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  1. Labelme is a graphical image annotation tool inspired by http://labelme.csail.mit.edu. It is written in Python and uses Qt for its graphical interface. VOC dataset example of instance segmentation. Other examples (semantic segmentation, bbox detection, and classification). Various primitives (polygon, rectangle, circle, line, and point). Features.

  2. Welcome to LabelMe, the open annotation tool. The goal of LabelMe is to provide an online annotation tool to build image databases for computer vision research. You can contribute to the database by visiting the annotation tool. Label objects in the images. Edit your annotations.

  3. pypi.org › project › labelmelabelme · PyPI

    May 9, 2016 · Labelme is a graphical image annotation tool inspired by http://labelme.csail.mit.edu. It is written in Python and uses Qt for its graphical interface. VOC dataset example of instance segmentation. Other examples (semantic segmentation, bbox detection, and classification). Various primitives (polygon, rectangle, circle, line, and point).

  4. www.labelme.ioLabelme

    Build your own data and AI. Get images annotated fast with offline, flexible, and AI-powered annotation tools that runs via a few commands.

  5. Use LabelMe, the open annotation tool, to label images online and share them with the research community.

  6. The goal of LabelMe is to provide an online annotation tool to build a large database of annotated images by collecting contributions from many people. You can contribute to the database by visiting the annotation tool.

  7. LabelMe is a WEB-based image annotation tool that allows researchers to label images and share the annotations with the world. LabelMe allows: Creation of user accounts: You will be able to create image databases for annotation. Organization of images into collections: You can organize the images into collections.