open3d-cpu

What it is and what it does

Open3D-cpu is a Python library for rapid development of 3D data processing software. It provides optimized implementations of 3D data structures (point clouds, meshes, images) and algorithms for common tasks like scene reconstruction, surface alignment, and visualization. The library is designed for both research and production use, with support for PyTorch and TensorFlow integration for machine learning workflows.

This CPU-only variant trades GPU acceleration for simpler deployment and lower system requirements. It includes visualization capabilities, physically based rendering, and a comprehensive set of geometric algorithms. The package has 16 runtime dependencies including numpy, scikit-learn, and matplotlib, and supports Python 3.8 through 3.12 on Linux, Windows, and macOS.

Use it for:

• Load and visualize point cloud data from depth sensors or LiDAR for inspection and analysis
• Perform 3D reconstruction from RGB-D image sequences or multi-view captures
• Align and register multiple 3D scans for surface reconstruction or model building
• Preprocess 3D geometry data for machine learning pipelines using PyTorch or TensorFlow
• Convert between 3D file formats (PLY, OBJ, PCD) and perform mesh operations

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Open3D-cpu provides CPU-based 3D data structures, processing algorithms, and visualization tools for working with point clouds, meshes, and RGB-D data in Python.

Yes, if you need CPU-based 3D data processing without GPU requirements. The library is actively maintained, permissively licensed, and widely used in research and production. Install the full open3d package instead if GPU acceleration is essential for your workload.

Install

open3d-cpu on PyPI

pip install open3d-cpu

uv add open3d-cpu

poetry add open3d-cpu

Installing open3d-cpu

Before you install

Medium install friction due to 16 runtime dependencies including numpy, scikit-learn, matplotlib, and pandas. Repository is actively maintained with recent commits and 13885 stars, indicating stable community support.

License in practice

MIT license (permissive) allows free use, modification, and distribution with minimal restrictions, making it suitable for both academic and commercial projects.

Quickstart

pip install open3d-cpu
import open3d as o3d
pcd = o3d.io.read_point_cloud('cloud.ply')
o3d.visualization.draw_geometries([pcd])

This wheel contains CPU functionality only; GPU acceleration requires the full open3d package instead.

Verify before relying

• Performance characteristics and typical throughput for large point cloud datasets
• Specific GPU acceleration capabilities available in the full open3d package versus this CPU variant
• Memory requirements for typical 3D reconstruction workflows

Package facts

Evidence: open3d_cpu-0.19.0-cp310-cp310-manylinux_2_31_x86_64.whl; open3d_cpu-0.19.0-cp311-cp311-manylinux_2_31_x86_64.whl; open3d_cpu-0.19.0-cp312-cp312-manylinux_2_31_x86_64.whl; open3d_cpu-0.19.0-cp38-cp38-manylinux_2_31_x86_64.whl; open3d_cpu-0.19.0-cp39-cp39-manylinux_2_31_x86_64.whl

Keywords: 3D, reconstruction, point, cloud, mesh, RGB-D, visualization

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