LabelMe Annotation Tool

LabelMe Annotation Tool

The LabelMe Annotation Tool is an open source image annotation tool developed by MIT for labeling images to generate training data for computer vision algorithms. It allows users to draw polygons and bounding boxes on images to annotate objects.
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LabelMe Annotation Tool: An Open Source Image Annotation Tool

The LabelMe Annotation Tool is an open source image annotation tool developed by MIT for labeling images to generate training data for computer vision algorithms. It allows users to draw polygons and bounding boxes on images to annotate objects.

What is LabelMe Annotation Tool?

The LabelMe Annotation Tool is an powerful open source image annotation tool originally developed at MIT to help researchers and developers easily acquire high quality labeled training data for developing computer vision algorithms. It provides an intuitive web-based graphical interface for anyone to efficiently label objects in images by drawing polygons to outline them or bounding boxes to enclose them.

Some key features and capabilities of LabelMe include:

  • Annotate images by drawing bounding boxes, polygons, lines, and points to mark objects and locations
  • Add textual tags to label objects with descriptive words
  • Flexible organization using projects, datasets, images to enable collaboration
  • Stores all annotations and labels in JSON format for easy exporting
  • Integrates with popular computer vision libraries and frameworks
  • Web-based so it runs on any platform or device with a browser
  • Free and open source tool maintained over decades of vision research

Overall the LabelMe Annotation Tool has proven to be an essential labeling solution to generate quality ground truth visual data at scale to feed the rising demands and progress being made in computer vision systems and deep learning algorithms.

LabelMe Annotation Tool Features

Features

  1. Web-based interface for drawing bounding boxes and polygons on images
  2. Ability to create and manage annotation projects
  3. Tools for labeling objects, scribbles, lines, etc
  4. Support for collaboration - multiple users can work on the same images
  5. Export annotations in multiple formats like JSON, CSV, PASCAL VOC XML
  6. APIs for accessing data programmatically

Pricing

  • Open Source

Pros

Free and open source

Intuitive interface

Active community support

Integrates with popular ML frameworks like TensorFlow, PyTorch, Keras

Can handle large annotation projects with many images and users

Cons

Limited documentation

Not many customization options for interface

No built-in auto-annotation or active learning capabilities

Only supports 2D image annotations

Official Links

Official Website
https://labelme.csail.mit.edu/Release3.0/

The Best LabelMe Annotation Tool Alternatives

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