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134 lines
3.3 KiB
C++
134 lines
3.3 KiB
C++
/**
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* @file HoughLines_Demo.cpp
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* @brief Demo code for Hough Transform
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* @author OpenCV team
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*/
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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#include <iostream>
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using namespace cv;
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using namespace std;
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/// Global variables
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/** General variables */
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Mat src, edges;
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Mat src_gray;
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Mat standard_hough, probabilistic_hough;
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int min_threshold = 50;
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int max_trackbar = 150;
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const char* standard_name = "Standard Hough Lines Demo";
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const char* probabilistic_name = "Probabilistic Hough Lines Demo";
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int s_trackbar = max_trackbar;
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int p_trackbar = max_trackbar;
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/// Function Headers
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void help();
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void Standard_Hough( int, void* );
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void Probabilistic_Hough( int, void* );
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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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// Read the image
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String imageName("../data/building.jpg"); // by default
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if (argc > 1)
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{
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imageName = argv[1];
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}
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src = imread( imageName, IMREAD_COLOR );
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if( src.empty() )
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{ help();
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return -1;
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}
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/// Pass the image to gray
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cvtColor( src, src_gray, COLOR_RGB2GRAY );
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/// Apply Canny edge detector
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Canny( src_gray, edges, 50, 200, 3 );
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/// Create Trackbars for Thresholds
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char thresh_label[50];
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sprintf( thresh_label, "Thres: %d + input", min_threshold );
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namedWindow( standard_name, WINDOW_AUTOSIZE );
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createTrackbar( thresh_label, standard_name, &s_trackbar, max_trackbar, Standard_Hough);
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namedWindow( probabilistic_name, WINDOW_AUTOSIZE );
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createTrackbar( thresh_label, probabilistic_name, &p_trackbar, max_trackbar, Probabilistic_Hough);
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/// Initialize
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Standard_Hough(0, 0);
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Probabilistic_Hough(0, 0);
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waitKey(0);
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return 0;
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}
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/**
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* @function help
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* @brief Indications of how to run this program and why is it for
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*/
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void help()
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{
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printf("\t Hough Transform to detect lines \n ");
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printf("\t---------------------------------\n ");
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printf(" Usage: ./HoughLines_Demo <image_name> \n");
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}
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/**
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* @function Standard_Hough
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*/
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void Standard_Hough( int, void* )
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{
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vector<Vec2f> s_lines;
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cvtColor( edges, standard_hough, COLOR_GRAY2BGR );
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/// 1. Use Standard Hough Transform
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HoughLines( edges, s_lines, 1, CV_PI/180, min_threshold + s_trackbar, 0, 0 );
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/// Show the result
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for( size_t i = 0; i < s_lines.size(); i++ )
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{
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float r = s_lines[i][0], t = s_lines[i][1];
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double cos_t = cos(t), sin_t = sin(t);
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double x0 = r*cos_t, y0 = r*sin_t;
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double alpha = 1000;
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Point pt1( cvRound(x0 + alpha*(-sin_t)), cvRound(y0 + alpha*cos_t) );
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Point pt2( cvRound(x0 - alpha*(-sin_t)), cvRound(y0 - alpha*cos_t) );
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line( standard_hough, pt1, pt2, Scalar(255,0,0), 3, LINE_AA);
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}
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imshow( standard_name, standard_hough );
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}
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/**
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* @function Probabilistic_Hough
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*/
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void Probabilistic_Hough( int, void* )
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{
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vector<Vec4i> p_lines;
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cvtColor( edges, probabilistic_hough, COLOR_GRAY2BGR );
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/// 2. Use Probabilistic Hough Transform
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HoughLinesP( edges, p_lines, 1, CV_PI/180, min_threshold + p_trackbar, 30, 10 );
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/// Show the result
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for( size_t i = 0; i < p_lines.size(); i++ )
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{
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Vec4i l = p_lines[i];
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line( probabilistic_hough, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(255,0,0), 3, LINE_AA);
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}
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imshow( probabilistic_name, probabilistic_hough );
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}
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