OpenCV  4.1.2
Open Source Computer Vision
Installation in Linux

The following steps have been tested for Ubuntu 10.04 but should work with other distros as well.

Required Packages

The packages can be installed using a terminal and the following commands or by using Synaptic Manager:

[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

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 as well.

For example

cd ~/<my_working_directory>
git clone https://github.com/opencv/opencv.git
git clone https://github.com/opencv/opencv_contrib.git

Building OpenCV from Source Using CMake

  1. Create a temporary directory, which we denote as <cmake_build_dir>, where you want to put the generated Makefiles, project files as well the object files and output binaries and enter there.

    For example

    cd ~/opencv
    mkdir build
    cd build
  2. Configuring. Run cmake [<some optional parameters>] <path to the OpenCV source directory>

    For example

    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 <cmake_build_dir>, e.g. /home/user/opencv/build
    • set optional parameters
    • run: “Configure”
    • run: “Generate”
    Note
    Use cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=/usr/local .. , without spaces after -D if the above example doesn't work.
  3. Description of some parameters
    • build type: CMAKE_BUILD_TYPE=Release\Debug
    • to build with modules from opencv_contrib set OPENCV_EXTRA_MODULES_PATH to <path to opencv_contrib/modules/>
    • set BUILD_DOCS for building documents
    • set BUILD_EXAMPLES to build all examples
  4. [optional] Building python. Set the following python parameters:
    • PYTHON2(3)_EXECUTABLE = <path to python>
    • PYTHON_INCLUDE_DIR = /usr/include/python<version>
    • PYTHON_INCLUDE_DIR2 = /usr/include/x86_64-linux-gnu/python<version>
    • PYTHON_LIBRARY = /usr/lib/x86_64-linux-gnu/libpython<version>.so
    • PYTHON2(3)_NUMPY_INCLUDE_DIRS = /usr/lib/python<version>/dist-packages/numpy/core/include/
  5. [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.
  6. [optional] Generate pkg-config info
    • Add this flag when running CMake: -DOPENCV_GENERATE_PKGCONFIG=ON
    • Will generate the .pc file for pkg-config and install it.
    • Useful if not using CMake in projects that use OpenCV
    • Installed as opencv4, usage: pkg-config --cflags --libs opencv4
  7. Build. From build directory execute make, it is recommended to do this in several threads

    For example

    make -j7 # runs 7 jobs in parallel
  8. [optional] Building documents. Enter <cmake_build_dir/doc/> and run make with target "doxygen"

    For example

    cd ~/opencv/build/doc/
    make -j7 doxygen
  9. To install libraries, execute the following command from build directory
    sudo make install
  10. [optional] Running tests

    For example

    git clone https://github.com/opencv/opencv_extra.git
    • set OPENCV_TEST_DATA_PATH environment variable to <path to opencv_extra/testdata>.
    • execute tests from build directory.

    For example

    <cmake_build_dir>/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 possible. The stripped version appears to be twice as small. However, we do not recommend using this unless those extra megabytes do really matter.