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LabelMe

Offline image annotation tool with polygons, masks, and AI-assisted labeling

Repository activity
  • Stars16k
  • Forks3.7k
  • Open Issues130
License

GPL-3.0

Languages
  • Python
  • Makefile
LabelMe screenshot

About LabelMe

LabelMe is a graphical image annotation tool for building labeled image datasets from images and video. It helps with polygon, rectangle, circle, line, and point annotations, plus classification flags and cleaning. The free pip-installed Python and Qt tool works 100% offline, with a paid standalone build that needs no Python or Qt.

It exports VOC-format data for semantic segmentation and instance segmentation, and COCO-format data for instance segmentation. AI-assisted annotation includes point-to-polygon and point-to-mask labeling with SAM and EfficientSAM, plus text-to-annotation with YOLO-World and SAM3. GUI options include predefined labels and flags, auto-saving, and label validation.

LabelMe is written in Python with a Qt interface and is available in 20 languages. A paid standalone build on labelme.io installs without Python or Qt, and because everything runs locally and offline, it suits air-gapped or privacy-sensitive workflows where data must stay on the machine.

Key features

  • Polygon, rectangle, circle, line, and point annotation
  • Image flag annotation for classification and cleaning
  • Video annotation
  • VOC and COCO export for segmentation datasets
  • AI-assisted labeling with SAM, EfficientSAM, YOLO-World, and SAM3

Details

First released
2016
Platforms
Windows · macOS · Linux
Deployment
offline-first
Language
Python · Qt
Localization
20 languages
Annotation types
Polygon · box · circle · line · point