Saving the first batch of tutorials: Short installation guide and a few tutorials for beginners

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.. _Adding_Images:
Adding (blending) two images using OpenCV
*******************************************
Goal
=====
In this tutorial you will learn how to:
* What is *linear blending* and why it is useful.
* Add two images using :add_weighted:`addWeighted <>`
Cool Theory
=================
.. note::
The explanation below belongs to the book `Computer Vision: Algorithms and Applications <http://szeliski.org/Book/>`_ by Richard Szeliski
From our previous tutorial, we know already a bit of *Pixel operators*. An interesting dyadic (two-input) operator is the *linear blend operator*:
.. math::
g(x) = (1 - \alpha)f_{0}(x) + \alpha f_{1}(x)
By varying :math:`\alpha` from :math:`0 \rightarrow 1` this operator can be used to perform a temporal *cross-disolve* between two images or videos, as seen in slide shows and film production (cool, eh?)
Code
=====
As usual, after the not-so-lengthy explanation, let's go to the code. Here it is:
.. code-block:: cpp
#include <cv.h>
#include <highgui.h>
#include <iostream>
using namespace cv;
int main( int argc, char** argv )
{
double alpha = 0.5; double beta; double input;
Mat src1, src2, dst;
/// Ask the user enter alpha
std::cout<<" Simple Linear Blender "<<std::endl;
std::cout<<"-----------------------"<<std::endl;
std::cout<<"* Enter alpha [0-1]: ";
std::cin>>input;
/// We use the alpha provided by the user iff it is between 0 and 1
if( alpha >= 0 && alpha <= 1 )
{ alpha = input; }
/// Read image ( same size, same type )
src1 = imread("../../images/LinuxLogo.jpg");
src2 = imread("../../images/WindowsLogo.jpg");
if( !src1.data ) { printf("Error loading src1 \n"); return -1; }
if( !src2.data ) { printf("Error loading src2 \n"); return -1; }
/// Create Windows
namedWindow("Linear Blend", 1);
beta = ( 1.0 - alpha );
addWeighted( src1, alpha, src2, beta, 0.0, dst);
imshow( "Linear Blend", dst );
waitKey(0);
return 0;
}
Explanation
============
#. Since we are going to perform:
.. math::
g(x) = (1 - \alpha)f_{0}(x) + \alpha f_{1}(x)
We need two source images (:math:`f_{0}(x)` and :math:`f_{1}(x)`). So, we load them in the usual way:
.. code-block:: cpp
src1 = imread("../../images/LinuxLogo.jpg");
src2 = imread("../../images/WindowsLogo.jpg");
.. warning::
Since we are *adding* *src1* and *src2*, they both have to be of the same size (width and height) and type.
#. Now we need to generate the :math:`g(x)` image. For this, the function :add_weighted:`addWeighted <>` comes quite handy:
.. code-block:: cpp
beta = ( 1.0 - alpha );
addWeighted( src1, alpha, src2, beta, 0.0, dst);
since :add_weighted:`addWeighted <>` produces:
.. math::
dst = \alpha \cdot src1 + \beta \cdot src2 + \gamma
In this case, :math:`\gamma` is the argument :math:`0.0` in the code above.
#. Create windows, show the images and wait for the user to end the program.
Result
=======
.. image:: images/Adding_Images_Tutorial_Result_0.png
:alt: Blending Images Tutorial - Final Result
:align: center

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.. _Adding_Trackbars:
Adding a Trackbar to our applications!
***************************************
* In the previous tutorials (about *linear blending* and the *brightness and contrast adjustments*) you might have noted that we needed to give some **input** to our programs, such as :math:`\alpha` and :math:`beta`. We accomplished that by entering this data using the Terminal
* Well, it is time to use some fancy GUI tools. OpenCV provides some GUI utilities (*highgui.h*) for you. An example of this is a **Trackbar**
.. image:: images/Adding_Trackbars_Tutorial_Trackbar.png
:alt: Trackbar example
:align: center
* In this tutorial we will just modify our two previous programs so that they get the input information from the trackbar.
Goals
======
In this tutorial you will learn how to:
* Add a Trackbar in an OpenCV window by using :create_trackbar:`createTrackbar <>`
Code
=====
Let's modify the program made in the tutorial :ref:`Adding_Images`. We will let the user enter the :math:`\alpha` value by using the Trackbar.
