# runevision/Dither3D

Surface-Stable Fractal Dithering

Repository: https://github.com/runevision/Dither3D
Canonical: https://ross.abutalabs.com/products/dither3d
Language: ShaderLab
License: MPL-2.0
License Family: copyleft
Last push: 2025-02-09T13:10:28+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 5, release rhythm 35, longevity 41
- inputs: {"age_days": 587, "days_push": 570, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1585, forks 104 (observed 2026-08-28T04:05:07.483777+00:00)

## What it is
An implementation of Surface-Stable Fractal Dithering, a novel dithering technique for 3D surfaces where dither dots stick to surfaces while maintaining constant screen-space size. It ships as Unity shaders and textures with an example project demonstrating grayscale, RGB, and CMYK halftone modes.

## Use cases
- apply 1-bit dithering effects to 3D scenes
- create halftone CMYK rendering in Unity
- make dither patterns that stick to moving 3D surfaces
- achieve retro low-resolution looks in modern 3D games
- experiment with novel real-time shader techniques
- render stylized non-photorealistic 3D graphics

## When to choose
- you use Unity's Built-in Render Pipeline and want surface-stable dithering
- you need stylized retro or halftone visuals in a 3D project
- you want a reference implementation of fractal dithering research

## When to avoid
- you need dithering for 2D images or post-processing only
- you use URP/HDRP without porting the shaders
- your project is not built with Unity

## Facets
- artifact type: library
- maturity: stable
- function: graphics, image-processing
- domain: graphics, computer-vision
- platform: game-engine, cross-platform
- tags: dithering, shaders, unity, rendering, fractal-dithering, 3d-graphics, shader, game-development

## Member repositories
- runevision/Dither3D (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:07.483777+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 2026-08-30T03:55:39.152230+00:00, confidence not recorded.
  - readme: https://github.com/runevision/Dither3D (fetched 2026-08-28T04:05:07.483777+00:00, sha c1493eb8300c)
- Data as of 2026-08-30T08:39:29.467469+00:00.