iTriangle

iTriangle is a high-performance 2D polygon triangulation library for Rust. It solves robust triangulation for real-world, messy input (holes, self-intersections, mixed winding) and is built for GIS/CAD, simulation, and rendering pipelines that need deterministic results.

For detailed performance benchmarks, check out the Performance Comparison

Table of Contents

• Why iTriangle?
• Features
• Architecture Overview
• Quick Start
• Documentation
• Examples
• Performance
• Gallery
• Contributing
• License

Why iTriangle?

• Robust on complex input: supports holes and self-intersections with automatic resolution.
• Deterministic and stable: integer-based core avoids floating-point corner cases.
• High-performance: optimized sweep-line triangulation with cache-friendly outputs.
• Flexible outputs: Delaunay, convex decomposition, tessellation, and centroid nets.

Features

• Sweep-line Triangulation - Fast and simple triangulation of polygons with or without holes.
• Delaunay Triangulation - Efficient and robust implementation for generating Delaunay triangulations.
• Self-Intersection Handling – Fully supports self-intersecting polygons with automatic resolution.
• Adaptive Tessellation - Refine Delaunay triangles using circumcenters for better shape quality.
• Convex Decomposition - Convert triangulation into convex polygons.
• Centroidal Polygon Net: Build per-vertex dual polygons using triangle centers and edge midpoints.
• Steiner Points: Add custom inner points to influence triangulation.
• GPU-Friendly Layout: Triangles and vertices are naturally ordered by X due to the sweep-line algorithm, improving cache locality for rendering.

Architecture Overview

Mermaid source

flowchart TD
    A[Input contours] --> B[Normalize and fix self-intersections]
    B --> C[Sweep-line triangulation]
    C --> D[Raw triangulation]
    D -->|Delaunay| E[Delaunay triangulation]
    D --> I[Triangles and indices]
    E -->|Tessellation| F[Adaptive refinement]
    F --> E
    E --> G[Convex decomposition]
    E --> H[Centroid net]
    E --> I

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Quick Start

Add to your Cargo.toml:

[dependencies]
i_triangle = "0.36"

Minimal example:

use i_triangle::float::triangulatable::Triangulatable;

let contour = vec![
    [0.0, 0.0],
    [10.0, 0.0],
    [10.0, 10.0],
    [0.0, 10.0],
];

let triangulation = vec![contour].triangulate().to_triangulation::<u16>();
println!("triangles: {}", triangulation.indices.len() / 3);

Documentation

• Docs.rs
• Delaunay
• Demos

Examples

Single Shape Triangulation

use i_triangle::float::triangulatable::Triangulatable;
use i_triangle::float::triangulation::Triangulation;

let shape = vec![
    vec![
        // body
        [0.0, 20.0],    // 0
        [-10.0, 8.0],   // 1
        [-7.0, 6.0],    // 2
        [-6.0, 2.0],    // 3
        [-8.0, -2.0],   // 4
        [-13.0, -4.0],  // 5
        [-16.0, -3.0],  // 6
        [-18.0, 0.0],   // 7
        [-25.0, -7.0],  // 8
        [-14.0, -15.0], // 9
        [0.0, -18.0],   // 10
        [14.0, -15.0],  // 11
        [26.0, -7.0],   // 12
        [17.0, 1.0],    // 13
        [13.0, -1.0],   // 14
        [9.0, 1.0],     // 15
        [7.0, 6.0],     // 16
        [8.0, 10.0],    // 17
    ],
    vec![
        // hole
        [2.0, 0.0],   // 0
        [5.0, -2.0],  // 1
        [7.0, -5.0],  // 2
        [5.0, -9.0],  // 3
        [2.0, -11.0], // 4
        [-2.0, -9.0], // 5
        [-4.0, -5.0], // 6
        [-2.0, -2.0], // 7
    ],
];

let triangulation = shape.triangulate().to_triangulation::<u16>();

println!("points: {:?}", triangulation.points);
println!("indices: {:?}", triangulation.indices);

let delaunay_triangulation: Triangulation<[f64; 2], u16> =
    shape.triangulate().into_delaunay().to_triangulation();

println!("points: {:?}", delaunay_triangulation.points);
println!("indices: {:?}", delaunay_triangulation.indices);

let convex_polygons = shape.triangulate().into_delaunay().to_convex_polygons();

println!("convex polygons: {:?}", convex_polygons);

let tessellation: Triangulation<[f64; 2], u16> = shape
    .triangulate()
    .into_delaunay()
    .refine_with_circumcenters_by_obtuse_angle(0.0)
    .to_triangulation();

println!("points: {:?}", tessellation.points);
println!("indices: {:?}", tessellation.indices);

let centroids = shape
    .triangulate()
    .into_delaunay()
    .refine_with_circumcenters_by_obtuse_angle(0.0)
    .to_centroid_net(0.0);

println!("centroids: {:?}", centroids);

💡 Output: Triangle indices and vertices, where all triangles oriented in a counter-clockwise direction.

Triangulating Multiple Shapes Efficiently

If you need to triangulate many shapes, it is more efficient to use Triangulator.

let contours = random_contours(100);

let mut triangulator = Triangulator::<u32>::default();

// Enable Delaunay refinement
triangulator.delaunay(true);

// Use fast Earcut solver for contours with ≤ 64 points
triangulator.earcut(true);

let mut triangulation = Triangulation::with_capacity(100);

for contour in contours.iter() {
    // Triangulate using self-intersection resolver
    triangulator.triangulate_into(contour, &mut triangulation);

    println!("points: {:?}", triangulation.points);
    println!("indices: {:?}", triangulation.indices);
}

Performance

Benchmarks and interactive demos are available here:

• Performance Comparison
• Triangulation Demo
• Tessellation Demo

Gallery

Delaunay	Convex Polygons	Steiner Points

Tessellation	Centroid Net

Contributing

See CONTRIBUTING.md for development setup, tests, and PR guidelines.

License

Licensed under either of:

• MIT license (LICENSE-MIT)
• Apache License, Version 2.0 (LICENSE-APACHE)