection/main.py
 create mode 100644 src/image_object_detection/requirements.txt

diff --git a/src/image_object_detection/main.py b/src/image_object_detection/main.py
new file mode 100644
index 0000000000..37419ff35f
--- /dev/null
+++ b/src/image_object_detection/main.py
@@ -0,0 +1,110 @@
+# 导入核心库
+from ultralytics import YOLO
+import cv2
+import matplotlib.pyplot as plt
+import os  # 新增：用于路径验证
+
+# -------------------------- 1. 基础配置（重点：替换成你的图片路径！） --------------------------
+# 模型路径：YOLOv8n轻量级预训练模型（自动下载）
+MODEL_PATH = "yolov8n.pt"
+
+# 🔥 关键修改：替换成你图片的绝对路径（右键图片→属性→复制完整路径，加r前缀避免转义）
+# 示例：IMAGE_PATH = r"C:\Users\apple\OneDrive\桌面\my_test_image.jpg"
+IMAGE_PATH = r"C:\Users\apple\OneDrive\桌面\test.jpg"  
+
+# 检测结果保存路径（建议保存到桌面，方便查找）
+SAVE_PATH = r"C:\Users\apple\OneDrive\桌面\detected_image.jpg"
+
+# -------------------------- 2. 加载YOLO模型 --------------------------
+# 加载预训练YOLOv8模型（首次运行自动下载权重，已下载则直接加载）
+model = YOLO(MODEL_PATH)
+
+# -------------------------- 3. 图像检测核心函数（含路径验证） --------------------------
+def detect_image_with_pretrained_model(image_path, save_path):
+    """
+    用预训练YOLO模型检测图像，包含路径验证和友好报错
+    :param image_path: 待检测图片路径
+    :param save_path: 检测结果保存路径
+    """
+    # 第一步：验证图片路径是否存在（核心解决FileNotFoundError）
+    if not os.path.exists(image_path):
+        print(f"\n❌ 错误：找不到图片文件！")
+        print(f"当前设置的图片路径：{image_path}")
+        print(f"请检查：1. 图片是否存在 2. 路径是否正确 3. 路径无中文/空格/特殊符号\n")
+        return  # 路径错误则终止函数
+    
+    # 第二步：执行目标检测（conf=0.25：只显示置信度≥25%的目标）
+    print(f"\n✅ 开始检测图片：{image_path}")
+    results = model(image_path, conf=0.25)
+    
+    # 第三步：可视化检测结果（绘制边界框、类别、置信度）
+    annotated_image = results[0].plot()  # 生成带标注的图片
+    
+    # 转换颜色通道（OpenCV默认BGR，Matplotlib显示需要RGB）
+    annotated_image_rgb = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
+    
+    # 第四步：显示检测结果图片
+    plt.figure(figsize=(12, 8))
+    plt.imshow(annotated_image_rgb)
+    plt.axis("off")  # 隐藏坐标轴
+    plt.title("YOLOv8 Object Detection Result", fontsize=16)
+    plt.show()
+    
+    # 第五步：保存检测结果到指定路径
+    cv2.imwrite(save_path, annotated_image)
+    print(f"\n✅ 检测结果已保存：{save_path}")
+    
+    # 第六步：打印详细检测信息（类别、置信度、坐标）
+    print("\n📌 检测到的目标信息：")
+    for result in results:
+        boxes = result.boxes  # 获取所有检测框
+        if len(boxes) == 0:
+            print("   未检测到任何目标（可降低conf阈值试试，比如conf=0.1）")
+            continue
+        for box in boxes:
+            cls_index = int(box.cls)  # 类别索引
+            cls_name = model.names[cls_index]  # 类别名称（如person/car/cat）
+            confidence = box.conf.item()  # 置信度
+            coordinates = box.xyxy.tolist()[0]  # 边界框坐标 [x1, y1, x2, y2]
+            print(f"   类别：{cls_name} | 置信度：{confidence:.2f} | 坐标：{[round(x, 2) for x in coordinates]}")
+
+# -------------------------- 4. 自定义数据集训练函数（可选） --------------------------
+def train_custom_yolo_model(data_yaml_path, epochs=10, imgsz=640):
+    """
+    训练自定义YOLO模型（需先准备数据集和.yaml配置文件）
+    :param data_yaml_path: 数据集配置文件路径（如dataset/data.yaml）
+    :param epochs: 训练轮数（入门建议10-30）
+    :param imgsz: 输入图像尺寸
+    """
+    if not os.path.exists(data_yaml_path):
+        print(f"\n❌ 错误：数据集配置文件不存在！路径：{data_yaml_path}")
+        return
+    
+    # 加载模型并开始训练
+    train_model = YOLO(MODEL_PATH)
+    train_results = train_model.train(
+        data=data_yaml_path,
+        epochs=epochs,
+        imgsz=imgsz,
+        batch=-1,  # 自动适配批次大小
+        device="cpu",  # 无GPU则用cpu，有GPU改0
+        patience=50,
+        save=True,
+        project="runs/train",
+        name="custom_yolo",
+        exist_ok=True
+    )
+    # 验证模型
+    val_results = train_model.val()
+    print("\n✅ 自定义模型训练完成！验证集指标：", val_results.results_dict)
+
+# -------------------------- 主程序运行入口 --------------------------
+if __name__ == "__main__":
+    # 运行预训练模型检测（核心功能，必执行）
+    detect_image_with_pretrained_model(IMAGE_PATH, SAVE_PATH)
+    
+    # 如需训练自定义数据集，取消下面注释并配置data_yaml_path
+    # train_custom_yolo_model(data_yaml_path=r"C:\Users\apple\OneDrive\桌面\dataset\data.yaml", epochs=10)
+
+
+
diff --git a/src/image_object_detection/requirements.txt b/src/image_object_detection/requirements.txt
new file mode 100644
index 0000000000..f1cc19c3c9
--- /dev/null
+++ b/src/image_object_detection/requirements.txt
@@ -0,0 +1,15 @@
+# YOLOv8核心库（必须）
+ultralytics>=8.0.0  # 推荐8.2.0（稳定版）
+# 图像处理（必须）
+opencv-python>=4.5.0  # 推荐4.8.1.78
+# 可视化（必须）
+matplotlib>=3.0.0  # 推荐3.7.1
+# PyTorch核心（ultralytics依赖，必须）
+torch>=2.0.0  # 推荐2.0.1或2.1.0
+torchvision>=0.15.0  # 与torch版本匹配
+# 基础数值计算（间接依赖，建议指定）
+numpy>=1.21.0  # 推荐1.24.3
+# 可选（补充依赖，避免隐性报错）
+pillow>=8.0.0  # 推荐9.5.0
+psutil>=5.8.0  # ultralytics监控系统资源用
+pyyaml>=6.0  # 自定义训练时解析yaml配置文件
\ No newline at end of file

From 09aeed328f3ed68906bbdbc6fe423ebeb741d4ec Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 10:40:27 +0800
Subject: [PATCH 15/30] Add files via upload
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

项目源代码及其依赖版本

From 556825aea64df3468ae06e5c1e06727c407f0e70 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 10:47:21 +0800
Subject: [PATCH 16/30] Add files via upload
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

项目源代码及依赖版本

From e5faaee653d68f8711293235e61c8f46fbd9041e Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 12:03:21 +0800
Subject: [PATCH 17/30] Delete src/image_object_detection/main.py

