| Original author(s) | Intel Corporation, Willow Garage, Itseez |
|---|---|
| Initial release | June 2000; 20 years ago |
| Stable release | |
| Repository | |
| Written in | C/C++ |
| Operating system | Cross-platform |
| Size | ~200 MB |
| Type | Library |
| License | Apache license |
| Website | opencv.org |
OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly aimed at real-time computer vision.[1] Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel[2]). The library is cross-platform and free for use under the open-sourceApache 2 License. Starting with 2011, OpenCV features GPU acceleration for real-time operations.[3]
History[edit]
Officially launched in 1999 the OpenCV project was initially an Intel Research initiative to advance CPU-intensive applications, part of a series of projects including real-timeray tracing and 3D display walls.[4] The main contributors to the project included a number of optimization experts in Intel Russia, as well as Intel's Performance Library Team. In the early days of OpenCV, the goals of the project were described[5] as:
Installing OpenCV from source takes up a lot of time. Depending on your hardware, and the installation configuration, it can take anywhere from 5 minutes up to 2 hours. Moreover, the installation is not a cakewalk. Hence, we have come up with a solution for Windows users – OpenCV Windows installers. These installers will only work for. Mar 25, 2019 OpenCV is continually adding new modules for latest algorithms from Machine learning, do check out their Github repository and get familiar with implementation. You can even contribute to the library which is a great way to learn and interact with the community.
Opencv Python
- Advance vision research by providing not only open but also optimized code for basic vision infrastructure. No more reinventing the wheel.
- Disseminate vision knowledge by providing a common infrastructure that developers could build on, so that code would be more readily readable and transferable.
- Advance vision-based commercial applications by making portable, performance-optimized code available for free – with a license that did not require code to be open or free itself.
The first alpha version of OpenCV was released to the public at the IEEE Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005. The first 1.0 version was released in 2006. A version 1.1 'pre-release' was released in October 2008.
The second major release of the OpenCV was in October 2009. OpenCV 2 includes major changes to the C++ interface, aiming at easier, more type-safe patterns, new functions, and better implementations for existing ones in terms of performance (especially on multi-core systems). Official releases now occur every six months[6] and development is now done by an independent Russian team supported by commercial corporations.
In August 2012, support for OpenCV was taken over by a non-profit foundation OpenCV.org, which maintains a developer[7] and user site.[8]
On May 2016, Intel signed an agreement to acquire Itseez,[9] a leading developer of OpenCV.[10]
In July 2020, OpenCV announced and began a Kickstarter campaign for the OpenCV AI Kit, a series of hardware modules and additions to OpenCV supporting Spatial AI.
Applications[edit]
OpenCV's application areas include:
- 2D and 3D feature toolkits
- Egomotion estimation
- Human–computer interaction (HCI)
- Motion understanding
- Segmentation and recognition
- Stereopsis stereo vision: depth perception from 2 cameras
- Structure from motion (SFM)
To support some of the above areas, OpenCV includes a statistical machine learning library that contains:
- Gradient boosting trees
- Support vector machine (SVM)
- Deep neural networks (DNN)[11]
Programming language[edit]
OpenCV is written in C++ and its primary interface is in C++, but it still retains a less comprehensive though extensive older C interface. All of the new developments and algorithms appear in the C++ interface. There are bindings in Python, Java and MATLAB/OCTAVE. The API for these interfaces can be found in the online documentation.[12] Wrappers in several programming languages have been developed to encourage adoption by a wider audience. In version 3.4, JavaScript bindings for a selected subset of OpenCV functions was released as OpenCV.js, to be used for web platforms.[13]
Hardware acceleration[edit]
If the library finds Intel's Integrated Performance Primitives on the system, it will use these proprietary optimized routines to accelerate itself.
A CUDA-based GPU interface has been in progress since September 2010.[14]
An OpenCL-based GPU interface has been in progress since October 2012,[15] documentation for version 2.4.13.3 can be found at docs.opencv.org.[16]
OS support[edit]
Opencv Mat
OpenCV runs on the following desktop operating systems: Windows, Linux, macOS, FreeBSD, NetBSD, OpenBSD. OpenCV runs on the following mobile operating systems: Android, iOS, Maemo,[17]BlackBerry 10.[18] The user can get official releases from SourceForge or take the latest sources from GitHub.[19] OpenCV uses CMake.
Opencv Github
See also[edit]
- AForge.NET, a computer vision library for the Common Language Runtime (.NET Framework and Mono).
- ROS (Robot Operating System). OpenCV is used as the primary vision package in ROS.
- VXL, an alternative library written in C++.
- CVIPtools, a complete GUI-based computer-vision and image-processing software environment, with C function libraries, a COM-based DLL, along with two utility programs for algorithm development and batch processing.
- OpenNN, an open-source neural networks library written in C++.
References[edit]
- ^Pulli, Kari; Baksheev, Anatoly; Kornyakov, Kirill; Eruhimov, Victor (1 April 2012). 'Realtime Computer Vision with OpenCV'. Queue. 10 (4): 40:40–40:56. doi:10.1145/2181796.2206309.
- ^Intel acquires Itseez: https://opencv.org/intel-acquires-itseez.html
- ^'CUDA'. opencv.org. Retrieved 2020-10-15.
- ^Adrian Kaehler; Gary Bradski (14 December 2016). Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library. O'Reilly Media. pp. 26ff. ISBN978-1-4919-3800-3.
- ^Bradski, Gary; Kaehler, Adrian (2008). Learning OpenCV: Computer vision with the OpenCV library. O'Reilly Media, Inc. p. 6.
- ^OpenCV change logs: http://code.opencv.org/projects/opencv/wiki/ChangeLogArchived 2013-01-15 at the Wayback Machine
- ^OpenCV Developer Site: http://code.opencv.orgArchived 2013-01-13 at archive.today
- ^OpenCV User Site: http://opencv.org/
- ^'Intel Acquires Computer Vision for IOT, Automotive | Intel Newsroom'. Intel Newsroom. Retrieved 2018-11-26.
- ^'Intel acquires Russian computer vision company Itseez'. East-West Digital News. 2016-05-31. Retrieved 2018-11-26.
- ^OpenCV: http://opencv.org/opencv-3-3.html
- ^OpenCV C interface: http://docs.opencv.org
- ^Introduction to OpenCV.js and Tutorials
- ^Cuda GPU port: http://opencv.org/platforms/cuda.htmlArchived 2016-05-21 at the Wayback Machine
- ^OpenCL Announcement: http://opencv.org/opencv-v2-4-3rc-is-under-way.html
- ^OpenCL-accelerated Computer Vision API Reference: http://docs.opencv.org/modules/ocl/doc/ocl.html
- ^Maemo port: https://garage.maemo.org/projects/opencv
- ^BlackBerry 10 (partial port): https://github.com/blackberry/OpenCV
- ^'GitHub - opencv/Opencv: Open Source Computer Vision Library'. 21 May 2020.
