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Annotate-Lab review

Free#26 of 28 in Image Annotation Software

A focused, free self-hosted annotator with useful exports but no collaboration layer.

6.4/10Editor score
Annotate-Lab6.4 Visit Annotate-Lab

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Annotate-Lab is an open-source image annotation application for developers and small teams that want a minimal, self-hosted workspace. Its React client and Flask server run locally, with annotation performed in a browser. Users configure images, labels and region tools, then create labeled datasets using polygon, bounding-box and other configured regions. The product fits solo practitioners and small groups that prefer control over deployment and project files rather than a hosted service.

Its annotation workflow covers practical dataset management. Regions can be locked, deleted or hidden, while annotation history supports reviewing actions and reverting changes. Progress can be saved during a session, and completed work can be downloaded as annotated images, masks and annotation settings. YOLO-format output is also described, giving computer-vision workflows a direct export option. When enabled in configuration, optional Segment Anything Model support provides automatic bounding-box selection to assist labeling.

Setup is centered on repository installation and local execution, including Docker, so teams must manage their own deployment. The published positioning describes self-hosted use without collaboration or API access, which keeps the scope narrow for individual annotators and small projects. Choose Annotate-Lab when configurable regions, history, local control and straightforward exports matter more than shared workspaces or programmatic connectivity. Teams coordinating annotation across users, or integrating labeling into a broader service through an API, should choose a product designed around those requirements.

Annotate-Lab pros and cons

  • Where it wins
    • Configurable polygon and bounding-box region annotation tools
    • History, revert, masks, settings and YOLO exports support dataset workflows
    • Optional Segment Anything Model can assist bounding-box selection
  • Where it doesn't
    • Self-hosted deployment requires local installation and configuration
    • No collaboration features for team annotation workflows
    • No API access limits automated integrations

Annotate-Lab fact sheet, pricing and score →

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