---
 src/image_object_detection/main.py | 110 -----------------------------
 1 file changed, 110 deletions(-)
 delete mode 100644 src/image_object_detection/main.py

diff --git a/src/image_object_detection/main.py b/src/image_object_detection/main.py
deleted file mode 100644
index 37419ff35f..0000000000
--- a/src/image_object_detection/main.py
+++ /dev/null
@@ -1,110 +0,0 @@
-# 导入核心库
-from ultralytics import YOLO
-import cv2
-import matplotlib.pyplot as plt
-import os  # 新增：用于路径验证
-
-# -------------------------- 1. 基础配置（重点：替换成你的图片路径！） --------------------------
-# 模型路径：YOLOv8n轻量级预训练模型（自动下载）
-MODEL_PATH = "yolov8n.pt"
-
-# 🔥 关键修改：替换成你图片的绝对路径（右键图片→属性→复制完整路径，加r前缀避免转义）
-# 示例：IMAGE_PATH = r"C:\Users\apple\OneDrive\桌面\my_test_image.jpg"
-IMAGE_PATH = r"C:\Users\apple\OneDrive\桌面\test.jpg"  
-
-# 检测结果保存路径（建议保存到桌面，方便查找）
-SAVE_PATH = r"C:\Users\apple\OneDrive\桌面\detected_image.jpg"
-
-# -------------------------- 2. 加载YOLO模型 --------------------------
-# 加载预训练YOLOv8模型（首次运行自动下载权重，已下载则直接加载）
-model = YOLO(MODEL_PATH)
-
-# -------------------------- 3. 图像检测核心函数（含路径验证） --------------------------
-def detect_image_with_pretrained_model(image_path, save_path):
-    """
-    用预训练YOLO模型检测图像，包含路径验证和友好报错
-    :param image_path: 待检测图片路径
-    :param save_path: 检测结果保存路径
-    """
-    # 第一步：验证图片路径是否存在（核心解决FileNotFoundError）
-    if not os.path.exists(image_path):
-        print(f"\n❌ 错误：找不到图片文件！")
-        print(f"当前设置的图片路径：{image_path}")
-        print(f"请检查：1. 图片是否存在 2. 路径是否正确 3. 路径无中文/空格/特殊符号\n")
-        return  # 路径错误则终止函数
-    
-    # 第二步：执行目标检测（conf=0.25：只显示置信度≥25%的目标）
-    print(f"\n✅ 开始检测图片：{image_path}")
-    results = model(image_path, conf=0.25)
-    
-    # 第三步：可视化检测结果（绘制边界框、类别、置信度）
-    annotated_image = results[0].plot()  # 生成带标注的图片
-    
-    # 转换颜色通道（OpenCV默认BGR，Matplotlib显示需要RGB）
-    annotated_image_rgb = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
-    
-    # 第四步：显示检测结果图片
-    plt.figure(figsize=(12, 8))
-    plt.imshow(annotated_image_rgb)
-    plt.axis("off")  # 隐藏坐标轴
-    plt.title("YOLOv8 Object Detection Result", fontsize=16)
-    plt.show()
-    
-    # 第五步：保存检测结果到指定路径
-    cv2.imwrite(save_path, annotated_image)
-    print(f"\n✅ 检测结果已保存：{save_path}")
-    
-    # 第六步：打印详细检测信息（类别、置信度、坐标）
-    print("\n📌 检测到的目标信息：")
-    for result in results:
-        boxes = result.boxes  # 获取所有检测框
-        if len(boxes) == 0:
-            print("   未检测到任何目标（可降低conf阈值试试，比如conf=0.1）")
-            continue
-        for box in boxes:
-            cls_index = int(box.cls)  # 类别索引
-            cls_name = model.names[cls_index]  # 类别名称（如person/car/cat）
-            confidence = box.conf.item()  # 置信度
-            coordinates = box.xyxy.tolist()[0]  # 边界框坐标 [x1, y1, x2, y2]
-            print(f"   类别：{cls_name} | 置信度：{confidence:.2f} | 坐标：{[round(x, 2) for x in coordinates]}")
-
-# -------------------------- 4. 自定义数据集训练函数（可选） --------------------------
-def train_custom_yolo_model(data_yaml_path, epochs=10, imgsz=640):
-    """
-    训练自定义YOLO模型（需先准备数据集和.yaml配置文件）
-    :param data_yaml_path: 数据集配置文件路径（如dataset/data.yaml）
-    :param epochs: 训练轮数（入门建议10-30）
-    :param imgsz: 输入图像尺寸
-    """
-    if not os.path.exists(data_yaml_path):
-        print(f"\n❌ 错误：数据集配置文件不存在！路径：{data_yaml_path}")
-        return
-    
-    # 加载模型并开始训练
-    train_model = YOLO(MODEL_PATH)
-    train_results = train_model.train(
-        data=data_yaml_path,
-        epochs=epochs,
-        imgsz=imgsz,
-        batch=-1,  # 自动适配批次大小
-        device="cpu",  # 无GPU则用cpu，有GPU改0
-        patience=50,
-        save=True,
-        project="runs/train",
-        name="custom_yolo",
-        exist_ok=True
-    )
-    # 验证模型
-    val_results = train_model.val()
-    print("\n✅ 自定义模型训练完成！验证集指标：", val_results.results_dict)
-
-# -------------------------- 主程序运行入口 --------------------------
-if __name__ == "__main__":
-    # 运行预训练模型检测（核心功能，必执行）
-    detect_image_with_pretrained_model(IMAGE_PATH, SAVE_PATH)
-    
-    # 如需训练自定义数据集，取消下面注释并配置data_yaml_path
-    # train_custom_yolo_model(data_yaml_path=r"C:\Users\apple\OneDrive\桌面\dataset\data.yaml", epochs=10)
-
-
-

From cbe3f1fa350e2090862e11d770ed7e9bb82a8d4f Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 12:03:33 +0800
Subject: [PATCH 18/30] Delete src/image_object_detection/requirements.txt

---
 src/image_object_detection/requirements.txt | 15 ---------------
 1 file changed, 15 deletions(-)
 delete mode 100644 src/image_object_detection/requirements.txt

diff --git a/src/image_object_detection/requirements.txt b/src/image_object_detection/requirements.txt
deleted file mode 100644
index f1cc19c3c9..0000000000
--- a/src/image_object_detection/requirements.txt
+++ /dev/null
@@ -1,15 +0,0 @@
-# YOLOv8核心库（必须）
-ultralytics>=8.0.0  # 推荐8.2.0（稳定版）
-# 图像处理（必须）
-opencv-python>=4.5.0  # 推荐4.8.1.78
-# 可视化（必须）
-matplotlib>=3.0.0  # 推荐3.7.1
-# PyTorch核心（ultralytics依赖，必须）
-torch>=2.0.0  # 推荐2.0.1或2.1.0
-torchvision>=0.15.0  # 与torch版本匹配
-# 基础数值计算（间接依赖，建议指定）
-numpy>=1.21.0  # 推荐1.24.3
-# 可选（补充依赖，避免隐性报错）
-pillow>=8.0.0  # 推荐9.5.0
-psutil>=5.8.0  # ultralytics监控系统资源用
-pyyaml>=6.0  # 自定义训练时解析yaml配置文件
\ No newline at end of file

From de9a2d26ad9b83ffe76a31c699f545721d57ab39 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 17:55:40 +0800
Subject: [PATCH 19/30] Add files via upload
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

项目需要的依赖及其版本
---
 src/image_object_detection/requirements.txt | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
 create mode 100644 src/image_object_detection/requirements.txt

diff --git a/src/image_object_detection/requirements.txt b/src/image_object_detection/requirements.txt
new file mode 100644
index 0000000000..f1cc19c3c9
--- /dev/null
+++ b/src/image_object_detection/requirements.txt
@@ -0,0 +1,15 @@
+# YOLOv8核心库（必须）
+ultralytics>=8.0.0  # 推荐8.2.0（稳定版）
+# 图像处理（必须）
+opencv-python>=4.5.0  # 推荐4.8.1.78
+# 可视化（必须）
+matplotlib>=3.0.0  # 推荐3.7.1
+# PyTorch核心（ultralytics依赖，必须）
+torch>=2.0.0  # 推荐2.0.1或2.1.0
+torchvision>=0.15.0  # 与torch版本匹配
+# 基础数值计算（间接依赖，建议指定）
+numpy>=1.21.0  # 推荐1.24.3
+# 可选（补充依赖，避免隐性报错）
+pillow>=8.0.0  # 推荐9.5.0
+psutil>=5.8.0  # ultralytics监控系统资源用
+pyyaml>=6.0  # 自定义训练时解析yaml配置文件
\ No newline at end of file

