from pathlib import Path import cv2 import numpy as np from matplotlib import pyplot as plt def get_rotation( img: np.ndarray, pt1: np.ndarray, pt2: np.ndarray, rows: int, cols: int ) -> np.ndarray: """ Get image rotation :param img: np.ndarray :param pt1: 3x2 list :param pt2: 3x2 list :param rows: columns image shape :param cols: rows image shape :return: np.ndarray """ matrix = cv2.getAffineTransform(pt1, pt2) return cv2.warpAffine(img, matrix, (rows, cols)) if __name__ == "__main__": # read original image image = cv2.imread( str(Path(__file__).resolve().parent.parent / "image_data" / "lena.jpg") ) # turn image in gray scale value gray_img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # get image shape img_rows, img_cols = gray_img.shape # set different points to rotate image pts1 = np.array([[50, 50], [200, 50], [50, 200]], np.float32) pts2 = np.array([[10, 100], [200, 50], [100, 250]], np.float32) pts3 = np.array([[50, 50], [150, 50], [120, 200]], np.float32) pts4 = np.array([[10, 100], [80, 50], [180, 250]], np.float32) # add all rotated images in a list images = [ gray_img, get_rotation(gray_img, pts1, pts2, img_rows, img_cols), get_rotation(gray_img, pts2, pts3, img_rows, img_cols), get_rotation(gray_img, pts2, pts4, img_rows, img_cols), ] # plot different image rotations fig = plt.figure(1) titles = ["Original", "Rotation 1", "Rotation 2", "Rotation 3"] for i, image in enumerate(images): plt.subplot(2, 2, i + 1), plt.imshow(image, "gray") plt.title(titles[i]) plt.axis("off") plt.subplots_adjust(left=0.0, bottom=0.05, right=1.0, top=0.95) plt.show()