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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()

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