


"""simple docstring"""







from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uinta, zeros
def _A		(		lowercase			,       lowercase						):







    """simple docstring"""
    a											=image.shape
    a											=cols - block_size[1] + 1
    a											=rows - block_size[0] + 1
    a											=zeros((dst_height * dst_width, block_size[1] * block_size[0])						)
    a											=0
    for i in range(0			,       lowerCAmelCase_						):
        for j in range(0			,       lowerCAmelCase_						):
            a											=ravel(image[i : i + block_size[0], j : j + block_size[1]]						)
            a											=window
            row += 1

    return image_array
def _A		(		lowercase			,       lowercase						):







    """simple docstring"""
    a											=image.shape[0], image.shape[1]
    a											=filter_kernel.shape[0]
    a											=k_size // 2
    # Pads image with the edge values of array.
    a											=pad(lowerCAmelCase_			,       lowerCAmelCase_			,       mode='''edge'''						)

    # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
    a											=imacol(lowerCAmelCase_			,       (k_size, k_size)						)

    #  turn the kernel into shape(k*k, 1)
    a											=ravel(lowerCAmelCase_						)
    # reshape and get the dst image
    a											=dot(lowerCAmelCase_			,       lowerCAmelCase_						).reshape(lowerCAmelCase_			,       lowerCAmelCase_						)
    return dst


if __name__ == "__main__":
       # read original image
       lowerCamelCase_  :  Tuple     		=    imread(R"""../image_data/lena.jpg""")
       # turn image in gray scale value
       lowerCamelCase_  :  Optional[Any]     		=    cvtColor(img, COLOR_BGR2GRAY)
       # Laplace operator
       lowerCamelCase_  :  Dict     		=    array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
       lowerCamelCase_  :  Dict     		=    img_convolve(gray, Laplace_kernel).astype(uinta)
       imshow("""Laplacian""", out)
       waitKey(0)






'''simple docstring'''

from __future__ import annotations

import random

# Adjacency list representation of this graph:
# https://en.wikipedia.org/wiki/File:Single_run_of_Karger%E2%80%99s_Mincut_algorithm.svg
UpperCAmelCase       :		List[Any]		=				{
    '1': ['2', '3', '4', '5'],
    '2': ['1', '3', '4', '5'],
    '3': ['1', '2', '4', '5', '10'],
    '4': ['1', '2', '3', '5', '6'],
    '5': ['1', '2', '3', '4', '7'],
    '6': ['7', '8', '9', '10', '4'],
    '7': ['6', '8', '9', '10', '5'],
    '8': ['6', '7', '9', '10'],
    '9': ['6', '7', '8', '10'],
    '10': ['6', '7', '8', '9', '3'],
}




def  _a     (				lowerCAmelCase_						):





      """simple docstring"""



      _snake_case		:						Dict         =  {node: {node} for node in graph}

      _snake_case		:						str         =  {node: graph[node][:] for node in graph}

      while len(lowerCAmelCase_						) > 2:
            # Choose a random edge.
            _snake_case		:						Optional[Any]         =  random.choice(list(graph_copy.keys()						)						)
            _snake_case		:						Union[str, Any]         =  random.choice(graph_copy[u]						)

            # Contract edge (u, v) to new node uv
            _snake_case		:						List[str]         =  u + v
            _snake_case		:						List[str]         =  list(set(graph_copy[u] + graph_copy[v]						)						)
            uv_neighbors.remove(lowerCAmelCase_						)
            uv_neighbors.remove(lowerCAmelCase_						)
            _snake_case		:						Tuple         =  uv_neighbors
            for neighbor in uv_neighbors:
                  graph_copy[neighbor].append(lowerCAmelCase_						)

            _snake_case		:						Tuple         =  set(contracted_nodes[u].union(contracted_nodes[v]						)						)

            # Remove nodes u and v.
            del graph_copy[u]
            del graph_copy[v]
            for neighbor in uv_neighbors:
                  if u in graph_copy[neighbor]:
                        graph_copy[neighbor].remove(lowerCAmelCase_						)
                  if v in graph_copy[neighbor]:
                        graph_copy[neighbor].remove(lowerCAmelCase_						)

    # Find cutset.
      _snake_case		:						Any         =  [contracted_nodes[node] for node in graph_copy]
      return {
          (node, neighbor)
          for node in groups[0]
          for neighbor in graph[node]
          if neighbor in groups[1]
      }


if __name__ == "__main__":
   print(partition_graph(TEST_GRAPH))


