Codes and trained models for RGB image pairs

[hermosayhl]

Firstly

All the codes and trained models I modified are located here: CURL_for_RGB_images.
The README.md is really necessary to read.

Secondly

The dataset I use is avaliable at: https://pan.baidu.com/s/1_VwqWqpPGw5piLxg8pWEZg extract code: 0212
If not convenient, extra link: https://mega.nz/file/IZ9njZBJ#8J-cy5GxWj2NedZu360qU2vkLecXSc9IL_G51_Iymms.
Factually, the dataset is made from the original Adobe MIT-FiveK datasets and please look up https://data.csail.mit.edu/graphics/fivek/.

@inproceedings{fivek,
author = "Vladimir Bychkovsky and Sylvain Paris and Eric Chan and Fr{'e}do Durand",
title = "Learning Photographic Global Tonal Adjustment with a Database of Input / Output Image Pairs",
booktitle = "The Twenty-Fourth IEEE Conference on Computer Vision and Pattern Recognition",
year = "2011"
}

If copyright infringement, please contact me to delete the link.

Thirdly

MIT-FiveK datasets; ExpertC; 1-4500 for training and 4501-5000 for testing; Resized to max edge of 512px.
After 30 epoches of training, testing PSNR reaches 25.09db and SSIM reaches 0.9.
Listed below are some results:

[sjmoran]

Thank you hermosayhl!

[McFly-Jia]

Thank you hermosayhl!
Is the data you use in PNG format or JPG format？ Can you release the link of the RGB data you use?