# class 0 for T or 1 for CT
python vid.py --vid ./videos/t_model_0.mp4 --cls 0 --ml True
python yolov5/train.py --img 640 --batch 10 --epochs 500 --data dataset.yaml --weights yolov5/yolov5s.pt
python yolov5/detect.py --img 640 --conf 0.2 --weights ./data/weights/best.pt --source ./data/images
python detect.py
extract-video-subtittle 使用深度学习框架提取视频硬字幕； 本地识别无需联网； CPU识别速度可观； 容器提供API接口； 运行环境 本项目运行环境非常好搭建，我做好了docker容器免安装各种深度学习包； 提供windows界面操作； 容器为CPU版本； 视频演示 https
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