GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. Colab Demo for GFPGAN; (Another Colab Demo for the original paper model) Online demo: Huggingface (return only the cropped face) Online demo: Replicate.ai (may need to sign in, return the whole image). Online demo: Baseten.co (backed by GPU, returns the whole image). We provide a clean version of GFPGAN, which can run without CUDA extensions. So that it can run in Windows or on CPU mode. GFPGAN aims at developing a Practical Algorithm for Real-world Face Restoration. It leverages rich and diverse priors encapsulated in a pretrained face GAN (e.g., StyleGAN2) for blind face restoration. Add V1.3 model, which produces more natural restoration results, and better results on very low-quality / high-quality inputs.

Features

  • Practical algorithm for general image restoration
  • Open-source image and video restoration toolbox
  • Collection that provides useful face-relation functions
  • PyQt5-based image viewer that is handy for view and comparison
  • Requires Python >= 3.7
  • NVIDIA GPU + CUDA

Project Samples

Project Activity

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License

Apache License V2.0

Follow GFPGAN

GFPGAN Web Site

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Additional Project Details

Operating Systems

Linux, Windows

Programming Language

Python

Related Categories

Python Algorithms, Python Machine Learning Software

Registered

2022-07-28