.. code-block:: cpp
#include <cv.h>
#include <highgui.h>
using namespace cv;
/// Global Variables
const int alpha_slider_max = 100;
int alpha_slider;
double alpha;
double beta;
/// Matrices to store images
Mat src1;
Mat src2;
Mat dst;
/**
* @function on_trackbar
* @brief Callback for trackbar
*/
void on_trackbar( int, void* )
{
alpha = (double) alpha_slider/alpha_slider_max ;
beta = ( 1.0 - alpha );
addWeighted( src1, alpha, src2, beta, 0.0, dst);
imshow( "Linear Blend", dst );
}
int main( int argc, char** argv )
{
/// Read image ( same size, same type )
src1 = imread("../../images/LinuxLogo.jpg");
src2 = imread("../../images/WindowsLogo.jpg");
if( !src1.data ) { printf("Error loading src1 \n"); return -1; }
if( !src2.data ) { printf("Error loading src2 \n"); return -1; }
/// Initialize values
alpha_slider = 0;
/// Create Windows
namedWindow("Linear Blend", 1);
/// Create Trackbars
char TrackbarName[50];
sprintf( TrackbarName, "Alpha x %d", alpha_slider_max );
createTrackbar( TrackbarName, "Linear Blend", &alpha_slider, alpha_slider_max, on_trackbar );
/// Show some stuff
on_trackbar( alpha_slider, 0 );
/// Wait until user press some key
waitKey(0);
return 0;
}
Explanation
============
We only analyze the code that is related to Trackbar:
#. First, we load 02 images, which are going to be blended.
.. code-block:: cpp
src1 = imread("../../images/LinuxLogo.jpg");
src2 = imread("../../images/WindowsLogo.jpg");
#. To create a trackbar, first we have to create the window in which it is going to be located. So:
.. code-block:: cpp
namedWindow("Linear Blend", 1);
#. Now we can create the Trackbar:
.. code-block:: cpp
createTrackbar( TrackbarName, "Linear Blend", &alpha_slider, alpha_slider_max, on_trackbar );
Note the following:
* Our Trackbar has a label **TrackbarName**
* The Trackbar is located in the window named **"Linear Blend"**
* The Trackbar values will be in the range from :math:`0` to **alpha_slider_max** (the minimum limit is always **zero**).
* The numerical value of Trackbar is stored in **alpha_slider**
* Whenever the user moves the Trackbar, the callback function **on_trackbar** is called
#. Finally, we have to define the callback function **on_trackbar**
.. code-block:: cpp
void on_trackbar( int, void* )
{
alpha = (double) alpha_slider/alpha_slider_max ;
beta = ( 1.0 - alpha );
addWeighted( src1, alpha, src2, beta, 0.0, dst);
imshow( "Linear Blend", dst );
}
Note that:
* We use the value of **alpha_slider** (integer) to get a double value for **alpha**.
* **alpha_slider** is updated each time the trackbar is displaced by the user.
* We define *src1*, *src2*, *dist*, *alpha*, *alpha_slider* and *beta* as global variables, so they can be used everywhere.
Result
=======
* Our program produces the following output:
.. image:: images/Adding_Trackbars_Tutorial_Result_0.png
:alt: Adding Trackbars - Windows Linux
:align: center
* As a manner of practice, you can also add 02 trackbars for the program made in :ref:`Basic_Linear_Transform`. One trackbar to set :math:`\alpha` and another for :math:`\beta`. The output might look like:
.. image:: images/Adding_Trackbars_Tutorial_Result_1.png
:alt: Adding Trackbars - Lena
:height: 500px
:align: center

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.. _Basic_Linear_Transform:
Changing the contrast and brightness of an image!
***************************************************
Goal
=====
In this tutorial you will learn how to:
* Access pixel values
* Initialize a matrix with zeros
* Learn what :saturate_cast:`saturate_cast <>` does and why it is useful
* Get some cool info about pixel transformations
Cool Theory
=================
.. note::
The explanation below belongs to the book `Computer Vision: Algorithms and Applications <http://szeliski.org/Book/>`_ by Richard Szeliski
Image Processing
--------------------
* A general image processing operator is a function that takes one or more input images and produces an output image.
* Image transforms can be seen as:
* Point operators (pixel transforms)
* Neighborhood (area-based) operators
Pixel Transforms
^^^^^^^^^^^^^^^^^
* In this kind of image processing transform, each output pixel's value depends on only the corresponding input pixel value (plus, potentially, some globally collected information or parameters).
* Examples of such operators include *brightness and contrast adjustments* as well as color correction and transformations.
Brightness and contrast adjustments
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
* Two commonly used point processes are *multiplication* and *addition* with a constant:
.. math::
g(x) = \alpha f(x) + \beta
* The parameters :math:`\alpha > 0` and :math:`\beta` are often called the *gain* and *bias* parameters; sometimes these parameters are said to control *contrast* and *brightness* respectively.
* You can think of :math:`f(x)` as the source image pixels and :math:`g(x)` as the output image pixels. Then, more conveniently we can write the expression as:
.. math::
g(i,j) = \alpha \cdot f(i,j) + \beta
where :math:`i` and :math:`j` indicates that the pixel is located in the *i-th* row and *j-th* column.
Code
=====
* The following code performs the operation :math:`g(i,j) = \alpha \cdot f(i,j) + \beta`
* Here it is:
.. code-block:: cpp
#include <cv.h>
#include <highgui.h>
#include <iostream>
using namespace cv;
double alpha; /**< Simple contrast control */
int beta; /**< Simple brightness control */
int main( int argc, char** argv )
{
/// Read image given by user
Mat image = imread( argv[1] );
Mat new_image = Mat::zeros( image.size(), image.type() );
/// Initialize values
std::cout<<" Basic Linear Transforms "<<std::endl;
std::cout<<"-------------------------"<<std::endl;
std::cout<<"* Enter the alpha value [1.0-3.0]: ";std::cin>>alpha;
std::cout<<"* Enter the beta value [0-100]: "; std::cin>>beta;
/// Do the operation new_image(i,j) = alpha*image(i,j) + beta
for( int y = 0; y < image.rows; y++ )
{ for( int x = 0; x < image.cols; x++ )
{ for( int c = 0; c < 3; c++ )
{
new_image.at<Vec3b>(y,x)[c] = saturate_cast<uchar>( alpha*( image.at<Vec3b>(y,x)[c] ) + beta );
}
}
}
/// Create Windows
namedWindow("Original Image", 1);
namedWindow("New Image", 1);
/// Show stuff
imshow("Original Image", image);
imshow("New Image", new_image);
/// Wait until user press some key
waitKey();
return 0;
}
Explanation
============
#. We begin by creating parameters to save :math:`\alpha` and :math:`\beta` to be entered by the user:
.. code-block:: cpp
double alpha;
int beta;
#. We load an image using :imread:`imread <>` and save it in a Mat object:
.. code-block:: cpp
Mat image = imread( argv[1] );
#. Now, since we will make some transformations to this image, we need a new Mat object to store it. Also, we want this to have the following features:
* Initial pixel values equal to zero
* Same size and type as the original image
.. code-block:: cpp
Mat new_image = Mat::zeros( image.size(), image.type() );
We observe that :mat_zeros:`Mat::zeros <>` returns a Matlab-style zero initializer based on *image.size()* and *image.type()*
#. Now, to perform the operation :math:`g(i,j) = \alpha \cdot f(i,j) + \beta` we will access to each pixel in image. Since we are operating with RGB images, we will have three values per pixel (R, G and B), so we will also access them separately. Here is the piece of code:
.. code-block:: cpp
for( int y = 0; y < image.rows; y++ )
{ for( int x = 0; x < image.cols; x++ )
{ for( int c = 0; c < 3; c++ )
{ new_image.at<Vec3b>(y,x)[c] = saturate_cast<uchar>( alpha*( image.at<Vec3b>(y,x)[c] ) + beta ); }
}
}
Notice the following:
* To access each pixel in the images we are using this syntax: *image.at<Vec3b>(y,x)[c]* where *y* is the row, *x* is the column and *c* is R, G or B (0, 1 or 2).
* Since the operation :math:`\alpha \cdot p(i,j) + \beta` can give values out of range or not integers (if :math:`\alpha` is float), we use :saturate_cast:`saturate_cast <>` to make sure the values are valid.
#. Finally, we create windows and show the images, the usual way.
.. code-block:: cpp
namedWindow("Original Image", 1);
namedWindow("New Image", 1);
imshow("Original Image", image);
imshow("New Image", new_image);
waitKey(0);
.. note::
Instead of using the **for** loops to access each pixel, we could have simply used this command:
.. code-block:: cpp
image.convertTo(new_image, -1, alpha, beta);
where :convert_to:`convertTo <>` would effectively perform *new_image = a*image + beta*. However, we wanted to show you how to access each pixel. In any case, both methods give the same result.
Result
=======
* Running our code and using :math:`\alpha = 2.2` and :math:`\beta = 50`
.. code-block:: bash
$ ./BasicLinearTransforms lena.png
Basic Linear Transforms
-------------------------
* Enter the alpha value [1.0-3.0]: 2.2
* Enter the beta value [0-100]: 50
* We get this:
.. image:: images/Basic_Linear_Transform_Tutorial_Result_0.png
:height: 400px
:alt: Basic Linear Transform - Final Result
:align: center

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.. _Display_Image:
Display an Image
*****************
Goal
=====
In this tutorial you will learn how to:
* Load an image using :imread:`imread <>`
* Create a named window (using :named_window:`namedWindow <>`)
* Display an image in an OpenCV window (using :imshow:`imshow <>`)
Code
=====
Here it is:
.. code-block:: cpp
#include <cv.h>
#include <highgui.h>
using namespace cv;
int main( int argc, char** argv )
{
Mat image;
image = imread( argv[1], 1 );
if( argc != 2 || !image.data )
{
printf( "No image data \n" );
return -1;
}
namedWindow( "Display Image", CV_WINDOW_AUTOSIZE );
imshow( "Display Image", image );
waitKey(0);
return 0;
}
Explanation
============
#. .. code-block:: cpp
#include <cv.h>
#include <highgui.h>
using namespace cv;
These are OpenCV headers:
* *cv.h* : Main OpenCV functions
* *highgui.h* : Graphical User Interface (GUI) functions
Now, let's analyze the *main* function:
#. .. code-block:: cpp
Mat image;
We create a Mat object to store the data of the image to load.
#. .. code-block:: cpp
image = imread( argv[1], 1 );
Here, we called the function :imread:`imread <>` which basically loads the image specified by the first argument (in this case *argv[1]*). The second argument is by default.
#. After checking that the image data was loaded correctly, we want to display our image, so we create a window:
.. code-block:: cpp
namedWindow( "Display Image", CV_WINDOW_AUTOSIZE );
:named_window:`namedWindow <>` receives as arguments the window name ("Display Image") and an additional argument that defines windows properties. In this case **CV_WINDOW_AUTOSIZE** indicates that the window will adopt the size of the image to be displayed.
#. Finally, it is time to show the image, for this we use :imshow:`imshow <>`
.. code-block:: cpp
imshow( "Display Image", image )
#. Finally, we want our window to be displayed until the user presses a key (otherwise the program would end far too quickly):
.. code-block:: cpp
waitKey(0);
We use the :wait_key:`waitKey <>` function, which allow us to wait for a keystroke during a number of milliseconds (determined by the argument). If the argument is zero, then it will wait indefinitely.
Result
=======
* Compile your code and then run the executable giving a image path as argument:
.. code-block:: bash
./DisplayImage HappyFish.jpg
* You should get a nice window as the one shown below:
.. image:: images/Display_Image_Tutorial_Result.png
:alt: Display Image Tutorial - Final Result
:align: center

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.. _Drawing_1:
Basic Drawing
****************
Result
=======
.. image:: images/Adding_Images_Tutorial_Result_0.png
:alt: Blending Images Tutorial - Final Result
:align: center

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.. _Drawing_2:
Fancy Drawing!
****************
Result
========

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.. _Linux_Eclipse_Usage:
Using OpenCV with Eclipse (plugin CDT)
****************************************
.. note::
For me at least, this works, is simple and quick. Suggestions are welcome
Prerequisites
===============
#. Having installed `Eclipse <http://www.eclipse.org/>`_ in your workstation (only the CDT plugin for C/C++ is needed). You can follow the following steps:
* Go to the Eclipse site
* Download `Eclipse IDE for C/C++ Developers <http://www.eclipse.org/downloads/packages/eclipse-ide-cc-developers/heliossr2>`_ . Choose the link according to your workstation.
#. Having installed OpenCV. If not yet, go :ref:`here <Linux_Installation>`
Making a project
=================
#. Start Eclipse. Just run the executable that comes in the folder.
#. Go to **File -> New -> C/C++ Project**
.. image:: images/Eclipse_Tutorial_Screenshot-0.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 0
:align: center
#. Choose a name for your project (i.e. DisplayImage). An **Empty Project** should be okay for this example.
.. image:: images/Eclipse_Tutorial_Screenshot-1.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 1
:align: center
#. Leave everything else by default. Press **Finish**.
.. image:: images/Eclipse_Tutorial_Screenshot-2.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 2
:align: center
#. Your project (in this case DisplayImage) should appear in the **Project Navigator** (usually at the left side of your window).
.. image:: images/Eclipse_Tutorial_Screenshot-3.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 3
:align: center
#. Now, let's add a source file using OpenCV:
* Right click on **DisplayImage** (in the Navigator). **New -> Folder** .
.. image:: images/Eclipse_Tutorial_Screenshot-4.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 4
:align: center
* Name your folder **src** and then hit **Finish**
.. image:: images/Eclipse_Tutorial_Screenshot-5.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 5
:align: center
* Right click on your newly created **src** folder. Choose **New source file**:
.. image:: images/Eclipse_Tutorial_Screenshot-6.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 6
:align: center
* Call it **DisplayImage.cpp**. Hit **Finish**
.. image:: images/Eclipse_Tutorial_Screenshot-7.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 7
:align: center
#. So, now you have a project with a empty .cpp file. Let's fill it with some sample code (in other words, copy and paste the snippet below):
.. code-block:: cpp
#include <cv.h>
#include <highgui.h>
using namespace cv;
int main( int argc, char** argv )
{
Mat image;
image = imread( argv[1], 1 );
if( argc != 2 || !image.data )
{
printf( "No image data \n" );
return -1;
}
namedWindow( "Display Image", CV_WINDOW_AUTOSIZE );
imshow( "Display Image", image );
waitKey(0);
return 0;
}
#. We are only missing one final step: To tell OpenCV where the OpenCV headers and libraries are. For this, do the following:
* Go to **Project-->Properties**
.. image:: images/Eclipse_Tutorial_Screenshot-8.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 8
:align: center
* In **C/C++ Build**, click on **Settings**. At the right, choose the **Tool Settings** Tab. Here we will enter the headers and libraries info:
a. In **GCC C++ Compiler**, go to **Includes**. In **Include paths(-l)** you should include the path of the folder where opencv was installed. In our example, this is:
::
/usr/local/include/opencv
.. image:: images/Eclipse_Tutorial_Screenshot-9.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 9
:align: center
.. note::
If you do not know where your opencv files are, open the **Terminal** and type:
.. code-block:: bash
pkg-config --cflags opencv
For instance, that command gave me this output:
.. code-block:: bash
-I/usr/local/include/opencv -I/usr/local/include
b. Now go to **GCC C++ Linker**,there you have to fill two spaces:
* In **Library search path (-L)** you have to write the path to where the opencv libraries reside, in my case the path is:
::
/usr/local/lib
* In **Libraries(-l)** add the OpenCV libraries that you may need. Usually just the 3 first on the list below are enough (for simple applications) . In my case, I am putting all of them since I plan to use the whole bunch:
* opencv_core
* opencv_imgproc
* opencv_highgui
* opencv_ml
* opencv_video
* opencv_features2d
* opencv_calib3d
* opencv_objdetect
* opencv_contrib
* opencv_legacy
* opencv_flann
.. image:: images/Eclipse_Tutorial_Screenshot-10.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 10
:align: center
.. note::
If you don't know where your libraries are (or you are just psychotic and want to make sure the path is fine), type in **Terminal**:
.. code-block:: bash
pkg-config --libs opencv
My output (in case you want to check) was:
.. code-block:: bash
-L/usr/local/lib -lopencv_core -lopencv_imgproc -lopencv_highgui -lopencv_ml -lopencv_video -lopencv_features2d -lopencv_calib3d -lopencv_objdetect -lopencv_contrib -lopencv_legacy -lopencv_flann
Now you are done. Click **OK**
* Your project should be ready to be built. For this, go to **Project->Build all**
.. image:: images/Eclipse_Tutorial_Screenshot-11.png
:height: 400px
:alt: Eclipse Tutorial Screenshot 11
:align: center
In the Console you should get something like
.. image:: images/Eclipse_Tutorial_Screenshot-12.png
:height: 200px
:alt: Eclipse Tutorial Screenshot 12
:align: center
If you check in your folder, there should be an executable there.
