Deep Color Consistent Network for Low Light-Image Enhancement (CVPR 2022)

Pytorch implementation of Deep Color Consistent Network for Low Light-Image Enhancement. Note that we do some adjustments to the model for flexibility. Please refer to the code for more detailes.

Environment:

1. Python 3.6
2. Pytorch 1.3.0
3. torchvision 0.4.1
4. cuda 11.4

Pretrained Model and Testing Results:

1. Download the pretrained model on LOL dataset from this link.
2. The testing results of LOL dataset can be found here.

Test:

python test.py --filepath img_path --pretrain_path model_path

Evaluation

python metrics.py --data-path gt_path --output-path pre_img_path

Bibtex:

@inproceedings{zhang2022deep,
  title={Deep Color Consistent Network for Low-Light Image Enhancement},
  author={Zhao Zhang, Huan Zheng, Richang Hong, Mingliang Xu, Shuicheng Yan and Meng Wang},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2022}
}