From 0c432cdd6d160f52ea6ed55c823d60177ffc43a3 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 17:56:39 +0800
Subject: [PATCH 20/30] Delete src/image_object_detection/requirements.txt

---
 src/image_object_detection/requirements.txt | 15 ---------------
 1 file changed, 15 deletions(-)
 delete mode 100644 src/image_object_detection/requirements.txt

diff --git a/src/image_object_detection/requirements.txt b/src/image_object_detection/requirements.txt
deleted file mode 100644
index f1cc19c3c9..0000000000
--- a/src/image_object_detection/requirements.txt
+++ /dev/null
@@ -1,15 +0,0 @@
-# YOLOv8核心库（必须）
-ultralytics>=8.0.0  # 推荐8.2.0（稳定版）
-# 图像处理（必须）
-opencv-python>=4.5.0  # 推荐4.8.1.78
-# 可视化（必须）
-matplotlib>=3.0.0  # 推荐3.7.1
-# PyTorch核心（ultralytics依赖，必须）
-torch>=2.0.0  # 推荐2.0.1或2.1.0
-torchvision>=0.15.0  # 与torch版本匹配
-# 基础数值计算（间接依赖，建议指定）
-numpy>=1.21.0  # 推荐1.24.3
-# 可选（补充依赖，避免隐性报错）
-pillow>=8.0.0  # 推荐9.5.0
-psutil>=5.8.0  # ultralytics监控系统资源用
-pyyaml>=6.0  # 自定义训练时解析yaml配置文件
\ No newline at end of file

From d46dbef0c3f9c6f9256a62a5c03cb7ac75ce76a7 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 17:57:36 +0800
Subject: [PATCH 21/30] Add files via upload
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

项目需要的依赖及其版本
---
 src/image_object_detection/requirements.txt | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
 create mode 100644 src/image_object_detection/requirements.txt

diff --git a/src/image_object_detection/requirements.txt b/src/image_object_detection/requirements.txt
new file mode 100644
index 0000000000..f1cc19c3c9
--- /dev/null
+++ b/src/image_object_detection/requirements.txt
@@ -0,0 +1,15 @@
+# YOLOv8核心库（必须）
+ultralytics>=8.0.0  # 推荐8.2.0（稳定版）
+# 图像处理（必须）
+opencv-python>=4.5.0  # 推荐4.8.1.78
+# 可视化（必须）
+matplotlib>=3.0.0  # 推荐3.7.1
+# PyTorch核心（ultralytics依赖，必须）
+torch>=2.0.0  # 推荐2.0.1或2.1.0
+torchvision>=0.15.0  # 与torch版本匹配
+# 基础数值计算（间接依赖，建议指定）
+numpy>=1.21.0  # 推荐1.24.3
+# 可选（补充依赖，避免隐性报错）
+pillow>=8.0.0  # 推荐9.5.0
+psutil>=5.8.0  # ultralytics监控系统资源用
+pyyaml>=6.0  # 自定义训练时解析yaml配置文件
\ No newline at end of file

From 7baa7199aff1ba38ffdf91e1c9b26d2d785ba9f5 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 18:11:58 +0800
Subject: [PATCH 22/30] Add files via upload
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

添加YOLO对象检测系统的主程序(main)，UI处理器(ui_handler)，配置文件(config)，检测引擎(detection_engint)，图像检测器(image_detector)
---
 src/image_object_detection/config.py          | 15 ++++
 .../detection_engine.py                       | 57 ++++++++++++++
 src/image_object_detection/image_detector.py  | 63 ++++++++++++++++
 src/image_object_detection/main.py            | 11 +++
 src/image_object_detection/ui_handler.py      | 75 +++++++++++++++++++
 5 files changed, 221 insertions(+)
 create mode 100644 src/image_object_detection/config.py
 create mode 100644 src/image_object_detection/detection_engine.py
 create mode 100644 src/image_object_detection/image_detector.py
 create mode 100644 src/image_object_detection/main.py
 create mode 100644 src/image_object_detection/ui_handler.py

