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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.
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.
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 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.
Output of DenseCap "dense captioning" software, analysing a photograph of a man riding an elephant. Automatic image annotation (also known as automatic image tagging or linguistic indexing) is the process by which a computer system automatically assigns metadata in the form of captioning or keywords to a digital image.
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]
ELAN is computer software, a professional tool to manually and semi-automatically annotate and transcribe audio or video recordings. [2] It has a tier-based data model that supports multi-level, multi-participant annotation of time-based media.
MG-RAST, an open-source web application server, facilitates automatic phylogenetic and functional analysis of metagenomes.It stands as one of the largest repositories for metagenomic data, employing the acronym for Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST).