tensorlayer/SRGAN
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
Flags: no_license
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: 3422
- days_rel: n/a
- days_push: 924
- n_releases_24m: 0
Adoption not part of the score
3466 stars · 811 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Reference implementation of SRGAN, a generative adversarial network for photo-realistic single image super-resolution, built on TensorLayerX/TensorFlow. It includes training scripts, VGG19 perceptual loss, and DIV2K dataset support.
Use cases
- upscale low-resolution images with a GAN
- train an SRGAN super-resolution model
- reproduce the SRGAN paper
- image super-resolution with VGG perceptual loss
- enhance photo resolution using deep learning
When to choose
- you want a faithful SRGAN reference implementation
- you already use TensorLayerX or TensorFlow
- you want to train super-resolution on DIV2K or custom images
When to avoid
- you need a production-ready super-resolution library
- you need a maintained project with a license
- you use PyTorch exclusively without TensorLayerX
Facets
library · maturity maintenance
machine-learning deep-learning image-processing computer-vision computer-vision image-processing deep-learning python cross-platform super-resolution gan srgan tensorlayerx vgg19 example-code gpu
2 sources
- readme: https://github.com/tensorlayer/SRGAN · fetched 2026-08-28 · c6a6480eed5d
- homepage: https://github.com/tensorlayer/tensorlayerx · fetched 2026-08-29 · 469f2bdb4d1a
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| tensorlayer/SRGAN | main | 23 |
For agents
markdown · JSON · MCP: product_card(name="tensorlayer/SRGAN")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem