OpenCV-Python is a library of Python bindings designed to solve computer vision problems. cv2.rotate()
method is used to rotate a 2D array in multiples of 90 degrees. The function cv::rotate rotates the array in three different ways.
Syntax: cv2.cv.rotate( src, rotateCode[, dst] )
Parameters:
src: It is the image whose color space is to be changed.
rotateCode: It is an enum to specify how to rotate the array.
dst: It is the output image of the same size and depth as src image. It is an optional parameter.Return Value: It returns an image.
Image used for all the below examples:
Example #1: Rotate by 90 degrees clockwise
# Python program to explain cv2.rotate() method # importing cv2 import cv2 # path path = r 'C:\Users\user\Desktop\geeks14.png' # Reading an image in default mode src = cv2.imread(path) # Window name in which image is displayed window_name = 'Image' # Using cv2.rotate() method # Using cv2.ROTATE_90_CLOCKWISE rotate # by 90 degrees clockwise image = cv2.rotate(src, cv2.cv2.ROTATE_90_CLOCKWISE) # Displaying the image cv2.imshow(window_name, image) cv2.waitKey( 0 ) |
Output:
Example #2: Rotate by 180 degrees clockwise
# Python program to explain cv2.rotate() method # importing cv2 import cv2 # path path = r 'C:\Users\user\Desktop\geeks14.png' # Reading an image in default mode src = cv2.imread(path) # Window name in which image is displayed window_name = 'Image' # Using cv2.rotate() method # Using cv2.ROTATE_180 rotate by # 180 degrees clockwise image = cv2.rotate(src, cv2.ROTATE_180) # Displaying the image cv2.imshow(window_name, image) cv2.waitKey( 0 ) |
Output:
Example #3: Rotate by 270 degrees clockwise
# Python program to explain cv2.rotate() method # importing cv2 import cv2 # path path = r 'C:\Users\user\Desktop\geeks14.png' # Reading an image in default mode src = cv2.imread(path) # Window name in which image is displayed window_name = 'Image' # Using cv2.rotate() method # Using cv2.ROTATE_90_COUNTERCLOCKWISE # rotate by 270 degrees clockwise image = cv2.rotate(src, cv2.ROTATE_90_COUNTERCLOCKWISE) # Displaying the image cv2.imshow(window_name, image) cv2.waitKey( 0 ) |
Output:
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