OpenCV  4.2.0
Open Source Computer Vision
Load and Display an Image

Goal

In this tutorial you will learn how to:

Source Code

Download the source code from here.

#include <opencv2/core.hpp>
#include <iostream>
using namespace cv;
using namespace std;
int main( int argc, char** argv )
{
String imageName( "HappyFish.jpg" ); // by default
if( argc > 1)
{
imageName = argv[1];
}
Mat image;
image = imread( samples::findFile( imageName ), IMREAD_COLOR ); // Read the file
if( image.empty() ) // Check for invalid input
{
cout << "Could not open or find the image" << std::endl ;
return -1;
}
namedWindow( "Display window", WINDOW_AUTOSIZE ); // Create a window for display.
imshow( "Display window", image ); // Show our image inside it.
waitKey(0); // Wait for a keystroke in the window
return 0;
}

Explanation

In OpenCV 2 we have multiple modules. Each one takes care of a different area or approach towards image processing. You could already observe this in the structure of the user guide of these tutorials itself. Before you use any of them you first need to include the header files where the content of each individual module is declared.

You'll almost always end up using the:

#include <opencv2/core.hpp>
#include <iostream>

We also include the iostream to facilitate console line output and input. To avoid data structure and function name conflicts with other libraries, OpenCV has its own namespace: cv. To avoid the need appending prior each of these the cv:: keyword you can import the namespace in the whole file by using the lines:

using namespace cv;
using namespace std;

This is true for the STL library too (used for console I/O). Now, let's analyze the main function. We start up assuring that we acquire a valid image name argument from the command line. Otherwise take a picture by default: "HappyFish.jpg".

String imageName( "HappyFish.jpg" ); // by default
if( argc > 1)
{
imageName = argv[1];
}

Then create a Mat object that will store the data of the loaded image.

Mat image;

Now we call the cv::imread function which loads the image name specified by the first argument (argv[1]). The second argument specifies the format in what we want the image. This may be:

image = imread( samples::findFile( imageName ), IMREAD_COLOR ); // Read the file
Note
OpenCV offers support for the image formats Windows bitmap (bmp), portable image formats (pbm, pgm, ppm) and Sun raster (sr, ras). With help of plugins (you need to specify to use them if you build yourself the library, nevertheless in the packages we ship present by default) you may also load image formats like JPEG (jpeg, jpg, jpe), JPEG 2000 (jp2 - codenamed in the CMake as Jasper), TIFF files (tiff, tif) and portable network graphics (png). Furthermore, OpenEXR is also a possibility.

After checking that the image data was loaded correctly, we want to display our image, so we create an OpenCV window using the cv::namedWindow function. These are automatically managed by OpenCV once you create them. For this you need to specify its name and how it should handle the change of the image it contains from a size point of view. It may be:

namedWindow( "Display window", WINDOW_AUTOSIZE ); // Create a window for display.

Finally, to update the content of the OpenCV window with a new image use the cv::imshow function. Specify the OpenCV window name to update and the image to use during this operation:

imshow( "Display window", image ); // Show our image inside it.

Because we want our window to be displayed until the user presses a key (otherwise the program would end far too quickly), we use the cv::waitKey function whose only parameter is just how long should it wait for a user input (measured in milliseconds). Zero means to wait forever.

waitKey(0); // Wait for a keystroke in the window

Result