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yolov5_industry

yolov5从模型训练到C++部署,一条龙服务!!!!

1 训练

一:数据摆放

paper_data文件夹内:

①images放入图片
②标注,保存在annotations

二:数据转换为yolo

回到python工程
1.py
2.py

三:训练并且测试

###训练
打开出现的浏览器地址,查看训练准确度
python train.py --img 640 --batch 4 --epoch 100 --data data/myvoc.yaml --cfg models/yolov5s.yaml --weights yolov5s.pt


#训练完测试测试集
python test.py  --data data/myvoc.yaml --weights best.pt --augment


#直接图片测试
 python detect.py --weights best.pt --source data/images/

2 导出onnx

python models/export.py --weights yolov5s.pt --img 640 --batch 1 

3 qt使用

①onnx放进去
②coco.names 改为自己的类别

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