4 releases (breaking)
0.5.0 | Jun 20, 2024 |
---|---|
0.4.0 | Nov 2, 2023 |
0.2.0 | Oct 11, 2021 |
0.1.0 | Mar 22, 2021 |
#1839 in Data structures
Used in 3 crates
34KB
491 lines
pasture
A Rust library for working with point cloud data. It features:
- Fine-grained support for arbitrary point attributes, similar to PDAL, but with added type safety
- A very flexible memory model, natively supporting both Array-of-Structs (AoS) and Struct-of-Arrays (SoA) memory layouts (which
pasture
calls 'interleaved' and 'columnar') - Support for reading and writing various point cloud formats with the
pasture-io
crate (such asLAS
,LAZ
,3D Tiles
, as well as ASCII files) - A growing set of algorithms with the
pasture-algorithms
crate
To this end, pasture
chooses flexibility over simplicity. If you are looking for something small and simple, for example to work with LAS files, try a crate like las
. If you are planning to implement high-performance tools and services that will work with very large point cloud data, pasture
is what you are looking for!
Usage
Add this to your Cargo.toml
:
[dependencies]
pasture-core = "0.4.0"
# You probably also want I/O support
pasture-io = "0.4.0"
Here is an example on how to load a pointcloud from an LAS file and do something with it:
use anyhow::{bail, Context, Result};
use pasture_core::{
containers::{BorrowedBuffer, VectorBuffer},
layout::attributes::POSITION_3D,
nalgebra::Vector3,
};
use pasture_io::base::{read_all};
fn main() -> Result<()> {
// Reading a point cloud file is as simple as calling `read_all`
let points = read_all::<VectorBuffer, _>("pointcloud.las").context("Failed to read points")?;
if points.point_layout().has_attribute(&POSITION_3D) {
for position in points
.view_attribute::<Vector3<f64>>(&POSITION_3D)
.into_iter()
.take(10)
{
println!("({};{};{})", position.x, position.y, position.z);
}
} else {
bail!("Point cloud files has no positions!");
}
Ok(())
}
For more examples, check out the pasture_core
examples and the pasture_io
examples.
Migration from versions < 0.4
With version 0.4
, the buffer API of pasture-core
was rewritten. If you are migrating from an earlier version, here are some guidelines for migration. Also check out the documentation of the containers
module.
New buffer types
The main buffer types were renamed:
InterleavedVecPointStorage
is nowVectorBuffer
PerAttributeVecPointStorage
is nowHashMapBuffer
The trait structure is also different:
PointBuffer
andPointBufferWriteable
are replaced byBorrowedBuffer
,BorrowedMutBuffer
, andOwningBuffer
, which define the ownership model of the buffer memoryInterleavedPointBuffer
andInterleavedPointBufferMut
are nowInterleavedBuffer
andInterleavedBufferMut
PerAttributePointBuffer
andPerAttributePointBufferMut
are nowColumnarBuffer
andColumnarBufferMut
. In general, the termPerAttribute
is replaced by the more common termColumnar
There are no more extension traits (e.g. PointBufferExt
). To get/set strongly typed point data, you now use views which can be obtained through the BorrowedBuffer
and BorrowedBufferMut
traits:
let view = buffer.view_attribute::<Vector3<f64>>(&POSITION_3D);
Views support strongly typed access to the data and are convertible to iterators.
New interface for readers and writers
The PointReader
and PointWriter
traits are no longer object safe. Instead, they have read
and read_into
methods that are strongly typed over the buffer type for improved efficiency. There is a GenericPointReader
type, which uses static dispatch and encapsulates readers for LAS, LAZ, and 3D Tiles.
Development
pasture
is in the early stages of development and bugs may occur.
License
pasture
is distributed under the terms of the Apache License (Version 2.0). See LICENSE for details.
Dependencies
~1.5MB
~39K SLoC