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BrunoVox/SRGAN 4

PyTorch implementation of SRGAN. Contribute to BrunoVox/SRGAN development by creating an account on GitHub.


  
  
    
    
  
  


Sorry for the delay, I was basically rewriting the code. It seems a decent version to be shared for now. I will be writing a README tomorrow, which will help you training the model/testing it. I will also upload a pretrained SRResNet tomorrow. You can control the training parameters by editing “config/train.json” and you will need to manually change the folder output of testing in the test.py. I’m training it on aproximately 400k images from Imagenet. You will need to download the eval datasets too, but I’ll upload them tomorrow, when I’ll have some free time. The eval datasets I’m using at the moment are: Set5, Set14, BSD100. Urban100 and Manga109. Share with me what you think. The SRResNet-MSE seems just fine, and SRResNet-VGG22 looks better, but there’s still room to improve. I haven’t tested SRGAN yet. If you have any feedback, mainly regarding SRResNet-VGG22, please share with me.
Also, the PyTorch pretrained models of VGG requires an input of, at least, 3x224x224. I didn’t think about it, it occurred to me a few minutes ago, but I need to forward 96x96 images through this VGG model. What would you do? I’m thinking about rescaling the image to 224, forwarding in the VGG, and then downscale the feature map, but it seems odd to me, I will be losing information. Best case scenario would be training VGG from scratch I think, with the 3x96x96 inputs I need.