Merge pull request #9406 from Cartucho:update_core_tutorials

doc/tutorials/core/adding_images/adding_images.markdown

 Adding (blending) two images using OpenCV {#tutorial_adding_images}
 =========================================
 
+@prev_tutorial{tutorial_mat_operations}
+@next_tutorial{tutorial_basic_linear_transform}
+
 Goal
 ----
 
 In this tutorial you will learn:
 
 -   what is *linear blending* and why it is useful;
--   how to add two images using @ref cv::addWeighted
+-   how to add two images using **addWeighted()**
 
 Theory
 ------
@@ -28,33 +31,83 @@ eh?)
 Source Code
 -----------
 
+@add_toggle_cpp
 Download the source code from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/AddingImages/AddingImages.cpp).
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/core/AddingImages/AddingImages.cpp).
 @include cpp/tutorial_code/core/AddingImages/AddingImages.cpp
+@end_toggle
+
+@add_toggle_java
+Download the source code from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/core/AddingImages/AddingImages.java).
+@include java/tutorial_code/core/AddingImages/AddingImages.java
+@end_toggle
+
+@add_toggle_python
+Download the source code from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/core/AddingImages/adding_images.py).
+@include python/tutorial_code/core/AddingImages/adding_images.py
+@end_toggle
 
 Explanation
 -----------
 
--#  Since we are going to perform:
+Since we are going to perform:
+
+\f[g(x) = (1 - \alpha)f_{0}(x) + \alpha f_{1}(x)\f]
+
+We need two source images (\f$f_{0}(x)\f$ and \f$f_{1}(x)\f$). So, we load them in the usual way:
+@add_toggle_cpp
+@snippet cpp/tutorial_code/core/AddingImages/AddingImages.cpp load
+@end_toggle
+
+@add_toggle_java
+@snippet java/tutorial_code/core/AddingImages/AddingImages.java load
+@end_toggle
+
+@add_toggle_python
+@snippet python/tutorial_code/core/AddingImages/adding_images.py load
+@end_toggle
+
+We used the following images: [LinuxLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/LinuxLogo.jpg) and [WindowsLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/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 `g(x)` image. For this, the function **addWeighted()** comes quite handy:
+
+@add_toggle_cpp
+@snippet cpp/tutorial_code/core/AddingImages/AddingImages.cpp blend_images
+@end_toggle
 
-    \f[g(x) = (1 - \alpha)f_{0}(x) + \alpha f_{1}(x)\f]
+@add_toggle_java
+@snippet java/tutorial_code/core/AddingImages/AddingImages.java blend_images
+@end_toggle
 
-    We need two source images (\f$f_{0}(x)\f$ and \f$f_{1}(x)\f$). So, we load them in the usual way:
-    @snippet cpp/tutorial_code/core/AddingImages/AddingImages.cpp load
+@add_toggle_python
+@snippet python/tutorial_code/core/AddingImages/adding_images.py blend_images
+Numpy version of above line (but cv2 function is around 2x faster):
+\code{.py}
+    dst = np.uint8(alpha*(img1)+beta*(img2))
+\endcode
+@end_toggle
 
-    **warning**
+since **addWeighted()**  produces:
+\f[dst = \alpha \cdot src1 + \beta \cdot src2 + \gamma\f]
+In this case, `gamma` is the argument \f$0.0\f$ in the code above.
 
-    Since we are *adding* *src1* and *src2*, they both have to be of the same size (width and
-    height) and type.
+Create windows, show the images and wait for the user to end the program.
+@add_toggle_cpp
+@snippet cpp/tutorial_code/core/AddingImages/AddingImages.cpp display
+@end_toggle
 
--#  Now we need to generate the `g(x)` image. For this, the function @ref cv::addWeighted comes quite handy:
-    @snippet cpp/tutorial_code/core/AddingImages/AddingImages.cpp blend_images
-    since @ref cv::addWeighted  produces:
-    \f[dst = \alpha \cdot src1 + \beta \cdot src2 + \gamma\f]
-    In this case, `gamma` is the argument \f$0.0\f$ in the code above.
+@add_toggle_java
+@snippet java/tutorial_code/core/AddingImages/AddingImages.java display
+@end_toggle
 
--#  Create windows, show the images and wait for the user to end the program.
-    @snippet cpp/tutorial_code/core/AddingImages/AddingImages.cpp display
+@add_toggle_python
+@snippet python/tutorial_code/core/AddingImages/adding_images.py display
+@end_toggle
 
 Result
 ------

doc/tutorials/core/mat-mask-operations/mat_mask_operations.markdown

@@ -28,24 +28,39 @@ the zero-zero index) on the pixel you want to calculate and sum up the pixel val
 the overlapped matrix values. It's the same thing, however in case of large matrices the latter
 notation is a lot easier to look over.
 
