In this article, let’s see how to rotate an Image using Python. By Image Rotation, the image is rotated about its center by a specified number of degrees. The rotation of an image is a geometric transformation. It can be done either by Forward Transformation (or) Inverse Transformation.
Here Image Processing Library with Pillow uses Inverse Transformation. If the Number Of Degrees Specified for Image Rotation is Not an Integer Multiple of 90 Degrees, then some Pixel Values Beyond Image Boundaries i.e Pixel values lying outside the Dimension of the image. Such Values will not be displayed in the output image.
Method:1 Using Image Processing Library Pillow
Python3
# import the Python Image # processing Libraryfrom PIL import Image # Giving The Original image Directory # SpecifiedOriginal_Image = Image.open("./gfgrotate.jpg") # Rotate Image By 180 Degreerotated_image1 = Original_Image.rotate(180) # This is Alternative Syntax To Rotate # The Imagerotated_image2 = Original_Image.transpose(Image.ROTATE_90) # This Will Rotate Image By 60 Degreerotated_image3 = Original_Image.rotate(60) rotated_image1.show()rotated_image2.show()rotated_image3.show() |
Output:
This is Image is Rotated By 180 Degree
This Image Is Rotated By 60 Degree
This Image Is Rotated By 90 Degree
The rotate() method of Python Image Processing Library Pillow Takes the number of degrees as a parameter and rotates the image in Counter Clockwise Direction to the number of degrees specified.
Method 2: Using Open-CV to rotate an image by an angle in Python
This is common that everyone knows that Python Open-CV is a module that will handle real-time applications related to computer vision. Open-CV works with image processing library imutils which deals with images. The imutils.rotate() function is used to rotate an image by an angle in Python.
Python3
import cv2 # importing cvimport imutils # read an image as input using OpenCVimage = cv2.imread(r".\gfgrotate.jpg") Rotated_image = imutils.rotate(image, angle=45)Rotated1_image = imutils.rotate(image, angle=90) # display the image using OpenCV of# angle 45cv2.imshow("Rotated", Rotated_image) # display the image using OpenCV of # angle 90cv2.imshow("Rotated", Rotated1_image) # This is used for To Keep On Displaying# The Image Until Any Key is Pressedcv2.waitKey(0) |
Output:
Image Rotated Using Open-CV in 45 Degree
Image Rotated Using Open-CV in 90 Degree
Even this Open-CV Rotates the image in Counter Clockwise direction to the number of degrees specified
