LSDIR: A Large Scale Dataset for Image Restoration

How to use the dataset?

1. Download the dataset from the LSDIR website.
2. Load the JSON file for the specific task.
   • train.json: for image restoration tasks based on synthetic data such as image denoising, real-world image super-resolution based on pure data synthesis, JPEG compression artifact removal, Gaussian image deblurring, image demosaicking.
     • path: path to ground-truth images
   • train_X2.json: for X2 image super-resolution
     • path_gt: path to ground-truth images
     • path_lq: path to X2 low-resolution images
   • train_X3.json: for X3 image super-resolution
     • path_gt: path to ground-truth images
     • path_lq: path to X3 low-resolution images
   • train_X4.json: for X4 image super-resolution
     • path_gt: path to ground-truth images
     • path_lq: path to X4 low-resolution images
3. Write your own dataloader based on the loaded JSON file. (We will provide our dataloader soon.)

Stay tuned!

The paper, code, and benchmark will be released soon.