copc-rs is a rust library for reading and writing Cloud Optimized Point Cloud (COPC) data. It utilizes the las and laz crates heavily and tries to offer a similiar API to las.
let mut copc_reader = CopcReader::from_path("autzen-classified.copc.laz")?;
for point in copc_reader.points(LodSelection::Level(0), BoundsSelection::All)?.take(5) {
println!("Point coordinates: ({}, {}, {})", point.x, point.y, point.z);
}
Full example with bounds selection:
use copc_rs::{Bounds, BoundsSelection, CopcReader, LodSelection, Vector};
fn main() {
let mut copc_reader = CopcReader::from_path("./lidar.copc.laz").unwrap();
let bounds = Bounds {
min: Vector {
x: 698_100.,
y: 6_508_100.,
z: 0.,
},
max: Vector {
x: 698_230.,
y: 6_508_189.,
z: 2_000.,
},
};
for point in copc_reader
.points(LodSelection::Resolution(1.), BoundsSelection::Within(bounds))
.unwrap()
{
// do something with the points
}
}
Run an example:
cargo run --example copc_http
Writer [*]
use copc_rs::CopcWriter;
use las::Reader;
fn main() {
let mut las_reader = Reader::from_path("./lidar.las").unwrap();
let header = las_reader.header().clone();
let num_points = header.number_of_points() as i32;
let points = las_reader.points().filter_map(las::Result::ok);
let mut copc_writer = CopcWriter::from_path("./lidar.copc.laz", header, -1, -1).unwrap();
copc_writer.write(points, num_points).unwrap();
println!("{:#?}", copc_writer.copc_info());
}
Writing of the octree structure seem to work, so spatial queries in full resolution on copc-rs written files should be good. BUT the octree levels does not yet contain a similar point distribution as the whole cloud so results from resolution queries on copc-rs written files are wrong. This means the written files will look bad in viewers.
I will look into it when I find time, for now I only need full resolution spatial queries in my current project anyway.
-yvind
This library depends heavily on the work of Thomas Montaigu (@tmontaigu) and Pete Gadomski (@gadomski), the authors of the laz and las crates.