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

samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py

@@ -3,12 +3,12 @@
 @brief Sample code showing how to detect edges using the Laplace operator
 """
 import sys
-import cv2
+import cv2 as cv
 
 def main(argv):
     # [variables]
     # Declare the variables we are going to use
-    ddepth = cv2.CV_16S
+    ddepth = cv.CV_16S
     kernel_size = 3
     window_name = "Laplace Demo"
     # [variables]
@@ -16,7 +16,7 @@ def main(argv):
     # [load]
     imageName = argv[0] if len(argv) > 0 else "../data/lena.jpg"
 
-    src = cv2.imread(imageName, cv2.IMREAD_COLOR) # Load an image
+    src = cv.imread(imageName, cv.IMREAD_COLOR) # Load an image
 
     # Check if image is loaded fine
     if src is None:
@@ -27,30 +27,30 @@ def main(argv):
 
     # [reduce_noise]
     # Remove noise by blurring with a Gaussian filter
-    src = cv2.GaussianBlur(src, (3, 3), 0)
+    src = cv.GaussianBlur(src, (3, 3), 0)
     # [reduce_noise]
 
     # [convert_to_gray]
     # Convert the image to grayscale
-    src_gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
+    src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
     # [convert_to_gray]
 
     # Create Window
-    cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)
+    cv.namedWindow(window_name, cv.WINDOW_AUTOSIZE)
 
     # [laplacian]
     # Apply Laplace function
-    dst = cv2.Laplacian(src_gray, ddepth, kernel_size)
+    dst = cv.Laplacian(src_gray, ddepth, kernel_size)
     # [laplacian]
 
     # [convert]
     # converting back to uint8
-    abs_dst = cv2.convertScaleAbs(dst)
+    abs_dst = cv.convertScaleAbs(dst)
     # [convert]
 
     # [display]
-    cv2.imshow(window_name, abs_dst)
-    cv2.waitKey(0)
+    cv.imshow(window_name, abs_dst)
+    cv.waitKey(0)
     # [display]
 
     return 0