基于yolov5的安全帽佩戴检测
本项目中使用的预训练模型为官方提供的 yolov5m.pt 来训练数据集，另外三种模型分别为：yolov5l.pt、yolov5s.pt、yolov5x.pt。可以更换预训练模型来训练数据集。
一：下载模型
二：将模型放入weights文件夹下（实际上可以放入任何位置，只需要做相应的路径更改）
三：更改 train.py 下预训练模型的路径以及对应模型cfg配置文件的对应位置
--weights 参数的 default 更改为：例如 weights/yolov5m.pt（使用命令行运行则直接 --weights 指定即可）
--cfg 参数的 default 更改为：例如对应的 models/yolov5m.yaml（使用命令行运行则直接 --cfg 指定即可）
**强调一点：**cfg 官方默认的 4 个 yaml 文件的配置为 coco 数据集的 80 个识别类别。如果你更换了预训练模型，yaml 里面的参数nc也需要修改为对应你自己项目的类别个数，例如本项目中 nc: 2。
四：命令行或者直接运行 train.py 训练
2：添加数据集
可
文件下载
资源详情
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