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Desktop open source interactive software system for facilitating the precise annotation of benthic species in orthophoto of the bottom of the sea. Python [5] GPL [6] [7] VoTT (Visual Object Tagging Tool) Free and open source electron app for image annotation and labeling developed by Microsoft. TypeScript/Electron (Windows, Linux, macOS) MIT ...
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.
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.
If the user needs to add annotations, highlightings or obfuscations to the screenshot the built-in image editor can be used. Greenshot's image editor is a basic vector graphics editor; however, it offers some pixel-based filters. It allows to draw basic shapes (rectangles, ellipses, lines, arrows and freehand) and add text to a screenshot.
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.
ImageNets is an open source and platform independent (Windows & Linux) framework for rapid prototyping of machine vision algorithms. With the GUI ImageNet Designer, no programming knowledge is required to perform operations on images.
ITK-SNAP provides tools for manual delineation of anatomical structures in images. Labeling can take place in all three orthogonal cut planes and results can be visualized as a three-dimensional rendering. This makes it easier to ensure that the segmentation maintains reasonable shape in 3D. Automatic segmentation