diff --git a/src/image_object_detection/config.py b/src/image_object_detection/config.py
new file mode 100644
index 0000000000..abee289e3d
--- /dev/null
+++ b/src/image_object_detection/config.py
@@ -0,0 +1,15 @@
+# config.py
+class Config:
+    def __init__(self):
+        # 测试图像路径
+        self.test_image_path = r"C:\Users\apple\OneDrive\桌面\test.jpg"
+        
+        # YOLO模型配置
+        self.model_path = "yolov8n.pt"
+        self.confidence_threshold = 0.25
+        
+        # 摄像头配置
+        self.camera_index = 0
+        
+        # 输出频率控制（秒）
+        self.output_interval = 1.0
\ No newline at end of file
diff --git a/src/image_object_detection/detection_engine.py b/src/image_object_detection/detection_engine.py
new file mode 100644
index 0000000000..6f2df4b08b
--- /dev/null
+++ b/src/image_object_detection/detection_engine.py
@@ -0,0 +1,57 @@
+# detection_engine.py
+from ultralytics import YOLO
+import io
+import sys
+
+class DetectionEngine:
+    def __init__(self, model_path="yolov8n.pt", conf_threshold=0.25):
+        self.model_path = model_path
+        self.conf_threshold = conf_threshold
+        self.model = self._load_model()
+    
+    def _load_model(self):
+        """加载YOLO模型并抑制输出"""
+        old_stdout = sys.stdout
+        old_stderr = sys.stderr
+        sys.stdout = io.StringIO()
+        sys.stderr = io.StringIO()
+        
+        try:
+            model = YOLO(self.model_path)
+        finally:
+            sys.stdout = old_stdout
+            sys.stderr = old_stderr
+        
+        return model
+    
+    def detect(self, frame):
+        """对输入帧进行检测"""
+        old_stdout = sys.stdout
+        old_stderr = sys.stderr
+        sys.stdout = io.StringIO()
+        sys.stderr = io.StringIO()
+        
+        try:
+            results = self.model(frame, conf=self.conf_threshold, verbose=False)
+        finally:
+            sys.stdout = old_stdout
+            sys.stderr = old_stderr
+        
+        annotated_frame = results[0].plot()
+        return annotated_frame, results
+    
+    def find_objects(self, frame):
+        """检测并分类图像中的对象"""
+        _, results = self.detect(frame)
+        objects = []
+        for box in results[0].boxes:
+            cls_index = int(box.cls)
+            cls_name = self.model.names[cls_index]
+            coords = box.xyxy.tolist()[0]
+            confidence = box.conf.item()
+            objects.append({
+                "type": cls_name,
+                "bbox": coords,
+                "confidence": confidence
+            })
+        return objects
\ No newline at end of file
diff --git a/src/image_object_detection/image_detector.py b/src/image_object_detection/image_detector.py
new file mode 100644
index 0000000000..ebfbc90bf4
--- /dev/null
+++ b/src/image_object_detection/image_detector.py
@@ -0,0 +1,63 @@
+# image_detector.py
+import cv2
+
+class ImageDetector:
+    def __init__(self, detection_engine):
+        self.engine = detection_engine
+    
+    def detect_static_image(self, image_path):
+        """检测静态图像"""
+        print(f"正在加载图像: {image_path}")
+        
+        if not self._check_image_exists(image_path):
+            return
+        
+        frame = self._load_image(image_path)
+        if frame is None:
+            print("错误: 无法读取图像文件")
+            return
+        
+        print("正在检测图像...")
+        results = self._perform_detection(frame)
+        
+        # 显示检测结果
+        self._display_results(results)
+        
+        # 显示图像
+        self._show_image(results[1][0].plot(), 'YOLO 检测结果 - 静态图像')
+    
+    def _check_image_exists(self, image_path):
+        """检查图像文件是否存在"""
+        if not cv2.os.path.exists(image_path):
+            print(f"错误: 图像文件不存在 - {image_path}")
+            return False
+        return True
+    
+    def _load_image(self, image_path):
+        """加载图像"""
+        return cv2.imread(image_path)
+    
+    def _perform_detection(self, frame):
+        """执行检测"""
+        annotated_frame, results = self.engine.detect(frame)
+        return results
+    
+    def _display_results(self, results):
+        """显示检测结果"""
+        detected_count = len(results[0].boxes)
+        print("检测完成，正在显示结果...")
+        print(f"检测到 {detected_count} 个对象:")
+        
+        for i, box in enumerate(results[0].boxes):
+            cls_index = int(box.cls)
+            cls_name = self.engine.model.names[cls_index]
+            confidence = box.conf.item()
+            print(f"  {i+1}. {cls_name} (置信度: {confidence:.2f})")
+    
+    def _show_image(self, annotated_frame, window_name):
+        """显示图像"""
+        print("\n图像已显示。按任意键关闭窗口...")
+        cv2.imshow(window_name, annotated_frame)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+        print("窗口已关闭。")
\ No newline at end of file
diff --git a/src/image_object_detection/main.py b/src/image_object_detection/main.py
new file mode 100644
index 0000000000..6c1bda8efd
--- /dev/null
+++ b/src/image_object_detection/main.py
@@ -0,0 +1,11 @@
+# main.py
+from ui_handler import UIHandler
+from config import Config
+
+def main():
+    config = Config()
+    ui_handler = UIHandler(config)
+    ui_handler.run()
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/src/image_object_detection/ui_handler.py b/src/image_object_detection/ui_handler.py
new file mode 100644
index 0000000000..53e4036e0d
--- /dev/null
+++ b/src/image_object_detection/ui_handler.py
@@ -0,0 +1,75 @@
+# ui_handler.py
+import cv2
+from detection_engine import DetectionEngine
+from image_detector import ImageDetector
+from camera_detector import CameraDetector
+import sys
+import os
+
+class UIHandler:
+    def __init__(self, config):
+        self.config = config
+        self.detection_engine = DetectionEngine()
+        self.image_detector = ImageDetector(self.detection_engine)
+        self.camera_detector = CameraDetector(self.detection_engine)
+    
+    def print_debug(self, message):
+        """调试输出函数"""
+        print(f"[DEBUG] {message}")
+        sys.stdout.flush()  # 强制刷新输出缓冲区
+    
+    def display_menu(self):
+        """显示主菜单"""
+        print("=" * 60)
+        print("           欢迎使用 YOLO 对象检测系统")
+        print("=" * 60)
+        
+        print(f"\n测试图像路径: {self.config.test_image_path}")
+        print(f"图像文件存在: {os.path.exists(self.config.test_image_path)}")
+        
+        print("\n请选择检测模式:")
+        print("1. 检测静态图像")
+        print("2. 检测摄像头实时画面")
+        print("3. 退出程序")
+    
+    def handle_choice(self, choice):
+        """处理用户选择"""
+        if choice == '1':
+            print("\n您选择了: 检测静态图像")
+            self.image_detector.detect_static_image(self.config.test_image_path)
+            return True
+        elif choice == '2':
+            print("\n您选择了: 检测摄像头实时画面")
+            print("注意：要退出摄像头模式，请按 Ctrl+C ！")
+            self.camera_detector.detect_camera()
+            return True
+        elif choice == '3':
+            print("\n程序已退出。")
+            return False
+        else:
+            print("\n无效选择，请输入 1、2 或 3")
+            return True
+    
+    def run(self):
+        """运行主程序"""
+        self.print_debug("程序开始执行")
+        self.display_menu()
+        
+        running = True
+        while running:
+            try:
+                choice = input("\n请输入您的选择 (1/2/3): ").strip()
+                self.print_debug(f"用户输入: {choice}")
+                running = self.handle_choice(choice)
+                
+            except KeyboardInterrupt:
+                print("\n\n程序被用户中断。")
+                break
+            except EOFError:
+                print("\n输入结束，程序退出。")
+                break
+            except Exception as e:
+                print(f"\n发生错误: {e}")
+                break
+        
+        self.print_debug("程序结束")
\ No newline at end of file

From e2c38edb5e86cab99bb8d14f57f3ec95cf6fde93 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 18:36:10 +0800
Subject: [PATCH 23/30] Update detection_engine.py

---
 .../detection_engine.py                       | 25 ++++++-------------
 1 file changed, 7 insertions(+), 18 deletions(-)

diff --git a/src/image_object_detection/detection_engine.py b/src/image_object_detection/detection_engine.py
index 6f2df4b08b..7e68491ece 100644
--- a/src/image_object_detection/detection_engine.py
+++ b/src/image_object_detection/detection_engine.py
@@ -25,7 +25,11 @@ def _load_model(self):
         return model
     
     def detect(self, frame):
-        """对输入帧进行检测"""
+        """
+        对输入帧进行检测。
+        返回: (annotated_frame: np.ndarray, results: List[Results])
+        即使无检测框，annotated_frame 也是原始图像（HWC格式）。
+        """
         old_stdout = sys.stdout
         old_stderr = sys.stderr
         sys.stdout = io.StringIO()
@@ -37,21 +41,6 @@ def detect(self, frame):
             sys.stdout = old_stdout
             sys.stderr = old_stderr
         
-        annotated_frame = results[0].plot()
+        # YOLOv8 always returns at least one result
+        annotated_frame = results[0].plot()  # numpy array (H, W, C)
         return annotated_frame, results
-    
-    def find_objects(self, frame):
-        """检测并分类图像中的对象"""
-        _, results = self.detect(frame)
-        objects = []
-        for box in results[0].boxes:
-            cls_index = int(box.cls)
-            cls_name = self.model.names[cls_index]
-            coords = box.xyxy.tolist()[0]
-            confidence = box.conf.item()
-            objects.append({
-                "type": cls_name,
-                "bbox": coords,
-                "confidence": confidence
-            })
-        return objects
\ No newline at end of file

From 43271ab42e58c8da1b19fd449233c45af8ad45fc Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 18:37:00 +0800
Subject: [PATCH 24/30] Update image_detector.py

---
 src/image_object_detection/image_detector.py | 101 ++++++++++++++-----
 1 file changed, 75 insertions(+), 26 deletions(-)

diff --git a/src/image_object_detection/image_detector.py b/src/image_object_detection/image_detector.py
index ebfbc90bf4..b161b45597 100644
--- a/src/image_object_detection/image_detector.py
+++ b/src/image_object_detection/image_detector.py
@@ -1,5 +1,7 @@
 # image_detector.py
 import cv2
+import numpy as np
+import traceback
 
 class ImageDetector:
     def __init__(self, detection_engine):
@@ -13,51 +15,98 @@ def detect_static_image(self, image_path):
             return
         
         frame = self._load_image(image_path)
-        if frame is None:
-            print("错误: 无法读取图像文件")
+        if frame is None or frame.size == 0:
+            print("错误: 无法读取图像文件或图像为空")
             return
         
         print("正在检测图像...")
-        results = self._perform_detection(frame)
+        results, annotated_frame = self._perform_detection(frame)
         
