leftthomas/SRGAN
A PyTorch implementation of SRGAN based on CVPR 2017 paper "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3224
- days_rel: n/a
- days_push: 773
- n_releases_24m: 0
Adoption not part of the score
1248 stars · 353 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A PyTorch implementation of SRGAN, the CVPR 2017 generative adversarial network for photo-realistic single-image super-resolution. It includes training, benchmark testing, and single image/video upscaling scripts with pretrained model support.
Use cases
- upscale low resolution images with a GAN
- train an SRGAN super-resolution model on VOC2012
- evaluate super-resolution on Set5, Set14, BSD100 benchmarks
- enhance resolution of a single video
- reproduce the SRGAN paper in PyTorch
When to choose
- you want a faithful PyTorch reproduction of the SRGAN paper
- you need 2x/4x/8x image upscaling with GAN-based detail
- you want to experiment with or fine-tune a super-resolution GAN
When to avoid
- you need production-grade, well-maintained super-resolution (consider Real-ESRGAN)
- you want the latest transformer-based upscalers
- you need a packaged library API rather than training/testing scripts
Facets
library · maturity maintenance
machine-learning deep-learning image-processing computer-vision deep-learning computer-vision image-processing python cross-platform pytorch srgan super-resolution gan research-code gpu
1 source
- readme: https://github.com/leftthomas/SRGAN · fetched 2026-08-28 · df3186a77e8d
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| leftthomas/SRGAN | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="leftthomas/SRGAN")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem