--- /dev/null
+.. _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
--- /dev/null
+.. _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
+
+
+
+
+
--- /dev/null
+.. _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
--- /dev/null
+.. _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
--- /dev/null
+.. _Drawing_1:
+
+Basic Drawing
+****************
+
+
+Result
+=======
+
+.. image:: images/Adding_Images_Tutorial_Result_0.png
+ :alt: Blending Images Tutorial - Final Result
+ :align: center
--- /dev/null
+.. _Drawing_2:
+
+Fancy Drawing!
+****************
+
+Result
+========
--- /dev/null
+.. _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.
--- /dev/null
+.. _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
+
--- /dev/null
+.. _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
+
+
--- /dev/null
+.. _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!
#################
.. 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
projects / platform / upstream / opencv.git / commitdiff
