# TianZerL/Anime4KCPP

A high performance anime upscaler

Repository: https://github.com/TianZerL/Anime4KCPP
Canonical: https://ross.abutalabs.com/products/anime4kcpp
Language: C++
License: GPL-3.0
License Family: copyleft
Topics: anime4k, video-processing, upscaling, anime, computer-graphics, cpp, anime4kcpp, vapoursynth, avisynth, vapoursynth-plugin, avisynthplus-plugin, gpu-acceleration, machine-learning, cnn, directshow-filter
Last push: 2026-07-04T17:01:36+00:00

## Health v2 (maintenance only)
Score: 78/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 90, release rhythm 51, longevity 100
- inputs: {"age_days": 2352, "days_push": 60, "days_rel": 115, "gap_med": 282, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2022, forks 144 (observed 2026-08-28T04:06:06.469574+00:00)

## What it is
Anime4KCPP is a high-performance anime image and video upscaler built on CNN-based algorithms, written in C++. It ships as a library plus VapourSynth/AviSynth plugins, a CLI, and a WebAssembly playground.

## Use cases
- upscale anime images
- upscale anime videos to 4k
- enhance low-resolution anime frames
- super-resolution for anime artwork
- run anime upscaling in the browser
- integrate upscaling into VapourSynth pipeline

## When to choose
- you need fast GPU-accelerated anime upscaling
- you want CNN-based quality with a simple C++ integration
- you work in VapourSynth or AviSynth workflows

## When to avoid
- you need upscaling for photorealistic content rather than anime
- you want a plug-and-play GUI without building from source

## Facets
- artifact type: library
- maturity: active
- function: image-processing, video-processing, machine-learning, deep-learning
- domain: image-processing
- platform: cpp, cross-platform, wasm
- tags: anime-upscaling, cnn, super-resolution, vapoursynth-plugin, avisynth-plugin, directshow, video, gpu

## Member repositories
- TianZerL/Anime4KCPP (main) score 78

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:06.469574+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 2026-08-30T03:00:05.133329+00:00, confidence not recorded.
  - readme: https://github.com/TianZerL/Anime4KCPP (fetched 2026-08-28T04:06:06.469574+00:00, sha 02e16f2c087a)
- Data as of 2026-08-30T08:39:29.467469+00:00.