Installation in Linux

The following 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
[optional] CUDA Toolkit 6.5 or higher
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
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 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
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
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.
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
[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/
[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, it is recommended to do this in several threads

For example

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

For example

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

Get the required test data from OpenCV extra repository.
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.

 https://docs.opencv.org/3.4.0/d7/d9f/tutorial_linux_install.html

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