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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.
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.
ExifTool is a free and open-source software program for reading, writing, and manipulating image, audio, video, and PDF metadata.As such, ExifTool classes as a tag editor.It is platform independent, available as both a Perl library (Image::ExifTool) and a command-line application.
Many applications on Mac OS X use either the Core Image or QuickTime APIs for image support. This enables reading and writing to a variety of formats, including JPEG , JPEG 2000 , Apple Icon Image format , TIFF , PNG , PDF , BMP and more.
A code quality analysis tool that uses static code analysis. RIPS: 2020-02-17 (3.4) No; proprietary — — Java — — — PHP A static code analysis solution with many integration options for the automated detection of complex security vulnerabilities. SAST Online: 2022-03-07 (1.1.0) No; proprietary — — Java — — — Kotlin, APK
Concerned by the high cost of commercial screen readers, in April 2006, Michael Curran began writing a Python-based screen reader with Microsoft SAPI as its speech engine. It provided support for Microsoft Windows 2000 onwards, and provided screen reading capabilities such as basic support for some third-party software and web browsing.
The advantages of automatic image annotation versus content-based image retrieval (CBIR) are that queries can be more naturally specified by the user. [2] 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. However, certain image features ...
A 2023–2024 screen reader user survey by WebAIM, a web accessibility company, found JAWS to be the most popular desktop/laptop screen reader worldwide for primary usage (at 40.5%), while 60.5% of participants listed it as a commonly used screen reader, ranking it second in this measure behind NVDA.