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PyTorchSRGAN

A modern PyTorch implementation of SRGAN

It is deeply based on Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network paper published by the Twitter team (https://arxiv.org/abs/1609.04802) but modernizing it with some new promising discoveries such as DenseNets (https://arxiv.org/abs/1608.06993)

I also try to follow best practices described here: https://github.com/soumith/ganhacks

Still a work in progress for now, but hopefully it will serve as a guide for people implementing somewhat complex GANs with PyTorch.

Contributions are welcome!

Status

Work in progress. Good results are starting to be visible with the CIFAR-100 dataset.

To start a training session:

./train --cuda 

Requirements

  • PyTorch
  • torchvision

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A modern PyTorch implementation of SRGAN by Py3

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