Hi everyone,
the documentation about torchvision.models in the video classification paragraph says that the expected input size of the frames should be 112x112. Why is there this constraint?
I used a Resnet(2+1)D model as a fixed feature extractor with 180x320 input frames, and it seems to work without any problems, should I resize frames to 112x112 or not? Why?
Thanks.
PS: I think it works anyway thanks to the AdaptivePool at the end of the network, is it right?