Merge pull request #16889 from mehlukas:3.4-consolidateImshow
* consolidate tutorials on image read/display/write * fix unsused variables * apply requested changes * apply requested changes * fix mistake
This commit is contained in:
mehlukas
@@ -1,63 +1,82 @@
|
||||
Load and Display an Image {#tutorial_display_image}
|
||||
=========================
|
||||
Getting Started with Images {#tutorial_display_image}
|
||||
===========================
|
||||
|
||||
Goal
|
||||
----
|
||||
|
||||
In this tutorial you will learn how to:
|
||||
|
||||
- Load an image (using @ref cv::imread )
|
||||
- Create a named OpenCV window (using @ref cv::namedWindow )
|
||||
- Display an image in an OpenCV window (using @ref cv::imshow )
|
||||
- Read an image from file (using @ref cv::imread)
|
||||
- Display an image in an OpenCV window (using @ref cv::imshow)
|
||||
- Write an image to a file (using @ref cv::imwrite)
|
||||
|
||||
Source Code
|
||||
-----------
|
||||
|
||||
Download the source code from
|
||||
[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/introduction/display_image/display_image.cpp).
|
||||
@add_toggle_cpp
|
||||
- **Downloadable code**: Click
|
||||
[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/introduction/display_image/display_image.cpp)
|
||||
|
||||
- **Code at glance:**
|
||||
@include samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
|
||||
@end_toggle
|
||||
|
||||
@add_toggle_python
|
||||
- **Downloadable code**: Click
|
||||
[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/introduction/display_image/display_image.py)
|
||||
|
||||
- **Code at glance:**
|
||||
@include samples/python/tutorial_code/introduction/display_image/display_image.py
|
||||
@end_toggle
|
||||
|
||||
@include cpp/tutorial_code/introduction/display_image/display_image.cpp
|
||||
|
||||
Explanation
|
||||
-----------
|
||||
|
||||
In OpenCV 2 we have multiple modules. Each one takes care of a different area or approach towards
|
||||
@add_toggle_cpp
|
||||
In OpenCV 3 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:
|
||||
|
||||
- *core* section, as here are defined the basic building blocks of the library
|
||||
- *highgui* module, as this contains the functions for input and output operations
|
||||
- @ref core "core" section, as here are defined the basic building blocks of the library
|
||||
- @ref imgcodecs "imgcodecs" module, which provides functions for reading and writing
|
||||
- @ref highgui "highgui" module, as this contains the functions to show an image in a window
|
||||
|
||||
We also include the *iostream* to facilitate console line output and input.
|
||||
|
||||
By declaring `using namespace cv;`, in the following, the library functions can be accessed without explicitly stating the namespace.
|
||||
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp includes
|
||||
@end_toggle
|
||||
|
||||
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:
|
||||
@add_toggle_python
|
||||
As a first step, the OpenCV python library is imported.
|
||||
The proper way to do this is to additionally assign it the name *cv*, which is used in the following to reference the library.
|
||||
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp namespace
|
||||
@snippet samples/python/tutorial_code/introduction/display_image/display_image.py imports
|
||||
@end_toggle
|
||||
|
||||
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".
|
||||
Now, let's analyze the main code.
|
||||
As a first step, we read the image "starry_night.jpg" from the OpenCV samples.
|
||||
In order to do so, a call to the @ref cv::imread function loads the image using the file path specified by the first argument.
|
||||
The second argument is optional and specifies the format in which we want the image. This may be:
|
||||
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp load
|
||||
- IMREAD_COLOR loads the image in the BGR 8-bit format. This is the **default** that is used here.
|
||||
- IMREAD_UNCHANGED loads the image as is (including the alpha channel if present)
|
||||
- IMREAD_GRAYSCALE loads the image as an intensity one
|
||||
|
||||
Then create a *Mat* object that will store the data of the loaded image.
|
||||
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp mat
|
||||
|
||||
Now we call the @ref 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:
|
||||
|
||||
- IMREAD_UNCHANGED (\<0) loads the image as is (including the alpha channel if present)
|
||||
- IMREAD_GRAYSCALE ( 0) loads the image as an intensity one
|
||||
- IMREAD_COLOR (\>0) loads the image in the RGB format
|
||||
After reading in the image data will be stored in a @ref cv::Mat object.
|
||||
|
||||
@add_toggle_cpp
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp imread
|
||||
@end_toggle
|
||||
|
||||
@add_toggle_python
|
||||
@snippet samples/python/tutorial_code/introduction/display_image/display_image.py imread
|
||||
@end_toggle
|
||||
|
||||
@note
|
||||
OpenCV offers support for the image formats Windows bitmap (bmp), portable image formats (pbm,
|
||||
@@ -67,42 +86,38 @@ Now we call the @ref cv::imread function which loads the image name specified by
|
||||
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 @ref 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:
|
||||
Afterwards, a check is executed, if the image was loaded correctly.
|
||||
@add_toggle_cpp
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp empty
|
||||
@end_toggle
|
||||
|
||||
- *WINDOW_AUTOSIZE* is the only supported one if you do not use the Qt backend. In this case the
|
||||
window size will take up the size of the image it shows. No resize permitted!
|
||||
- *WINDOW_NORMAL* on Qt you may use this to allow window resize. The image will resize itself
|
||||
according to the current window size. By using the | operator you also need to specify if you
|
||||
would like the image to keep its aspect ratio (*WINDOW_KEEPRATIO*) or not
|
||||
(*WINDOW_FREERATIO*).
|
||||
@add_toggle_python
|
||||
@snippet samples/python/tutorial_code/introduction/display_image/display_image.py empty
|
||||
@end_toggle
|
||||
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp window
|
||||
|
||||
Finally, to update the content of the OpenCV window with a new image use the @ref cv::imshow
|
||||
function. Specify the OpenCV window name to update and the image to use during this operation:
|
||||
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp imshow
|
||||
Then, the image is shown using a call to the @ref cv::imshow function.
|
||||
The first argument is the title of the window and the second argument is the @ref cv::Mat object that will be shown.
|
||||
|
||||
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 @ref 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.
|
||||
The return value is the key that was pressed.
|
||||
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp wait
|
||||
@add_toggle_cpp
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp imshow
|
||||
@end_toggle
|
||||
|
||||
Result
|
||||
------
|
||||
@add_toggle_python
|
||||
@snippet samples/python/tutorial_code/introduction/display_image/display_image.py imshow
|
||||
@end_toggle
|
||||
|
||||
- Compile your code and then run the executable giving an image path as argument. If you're on
|
||||
Windows the executable will of course contain an *exe* extension too. Of course assure the image
|
||||
file is near your program file.
|
||||
@code{.sh}
|
||||
./DisplayImage HappyFish.jpg
|
||||
@endcode
|
||||
- You should get a nice window as the one shown below:
|
||||
In the end, the image is written to a file if the pressed key was the "s"-key.
|
||||
For this the cv::imwrite function is called that has the file path and the cv::Mat object as an argument.
|
||||
|
||||
|
||||
@add_toggle_cpp
|
||||
@snippet cpp/tutorial_code/introduction/display_image/display_image.cpp imsave
|
||||
@end_toggle
|
||||
|
||||
@youtube{1OJEqpuaGc4}
|
||||
@add_toggle_python
|
||||
@snippet samples/python/tutorial_code/introduction/display_image/display_image.py imsave
|
||||
@end_toggle
|
||||
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 19 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 17 KiB |
@@ -1,105 +1,4 @@
|
||||
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:
|
||||
|
||||
|
||||
|
||||
And if you check in your folder (in my case *images*), you should have a newly .jpg file named
|
||||
*Gray_Image.jpg*:
|
||||
|
||||
|
||||
|
||||
Congratulations, you are done with this tutorial!
|
||||
Tutorial content has been moved: @ref tutorial_display_image
|
||||
|
||||
@@ -144,19 +144,13 @@ Additionally you can find very basic sample source code to introduce you to the
|
||||
|
||||
- @subpage tutorial_display_image
|
||||
|
||||
_Compatibility:_ \> OpenCV 2.0
|
||||
_Languages:_ C++, Python
|
||||
|
||||
_Compatibility:_ \> OpenCV 3.4.4
|
||||
|
||||
_Author:_ Ana Huamán
|
||||
|
||||
We will learn how to display an image using OpenCV
|
||||
|
||||
- @subpage tutorial_load_save_image
|
||||
|
||||
_Compatibility:_ \> OpenCV 2.0
|
||||
|
||||
_Author:_ Ana Huamán
|
||||
|
||||
We will learn how to save an Image in OpenCV...plus a small conversion to grayscale
|
||||
We will learn how to read an image, display it in a window and write it to a file using OpenCV
|
||||
|
||||
- @subpage tutorial_documentation
|
||||
|
||||
|
||||
Reference in New Issue
Block a user