ESRGAN in Pytorch

• Implementation of Enhanced Super-resolution model in pytorch

• Model runs - wandb experiment tracker

• Some basic details about training process. Apart from the default parameters described in the paper the changes are as follows:

  • Increase adverserial loss factor in stage 2 for 30 epochs then come back to original state.
  • Used Spectral normalization and Two-time Update rule.
  • Two stage training in total 100 and 174 epochs each.
  • LR image of size 64x64 with 4x HR of 256x256.
  • Added FID metric.
  • Training data consists of whole trainig and validation images from Div2k and 1000 images from Flick2k dataset.

• More in-depth details will be updated ASAP. The project has been completed.