pointpca2 0.3.0

A Rust-based Python library for extracting pointpca2 features from Point Clouds.

PointPCA2 - Python Lib

A seamless Python integration to the Rust implementation of PointPCA2

This project aims to integrate Python to pointpca2-rs, enabling the use of Python's comprehensive data science tools combined to the performance provided by the Rust implementation of PointPCA2.

Setup

From PyPI

pip install pointpca2
# or
python -m pip install pointpca2

From source

• Prerequisites

  • rustc == 1.77.2
  • anaconda3 >= 23.7.4

• Build

# Clone this repository
https://github.com/akaTsunemori/pointpca2-pylib.git

# cd into the project folder
cd pointpca2-pylib

# Setup and activate the conda environment
conda env create -f environment.yml
conda activate pointpca2-pylib

# Compile the project into a python module using maturin
maturin develop -r

Usage

import open3d as o3d
import numpy as np
import pointpca2

# Load both reference and test PCs
PC_REF_PATH = "examples/pcs/amphoriskos_vox10.ply"
pc_ref = o3d.io.read_point_cloud(PC_REF_PATH)
points_a, colors_a = np.asarray(pc_ref.points), np.asarray(pc_ref.colors)
PC_TEST_PATH = "examples/pcs/tmc13_amphoriskos_vox10_dec_geom01_text01_octree-predlift.ply"
pc_test = o3d.io.read_point_cloud(PC_TEST_PATH)
points_b, colors_b = np.asarray(pc_test.points), np.asarray(pc_test.colors)

# Compute the features (predictors) through the pointpca2 function
predictors = pointpca2.compute_pointpca2(
    points_a, colors_a, points_b, colors_b, search_size=81, verbose=True
)
print(*predictors)

Contributing

Feel free to open any kind of issues and contributions related to this Python package. Issues related to the Rust implementation should be open on the pointpca2-rs repository.

Acknowledgments

• pointpca2-rs - An implementation of PointPCA2 in Rust

License

MIT License

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GitHub @akaTsunemori