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Computer Vision Annotation Tool (CVAT) is an open source, web-based image and video annotation tool used for labeling data for computer vision algorithms. Originally developed by Intel , CVAT is designed for use by a professional data annotation team, with a user interface optimized for computer vision annotation tasks.
The LabelMe annotation tool provides a means for users to contribute to the project. The tool can be accessed anonymously or by logging into a free account. To access the tool, users must have a compatible web browser with JavaScript support. When the tool is loaded, it chooses a random image from the LabelMe dataset and displays it on the screen.
VoTT (Visual Object Tagging Tool) is a free and open source Electron app for image annotation and labeling developed by Microsoft. [1] The software is written in the TypeScript programming language and used for building end-to-end object detection models from image and videos assets for computer vision algorithms.
The first version was released around the year 2000 under the name EAT, Eudico Annotation Tool. It was renamed to ELAN in 2002. Since then, two to three new versions are released each year. It is developed in the programming language Java with interfaces to platform native media frameworks developed in C, C++, and Objective-C.
The advantages of automatic image annotation versus content-based image retrieval (CBIR) are that queries can be more naturally specified by the user. [1] At present, Content-Based Image Retrieval (CBIR) generally requires users to search by image concepts such as color and texture or by finding example queries.
Perusall is a social web annotation tool intended for use by students at schools and universities. [1] It allows users to annotate the margins of a text in a virtual group setting that is similar to social media—with upvoting, emojis, chat functionality, and notification. It also includes automatic AI grading. [2]
Manual image annotation is the process of manually defining regions in an image and creating a textual description of those regions. Such annotations can for instance be used to train machine learning algorithms for computer vision applications. This is a list of computer software which can be used for manual annotation of images.
Automatic segmentation ITK-SNAP provides automatic functionality segmentation using the level-set method. This makes it possible to segment structures that appear somewhat homogeneous in medical images using very little human interaction. For example, the lateral ventricles in MRI can be segmented reliably, as can some types of tumors in CT and ...