Tutorial Hough Circles

samples/cpp/houghcircles.cpp

@@ -1,71 +0,0 @@
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/highgui.hpp"
-#include "opencv2/imgproc.hpp"
-
-#include <iostream>
-
-using namespace cv;
-using namespace std;
-
-static void help()
-{
-    cout << "\nThis program demonstrates circle finding with the Hough transform.\n"
-            "Usage:\n"
-            "./houghcircles <image_name>, Default is ../data/board.jpg\n" << endl;
-}
-
-int main(int argc, char** argv)
-{
-    cv::CommandLineParser parser(argc, argv,
-        "{help h ||}{@image|../data/board.jpg|}"
-    );
-    if (parser.has("help"))
-    {
-        help();
-        return 0;
-    }
-    //![load]
-    string filename = parser.get<string>("@image");
-    Mat img = imread(filename, IMREAD_COLOR);
-    if(img.empty())
-    {
-        help();
-        cout << "can not open " << filename << endl;
-        return -1;
-    }
-    //![load]
-
-    //![convert_to_gray]
-    Mat gray;
-    cvtColor(img, gray, COLOR_BGR2GRAY);
-    //![convert_to_gray]
-
-    //![reduce_noise]
-    medianBlur(gray, gray, 5);
-    //![reduce_noise]
-
-    //![houghcircles]
-    vector<Vec3f> circles;
-    HoughCircles(gray, circles, HOUGH_GRADIENT, 1,
-                 gray.rows/16, // change this value to detect circles with different distances to each other
-                 100, 30, 1, 30 // change the last two parameters
-                                // (min_radius & max_radius) to detect larger circles
-                 );
-    //![houghcircles]
-
-    //![draw]
-    for( size_t i = 0; i < circles.size(); i++ )
-    {
-        Vec3i c = circles[i];
-        circle( img, Point(c[0], c[1]), c[2], Scalar(0,0,255), 3, LINE_AA);
-        circle( img, Point(c[0], c[1]), 2, Scalar(0,255,0), 3, LINE_AA);
-    }
-    //![draw]
-
-    //![display]
-    imshow("detected circles", img);
-    waitKey();
-    //![display]
-
-    return 0;
-}

samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp

@@ -0,0 +1,65 @@
+/**
+ * @file houghcircles.cpp
+ * @brief This program demonstrates circle 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)
+{
+    //![load]
+    const char* filename = argc >=2 ? argv[1] : "../../../data/smarties.png";
+
+    // Loads an image
+    Mat src = imread( filename, IMREAD_COLOR );
+
+    // Check if image is loaded fine
+    if(src.empty()){
+        printf(" Error opening image\n");
+        printf(" Program Arguments: [image_name -- default %s] \n", filename);
+        return -1;
+    }
+    //![load]
+
+    //![convert_to_gray]
+    Mat gray;
+    cvtColor(src, gray, COLOR_BGR2GRAY);
+    //![convert_to_gray]
+
+    //![reduce_noise]
+    medianBlur(gray, gray, 5);
+    //![reduce_noise]
+
+    //![houghcircles]
+    vector<Vec3f> circles;
+    HoughCircles(gray, circles, HOUGH_GRADIENT, 1,
+                 gray.rows/16,  // change this value to detect circles with different distances to each other
+                 100, 30, 1, 30 // change the last two parameters
+            // (min_radius & max_radius) to detect larger circles
+    );
+    //![houghcircles]
+
+    //![draw]
+    for( size_t i = 0; i < circles.size(); i++ )
+    {
+        Vec3i c = circles[i];
+        Point center = Point(c[0], c[1]);
+        // circle center
+        circle( src, center, 1, Scalar(0,100,100), 3, LINE_AA);
+        // circle outline
+        int radius = c[2];
+        circle( src, center, radius, Scalar(255,0,255), 3, LINE_AA);
+    }
+    //![draw]
+
+    //![display]
+    imshow("detected circles", src);
+    waitKey();
+    //![display]
+
+    return 0;
+}