xinntao/ESRGAN

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

6568 stars · 1119 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

ESRGAN (Enhanced SRGAN) is a PyTorch-based image super-resolution model that won the PIRM 2018 Challenge on Perceptual Super-Resolution. This repository provides testing code, pretrained models, and a network interpolation demo, with training code moved to BasicSR and development continued in Real-ESRGAN.

Use cases

• upscale low-resolution images with better perceptual quality
• enhance old photos by increasing resolution
• test pretrained super-resolution models in python
• interpolate between SRGAN and ESRGAN models
• research perceptual image super-resolution

When to choose

• you need a proven perceptual super-resolution model with pretrained weights
• you want a simple inference/testing setup for ESRGAN
• you are reproducing ECCV18 workshop or PIRM challenge results

When to avoid

• you need training code - use BasicSR instead
• you want practical real-world restoration with artifact removal - use Real-ESRGAN
• you need tile inference, alpha channel, or 16-bit image support - available in Real-ESRGAN
• you need an actively developed tool - this repo is frozen for compatibility

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision image-processing deep-learning python windows super-resolution esrgan srgan image-restoration pytorch pretrained-models pirm-challenge linux macos

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markdown · JSON · MCP: product_card(name="xinntao/ESRGAN")