# strawlab/python-pcl

Python bindings to the pointcloud library (pcl)

Repository: https://github.com/strawlab/python-pcl
Canonical: https://ross.abutalabs.com/products/python-pcl
Homepage: http://strawlab.github.com/python-pcl/
Language: Cython
License: NOASSERTION
License Family: other
Archived: true
Last push: 2023-12-30T22:30:45+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 5222, "days_push": 977, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived, no_license, no_readme
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2056, forks 689 (observed 2026-08-28T04:06:09.864869+00:00)

## What it is
Python bindings for the Point Cloud Library (PCL), implemented with Cython. It exposes PCL's 3D point cloud processing algorithms (filtering, segmentation, feature estimation) to Python.

## Use cases
- process lidar point clouds in python
- filter and downsample 3d point clouds
- segment planes or objects from point cloud data
- compute features on 3d point clouds
- wrap pcl algorithms in a python pipeline

## When to choose
- you need PCL's 3D point cloud algorithms from Python
- you work with lidar or depth-camera data
- you want Cython-level performance over the native PCL API

## When to avoid
- you need actively maintained bindings with recent PCL support
- you prefer pure-Python or pip-installable solutions
- you work mainly with meshes rather than point clouds

## Facets
- artifact type: library
- maturity: maintenance
- function: computer-vision, image-processing, sdk
- domain: computer-vision, robotics, machine-learning
- platform: python, cpp
- tags: point-cloud, pcl, 3d, cython, lidar, bindings, linux

## Member repositories
- strawlab/python-pcl (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:09.864869+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:57:15.079503+00:00, confidence not recorded.
  - registry_pypi: https://pypi.org/pypi/python-pcl/json (fetched 2026-08-29T10:37:42.313307+00:00, sha b6e6c0a32856)
- Data as of 2026-08-30T08:39:29.467469+00:00.