+Code
+----
+
 @add_toggle_cpp
-Now let us see how we can make this happen by using the basic pixel access method or by using the
-@ref cv::filter2D function.
+You can download this source code from [here
+](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
+OpenCV source code libraries sample directory at
+`samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp`.
+@include samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp
 @end_toggle
 
 @add_toggle_java
-Now let us see how we can make this happen by using the basic pixel access method or by using the
-**Imgproc.filter2D()** function.
+You can download this source code from [here
+](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java) or look in the
+OpenCV source code libraries sample directory at
+`samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java`.
+@include samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java
 @end_toggle
 
 @add_toggle_python
-Now let us see how we can make this happen by using the basic pixel access method or by using the
-**cv2.filter2D()** function.
+You can download this source code from [here
+](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py) or look in the
+OpenCV source code libraries sample directory at
+`samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py`.
+@include samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py
 @end_toggle
 
 The Basic Method
 ----------------
 
+Now let us see how we can make this happen by using the basic pixel access method or by using the
+**filter2D()** function.
+
 Here's a function that will do this:
 @add_toggle_cpp
 @snippet samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp basic_method
@@ -132,37 +147,38 @@ The filter2D function
 Applying such filters are so common in image processing that in OpenCV there exist a function that
 will take care of applying the mask (also called a kernel in some places). For this you first need
 to define an object that holds the mask:
+
 @add_toggle_cpp
 @snippet samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp kern
-
-Then call the @ref cv::filter2D function specifying the input, the output image and the kernel to
-use:
-@snippet samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp filter2D
-
-The function even has a fifth optional argument to specify the center of the kernel, a sixth
-for adding an optional value to the filtered pixels before storing them in K and a seventh one
-for determining what to do in the regions where the operation is undefined (borders).
 @end_toggle
 
 @add_toggle_java
 @snippet samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java kern
-
-Then call the **Imgproc.filter2D()** function specifying the input, the output image and the kernel to
-use:
-@snippet samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java filter2D
-The function even has a fifth optional argument to specify the center of the kernel, a sixth
-for adding an optional value to the filtered pixels before storing them in K and a seventh one
-for determining what to do in the regions where the operation is undefined (borders).
 @end_toggle
 
 @add_toggle_python
 @snippet samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py kern
+@end_toggle
 
-Then call the **cv2.filter2D()** function specifying the input, the output image and the kernell to
+Then call the **filter2D()** function specifying the input, the output image and the kernel to
 use:
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp filter2D
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java filter2D
+@end_toggle
+
+@add_toggle_python
 @snippet samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py filter2D
 @end_toggle
 
+The function even has a fifth optional argument to specify the center of the kernel, a sixth
+for adding an optional value to the filtered pixels before storing them in K and a seventh one
+for determining what to do in the regions where the operation is undefined (borders).
+
 This function is shorter, less verbose and, because there are some optimizations, it is usually faster
 than the *hand-coded method*. For example in my test while the second one took only 13
 milliseconds the first took around 31 milliseconds. Quite some difference.
@@ -172,22 +188,7 @@ For example:
 ![](images/resultMatMaskFilter2D.png)
 
 @add_toggle_cpp
-You can download this source code from [here
-](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
-OpenCV source code libraries sample directory at
-`samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp`.
-
 Check out an instance of running the program on our [YouTube
 channel](http://www.youtube.com/watch?v=7PF1tAU9se4) .
 @youtube{7PF1tAU9se4}
 @end_toggle
-
-@add_toggle_java
-You can look in the OpenCV source code libraries sample directory at
-`samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java`.
-@end_toggle
-
-@add_toggle_python
-You can look in the OpenCV source code libraries sample directory at
-`samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py`.
-@end_toggle

doc/tutorials/core/table_of_content_core.markdown

@@ -40,6 +40,8 @@ understanding how to manipulate the images on a pixel level.
 
 -   @subpage tutorial_adding_images
 
+    *Languages:* C++, Java, Python
+
     *Compatibility:* \> OpenCV 2.0
 
     *Author:* Ana Huamán
@@ -56,6 +58,8 @@ understanding how to manipulate the images on a pixel level.
 
 -   @subpage tutorial_basic_geometric_drawing
 
+    *Languages:* C++, Java, Python
+
     *Compatibility:* \> OpenCV 2.0
 
     *Author:* Ana Huamán
@@ -72,6 +76,8 @@ understanding how to manipulate the images on a pixel level.
 
 -   @subpage tutorial_discrete_fourier_transform
 
+    *Languages:* C++, Java, Python
+
     *Compatibility:* \> OpenCV 2.0
 
     *Author:* Bernát Gábor

samples/cpp/tutorial_code/core/AddingImages/AddingImages.cpp

@@ -3,7 +3,6 @@
  * @brief Simple linear blender ( dst = alpha*src1 + beta*src2 )
  * @author OpenCV team
  */
-
 #include "opencv2/imgcodecs.hpp"
 #include "opencv2/highgui.hpp"
 #include <iostream>
@@ -24,7 +23,7 @@ int main( void )
    /// Ask the user enter alpha
    cout << " Simple Linear Blender " << endl;
    cout << "-----------------------" << endl;
-   cout << "* Enter alpha [0-1]: ";
+   cout << "* Enter alpha [0.0-1.0]: ";
    cin >> input;
 
    // We use the alpha provided by the user if it is between 0 and 1

samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp

 /**
  * @file Drawing_1.cpp
- * @brief Simple sample code
+ * @brief Simple geometric drawing
+ * @author OpenCV team
  */
-
 #include <opencv2/core.hpp>
 #include <opencv2/imgproc.hpp>
 #include <opencv2/highgui.hpp>
@@ -83,11 +83,11 @@ int main( void ){
 
 /// Function Declaration
 
-//![myellipse]
 /**
  * @function MyEllipse
  * @brief Draw a fixed-size ellipse with different angles
  */
+//![my_ellipse]
 void MyEllipse( Mat img, double angle )
 {
   int thickness = 2;
@@ -103,13 +103,13 @@ void MyEllipse( Mat img, double angle )
        thickness,
        lineType );
 }
-//![myellipse]
+//![my_ellipse]
 