Running the executable
========================
So, now we have an executable ready to run. If we were to use the Terminal, we would probably do something like:
.. code-block:: bash
cd <DisplayImage_directory>
cd src
./DisplayImage ../images/HappyLittleFish.jpg
Assuming that the image to use as the argument would be located in <DisplayImage_directory>/images/HappyLittleFish.jpg. We can still do this, but let's do it from Eclipse:
#. Go to **Run->Run Configurations**
.. image:: images/Eclipse_Tutorial_Screenshot-13.png
:height: 300px
:alt: Eclipse Tutorial Screenshot 13
:align: center
#. Under C/C++ Application you will see the name of your executable + Debug (if not, click over C/C++ Application a couple of times). Select the name (in this case **DisplayImage Debug**).
#. Now, in the right side of the window, choose the **Arguments** Tab. Write the path of the image file we want to open (path relative to the workspace/DisplayImage folder). Let's use **HappyLittleFish.jpg**:
.. image:: images/Eclipse_Tutorial_Screenshot-14.png
:height: 300px
:alt: Eclipse Tutorial Screenshot 14
:align: center
#. Click on the **Apply** button and then in Run. An OpenCV window should pop up with the fish image (or whatever you used).
.. image:: images/Eclipse_Tutorial_Screenshot-15.png
:alt: Eclipse Tutorial Screenshot 15
:align: center
#. Congratulations! You are ready to have fun with OpenCV using Eclipse.

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.. _Linux_GCC_Usage:
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 <http://www.cmake.org/>`_. 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 <http://www.cmake.org/cmake/help/cmake_tutorial.html>`_ on its website.
Steps
======
Create a program using OpenCV
-------------------------------
Let's use a simple program such as DisplayImage.cpp shown below.
.. code-block:: cpp
#include <cv.h>
#include <highgui.h>
using namespace cv;
int main( int argc, char** argv )
{
Mat image;
image = imread( argv[1], 1 );
if( argc != 2 || !image.data )
{
printf( "No image data \n" );
return -1;
}
namedWindow( "Display Image", CV_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:
.. code-block:: cmake
project( DisplayImage )
find_package( OpenCV REQUIRED )
add_executable( DisplayImage DisplayImage )
target_link_libraries( DisplayImage ${OpenCV_LIBS} )
Generate the executable
-------------------------
This part is easy, just proceed as with any other project using CMake:
.. code-block:: bash
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.:
.. code-block:: bash
./DisplayImage lena.jpg
You should get a nice window as the one shown below:
.. image:: images/GCC_CMake_Example_Tutorial.png
:alt: Display Image - Lena
:align: center

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.. _Linux_Installation:
Installation in Linux
***********************
These steps have been tested for Ubuntu 10.04 but should work with other distros.
