[Youtube] and [Bilibili]

pip install -r requirements.txt

LOLv1 dataset: Chen Wei, Wenjing Wang, Wenhan Yang, and Jiaying Liu. "Deep Retinex Decomposition for Low-Light Enhancement", BMVC, 2018. [Baiduyun (extracted code: sdd0)] [Google Drive]

LOLv2 dataset: Wenhan Yang, Haofeng Huang, Wenjing Wang, Shiqi Wang, and Jiaying Liu. "Sparse Gradient Regularized Deep Retinex Network for Robust Low-Light Image Enhancement", TIP, 2021. [Baiduyun (extracted code: l9xm)] [Google Drive]

LSRW dataset: Jiang Hai, Zhu Xuan, Ren Yang, Yutong Hao, Fengzhu Zou, Fang Lin, and Songchen Han. "R2RNet: Low-light Image Enhancement via Real-low to Real-normal Network", Journal of Visual Communication and Image Representation, 2023. [Baiduyun (extracted code: wmrr)]

Please refer to [Project Page of RetinexNet.]

You can downlaod our pre-trained model from [Google Drive] and [Baidu Yun (extracted code:wsw7)]

You need to modify datasets/dataset.py slightly for your environment, and then

python train.py  

python evaluate.py

If you use this code or ideas from the paper for your research, please cite our paper:

@article{jiang2023low,
  title={Low-Light Image Enhancement with Wavelet-based Diffusion Models},
  author={Jiang, Hai and Luo, Ao and Han, Songchen and Fan, Haoqiang and Liu, Shuaicheng},
  journal={arXiv preprint arXiv:2306.00306},
  year={2023}
}

Part of the code is adapted from previous works: WeatherDiff, SDWNet, and MIMO-UNet. We thank all the authors for their contributions.