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Merge branch 'detached2' into YOLO

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# YOLO调试记录
## data 数据yaml文件配置
## 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
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python export.py --weights runs/train/exp4/weights/best.pt --img 640 --batch 1 --device 0 --include onnx --opset 15
```
weights地址: runs/train/exp4/weights/xxx.pt 路径中的模型为pt文件
在detect.py中batch为1 batch在detect中不能更改
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)
@ -45,15 +52,31 @@ onnx
```
![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
@ -61,8 +84,10 @@ D:\yolov5-master\data\dimo4.yaml
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)
![image-20241113133850391](./README.assets/image-20241113133850391.png)