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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 (NeurIPS 2022) | |
| [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://huggingface.co/spaces/sczhou/CodeFormer) [](https://replicate.com/sczhou/codeformer) [](https://openxlab.org.cn/apps/detail/ShangchenZhou/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 | |
| - **2023.07.20**: Integrated to :panda_face: [OpenXLab](https://openxlab.org.cn/apps). Try out online demo! [](https://openxlab.org.cn/apps/detail/ShangchenZhou/CodeFormer) | |
| - **2023.04.19**: :whale: Training codes and config files are public available now. | |
| - **2023.04.09**: Add features of inpainting and colorization for cropped and aligned face images. | |
| - **2023.02.10**: Include `dlib` as a new face detector option, it produces more accurate face identity. | |
| - **2022.10.05**: Support video input `--input_path [YOUR_VIDEO.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) | |
| - [**More**](docs/history_changelog.md) | |
| ### TODO | |
| - [x] Add training code and config files | |
| - [x] Add checkpoint and script for face inpainting | |
| - [x] Add checkpoint and script for face colorization | |
| - [x] ~~Add background image enhancement~~ | |
| #### :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) | |
| #### 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 (only for face detection or cropping with dlib) | |
| ``` | |
| <!-- conda install -c conda-forge dlib --> | |
| ### Quick Inference | |
| #### Download Pre-trained Models: | |
| Download the facelib and dlib pretrained models from [[Releases](https://github.com/sczhou/CodeFormer/releases/tag/v0.1.0) | [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 | |
| python scripts/download_pretrained_models.py dlib (only for dlib face detector) | |
| ``` | |
| Download the CodeFormer pretrained models from [[Releases](https://github.com/sczhou/CodeFormer/releases/tag/v0.1.0) | [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 | |
| ``` | |
| #### 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. You can get the cropped and aligned faces by running the following command: | |
| ``` | |
| # you may need to install dlib via: conda install -c conda-forge dlib | |
| python scripts/crop_align_face.py -i [input folder] -o [output folder] | |
| ``` | |
| #### Testing: | |
| [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. | |
| 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. The results will be saved in the `results` folder. | |
| ๐ง๐ป Face Restoration (cropped and aligned face) | |
| ``` | |
| # For cropped and aligned faces (512x512) | |
| python inference_codeformer.py -w 0.5 --has_aligned --input_path [image folder]|[image path] | |
| ``` | |
| :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] | |
| ``` | |
| :clapper: Video Enhancement | |
| ``` | |
| # For Windows/Mac users, please install ffmpeg first | |
| conda install -c conda-forge ffmpeg | |
| ``` | |
| ``` | |
| # For video clips | |
| # Video path should end with '.mp4'|'.mov'|'.avi' | |
| python inference_codeformer.py --bg_upsampler realesrgan --face_upsample -w 1.0 --input_path [video path] | |
| ``` | |
| ๐ Face Colorization (cropped and aligned face) | |
| ``` | |
| # For cropped and aligned faces (512x512) | |
| # Colorize black and white or faded photo | |
| python inference_colorization.py --input_path [image folder]|[image path] | |
| ``` | |
| ๐จ Face Inpainting (cropped and aligned face) | |
| ``` | |
| # For cropped and aligned faces (512x512) | |
| # Inputs could be masked by white brush using an image editing app (e.g., Photoshop) | |
| # (check out the examples in inputs/masked_faces) | |
| python inference_inpainting.py --input_path [image folder]|[image path] | |
| ``` | |
| ### Training: | |
| The training commands can be found in the documents: [English](docs/train.md) **|** [็ฎไฝไธญๆ](docs/train_CN.md). | |
| ### Citation | |
| If our work is useful for your research, please consider citing: | |
| @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 | |
| 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. | |
| ### Acknowledgement | |
| 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. | |
| ### Contact | |
| If you have any questions, please feel free to reach me out at `[email protected]`. | |