GFP-GAN：利用生成性面部优先权实现现实世界的盲目面部修复；GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial PriorGFPGAN旨在开发一个实用的算法用于现实世界的人脸修复。
它利用预先训练好的人脸GAN（如StyleGAN2）中封装的丰富和多样的先验因素进行盲目的人脸修复。
安装
-
Clone repo
git clone https://github.com/TencentARC/GFPGAN.git cd GFPGAN -
Install dependent packages
# Install basicsr - https://github.com/xinntao/BasicSR # We use BasicSR for both training and inference pip install basicsr # Install facexlib - https://github.com/xinntao/facexlib # We use face detection and face restoration helper in the facexlib package pip install facexlib pip install -r requirements.txt python setup.py develop # If you want to enhance the background (non-face) regions with Real-ESRGAN, # you also need to install the realesrgan package pip install realesrgan
快速开始：
下载预训练模型: GFPGANv1.3.pth，
wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth -P experiments/pretrained_models
其他模型下载链接：https://share.weiyun.com/ShYoCCoc
使用方法：
python inference_gfpgan.py -i inputs/whole_imgs -o results -v 1.3 -s 2
Usage: python inference_gfpgan.py -i inputs/whole_imgs -o results -v 1.3 -s 2 [options]...
-h show this help
-i input Input image or folder. Default: inputs/whole_imgs
-o output Output folder. Default: results
-v version GFPGAN model version. Option: 1 | 1.2 | 1.3. Default: 1.3
-s upscale The final upsampling scale of the image. Default: 2
-bg_upsampler background upsampler. Default: realesrgan
-bg_tile Tile size for background sampler, 0 for no tile during testing. Default: 400
-suffix Suffix of the restored faces
-only_center_face Only restore the center face
-aligned Input are aligned faces
-ext Image extension. Options: auto | jpg | png, auto means using the same extension as inputs.
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