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YOLO/README.md

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+# YOLO调试记录
+
+
+## data文件夹 yaml文件配置
+
+该文件夹中配置的是数据集的路径及类别信息
+
+
+```python
+path: ../datasets/dimo4
+train: D:\yolov5-master\datasets\dimo4\images\train
+val: D:\yolov5-master\datasets\dimo4\images\val
+test: # test images (optional)
+# Classes
+names:
+  0: dimo
+```
+
+## 模型导出
+
+### 命令行形式
+
+```bash
+python export.py --weights runs/train/exp4/weights/best.pt --img 640 --batch 1 --device 0 --include onnx --opset 15       
+```
+
+
+通过export.py导出的文件格式为onnx
+
+weights地址: runs/train/exp4/weights/xxx.pt    best.pt为train.py训练后所得模型
+
+在detect.py中batch为1，batch在detect中不能更改,所以在导出onnx模型文件时要设置batch 1     batch在detect中不能更改
+
+![image-20241113133535978](./README.assets/image-20241113133535978.png)
+
+![1](./README.assets/1.png)
+
+### PyCharm配置
+
+##### export.py
+
+```bash
+--weights
+runs/train/exp4/weights/best.pt
+--img
+640
+--device0
+--include
+onnx
+--opset
+15
+```
+
+
+![image-20241113182234260](C:\Users\91492\AppData\Roaming\Typora\typora-user-images\image-20241113182234260.png)
+
+## 模型加载
+
+### 命令行形式
+
+```bash
+python detect.py --weights runs\train\exp4\weights\best.onnx --data D:\yolov5- master\data\dimo4.yaml
+```
+
+![image-20241113133825646](./README.assets/image-20241113133825646.png)
+
+![image-20241113133840896](./README.assets/image-20241113133840896.png)
+
+![image-20241113133850391](./README.assets/image-20241113133850391.png)
+
+### PyCharm配置
+
+```bash
+--weights
+runs\train\exp4\weights\best.onnx
+--data
+D:\yolov5-master\data\dimo4.yaml
+```
+![image-20241113182433935](C:\Users\91492\AppData\Roaming\Typora\typora-user-images\image-20241113182433935.png)
+
+在detect.py中
+
+输入的模型为在train.py中训练好的模型   ：地址: runs/train/exp4/weights/xxx.pt      
+
+或者 ：runs/train/exp4/weights/xxx.onnx
+
+
+![image-20241113133825646](./README.assets/image-20241113133825646.png)
+
+![image-20241113133840896](./README.assets/image-20241113133840896.png)
+
+![image-20241113133850391](./README.assets/image-20241113133850391.png)
+