OpenCV: The Open Source Computer Vision Library
OpenCV stands for Open Source Computer Vision Library and is arguably the most used computer vision library in the world. It was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being open-source, it has a vast repository of over 2,500 algorithms that are both classic and state-of-the-art.
Key Features of OpenCV
- Cross-Platform: Works on Windows, Linux, Mac OS, iOS, and Android.
- Comprehensive Modules: Includes modules for image processing, video capture, machine learning, GUI operations, and more.
- Language Support: Provides interfaces for C++, Python, Java, and has partial support for MATLAB/Octave.
Applications of OpenCV
- Real-time vision applications like motion-tracking, facial recognition, and object detection.
- Advanced robotics for navigation and human-robot interaction.
To read more about Opencv Please read this article – OpenCV tutorial
Computer Vision Libraries for Python: Features, Applications, and Suitability
Computer Vision allows machines to perceive and interpret the visual world. Computer vision captures images to understand the content and context of what is being seen and enables applications like autonomous driving, augmented reality, and more. Computer vision libraries are the backbone of these applications.