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
Python3
# Python program to explain cv2.rotate() method# importing cv2import cv2# pathpath = r'C:\Users\user\Desktop\Lazyroar14.png'# Reading an image in default modesrc = cv2.imread(path)# Window name in which image is displayedwindow_name = 'Image'# Using cv2.rotate() method# Using cv2.ROTATE_90_CLOCKWISE rotate# by 90 degrees clockwiseimage = cv2.rotate(src, cv2.ROTATE_90_CLOCKWISE)# Displaying the imagecv2.imshow(window_name, image)cv2.waitKey(0) |
Output: 
Example #2: Rotate by 180 degrees clockwise
Python3
# Python program to explain cv2.rotate() method# importing cv2import cv2# pathpath = r'C:\Users\user\Desktop\Lazyroar14.png'# Reading an image in default modesrc = cv2.imread(path)# Window name in which image is displayedwindow_name = 'Image'# Using cv2.rotate() method# Using cv2.ROTATE_180 rotate by# 180 degrees clockwiseimage = cv2.rotate(src, cv2.ROTATE_180)# Displaying the imagecv2.imshow(window_name, image)cv2.waitKey(0) |
Output: 
Example #3: Rotate by 270 degrees clockwise
Python3
# Python program to explain cv2.rotate() method# importing cv2import cv2# pathpath = r'C:\Users\user\Desktop\Lazyroar14.png'# Reading an image in default modesrc = cv2.imread(path)# Window name in which image is displayedwindow_name = 'Image'# Using cv2.rotate() method# Using cv2.ROTATE_90_COUNTERCLOCKWISE# rotate by 270 degrees clockwiseimage = cv2.rotate(src, cv2.ROTATE_90_COUNTERCLOCKWISE)# Displaying the imagecv2.imshow(window_name, image)cv2.waitKey(0) |
Output: 
