




'''simple docstring'''







import numpy as np

lowercase      :   str      =       [
    ["""a""", """b""", """c""", """d""", """e"""],
    ["""f""", """g""", """h""", """i""", """k"""],
    ["""l""", """m""", """n""", """o""", """p"""],
    ["""q""", """r""", """s""", """t""", """u"""],
    ["""v""", """w""", """x""", """y""", """z"""],
]







class 					_a :





     '''simple docstring'''



     def __init__(				self							)      ->				None:
          snake_case			:      Dict        =			np.array(__a							)







     def 			snake_case_      (				self							,__a							)      ->				np.ndarray:
          snake_case ,		snake_case			:      Optional[Any]        =			np.where(letter == self.SQUARE							)
          snake_case			:      List[Any]        =			np.concatenate([indexa + 1, indexa + 1]							)
          return indexes







     def 			snake_case_      (				self							,__a							,__a							)      ->				str:
          snake_case			:      List[Any]        =			self.SQUARE[indexa - 1, indexa - 1]
          return letter







     def 			snake_case_      (				self							,__a							)      ->				str:
          snake_case			:      List[Any]        =			message.lower()
          snake_case			:      Dict        =			message.replace(""" """							,""""""							)
          snake_case			:      List[str]        =			message.replace("""j"""							,"""i"""							)

          snake_case			:      Optional[int]        =			np.empty((2, len(__a							))							)
          for letter_index in range(len(__a							)							):
               snake_case			:      Tuple        =			self.letter_to_numbers(message[letter_index]							)

               snake_case			:      Optional[Any]        =			numbers[0]
               snake_case			:      List[str]        =			numbers[1]

          snake_case			:      List[str]        =			first_step.reshape(2 * len(__a							)							)
          snake_case			:      List[Any]        =			""""""
          for numbers_index in range(len(__a							)							):
               snake_case			:      List[str]        =			int(second_step[numbers_index * 2]							)
               snake_case			:      List[Any]        =			int(second_step[(numbers_index * 2) + 1]							)
               snake_case			:      str        =			self.numbers_to_letter(__a							,__a							)
               snake_case			:      Any        =			encoded_message + letter

          return encoded_message







     def 			snake_case_      (				self							,__a							)      ->				str:
          snake_case			:      Any        =			message.lower()
          message.replace(""" """							,""""""							)
          snake_case			:      Dict        =			np.empty(2 * len(__a							)							)
          for letter_index in range(len(__a							)							):
               snake_case			:      str        =			self.letter_to_numbers(message[letter_index]							)
               snake_case			:      Any        =			numbers[0]
               snake_case			:      int        =			numbers[1]

          snake_case			:      List[str]        =			first_step.reshape((2, len(__a							))							)
          snake_case			:      Dict        =			""""""
          for numbers_index in range(len(__a							)							):
               snake_case			:      Optional[Any]        =			int(second_step[0, numbers_index]							)
               snake_case			:      Optional[int]        =			int(second_step[1, numbers_index]							)
               snake_case			:      Tuple        =			self.numbers_to_letter(__a							,__a							)
               snake_case			:      int        =			decoded_message + letter

          return decoded_message









'''simple docstring'''







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

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



def        lowerCamelCase__				(      ):
     snake_case			:      Optional[int]        =			cn.convert_to_negative(__lowercase				)
     # assert negative_img array for at least one True
     assert negative_img.any()



def        lowerCamelCase__				(      ):
     with Image.open("""digital_image_processing/image_data/lena_small.jpg"""				) as img:
          # Work around assertion for response
          assert str(cc.change_contrast(__lowercase     ,   110				)				).startswith(
              """<PIL.Image.Image image mode=RGB size=100x100 at"""				)



def        lowerCamelCase__				(      ):
     snake_case			:      Union[str, Any]        =			canny.gen_gaussian_kernel(9     ,   sigma=1.4				)
     # Assert ambiguous array
     assert resp.all()



def        lowerCamelCase__				(      ):
     snake_case			:      Optional[Any]        =			imread("""digital_image_processing/image_data/lena_small.jpg"""     ,   0				)
     # assert ambiguous array for all == True
     assert canny_img.all()
     snake_case			:      Any        =			canny.canny(__lowercase				)
     # assert canny array for at least one True
     assert canny_array.any()



def        lowerCamelCase__				(      ):
     assert gg.gaussian_filter(__lowercase     ,   5     ,   sigma=0.9				).all()



def        lowerCamelCase__				(      ):
     # laplace diagonals
     snake_case			:      int        =			array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]				)
     snake_case			:      Tuple        =			conv.img_convolve(__lowercase     ,   __lowercase				).astype(__lowercase				)
     assert res.any()



def        lowerCamelCase__				(      ):
     assert med.median_filter(__lowercase     ,   3				).any()



def        lowerCamelCase__				(      ):
     snake_case ,		snake_case			:      Dict        =			sob.sobel_filter(__lowercase				)
     assert grad.any() and theta.any()



def        lowerCamelCase__				(      ):
     snake_case			:      int        =			sp.make_sepia(__lowercase     ,   20				)
     assert sepia.all()



def        lowerCamelCase__				(      __lowercase = "digital_image_processing/image_data/lena_small.jpg"				):
     snake_case			:      int        =			bs.Burkes(imread(__lowercase     ,   1				)     ,   120				)
     burkes.process()
     assert burkes.output_img.any()



def        lowerCamelCase__				(      __lowercase = "digital_image_processing/image_data/lena_small.jpg"     ,   ):
     snake_case			:      Dict        =			rs.NearestNeighbour(imread(__lowercase     ,   1				)     ,   400     ,   200				)
     nn.process()
     assert nn.output.any()







def        lowerCamelCase__				(      ):
     snake_case			:      int        =			"""digital_image_processing/image_data/lena.jpg"""

     # Reading the image and converting it to grayscale.
     snake_case			:      Tuple        =			imread(__lowercase     ,   0				)

     # Test for get_neighbors_pixel function() return not None
     snake_case			:      Optional[int]        =			0
     snake_case			:      Tuple        =			0
     snake_case			:      Any        =			image[x_coordinate][y_coordinate]

     snake_case			:      Any        =			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
     snake_case			:      List[Any]        =			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]				):
               snake_case			:      Optional[Any]        =			lbp.local_binary_value(__lowercase     ,   __lowercase     ,   __lowercase				)

     assert lbp_image.any()



