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

Web labeling tool for bitmap images and point clouds

Repository: https://github.com/Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor
Canonical: https://ross.abutalabs.com/products/semantic-segmentation-editor
Language: JavaScript
License: MIT
License Family: permissive
Topics: labeling-tool, machine-learning, manual-annotations, semantic-segmentation, pcd, image-labeling, image-labeling-tool, pointcloud
Last push: 2024-09-18T15:04:01+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2961, "days_push": 714, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1970, forks 447 (observed 2026-08-28T04:06:00.812985+00:00)

## What it is
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
- artifact type: application
- maturity: maintenance
- function: image-processing, computer-vision, machine-learning, gui
- domain: machine-learning, computer-vision, autonomous-vehicles, image-processing
- platform: self-hosted, cross-platform
- tags: labeling-tool, semantic-segmentation, point-cloud, annotation, meteor, react, threejs, pcd, training-data, web-server, docker

## Member repositories
- Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:00.812985+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 2026-08-30T03:05:07.024688+00:00, confidence not recorded.
  - readme: https://github.com/Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor (fetched 2026-08-28T04:06:00.812985+00:00, sha 68117b156157)
- Data as of 2026-08-30T08:39:29.467469+00:00.