Geometry processing library in pure Rust

❗ Under development. API may change.

Features

• Corner table implementation for efficient mesh traversal
• STL reader/writer
• Remeshing
• Mesh simplification (decimation)
• 2D triangulation
• Spatial index
  • Bounding volume hierarchy of axis aligned bounding boxes
  • Infinite grid

Reading/writing mesh from/to STL file

You can read/write STL files using StlReader and StlWriter structs. Ony binary STLs are supported.

Example

use std::path::Path;

use baby_shark::{
    io::stl::{StlReader, StlWriter}, 
    mesh::corner_table::prelude::CornerTableF
};

fn main() {
    let mut reader = StlReader::new();
    let mesh: CornerTableF = reader.read_stl_from_file(Path::new("./read.stl"))
        .expect("Read mesh from STL file");

    let writer = StlWriter::new();
    writer.write_stl_to_file(&mesh, Path::new("./write.stl"))
        .expect("Save mesh to STL file");
}

Isotropic remeshing

This algorithm incrementally performs simple operations such as edge splits, edge collapses, edge flips, and Laplacian smoothing. All the vertices of the remeshed patch are reprojected to the original surface to keep a good approximation of the input. Any of those operations can be turned off using appropriate method (with_<operation>(false)).

Example

let remesher = IncrementalRemesher::new()
    .with_iterations_count(10)
    .with_split_edges(true)
    .with_collapse_edges(true)
    .with_flip_edges(true)
    .with_shift_vertices(true)
    .with_project_vertices(true);
remesher.remesh(&mut mesh, 0.002f32);

Mesh simplification (decimation)

This library implements incremental edge decimation algorithm. On each iteration edge with lowest collapse cost is collapsed. Several stop condition are supported:

• Max error - algorithm stops when collapse lowest cost is bigger than given value
• Min faces count - algorithm stops when faces count drops below given value
• Bounding sphere - adaptive error algorithm based upon distance from a point. Useful for LOD mesh decimation.

Example

    let mut decimator = EdgeDecimator::new()
        .decimation_criteria(ConstantErrorDecimationCriteria::new(0.0005))
        .min_faces_count(Some(10000));
    decimator.decimate(&mut mesh);

Bounded Sphere Example

    let origin = Point3::<f32>::origin();
    let radii_error_map = vec![
        (10.0f32, 0.0001f32),
        (15.0f32, 0.05f32),
        (40.0f32, 0.8f32),
    ];

    let criteria = BoundingSphereDecimationCriteria::new(origin, radii_error_map);

    let mut decimator = EdgeDecimator::new().decimation_criteria(criteria);
    decimator.decimate(&mut mesh);

2D triangulation

Triangulation2 struct implements fast 2D delaunay triangulation of points set.

Example

let mut triangulation = Triangulation2::new();
triangulation.triangulate(&vec![
    Point2::new(1.0, 2.0),
    Point2::new(5.0, 1.0),
    Point2::new(8.0, 6.0),
    Point2::new(2.0, 8.0)
]);

Constrained 2D triangulation

The ConstrainedTriangulation2 struct facilitates the constrained triangulation of a set of points. It builds upon the unconstrained Delaunay triangulation by inserting constrained edges. However, it's important to note that the resulting triangulation may not always be a Delaunay triangulation.

Conflicting constraints are automatically resolved through the following steps:

• When a new constrained edge intersects with another constrained edge, both edges are split into two at the intersection point
• When a new constrained edge intersects with a point, the edge is split into two at that point

Example

let points = vec![
    Point2::new(-3.0, 1.0),
    Point2::new(0.0, 0.0),
    Point2::new(0.0, 4.0),
    Point2::new(3.0, 2.0),
    Point2::new(6.0, 0.0),
    Point2::new(6.0, 4.0),
    Point2::new(9.0, 2.0)
];
let mut tri = ConstrainedTriangulation2::from_points(&points);
tri.insert_constrained_edge(0, 6);