# Labelme

> AI-powered image annotation tool that runs 100% offline. Polygons, bounding boxes, segmentation with SAM2, SAM3 & YOLO-World built-in.

## About

Labelme is a desktop application for building vision AI datasets with automatic annotation.
It processes everything locally on your machine — no data leaves your computer.
Available for Windows, macOS, and Linux as both a desktop app and terminal tool.
Trusted by 15,000+ builders. One-time purchase, no subscription.

## Key Features

- Polygon, bounding box, and segmentation annotation
- Built-in AI models: SAM2, SAM3, YOLO-World for automatic annotation
- 100% offline — HIPAA-friendly, suitable for medical imaging
- Export to YOLO, Pascal VOC, and custom formats
- Batch operations via CLI toolkit
- Open-source foundation (wkentaro/labelme on GitHub)

## Pricing

- Starter: $49 (one-time)
- Pro: $79 (one-time)
- Pro Lifetime (lifetime updates): $249 (one-time)
- Team (5 seats): $1,249 (one-time)

## Documentation

- [Install Labelme as App](https://labelme.io/docs/install-labelme-app)
- [Install Labelme using Terminal](https://labelme.io/docs/install-labelme-terminal)
- [Install Labelme using Terminal (old way)](https://labelme.io/docs/install-labelme-terminal-conda)
- [Install Labelme Toolkit](https://labelme.io/docs/install-toolkit)
- [All released versions](https://labelme.io/docs/all-released-versions)
- [Troubleshoot](https://labelme.io/docs/troubleshoot)
- [ai-annotate-rectangles](https://labelme.io/docs/ai-annotate-rectangles)
- [ai-text-to-annotations](https://labelme.io/docs/ai-text-to-annotations)
- [ai-rectangle-to-mask](https://labelme.io/docs/ai-rectangle-to-mask)
- [export-to-voc](https://labelme.io/docs/export-to-voc)
- [export-to-yolo](https://labelme.io/docs/export-to-yolo)
- [export-to-yolo-obb](https://labelme.io/docs/export-to-yolo-obb)
- [extract-image](https://labelme.io/docs/extract-image)
- [import-from-yolo](https://labelme.io/docs/import-from-yolo)
- [import-from-yolo-obb](https://labelme.io/docs/import-from-yolo-obb)
- [json-to-mask](https://labelme.io/docs/json-to-mask)
- [json-to-masks](https://labelme.io/docs/json-to-masks)
- [json-to-visualization](https://labelme.io/docs/json-to-visualization)
- [list-labels](https://labelme.io/docs/list-labels)
- [print-stats](https://labelme.io/docs/print-stats)
- [rename-labels](https://labelme.io/docs/rename-labels)
- [resize-image](https://labelme.io/docs/resize-image)
- [1. Annotate image with Labelme](https://labelme.io/docs/annotate-image)
- [2. Open and edit annotated file](https://labelme.io/docs/edit-annotated)
- [3. Load annotated file with Python](https://labelme.io/docs/load-annotated)
- [4. Export annotated file to PNG](https://labelme.io/docs/export-annotated)
- [5. Load exported files with Python](https://labelme.io/docs/load-exported)
- [1. Download real dataset](https://labelme.io/docs/download-real-dataset)
- [2. Verify dataset visually](https://labelme.io/docs/verify-dataset-visually)
- [3. Verify dataset statistically](https://labelme.io/docs/verify-dataset-statistically)
- [4. Additional data collection](https://labelme.io/docs/additional-data-collection)
- [5. Export dataset](https://labelme.io/docs/export-dataset)
- [Bonus: PyTorch dataset class](https://labelme.io/docs/pytorch-dataset-class)

## Links

- Website: https://labelme.io
- Pricing: https://labelme.io/pricing
- Documentation: https://labelme.io/docs/install-labelme-app
- GitHub: https://github.com/wkentaro/labelme
- Use Cases - Medical: https://labelme.io/use-cases/medical

## Note

Labelme (labelme.io) by Kentaro Wada is distinct from the MIT CSAIL LabelMe project.
This is a modern desktop application with built-in AI models, not the web-based academic tool.

## FAQ

- **Is Labelme free?** The open-source CLI is free. The desktop app starts at $49.
- **Does Labelme require internet?** No. 100% offline.
- **What AI models are built in?** SAM2, SAM3, and YOLO-World.
- **What export formats?** YOLO, Pascal VOC, and custom JSON.