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dlib as a new face detector option, it produces more accurate face identity.--input_path [YOUR_VIDEO.mp4]. Try it to enhance your videos! :clapper:
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)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)weights/CodeFormer folder. You can manually download the pretrained models OR download by running the following command:python scripts/download_pretrained_models.py CodeFormerinputs/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]--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.results folder.# For cropped and aligned faces (512x512)
python inference_codeformer.py -w 0.5 --has_aligned --input_path [image folder]|[image path]# 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]# 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]# For cropped and aligned faces (512x512)
# Colorize black and white or faded photo
python inference_colorization.py --input_path [image folder]|[image path]# 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]Only demos on Hugging Face Space, Replicate, and OpenXLab are official deployments maintained by the authors. All other demos, APIs, apps, websites, and integrations listed below are third-party (non-official) and are not affiliated with the CodeFormer authors. Please verify their legitimacy to avoid potential financial loss.
| Website | Link | Notes |
|---|---|---|
| CodeFormer.net | https://codeformer.net/ | Non-official website |
| CodeFormer.cn | https://www.codeformer.cn/ | Non-official website |
| CodeFormerAI.com | https://codeformerai.com/ | Non-official website |
| Project / Toolkit | Link | Notes |
|---|---|---|
| Stable Diffusion GUI | https://nmkd.itch.io/t2i-gui | Integration |
| Stable Diffusion WebUI | https://github.com/AUTOMATIC1111/stable-diffusion-webui | Integration |
| ChaiNNer | https://github.com/chaiNNer-org/chaiNNer | Integration |
| PyPI | https://pypi.org/project/codeformer/ ; https://pypi.org/project/codeformer-pip/ | Python packages |
| ComfyUI | https://stable-diffusion-art.com/codeformer/ | Integration |
@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}
}shangchenzhou@gmail.com.