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Merge pull request #16889 from mehlukas:3.4-consolidateImshow

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* consolidate tutorials on image read/display/write

* fix unsused variables

* apply requested changes

* apply requested changes

* fix mistake
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mehlukas
2020-04-07 16:14:51 +02:00
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parent 734771418e
commit 75bd9f86b2
11 changed files with 118 additions and 352 deletions
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doc/tutorials/introduction/load_save_image/load_save_image.markdown
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Load, Modify, and Save an Image {#tutorial_load_save_image}
===============================
@note
We assume that by now you know how to load an image using @ref cv::imread and to display it in a
window (using @ref cv::imshow ). Read the @ref tutorial_display_image tutorial otherwise.
Goals
-----
In this tutorial you will learn how to:
- Load an image using @ref cv::imread
- Transform an image from BGR to Grayscale format by using @ref cv::cvtColor
- Save your transformed image in a file on disk (using @ref cv::imwrite )
Code
----
Here it is:
@code{.cpp}
#include <opencv2/opencv.hpp>
using namespace cv;
int main( int argc, char** argv )
{
char* imageName = argv[1];
Mat image;
image = imread( imageName, IMREAD_COLOR );
if( argc != 2 || !image.data )
{
printf( " No image data \n " );
return -1;
}
Mat gray_image;
cvtColor( image, gray_image, COLOR_BGR2GRAY );
imwrite( "../../images/Gray_Image.jpg", gray_image );
namedWindow( imageName, WINDOW_AUTOSIZE );
namedWindow( "Gray image", WINDOW_AUTOSIZE );
imshow( imageName, image );
imshow( "Gray image", gray_image );
waitKey(0);
return 0;
}
@endcode
Explanation
-----------
-# We begin by loading an image using @ref cv::imread , located in the path given by *imageName*.
For this example, assume you are loading a BGR image.
-# Now we are going to convert our image from BGR to Grayscale format. OpenCV has a really nice
function to do this kind of transformations:
@code{.cpp}
cvtColor( image, gray_image, COLOR_BGR2GRAY );
@endcode
As you can see, @ref cv::cvtColor takes as arguments:
- a source image (*image*)
- a destination image (*gray_image*), in which we will save the converted image.
- an additional parameter that indicates what kind of transformation will be performed. In
this case we use **COLOR_BGR2GRAY** (because of @ref cv::imread has BGR default channel
order in case of color images).
-# So now we have our new *gray_image* and want to save it on disk (otherwise it will get lost
after the program ends). To save it, we will use a function analogous to @ref cv::imread : @ref
cv::imwrite
@code{.cpp}
imwrite( "../../images/Gray_Image.jpg", gray_image );
@endcode
Which will save our *gray_image* as *Gray_Image.jpg* in the folder *images* located two levels
up of my current location.
-# Finally, let's check out the images. We create two windows and use them to show the original
image as well as the new one:
@code{.cpp}
namedWindow( imageName, WINDOW_AUTOSIZE );
namedWindow( "Gray image", WINDOW_AUTOSIZE );
imshow( imageName, image );
imshow( "Gray image", gray_image );
@endcode
-# Add the *waitKey(0)* function call for the program to wait forever for an user key press.
Result
------
When you run your program you should get something like this:
![](images/Load_Save_Image_Result_1.jpg)
And if you check in your folder (in my case *images*), you should have a newly .jpg file named
*Gray_Image.jpg*:
![](images/Load_Save_Image_Result_2.jpg)
Congratulations, you are done with this tutorial!
Tutorial content has been moved: @ref tutorial_display_image