Label Studio From $99/mo · Free plan 8.9 Visit LabelU
github.com
What it is
LabelU is an open-source platform for annotating image, video, and audio data, with tools for both manual work and model-assisted labeling. Image annotations include 2D bounding boxes, semantic segmentation, polylines, and keypoints; video and audio support segmentation, classification, and information extraction. Users can load pre-annotated data and refine it, or use AI services to detect and segment image objects, including batch work with progress tracking. LabelU imports annotation data from S3-compatible storage such as AWS S3 and MinIO, and exports JSON, COCO, and MASK formats. Its model server exposes a unified HTTP API with POST / and GET /health endpoints. Local deployment uses Miniconda, Python 3.11, pip, and a server at http://localhost:8000/. SQLite is included, with MySQL installation and migration also supported. Reference models have stated hardware requirements: Florence-2 and GroundingDINO plus SAM ViT-B each need about 4GB VRAM; SAM 3 needs about 8GB and CUDA 12.6 or later. LabelU is free and released under Apache 2.0.
Spec sheet
- Purpose
- LabelU is an open-source multimodal data annotation platform for image, video, and audio tasks.Read 2 Oct 2026 · github.com
- Intended users
- The README describes the platform as suited to annotation work supporting complex data analysis and model training.Read 2 Oct 2026 · github.com
- Deployment
- The project documents local installation with Python 3.11 or later and running a local server at localhost:8000.Read 2 Oct 2026 · github.com
- API
- The model server exposes a unified HTTP API with POST / and GET /health endpoints.Read 1 Oct 2026 · github.com
- Support
- The project README invites users to join the official OpenDataLab WeChat group.Read 1 Oct 2026 · github.com
- License
- The project is released under the Apache 2.0 license.Read 2 Oct 2026 · github.com
- AI assistance
- Users can load pre-annotated data in one click and refine it in the platform.Read 2 Oct 2026 · github.com
- AI assisted labeling
- Users can load pre-annotated data with one click and refine or adjust it.Read 1 Oct 2026 · github.com
- AI auto-annotation
- Image auto-annotation can detect and segment objects, with batch task annotation and real-time progress tracking.Read 2 Oct 2026 · github.com
- Audio annotation
- Audio tools support audio segmentation, audio classification, and audio information extraction.Read 1 Oct 2026 · github.com
- Audio tools
- Audio annotation supports segmentation, classification, and information extraction.Read 2 Oct 2026 · github.com
- Database support
- SQLite is the documented default database, and MySQL can be installed as an optional dependency.Read 2 Oct 2026 · github.com
- Export formats
- The README lists JSON, COCO, and MASK among supported export formats.Read 2 Oct 2026 · github.com
- Image annotation
- Image tools include 2D bounding boxes, semantic segmentation, polylines, and keypoints.Read 1 Oct 2026 · github.com
- Image tools
- Image annotations include 2D bounding boxes, semantic segmentation, polylines, and keypoints.Read 2 Oct 2026 · github.com
- Model requirements
- Florence-2 requires about 4GB VRAM, GroundingDINO plus SAM ViT-B about 4GB, and SAM 3 about 8GB with CUDA 12.6+.Read 1 Oct 2026 · github.com
- Object storage
- LabelU can import annotation data from S3-compatible storage such as AWS S3 and MinIO.Read 1 Oct 2026 · github.com
- Reference models
- The project lists Florence-2, GroundingDINO with SAM ViT-B, and SAM 3 reference model servers, with GPU memory requirements stated for each.Read 2 Oct 2026 · github.com
- Storage integration
- LabelU can import files from S3-compatible storage, including AWS S3 and MinIO.Read 2 Oct 2026 · github.com
- Support channel
- The project README invites users to join the OpenDataLab official WeChat group.Read 2 Oct 2026 · github.com
- Video annotation
- Video capabilities include video segmentation, video classification, and video information extraction.Read 1 Oct 2026 · github.com
- Video tools
- Video annotation supports segmentation, classification, and information extraction.Read 2 Oct 2026 · github.com
Strong points and limits
Strong points
- Supports image, video, and audio annotation.
- Can refine pre-annotated data in the platform.
- Imports annotation data from S3-compatible storage.
- Exports JSON, COCO, and MASK formats.
- Free and licensed under Apache 2.0.
Limits
- Local setup specifies Miniconda and Python 3.11.
- SAM 3 requires about 8GB VRAM and CUDA 12.6+.
- Reference models have stated VRAM requirements.
Who it suits
LabelU suits teams preparing image, video, or audio annotations for complex data analysis and model training. Its self-hosted deployment, review of pre-annotations, and API may suit teams integrating annotation into their workflows.
Verdict
LabelU combines multimodal annotation with model-assisted image labeling, storage imports, and several export formats. It is free, but local setup and model hardware requirements are worth checking before deployment.
Where Specifiction places it
- AI Data Labeling Tools#16 of 227.4
