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| <p align="center"> | |
| <img src="assets/CodeFormer_logo.png" height=110> | |
| </p> | |
| ## Towards Robust Blind Face Restoration with Codebook Lookup Transformer | |
| [Paper](https://arxiv.org/abs/2206.11253) | [Project Page](https://shangchenzhou.com/projects/CodeFormer/) | [Video](https://youtu.be/d3VDpkXlueI) | |
| <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> [](https://replicate.com/sczhou/codeformer)  | |
| [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/) | |
| S-Lab, Nanyang Technological University | |
| <img src="assets/network.jpg" width="800px"/> | |
| :star: If CodeFormer is helpful to your images or projects, please help star this repo. Thanks! :hugs: | |
| ### Update | |
| - **2022.09.09**: Integrated to :rocket: [Replicate](https://replicate.com/). Try out online demo! [](https://replicate.com/sczhou/codeformer) | |
| - **2022.09.04**: Add face upsampling `--face_upsample` for high-resolution AI-created face enhancement. | |
| - **2022.08.23**: Some modifications on face detection and fusion for better AI-created face enhancement. | |
| - **2022.08.07**: Integrate [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN) to support background image enhancement. | |
| - **2022.07.29**: Integrate new face detectors of `['RetinaFace'(default), 'YOLOv5']`. | |
| - **2022.07.17**: Add Colab demo of CodeFormer. <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> | |
| - **2022.07.16**: Release inference code for face restoration. :blush: | |
| - **2022.06.21**: This repo is created. | |
| ### TODO | |
| - [ ] Add checkpoint for face inpainting | |
| - [ ] Add training code and config files | |
| - [x] ~~Add background image enhancement~~ | |
| #### Face Restoration | |
| <img src="assets/restoration_result1.png" width="400px"/> <img src="assets/restoration_result2.png" width="400px"/> | |
| <img src="assets/restoration_result3.png" width="400px"/> <img src="assets/restoration_result4.png" width="400px"/> | |
| #### Face Color Enhancement and Restoration | |
| <img src="assets/color_enhancement_result1.png" width="400px"/> <img src="assets/color_enhancement_result2.png" width="400px"/> | |
| #### Face Inpainting | |
| <img src="assets/inpainting_result1.png" width="400px"/> <img src="assets/inpainting_result2.png" width="400px"/> | |
| ### Dependencies and Installation | |
| - Pytorch >= 1.7.1 | |
| - CUDA >= 10.1 | |
| - Other required packages in `requirements.txt` | |
| ``` | |
| # git clone this repository | |
| git clone https://github.com/sczhou/CodeFormer | |
| cd CodeFormer | |
| # create new anaconda env | |
| conda create -n codeformer python=3.8 -y | |
| conda activate codeformer | |
| # install python dependencies | |
| pip3 install -r requirements.txt | |
| python basicsr/setup.py develop | |
| ``` | |
| <!-- conda install -c conda-forge dlib --> | |
| ### Quick Inference | |
| ##### Download Pre-trained Models: | |
| Download the facelib pretrained models from [[Google Drive](https://drive.google.com/drive/folders/1b_3qwrzY_kTQh0-SnBoGBgOrJ_PLZSKm?usp=sharing) | [OneDrive](https://entuedu-my.sharepoint.com/:f:/g/personal/s200094_e_ntu_edu_sg/EvDxR7FcAbZMp_MA9ouq7aQB8XTppMb3-T0uGZ_2anI2mg?e=DXsJFo)] to the `weights/facelib` folder. You can manually download the pretrained models OR download by runing the following command. | |
| ``` | |
| python scripts/download_pretrained_models.py facelib | |
| ``` | |
| Download the CodeFormer pretrained models from [[Google Drive](https://drive.google.com/drive/folders/1CNNByjHDFt0b95q54yMVp6Ifo5iuU6QS?usp=sharing) | [OneDrive](https://entuedu-my.sharepoint.com/:f:/g/personal/s200094_e_ntu_edu_sg/EoKFj4wo8cdIn2-TY2IV6CYBhZ0pIG4kUOeHdPR_A5nlbg?e=AO8UN9)] to the `weights/CodeFormer` folder. You can manually download the pretrained models OR download by runing the following command. | |
| ``` | |
| python scripts/download_pretrained_models.py CodeFormer | |
| ``` | |
| ##### Prepare Testing Data: | |
| 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. | |
| ##### Testing on Face Restoration: | |
| ``` | |
| # For cropped and aligned faces | |
| python inference_codeformer.py --w 0.5 --has_aligned --test_path [input folder] | |
| # For the whole images | |
| # Add '--bg_upsampler realesrgan' to enhance the background regions with Real-ESRGAN | |
| # Add '--face_upsample' to further upsample restorated face with Real-ESRGAN | |
| python inference_codeformer.py --w 0.7 --test_path [input folder] | |
| ``` | |
| NOTE that *w* is in [0, 1]. Generally, smaller *w* tends to produce a higher-quality result, while larger *w* yields a higher-fidelity result. | |
| The results will be saved in the `results` folder. | |
| ### Citation | |
| If our work is useful for your research, please consider citing: | |
| @article{zhou2022codeformer, | |
| author = {Zhou, Shangchen and Chan, Kelvin C.K. and Li, Chongyi and Loy, Chen Change}, | |
| title = {Towards Robust Blind Face Restoration with Codebook Lookup TransFormer}, | |
| journal = {arXiv preprint arXiv:2206.11253}, | |
| year = {2022} | |
| } | |
| ### License | |
| <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>. | |
| ### Acknowledgement | |
| This project is based on [BasicSR](https://github.com/XPixelGroup/BasicSR). We also borrow some codes from [Unleashing Transformers](https://github.com/samb-t/unleashing-transformers), [YOLOv5-face](https://github.com/deepcam-cn/yolov5-face), and [FaceXLib](https://github.com/xinntao/facexlib). Thanks for their awesome works. | |
| ### Contact | |
| If you have any question, please feel free to reach me out at `shangchenzhou@gmail.com`. |