ch-sa/labelCloud
A lightweight tool for labeling 3D bounding boxes in point clouds.
This tool helps engineers and researchers accurately label 3D objects within point cloud data. You input raw point cloud scans (like from LiDAR or depth sensors), then interactively draw and adjust 3D bounding boxes around objects of interest. The output is a structured file containing the precise location, dimensions, and orientation of each labeled object, suitable for training machine learning models or spatial analysis.
770 stars. Available on PyPI.
Use this if you need to manually outline objects in 3D point clouds with high precision for tasks like autonomous driving datasets, robotics, or augmented reality.
Not ideal if you're dealing with standard 2D images or videos, or if your labeling task primarily involves semantic segmentation of individual points rather than entire objects.
Stars
770
Forks
134
Language
Python
License
GPL-3.0
Category
Last pushed
Nov 09, 2025
Commits (30d)
0
Dependencies
5
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