-//![myfilledcircle]
 /**
  * @function MyFilledCircle
  * @brief Draw a fixed-size filled circle
  */
+//![my_filled_circle]
 void MyFilledCircle( Mat img, Point center )
 {
   circle( img,
@@ -119,13 +119,13 @@ void MyFilledCircle( Mat img, Point center )
       FILLED,
       LINE_8 );
 }
-//![myfilledcircle]
+//![my_filled_circle]
 
-//![mypolygon]
 /**
  * @function MyPolygon
  * @brief Draw a simple concave polygon (rook)
  */
+//![my_polygon]
 void MyPolygon( Mat img )
 {
   int lineType = LINE_8;
@@ -163,17 +163,18 @@ void MyPolygon( Mat img )
         Scalar( 255, 255, 255 ),
         lineType );
 }
-//![mypolygon]
+//![my_polygon]
 
-//![myline]
 /**
  * @function MyLine
  * @brief Draw a simple line
  */
+//![my_line]
 void MyLine( Mat img, Point start, Point end )
 {
   int thickness = 2;
   int lineType = LINE_8;
+
   line( img,
     start,
     end,
@@ -181,4 +182,4 @@ void MyLine( Mat img, Point start, Point end )
     thickness,
     lineType );
 }
-//![myline]
+//![my_line]

samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp

@@ -8,45 +8,58 @@
 using namespace cv;
 using namespace std;
 
-static void help(char* progName)
+static void help(void)
 {
     cout << endl
         <<  "This program demonstrated the use of the discrete Fourier transform (DFT). " << endl
         <<  "The dft of an image is taken and it's power spectrum is displayed."          << endl
         <<  "Usage:"                                                                      << endl
-        << progName << " [image_name -- default ../data/lena.jpg] "               << endl << endl;
+        <<  "./discrete_fourier_transform [image_name -- default ../data/lena.jpg]"       << endl;
 }
 
 int main(int argc, char ** argv)
 {
-    help(argv[0]);
+    help();
 
     const char* filename = argc >=2 ? argv[1] : "../data/lena.jpg";
 
     Mat I = imread(filename, IMREAD_GRAYSCALE);
-    if( I.empty())
+    if( I.empty()){
+        cout << "Error opening image" << endl;
         return -1;
+    }
 
+//! [expand]
     Mat padded;                            //expand input image to optimal size
     int m = getOptimalDFTSize( I.rows );
     int n = getOptimalDFTSize( I.cols ); // on the border add zero values
     copyMakeBorder(I, padded, 0, m - I.rows, 0, n - I.cols, BORDER_CONSTANT, Scalar::all(0));
+//! [expand]
 
+//! [complex_and_real]
     Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)};
     Mat complexI;
     merge(planes, 2, complexI);         // Add to the expanded another plane with zeros
+//! [complex_and_real]
 
+//! [dft]
     dft(complexI, complexI);            // this way the result may fit in the source matrix
+//! [dft]
 
     // compute the magnitude and switch to logarithmic scale
     // => log(1 + sqrt(Re(DFT(I))^2 + Im(DFT(I))^2))
+//! [magnitude]
     split(complexI, planes);                   // planes[0] = Re(DFT(I), planes[1] = Im(DFT(I))
     magnitude(planes[0], planes[1], planes[0]);// planes[0] = magnitude
     Mat magI = planes[0];
+//! [magnitude]
 
+//! [log]
     magI += Scalar::all(1);                    // switch to logarithmic scale
     log(magI, magI);
+//! [log]
 
+//! [crop_rearrange]
     // crop the spectrum, if it has an odd number of rows or columns
     magI = magI(Rect(0, 0, magI.cols & -2, magI.rows & -2));
 
@@ -67,9 +80,12 @@ int main(int argc, char ** argv)
     q1.copyTo(tmp);                    // swap quadrant (Top-Right with Bottom-Left)
     q2.copyTo(q1);
     tmp.copyTo(q2);
+//! [crop_rearrange]
 
+//! [normalize]
     normalize(magI, magI, 0, 1, NORM_MINMAX); // Transform the matrix with float values into a
                                             // viewable image form (float between values 0 and 1).
+//! [normalize]
 
     imshow("Input Image"       , I   );    // Show the result
     imshow("spectrum magnitude", magI);

samples/java/tutorial_code/core/AddingImages/AddingImages.java

+import org.opencv.core.*;
+import org.opencv.highgui.HighGui;
+import org.opencv.imgcodecs.Imgcodecs;
+
+import java.util.Locale;
+import java.util.Scanner;
+
+class AddingImagesRun{
+    public void run() {
+        double alpha = 0.5; double beta; double input;
+
+        Mat src1, src2, dst = new Mat();
+
+        System.out.println(" Simple Linear Blender ");
+        System.out.println("-----------------------");
+        System.out.println("* Enter alpha [0.0-1.0]: ");
+        Scanner scan = new Scanner( System.in ).useLocale(Locale.US);
+        input = scan.nextDouble();
+
+        if( input >= 0.0 && input <= 1.0 )
+            alpha = input;
+
+        //! [load]
+        src1 = Imgcodecs.imread("../../images/LinuxLogo.jpg");
+        src2 = Imgcodecs.imread("../../images/WindowsLogo.jpg");
+        //! [load]
+
+        if( src1.empty() == true ){ System.out.println("Error loading src1"); return;}
+        if( src2.empty() == true ){ System.out.println("Error loading src2"); return;}
+
+        //! [blend_images]
+        beta = ( 1.0 - alpha );
+        Core.addWeighted( src1, alpha, src2, beta, 0.0, dst);
+        //! [blend_images]
+
+        //![display]
+        HighGui.imshow("Linear Blend", dst);
+        HighGui.waitKey(0);
+        //![display]
+
+        System.exit(0);
+    }
+}
+
+public class AddingImages {
+    public static void main(String[] args) {
+        // Load the native library.
+        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
+        new AddingImagesRun().run();
+    }
+}

