opencv Installation in Linux and hello world

http://opencv.org/quickstart.html

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:

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

cd ~/<my_working_directory>
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 <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”

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, recomend to do it 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 “html_docs”

For example

cd ~/opencv/build/doc/
make -j7 html_docs

To install libraries, from build directory execute

sudo make install

[optional] Running tests

Get the required test data from OpenCV extra repository.

For example

git clone https://github.com/Itseez/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 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.

Using OpenCV with gcc and CMake

Note

We assume that you have successfully installed OpenCV in your workstation.

The easiest way of using OpenCV in your code is to use CMake. A few advantages (taken from the Wiki):
No need to change anything when porting between Linux and Windows

Can easily be combined with other tools by CMake( i.e. Qt, ITK and VTK )

If you are not familiar with CMake, checkout the tutorial on its website.

Steps

Create a program using OpenCV

Let’s use a simple program such as DisplayImage.cpp shown below.

#include <stdio.h>
#include <opencv2/opencv.hpp>

using namespace cv;

int main(int argc, char** argv )
{
if ( argc != 2 )
{
printf("usage: DisplayImage.out <Image_Path>\n");
return -1;
}

Mat image;
image = imread( argv[1], 1 );

if ( !image.data )
{
printf("No image data \n");
return -1;
}
namedWindow("Display Image", WINDOW_AUTOSIZE );
imshow("Display Image", image);

waitKey(0);

return 0;
}

Create a CMake file

Now you have to create your CMakeLists.txt file. It should look like this:

cmake_minimum_required(VERSION 2.8)
project( DisplayImage )
find_package( OpenCV REQUIRED )
include_directories( ${OpenCV_INCLUDE_DIRS} )
add_executable( DisplayImage DisplayImage.cpp )
target_link_libraries( DisplayImage ${OpenCV_LIBS} )

Generate the executable

This part is easy, just proceed as with any other project using CMake:

cd <DisplayImage_directory>
cmake .
make

Result

By now you should have an executable (called DisplayImage in this case). You just have to run it giving an image location as an argument, i.e.:

./DisplayImage lena.jpg

You should get a nice window as the one shown below: