ARWGAN

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This repository is the official PyTorch implementation of ARWGAN: attention-guided robust image watermarking model based on GAN.

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# ARWGAN
This repository is the official PyTorch implementation of ARWGAN: attention-guided robust image watermarking model based on GAN.

## Pretrain
The pre-trained model of [ARWGAN](https://drive.google.com/file/d/1jDpF0LBmuFiy4PNvqaaz7vXyHCbHA4ao/view?usp=drive_link) is avaliable.

## Train
If you need to train ARWGAN from scratch, you should use commond line as following.

python mian.py new -n name -d data-dir -b batch-size -e epochs  -n noise
      
Environmental requirements:
+ Python == 3.7.4; Torch == 1.12.1 + cu102; Torchvision == 0.13.1; PIL == 7.2.0

## Test
Put the pre-trained model into pretrain floder, and you can test ARWGAN by command line as following.

python test.py -o ./pretrain/options-and-config.pickle -c ./pretrain/ARWGAN.pyt -s data-dir -n noise

## Citation
```bib
@ARTICLE{10155247,
  author={Huang, Jiangtao and Luo, Ting and Li, Li and Yang, Gaobo and Xu, Haiyong and Chang, Chin-Chen},
  journal={IEEE Transactions on Instrumentation and Measurement}, 
  title={ARWGAN: Attention-Guided Robust Image Watermarking Model Based on GAN}, 
  year={2023},
  volume={72},
  number={},
  pages={1-17},
  doi={10.1109/TIM.2023.3285981}}
```

## Acknowledgement
The codes are designed based on [HiDDeN](https://github.com/ando-khachatryan/HiDDeN).

ARWGAN

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