





from pathlib import Path

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



def _a				(	lowerCamelCase:   np.ndarray					,				lowerCamelCase:   np.ndarray					,				lowerCamelCase:   np.ndarray					,				lowerCamelCase:   int					,				lowerCamelCase:   int )	->						np.ndarray:







      '''simple docstring'''






      __A          =				cva.getAffineTransform(lowerCamelCase					,				lowerCamelCase )
      return cva.warpAffine(lowerCamelCase					,				lowerCamelCase					,				(rows, cols) )


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

       # set different points to rotate image
       snake_case__					:							Any													=     np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
       snake_case__					:							str													=     np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
       snake_case__					:							int													=     np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
       snake_case__					:							List[str]													=     np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

       # add all rotated images in a list
       snake_case__					:							Optional[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
       snake_case__					:							Optional[Any]													=     plt.figure(1)
       snake_case__					:							Dict													=     ['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()












def _a				(	lowerCamelCase:   dict )	->						bool:







      '''simple docstring'''






      __A          =				set()
      # To detect a back edge, keep track of vertices currently in the recursion stack
      __A          =				set()
      return any(
          node not in visited and depth_first_search(lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase )
          for node in graph )



def _a				(	lowerCamelCase:   dict					,				lowerCamelCase:   int					,				lowerCamelCase:   set					,				lowerCamelCase:   set )	->						bool:







      '''simple docstring'''






      visited.add(lowerCamelCase )
      rec_stk.add(lowerCamelCase )

      for node in graph[vertex]:
            if node not in visited:
                  if depth_first_search(lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase ):
                        return True
            elif node in rec_stk:
                  return True

    # The node needs to be removed from recursion stack before function ends
      rec_stk.remove(lowerCamelCase )
      return False


if __name__ == "__main__":
       from doctest import testmod

       testmod()





