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OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]).
opencv.github.io /cvat /about / 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 ...
OpenVX is an open, royalty-free standard for cross-platform acceleration of computer vision applications. It is designed by the Khronos Group to facilitate portable, optimized and power-efficient processing of methods for vision algorithms.
This is a list of free and open-source software (FOSS) packages, computer software licensed under free software licenses and open-source licenses.Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. [1]
Gary Bradski is an American scientist, engineer, entrepreneur, and author. He co-founded Industrial Perception, a company that developed perception applications for industrial robotic application (since acquired by Google in 2012 [2]) and has worked on the OpenCV Computer Vision library, as well as published a book on that library.
The AMD APP SDK v3.0 supports OpenCL 2.0 and Catalyst Omega 15.7 driver, also it includes samples for OpenCL as well as accelerated libraries such as Bolt (an open-source C++ template library) and the OpenCL accelerated OpenCV (Open Computer Vision) library.
OpenCV's Cascade Classifiers support LBPs as of version 2. VLFeat , an open source computer vision library in C (with bindings to multiple languages including MATLAB) has an implementation . LBPLibrary is a collection of eleven Local Binary Patterns (LBP) algorithms developed for background subtraction problem.
Originally published in 2006, Kaehler's book Learning OpenCV (O'Reilly) serves as an introduction to the library and its use. The book continues to be heavily used by both professionals and students. An updated version of the book, which covers OpenCV 3, was published by O'Reilly Media in 2016. [5]