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توضیحات

Towards Robust Blind Face Restoration with Codebook Lookup Transformer (NeurIPS 2022)

ویژگی	مقدار
سیستم عامل	-
نام فایل	codeformer-perceptor-0.1.2
نام	codeformer-perceptor
نسخه کتابخانه	0.1.2
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Shangchen Zhou, Kelvin C.K. Chan, Chongyi Li, Chen Change Loy
ایمیل نویسنده	-
آدرس صفحه اصلی	-
آدرس اینترنتی	https://pypi.org/project/codeformer-perceptor/
مجوز	S-Lab License 1.0

<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> [![Hugging Face](https://img.shields.io/badge/Demo-%F0%9F%A4%97%20Hugging%20Face-blue)](https://huggingface.co/spaces/sczhou/CodeFormer) [![Replicate](https://img.shields.io/badge/Demo-%F0%9F%9A%80%20Replicate-blue)](https://replicate.com/sczhou/codeformer) ![visitors](https://visitor-badge.laobi.icu/badge?page_id=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: ## Install ```bash poetry add codeformer-perceptor ``` or ```bash pip install codeformer-perceptor ``` ## Usage ```python from PIL import Image from codeformer import CodeFormer model = CodeFormer().cuda() image = Image.open("test.jpg") restored_image = model(image) ``` **[<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! [![Hugging Face](https://img.shields.io/badge/Demo-%F0%9F%A4%97%20Hugging%20Face-blue)](https://huggingface.co/spaces/sczhou/CodeFormer) - **2022.09.09**: Integrated to :rocket: [Replicate](https://replicate.com/explore). Try out online demo! [![Replicate](https://img.shields.io/badge/Demo-%F0%9F%9A%80%20Replicate-blue)](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 checkpoint for face colorization - [ ] Add training code and config files - [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 ```  ### 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: [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. 🧑🏻 Face Restoration (cropped and aligned face) ``` # For cropped and aligned faces python inference_codeformer.py -w 0.5 --has_aligned --input_path [input folder] ``` :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 video clips # Set frame rate of saved video via '--save_video_fps 24' python inference_codeformer.py --bg_upsampler realesrgan --face_upsample -w 1.0 --input_path [video path] --save_video_fps 24 ``` 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. ### 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">S-Lab License 1.0</a>. Redistribution and use for non-commercial purposes 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 question, please feel free to reach me out at `shangchenzhou@gmail.com`.

نیازمندی

مقدار	نام
>=2.4.0,<3.0.0	addict
>=0.18.2,<0.19.0	future
>=1.3.0,<2.0.0	lmdb
>=1.21.5,<2.0.0	numpy
>=4.6.0.66,<5.0.0.0	opencv-python
>=9.2.0,<10.0.0	Pillow
>=6.0,<7.0	PyYAML
>=2.28.1,<3.0.0	requests
>=0.19.3,<0.20.0	scikit-image
>=1.9.2,<2.0.0	scipy
>=2.11.0a20221016,<3.0.0	tb-nightly
>=1.11.0,<2.0.0	torch
<1.0.0	torchvision
>=4.64.1,<5.0.0	tqdm
>=0.32.0,<0.33.0	yapf
>=0.1.4,<0.2.0	lpips
>=4.5.1,<5.0.0	gdown
>=3.2,<4.0	wget
>=1.4.2,<2.0.0	basicsr

زبان مورد نیاز

مقدار	نام
>=3.8,<4.0	Python

نحوه نصب

نصب پکیج whl codeformer-perceptor-0.1.2:

pip install codeformer-perceptor-0.1.2.whl

نصب پکیج tar.gz codeformer-perceptor-0.1.2:

pip install codeformer-perceptor-0.1.2.tar.gz