samples/java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java

+import org.opencv.core.*;
+import org.opencv.core.Point;
+import org.opencv.highgui.HighGui;
+import org.opencv.imgproc.Imgproc;
+
+import java.util.*;
+import java.util.List;
+
+class GeometricDrawingRun{
+
+    private static final int W = 400;
+
+    public void run(){
+        //! [create_images]
+        /// Windows names
+        String atom_window = "Drawing 1: Atom";
+        String rook_window = "Drawing 2: Rook";
+
+        /// Create black empty images
+        Mat atom_image = Mat.zeros( W, W, CvType.CV_8UC3 );
+        Mat rook_image = Mat.zeros( W, W, CvType.CV_8UC3 );
+        //! [create_images]
+
+        //! [draw_atom]
+        /// 1. Draw a simple atom:
+        /// -----------------------
+        MyEllipse( atom_image, 90.0 );
+        MyEllipse( atom_image, 0.0 );
+        MyEllipse( atom_image, 45.0 );
+        MyEllipse( atom_image, -45.0 );
+
+        /// 1.b. Creating circles
+        MyFilledCircle( atom_image, new Point( W/2, W/2) );
+        //! [draw_atom]
+
+        //! [draw_rook]
+        /// 2. Draw a rook
+        /// ------------------
+        /// 2.a. Create a convex polygon
+        MyPolygon( rook_image );
+
+        //! [rectangle]
+        /// 2.b. Creating rectangles
+        Imgproc.rectangle( rook_image,
+                new Point( 0, 7*W/8 ),
+                new Point( W, W),
+                new Scalar( 0, 255, 255 ),
+                -1,
+                8,
+                0 );
+        //! [rectangle]
+
+        /// 2.c. Create a few lines
+        MyLine( rook_image, new Point( 0, 15*W/16 ), new Point( W, 15*W/16 ) );
+        MyLine( rook_image, new Point( W/4, 7*W/8 ), new Point( W/4, W ) );
+        MyLine( rook_image, new Point( W/2, 7*W/8 ), new Point( W/2, W ) );
+        MyLine( rook_image, new Point( 3*W/4, 7*W/8 ), new Point( 3*W/4, W ) );
+        //! [draw_rook]
+
+        /// 3. Display your stuff!
+        HighGui.imshow( atom_window, atom_image );
+        HighGui.moveWindow( atom_window, 0, 200 );
+        HighGui.imshow( rook_window, rook_image );
+        HighGui.moveWindow( rook_window, W, 200 );
+
+        HighGui.waitKey( 0 );
+        System.exit(0);
+    }
+
+    /// Function Declaration
+
+    /**
+     * @function MyEllipse
+     * @brief Draw a fixed-size ellipse with different angles
+     */
+    //! [my_ellipse]
+    private void MyEllipse( Mat img, double angle ) {
+        int thickness = 2;
+        int lineType = 8;
+        int shift = 0;
+
+        Imgproc.ellipse( img,
+                new Point( W/2, W/2 ),
+                new Size( W/4, W/16 ),
+                angle,
+                0.0,
+                360.0,
+                new Scalar( 255, 0, 0 ),
+                thickness,
+                lineType,
+                shift );
+    }
+    //! [my_ellipse]
+    /**
+     * @function MyFilledCircle
+     * @brief Draw a fixed-size filled circle
+     */
+    //! [my_filled_circle]
+    private void MyFilledCircle( Mat img, Point center ) {
+        int thickness = -1;
+        int lineType = 8;
+        int shift = 0;
+
+        Imgproc.circle( img,
+                center,
+                W/32,
+                new Scalar( 0, 0, 255 ),
+                thickness,
+                lineType,
+                shift );
+    }
+    //! [my_filled_circle]
+    /**
+     * @function MyPolygon
+     * @function Draw a simple concave polygon (rook)
+     */
+    //! [my_polygon]
+    private void MyPolygon( Mat img ) {
+        int lineType = 8;
+        int shift = 0;
+
+        /** Create some points */
+        Point[] rook_points = new Point[20];
+        rook_points[0]  = new Point(     W/4, 7*W/8   );
+        rook_points[1]  = new Point(   3*W/4, 7*W/8   );
+        rook_points[2]  = new Point(   3*W/4, 13*W/16 );
+        rook_points[3]  = new Point( 11*W/16, 13*W/16 );
+        rook_points[4]  = new Point( 19*W/32, 3*W/8   );
+        rook_points[5]  = new Point(   3*W/4, 3*W/8   );
+        rook_points[6]  = new Point(   3*W/4, W/8     );
+        rook_points[7]  = new Point( 26*W/40, W/8     );
+        rook_points[8]  = new Point( 26*W/40, W/4     );
+        rook_points[9]  = new Point( 22*W/40, W/4     );
+        rook_points[10] = new Point( 22*W/40, W/8     );
+        rook_points[11] = new Point( 18*W/40, W/8     );
+        rook_points[12] = new Point( 18*W/40, W/4     );
+        rook_points[13] = new Point( 14*W/40, W/4     );
+        rook_points[14] = new Point( 14*W/40, W/8     );
+        rook_points[15] = new Point(     W/4, W/8     );
+        rook_points[16] = new Point(     W/4, 3*W/8   );
+        rook_points[17] = new Point( 13*W/32, 3*W/8   );
+        rook_points[18] = new Point(  5*W/16, 13*W/16 );
+        rook_points[19] = new Point(     W/4, 13*W/16 );
+
+        MatOfPoint matPt = new MatOfPoint();
+        matPt.fromArray(rook_points);
+
+        List<MatOfPoint> ppt = new ArrayList<MatOfPoint>();
+        ppt.add(matPt);
+
+        Imgproc.fillPoly(img,
+                ppt,
+                new Scalar( 255, 255, 255 ),
+                lineType,
+                shift,
+                new Point(0,0) );
+    }
+    //! [my_polygon]
+    /**
+     * @function MyLine
+     * @brief Draw a simple line
+     */
+    //! [my_line]
+    private void MyLine( Mat img, Point start, Point end ) {
+        int thickness = 2;
+        int lineType = 8;
+        int shift = 0;
+
+        Imgproc.line( img,
+                start,
+                end,
+                new Scalar( 0, 0, 0 ),
+                thickness,
+                lineType,
+                shift );
+    }
+    //! [my_line]
+}
+
+public class BasicGeometricDrawing {
+    public static void main(String[] args) {
+        // Load the native library.
+        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
+        new GeometricDrawingRun().run();
+    }
+}

samples/java/tutorial_code/core/discrete_fourier_transform/DiscreteFourierTransform.java

+import org.opencv.core.*;
+import org.opencv.highgui.HighGui;
+import org.opencv.imgcodecs.Imgcodecs;
+
+import java.util.List;
+import java.util.*;
+
+class DiscreteFourierTransformRun{
+    private void help() {
+        System.out.println("" +
+                "This program demonstrated the use of the discrete Fourier transform (DFT). \n" +
+                "The dft of an image is taken and it's power spectrum is displayed.\n" +
+                "Usage:\n" +
+                "./DiscreteFourierTransform [image_name -- default ../data/lena.jpg]");
+    }
+
+    public void run(String[] args){
+
+        help();
+
+        String filename = ((args.length > 0) ? args[0] : "../data/lena.jpg");
+
+        Mat I = Imgcodecs.imread(filename, Imgcodecs.IMREAD_GRAYSCALE);
+        if( I.empty() ) {
+            System.out.println("Error opening image");
+            System.exit(-1);
+        }
+
+        //! [expand]
+        Mat padded = new Mat();                     //expand input image to optimal size
+        int m = Core.getOptimalDFTSize( I.rows() );
+        int n = Core.getOptimalDFTSize( I.cols() ); // on the border add zero values
+        Core.copyMakeBorder(I, padded, 0, m - I.rows(), 0, n - I.cols(), Core.BORDER_CONSTANT, Scalar.all(0));
+        //! [expand]
+
+        //! [complex_and_real]
+        List<Mat> planes = new ArrayList<Mat>();
+        padded.convertTo(padded, CvType.CV_32F);
+        planes.add(padded);
+        planes.add(Mat.zeros(padded.size(), CvType.CV_32F));
+        Mat complexI = new Mat();
+        Core.merge(planes, complexI);         // Add to the expanded another plane with zeros
+        //! [complex_and_real]
+
+        //! [dft]
+        Core.dft(complexI, complexI);         // this way the result may fit in the source matrix
+        //! [dft]
+
+        // compute the magnitude and switch to logarithmic scale
+        // => log(1 + sqrt(Re(DFT(I))^2 + Im(DFT(I))^2))
+        //! [magnitude]
+        Core.split(complexI, planes);                               // planes.get(0) = Re(DFT(I)
+                                                                    // planes.get(1) = Im(DFT(I))
+        Core.magnitude(planes.get(0), planes.get(1), planes.get(0));// planes.get(0) = magnitude
+        Mat magI = planes.get(0);
+        //! [magnitude]
+
+        //! [log]
+        Mat matOfOnes = Mat.ones(magI.size(), magI.type());
+        Core.add(matOfOnes, magI, magI);         // switch to logarithmic scale
+        Core.log(magI, magI);
+        //! [log]
+
+        //! [crop_rearrange]
+        // crop the spectrum, if it has an odd number of rows or columns
+        magI = magI.submat(new Rect(0, 0, magI.cols() & -2, magI.rows() & -2));
+
+        // rearrange the quadrants of Fourier image  so that the origin is at the image center
+        int cx = magI.cols()/2;
+        int cy = magI.rows()/2;
+
+        Mat q0 = new Mat(magI, new Rect(0, 0, cx, cy));   // Top-Left - Create a ROI per quadrant
+        Mat q1 = new Mat(magI, new Rect(cx, 0, cx, cy));  // Top-Right
+        Mat q2 = new Mat(magI, new Rect(0, cy, cx, cy));  // Bottom-Left
+        Mat q3 = new Mat(magI, new Rect(cx, cy, cx, cy)); // Bottom-Right
+
+        Mat tmp = new Mat();               // swap quadrants (Top-Left with Bottom-Right)
+        q0.copyTo(tmp);
+        q3.copyTo(q0);
+        tmp.copyTo(q3);
+
+        q1.copyTo(tmp);                    // swap quadrant (Top-Right with Bottom-Left)
+        q2.copyTo(q1);
+        tmp.copyTo(q2);
+        //! [crop_rearrange]
+
+        magI.convertTo(magI, CvType.CV_8UC1);
+        //! [normalize]
+        Core.normalize(magI, magI, 0, 255, Core.NORM_MINMAX, CvType.CV_8UC1); // Transform the matrix with float values
+                                                                            // into a viewable image form (float between
+                                                                            // values 0 and 255).
+        //! [normalize]
+
+        HighGui.imshow("Input Image"       , I   );    // Show the result
+        HighGui.imshow("Spectrum Magnitude", magI);
+        HighGui.waitKey();
+
+        System.exit(0);
+    }
+}
+
+
+public class DiscreteFourierTransform {
+    public static void main(String[] args) {
+        // Load the native library.
+        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
+        new DiscreteFourierTransformRun().run(args);
+    }
+}

samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java

@@ -2,14 +2,10 @@ import org.opencv.core.Core;
 import org.opencv.core.CvType;
 import org.opencv.core.Mat;
 import org.opencv.core.Scalar;
+import org.opencv.highgui.HighGui;
 import org.opencv.imgcodecs.Imgcodecs;
 import org.opencv.imgproc.Imgproc;
 
-import javax.swing.*;
-import java.awt.*;
-import java.awt.image.BufferedImage;
-import java.awt.image.DataBufferByte;
-
 class MatMaskOperationsRun {
 
     public void run(String[] args) {
@@ -31,8 +27,10 @@ class MatMaskOperationsRun {
             System.exit(-1);
         }
 
-        Image img = toBufferedImage(src);
-        displayImage("Input", img, 0, 200);
+        HighGui.namedWindow("Input", HighGui.WINDOW_AUTOSIZE);
+        HighGui.namedWindow("Output", HighGui.WINDOW_AUTOSIZE);
+
+        HighGui.imshow( "Input", src );
         double t = System.currentTimeMillis();
 
         Mat dst0 = sharpen(src, new Mat());
@@ -40,8 +38,9 @@ class MatMaskOperationsRun {
         t = ((double) System.currentTimeMillis() - t) / 1000;
         System.out.println("Hand written function time passed in seconds: " + t);
 
-        Image img2 = toBufferedImage(dst0);
-        displayImage("Output", img2, 400, 400);
+        HighGui.imshow( "Output", dst0 );
+        HighGui.moveWindow("Output", 400, 400);
+        HighGui.waitKey();
 
         //![kern]
         Mat kern = new Mat(3, 3, CvType.CV_8S);
@@ -58,8 +57,10 @@ class MatMaskOperationsRun {
         t = ((double) System.currentTimeMillis() - t) / 1000;
         System.out.println("Built-in filter2D time passed in seconds:     " + t);
 
-        Image img3 = toBufferedImage(dst1);
-        displayImage("Output", img3, 800, 400);
+        HighGui.imshow( "Output", dst1 );
+
+        HighGui.waitKey();
+        System.exit(0);
     }
 
     //! [basic_method]
@@ -108,38 +109,12 @@ class MatMaskOperationsRun {
         return Result;
     }
     //! [basic_method]
-
-    public Image toBufferedImage(Mat m) {
-        int type = BufferedImage.TYPE_BYTE_GRAY;
-        if (m.channels() > 1) {
-            type = BufferedImage.TYPE_3BYTE_BGR;
-        }
-        int bufferSize = m.channels() * m.cols() * m.rows();
-        byte[] b = new byte[bufferSize];
-        m.get(0, 0, b); // get all the pixels
-        BufferedImage image = new BufferedImage(m.cols(), m.rows(), type);
-        final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
-        System.arraycopy(b, 0, targetPixels, 0, b.length);
-        return image;
-    }
-
-    public void displayImage(String title, Image img, int x, int y) {
-        ImageIcon icon = new ImageIcon(img);
-        JFrame frame = new JFrame(title);
-        JLabel lbl = new JLabel(icon);
-        frame.add(lbl);
-        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
-        frame.pack();
-        frame.setLocation(x, y);
-        frame.setVisible(true);
-    }
 }
 
 public class MatMaskOperations {
     public static void main(String[] args) {
         // Load the native library.
         System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
-
-        new MatMaskOperationsRun().run(args); // run code
+        new MatMaskOperationsRun().run(args);
     }
 }

samples/python/tutorial_code/core/AddingImages/adding_images.py

+from __future__ import print_function
+import sys
+
+import cv2
+
+alpha = 0.5
+
+print(''' Simple Linear Blender
+-----------------------
+* Enter alpha [0.0-1.0]: ''')
+if sys.version_info >= (3, 0): # If Python 3.x
+    input_alpha = float(input())
+else:
+    input_alpha = float(raw_input())
+if 0 <= alpha <= 1:
+    alpha = input_alpha
+## [load]
+src1 = cv2.imread('../../../../data/LinuxLogo.jpg')
+src2 = cv2.imread('../../../../data/WindowsLogo.jpg')
+## [load]
+if src1 is None:
+    print ("Error loading src1")
+    exit(-1)
+elif src2 is None:
+    print ("Error loading src2")
+    exit(-1)
+## [blend_images]
+beta = (1.0 - alpha)
+dst = cv2.addWeighted(src1, alpha, src2, beta, 0.0)
+## [blend_images]
+## [display]
+cv2.imshow('dst', dst)
+cv2.waitKey(0)
+## [display]
+cv2.destroyAllWindows()

