Hi, thank you for providing this excellent code.
I have some questions about the different image size at training and testing.
In training, you calculate loss based on the upsampled output, which has the same image size as the input image. However, in testing(prediction), you calculate the keypoints based on the results before Upsampling.
I was wondering why you do this in testing time? For efficiency or something else?
Look forward to your reply, thank you!