OpenCV helps create real-time computer vision applications. It maintains a cross-platform library. It includes operations like image manipulation, pattern classification, and picture analysis. OpenCV focuses on processing an image and capturing videos. Also, it also includes testing features of an image such as detection of faces or objects. Apart from supporting computer vision and related algorithms, OpenCV programming also promotes algorithms of machine learning.
One can learn OpenCV and its features easily if they have a strong base in Mathematics. This simplifies the process of designing algorithms through OpenCV library. Besides, knowledge of C or C++ programming is helpful for coding. Don’t worry if you are unaware of any of these concepts. You can start learning fresh via OpenCV tutorials for beginners.
OpenCV applications deal with digital images and videos. OpenCV has been helpful in developing applications for fields like industrial automation, robotics, security, medicine, and transport. The developers can process images and videos using the cross-platform library. Image processing becomes faster in OpenCV as the machine language can be directly executed without performing interpretation. One can perform complex math on images with C and offer speed to applications.
OpenCV is supported by various programming languages like C++, Java, and Python. Moreover, OpenCV works on almost all platforms like Linux, Windows, OS X, Android, iOS, and others.
Hackr.io is the best place to learn programming languages and frameworks. One can start learning from scratch using our community-recommended and reviewed OpenCV Tutorials and courses for beginners as well as advanced users. Feel free to ask your OpenCV questions/doubts in our OpenCV forum. Keep can also keep yourself updated with the latest news and articles of OpenCV by following this category on Hackr.io.