# opendatalab/labelU

Open-source multimodal data annotation platform with AI auto-annotation support.

Repository: https://github.com/opendatalab/labelU
Canonical: https://ross.abutalabs.com/products/labelu
Homepage: https://opendatalab.github.io/labelU/
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2026-07-28T12:11:08+00:00

## Health v2 (maintenance only)
Score: 96/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 94, release rhythm 95, longevity 100
- inputs: {"age_days": 1414, "days_push": 36, "days_rel": 36, "gap_med": 0, "n_releases_24m": 50}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1665, forks 183 (observed 2026-08-28T04:05:19.022790+00:00)

## What it is
LabelU is an open-source multimodal data annotation platform supporting images, video, and audio with tools like bounding boxes, segmentation, and keypoints. It integrates AI model services (Florence-2, GroundingDINO+SAM, SAM 3) for automatic pre-annotation that humans can refine.

## Use cases
- annotate images with bounding boxes for object detection training
- label video segments for action recognition datasets
- create audio segmentation and classification annotations
- run AI auto-annotation on image datasets then manually refine
- prepare labeled multimodal datasets for model training

## When to choose
- you need a self-hosted annotation tool covering image, video, and audio in one platform
- you want AI-assisted pre-labeling to speed up annotation
- your team needs flexible 2D annotation tools like polylines and keypoints

## When to avoid
- you only need text or NLP annotation, which is not its focus
- you want a fully managed cloud annotation service without self-hosting
- you lack GPU resources for the AI auto-annotation features

## Facets
- artifact type: application
- maturity: active
- function: image-processing, audio-processing, video-processing, machine-learning, data-science
- domain: machine-learning, computer-vision, data-science, artificial-intelligence
- platform: python, self-hosted
- tags: data-annotation, labeling, multimodal, auto-annotation, segmentation, bounding-boxes, web-server, docker

## Member repositories
- opendatalab/labelU (main) score 96

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:19.022790+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 2026-08-30T03:44:26.703458+00:00, confidence not recorded.
  - readme: https://github.com/opendatalab/labelU (fetched 2026-08-28T04:05:19.022790+00:00, sha 4343bc0e8ce8)
  - homepage: https://opendatalab.github.io/labelU/ (fetched 2026-08-29T11:16:31.380070+00:00, sha 44136fa355b3)
  - registry_pypi: https://pypi.org/pypi/labelu/json (fetched 2026-08-29T11:16:31.386416+00:00, sha ec716e100e3f)
- Data as of 2026-08-30T08:39:29.467469+00:00.