Required packages
==================
* GCC 4.x or later. This can be installed with
.. code-block:: bash
sudo apt-get install build-essential
* CMake 2.6 or higher
* Subversion (SVN) client
* GTK+2.x or higher, including headers
* pkgconfig
* libpng, zlib, libjpeg, libtiff, libjasper with development files (e.g. libpjeg-dev)
* Python 2.3 or later with developer packages (e.g. python-dev)
* SWIG 1.3.30 or later
* libavcodec
* libdc1394 2.x
All the libraries above can be installed via Terminal or by using Synaptic Manager
Getting OpenCV source code
============================
You can use the latest stable OpenCV version available in *sourceforge* or you can grab the latest snapshot from the SVN repository:
Getting the latest stable OpenCV version
------------------------------------------
* Go to http://sourceforge.net/projects/opencvlibrary
* Download the source tarball and unpack it
Getting the cutting-edge OpenCV from SourceForge SVN repository
-----------------------------------------------------------------
Launch SVN client and checkout either
a. the current OpenCV snapshot from here: https://code.ros.org/svn/opencv/trunk
#. or the latest tested OpenCV snapshot from here: http://code.ros.org/svn/opencv/tags/latest_tested_snapshot
In Ubuntu it can be done using the following command, e.g.:
.. code-block:: bash
cd ~/<my_working _directory>
svn co https://code.ros.org/svn/opencv/trunk
Building OpenCV from source using CMake, using the command line
================================================================
#. Create a temporary directory, which we denote as <cmake_binary_dir>, where you want to put the generated Makefiles, project files as well the object filees and output binaries
#. Enter the <cmake_binary_dir> and type
.. code-block:: bash
cmake [<some optional parameters>] <path to the OpenCV source directory>
For example
.. code-block:: bash
cd ~/opencv
mkdir release
cd release
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX= /usr/local
#. Enter the created temporary directory (<cmake_binary_dir>) and proceed with:
.. code-block:: bash
make
sudo make install

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@ -0,0 +1,122 @@
.. _Load_Save_Image:
Load and Save an Image
***********************
.. note::
We assume that by now you know:
* Load an image using :imread:`imread <>`
* Display an image in an OpenCV window (using :imshow:`imshow <>`)
Goals
======
In this tutorial you will learn how to:
* Transform an image from RGB to Grayscale format by using :cvt_color:`cvtColor <>`
* Save your transformed image in a file on disk (using :imwrite:`imwrite <>`)
Code
======
Here it is:
.. code-block:: cpp
:linenos:
#include <cv.h>
#include <highgui.h>
using namespace cv;
int main( int argc, char** argv )
{
char* imageName = argv[1];
Mat image;
image = imread( imageName, 1 );
if( argc != 2 || !image.data )
{
printf( " No image data \n " );
return -1;
}
Mat gray_image;
cvtColor( image, gray_image, CV_RGB2GRAY );
imwrite( "../../images/Gray_Image.png", gray_image );
namedWindow( imageName, CV_WINDOW_AUTOSIZE );
namedWindow( "Gray image", CV_WINDOW_AUTOSIZE );
imshow( imageName, image );
imshow( "Gray image", gray_image );
waitKey(0);
return 0;
}
Explanation
============
#. We begin by:
* Creating a Mat object to store the image information
* Load an image using :imread:`imread <>`, located in the path given by *imageName*. Fort this example, assume you are loading a RGB image.
#. Now we are going to convert our image from RGB to Grayscale format. OpenCV has a really nice function to do this kind of transformations:
.. code-block:: cpp
cvtColor( image, gray_image, CV_RGB2GRAY );
As you can see, :cvt_color:`cvtColor <>` takes as arguments:
* a source image (*image*)
* a destination image (*gray_image*), in which we will save the converted image.
And an additional parameter that indicates what kind of transformation will be performed. In this case we use **CV_RGB2GRAY** (self-explanatory).
#. 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 analagous to :imread:`imread <>`: :imwrite:`imwrite <>`
.. code-block:: cpp
imwrite( "../../images/Gray_Image.png", gray_image );
Which will save our *gray_image* as *Gray_Image.png* in the folder *images* located two levels up of my current location.
#. Finally, let's check out the images. We create 02 windows and use them to show the original image as well as the new one:
.. code-block:: cpp
namedWindow( imageName, CV_WINDOW_AUTOSIZE );
namedWindow( "Gray image", CV_WINDOW_AUTOSIZE );
imshow( imageName, image );
imshow( "Gray image", gray_image );
#. Add the usual *waitKey(0)* for the program to wait forever until the user presses a key.
Result
=======
When you run your program you should get something like this:
.. image:: images/Load_Save_Image_Result_1.png
:alt: Load Save Image Result 1
:height: 400px
:align: center
And if you check in your folder (in my case *images*), you should have a newly .png file named *Gray_Image.png*:
.. image:: images/Load_Save_Image_Result_2.png
:alt: Load Save Image Result 2
:height: 250px
:align: center
Congratulations, you are done with this tutorial!

