One more thing. The paper says that it was used a 96 crop size. Pytorch’s VGG pretrained models need to have at least 224 crop size. What would you do? Using 224 severely increases training time, but I’m unsure what it would mean to forward a smaller image to the VGG in this case. From what I see, I have three options:


Train with 96 crop size (faster);


Train with 224 crop size (slower);


Use interpolate to generate a 224 patch given a 96 patch (medium).