install opencv with 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 ~/

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 , 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 []

   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 , 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
   • 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 =
   • 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/
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. Build. From build directory execute make, it is recommended to do this in several threads

   For example

   make -j7 # runs 7 jobs in parallel

7. [optional] Building documents. Enter and run make with target "html_docs"

   For example

   cd ~/opencv/build/doc/

   make -j7 html_docs
8. To install libraries, execute the following command from build directory
   sudo make install

9. [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 .
   • execute tests from build directory.

   For example

   /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.