-        # 显示检测结果
+        if annotated_frame is None:
+            print("错误: 检测未返回有效图像")
+            return
+        
+        # 显示检测结果文本
         self._display_results(results)
         
-        # 显示图像
-        self._show_image(results[1][0].plot(), 'YOLO 检测结果 - 静态图像')
+        # 显示图像窗口（带固定初始大小）
+        self._show_image(annotated_frame, 'YOLO 检测结果 - 静态图像')
     
     def _check_image_exists(self, image_path):
-        """检查图像文件是否存在"""
-        if not cv2.os.path.exists(image_path):
+        import os
+        if not os.path.exists(image_path):
             print(f"错误: 图像文件不存在 - {image_path}")
             return False
         return True
     
     def _load_image(self, image_path):
-        """加载图像"""
-        return cv2.imread(image_path)
+        try:
+            with open(image_path, "rb") as f:
+                bytes_data = bytearray(f.read())
+            nparr = np.frombuffer(bytes_data, np.uint8)
+            frame = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+            return frame
+        except Exception as e:
+            print(f"加载图像时出错: {e}")
+            return None
     
     def _perform_detection(self, frame):
-        """执行检测"""
-        annotated_frame, results = self.engine.detect(frame)
-        return results
+        try:
+            annotated_frame, results = self.engine.detect(frame)
+            return results, annotated_frame
+        except Exception as e:
+            print(f"检测过程中发生错误: {e}")
+            traceback.print_exc()
+            return [], None
     
     def _display_results(self, results):
-        """显示检测结果"""
-        detected_count = len(results[0].boxes)
+        if not results:
+            print("未检测到任何对象（results 为空）")
+            return
+        
+        result = results[0]
+        boxes = result.boxes
+        if len(boxes) == 0:
+            print("未检测到任何对象")
+            return
+        
         print("检测完成，正在显示结果...")
-        print(f"检测到 {detected_count} 个对象:")
+        print(f"检测到 {len(boxes)} 个对象:")
+        
+        names_list = self.engine.model.names
         
-        for i, box in enumerate(results[0].boxes):
-            cls_index = int(box.cls)
-            cls_name = self.engine.model.names[cls_index]
-            confidence = box.conf.item()
-            print(f"  {i+1}. {cls_name} (置信度: {confidence:.2f})")
+        for i, box in enumerate(boxes):
+            try:
+                cls_index = int(box.cls.item())
+                confidence = box.conf.item()
+                
+                if 0 <= cls_index < len(names_list):
+                    cls_name = names_list[cls_index]
+                else:
+                    cls_name = f"unknown_class_{cls_index}"
+                    print(f"  ⚠️ 警告：类别索引 {cls_index} 超出范围（共 {len(names_list)} 类）")
+                
+                print(f"  {i+1}. {cls_name} (置信度: {confidence:.2f})")
+            except Exception as e:
+                print(f"  ⚠️ 解析第 {i+1} 个检测框时出错: {e}")
     
     def _show_image(self, annotated_frame, window_name):
-        """显示图像"""
+        """显示图像，并设置窗口为可调整的小尺寸"""
+        if annotated_frame is None or annotated_frame.size == 0:
+            print("错误: 标注帧无效，无法显示")
+            return
+        
         print("\n图像已显示。按任意键关闭窗口...")
-        cv2.imshow(window_name, annotated_frame)
-        cv2.waitKey(0)
-        cv2.destroyAllWindows()
-        print("窗口已关闭。")
\ No newline at end of file
+        try:
+            # 创建可调整大小的窗口
+            cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
+            # 设置初始窗口大小为 800x600（你可以按需修改）
+            cv2.resizeWindow(window_name, 800, 600)
+            # 显示图像（OpenCV 会自动适应窗口）
+            cv2.imshow(window_name, annotated_frame)
+            cv2.waitKey(0)
+            cv2.destroyAllWindows()
+            print("窗口已关闭。")
+        except Exception as e:
+            print(f"显示图像时发生错误: {e}")
+            traceback.print_exc()

From 13fa00c88373bb1b40f81efe13f3cd94fd54c391 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Mon, 15 Dec 2025 20:09:23 +0800
Subject: [PATCH 25/30] Create camera_detector.py
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

添加相机识别模块
---
 src/image_object_detection/camera_detector.py | 98 +++++++++++++++++++
 1 file changed, 98 insertions(+)
 create mode 100644 src/image_object_detection/camera_detector.py

diff --git a/src/image_object_detection/camera_detector.py b/src/image_object_detection/camera_detector.py
new file mode 100644
index 0000000000..3964fcc2c6
--- /dev/null
+++ b/src/image_object_detection/camera_detector.py
@@ -0,0 +1,98 @@
+# camera_detector.py
+import cv2
+import time
+
+class CameraDetector:
+    def __init__(self, detection_engine):
+        self.engine = detection_engine
+    
+    def detect_camera(self):
+        """检测摄像头实时画面"""
+        try:
+            # 打开摄像头
+            print("正在打开摄像头...")
+            cap = self._open_camera()
+            
+            if cap is None:
+                return
+            
+            print("摄像头已打开，开始实时检测。")
+            print("在显示窗口中按 'q' 键退出，或在终端中按 Ctrl+C 中断程序。\n")
+            
+            self._run_camera_loop(cap)
+            
+        except KeyboardInterrupt:
+            print("\n\n用户按下了 Ctrl+C，强制退出摄像头检测...")
+            print("程序已安全退出。")
+        except Exception as e:
+            print(f"摄像头检测过程中发生错误: {e}")
+        finally:
+            self._cleanup_resources(cap)
+    
+    def _open_camera(self):
+        """打开摄像头"""
+        cap = cv2.VideoCapture(0)
+        
+        if not cap.isOpened():
+            print("错误: 无法打开摄像头")
+            return None
+        
+        return cap
+    
+    def _run_camera_loop(self, cap):
+        """摄像头检测主循环"""
+        # 记录上次输出时间，控制输出频率
+        last_output_time = time.time()
+        output_interval = 1.0  # 每秒最多输出一次检测信息
+        
+        while True:
+            ret, frame = cap.read()
+            if not ret:
+                print("无法读取摄像头画面，退出...")
+                break
+            
+            results = self._perform_detection(frame)
+            annotated_frame = results[0].plot()
+            
+            # 控制输出频率，避免终端被刷屏
+            self._handle_output_frequency(results, last_output_time, output_interval)
+            last_output_time = time.time()
+            
+            cv2.imshow('YOLO 检测结果 - 摄像头', annotated_frame)
+            
+            # 按 'q' 键退出
+            key = cv2.waitKey(1) & 0xFF
+            if key == ord('q'):
+                print("\n用户按下 'q' 键，退出摄像头检测...")
+                break
+    
+    def _perform_detection(self, frame):
+        """执行检测"""
+        annotated_frame, results = self.engine.detect(frame)
+        return results
+    
+    def _handle_output_frequency(self, results, last_output_time, output_interval):
+        """处理输出频率"""
+        current_time = time.time()
+        if current_time - last_output_time >= output_interval:
+            detected_count = len(results[0].boxes)
+            if detected_count > 0:
+                # 构建检测对象字符串
+                detected_objects = []
+                for box in results[0].boxes:
+                    cls_index = int(box.cls)
+                    cls_name = self.engine.model.names[cls_index]
+                    confidence = box.conf.item()
+                    detected_objects.append(f"{cls_name}({confidence:.2f})")
+                
+                print(f"检测到 {detected_count} 个对象: {', '.join(detected_objects)}")
+    
+    def _cleanup_resources(self, cap):
+        """清理资源"""
+        print("释放摄像头资源...")
+        try:
+            cap.release()
+            cv2.destroyAllWindows()
+        except:
+            pass
+        print("摄像头检测已停止。")

