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@@ -1,20 +1,46 @@
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-# 注:新数据应先放入下面路径的total_data中(total_data需新建,在本地导入数据放入;项目名称根据具体项目新建)
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+# Object Detection Model Training and Deployment
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-code and data location
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-url:192.168.20.250
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-directory:/data/object_detection
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+This project involves training object detection models using the YOLOv5 framework, exporting the trained model from `.pt` format to `.pb` format, and testing the performance of the model. The new data should be imported to the appropriate directory as described below.
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-训练模型执行步骤
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-1、./object_detection.sh /data2/object_detection/data/image/项目名称/
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+## Project Steps
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-2、训练结束,保存.pt格式:
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+### 1. Data Preparation
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+- Create a new folder `total_data` under the project directory and place the newly imported data there.
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+- **Code and Data Location**:
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+ - **Server URL**: `192.168.20.250`
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+ - **Directory**: `/data/object_detection`
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-3、.pt格式模型导出为.pb格式模型
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-获取pt文件路径:cat export.sh
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-进入yolov5文件夹 (/data/object_detection/code/yolov5/)后运行
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-python export.py --weights ./runs/train/helmet_fall_phone/weights/best.pt --include pb #修改项目名称
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+### 2. Model Training
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+- Run the following script to train the model, where `<project_name>` is the name of the newly created project:
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+ ```bash
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+ ./object_detection.sh /data2/object_detection/data/image/<project_name>/
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+ ```
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-转换为.pb格式,并保存
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+### 3. Save the Model
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+- Once training is complete, the model will be saved in `.pt` format.
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+
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+### 4. Export Model to `.pb` Format
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+- To export the `.pt` model to `.pb` format, first find the `.pt` file path by running:
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+ ```bash
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+ cat export.sh
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+ ```
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+- Navigate to the YOLOv5 directory:
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+ ```bash
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+ cd /data/object_detection/code/yolov5/
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+ ```
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+- Run the export script to convert the `.pt` model to `.pb` format:
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+ ```bash
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+ python export.py --weights ./runs/train/helmet_fall_phone/weights/best.pt --include pb
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+ ```
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+ - *Note*: Change `helmet_fall_phone` to the correct project name before running the script.
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+
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+### 5. Model Testing
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+- To test the model, run the following command:
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+ ```bash
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+ python detect.py --weights runs/train/safebelt_data/weights/best.pt --source /data2/object_detection/code/yolov5/safebelt_test --data /data2/object_detection/data/image/safebelt_data/yolo/safebelt_data.yaml --device 0
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+ ```
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+ - *Note*: Adjust the `--weights`, `--source`, and `--data` parameters to the correct project paths.
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+
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+## Contact
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+For any inquiries or issues, please contact the development team.
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-4、测试:
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-python detect.py --weights runs/train/safebelt_data/weights/best.pt --source /data2/object_detection/code/yolov5/safebelt_test --data /data2/object_detection/data/image/safebelt_data/yolo/safebelt_data.yaml --device 0
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