IceClear/StableSR

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2668 stars · 171 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

StableSR is a Python research library that leverages pre-trained Stable Diffusion priors for real-world blind image super-resolution. It provides a time-aware encoder, controllable feature wrapping for quality-fidelity tradeoff, and progressive aggregation sampling for arbitrary-size upscaling.

Use cases

• upscale low-quality real-world photos
• restore degraded images with diffusion models
• super-resolve old or compressed images
• enhance faces in low-resolution images
• run image super-resolution with stable diffusion prior
• balance fidelity and quality when upscaling

When to choose

• you need state-of-the-art blind super-resolution on real-world degraded images
• you want to leverage Stable Diffusion priors for restoration research
• you need arbitrary-resolution upscaling with controllable quality-fidelity tradeoff

When to avoid

• you need a lightweight fast upscaler without GPU or diffusion model overhead
• you only need simple bicubic-style resizing
• you need a production service with a stable license (license is non-standard)

Facets

library · maturity stable

image-processing machine-learning deep-learning stable-diffusion image-processing computer-vision deep-learning artificial-intelligence python cross-platform super-resolution diffusion-models stable-diffusion image-restoration blind-sr research-code gpu linux

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markdown · JSON · MCP: product_card(name="IceClear/StableSR")