From a85a0bd8dbcfcc27b0482c8b39c6e48b4f118fe8 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Tue, 16 Dec 2025 12:11:33 +0800
Subject: [PATCH 26/30] Update camera_detector.py

---
 src/image_object_detection/camera_detector.py | 172 ++++++++++--------
 1 file changed, 92 insertions(+), 80 deletions(-)

diff --git a/src/image_object_detection/camera_detector.py b/src/image_object_detection/camera_detector.py
index 3964fcc2c6..cb0ad65ca4 100644
--- a/src/image_object_detection/camera_detector.py
+++ b/src/image_object_detection/camera_detector.py
@@ -1,98 +1,110 @@
 # camera_detector.py
 import cv2
 import time
+import os
+import traceback
 
 class CameraDetector:
-    def __init__(self, detection_engine):
+    def __init__(self, detection_engine, camera_index=0):
         self.engine = detection_engine
+        self.camera_index = camera_index
+        self.window_name = "YOLO 实时检测 - 摄像头"
     
     def detect_camera(self):
-        """检测摄像头实时画面"""
+        """对外统一接口：启动摄像头实时检测"""
+        self.start_detection()
+
+    def start_detection(self):
+        """实际执行摄像头检测的逻辑"""
+        print("正在初始化摄像头...")
+        cap = self._open_camera()
+        if cap is None:
+            return
+        
+        cv2.namedWindow(self.window_name, cv2.WINDOW_NORMAL)
+        cv2.resizeWindow(self.window_name, 800, 600)
+        
+        print("摄像头已启动。按 'q' 或 ESC 退出，按 's' 保存当前帧。")
+        
+        prev_time = time.time()
+        saved_frame_index = 0
+        
         try:
-            # 打开摄像头
-            print("正在打开摄像头...")
-            cap = self._open_camera()
-            
-            if cap is None:
-                return
-            
-            print("摄像头已打开，开始实时检测。")
-            print("在显示窗口中按 'q' 键退出，或在终端中按 Ctrl+C 中断程序。\n")
-            
-            self._run_camera_loop(cap)
-            
-        except KeyboardInterrupt:
-            print("\n\n用户按下了 Ctrl+C，强制退出摄像头检测...")
-            print("程序已安全退出。")
+            while True:
+                ret, frame = cap.read()
+                if not ret:
+                    print("警告: 无法读取摄像头帧（可能设备被拔出或占用）")
+                    break
+                
+                annotated_frame, results = self._perform_detection(frame)
+                if annotated_frame is None:
+                    annotated_frame = frame
+                
+                curr_time = time.time()
+                fps = 1.0 / (curr_time - prev_time) if (curr_time - prev_time) > 0 else 0
+                prev_time = curr_time
+                
+                num_objects = len(results[0].boxes) if results else 0
+                info_text = f"FPS: {fps:.1f} | Objects: {num_objects}"
+                cv2.putText(
+                    annotated_frame,
+                    info_text,
+                    (10, 30),
+                    cv2.FONT_HERSHEY_SIMPLEX,
+                    0.7,
+                    (0, 255, 0),
+                    2
+                )
+                
+                cv2.imshow(self.window_name, annotated_frame)
+                
+                key = cv2.waitKey(1) & 0xFF
+                if key == ord('q') or key == 27:
+                    print("用户请求退出。")
+                    break
+                elif key == ord('s'):
+                    saved_frame_index = self._save_frame(annotated_frame, saved_frame_index)
+        
         except Exception as e:
-            print(f"摄像头检测过程中发生错误: {e}")
+            print(f"检测过程中发生未预期错误: {e}")
+            traceback.print_exc()
         finally:
-            self._cleanup_resources(cap)
-    
+            cap.release()
+            cv2.destroyAllWindows()
+            print("摄像头已关闭，窗口已清理.")
+
     def _open_camera(self):
-        """打开摄像头"""
-        cap = cv2.VideoCapture(0)
-        
+        cap = cv2.VideoCapture(self.camera_index)
         if not cap.isOpened():
-            print("错误: 无法打开摄像头")
+            print(f"错误: 无法打开摄像头（索引 {self.camera_index}）")
+            print("请检查摄像头是否连接、是否被其他程序占用。")
             return None
         
+        cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
+        cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
         return cap
-    
-    def _run_camera_loop(self, cap):
-        """摄像头检测主循环"""
-        # 记录上次输出时间，控制输出频率
-        last_output_time = time.time()
-        output_interval = 1.0  # 每秒最多输出一次检测信息
-        
-        while True:
-            ret, frame = cap.read()
-            if not ret:
-                print("无法读取摄像头画面，退出...")
-                break
-            
-            results = self._perform_detection(frame)
-            annotated_frame = results[0].plot()
-            
-            # 控制输出频率，避免终端被刷屏
-            self._handle_output_frequency(results, last_output_time, output_interval)
-            last_output_time = time.time()
-            
-            cv2.imshow('YOLO 检测结果 - 摄像头', annotated_frame)
-            
-            # 按 'q' 键退出
-            key = cv2.waitKey(1) & 0xFF
-            if key == ord('q'):
-                print("\n用户按下 'q' 键，退出摄像头检测...")
-                break
-    
+
     def _perform_detection(self, frame):
-        """执行检测"""
-        annotated_frame, results = self.engine.detect(frame)
-        return results
-    
-    def _handle_output_frequency(self, results, last_output_time, output_interval):
-        """处理输出频率"""
-        current_time = time.time()
-        if current_time - last_output_time >= output_interval:
-            detected_count = len(results[0].boxes)
-            if detected_count > 0:
-                # 构建检测对象字符串
-                detected_objects = []
-                for box in results[0].boxes:
-                    cls_index = int(box.cls)
-                    cls_name = self.engine.model.names[cls_index]
-                    confidence = box.conf.item()
-                    detected_objects.append(f"{cls_name}({confidence:.2f})")
-                
-                print(f"检测到 {detected_count} 个对象: {', '.join(detected_objects)}")
-    
-    def _cleanup_resources(self, cap):
-        """清理资源"""
-        print("释放摄像头资源...")
         try:
-            cap.release()
-            cv2.destroyAllWindows()
-        except:
-            pass
-        print("摄像头检测已停止。")
+            # 抑制 YOLO 内部输出
+            import sys, os
+            old_stdout = sys.stdout
+            sys.stdout = open(os.devnull, 'w')
+            annotated_frame, results = self.engine.detect(frame)
+            sys.stdout = old_stdout
+            return annotated_frame, results
+        except Exception as e:
+            print(f"单帧检测失败: {e}")
+            return None, []
+
+    def _save_frame(self, frame, index):
+        save_dir = "saved_frames"
+        os.makedirs(save_dir, exist_ok=True)
+        filename = os.path.join(save_dir, f"frame_{index:04d}.jpg")
+        success = cv2.imwrite(filename, frame)
+        if success:
+            print(f"✅ 帧已保存: {filename}")
+            return index + 1
+        else:
+            print("❌ 保存帧失败！")
+            return index

From 4ec40e15c67ddd333f49eb43ae01f42dd2f85009 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Tue, 16 Dec 2025 17:28:03 +0800
Subject: [PATCH 27/30] Update main.py
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

禁用GUI
---
 src/image_object_detection/main.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/src/image_object_detection/main.py b/src/image_object_detection/main.py
index 6c1bda8efd..dc6d559477 100644
--- a/src/image_object_detection/main.py
+++ b/src/image_object_detection/main.py
@@ -1,4 +1,7 @@
 # main.py
+import matplotlib
+matplotlib.use('Agg')  # 必须在最前，禁用 GUI 后端
+
 from ui_handler import UIHandler
 from config import Config
 
