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Labelme is a graphical tool for polygonal annotation of images, videos, and flags. It supports various formats, primitives, and features for semantic and instance segmentation, classification, and cleaning.
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. Upload your own pictures and explore the public collections.
Use LabelMe, the open annotation tool, to label images online and share them with the research community.
Labelme is a Python package that allows you to draw shapes, labels and masks on images. You can also export your annotations to various formats, such as VOC, COCO and ONNX, and integrate with Segment Anything Model (SAM).
Jul 21, 2019 · Label Me: Directed by Kai Kreuser. With Nikolaus Benda, Renato Schuch, Jogi Kaiser, Georg Paluza. Waseem a refugee crosses paths with well-heeled German Lars via a hookup app. Lars coldly negotiates cash for sex.
- (1.2K)
- Drama
- Kai Kreuser
- 2019-07-21
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.
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What is a LabelMe annotation tool?
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LabelMe is a project created by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) that provides a dataset of digital images with annotations. The dataset is dynamic, free to use, and open to public contribution. The most applicable use of LabelMe is in computer vision research.
