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update readme.
Browse files- .gitignore +120 -0
- README.md +101 -0
- assets/CodeFormer_logo.png +0 -0
- assets/color_enhancement_result1.png +0 -0
- assets/color_enhancement_result2.png +0 -0
- assets/inpainting_result1.png +0 -0
- assets/inpainting_result2.png +0 -0
- assets/network.jpg +0 -0
- assets/restoration_result1.png +0 -0
- assets/restoration_result2.png +0 -0
- assets/restoration_result3.png +0 -0
- assets/restoration_result4.png +0 -0
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README.md
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<p align="center">
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<img src="assets/CodeFormer_logo.png" height=110>
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</p>
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## Towards Robust Blind Face Restoration with Codebook Lookup Transformer
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[Paper](https://arxiv.org/abs/xxx) | [Project Page](https://shangchenzhou.com/projects/CodeFormer/) | [Video](https://youtu.be/d3VDpkXlueI)
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<!-- <a href="https://colab.research.google.com/drive/1m52PNveE4PBhYrecj34cnpEeiHcC5LTb?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="google colab logo"></a> -->
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[Shangchen Zhou](https://shangchenzhou.com/), [Kelvin C.K. Chan](https://ckkelvinchan.github.io/), [Chongyi Li](https://li-chongyi.github.io/), [Chen Change Loy](https://www.mmlab-ntu.com/person/ccloy/)
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S-Lab, Nanyang Technological University
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<img src="assets/network.jpg" width="800px"/>
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### Updates
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<!-- Test code and Colab demo for Face Restoration is available now. -->
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- **2022.07.02**: :star:We will release the test code and model by July 15th. Thanks for your attention! :blush:
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- **2022.06.21**: This repo is created.
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#### Face Restoration
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<img src="assets/restoration_result1.png" width="400px"/> <img src="assets/restoration_result2.png" width="400px"/>
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<img src="assets/restoration_result3.png" width="400px"/> <img src="assets/restoration_result4.png" width="400px"/>
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#### Face Color Enhancement and Restoration
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<img src="assets/color_enhancement_result1.png" width="400px"/> <img src="assets/color_enhancement_result2.png" width="400px"/>
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#### Face Inpainting
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<img src="assets/inpainting_result1.png" width="400px"/> <img src="assets/inpainting_result2.png" width="400px"/>
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<!-- ### Dependencies and Installation
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- Pytorch >= 1.7.1
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- CUDA >= 10.1
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- Other required packages in `requirements.txt`
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```
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# git clone this repository
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git clone https://github.com/sczhou/CodeFormer
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cd CodeFormer
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# create new anaconda env
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conda create -n codeformer python=3.8 -y
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source activate codeformer
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# install python dependencies
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pip3 install -r requirements.txt
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python basicsr/setup.py develop
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conda install -c conda-forge dlib
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```
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### Quick Inference
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##### Download Pre-trained Models:
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Download the dlib pretrained models from [[Google Drive]([xx](https://drive.google.com/drive/folders/1f24f1UqNY8OyeE9aWxswCKQbR7fe8yz4?usp=sharing)) | [OneDrive](xx)] to the `weights/dlib` folder.
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You can download by run the following command OR manually download the pretrained models.
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```
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python scripts/download_pretrained_models.py dlib
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```
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Download the CodeFormer pretrained models from [[Google Drive]([xx](https://drive.google.com/drive/folders/1f24f1UqNY8OyeE9aWxswCKQbR7fe8yz4?usp=sharing)) | [OneDrive](xx)] to the `weights/CodeFormer` folder.
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You can download by run the following command OR manually download the pretrained models.
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```
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python scripts/download_pretrained_models.py CodeFormer
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```
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##### Prepare Testing Data:
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You can put the testing images in the `inputs/TestWhole` folder. If you would like to test on cropped and aligned faces, you can put them in the `inputs/cropped_faces` folder.
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##### Testing for Face Restoration:
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```
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python inference_codeformer.py --w 0.5 --test_path [input folder]
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```
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NOTE that we set *w* to -->
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### Citation
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If our work is useful for your research, please consider citing:
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@article{zhou2022codeformer,
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author = {Zhou, Shangchen and Chan, Kelvin C.K. and Li, Chongyi and Loy, Chen Change},
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title = {Towards Robust Blind Face Restoration with Codebook Lookup TransFormer},
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journal = {arXiv preprint arXiv:2206.11253},
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year = {2022}
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}
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### License
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<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.
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### Acknowledgement
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This project is based on [BasicSR](https://github.com/XPixelGroup/BasicSR).
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assets/CodeFormer_logo.png
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assets/color_enhancement_result1.png
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assets/color_enhancement_result2.png
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assets/inpainting_result1.png
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assets/inpainting_result2.png
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assets/network.jpg
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assets/restoration_result1.png
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assets/restoration_result2.png
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assets/restoration_result3.png
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assets/restoration_result4.png
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