# rh12503/triangula

Generate high-quality triangulated and polygonal art from images.

Repository: https://github.com/rh12503/triangula
Canonical: https://ross.abutalabs.com/products/triangula
Language: Go
License: MIT
License Family: permissive
Topics: triangula, triangles, evolutionary-algorithms, evolutionary-art, genetic-algorithm, gui, generative-art, golang, art, go, polygons
Last push: 2026-03-21T00:05:04+00:00

## Health v2 (maintenance only)
Score: 56/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 73, release rhythm 8, longevity 100
- inputs: {"age_days": 1979, "days_push": 166, "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 3874, forks 119 (observed 2026-08-28T04:08:27.854165+00:00)

## What it is
Triangula is a Go application that generates triangulated and polygonal art from images using a modified genetic algorithm. It ships as a desktop GUI app and a CLI, and can render results to SVG or PNG.

## Use cases
- convert a photo into low-poly triangle art
- generate polygonal art from images
- triangulate an image with a genetic algorithm
- create SVG artwork from a picture
- stylize images with generative art algorithms

## When to choose
- you want high-quality triangulated or polygonal renditions of images
- you prefer a desktop GUI or a scriptable CLI for batch image stylization
- you want an open-source, MIT-licensed generative art tool

## When to avoid
- your images are very large (over 3000px) or need more than 3000 points
- you need real-time or instant processing
- you need general-purpose image editing rather than triangulation art

## Facets
- artifact type: application
- maturity: active
- function: image-processing, gui, cli
- domain: graphics, image-processing, developer-tools
- platform: go, cross-platform, cli
- tags: generative-art, genetic-algorithm, triangulation, polygon-art, svg-rendering, evolutionary-algorithms, desktop

## Member repositories
- rh12503/triangula (main) score 56

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:27.854165+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 2026-08-29T18:25:47.208218+00:00, confidence not recorded.
  - readme: https://github.com/rh12503/triangula (fetched 2026-08-28T04:08:27.854165+00:00, sha f3e98016396a)
- Data as of 2026-08-30T08:39:29.467469+00:00.