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

samples/python/texture_flow.py

@@ -3,7 +3,7 @@
 '''
 Texture flow direction estimation.
 
-Sample shows how cv2.cornerEigenValsAndVecs function can be used
+Sample shows how cv.cornerEigenValsAndVecs function can be used
 to estimate image texture flow direction.
 
 Usage:
@@ -14,7 +14,7 @@ Usage:
 from __future__ import print_function
 
 import numpy as np
-import cv2
+import cv2 as cv
 
 if __name__ == '__main__':
     import sys
@@ -23,15 +23,15 @@ if __name__ == '__main__':
     except:
         fn = '../data/starry_night.jpg'
 
-    img = cv2.imread(fn)
+    img = cv.imread(fn)
     if img is None:
         print('Failed to load image file:', fn)
         sys.exit(1)
 
-    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
     h, w = img.shape[:2]
 
-    eigen = cv2.cornerEigenValsAndVecs(gray, 15, 3)
+    eigen = cv.cornerEigenValsAndVecs(gray, 15, 3)
     eigen = eigen.reshape(h, w, 3, 2)  # [[e1, e2], v1, v2]
     flow = eigen[:,:,2]
 
@@ -41,7 +41,7 @@ if __name__ == '__main__':
     points =  np.dstack( np.mgrid[d/2:w:d, d/2:h:d] ).reshape(-1, 2)
     for x, y in np.int32(points):
         vx, vy = np.int32(flow[y, x]*d)
-        cv2.line(vis, (x-vx, y-vy), (x+vx, y+vy), (0, 0, 0), 1, cv2.LINE_AA)
-    cv2.imshow('input', img)
-    cv2.imshow('flow', vis)
-    cv2.waitKey()
+        cv.line(vis, (x-vx, y-vy), (x+vx, y+vy), (0, 0, 0), 1, cv.LINE_AA)
+    cv.imshow('input', img)
+    cv.imshow('flow', vis)
+    cv.waitKey()