Python OpenCV - getRotationMatrix2D() Function

Last Updated : 04 Apr, 2025

cv2.getRotationMatrix2D() function is used to make the transformation matrix M which will be used for rotating a image.

Syntax:

cv2.getRotationMatrix2D(center, angle, scale)

Parameters:

center: Center of rotation
angle(θ): The angle of rotation in degrees. A positive value rotates the image anti-clockwise, while a negative value rotates the image clockwise.
scale: scaling factor which scales the image

Return: 2x3 Rotation Matrix M

M = \begin{bmatrix}\alpha & \beta & (1-\alpha)\cdot c_x-\beta \cdot c_y\\-\beta & \alpha & \beta\cdot c_x+(1-\alpha) \cdot c_y\end{bmatrix}

where,

\alpha = scale\cdot cos(\theta)\\\beta = scale\cdot sin(\theta)\\c_x\ and\ c_y\ are\ the\ coordinates\ of\ the\ center\ of\ the\ image.\\

This is a type of affine transformation. An affine transformation is transformation which preserves lines and parallelism. These transformation matrix are taken by warpaffine() function as parameter and the rotated image will be returned.

Image Used:

Example 1:

Python

import cv2  # Reading the image image = cv2.imread('image.jpeg')  # Extracting height and width from  # image shape height, width = image.shape[:2]  # get the center coordinates of the # image to create the 2D rotation # matrix center = (width/2, height/2)  # using cv2.getRotationMatrix2D()  # to get the rotation matrix rotate_matrix = cv2.getRotationMatrix2D(center=center, angle=90, scale=1)  # rotate the image using cv2.warpAffine  # 90 degree anticlockwise rotated_image = cv2.warpAffine(     src=image, M=rotate_matrix, dsize=(width, height))  cv2.imshow("rotated image:", rotated_image) cv2.imwrite('rotated_image.jpg', rotated_image)

Output-

Example 2:

Python

import cv2  # Reading the image image = cv2.imread('image.jpeg')  # Extracting height and width from  # image shape height, width = image.shape[:2]  # get the center coordinates of the  # image to create the 2D rotation matrix center = (width/2, height/2)  # using cv2.getRotationMatrix2D() to get # the rotation matrix rotate_matrix = cv2.getRotationMatrix2D(center=center, angle=-90, scale=1)  # rotate the image using cv2.warpAffine 90  # degree clockwise rotated_image = cv2.warpAffine(     src=image, M=rotate_matrix, dsize=(width, height))  cv2.imshow("rotated image:",rotated_image) cv2.imwrite('rotated_image.jpg', rotated_image)

Output-

Python

import cv2  # Reading the image image = cv2.imread('image.jpeg')  # Extracting height and width from image shape height, width = image.shape[:2]  # get the center coordinates of the image to  # create the 2D rotation matrix center = (width/2, height/2)  # using cv2.getRotationMatrix2D() to get  # the rotation matrix rotate_matrix = cv2.getRotationMatrix2D(center=center, angle=180, scale=1)  # rotate the image using cv2.warpAffine 180  # degree anticlockwise rotated_image = cv2.warpAffine(     src=image, M=rotate_matrix, dsize=(width, height))  cv2.imshow("rotated image:", rotated_image) cv2.imwrite('rotated_image.jpg', rotated_image)

Output-

Example 4:

Python

import cv2  # Reading the image image = cv2.imread('image.jpeg')  # Extracting height and width from image shape height, width = image.shape[:2]  # get the center coordinates of the image to # create the 2D rotation matrix center = (width/2, height/2)  # using cv2.getRotationMatrix2D() to get the # rotation matrix rotate_matrix = cv2.getRotationMatrix2D(center=center, angle=-180, scale=1)  # rotate the image using cv2.warpAffine 180 # degree clockwise rotated_image = cv2.warpAffine(     src=image, M=rotate_matrix, dsize=(width, height))  cv2.imshow("rotated image:", rotated_image) cv2.imwrite('rotated_image.jpg', rotated_image)

Output -

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Python OpenCV - getRotationMatrix2D() Function

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