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How to rotate an image in OpenCV Python?
OpenCV provides us the function cv.rotate() to rotate an image (NumPy array) in multiples of 90 degrees. This function rotates an image in three possible ways: 90, 180, and 270 degrees clockwise. We use the following syntax −
Syntax
cv2.rotate(img, rotateCode)
rotateCode is a rotate flag specifying how to rotate the array. The three rotate flags are as below −
cv2.ROTATE_90_CLOCKWISE
cv2.ROTATE_180
cv2.ROTATE_90_COUNTERCLOCKWISE
Steps
To rotate an input image, you could follow the steps given below −
Import the required libraries OpenCV and matplotlib. Make sure you have already installed them.
Read the input image using cv2.imread() method. Specify the full path of the image.
Rotate the input image using cv2.rotate() function. Pass the desired rotateCode to the function as a parameter. We can pass cv2.ROTATE_180, cv2.ROTATE_90_CLOCKWISE or cv2.ROTATE_90_COUNTERCLOCKWISE as a parameter.
Display the rotated image.
Let's see the examples to rotate an input image.
Input Image
We will use the following image as an input file in the examples below −
Example
In this example, we rotate the input image by 180 degrees clockwise.
# import required libraries import cv2 # load the input image img = cv2.imread('leaf.jpg') # rotate the image by 180 degree clockwise img_cw_180 = cv2.rotate(img, cv2.ROTATE_180) # display the rotated image cv2.imshow("Image rotated by 180 degree", img_cw_180) cv2.waitKey(0) cv2.destroyAllWindows()
Output
When you execute the above program, it will produce the following output window −
Notice that the input image is rotated 180 degrees clockwise.
Let's see other rotations available in OpenCV.
Example
In this example, we show how to rotate the input image by 90, 180, and 270 degrees.
# import required libraries import cv2 import matplotlib.pyplot as plt # load the input image img = cv2.imread('leaf.jpg') # convert the image to grayscale img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # rotate the image by 90 degree clockwise img_cw_90 = cv2.rotate(img, cv2.ROTATE_90_CLOCKWISE) # rotate the image by 270 degree clockwise or 90 degree counterclockwise img_ccw_90 = cv2.rotate(img, cv2.ROTATE_90_COUNTERCLOCKWISE) # rotate the image by 180 degree clockwise img_cw_180 = cv2.rotate(img, cv2.ROTATE_180) # display all the images plt.subplot(221), plt.imshow(img, 'gray'), plt.title('Original Image'), plt.axis('off') plt.subplot(222), plt.imshow(img_cw_90,'gray'), plt.title('(90 degree clockwise)'), plt.axis('off') plt.subplot(223), plt.imshow(img_cw_180, 'gray'), plt.title('180 degree'), plt.axis('off') plt.subplot(224), plt.imshow(img_ccw_90, 'gray'), plt.title('270 degree clockwise/\n 90 degree counter clockwise'), plt.axis('off') plt.show()
Output
The above program, on execution, will produce the following output window −
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