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@ -3,8 +3,162 @@ OpenCV Tutorials
#################
.. toctree::
:maxdepth: 2
prerequisites.rst
features2d.rst
calib3d.rst
The following links describe a set of basic OpenCV tutorials. All the source code mentioned here is provide as part of the OpenCV regular releases, so check before you start copy & pasting the code. The list of tutorials below is automatically generated from reST files located in our SVN repository.
.. note::
YouTube videos yet to come...we have to think about them!
As always, we would be happy to hear your comments and receive your contributions on any tutorial.
* **INSTALLATION**
* :ref:`Linux_Installation`
=========== ======================================================
|Install_1| *Title:* **Installation steps in Linux**
*Compatibility:* > OpenCV 2.0
We will learn how to setup OpenCV in your computer!
=========== ======================================================
.. |Install_1| image:: images/ubuntu_logo.jpeg
:height: 120px
* **USAGE AND COMPILATION**
* :ref:`Linux_GCC_Usage`
=========== ======================================================
|Usage_1| *Title:* **Using OpenCV with gcc (and CMake)**
*Compatibility:* > OpenCV 2.0
We will learn how to compile your first project using gcc and CMake
=========== ======================================================
.. |Usage_1| image:: images/gccegg-65-2.png
:height: 120px
* :ref:`Linux_Eclipse_Usage`
=========== ======================================================
|Usage_2| *Title:* **Using OpenCV with Eclipse (CDT plugin)**
*Compatibility:* > OpenCV 2.0
We will learn how to compile your first project using the Eclipse environment
=========== ======================================================
.. |Usage_2| image:: images/eclipse_cpp_logo.jpeg
:height: 120px
* **BEGINNERS SECTION**
* :ref:`Display_Image`
=============== ======================================================
|Beginners_1| *Title:* **Display an Image**
*Compatibility:* > OpenCV 2.0
We will learn how to display an image using OpenCV
=============== ======================================================
.. |Beginners_1| image:: images/Display_Image_Tutorial_Result.png
:height: 150px
* :ref:`Load_Save_Image`
=============== ======================================================
|Beginners_2| *Title:* **Load and save an Image**
*Compatibility:* > OpenCV 2.0
We will learn how to save an Image in OpenCV...plus a small conversion to grayscale
=============== ======================================================
.. |Beginners_2| image:: images/Load_Save_Image_Result_1.png
:height: 150px
* :ref:`Basic_Linear_Transform`
=============== ======================================================
|Beginners_3| *Title:* **Changing the contrast and brightness of an image**
*Compatibility:* > OpenCV 2.0
We will learn how to change our image appearance!
=============== ======================================================
.. |Beginners_3| image:: images/Basic_Linear_Transform_Tutorial_Result_0.png
:height: 200px
* :ref:`Adding_Images`
=============== ======================================================
|Beginners_4| *Title:* **Linear Blending**
*Compatibility:* > OpenCV 2.0
We will learn how to blend two images!
=============== ======================================================
.. |Beginners_4| image:: images/Adding_Images_Tutorial_Result_0.png
:height: 200px
* :ref:`Adding_Trackbars`
=============== ======================================================
|Beginners_5| *Title:* **Creating Trackbars**
*Compatibility:* > OpenCV 2.0
We will learn how to add a Trackbar to our applications
=============== ======================================================
.. |Beginners_5| image:: images/Adding_Trackbars_Tutorial_Cover.png
:height: 200px
* :ref:`Drawing_1`
=============== ======================================================
|Beginners_6| *Title:* **Basic Drawing**
*Compatibility:* > OpenCV 2.0
We will learn how to draw simple geometry with OpenCV!
=============== ======================================================
.. |Beginners_6| image:: images/Drawing_1_Tutorial_Result_0.png
:height: 200px
* :ref:`Drawing_2`
=============== ======================================================
|Beginners_7| *Title:* **Cool Drawing**
*Compatibility:* > OpenCV 2.0
We will draw some *fancy-looking* stuff using OpenCV!
=============== ======================================================
.. |Beginners_7| image:: images/Drawing_1_Tutorial_Result_0.png
:height: 200px