python: 'cv2.' -> 'cv.' via 'import cv2 as cv'

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

@@ -1,5 +1,5 @@
 import sys
-import cv2
+import cv2 as cv
 import numpy as np
 
 
@@ -9,7 +9,7 @@ def main(argv):
     filename = argv[0] if len(argv) > 0 else default_file
 
     # Loads an image
-    src = cv2.imread(filename, cv2.IMREAD_COLOR)
+    src = cv.imread(filename, cv.IMREAD_COLOR)
 
     # Check if image is loaded fine
     if src is None:
@@ -20,17 +20,17 @@ def main(argv):
 
     ## [convert_to_gray]
     # Convert it to gray
-    gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
+    gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
     ## [convert_to_gray]
 
     ## [reduce_noise]
     # Reduce the noise to avoid false circle detection
-    gray = cv2.medianBlur(gray, 5)
+    gray = cv.medianBlur(gray, 5)
     ## [reduce_noise]
 
     ## [houghcircles]
     rows = gray.shape[0]
-    circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, rows / 8,
+    circles = cv.HoughCircles(gray, cv.HOUGH_GRADIENT, 1, rows / 8,
                                param1=100, param2=30,
                                minRadius=1, maxRadius=30)
     ## [houghcircles]
@@ -41,15 +41,15 @@ def main(argv):
         for i in circles[0, :]:
             center = (i[0], i[1])
             # circle center
-            cv2.circle(src, center, 1, (0, 100, 100), 3)
+            cv.circle(src, center, 1, (0, 100, 100), 3)
             # circle outline
             radius = i[2]
-            cv2.circle(src, center, radius, (255, 0, 255), 3)
+            cv.circle(src, center, radius, (255, 0, 255), 3)
     ## [draw]
 
     ## [display]
-    cv2.imshow("detected circles", src)
-    cv2.waitKey(0)
+    cv.imshow("detected circles", src)
+    cv.waitKey(0)
     ## [display]
 
     return 0