# rh12503/triangula

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3,876 stars · 119 forks · Go · MIT

## Links

- GitHub: https://github.com/rh12503/triangula
- awesome-repositories: https://awesome-repositories.com/repository/rh12503-triangula.md

## Topics

`art` `evolutionary-algorithms` `evolutionary-art` `generative-art` `genetic-algorithm` `go` `golang` `gui` `polygons` `triangles` `triangula`

## Description

Triangula is a genetic algorithm image stylizer and renderer that transforms raster images into stylized polygonal artwork. It functions as an image-to-SVG converter that optimizes point placement to recreate the shapes and colors of a source image using triangulated polygons.

The project utilizes a fitness-based point selection process and genetic algorithm optimization to iteratively evolve vertex positions. This approach minimizes the difference between the generated polygons and the original image through crossover, mutation, and iterative polygon refinement.

The system covers the full pipeline from raster-to-polygon mapping to the generation of scalable vector graphics. It includes controls for algorithm precision, allowing for the adjustment of population size and mutation rates to balance detail and accuracy in the final render.

Final outputs are rendered as scalable vector graphics or raster image formats.

## Tags

### Artificial Intelligence & ML

- [Genetic Algorithms](https://awesome-repositories.com/f/artificial-intelligence-ml/genetic-algorithms.md) — Uses genetic algorithms to iteratively evolve vertex positions through crossover and mutation to minimize image error.
- [Image Fidelity Evaluation](https://awesome-repositories.com/f/artificial-intelligence-ml/fitness-based-selection/image-fidelity-evaluation.md) — Implements a fitness-based selection process that measures the structural and color difference between generated polygons and the original image.
- [Image Stylization Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/genetic-algorithms/image-stylization-tools.md) — Transforms photographs into triangulated and polygonal artwork using genetic algorithms.
- [Optimization-Based](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-image-models/autoregressive-image-generation/llm-based-generators/svg-generators/optimization-based.md) — Produces scalable vector graphics by optimizing point placement to recreate the shapes in a source image.
- [Evolutionary Parameter Controls](https://awesome-repositories.com/f/artificial-intelligence-ml/hyperparameter-configurations/mutation-controls/evolutionary-parameter-controls.md) — Provides parametric controls for mutation rates and population size to balance generation speed and artistic detail.

### Graphics & Multimedia

- [Artistic Image Processing](https://awesome-repositories.com/f/graphics-multimedia/artistic-image-processing.md) — Transforms standard images into artistic renders with adjustable precision for a low-poly aesthetic.
- [Artistic Triangulation](https://awesome-repositories.com/f/graphics-multimedia/cad-to-mesh-tessellators/polygon-triangulators/artistic-triangulation.md) — Transforms images into polygonal artwork by iteratively optimizing point placement using a genetic algorithm. ([source](https://github.com/rh12503/triangula#readme))
- [Image-to-Polygonal Art Conversion](https://awesome-repositories.com/f/graphics-multimedia/image-to-polygonal-art-conversion.md) — Converts photographs into stylized geometric artwork using genetic algorithms to optimize vertex placement.
- [Vertex Refinement](https://awesome-repositories.com/f/graphics-multimedia/iterative-surface-refinement/vertex-refinement.md) — Progressively updates the position and count of vertices to improve the visual accuracy of the stylized output.
- [Stylized Rendering Techniques](https://awesome-repositories.com/f/graphics-multimedia/media-production-suites/animation-tools/mathematical-visualization-engines/3d-surface-visualizations/3d-visual-effects/stylized-rendering-techniques.md) — Produces non-photorealistic artistic outputs in SVG or PNG formats based on calculated triangulation fitness. ([source](https://github.com/rh12503/triangula#readme))
- [Polygonal Art Renderers](https://awesome-repositories.com/f/graphics-multimedia/polygonal-art-renderers.md) — Converts images into a stylized geometric aesthetic using iterative optimization for precision and detail.
- [Raster-to-Polygon Mappings](https://awesome-repositories.com/f/graphics-multimedia/raster-to-polygon-mappings.md) — Maps pixels from a source image onto a geometric mesh to determine the average color for each triangle.
- [Raster-to-Polygonal SVG Converters](https://awesome-repositories.com/f/graphics-multimedia/raster-to-polygonal-svg-converters.md) — Translates raster images into simplified polygonal SVG formats through a fitness-based point selection process.
- [Algorithm Precision Controls](https://awesome-repositories.com/f/graphics-multimedia/algorithm-precision-controls.md) — Provides mechanisms to balance detail and accuracy by adjusting point counts, population size, and mutation rates. ([source](https://github.com/rh12503/triangula#readme))
- [Algorithmic Art Composition](https://awesome-repositories.com/f/graphics-multimedia/algorithmic-art-composition.md) — Creates high-quality abstract visuals from images by balancing detail and accuracy through iterative processing.
- [Vector Asset Pipelines](https://awesome-repositories.com/f/graphics-multimedia/vector-asset-pipelines.md) — Implements a pipeline that translates calculated vertex coordinates and color data into scalable vector graphics.
- [Raster-to-SVG Transformers](https://awesome-repositories.com/f/graphics-multimedia/vector-graphics-export/raster-to-svg-transformers.md) — Produces scalable vector graphics from raster images by simplifying them into a collection of triangulated polygons.