Install dependent packages # Install basicsr - # We use BasicSR for both training and inference If you want to use the original model in our paper, please see PaperModel.md for installation. We now provide a clean version of GFPGAN, which does not require customized CUDA extensions. Python >= 3.7 (Recommend to use Anaconda or Miniconda).Xintao Wang, Yu Li, Honglun Zhang, Ying ShanĪpplied Research Center (ARC), Tencent PCG :book: GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior :arrow_forward: HandyView: A PyQt5-based image viewer that is handy for view and comparison :arrow_forward: facexlib: A collection that provides useful face-relation functions :arrow_forward: BasicSR: An open-source image and video restoration toolbox :arrow_forward: Real-ESRGAN: A practical algorithm for general image restoration If GFPGAN is helpful in your photos/projects, please help to :star: this repo or recommend it to your friends. :white_check_mark: We provide an updated model without colorizing faces.:white_check_mark: We provide a clean version of GFPGAN, which does not require CUDA extensions.:white_check_mark: Support enhancing non-face regions (background) with Real-ESRGAN.:white_check_mark: Integrated to Huggingface Spaces with Gradio.:white_check_mark: Add V1.3 model, which produces more natural restoration results, and better results on very low-quality / high-quality inputs.:white_check_mark: Add V1.4 model, which produces slightly more details and better identity than V1.3.:white_check_mark: Add RestoreFormer inference codes.:question: Frequently Asked Questions can be found in FAQ.md. It leverages rich and diverse priors encapsulated in a pretrained face GAN ( e.g., StyleGAN2) for blind face restoration. GFPGAN aims at developing a Practical Algorithm for Real-world Face Restoration. You may also want to check our new updates on the tiny models for anime images and videos in Real-ESRGAN :blush: :rocket: Thanks for your interest in our work. Colab Demo for GFPGAN (Another Colab Demo for the original paper model).
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