samples/python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py

+import cv2
+import numpy as np
+
+W = 400
+## [my_ellipse]
+def my_ellipse(img, angle):
+    thickness = 2
+    line_type = 8
+
+    cv2.ellipse(img,
+                (W / 2, W / 2),
+                (W / 4, W / 16),
+                angle,
+                0,
+                360,
+                (255, 0, 0),
+                thickness,
+                line_type)
+## [my_ellipse]
+## [my_filled_circle]
+def my_filled_circle(img, center):
+    thickness = -1
+    line_type = 8
+
+    cv2.circle(img,
+               center,
+               W / 32,
+               (0, 0, 255),
+               thickness,
+               line_type)
+## [my_filled_circle]
+## [my_polygon]
+def my_polygon(img):
+    line_type = 8
+
+    # Create some points
+    ppt = np.array([[W / 4, 7 * W / 8], [3 * W / 4, 7 * W / 8],
+                    [3 * W / 4, 13 * W / 16], [11 * W / 16, 13 * W / 16],
+                    [19 * W / 32, 3 * W / 8], [3 * W / 4, 3 * W / 8],
+                    [3 * W / 4, W / 8], [26 * W / 40, W / 8],
+                    [26 * W / 40, W / 4], [22 * W / 40, W / 4],
+                    [22 * W / 40, W / 8], [18 * W / 40, W / 8],
+                    [18 * W / 40, W / 4], [14 * W / 40, W / 4],
+                    [14 * W / 40, W / 8], [W / 4, W / 8],
+                    [W / 4, 3 * W / 8], [13 * W / 32, 3 * W / 8],
+                    [5 * W / 16, 13 * W / 16], [W / 4, 13 * W / 16]], np.int32)
+    ppt = ppt.reshape((-1, 1, 2))
+    cv2.fillPoly(img, [ppt], (255, 255, 255), line_type)
+    # Only drawind the lines would be:
+    # cv2.polylines(img, [ppt], True, (255, 0, 255), line_type)
+## [my_polygon]
+## [my_line]
+def my_line(img, start, end):
+    thickness = 2
+    line_type = 8
+
+    cv2.line(img,
+             start,
+             end,
+             (0, 0, 0),
+             thickness,
+             line_type)
+## [my_line]
+## [create_images]
+# Windows names
+atom_window = "Drawing 1: Atom"
+rook_window = "Drawing 2: Rook"
+
+# Create black empty images
+size = W, W, 3
+atom_image = np.zeros(size, dtype=np.uint8)
+rook_image = np.zeros(size, dtype=np.uint8)
+## [create_images]
+## [draw_atom]
+# 1. Draw a simple atom:
+# -----------------------
+
+# 1.a. Creating ellipses
+my_ellipse(atom_image, 90)
+my_ellipse(atom_image, 0)
+my_ellipse(atom_image, 45)
+my_ellipse(atom_image, -45)
+
+# 1.b. Creating circles
+my_filled_circle(atom_image, (W / 2, W / 2))
+## [draw_atom]
+## [draw_rook]
+
+# 2. Draw a rook
+# ------------------
+# 2.a. Create a convex polygon
+my_polygon(rook_image)
+## [rectangle]
+# 2.b. Creating rectangles
+cv2.rectangle(rook_image,
+              (0, 7 * W / 8),
+              (W, W),
+              (0, 255, 255),
+              -1,
+              8)
+## [rectangle]
+
+#  2.c. Create a few lines
+my_line(rook_image, (0, 15 * W / 16), (W, 15 * W / 16))
+my_line(rook_image, (W / 4, 7 * W / 8), (W / 4, W))
+my_line(rook_image, (W / 2, 7 * W / 8), (W / 2, W))
+my_line(rook_image, (3 * W / 4, 7 * W / 8), (3 * W / 4, W))
+## [draw_rook]
+cv2.imshow(atom_window, atom_image)
+cv2.moveWindow(atom_window, 0, 200)
+cv2.imshow(rook_window, rook_image)
+cv2.moveWindow(rook_window, W, 200)
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()

