





'''simple docstring'''

lowercase__						:      Optional[Any]	=    {
    'A': ['B', 'C', 'E'],
    'B': ['A', 'D', 'E'],
    'C': ['A', 'F', 'G'],
    'D': ['B'],
    'E': ['A', 'B', 'D'],
    'F': ['C'],
    'G': ['C'],
}







def  a__    (    lowercase :					dict, lowercase :					Union[str, Any], lowercase :					int				)		->		list[str]:





     """simple docstring"""

     _UpperCamelCase       =	set()
     # keep track of all the paths to be checked
     _UpperCamelCase       =	[[start]]

     # return path if start is goal
     if start == goal:
          return [start]

     # keeps looping until all possible paths have been checked
     while queue:
          # pop the first path from the queue
          _UpperCamelCase       =	queue.pop(0				)
          # get the last node from the path
          _UpperCamelCase       =	path[-1]
          if node not in explored:
               _UpperCamelCase       =	graph[node]
               # go through all neighbour nodes, construct a new path and
               # push it into the queue
               for neighbour in neighbours:
                    _UpperCamelCase       =	list(lowercase				)
                    new_path.append(lowercase				)
                    queue.append(lowercase				)
                    # return path if neighbour is goal
                    if neighbour == goal:
                         return new_path

            # mark node as explored
               explored.add(lowercase				)

    # in case there's no path between the 2 nodes
     return []







def  a__    (    lowercase :					dict, lowercase :					Dict, lowercase :					Union[str, Any]				)		->		int:





     """simple docstring"""

     if not graph or start not in graph or target not in graph:
          return -1
     if start == target:
          return 0
     _UpperCamelCase       =	[start]
     _UpperCamelCase       =	set(lowercase				)
     # Keep tab on distances from `start` node.
     _UpperCamelCase       =	{start: 0, target: -1}
     while queue:
          _UpperCamelCase       =	queue.pop(0				)
          if node == target:
               _UpperCamelCase       =	(
                   dist[node] if dist[target] == -1 else min(dist[target], dist[node]				)
               )
          for adjacent in graph[node]:
               if adjacent not in visited:
                    visited.add(lowercase				)
                    queue.append(lowercase				)
                    _UpperCamelCase       =	dist[node] + 1
     return dist[target]


if __name__ == "__main__":
   print(bfs_shortest_path(demo_graph, 'G', 'D'))  # returns ['G', 'C', 'A', 'B', 'D']
   print(bfs_shortest_path_distance(demo_graph, 'G', 'D'))  # returns 4










'''simple docstring'''

from cva import destroyAllWindows, imread, imshow, waitKey







def  a__    (    lowercase :					str				)		->		Optional[int]:





     """simple docstring"""

     _UpperCamelCase   ,    _UpperCamelCase       =	img.shape[0], img.shape[1]

     # converting each pixel's color to its negative
     for i in range(lowercase				):
          for j in range(lowercase				):
               _UpperCamelCase       =	[255, 255, 255] - img[i][j]

     return img


if __name__ == "__main__":
   # read original image
   lowercase__						:      Optional[int]	=    imread('image_data/lena.jpg', 1)

   # convert to its negative
   lowercase__						:      Union[str, Any]	=    convert_to_negative(img)

   # show result image
   imshow('negative of original image', img)
   waitKey(0)
   destroyAllWindows()



