opendatalab/labelU

Health v2 · maintenance only

Adoption not part of the score

1665 stars · 183 forks observed · 2026-08-28

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

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

application · maturity active

image-processing audio-processing video-processing machine-learning data-science machine-learning computer-vision data-science artificial-intelligence python self-hosted data-annotation labeling multimodal auto-annotation segmentation bounding-boxes web-server docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="opendatalab/labelU")