What is the FPS(testing speed)? about pytorch_yolov3

[hirotomusiker]

I did not put FPS performance results on README because the frame rate performance largely depends on :

• Hardware (GPU, CPU)
• Cuda and CuDNN versions
• PyTorch and other package versions
• preprocess and postprocess
  The papers usually don't disclose all the conditions on which their benchmark was done.

But as long as I see your code, preprocessing to re-size your large image and imwrite (if you do that every frame) should be slow. I recommend you to perform only the forward process on GPU and measure the inference speed firstly.

Thank you!

[sisrfeng]

Thanks a lot!
If I feed 1600x1200 imgs to pytorch_GaussianYOLOv3 , I get 10 fps (the time includes preprossing)
Then I re-size 1600x1200 imgs to 416x416 and imwrite. The original code after imwrite is commented:

img = np.transpose(img / 255., (2, 0, 1))
img = torch.from_numpy(img).float().unsqueeze(0)

if gpu >= 0:
    # Send model to GPU
    img = Variable(img.type(torch.cuda.FloatTensor))
else:
    img = Variable(img.type(torch.FloatTensor))

If I feed 416x416 imgs to pytorch_GaussianYOLOv3, I get 21 fps.

Which of these two types of FPS is usually mentioned on the papers?

[hirotomusiker]

I'm not sure but in the following code they measure fps including pre-process.
https://github.com/pjreddie/darknet/blob/master/src/demo.c