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3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/ImgTrans/houghlines.cpp 2.5 KB
f4334277   Hu Chunming   提交3rdparty
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  /**
   * @file houghlines.cpp
   * @brief This program demonstrates line finding with the Hough transform
   */
  
  #include "opencv2/imgcodecs.hpp"
  #include "opencv2/highgui.hpp"
  #include "opencv2/imgproc.hpp"
  
  using namespace cv;
  using namespace std;
  
  int main(int argc, char** argv)
  {
      // Declare the output variables
      Mat dst, cdst, cdstP;
  
      //![load]
      const char* default_file = "sudoku.png";
      const char* filename = argc >=2 ? argv[1] : default_file;
  
      // Loads an image
      Mat src = imread( samples::findFile( filename ), IMREAD_GRAYSCALE );
  
      // Check if image is loaded fine
      if(src.empty()){
          printf(" Error opening image\n");
          printf(" Program Arguments: [image_name -- default %s] \n", default_file);
          return -1;
      }
      //![load]
  
      //![edge_detection]
      // Edge detection
      Canny(src, dst, 50, 200, 3);
      //![edge_detection]
  
      // Copy edges to the images that will display the results in BGR
      cvtColor(dst, cdst, COLOR_GRAY2BGR);
      cdstP = cdst.clone();
  
      //![hough_lines]
      // Standard Hough Line Transform
      vector<Vec2f> lines; // will hold the results of the detection
      HoughLines(dst, lines, 1, CV_PI/180, 150, 0, 0 ); // runs the actual detection
      //![hough_lines]
      //![draw_lines]
      // Draw the lines
      for( size_t i = 0; i < lines.size(); i++ )
      {
          float rho = lines[i][0], theta = lines[i][1];
          Point pt1, pt2;
          double a = cos(theta), b = sin(theta);
          double x0 = a*rho, y0 = b*rho;
          pt1.x = cvRound(x0 + 1000*(-b));
          pt1.y = cvRound(y0 + 1000*(a));
          pt2.x = cvRound(x0 - 1000*(-b));
          pt2.y = cvRound(y0 - 1000*(a));
          line( cdst, pt1, pt2, Scalar(0,0,255), 3, LINE_AA);
      }
      //![draw_lines]
  
      //![hough_lines_p]
      // Probabilistic Line Transform
      vector<Vec4i> linesP; // will hold the results of the detection
      HoughLinesP(dst, linesP, 1, CV_PI/180, 50, 50, 10 ); // runs the actual detection
      //![hough_lines_p]
      //![draw_lines_p]
      // Draw the lines
      for( size_t i = 0; i < linesP.size(); i++ )
      {
          Vec4i l = linesP[i];
          line( cdstP, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0,0,255), 3, LINE_AA);
      }
      //![draw_lines_p]
  
      //![imshow]
      // Show results
      imshow("Source", src);
      imshow("Detected Lines (in red) - Standard Hough Line Transform", cdst);
      imshow("Detected Lines (in red) - Probabilistic Line Transform", cdstP);
      //![imshow]
  
      //![exit]
      // Wait and Exit
      waitKey();
      return 0;
      //![exit]
  }