LabelU

At a glance

• Editor score
  7.0 / 10
• Pricing
  Open source
• Best for
  Open-source image, video, and audio projects
• Paid from
  Free
• Model-assisted labeling
  Yes
• Facts checked
  21 Sep 2026

• Where it wins

  • Supports bounding boxes, segmentation, polylines, keypoints, and more
  • Covers image, video, and audio annotation workflows
  • Offers AI-assisted image labeling and S3-compatible imports

• Where it doesn't

  • AI-assisted auto-annotation is focused on image labeling
  • Exports are limited to JSON, COCO, and MASK formats
  • Browser access depends on local installation or the online demo

Our verdict on LabelU

LabelU is an open-source multimodal data annotation platform from OpenDataLab for teams preparing machine-learning datasets. It supports image annotation with bounding boxes, semantic segmentation, polylines, and keypoints, while video and audio workflows cover segmentation, classification, and information extraction. The browser-based platform is suited to projects that need one annotation environment across several media types, particularly when local deployment and control over dataset handling matter.

Its strongest area is multimodal coverage paired with model-assisted image labeling. Reference model servers can support AI-assisted image auto-annotation, and pre-annotated data can be loaded for refinement. That combination gives teams a path from initial model output to human-edited labels rather than requiring every image to be labeled from scratch. Video and audio annotation broaden the platform beyond image-only tools, although the documented AI auto-annotation capability is for images. Teams choosing LabelU should therefore value annotation breadth first and treat assisted labeling as a focused image feature.

Deployment and data movement are central to LabelU’s fit. LabelU can be installed locally with SQLite or optional MySQL support and accessed through a browser. It imports from S3-compatible storage, including AWS S3 and MinIO, and exports to JSON, COCO, and MASK formats. The product is distributed under Apache 2.0, which suits open-source projects and teams that want a locally hosted workflow. LabelU is a strong pick for multimodal dataset work with self-hosting requirements; teams needing a native desktop application, broader export coverage, or AI assistance across video and audio should consider alternatives.

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LabelU pricing

LabelU fact sheet

LabelU integrations

LabelU lists 2 integrations on its own site.

• AWS S3
• MinIO

Alternatives to LabelU

• ArgillaA free, open-source option for teams labeling text and multimodal AI data.9.4
• PotatoA broad self-hosted labeling platform for multimodal datasets and model-assisted workflows.9.2
• CVATCVAT combines broad annotation tools, AI assistance, collaboration, and open-source deployment.9.1

See all LabelU alternatives →

Featured on iTechGuides

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 7 Oct 2026 · How we research and update