I have changed test.py to run on a video. See implementation below:
device, model = init_model(args)
proc_size = eval(args.size)
cap = cv2.VideoCapture("/home/sieuwe/Downloads/Garmin Dash Cam 55 Video Sample (Highway) _ 1080p 30fps (HDR).mp4")
while(True):
begin = time.perf_counter()
ret, frame = cap.read()
img_raw, decoded = process_img(frame, proc_size, device, model)
cv2.imshow("OUT",decoded)
cv2.imshow("IN",img_raw)
end = time.perf_counter()
print("fps", 1 / (end - begin))
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
I am running a GTX1080 and thus expected a FPS of around 40. I however got a much lower fps of 21. When looking at my GPU util in nvidia-smi I see that it only uses 10% of my gpu. How can I increase the GPU util to get higher FPS.
Using CUDA 10.2 on Ubunut 18.04 with pytorch version 1.4.0
Hi @PingoLH
I have changed test.py to run on a video. See implementation below:
I am running a GTX1080 and thus expected a FPS of around 40. I however got a much lower fps of 21. When looking at my GPU util in nvidia-smi I see that it only uses 10% of my gpu. How can I increase the GPU util to get higher FPS.
Using CUDA 10.2 on Ubunut 18.04 with pytorch version 1.4.0
Thanks for your help
Sieuwe