




import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

lowerCamelCase							:						Any					       =  imread(r"digital_image_processing/image_data/lena_small.jpg")
lowerCamelCase							:						List[Any]					       =  cvtColor(img, COLOR_BGR2GRAY)

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      lowerCamelCase_							=       cn.convert_to_negative(lowercase	)
      # assert negative_img array for at least one True
      assert negative_img.any()

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      with Image.open('digital_image_processing/image_data/lena_small.jpg'	) as img:
            # Work around assertion for response
            assert str(cc.change_contrast(lowercase      ,				1_10	)	).startswith(
                '<PIL.Image.Image image mode=RGB size=100x100 at'	)

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      lowerCamelCase_							=       canny.gen_gaussian_kernel(9      ,				sigma=1.4	)
      # Assert ambiguous array
      assert resp.all()

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      lowerCamelCase_							=       imread('digital_image_processing/image_data/lena_small.jpg'      ,				0	)
      # assert ambiguous array for all == True
      assert canny_img.all()
      lowerCamelCase_							=       canny.canny(lowercase	)
      # assert canny array for at least one True
      assert canny_array.any()

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      assert gg.gaussian_filter(lowercase      ,				5      ,				sigma=0.9	).all()

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      lowerCamelCase_							=       array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]	)
      lowerCamelCase_							=       conv.img_convolve(lowercase      ,				lowercase	).astype(lowercase	)
      assert res.any()

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      assert med.median_filter(lowercase      ,				3	).any()

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      lowerCamelCase_	,							lowerCamelCase_							=       sob.sobel_filter(lowercase	)
      assert grad.any() and theta.any()

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      lowerCamelCase_							=       sp.make_sepia(lowercase      ,				20	)
      assert sepia.all()

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			str = "digital_image_processing/image_data/lena_small.jpg"	):


      '''simple docstring'''



      lowerCamelCase_							=       bs.Burkes(imread(lowercase      ,				1	)      ,				1_20	)
      burkes.process()
      assert burkes.output_img.any()

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			str = "digital_image_processing/image_data/lena_small.jpg"      ,				):


      '''simple docstring'''



      lowerCamelCase_							=       rs.NearestNeighbour(imread(lowercase      ,				1	)      ,				4_00      ,				2_00	)
      nn.process()
      assert nn.output.any()






def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      lowerCamelCase_							=       'digital_image_processing/image_data/lena.jpg'

      # Reading the image and converting it to grayscale.
      lowerCamelCase_							=       imread(lowercase      ,				0	)

      # Test for get_neighbors_pixel function() return not None
      lowerCamelCase_							=       0
      lowerCamelCase_							=       0
      lowerCamelCase_							=       image[x_coordinate][y_coordinate]

      lowerCamelCase_							=       lbp.get_neighbors_pixel(
          lowercase      ,				lowercase      ,				lowercase      ,				lowercase	)

      assert neighbors_pixels is not None

      # Test for local_binary_pattern function()
      # Create a numpy array as the same height and width of read image
      lowerCamelCase_							=       np.zeros((image.shape[0], image.shape[1])	)

      # Iterating through the image and calculating the local binary pattern value
      # for each pixel.
      for i in range(0      ,				image.shape[0]	):
            for j in range(0      ,				image.shape[1]	):
                  lowerCamelCase_							=       lbp.local_binary_value(lowercase      ,				lowercase      ,				lowercase	)

      assert lbp_image.any()




"""simple docstring"""


import heapq






def      __UpperCAmelCase       (      lowercase		):







  """simple docstring"""
  _UpperCAmelCase    			=   []

  # for each node and his adjacency list add them and the rank of the node to queue
  # using heapq module the queue will be filled like a Priority Queue
  # heapq works with a min priority queue, so I used -1*len(v) to build it
  for key, value in graph.items():
    # O(log(n))
    heapq.heappush(lowercase ,[-1 * len(lowercase		), (key, value)]		)

  # chosen_vertices = set of chosen vertices
  _UpperCAmelCase    			=   set()

  # while queue isn't empty and there are still edges
  #   (queue[0][0] is the rank of the node with max rank)
  while queue and queue[0][0] != 0:
    # extract vertex with max rank from queue and add it to chosen_vertices
    _UpperCAmelCase    			=   heapq.heappop(lowercase		)[1][0]
    chosen_vertices.add(lowercase		)

    # Remove all arcs adjacent to argmax
    for elem in queue:
      # if v haven't adjacent node, skip
      if elem[0] == 0:
        continue
      # if argmax is reachable from elem
      # remove argmax from elem's adjacent list and update his rank
      if argmax in elem[1][1]:
        _UpperCAmelCase    			=   elem[1][1].index(lowercase		)
        del elem[1][1][index]
        elem[0] += 1
        # re-order the queue
    heapq.heapify(lowercase		)
  return chosen_vertices


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    UpperCAmelCase__			=    {0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
    print(F'''Minimum vertex cover:\n{greedy_min_vertex_cover(graph)}''')