samples/python/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.py

+from __future__ import print_function
+import sys
+
+import cv2
+import numpy as np
+
+
+def print_help():
+    print('''
+    This program demonstrated the use of the discrete Fourier transform (DFT).
+    The dft of an image is taken and it's power spectrum is displayed.
+    Usage:
+    discrete_fourier_transform.py [image_name -- default ../../../../data/lena.jpg]''')
+
+
+def main(argv):
+
+    print_help()
+
+    filename = argv[0] if len(argv) > 0 else "../../../../data/lena.jpg"
+
+    I = cv2.imread(filename, cv2.IMREAD_GRAYSCALE)
+    if I is None:
+        print('Error opening image')
+        return -1
+    ## [expand]
+    rows, cols = I.shape
+    m = cv2.getOptimalDFTSize( rows )
+    n = cv2.getOptimalDFTSize( cols )
+    padded = cv2.copyMakeBorder(I, 0, m - rows, 0, n - cols, cv2.BORDER_CONSTANT, value=[0, 0, 0])
+    ## [expand]
+    ## [complex_and_real]
+    planes = [np.float32(padded), np.zeros(padded.shape, np.float32)]
+    complexI = cv2.merge(planes)         # Add to the expanded another plane with zeros
+    ## [complex_and_real]
+    ## [dft]
+    cv2.dft(complexI, complexI)         # this way the result may fit in the source matrix
+    ## [dft]
+    # compute the magnitude and switch to logarithmic scale
+    # = > log(1 + sqrt(Re(DFT(I)) ^ 2 + Im(DFT(I)) ^ 2))
+    ## [magnitude]
+    cv2.split(complexI, planes)                   # planes[0] = Re(DFT(I), planes[1] = Im(DFT(I))
+    cv2.magnitude(planes[0], planes[1], planes[0])# planes[0] = magnitude
+    magI = planes[0]
+    ## [magnitude]
+    ## [log]
+    matOfOnes = np.ones(magI.shape, dtype=magI.dtype)
+    cv2.add(matOfOnes, magI, magI) #  switch to logarithmic scale
+    cv2.log(magI, magI)
+    ## [log]
+    ## [crop_rearrange]
+    magI_rows, magI_cols = magI.shape
+    # crop the spectrum, if it has an odd number of rows or columns
+    magI = magI[0:(magI_rows & -2), 0:(magI_cols & -2)]
+    cx = int(magI_rows/2)
+    cy = int(magI_cols/2)
+
+    q0 = magI[0:cx, 0:cy]         # Top-Left - Create a ROI per quadrant
+    q1 = magI[cx:cx+cx, 0:cy]     # Top-Right
+    q2 = magI[0:cx, cy:cy+cy]     # Bottom-Left
+    q3 = magI[cx:cx+cx, cy:cy+cy] # Bottom-Right
+
+    tmp = np.copy(q0)               # swap quadrants (Top-Left with Bottom-Right)
+    magI[0:cx, 0:cy] = q3
+    magI[cx:cx + cx, cy:cy + cy] = tmp
+
+    tmp = np.copy(q1)               # swap quadrant (Top-Right with Bottom-Left)
+    magI[cx:cx + cx, 0:cy] = q2
+    magI[0:cx, cy:cy + cy] = tmp
+    ## [crop_rearrange]
+    ## [normalize]
+    cv2.normalize(magI, magI, 0, 1, cv2.NORM_MINMAX) # Transform the matrix with float values into a
+    ## viewable image form(float between values 0 and 1).
+    ## [normalize]
+    cv2.imshow("Input Image"       , I   )    # Show the result
+    cv2.imshow("spectrum magnitude", magI)
+    cv2.waitKey()
+
+if __name__ == "__main__":
+    main(sys.argv[1:])

samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py

+from __future__ import print_function
 import sys
 import time
+
 import numpy as np
 import cv2
 
-
 ## [basic_method]
 def is_grayscale(my_image):
     return len(my_image.shape) < 3
@@ -26,7 +27,6 @@ def sharpen(my_image):
         height, width, n_channels = my_image.shape
 
     result = np.zeros(my_image.shape, my_image.dtype)
-
     ## [basic_method_loop]
     for j in range(1, height - 1):
         for i in range(1, width - 1):
@@ -36,17 +36,16 @@ def sharpen(my_image):
                 result[j, i] = saturated(sum_value)
             else:
                 for k in range(0, n_channels):
-                    sum_value = 5 * my_image[j, i, k] - my_image[j + 1, i, k] - my_image[j - 1, i, k] \
-                                - my_image[j, i + 1, k] - my_image[j, i - 1, k]
+                    sum_value = 5 * my_image[j, i, k] - my_image[j + 1, i, k]  \
+                                - my_image[j - 1, i, k] - my_image[j, i + 1, k]\
+                                - my_image[j, i - 1, k]
                     result[j, i, k] = saturated(sum_value)
     ## [basic_method_loop]
-
     return result
 ## [basic_method]
 
-
 def main(argv):
-    filename = "../data/lena.jpg"
+    filename = "../../../../data/lena.jpg"
 
     img_codec = cv2.IMREAD_COLOR
     if argv:
@@ -57,8 +56,9 @@ def main(argv):
     src = cv2.imread(filename, img_codec)
 
     if src is None:
-        print "Can't open image [" + filename + "]"
-        print "Usage:\nmat_mask_operations.py [image_path -- default ../data/lena.jpg] [G -- grayscale]"
+        print("Can't open image [" + filename + "]")
+        print("Usage:")
+        print("mat_mask_operations.py [image_path -- default ../../../../data/lena.jpg] [G -- grayscale]")
         return -1
 
     cv2.namedWindow("Input", cv2.WINDOW_AUTOSIZE)
@@ -70,7 +70,7 @@ def main(argv):
     dst0 = sharpen(src)
 
     t = (time.time() - t) / 1000
-    print "Hand written function time passed in seconds: %s" % t
+    print("Hand written function time passed in seconds: %s" % t)
 
     cv2.imshow("Output", dst0)
     cv2.waitKey()
@@ -81,13 +81,13 @@ def main(argv):
                        [-1, 5, -1],
                        [0, -1, 0]], np.float32)  # kernel should be floating point type
     ## [kern]
-
     ## [filter2D]
-    dst1 = cv2.filter2D(src, -1, kernel)  # ddepth = -1, means destination image has depth same as input image
+    dst1 = cv2.filter2D(src, -1, kernel)
+    # ddepth = -1, means destination image has depth same as input image
     ## [filter2D]
 
     t = (time.time() - t) / 1000
-    print "Built-in filter2D time passed in seconds:     %s" % t
+    print("Built-in filter2D time passed in seconds:     %s" % t)
 
     cv2.imshow("Output", dst1)