OpenCV is an open source programming library that provides functions for capturing, analyzing, and manipulating visual data. It can be used in various applications, including self-driving vehicles and digital art. The library eliminates the need for complex algorithms and allows developers to focus on building the application. It also contains sub-modules for machine learning and user interface elements. OpenCV has been used in practical and creative projects, including product inspection, medical imaging, and gaming.
Open Source Computer Vision (OpenCV) is an open source computer programming library developed to support applications that use computer vision. It provides hundreds of functions for capturing, analyzing, and manipulating visual data and can eliminate some of the problems programmers face when developing applications that rely on computer vision. Parts of the library also provide the user interface and pattern recognition functions. OpenCV has been employed in both practical and creative applications, including self-driving vehicles and new forms of digital art.
Programming libraries provide common functions or complex capabilities that developers can use in their programs. The OpenCV library contains hundreds of functions that support capturing, analyzing and manipulating visual information sent to a computer from webcams, video files or other types of devices. Simple functions can be used to draw a line or other shape on a screen, while the more advanced parts of the library contain algorithms for detecting faces, tracking movement and analyzing shapes. Many of the algorithms in this library are related to specific uses of computer vision, including product inspection, medical imaging, robotics, facial and gesture recognition, and human-computer interaction (HCI). As an open source programming library, OpenCV can be used with very few restrictions in both commercial and hobbyist projects.
With OpenCV, a developer can eliminate some of the complex and tedious work required to make computer vision work reliably and focus on building the application. Instead of creating algorithms for facial recognition and the like, a programmer can add just a few lines of code to allow a program to access the appropriate library function. It also means that a programmer doesn’t need to master every aspect of computer vision to build a program using it.
In addition to the core video and image processing functionality, OpenCV contains sub-modules intended to support other areas of an application. One of these modules includes machine learning algorithms that can analyze and predict visual patterns. The HighGUI module provides user interface elements and functions for storing and accessing video and image files.
The OpenCV library can be found at the heart of some very ambitious projects. Along with an assortment of sensors, computer hardware, and bespoke software, it powered a heavily modified sport-utility vehicle that covered a 132-mile (212km) desert race course without human intervention. However, not all projects that draw on library resources are so practical. Members of the creative coding movement, a loose confederation of people who view coding as a form of expression, have used the library to create new forms of digital art. Others have hacked into existing devices containing cameras and opened up new possibilities for gaming, interactive computing, and even telepresence.
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