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An Open Source Computer Vision Library (OpenCV) library is a collection of processes and algorithms that add new functionality to the total OpenCV Library. Commonly, but not always, an OpenCV library package is typically centered on a theme, and each of the features supports the entire theme. When someone upgrades the library, the new functions typically merge right into the old ones, creating one seamless library that allows users to easily select from the list of processes. OpenCV, and most libraries, are written in the C programming language, though some libraries are written in other programming languages.
An OpenCV library contains a wide array of different processes currently known and installed on a program. Users can download a new library or separate functions to add to OpenCV. A library typically consists of functions, processes, algorithms, tools and features. Each process can control and add something completely different to OpenCV, but OpenCV is commonly used for computer vision and graphics rendering, so most processes are made for these tasks.
While not always, most OpenCV library packs are centered on a theme. For example, if a library package is made for motion-capture, then it will normally include several processes and algorithms that support this. Some common processes in this type of pack may be those that detect a human, a feature to help detect the sensors, facial movement capturing, camera support and a physics algorithm that helps collect information on the movement and force. At the same time, a library package also may be just one process.
When a new feature is added to a program, the user commonly has to go through a complex installation to get the feature into the program. The OpenCV library is primarily run by officially released and fan-released libraries, so the installation has been made seamless. The new library package will be added directly into the overall library, and all the features will be accessible to the user within a few seconds.
OpenCV was made in the C programming language and, because of that, most OpenCV library packages also are written in C. At the same time, supporters are able to made a library package in a variety of languages, most of which will still easily install. This allows OpenCV supporters to take advantage of another programming language’s benefits to create a library that may be difficult or impossible in C, or this can play to the supporter’s knowledge of other programming languages.
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