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

doc/py_tutorials/py_gui/py_image_display/py_image_display.markdown

@@ -5,7 +5,7 @@ Goals
 -----
 
 -   Here, you will learn how to read an image, how to display it and how to save it back
--   You will learn these functions : **cv2.imread()**, **cv2.imshow()** , **cv2.imwrite()**
+-   You will learn these functions : **cv.imread()**, **cv.imshow()** , **cv.imwrite()**
 -   Optionally, you will learn how to display images with Matplotlib
 
 Using OpenCV
@@ -13,25 +13,25 @@ Using OpenCV
 
 ### Read an image
 
-Use the function **cv2.imread()** to read an image. The image should be in the working directory or
+Use the function **cv.imread()** to read an image. The image should be in the working directory or
 a full path of image should be given.
 
 Second argument is a flag which specifies the way image should be read.
 
--   cv2.IMREAD_COLOR : Loads a color image. Any transparency of image will be neglected. It is the
+-   cv.IMREAD_COLOR : Loads a color image. Any transparency of image will be neglected. It is the
     default flag.
--   cv2.IMREAD_GRAYSCALE : Loads image in grayscale mode
--   cv2.IMREAD_UNCHANGED : Loads image as such including alpha channel
+-   cv.IMREAD_GRAYSCALE : Loads image in grayscale mode
+-   cv.IMREAD_UNCHANGED : Loads image as such including alpha channel
 
 @note Instead of these three flags, you can simply pass integers 1, 0 or -1 respectively.
 
 See the code below:
 @code{.py}
 import numpy as np
-import cv2
+import cv2 as cv
 
 # Load an color image in grayscale
-img = cv2.imread('messi5.jpg',0)
+img = cv.imread('messi5.jpg',0)
 @endcode
 
 **warning**
@@ -40,21 +40,21 @@ Even if the image path is wrong, it won't throw any error, but `print img` will
 
 ### Display an image
 
-Use the function **cv2.imshow()** to display an image in a window. The window automatically fits to
+Use the function **cv.imshow()** to display an image in a window. The window automatically fits to
 the image size.
 
 First argument is a window name which is a string. second argument is our image. You can create as
 many windows as you wish, but with different window names.
 @code{.py}
-cv2.imshow('image',img)
-cv2.waitKey(0)
-cv2.destroyAllWindows()
+cv.imshow('image',img)
+cv.waitKey(0)
+cv.destroyAllWindows()
 @endcode
 A screenshot of the window will look like this (in Fedora-Gnome machine):
 
 ![image](images/opencv_screenshot.jpg)
 
-**cv2.waitKey()** is a keyboard binding function. Its argument is the time in milliseconds. The
+**cv.waitKey()** is a keyboard binding function. Its argument is the time in milliseconds. The
 function waits for specified milliseconds for any keyboard event. If you press any key in that time,
 the program continues. If **0** is passed, it waits indefinitely for a key stroke. It can also be
 set to detect specific key strokes like, if key a is pressed etc which we will discuss below.
@@ -62,30 +62,30 @@ set to detect specific key strokes like, if key a is pressed etc which we will d
 @note Besides binding keyboard events this function also processes many other GUI events, so you
 MUST use it to actually display the image.
 
-**cv2.destroyAllWindows()** simply destroys all the windows we created. If you want to destroy any
-specific window, use the function **cv2.destroyWindow()** where you pass the exact window name as
+**cv.destroyAllWindows()** simply destroys all the windows we created. If you want to destroy any
+specific window, use the function **cv.destroyWindow()** where you pass the exact window name as
 the argument.
 
 @note There is a special case where you can already create a window and load image to it later. In
 that case, you can specify whether window is resizable or not. It is done with the function
-**cv2.namedWindow()**. By default, the flag is cv2.WINDOW_AUTOSIZE. But if you specify flag to be
-cv2.WINDOW_NORMAL, you can resize window. It will be helpful when image is too large in dimension
+**cv.namedWindow()**. By default, the flag is cv.WINDOW_AUTOSIZE. But if you specify flag to be
+cv.WINDOW_NORMAL, you can resize window. It will be helpful when image is too large in dimension
 and adding track bar to windows.
 
 See the code below:
 @code{.py}
-cv2.namedWindow('image', cv2.WINDOW_NORMAL)
-cv2.imshow('image',img)
-cv2.waitKey(0)
-cv2.destroyAllWindows()
+cv.namedWindow('image', cv.WINDOW_NORMAL)
+cv.imshow('image',img)
+cv.waitKey(0)
+cv.destroyAllWindows()
 @endcode
 ### Write an image
 
-Use the function **cv2.imwrite()** to save an image.
+Use the function **cv.imwrite()** to save an image.
 
 First argument is the file name, second argument is the image you want to save.
 @code{.py}
-cv2.imwrite('messigray.png',img)
+cv.imwrite('messigray.png',img)
 @endcode
 This will save the image in PNG format in the working directory.
 
@@ -95,22 +95,22 @@ Below program loads an image in grayscale, displays it, save the image if you pr
 simply exit without saving if you press ESC key.
 @code{.py}
 import numpy as np
-import cv2
+import cv2 as cv
 
-img = cv2.imread('messi5.jpg',0)
-cv2.imshow('image',img)
-k = cv2.waitKey(0)
+img = cv.imread('messi5.jpg',0)
+cv.imshow('image',img)
+k = cv.waitKey(0)
 if k == 27:         # wait for ESC key to exit
-    cv2.destroyAllWindows()
+    cv.destroyAllWindows()
 elif k == ord('s'): # wait for 's' key to save and exit
-    cv2.imwrite('messigray.png',img)
-    cv2.destroyAllWindows()
+    cv.imwrite('messigray.png',img)
+    cv.destroyAllWindows()
 @endcode
 
 **warning**
 
-If you are using a 64-bit machine, you will have to modify `k = cv2.waitKey(0)` line as follows :
-`k = cv2.waitKey(0) & 0xFF`
+If you are using a 64-bit machine, you will have to modify `k = cv.waitKey(0)` line as follows :
+`k = cv.waitKey(0) & 0xFF`
 
 Using Matplotlib
 ----------------
@@ -120,10 +120,10 @@ will see them in coming articles. Here, you will learn how to display image with
 zoom images, save it etc using Matplotlib.
 @code{.py}
 import numpy as np
-import cv2
+import cv2 as cv
 from matplotlib import pyplot as plt
 
-img = cv2.imread('messi5.jpg',0)
+img = cv.imread('messi5.jpg',0)
 plt.imshow(img, cmap = 'gray', interpolation = 'bicubic')
 plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
 plt.show()