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Added Laplace, Canny and Sobel samples in tutorial cpp code
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samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp
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samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp
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/**
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* @file CannyDetector_Demo.cpp
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* @brief Sample code showing how to detect edges using the Canny Detector
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* @author OpenCV team
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*/
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include <stdlib.h>
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#include <stdio.h>
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using namespace cv;
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/// Global variables
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Mat src, src_gray;
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Mat dst, detected_edges;
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int edgeThresh = 1;
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int lowThreshold;
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int const max_lowThreshold = 100;
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int ratio = 3;
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int kernel_size = 3;
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char* window_name = "Edge Map";
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/**
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* @function CannyThreshold
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* @brief Trackbar callback - Canny thresholds input with a ratio 1:3
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*/
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void CannyThreshold(int, void*)
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{
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/// Reduce noise with a kernel 3x3
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blur( src_gray, dst, Size(3,3) );
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/// Canny detector
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Canny( src_gray, detected_edges, lowThreshold, lowThreshold*ratio, kernel_size );
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/// Using Canny's output as a mask, we display our result
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dst = Scalar::all(0);
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src.copyTo( dst, detected_edges);
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imshow( window_name, dst );
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}
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/**
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* @function main
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*/
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int main( int argc, char** argv )
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{
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/// Load an image
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src = imread( argv[1] );
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if( !src.data )
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{ return -1; }
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/// Convert the image to grayscale
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cvtColor( src, src_gray, CV_BGR2GRAY );
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/// Create a window
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namedWindow( window_name, CV_WINDOW_AUTOSIZE );
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/// Create a Trackbar for user to enter threshold
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createTrackbar( "Min Threshold:", window_name, &lowThreshold, max_lowThreshold, CannyThreshold );
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/// Show the image
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CannyThreshold(0, 0);
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/// Wait until user exit program by pressing a key
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waitKey(0);
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return 0;
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}
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56
samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp
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samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp
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/**
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* @file Laplace_Demo.cpp
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* @brief Sample code showing how to detect edges using the Laplace operator
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* @author OpenCV team
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*/
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include <stdlib.h>
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#include <stdio.h>
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using namespace cv;
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/**
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* @function main
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*/
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int main( int argc, char** argv )
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{
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Mat src, src_gray, dst;
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int kernel_size = 3;
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int scale = 1;
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int delta = 0;
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int ddepth = CV_16S;
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char* window_name = "Laplace Demo";
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int c;
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/// Load an image
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src = imread( argv[1] );
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if( !src.data )
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{ return -1; }
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/// Remove noise by blurring with a Gaussian filter
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GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
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/// Convert the image to grayscale
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cvtColor( src, src_gray, CV_RGB2GRAY );
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/// Create window
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namedWindow( window_name, CV_WINDOW_AUTOSIZE );
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/// Apply Laplace function
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Mat abs_dst;
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Laplacian( src_gray, dst, ddepth, kernel_size, scale, delta, BORDER_DEFAULT );
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convertScaleAbs( dst, abs_dst );
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/// Show what you got
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imshow( window_name, abs_dst );
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waitKey(0);
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return 0;
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}
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67
samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp
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samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp
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/**
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* @file Sobel_Demo.cpp
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* @brief Sample code using Sobel and/orScharr OpenCV functions to make a simple Edge Detector
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* @author OpenCV team
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*/
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include <stdlib.h>
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#include <stdio.h>
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using namespace cv;
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/**
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* @function main
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*/
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int main( int argc, char** argv )
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{
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Mat src, src_gray;
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Mat grad;
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char* window_name = "Sobel Demo - Simple Edge Detector";
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int scale = 1;
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int delta = 0;
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int ddepth = CV_16S;
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int c;
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/// Load an image
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src = imread( argv[1] );
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if( !src.data )
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{ return -1; }
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GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
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/// Convert it to gray
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cvtColor( src, src_gray, CV_RGB2GRAY );
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/// Create window
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namedWindow( window_name, CV_WINDOW_AUTOSIZE );
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/// Generate grad_x and grad_y
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Mat grad_x, grad_y;
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Mat abs_grad_x, abs_grad_y;
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/// Gradient X
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//Scharr( src_gray, grad_x, ddepth, 1, 0, scale, delta, BORDER_DEFAULT );
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Sobel( src_gray, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT );
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convertScaleAbs( grad_x, abs_grad_x );
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/// Gradient Y
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//Scharr( src_gray, grad_y, ddepth, 0, 1, scale, delta, BORDER_DEFAULT );
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Sobel( src_gray, grad_y, ddepth, 0, 1, 3, scale, delta, BORDER_DEFAULT );
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convertScaleAbs( grad_y, abs_grad_y );
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/// Total Gradient (approximate)
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addWeighted( abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad );
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imshow( window_name, grad );
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waitKey(0);
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return 0;
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}
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