Tutorial Hough Circles

samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py

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+import sys
+import cv2
+import numpy as np
+
+
+def main(argv):
+    ## [load]
+    default_file =  "../../../../data/smarties.png"
+    filename = argv[0] if len(argv) > 0 else default_file
+
+    # Loads an image
+    src = cv2.imread(filename, cv2.IMREAD_COLOR)
+
+    # Check if image is loaded fine
+    if src is None:
+        print ('Error opening image!')
+        print ('Usage: hough_circle.py [image_name -- default ' + default_file + '] \n')
+        return -1
+    ## [load]
+
+    ## [convert_to_gray]
+    # Convert it to gray
+    gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
+    ## [convert_to_gray]
+
+    ## [reduce_noise]
+    # Reduce the noise to avoid false circle detection
+    gray = cv2.medianBlur(gray, 5)
+    ## [reduce_noise]
+
+    ## [houghcircles]
+    rows = gray.shape[0]
+    circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, rows / 8,
+                               param1=100, param2=30,
+                               minRadius=1, maxRadius=30)
+    ## [houghcircles]
+
+    ## [draw]
+    if circles is not None:
+        circles = np.uint16(np.around(circles))
+        for i in circles[0, :]:
+            center = (i[0], i[1])
+            # circle center
+            cv2.circle(src, center, 1, (0, 100, 100), 3)
+            # circle outline
+            radius = i[2]
+            cv2.circle(src, center, radius, (255, 0, 255), 3)
+    ## [draw]
+
+    ## [display]
+    cv2.imshow("detected circles", src)
+    cv2.waitKey(0)
+    ## [display]
+
+    return 0
+
+
+if __name__ == "__main__":
+    main(sys.argv[1:])