Added Laplace, Canny and Sobel samples in tutorial cpp code

diff --git a/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp b/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp
new file mode 100644 (file)
index 0000000..929fcb0
--- /dev/null
+++ b/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp
@@ -0,0 +1,73 @@
+/**
+ * @file CannyDetector_Demo.cpp
+ * @brief Sample code showing how to detect edges using the Canny Detector
+ * @author OpenCV team
+ */
+
+#include "opencv2/imgproc/imgproc.hpp"
+#include "opencv2/highgui/highgui.hpp"
+#include <stdlib.h>
+#include <stdio.h>
+
+using namespace cv;
+
+/// Global variables
+
+Mat src, src_gray;
+Mat dst, detected_edges;
+
+int edgeThresh = 1;
+int lowThreshold;
+int const max_lowThreshold = 100;
+int ratio = 3;
+int kernel_size = 3;
+char* window_name = "Edge Map";
+
+/**
+ * @function CannyThreshold
+ * @brief Trackbar callback - Canny thresholds input with a ratio 1:3
+ */
+void CannyThreshold(int, void*)
+{
+    /// Reduce noise with a kernel 3x3
+    blur( src_gray, dst, Size(3,3) );
+
+    /// Canny detector
+    Canny( src_gray, detected_edges, lowThreshold, lowThreshold*ratio, kernel_size );
+
+    /// Using Canny's output as a mask, we display our result
+    dst = Scalar::all(0);
+    
+    src.copyTo( dst, detected_edges);
+    imshow( window_name, dst );
+}
+
+
+/**
+ * @function main
+ */
+int main( int argc, char** argv )
+{
+  /// Load an image
+  src = imread( argv[1] );
+
+  if( !src.data )
+    { return -1; }
+
+  /// Convert the image to grayscale
+  cvtColor( src, src_gray, CV_BGR2GRAY );
+
+  /// Create a window
+  namedWindow( window_name, CV_WINDOW_AUTOSIZE );
+
+  /// Create a Trackbar for user to enter threshold
+  createTrackbar( "Min Threshold:", window_name, &lowThreshold, max_lowThreshold, CannyThreshold );
+
+  /// Show the image
+  CannyThreshold(0, 0);
+
+  /// Wait until user exit program by pressing a key
+  waitKey(0);
+
+  return 0;
+}

diff --git a/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp b/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp
new file mode 100644 (file)
index 0000000..0893f27
--- /dev/null
+++ b/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp
@@ -0,0 +1,56 @@
+/**
+ * @file Laplace_Demo.cpp
+ * @brief Sample code showing how to detect edges using the Laplace operator
+ * @author OpenCV team
+ */
+
+#include "opencv2/imgproc/imgproc.hpp"
+#include "opencv2/highgui/highgui.hpp"
+#include <stdlib.h>
+#include <stdio.h>
+
+using namespace cv;
+
+/**
+ * @function main
+ */
+int main( int argc, char** argv )
+{
+
+  Mat src, src_gray, dst;
+  int kernel_size = 3; 
+  int scale = 1;
+  int delta = 0;
+  int ddepth = CV_16S;
+  char* window_name = "Laplace Demo";
+
+  int c;
+
+  /// Load an image
+  src = imread( argv[1] );
+
+  if( !src.data )
+    { return -1; }
+
+  /// Remove noise by blurring with a Gaussian filter
+  GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
+
+  /// Convert the image to grayscale
+  cvtColor( src, src_gray, CV_RGB2GRAY );
+
+  /// Create window
+  namedWindow( window_name, CV_WINDOW_AUTOSIZE );
+
+  /// Apply Laplace function
+  Mat abs_dst;
+
+  Laplacian( src_gray, dst, ddepth, kernel_size, scale, delta, BORDER_DEFAULT );
+  convertScaleAbs( dst, abs_dst );
+
+  /// Show what you got
+  imshow( window_name, abs_dst );
+
+  waitKey(0);
+
+  return 0;
+}

diff --git a/samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp b/samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp
new file mode 100644 (file)
index 0000000..0d161ce
--- /dev/null
+++ b/samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp
@@ -0,0 +1,67 @@
+/**
+ * @file Sobel_Demo.cpp
+ * @brief Sample code using Sobel and/orScharr OpenCV functions to make a simple Edge Detector
+ * @author OpenCV team
+ */
+
+#include "opencv2/imgproc/imgproc.hpp"
+#include "opencv2/highgui/highgui.hpp"
+#include <stdlib.h>
+#include <stdio.h>
+
+using namespace cv;
+
+/**
+ * @function main
+ */
+int main( int argc, char** argv )
+{
+
+  Mat src, src_gray;
+  Mat grad; 
+  char* window_name = "Sobel Demo - Simple Edge Detector";
+  int scale = 1;
+  int delta = 0;
+  int ddepth = CV_16S;
+
+  int c;
+
+  /// Load an image
+  src = imread( argv[1] );
+
+  if( !src.data )
+    { return -1; }
+
+  GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
+
+  /// Convert it to gray
+  cvtColor( src, src_gray, CV_RGB2GRAY );
+
+  /// Create window
+  namedWindow( window_name, CV_WINDOW_AUTOSIZE );
+
+  /// Generate grad_x and grad_y
+  Mat grad_x, grad_y;
+  Mat abs_grad_x, abs_grad_y;
+ 
+  /// Gradient X
+  //Scharr( src_gray, grad_x, ddepth, 1, 0, scale, delta, BORDER_DEFAULT );
+  Sobel( src_gray, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT );   
+  convertScaleAbs( grad_x, abs_grad_x );
+
+  /// Gradient Y  
+  //Scharr( src_gray, grad_y, ddepth, 0, 1, scale, delta, BORDER_DEFAULT );
+  Sobel( src_gray, grad_y, ddepth, 0, 1, 3, scale, delta, BORDER_DEFAULT );   
+  convertScaleAbs( grad_y, abs_grad_y );
+
+  /// Total Gradient (approximate)
+  addWeighted( abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad );
+
+  imshow( window_name, grad );
+
+  waitKey(0);
+
+  return 0;
+}
+
+