yolov5改进repvgg

根据引用中提到的信息，可以得知yolov5改进repvgg的方法是通过集成yolov5(v6.0)、注意力机制和repvgg结构来实现的。改进的代码包含了多头检测和关键点检测等功能，并且使用train_multiple_detection_head.py文件进行训练。这个改进方法可以在yolov5以及其他算法中同样适用。这种改进可以提供更好的效果和性能。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *2* [【YOLOv7/YOLOv5系列改进NO.38】引入RepVGG模型结构](https://blog.csdn.net/m0_70388905/article/details/127532645)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
- *3* [改进yolov5(多检测头+注意力机制+repvgg结构)pytorch源码+项目说明.zip](https://download.csdn.net/download/DeepLearning_/87249653)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
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