LabelU

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About

LabelU is an open-source platform for annotating image, video, and audio data, with self-hosted deployment and model-assisted labeling. Image work includes 2D bounding boxes, semantic segmentation, polylines, and keypoints; video and audio tasks include segmentation, classification, and information extraction. Users can load pre-annotated data to refine it, or run AI model services for image-object detection and segmentation, including batch annotation with progress tracking. LabelU imports annotation data from S3-compatible storage such as AWS S3 and MinIO, and exports JSON, COCO, and MASK formats. Local setup uses Miniconda, Python 3.11, pip, and a server at http://localhost:8000/. It includes SQLite and supports MySQL installation and migration. The model server exposes HTTP POST / and GET /health endpoints. Reference models have stated hardware requirements: Florence-2 and GroundingDINO with SAM ViT-B each need about 4GB VRAM; SAM 3 needs about 8GB and CUDA 12.6 or later. The project is released under Apache 2.0.

Who it is for

LabelU suits teams annotating multimodal datasets for complex analysis or model training, especially those that want to self-host and retain human review of AI-assisted labels. Its listed setup and reference-model hardware requirements matter when planning deployment.

What is good

Supports image, video, and audio annotation
AI-assisted detection and segmentation with batch progress tracking
Imports from S3-compatible storage
Exports JSON, COCO, and MASK
Apache 2.0 licensed

What to know first

Local setup requires Miniconda and Python 3.11
SAM 3 requires about 8GB VRAM and CUDA 12.6+
No hosted deployment option is listed

Verdict

LabelU covers several annotation modalities and offers both AI assistance and formats suited to downstream work. Its self-hosted setup and model hardware requirements make deployment planning part of the evaluation.

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