@@ -8,4 +11,4 @@ def main():
     ui_handler.run()
 
 if __name__ == "__main__":
-    main()
\ No newline at end of file
+    main()

From 93f4da1b708219ed7316098987c2535a7769f8ce Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Tue, 16 Dec 2025 17:29:31 +0800
Subject: [PATCH 28/30] Update image_detector.py

---
 src/image_object_detection/image_detector.py | 86 +++++---------------
 1 file changed, 20 insertions(+), 66 deletions(-)

diff --git a/src/image_object_detection/image_detector.py b/src/image_object_detection/image_detector.py
index b161b45597..70f31256b2 100644
--- a/src/image_object_detection/image_detector.py
+++ b/src/image_object_detection/image_detector.py
@@ -2,111 +2,65 @@
 import cv2
 import numpy as np
 import traceback
+import os
 
 class ImageDetector:
     def __init__(self, detection_engine):
         self.engine = detection_engine
     
     def detect_static_image(self, image_path):
-        """检测静态图像"""
-        print(f"正在加载图像: {image_path}")
+        print(f"Loading image: {image_path}")
         
-        if not self._check_image_exists(image_path):
+        if not os.path.exists(image_path):
+            print(f"Error: Image file not found - {image_path}")
             return
         
-        frame = self._load_image(image_path)
+        frame = cv2.imread(image_path)
         if frame is None or frame.size == 0:
-            print("错误: 无法读取图像文件或图像为空")
+            print("Error: Failed to load image")
             return
         
-        print("正在检测图像...")
-        results, annotated_frame = self._perform_detection(frame)
+        print("Running detection...")
+        annotated_frame, results = self.engine.detect(frame)
         
-        if annotated_frame is None:
-            print("错误: 检测未返回有效图像")
+        if annotated_frame is None or annotated_frame.size == 0:
+            print("Error: Invalid annotated frame")
             return
         
-        # 显示检测结果文本
         self._display_results(results)
-        
-        # 显示图像窗口（带固定初始大小）
-        self._show_image(annotated_frame, 'YOLO 检测结果 - 静态图像')
-    
-    def _check_image_exists(self, image_path):
-        import os
-        if not os.path.exists(image_path):
-            print(f"错误: 图像文件不存在 - {image_path}")
-            return False
-        return True
-    
-    def _load_image(self, image_path):
-        try:
-            with open(image_path, "rb") as f:
-                bytes_data = bytearray(f.read())
-            nparr = np.frombuffer(bytes_data, np.uint8)
-            frame = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-            return frame
-        except Exception as e:
-            print(f"加载图像时出错: {e}")
-            return None
-    
-    def _perform_detection(self, frame):
-        try:
-            annotated_frame, results = self.engine.detect(frame)
-            return results, annotated_frame
-        except Exception as e:
-            print(f"检测过程中发生错误: {e}")
-            traceback.print_exc()
-            return [], None
+        self._show_image(annotated_frame, "YOLO_Static_Detection")
     
     def _display_results(self, results):
         if not results:
-            print("未检测到任何对象（results 为空）")
+            print("No objects detected.")
             return
         
         result = results[0]
         boxes = result.boxes
         if len(boxes) == 0:
-            print("未检测到任何对象")
+            print("No objects detected.")
             return
         
-        print("检测完成，正在显示结果...")
-        print(f"检测到 {len(boxes)} 个对象:")
-        
+        print(f"Detected {len(boxes)} object(s):")
         names_list = self.engine.model.names
         
         for i, box in enumerate(boxes):
             try:
                 cls_index = int(box.cls.item())
                 confidence = box.conf.item()
-                
-                if 0 <= cls_index < len(names_list):
-                    cls_name = names_list[cls_index]
-                else:
-                    cls_name = f"unknown_class_{cls_index}"
-                    print(f"  ⚠️ 警告：类别索引 {cls_index} 超出范围（共 {len(names_list)} 类）")
-                
-                print(f"  {i+1}. {cls_name} (置信度: {confidence:.2f})")
+                cls_name = names_list[cls_index] if 0 <= cls_index < len(names_list) else f"unknown_{cls_index}"
+                print(f"  {i+1}. {cls_name} (confidence: {confidence:.2f})")
             except Exception as e:
-                print(f"  ⚠️ 解析第 {i+1} 个检测框时出错: {e}")
+                print(f"  Warning: Failed to parse box {i+1}: {e}")
     
-    def _show_image(self, annotated_frame, window_name):
-        """显示图像，并设置窗口为可调整的小尺寸"""
-        if annotated_frame is None or annotated_frame.size == 0:
-            print("错误: 标注帧无效，无法显示")
-            return
-        
-        print("\n图像已显示。按任意键关闭窗口...")
+    def _show_image(self, annotated_frame, window_name="YOLO_Static_Detection"):
         try:
-            # 创建可调整大小的窗口
+            cv2.destroyAllWindows()
             cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
-            # 设置初始窗口大小为 800x600（你可以按需修改）
             cv2.resizeWindow(window_name, 800, 600)
-            # 显示图像（OpenCV 会自动适应窗口）
             cv2.imshow(window_name, annotated_frame)
             cv2.waitKey(0)
             cv2.destroyAllWindows()
-            print("窗口已关闭。")
         except Exception as e:
-            print(f"显示图像时发生错误: {e}")
+            print(f"Failed to display image: {e}")
             traceback.print_exc()

From 2e4d4a8d39e3e8d58266db34a47c376cd93a5c92 Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Tue, 16 Dec 2025 17:30:16 +0800
Subject: [PATCH 29/30] Update camera_detector.py

---
 src/image_object_detection/camera_detector.py | 119 ++++++------------
 1 file changed, 41 insertions(+), 78 deletions(-)

diff --git a/src/image_object_detection/camera_detector.py b/src/image_object_detection/camera_detector.py
index cb0ad65ca4..466e923f15 100644
--- a/src/image_object_detection/camera_detector.py
+++ b/src/image_object_detection/camera_detector.py
@@ -1,110 +1,73 @@
 # camera_detector.py
 import cv2
 import time
-import os
 import traceback
 
 class CameraDetector:
-    def __init__(self, detection_engine, camera_index=0):
+    def __init__(self, detection_engine, output_interval=1.0):
         self.engine = detection_engine
-        self.camera_index = camera_index
-        self.window_name = "YOLO 实时检测 - 摄像头"
+        self.output_interval = output_interval
+        self.last_output_time = 0
+        self.frame_count = 0
+        self.window_name = "YOLO_Live_Detection"  # 👈 英文窗口名
     
-    def detect_camera(self):
-        """对外统一接口：启动摄像头实时检测"""
-        self.start_detection()
-
-    def start_detection(self):
-        """实际执行摄像头检测的逻辑"""
-        print("正在初始化摄像头...")
-        cap = self._open_camera()
-        if cap is None:
+    def start_detection(self, camera_index=0):
+        cap = cv2.VideoCapture(camera_index)
+        if not cap.isOpened():
+            print(f"Error: Cannot open camera {camera_index}")
             return
         
-        cv2.namedWindow(self.window_name, cv2.WINDOW_NORMAL)
-        cv2.resizeWindow(self.window_name, 800, 600)
-        
-        print("摄像头已启动。按 'q' 或 ESC 退出，按 's' 保存当前帧。")
-        
-        prev_time = time.time()
-        saved_frame_index = 0
+        print("Starting live detection. Press 'q' to quit, 's' to save frame.")
+        cv2.namedWindow(self.window_name, cv2.WINDOW_NORMAL)  # 创建一次即可
         
         try:
             while True:
                 ret, frame = cap.read()
                 if not ret:
-                    print("警告: 无法读取摄像头帧（可能设备被拔出或占用）")
+                    print("Warning: Failed to read frame from camera")
                     break
                 
