OpenCV Computer Vision Library

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library with over 2500 optimized algorithms. Originally developed by Intel in 1999 by Gary Bradsky, and later supported by Willow Garage and Itseez (acquired by Intel in 2016), OpenCV is the de facto standard for computer vision with over 75,000 stars. Key features: real-time computer vision algorithms including object detection, face recognition, feature extraction, optical flow, stereo vision, and camera calibration. Image processing operations including filtering, transformations, color space conversion, histograms, thresholding, morphology, and edge detection. Deep learning module (dnn) for inference with models from TensorFlow, PyTorch, Caffe, Darknet, and ONNX formats. Video analysis including motion detection, object tracking (KCF, CSRT, MOSSE, GOTURN), background subtraction, and optical flow. 2D feature framework with SIFT, SURF, ORB, FAST, BRIEF, AKAZE descriptors for feature matching and panorama stitching. Camera calibration and 3D reconstruction including stereo vision, structure from motion, and epipolar geometry. Machine learning module with SVM, KNN, random forests, decision trees, and boosting. GUI functions for displaying images, capturing mouse and keyboard events, and creating trackbars. Video I/O for reading and writing video files and streams from cameras. High-performance C++ core with SIMD optimizations using SSE, AVX, and NEON instructions. Python, Java, MATLAB, and C++ bindings. Cross-platform on Windows, Linux, macOS, Android, and iOS.