面罩检测:使用YOLO网络(Darknet)和更快的R-CNN网络(PyTorch)在Google Colab中进行面罩检测-源码

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面罩检测 使用YOLO网络(Darknet)和更快的R-CNN网络(PyTorch)在Google Colab中进行面罩检测。 检测到3类:正确佩戴的口罩,错误佩戴的口罩和未佩戴的口罩。 设置和执行YOLO: 在您的Google云端硬盘中创建名为yolov3的文件夹 下载数据集( , ) 执行jupyter Notebook 对于测试,请执行detection_utils.py或对视频进行检测,请执行detect_video.py您可以使用video_converter.py从视频创建数据集,从视频到图像或从图像到视频。 设置和执行PyTorch: 在您的Google云端硬盘中创建一个名为rcnn的文件夹,然后以zip格式上传数据集。 下载数据集( , ) 执行jupyter Notebook 预训练重量: 在Kaggle数据集上已经预先训练了 (和)网络和权重(方法

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