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Original author | Ana Huamán |
Compatibility | OpenCV >= 3.0 |
- Warning
- This tutorial can contain obsolete information.
- 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>
int main(
int argc,
char** argv )
{
if ( argc != 2 )
{
printf("usage: DisplayImage.out <Image_Path>\n");
return -1;
}
image = imread( argv[1], IMREAD_COLOR );
{
printf("No image data \n");
return -1;
}
namedWindow("Display Image", WINDOW_AUTOSIZE );
imshow("Display Image", image);
waitKey(0);
return 0;
}
n-dimensional dense array class
Definition mat.hpp:828
uchar * data
pointer to the data
Definition mat.hpp:2156
int main(int argc, char *argv[])
Definition highgui_qt.cpp:3
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.:
You should get a nice window as the one shown below: