| <p align="center"> |
| <img src="assets/CodeFormer_logo.png" height=110> |
| </p> |
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| ## Towards Robust Blind Face Restoration with Codebook Lookup Transformer (NeurIPS 2022) |
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| [Paper](https://arxiv.org/abs/2206.11253) | [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> [](https://huggingface.co/spaces/sczhou/CodeFormer) [](https://replicate.com/sczhou/codeformer)  |
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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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| :star: If CodeFormer is helpful to your images or projects, please help star this repo. Thanks! :hugs: |
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| **[<font color=#d1585d>News</font>]**: :whale: *Due to copyright issues, we have to delay the release of the training code (expected by the end of this year). Please star and stay tuned for our future updates!* |
| ### Update |
| - **2022.10.05**: Support video input `--input_path [YOUR_VIDOE.mp4]`. Try it to enhance your videos! :clapper: |
| - **2022.09.14**: Integrated to :hugs: [Hugging Face](https://huggingface.co/spaces). Try out online demo! [](https://huggingface.co/spaces/sczhou/CodeFormer) |
| - **2022.09.09**: Integrated to :rocket: [Replicate](https://replicate.com/explore). 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. |
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| ### TODO |
| - [ ] Add checkpoint for face inpainting |
| - [ ] Add checkpoint for face colorization |
| - [ ] Add training code and config files |
| - [x] ~~Add background image enhancement~~ |
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| #### :panda_face: Try Enhancing Old Photos / Fixing AI-arts |
| [<img src="assets/imgsli_1.jpg" height="226px"/>](https://imgsli.com/MTI3NTE2) [<img src="assets/imgsli_2.jpg" height="226px"/>](https://imgsli.com/MTI3NTE1) [<img src="assets/imgsli_3.jpg" height="226px"/>](https://imgsli.com/MTI3NTIw) |
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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"/> |
| <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 |
| - CUDA >= 10.1 |
| - Other required packages in `requirements.txt` |
| ``` |
| # git clone this repository |
| git clone https://github.com/sczhou/CodeFormer |
| cd CodeFormer |
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| # create new anaconda env |
| conda create -n codeformer python=3.8 -y |
| conda activate codeformer |
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| # install python dependencies |
| pip3 install -r requirements.txt |
| python basicsr/setup.py develop |
| ``` |
| <!-- conda install -c conda-forge dlib --> |
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| ### Quick Inference |
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| #### 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 running the following command. |
| ``` |
| python scripts/download_pretrained_models.py facelib |
| ``` |
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| 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 running the following command. |
| ``` |
| python scripts/download_pretrained_models.py CodeFormer |
| ``` |
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| #### 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. |
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| #### Testing on Face Restoration: |
| [Note] If you want to compare CodeFormer in your paper, please run the following command indicating `--has_aligned` (for cropped and aligned face), as the command for the whole image will involve a process of face-background fusion that may damage hair texture on the boundary, which leads to unfair comparison. |
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| 🧑🏻 Face Restoration (cropped and aligned face) |
| ``` |
| # For cropped and aligned faces |
| python inference_codeformer.py -w 0.5 --has_aligned --input_path [input folder] |
| ``` |
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| :framed_picture: Whole Image Enhancement |
| ``` |
| # For whole image |
| # 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 --input_path [image folder/image path] |
| ``` |
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| :clapper: Video Enhancement |
| ``` |
| # For video clips |
| python inference_codeformer.py --bg_upsampler realesrgan --face_upsample -w 1.0 --input_path [video path] |
| ``` |
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| Fidelity weight *w* lays in [0, 1]. Generally, smaller *w* tends to produce a higher-quality result, while larger *w* yields a higher-fidelity result. |
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| The results will be saved in the `results` folder. |
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| ### Citation |
| If our work is useful for your research, please consider citing: |
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| @inproceedings{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}, |
| booktitle = {NeurIPS}, |
| year = {2022} |
| } |
| |
| ### License |
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| This project is licensed under <a rel="license" href="https://github.com/sczhou/CodeFormer/blob/master/LICENSE">NTU S-Lab License 1.0</a>. Redistribution and use should follow this license. |
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| ### Acknowledgement |
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| This project is based on [BasicSR](https://github.com/XPixelGroup/BasicSR). Some codes are brought 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). We also adopt [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN) to support background image enhancement. Thanks for their awesome works. |
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| ### Contact |
| If you have any question, please feel free to reach me out at `shangchenzhou@gmail.com`. |
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