- 调用摄像头识别:Jetson nano之pytorch 深度学习_whujk的博客
- Yolov3系列最佳实践:GitHub - doubleZ0108/IDEA-Lab-Summer-Camp: ZJU IDEA Lab Summer Camp
核心检测命令
# 图片
./darknet detect cfg/yolov3.cfg yolov3.weights data/test.jpg
# 摄像头
./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights "nvarguscamerasrc ! video/x-raw(memory:NVMM), width=1280, height=720, format=NV12, framerate=30/1 ! nvvidconv flip-method=2 ! video/x-raw, width=1280, height=720, format=BGRx ! videoconvert ! video/x-raw, format=BGR ! appsink"
# 视频(暂时未成功)
./darknet detecte cfg/yolov3.cfg yolov3.weights -thresh 0.35 -dont_show data/test.mp4 -i 0 -out_filename results.avi
预测效果
关于帧率
视频只能达到<2 FPS
yolov3-tiny
帧率FPS: ~6yolov4-tiny
帧率FPS:12~13