






'''simple docstring'''





__A							:							Tuple  							=		tuple[float, float, float]
__A							:							int  							=		tuple[float, float, float]






def    lowerCamelCase_     (    lowercase__				,     lowercase__):
 lowerCamelCase__  =     end_pointa[0] - end_pointa[0]
 lowerCamelCase__  =     end_pointa[1] - end_pointa[1]
 lowerCamelCase__  =     end_pointa[2] - end_pointa[2]
 return (x, y, z)






def    lowerCamelCase_     (    lowercase__				,     lowercase__):
 lowerCamelCase__  =     ab[1] * ac[2] - ab[2] * ac[1]  # *i
 lowerCamelCase__  =     (ab[0] * ac[2] - ab[2] * ac[0]) * -1  # *j
 lowerCamelCase__  =     ab[0] * ac[1] - ab[1] * ac[0]  # *k
 return (x, y, z)






def    lowerCamelCase_     (    lowercase__				,     lowercase__):
 return tuple(round(lowercase__				,     lowercase__) for x in vector) == (0, 0, 0)






def    lowerCamelCase_     (    lowercase__				,     lowercase__				,     lowercase__				,     lowercase__ = 10):
 lowerCamelCase__  =     create_vector(lowercase__				,     lowercase__)
 lowerCamelCase__  =     create_vector(lowercase__				,     lowercase__)
 return is_zero_vector(get_ad_vectors_cross(lowercase__				,     lowercase__)				,     lowercase__)









'''simple docstring'''





from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt






def    lowerCamelCase_     (    lowercase__				,     lowercase__				,     lowercase__				,     lowercase__				,     lowercase__):
 lowerCamelCase__  =     cva.getAffineTransform(lowercase__				,     lowercase__)
 return cva.warpAffine(lowercase__				,     lowercase__				,     (rows, cols))


if __name__ == "__main__":
 # read original image
 __A							:							Any  							=		cva.imread(
     str(Path(__file__).resolve().parent.parent / """image_data""" / """lena.jpg""")
 )
 # turn image in gray scale value
 __A							:							int  							=		cva.cvtColor(image, cva.COLOR_BGR2GRAY)
 # get image shape
 __A							,			__A							:							Dict  							=		gray_img.shape

 # set different points to rotate image
 __A							:							int  							=		np.array([[50, 50], [2_00, 50], [50, 2_00]], np.floataa)
 __A							:							Any  							=		np.array([[10, 1_00], [2_00, 50], [1_00, 2_50]], np.floataa)
 __A							:							str  							=		np.array([[50, 50], [1_50, 50], [1_20, 2_00]], np.floataa)
 __A							:							Optional[int]  							=		np.array([[10, 1_00], [80, 50], [1_80, 2_50]], np.floataa)

 # add all rotated images in a list
 __A							:							List[Any]  							=		[
     gray_img,
     get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
     get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
     get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
 ]

 # plot different image rotations
 __A							:							int  							=		plt.figure(1)
 __A							:							int  							=		["""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()

