# nihui/realsr-ncnn-vulkan

RealSR super resolution implemented with ncnn library

Repository: https://github.com/nihui/realsr-ncnn-vulkan
Canonical: https://ross.abutalabs.com/products/realsr-ncnn-vulkan
Language: C
License: MIT
License Family: permissive
Topics: realsr, ncnn, vulkan, gpu, amd, nvidia, intel
Last push: 2023-03-12T03:03:53+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2290, "days_push": 1270, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1213, forks 112 (observed 2026-08-28T04:04:00.715698+00:00)

## What it is
A command-line tool implementing the RealSR real-world super-resolution model using the ncnn inference framework with Vulkan GPU acceleration. It upscales images 4x on Intel, AMD, and Nvidia GPUs without requiring CUDA or other deep learning runtimes.

## Use cases
- upscale low-resolution photos 4x
- enhance JPEG-compressed images with super resolution
- batch upscale a folder of images on GPU
- run super resolution without CUDA or PyTorch
- upscale anime or game screenshots
- process images on AMD or Intel GPUs

## When to choose
- you need portable GPU-accelerated image upscaling with no Python or CUDA dependencies
- you want a simple CLI for batch super-resolution on Windows/Linux/macOS
- your GPU is AMD or Intel where CUDA tools don't work

## When to avoid
- you need real-time or video super-resolution
- you want to train or fine-tune the model yourself
- you need arbitrary upscale ratios other than 4x

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: image-processing, machine-learning, llm-inference
- domain: image-processing, computer-vision, machine-learning
- platform: windows, cross-platform, cli
- tags: super-resolution, ncnn, vulkan, upscaling, image-enhancement, gpu-accelerated, linux, macos, gpu

## Member repositories
- nihui/realsr-ncnn-vulkan (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:00.715698+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:17:56.831558+00:00, confidence not recorded.
  - readme: https://github.com/nihui/realsr-ncnn-vulkan (fetched 2026-08-28T04:04:00.715698+00:00, sha 5eff124e1505)
- Data as of 2026-08-30T08:39:29.467469+00:00.