threecrate-io 0.7.0

I/O operations for point clouds and meshes in threecrate
Documentation

ThreeCrate I/O

Crates.io Documentation License

File I/O operations for point clouds and meshes in the threecrate ecosystem.

Supported Formats

Point Clouds

  • PLY: Polygon File Format (ASCII and binary)
  • PCD: Point Cloud Data format (ASCII and binary)
  • LAS/LAZ: LiDAR data formats via Pasture (feature-gated)
  • XYZ/CSV: Comma-separated values with configurable columns
  • E57: 3D imaging format (feature-gated)

Meshes

  • OBJ: Wavefront OBJ with materials and groups
  • PLY: Triangle meshes in PLY format

Features

  • Auto-detect format from file extension
  • Streaming readers for memory-efficient processing of large files
  • Memory-mapped I/O for large binary files (io-mmap feature)
  • Attribute-preserving read/write with metadata support
  • Robust readers with error recovery

Usage

Add this to your Cargo.toml:

[dependencies]
threecrate-io = "0.6.0"
threecrate-core = "0.6.0"

Optional Features

  • las_laz: Enable LAS/LAZ format support via Pasture
  • e57: Enable E57 format support
  • io-mmap: Enable memory-mapped I/O for improved performance on large binary files
[dependencies]
threecrate-io = { version = "0.6.0", features = ["io-mmap", "e57"] }

Examples

Basic Usage

use threecrate_io::{read_point_cloud, write_point_cloud, read_mesh, write_mesh};

// Auto-detect format and load point cloud
let cloud = read_point_cloud("input.ply")?;
println!("Loaded {} points", cloud.len());

// Save point cloud (format determined by extension)
write_point_cloud(&cloud, "output.pcd")?;

// Load and save mesh
let mesh = read_mesh("model.obj")?;
write_mesh("output.ply", &mesh)?;

Streaming I/O

use threecrate_io::read_point_cloud_iter;

// Process large files without loading everything into memory
for chunk in read_point_cloud_iter("large_scan.ply")? {
    let points = chunk?;
    // process chunk
}

Memory-Mapped I/O

For large binary files, enable the io-mmap feature for better performance:

cargo run --example mmap_example --features io-mmap
cargo bench --features io-mmap mmap_benchmarks

License

This project is licensed under either of

at your option.