strawlab/python-pcl
Python bindings to the pointcloud library (pcl) observed · 2026-08-28
Health v2 · maintenance only
10/100
- Activity 0
- Release rhythm 8
- Longevity 100
Flags: archived no_license no_readme
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 5222
- days_rel: n/a
- days_push: 977
- n_releases_24m: 0
Adoption not part of the score
2056 stars · 689 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
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
library · maturity maintenance
computer-vision image-processing sdk computer-vision robotics machine-learning python cpp point-cloud pcl 3d cython lidar bindings linux
1 source
- registry_pypi: https://pypi.org/pypi/python-pcl/json · fetched 2026-08-29 · b6e6c0a32856
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| strawlab/python-pcl | main | 10 |
For agents
markdown · JSON · MCP: product_card(name="strawlab/python-pcl")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem