Introduction

This is an implementation of SRGAN with pytorch lightning. I code this for learning pytorch lightning and SRGAN.

How to use

Environment setup

You can install the conda environment with environment.yml provided. Command:

conda env create -f environment.yml

Dataset

Eventually I used Flickr2K and DIV2K dataset to train my model. Additionally, I used VOC2012 and DIV2K to debug my model. You can link your dataset directory inside dataset. After that, add dataset/{PATH} in the config yaml file.

Training

In my project, I followed the training methods from the original paper. I trained my model with learning rate 1e-4 for 1e5 update iterations followed by 1e-5 for 1e5 update iterations.

Results

image: Set14_005
upscale factor: 4
ssim: 0.7730
psnr: 22.9948
You can access my model from my google drive.

Train your own model

In src/config, you can edit or create your own config yaml file. This project uses hydra to enable training configuration with yaml. The debug.yaml is for testing your environment.
After you have your own config yaml file, you can run my code with command:

python train.py --config-name {CONFIG_NAME}