OpenCVs

OpenCVs, commonly referred to as OpenCV, is an open-source computer vision and machine learning software library. It provides a wide range of optimized algorithms for image and video analysis, including image processing, feature detection, object recognition, camera calibration, motion tracking, and 3D reconstruction. The library is designed to be cross-platform and suitable for real-time applications.

OpenCV originated in 1999 as a project at Intel and was released as open-source software in 2000. It has since been maintained by a succession of organizations, including Willow Garage and Itseez, and today proceeds under the OpenCV community with contributions from researchers and developers worldwide. Development is conducted openly on public repositories, with frequent releases and extensive documentation and tutorials.

OpenCV is written primarily in C++, with official interfaces for Python and Java and broad language bindings through community projects. It is modular, comprising core functionality and modules such as imgproc, features2d, calib3d, video, ml, objdetect, highgui, and photo, as well as a deep learning module (dnn). The opencv_contrib repository hosts experimental and non-core algorithms. The library runs on Windows, Linux, macOS, Android, and iOS, and can take advantage of hardware acceleration via SIMD instructions, OpenCL, and CUDA where supported. The DNN module enables loading and running models in formats such as Caffe, TensorFlow, Torch, and ONNX.

OpenCV is distributed under a BSD-3-Clause license, permitting free use in academic and commercial projects. The project maintains a large user base, extensive documentation, tutorials, and a growing ecosystem of wrappers and tools, including the OpenCV-Python bindings and OpenCV.js for web applications.