Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor

Health v2 · maintenance only

Adoption not part of the score

1970 stars · 447 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A web-based labeling tool for creating AI training datasets from bitmap images (.jpg/.png) and point clouds (.pcd). Built as a Meteor app with React, Paper.js, and three.js, originally developed for autonomous driving research.

Use cases

• annotate images for semantic segmentation training data
• label 3D point clouds for autonomous driving datasets
• create manual annotations for computer vision models
• self-host a web-based image labeling tool
• label PCD files with RGB point cloud support
• generate 2D and 3D AI training datasets

When to choose

• you need to label both 2D images and 3D point clouds in one tool
• you work on autonomous driving or LiDAR dataset annotation
• you want a self-hosted, MIT-licensed labeling solution deployable via Docker
• you need to handle large point clouds (up to ~1M points)

When to avoid

• you need collaborative or actively developed labeling with modern features
• you only need simple bounding-box image annotation
• you cannot run Meteor/Docker infrastructure
• you need video or text annotation support

Facets

application · maturity maintenance

image-processing computer-vision machine-learning gui machine-learning computer-vision autonomous-vehicles image-processing self-hosted cross-platform labeling-tool semantic-segmentation point-cloud annotation meteor react threejs pcd training-data web-server docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor")