Image Rotation

Image rotation is a common image processing routine with applications in matching, alignment, and other image-based algorithms, in image rotation the image is rotated by a definite angle. It is used extensively in data augmentation, especially when it comes to image classification.

Python3

import numpy as np
import cv2 as cv
img = cv.imread('girlImage.jpg', 0)
rows, cols = img.shape
M = np.float32([[1,  0, 0], [0, -1, rows], [0,  0, 1]])
img_rotation = cv.warpAffine(img,
                             cv.getRotationMatrix2D((cols/2, rows/2),
                                                    30, 0.6),
                             (cols, rows))
cv.imshow('img', img_rotation)
cv.imwrite('rotation_out.jpg', img_rotation)
cv.waitKey(0)
cv.destroyAllWindows()

We have used the get rotation matrix function to define the parameter required in the warpAffine function to tell the function to make a matrix that can give a required rotation angle( here it is 30 degrees) with shrinkage of the image by 40%.

img_rotation = cv.warpAffine(img,
                             cv.getRotationMatrix2D((cols/2, rows/2), 30, 0.6),
                             (cols, rows))

Output:

Image Transformations using OpenCV in Python

In this tutorial, we are going to learn Image Transformation using the OpenCV module in Python.

Image Rotation

Python3

Image Transformations using OpenCV in Python

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