pcd-py 0.1.1

`pcd-py` is a high-speed Python library for reading and writing PCD (Point Cloud Data) files, powered by a core implementation in Rust (`rs-pcd`). It integrates seamlessly with **NumPy** for efficient data handling.

pcd-py: High-Performance PCD I/O for Python

pcd-py is a high-speed Python library for reading and writing PCD (Point Cloud Data) files, powered by a core implementation in Rust (rs-pcd). It integrates seamlessly with NumPy for efficient data handling.

Features

• Fast I/O: Leverages Rust for multi-threaded binary and compressed PCD handling.
• NumPy Integration: Reads/writes PCD fields directly as NumPy arrays.
• Full Format Support: Supports ASCII, Binary, and Binary Compressed formats.
• Metadata Access: Easy access to PCD header information (version, width, height, viewpoint).

Installation

# Requires maturin to build from source
pip install maturin numpy
cd pcd-py
maturin develop --release

Quick Start

import pcd_py
import numpy as np

# 1. Read a PCD file
meta, data = pcd_py.read_pcd("example.pcd")

print(f"Points: {meta.points}")
print(f"Fields: {data.keys()}")

x = data["x"]  # numpy array (f32)
intensity = data["intensity"]  # numpy array (f32)

# 2. Read from memory (e.g., from network)
with open("example.pcd", "rb") as f:
    data_bytes = f.read()

meta_buf, data_buf = pcd_py.read_pcd_from_buffer(data_bytes)

# 3. Write a PCD file
new_data = {
    "x": np.array([1.0, 2.0, 3.0], dtype=np.float32),
    "y": np.array([0.0, 0.0, 0.0], dtype=np.float32),
    "z": np.array([5.0, 5.0, 5.0], dtype=np.float32),
    "id": np.array([1, 2, 3], dtype=np.uint32),
}

pcd_py.write_pcd("output.pcd", new_data, format="binary_compressed")

Performance

For a point cloud with 1,000,000 points (XYZIRT schema):

• Read Binary: ~12 ms (Zero-Copy Mmap)
• Write Binary: ~135 ms

[!NOTE] Performance is now equivalent to native Rust, reading 1 million points in under 12ms.

License

Apache-2.0