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rh12503 avatar

rh12503/triangula

0
View on GitHub↗
3,876 stars·119 forks·Go·MIT·14 views

Triangula

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.

Features

  • Genetic Algorithms - Uses genetic algorithms to iteratively evolve vertex positions through crossover and mutation to minimize image error.
  • Image Fidelity Evaluation - Implements a fitness-based selection process that measures the structural and color difference between generated polygons and the original image.
  • Image Stylization Tools - Transforms photographs into triangulated and polygonal artwork using genetic algorithms.
  • Artistic Image Processing - Transforms standard images into artistic renders with adjustable precision for a low-poly aesthetic.
  • Artistic Triangulation - Transforms images into polygonal artwork by iteratively optimizing point placement using a genetic algorithm.
  • Image-to-Polygonal Art Conversion - Converts photographs into stylized geometric artwork using genetic algorithms to optimize vertex placement.
  • Vertex Refinement - Progressively updates the position and count of vertices to improve the visual accuracy of the stylized output.
  • Stylized Rendering Techniques - Produces non-photorealistic artistic outputs in SVG or PNG formats based on calculated triangulation fitness.
  • Polygonal Art Renderers - Converts images into a stylized geometric aesthetic using iterative optimization for precision and detail.
  • Raster-to-Polygon Mappings - Maps pixels from a source image onto a geometric mesh to determine the average color for each triangle.
  • Raster-to-Polygonal SVG Converters - Translates raster images into simplified polygonal SVG formats through a fitness-based point selection process.
  • Optimization-Based - Produces scalable vector graphics by optimizing point placement to recreate the shapes in a source image.
  • Evolutionary Parameter Controls - Provides parametric controls for mutation rates and population size to balance generation speed and artistic detail.
  • Algorithm Precision Controls - Provides mechanisms to balance detail and accuracy by adjusting point counts, population size, and mutation rates.
  • Algorithmic Art Composition - Creates high-quality abstract visuals from images by balancing detail and accuracy through iterative processing.
  • Vector Asset Pipelines - Implements a pipeline that translates calculated vertex coordinates and color data into scalable vector graphics.
  • Raster-to-SVG Transformers - Produces scalable vector graphics from raster images by simplifying them into a collection of triangulated polygons.

Star history

Star history chart for rh12503/triangulaStar history chart for rh12503/triangula

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What does rh12503/triangula do?

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.

What are the main features of rh12503/triangula?

The main features of rh12503/triangula are: Genetic Algorithms, Image Fidelity Evaluation, Image Stylization Tools, Artistic Image Processing, Artistic Triangulation, Image-to-Polygonal Art Conversion, Vertex Refinement, Stylized Rendering Techniques.

What are some open-source alternatives to rh12503/triangula?

Open-source alternatives to rh12503/triangula include: rhiever/data-analysis-and-machine-learning-projects — This is a collection of machine learning projects, data visualization portfolios, and predictive analytics tools. The… guofei9987/scikit-opt — scikit-opt is a Python optimization library and numerical framework designed to solve complex global optimization… deap/deap. deviavir/zenbot — Zenbot is an automated cryptocurrency trading bot designed to execute trades on exchanges based on technical analysis… epistasislab/tpot — TPOT is a Python automated machine learning tool and pipeline framework. It automatically searches, selects, and tunes… chrxh/alien — Evolve is an evolution-based organism designer and GPU-accelerated artificial life simulator that combines interactive…