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OpenCV.org, the provider of the most comprehensive curriculum for learning Computer Vision online, Open Source. OpenCV is open source and released under the BSD 3-Clause License. It is free for commercial use. OpenCV is a highly optimized library with focus on real-time applications. To run the OpenCV program, enter the name of the program. For example, say your compile command looks like this: g `pkg-config opencv -cflags` mycode.cpp -o mycode `pkg-config opencv -libs` The compile command will produce a file called mycode. Make sure you are in the same directory as mycode, and run it by typing its name./mycode.
OpenCV (Open Source Computer Vision Library) is released under a BSD license and hence it’s free for both academic and commercial use. It has C++, Python and Java interfaces and supports Windows, Linux, Mac OS, iOS and Android. It was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform.
Adopted all around the world, OpenCV has more than 47 thousand people of user community and estimated number of downloads exceeding 14 million. Usage ranges from interactive art, to mines inspection, stitching maps on the web or through advanced robotics. OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. It was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, It makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. It has more than 47 thousand people of user community and estimated number of downloads exceeding 14 million. The library is used extensively in companies, research groups and by governmental bodies. Open CV has C++, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS. It leans mostly towards real-time vision applications and takes advantage of MMX and SSE instructions when available. A full-featured CUDA and OpenCL interfaces are being actively developed right now. There are over 500 algorithms and about 10 times as many functions that compose or support those algorithms. Open CV is written natively in C++ and has a templated interface that works seamlessly with STL containers.
$ sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev$ sudo apt-get install python3.5-dev python3-numpy libtbb2 libtbb-dev$ sudo apt-get install libjpeg-dev libpng-dev libtiff5-dev libjasper-dev libdc1394-22-dev libeigen3-dev libtheora-dev libvorbis-dev libxvidcore-dev libx264-dev sphinx-common libtbb-dev yasm libfaac-dev libopencore-amrnb-dev libopencore-amrwb-dev libopenexr-dev libgstreamer-plugins-base1.0-dev libavutil-dev libavfilter-dev libavresample-dev. /opt$ cd opencv/opt/opencv$ mkdir release/opt/opencv$ cd release/opt/opencv/release$ cmake -D BUILDTIFF=ON -D WITHCUDA=OFF -D ENABLEAVX=OFF -D WITHOPENGL=OFF -D WITHOPENCL=OFF -D WITHIPP=OFF -D WITHTBB=ON -D BUILDTBB=ON -D WITHEIGEN=OFF -D WITHV4L=OFF -D WITHVTK=OFF -D BUILDTESTS=OFF -D BUILDPERFTESTS=OFF -D CMAKEBUILDTYPE=RELEASE -D CMAKEINSTALLPREFIX=/usr/local -D OPENCVEXTRAMODULESPATH=/opt/opencvcontrib/modules /opt/opencv//opt/opencv/release$ make -j4/opt/opencv/release$ make install/opt/opencv/release$ ldconfig/opt/opencv/release$ exit/opt/opencv/release$ cd.
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