.. _Linux-Installation: Installation in Linux ********************* These steps have been tested for Ubuntu 10.04 but should work with other distros as well. Required Packages ================= * GCC 4.4.x or later * CMake 2.8.7 or higher * Git * GTK+2.x or higher, including headers (libgtk2.0-dev) * pkg-config * Python 2.6 or later and Numpy 1.5 or later with developer packages (python-dev, python-numpy) * ffmpeg or libav development packages: libavcodec-dev, libavformat-dev, libswscale-dev * [optional] libtbb2 libtbb-dev * [optional] libdc1394 2.x * [optional] libjpeg-dev, libpng-dev, libtiff-dev, libjasper-dev, libdc1394-22-dev The packages can be installed using a terminal and the following commands or by using Synaptic Manager: .. code-block:: bash [compiler] sudo apt-get install build-essential [required] sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev [optional] sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev Getting OpenCV Source Code ========================== You can use the latest stable OpenCV version or you can grab the latest snapshot from our `Git repository `_. Getting the Latest Stable OpenCV Version ---------------------------------------- * Go to our `downloads page `_. * Download the source archive and unpack it. Getting the Cutting-edge OpenCV from the Git Repository ------------------------------------------------------- Launch Git client and clone `OpenCV repository `_. If you need modules from `OpenCV contrib repository `_ then clone it too. For example .. code-block:: bash cd ~/ git clone https://github.com/Itseez/opencv.git git clone https://github.com/Itseez/opencv_contrib.git Building OpenCV from Source Using CMake ======================================= #. Create a temporary directory, which we denote as , where you want to put the generated Makefiles, project files as well the object files and output binaries and enter there. For example .. code-block:: bash cd ~/opencv mkdir build cd build #. Configuring. Run cmake [] For example .. code-block:: bash cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local .. or cmake-gui * set full path to OpenCV source code, e.g. /home/user/opencv * set full path to , e.g. /home/user/opencv/build * set optional parameters * run: “Configure” * run: “Generate” #. Description of some parameters * build type: CMAKE_BUILD_TYPE=Release\\Debug * to build with modules from opencv_contrib set OPENCV_EXTRA_MODULES_PATH to * set BUILD_DOCS for building documents * set BUILD_EXAMPLES to build all examples #. [optional] Building python. Set the following python parameters: * PYTHON2(3)_EXECUTABLE = * PYTHON_INCLUDE_DIR = /usr/include/python * PYTHON_INCLUDE_DIR2 = /usr/include/x86_64-linux-gnu/python * PYTHON_LIBRARY = /usr/lib/x86_64-linux-gnu/libpython.so * PYTHON2(3)_NUMPY_INCLUDE_DIRS = /usr/lib/python/dist-packages/numpy/core/include/ #. [optional] Building java. * Unset parameter: BUILD_SHARED_LIBS * It is useful also to unset BUILD_EXAMPLES, BUILD_TESTS, BUILD_PERF_TESTS - as they all will be statically linked with OpenCV and can take a lot of memory. #. Build. From build directory execute make, recomend to do it in several threads For example .. code-block:: bash make -j7 # runs 7 jobs in parallel #. [optional] Building documents. Enter and run make with target "html_docs" For example .. code-block:: bash cd ~/opencv/build/doc/ make -j7 html_docs #. To install libraries, from build directory execute .. code-block:: bash sudo make install #. [optional] Running tests * Get the required test data from `OpenCV extra repository `_. For example .. code-block:: bash git clone https://github.com/Itseez/opencv_extra.git * set OPENCV_TEST_DATA_PATH environment variable to . * execute tests from build directory. For example .. code-block:: bash /bin/opencv_test_core .. note:: If the size of the created library is a critical issue (like in case of an Android build) you can use the ``install/strip`` command to get the smallest size as possible. The *stripped* version appears to be twice as small. However, we do not recommend using this unless those extra megabytes do really matter.