threecrate

A high-performance 3D point cloud and mesh processing library for Rust, with Python bindings.

What's inside

Crate	What it does
threecrate-core	Point, PointCloud, TriangleMesh, Transform3D
threecrate-algorithms	Filtering, ICP, NDT, global registration, segmentation, normals, FPFH/SHOT, mesh boolean, smoothing
threecrate-gpu	GPU filtering, ICP, normals, nearest-neighbor, TSDF, real-time rendering (wgpu)
threecrate-io	PLY, OBJ, PCD, XYZ/CSV, LAS/LAZ*, E57* — streaming and memory-mapped
threecrate-reconstruction	Poisson, BPA, alpha shapes, Delaunay, Marching Cubes, MLS, auto-select
threecrate-simplification	Quadric error, edge collapse, clustering, progressive mesh
threecrate-visualization	Interactive viewer — orbit/pan/zoom, GPU-accelerated

* opt-in feature flags

Viewer

Quick start

Rust

[dependencies]
threecrate = "0.7.1"

use threecrate::prelude::*;

let cloud = read_point_cloud("scan.ply")?;
let cloud = voxel_grid_filter(&cloud, 0.05)?;
let normals = estimate_normals(&cloud, 10)?;
let mesh = auto_reconstruct(&normals)?;
write_mesh("output.obj", &mesh)?;

Python

pip install threecrate

import threecrate as tc

cloud = tc.read_point_cloud("scan.ply")
cloud = tc.voxel_downsample(cloud, voxel_size=0.05)
normal_cloud = tc.estimate_normals(cloud)
mesh = tc.poisson_reconstruct(normal_cloud)
tc.write_mesh(mesh, "output.ply")

Comparison

Feature	threecrate	Open3D	PCL
Language	Rust + Python	Python (C++ core)	C++
pip install	✅	✅	❌
Memory safety	✅ Rust	❌	❌
GPU compute	✅ wgpu	✅ CUDA	Partial
Global registration	✅ FPFH+RANSAC	✅	✅
Surface reconstruction	✅ 6 algorithms	✅	✅
Streaming I/O	✅ PLY/OBJ/XYZ	❌	❌
E57 support	✅ opt-in	❌	❌
WebAssembly	Roadmap	❌	❌

Docs

• Installation & feature flags
• Crate reference
• Examples
• Python API reference
• API docs on docs.rs

Contributing

Contributions are welcome — algorithms, Python bindings, new formats, docs.

• CONTRIBUTING.md — setup and guidelines
• Open issues — look for good first issue
• GitHub Discussions — questions and ideas

License

licensed under MIT