


from __future__ import annotations


class       __lowerCAmelCase       :






  """simple docstring"""





  def __init__(       self    :    str      ,			_lowerCAmelCase    :    int					)				->	None:




     """simple docstring"""
     snake_case_         =   vertices
     snake_case_         =   [[0] * vertices for _ in range(_lowerCAmelCase					)]



  def    lowerCAmelCase__					(       self    :    Tuple      ,			_lowerCAmelCase    :    list[int]					)				->	None:




     """simple docstring"""
     print("Vertex \t Distance from Source"					)
     for vertex in range(self.vertices					):
        print(_lowerCAmelCase      ,			"\t\t"      ,			distances_from_source[vertex]					)



  def    lowerCAmelCase__					(       self    :    int      ,			_lowerCAmelCase    :    list[int]      ,			_lowerCAmelCase    :    list[bool]					)				->	int:




     """simple docstring"""
     snake_case_         =   1e7
     snake_case_         =   0

     # Search not nearest vertex not in the shortest path tree
     for vertex in range(self.vertices					):
        if distances_from_source[vertex] < minimum and visited[vertex] is False:
           snake_case_         =   distances_from_source[vertex]
           snake_case_         =   vertex
     return min_index



  def    lowerCAmelCase__					(       self    :    Optional[int]      ,			_lowerCAmelCase    :    int					)				->	None:




     """simple docstring"""
     snake_case_         =   [int(1e7					)] * self.vertices  # distances from the source
     snake_case_         =   0
     snake_case_         =   [False] * self.vertices

     for _ in range(self.vertices					):
        snake_case_         =   self.minimum_distance(_lowerCAmelCase      ,			_lowerCAmelCase					)
        snake_case_         =   True

        # Update dist value of the adjacent vertices
        # of the picked vertex only if the current
        # distance is greater than new distance and
        # the vertex in not in the shortest path tree
        for v in range(self.vertices					):
           if (
               self.graph[u][v] > 0
               and visited[v] is False
               and distances[v] > distances[u] + self.graph[u][v]
           ):
              snake_case_         =   distances[u] + self.graph[u][v]

     self.print_solution(_lowerCAmelCase					)


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE		:Optional[Any]											=       Graph(9)
   SCREAMING_SNAKE_CASE		:Any											=       [
       [0, 4, 0, 0, 0, 0, 0, 8, 0],
       [4, 0, 8, 0, 0, 0, 0, 11, 0],
       [0, 8, 0, 7, 0, 4, 0, 0, 2],
       [0, 0, 7, 0, 9, 14, 0, 0, 0],
       [0, 0, 0, 9, 0, 10, 0, 0, 0],
       [0, 0, 4, 14, 10, 0, 2, 0, 0],
       [0, 0, 0, 0, 0, 2, 0, 1, 6],
       [8, 11, 0, 0, 0, 0, 1, 0, 7],
       [0, 0, 2, 0, 0, 0, 6, 7, 0],
   ]
   graph.dijkstra(0)








import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey


class       __lowerCAmelCase       :






  """simple docstring"""





  def __init__(       self    :    Optional[Any]      ,			_lowerCAmelCase    :    Union[str, Any]      ,			_lowerCAmelCase    :    int					)				->	Tuple:




     """simple docstring"""
     snake_case_         =   0
     # max greyscale value for #FFFFFF
     snake_case_         =   int(self.get_greyscale(2_5_5      ,			2_5_5      ,			2_5_5					)					)

     if not self.min_threshold < threshold < self.max_threshold:
        snake_case_         =   F'''Factor value should be from 0 to {self.max_threshold}'''
        raise ValueError(_lowerCAmelCase					)

     snake_case_         =   input_img
     snake_case_         =   threshold
     snake_case_      ,      snake_case_         =   self.input_img.shape[1], self.input_img.shape[0]

     # error table size (+4 columns and +1 row) greater than input image because of
     # lack of if statements
     snake_case_         =   [
         [0 for _ in range(self.height + 4					)] for __ in range(self.width + 1					)
     ]
     snake_case_         =   np.ones((self.width, self.height, 3)      ,			np.uinta					) * 2_5_5



  @classmethod
  def    lowerCAmelCase__					(       cls    :    Optional[Any]      ,			_lowerCAmelCase    :    int      ,			_lowerCAmelCase    :    int      ,			_lowerCAmelCase    :    int					)				->	float:




     """simple docstring"""
     return 0.114 * blue + 0.587 * green + 0.2_126 * red



  def    lowerCAmelCase__					(       self    :    Union[str, Any]					)				->	None:




     """simple docstring"""
     for y in range(self.height					):
        for x in range(self.width					):
           snake_case_         =   int(self.get_greyscale(*self.input_img[y][x]					)					)
           if self.threshold > greyscale + self.error_table[y][x]:
              snake_case_         =   (0, 0, 0)
              snake_case_         =   greyscale + self.error_table[x][y]
           else:
              snake_case_         =   (2_5_5, 2_5_5, 2_5_5)
              snake_case_         =   greyscale + self.error_table[x][y] - 2_5_5
           self.error_table[y][x + 1] += int(8 / 3_2 * current_error					)
           self.error_table[y][x + 2] += int(4 / 3_2 * current_error					)
           self.error_table[y + 1][x] += int(8 / 3_2 * current_error					)
           self.error_table[y + 1][x + 1] += int(4 / 3_2 * current_error					)
           self.error_table[y + 1][x + 2] += int(2 / 3_2 * current_error					)
           self.error_table[y + 1][x - 1] += int(4 / 3_2 * current_error					)
           self.error_table[y + 1][x - 2] += int(2 / 3_2 * current_error					)


if __name__ == "__main__":
   # create Burke's instances with original images in greyscale
   SCREAMING_SNAKE_CASE		:Dict											=       [
       Burkes(imread('''image_data/lena.jpg''', 1), threshold)
       for threshold in (1, 1_26, 1_30, 1_40)
   ]

   for burkes in burkes_instances:
      burkes.process()

   for burkes in burkes_instances:
      imshow(
          F'''Original image with dithering threshold: {burkes.threshold}''',
          burkes.output_img,
      )

   waitKey(0)
   destroyAllWindows()




