Open Hemanth-TS opened 1 month ago
Hi,
Could you please provide your system details, command line, and Git commit version? For example, my setup is:
python yolo/lazy.py task=inference name=AnyNameYouWant device=cuda model=v9-c task.data.source=MOT20-05-raw.mp4 task.fast_inference=deploy
This configuration achieves 20 FPS without using ONNX or TensorRT.
best regards, Henry Tsui
when i ran the command with cuda , around 20% of gpu was used and like 200% cpu but it was still very slow, i was trying to infer a video. python yolo/lazy.py task=inference \ # default is inference name=AnyNameYouWant \ # AnyNameYouWant device=cuda\ # hardware cuda, cpu, mps model=v9-s \ # model version: v9-c, m, s task.nms.min_confidence=0.1 \ # nms config task.fast_inference=onnx \ # onnx, trt, deploy task.data.source=data/toy/images/train \ # file, dir, webcam +quite=True \ # Quite Output
Can someone guide me on how to infer videos properly with higher fps while using gpu efficiently.