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OpenCV (Open Source Computer Vision) is a library for real time computer vision. When using this tag, please add a language specific tag (python, c++, ...), if relevant.

OpenCV is a code library for Computer Vision related applications, spanning from many very basic tasks (capture and pre-processing of image data) to high-level algorithms (feature extraction, motion tracking, machine learning).

It is free software. Versions from 4.5.0 are licensed under the Apache 2 license, versions before that under the BSD 3-clause license. OpenCV provides a rich API in C++, Python, and Java. Third party wrappers are available. The library is platform-independent and often used for real-time image processing and computer vision (e.g. tracking in videos). It supports Windows, Linux, and OS X as well as Android (native and Java) and iOS.

OpenCV was officially launched by Intel in 1999. Version 2.0 (2009) was an important landmark as it introduced the new, comprehensive C++ interface, which since then is also to be used internally in the library. Since this release, OpenCV saw a strong acceleration of development in improving the library and adding new features. Version 3.0, released in 2015, deprecated the C API and emphasized object-oriented design for increased modularity and intuitive interface. More information may be found in Wikipedia.

Latest stable versions:

Homepage: https://opencv.org

Documentation: https://docs.opencv.org

Tutorials including source code:


Books

Note that this list is likely outdated and not vetted for quality. A book or course on computer vision in general, along with the official documentation of OpenCV, will give a better understanding of the matter and the library.