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LabelU

No phone app

5.8No. 16 of 20
in AI Data Labeling Tools
  • Recognised40% of the score15
  • Phone app26% of the score0
  • Documented20% of the score100
  • Free plan14% of the score30
Free plan
No
Runs on
api, Mac, self-hosted, Web, Windows
Visit site Alternatives

Summary

LabelU is an open-source platform for annotating image, video, and audio data, intended for work supporting complex data analysis and model training. Image tools cover 2D bounding boxes, semantic segmentation, polylines, and keypoints. Video and audio workflows support segmentation, classification, and information extraction. Users can bring in pre-annotated data for refinement, or use AI model services to detect and segment image objects, including batch jobs with live progress. Reference model servers include Florence-2, GroundingDINO with SAM ViT-B, and SAM 3. The platform imports annotation data from S3-compatible storage such as AWS S3 and MinIO, and exports JSON, COCO, and MASK formats. Local deployment uses Miniconda, Python 3.11, pip, and a local server at http://localhost:8000/. SQLite is included, with MySQL installation and migration also supported. The model server provides HTTP POST / and GET /health endpoints. Florence-2 and GroundingDINO with SAM ViT-B each require about 4GB VRAM; SAM 3 requires about 8GB and CUDA 12.6 or later. The project is licensed under Apache 2.0.

Who it is for

LabelU suits teams annotating multiple data types for analysis or model training, especially those wanting self-hosted deployment and model-assisted labeling. Its listed local setup and model hardware requirements are relevant for teams preparing their own environment.

What is good

  • Supports image, video, and audio annotation
  • Can refine imported pre-annotations
  • Imports from S3-compatible storage
  • Exports JSON, COCO, and MASK
  • Apache 2.0 licensed

What to know first

  • Local setup requires Miniconda, Python 3.11, and pip
  • SAM 3 requires about 8GB VRAM and CUDA 12.6+
  • Deployment is self-hosted

Verdict

LabelU combines multimodal annotation, import and export options, and model-assisted image labeling in an open-source package. Teams should account for the local deployment steps and hardware requirements of the reference models.

Compared on AI data labeling tools

Supported modalities
image, video, audiogithub.com
Model-assisted labeling
Yesgithub.com
Human review workflows
Yesgithub.com
Custom ontologies
Yesgithub.com
Deployment options
self hostedgithub.com
API access
Yesgithub.com

Facts

Purpose
LabelU is an open-source multimodal data annotation platform for image, video, and audio data.github.com · 1 Oct 2026
Image annotation
Image tools include 2D bounding boxes, semantic segmentation, polylines, and keypoints.github.com · 1 Oct 2026
Video annotation
Video capabilities include video segmentation, video classification, and video information extraction.github.com · 1 Oct 2026
Audio annotation
Audio tools support audio segmentation, audio classification, and audio information extraction.github.com · 1 Oct 2026
AI assisted labeling
Users can load pre-annotated data with one click and refine or adjust it.github.com · 1 Oct 2026
AI auto-annotation
AI model services can automatically detect and segment image objects, including batch annotation with real-time progress tracking.github.com · 1 Oct 2026
Reference models
Reference model servers include Florence-2, GroundingDINO plus SAM ViT-B, and SAM 3.github.com · 1 Oct 2026
Object storage
LabelU can import annotation data from S3-compatible storage such as AWS S3 and MinIO.github.com · 1 Oct 2026
Export formats
The platform supports exporting data in JSON, COCO, and MASK formats.github.com · 1 Oct 2026
Deployment
Local deployment uses Miniconda, Python 3.11, pip installation, and a local server at http://localhost:8000/.github.com · 1 Oct 2026
Database support
LabelU includes built-in SQLite and supports MySQL installation and migration.github.com · 1 Oct 2026
API
The model server exposes a unified HTTP API with POST / and GET /health endpoints.github.com · 1 Oct 2026
Model requirements
Florence-2 requires about 4GB VRAM, GroundingDINO plus SAM ViT-B about 4GB, and SAM 3 about 8GB with CUDA 12.6+.github.com · 1 Oct 2026
License
The project is released under the Apache 2.0 license.github.com · 1 Oct 2026
Support
The project README invites users to join the official OpenDataLab WeChat group.github.com · 1 Oct 2026
Image tools
Image annotations include 2D bounding boxes, semantic segmentation, polylines, and keypoints.github.com · 2 Oct 2026
Video tools
Video annotation supports segmentation, classification, and information extraction.github.com · 2 Oct 2026
Audio tools
Audio annotation supports segmentation, classification, and information extraction.github.com · 2 Oct 2026
AI assistance
Users can load pre-annotated data in one click and refine it in the platform.github.com · 2 Oct 2026
Storage integration
LabelU can import files from S3-compatible storage, including AWS S3 and MinIO.github.com · 2 Oct 2026
Intended users
The README describes the platform as suited to annotation work supporting complex data analysis and model training.github.com · 2 Oct 2026
Support channel
The project README invites users to join the OpenDataLab official WeChat group.github.com · 2 Oct 2026

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