Add YOLOv5-cls Model #335
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Add YOLOv5-cls Model #335
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DefTruth
requested changes
Oct 10, 2022
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| - YOLOv5 v6.0部署模型实现来自[YOLOv5](https://github.com/ultralytics/yolov5/tree/v6.0),和[基于COCO的预训练模型](https://github.com/ultralytics/yolov5/releases/tag/v6.0) | |||
| - （1）[官方库](https://github.com/ultralytics/yolov5/releases/tag/v6.0)提供的*.onnx可直接进行部署； | |||
| - （2）开发者基于自己数据训练的YOLOv5 v6.0模型，可使用[YOLOv5](https://github.com/ultralytics/yolov5)中的`export.py`导出ONNX文件后后，完成部署。 | |||
| - （2）开发者基于自己数据训练的YOLOv5 v6.0模型，可使用[YOLOv5](https://github.com/ultralytics/yolov5)中的`export.py`导出ONNX文件后，完成部署。 | |||
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yolov5-cls似乎不是 v6.0的版本？应该是v6.2
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这个是detection的yolov5，后后->后
fastdeploy/vision.h
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| #include "fastdeploy/core/config.h" | |||
| #ifdef ENABLE_VISION | |||
| #include "fastdeploy/vision/classification/contrib/yolov5.h" | |||
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比较建议头文件的命名和模型名称保持一致，比如yolov5cls.h，这样能够和原来的yolov5区分开来
| self.Predict(&mat, &res, topk); | ||
| return res; | ||
| }) | ||
| .def_readwrite("size", &vision::classification::YOLOv5Cls::size); |
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我看到还有mean和std是public的成员，但这里没看到被pybind
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Done.在public的成员中将mean和std去掉
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| // Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. | |||
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同上。建议修改成yolov5cls.cc，这样也和python保持一致，我看到python是yolov5cls.py
…eploy into add_yolov5_cls
DefTruth
approved these changes
Oct 11, 2022
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增加单测 |
Done. |
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Describe
1、添加YOLOv5-cls模型部署支持
2、solved #138
eval_classify（YOLOv5n-cls）