:pencil2: Web-based image segmentation tool for object detection, localization, and keypoints
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COCO Annotator is a web-based image annotation tool designed for versatility and efficiently label images to create training data for image localization and object detection. It provides many distinct features including the ability to label an image segment (or part of a segment), track object instances, labeling objects with disconnected visible parts, efficiently storing and export annotations in the well-known COCO format. The annotation process is delivered through an intuitive and customizable interface and provides many tools for creating accurate datasets.
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Checkout the video for a basic guide on installing and using COCO Annotator.
Note: This video is from v0.1.0 and many new features have been added.
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Several annotation tools are currently available, with most applications as a desktop installation. Once installed, users can manually define regions in an image and creating a textual description. Generally, objects can be marked by a bounding box, either directly, through a masking tool, or by marking points to define the containing area. COCO Annotator allows users to annotate images using free-form curves or polygons and provides many additional features were other annotations tool fall short.
For examples and more information check out the wiki.
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If you enjoy the development of coco-annotator or are looking for an enterprise annotation tool, consider checking out DataTorch.
https://datatorch.io · [email protected] · Next generation of coco-annotator
Thanks to all these wonderful libaries/frameworks:
@MISC{cocoannotator,
author = {Justin Brooks},
title = {{COCO Annotator}},
howpublished = "\url{https://github.com/jsbroks/coco-annotator/}",
year = {2019},
}