GFPGAN develops algorithms for restoring real-world faces in images, with its repository focused on practical face-restoration research.
Open source
18 alternativesReal-ESRGAN
Real-ESRGAN develops algorithms for general image and video restoration.
About Real-ESRGAN
Real-ESRGAN is an open-source project for general image and video restoration and upscaling. It extends ESRGAN and is trained with synthetic data, with Python scripts for image and video inference and separate models for general scenes and anime images and videos. It supports tiled inference, images with alpha channel, gray and 16-bit images, arbitrary output scaling, finetuning on own or paired data, and face enhancement through GFPGAN integration. Local use requires Python >= 3.7 and PyTorch >= 1.7 with manual installation, while portable executables and listed online demos provide other ways to try it.
Key features
- Restore and upscale general images and videos
- Anime-specific models for images and videos
- Face enhancement through GFPGAN integration
- Tiled inference with support for alpha, gray, 16-bit images
- Arbitrary output scaling with LANCZOS4 resizing
- Finetuning support on own or paired data
Best for: People with a Python and PyTorch setup who want to run image and video restoration locally, including anime content.
Good for
- Open-source repository with training code released
- Includes models for general scenes and anime images and videos
- Offers inference by Python script, portable executables, and online demos
Watch out for
- Requires Python >= 3.7 and PyTorch >= 1.7 with manual installation steps
- ARC online demo only supports the RealESRGAN_x4plus_anime_6B model
- Local use involves cloning the repository and installing multiple packages
Real-ESRGAN at a glance
- Category
- Design & Creative › Image Creation & Editing
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Real-ESRGAN FAQ
What is needed to install Real-ESRGAN?
Python >= 3.7, with Anaconda or Miniconda recommended, and PyTorch >= 1.7, plus packages including basicsr, facexlib, gfpgan, and requirements.txt.
What are the ways to run inference?
Online inference, portable executable files using NCNN, and Python scripts.
Does it support face enhancement?
Yes, it integrates GFPGAN to support face enhancement.
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