This is an implement of the TOPAL, “Target Oriented Perceptual Adversarial Fusion Network for Underwater Image Enhancement”, Zhiying Jiang, Zhuoxiao Li, Shuzhou Yang, Xin Fan, Risheng Liu*, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022.
Clone this repo:
conda create -n TOPAL python=3.7
conda activate TOPAL
conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
pip3 install thop matplotlib scikit-image opencv-python yacs joblib natsort h5py tqdm
Download the pre-trained model and put it in networks/model
- Baidu Yun
code: vtab - Google Drive
Put the images you want to process in the Underwater folder.
To test the pre-trained models for Underwater Enhancement on your own images, run
python main.py
Results will be shown in Result folder.
If you use TOPAL, please consider citing:
@ARTICLE{TOPAL,
author={Jiang, Zhiying and Li, Zhuoxiao and Yang, Shuzhou and Fan, Xin and Liu, Risheng},
journal={IEEE Transactions on Circuits and Systems for Video Technology},
title={Target Oriented Perceptual Adversarial Fusion Network for Underwater Image Enhancement},
year={2022},
pages={1-1},
doi={10.1109/TCSVT.2022.3174817}}
Should you have any question, please contact Zhiying Jiang.