-                annotated_frame, results = self._perform_detection(frame)
-                if annotated_frame is None:
-                    annotated_frame = frame
+                current_time = time.time()
+                annotated_frame, results = self.engine.detect(frame)
                 
-                curr_time = time.time()
-                fps = 1.0 / (curr_time - prev_time) if (curr_time - prev_time) > 0 else 0
-                prev_time = curr_time
-                
-                num_objects = len(results[0].boxes) if results else 0
-                info_text = f"FPS: {fps:.1f} | Objects: {num_objects}"
-                cv2.putText(
-                    annotated_frame,
-                    info_text,
-                    (10, 30),
-                    cv2.FONT_HERSHEY_SIMPLEX,
-                    0.7,
-                    (0, 255, 0),
-                    2
-                )
+                if annotated_frame is None or annotated_frame.size == 0:
+                    print("Warning: Invalid detection result")
+                    continue
                 
                 cv2.imshow(self.window_name, annotated_frame)
                 
                 key = cv2.waitKey(1) & 0xFF
-                if key == ord('q') or key == 27:
-                    print("用户请求退出。")
+                if key == ord('q'):
                     break
                 elif key == ord('s'):
-                    saved_frame_index = self._save_frame(annotated_frame, saved_frame_index)
-        
+                    self.save_frame(annotated_frame)
+                
+                self._print_fps_if_needed(current_time)
+                self.frame_count += 1
+            
+        except KeyboardInterrupt:
+            print("\nDetection interrupted by user.")
         except Exception as e:
-            print(f"检测过程中发生未预期错误: {e}")
+            print(f"Unexpected error during detection: {e}")
             traceback.print_exc()
         finally:
             cap.release()
             cv2.destroyAllWindows()
-            print("摄像头已关闭，窗口已清理.")
-
-    def _open_camera(self):
-        cap = cv2.VideoCapture(self.camera_index)
-        if not cap.isOpened():
-            print(f"错误: 无法打开摄像头（索引 {self.camera_index}）")
-            print("请检查摄像头是否连接、是否被其他程序占用。")
-            return None
-        
-        cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
-        cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
-        return cap
-
-    def _perform_detection(self, frame):
-        try:
-            # 抑制 YOLO 内部输出
-            import sys, os
-            old_stdout = sys.stdout
-            sys.stdout = open(os.devnull, 'w')
-            annotated_frame, results = self.engine.detect(frame)
-            sys.stdout = old_stdout
-            return annotated_frame, results
-        except Exception as e:
-            print(f"单帧检测失败: {e}")
-            return None, []
-
-    def _save_frame(self, frame, index):
-        save_dir = "saved_frames"
-        os.makedirs(save_dir, exist_ok=True)
-        filename = os.path.join(save_dir, f"frame_{index:04d}.jpg")
+            print("Camera released and windows closed.")
+    
+    def _print_fps_if_needed(self, current_time):
+        if current_time - self.last_output_time >= self.output_interval:
+            fps = self.frame_count / (current_time - self.last_output_time) if self.last_output_time > 0 else 0
+            print(f"FPS: {fps:.2f}")
+            self.last_output_time = current_time
+            self.frame_count = 0
+    
+    def save_frame(self, frame):
+        import os
+        timestamp = int(time.time())
+        filename = f"saved_frame_{timestamp}.jpg"
         success = cv2.imwrite(filename, frame)
         if success:
-            print(f"✅ 帧已保存: {filename}")
-            return index + 1
+            print(f"Frame saved as {filename}")
         else:
-            print("❌ 保存帧失败！")
-            return index
+            print("Failed to save frame")

From 950cf9f25d2dca065bf4bc23c040b41da5cf978f Mon Sep 17 00:00:00 2001
From: is-leplus <3210209742@qq.com>
Date: Tue, 16 Dec 2025 17:30:51 +0800
Subject: [PATCH 30/30] Update ui_handler.py

---
 src/image_object_detection/ui_handler.py | 94 +++++++++---------------
 1 file changed, 34 insertions(+), 60 deletions(-)

diff --git a/src/image_object_detection/ui_handler.py b/src/image_object_detection/ui_handler.py
index 53e4036e0d..1e3f1073c3 100644
--- a/src/image_object_detection/ui_handler.py
+++ b/src/image_object_detection/ui_handler.py
@@ -1,75 +1,49 @@
 # ui_handler.py
+import os
 import cv2
+import traceback
 from detection_engine import DetectionEngine
 from image_detector import ImageDetector
 from camera_detector import CameraDetector
-import sys
-import os
 
 class UIHandler:
     def __init__(self, config):
         self.config = config
-        self.detection_engine = DetectionEngine()
-        self.image_detector = ImageDetector(self.detection_engine)
-        self.camera_detector = CameraDetector(self.detection_engine)
+        self.engine = DetectionEngine(
+            model_path=config.model_path,
+            conf_threshold=config.confidence_threshold
+        )
+        self.stop_flag = False
     
-    def print_debug(self, message):
-        """调试输出函数"""
-        print(f"[DEBUG] {message}")
-        sys.stdout.flush()  # 强制刷新输出缓冲区
-    
-    def display_menu(self):
-        """显示主菜单"""
-        print("=" * 60)
-        print("           欢迎使用 YOLO 对象检测系统")
-        print("=" * 60)
+    def run(self):
+        print("=== YOLO Detection System ===")
+        print("1. Static Image Detection")
+        print("2. Live Camera Detection")
+        print("3. Exit")
         
-        print(f"\n测试图像路径: {self.config.test_image_path}")
-        print(f"图像文件存在: {os.path.exists(self.config.test_image_path)}")
+        choice = input("Please select an option (1-3): ").strip()
         
-        print("\n请选择检测模式:")
-        print("1. 检测静态图像")
-        print("2. 检测摄像头实时画面")
-        print("3. 退出程序")
-    
-    def handle_choice(self, choice):
-        """处理用户选择"""
-        if choice == '1':
-            print("\n您选择了: 检测静态图像")
-            self.image_detector.detect_static_image(self.config.test_image_path)
-            return True
-        elif choice == '2':
-            print("\n您选择了: 检测摄像头实时画面")
-            print("注意：要退出摄像头模式，请按 Ctrl+C ！")
-            self.camera_detector.detect_camera()
-            return True
-        elif choice == '3':
-            print("\n程序已退出。")
-            return False
+        if choice == "1":
+            self._run_static_detection()
+        elif choice == "2":
+            self._run_camera_detection()
+        elif choice == "3":
+            print("Exiting program.")
         else:
-            print("\n无效选择，请输入 1、2 或 3")
-            return True
+            print("Invalid option. Please enter 1, 2, or 3.")
     
-    def run(self):
-        """运行主程序"""
-        self.print_debug("程序开始执行")
-        self.display_menu()
+    def _run_static_detection(self):
+        image_path = self.config.test_image_path
+        if not os.path.exists(image_path):
+            print(f"Image not found: {image_path}")
+            return
         
-        running = True
-        while running:
-            try:
-                choice = input("\n请输入您的选择 (1/2/3): ").strip()
-                self.print_debug(f"用户输入: {choice}")
-                running = self.handle_choice(choice)
-                
-            except KeyboardInterrupt:
-                print("\n\n程序被用户中断。")
-                break
-            except EOFError:
-                print("\n输入结束，程序退出。")
-                break
-            except Exception as e:
-                print(f"\n发生错误: {e}")
-                break
-        
-        self.print_debug("程序结束")
\ No newline at end of file
+        detector = ImageDetector(self.engine)
+        detector.detect_static_image(image_path)
+    
+    def _run_camera_detection(self):
+        detector = CameraDetector(
+            detection_engine=self.engine,
+            output_interval=self.config.output_interval
+        )
+        detector.start_detection(camera_index=self.config.camera_index)