




"""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

A_      =    imread(r'''digital_image_processing/image_data/lena_small.jpg''')
A_      =    cvtColor(img, COLOR_BGR2GRAY)


def  UpperCAmelCase__	():
  """simple docstring"""

  _snake_case							:		Tuple								=  cn.convert_to_negative(snake_case__   )
  # assert negative_img array for at least one True
  assert negative_img.any()


def  UpperCAmelCase__	():
  """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(snake_case__		,       1_10   )   ).startswith(
        """<PIL.Image.Image image mode=RGB size=100x100 at"""   )


def  UpperCAmelCase__	():
  """simple docstring"""

  _snake_case							:		Optional[int]								=  canny.gen_gaussian_kernel(9		,       sigma=1.4   )
  # Assert ambiguous array
  assert resp.all()


def  UpperCAmelCase__	():
  """simple docstring"""

  _snake_case							:		int								=  imread("""digital_image_processing/image_data/lena_small.jpg"""		,       0   )
  # assert ambiguous array for all == True
  assert canny_img.all()
  _snake_case							:		Tuple								=  canny.canny(snake_case__   )
  # assert canny array for at least one True
  assert canny_array.any()


def  UpperCAmelCase__	():
  """simple docstring"""

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


def  UpperCAmelCase__	():
  """simple docstring"""

  _snake_case							:		Any								=  array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]   )
  _snake_case							:		Union[str, Any]								=  conv.img_convolve(snake_case__		,       snake_case__   ).astype(snake_case__   )
  assert res.any()


def  UpperCAmelCase__	():
  """simple docstring"""

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


def  UpperCAmelCase__	():
  """simple docstring"""

  _snake_case		, _snake_case							:		Any								=  sob.sobel_filter(snake_case__   )
  assert grad.any() and theta.any()


def  UpperCAmelCase__	():
  """simple docstring"""

  _snake_case							:		Optional[int]								=  sp.make_sepia(snake_case__		,       20   )
  assert sepia.all()


def  UpperCAmelCase__	(snake_case__							: str = "digital_image_processing/image_data/lena_small.jpg"   ):
  """simple docstring"""

  _snake_case							:		Union[str, Any]								=  bs.Burkes(imread(snake_case__		,       1   )		,       1_20   )
  burkes.process()
  assert burkes.output_img.any()


def  UpperCAmelCase__	(snake_case__							: str = "digital_image_processing/image_data/lena_small.jpg"		,       ):
  """simple docstring"""

  _snake_case							:		int								=  rs.NearestNeighbour(imread(snake_case__		,       1   )		,       4_00		,       2_00   )
  nn.process()
  assert nn.output.any()






def  UpperCAmelCase__	():
  """simple docstring"""

  _snake_case							:		Tuple								=  """digital_image_processing/image_data/lena.jpg"""

  # Reading the image and converting it to grayscale.
  _snake_case							:		Any								=  imread(snake_case__		,       0   )

  # Test for get_neighbors_pixel function() return not None
  _snake_case							:		Any								=  0
  _snake_case							:		str								=  0
  _snake_case							:		Union[str, Any]								=  image[x_coordinate][y_coordinate]

  _snake_case							:		List[Any]								=  lbp.get_neighbors_pixel(
      snake_case__		,       snake_case__		,       snake_case__		,       snake_case__   )

  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							:		Dict								=  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							:		List[str]								=  lbp.local_binary_value(snake_case__		,       snake_case__		,       snake_case__   )

  assert lbp_image.any()








"""simple docstring"""


def  UpperCAmelCase__	(snake_case__							: int = 1_00_00_00   ):
  """simple docstring"""

  _snake_case							:		Dict								=  [i - 1 for i in range(limit + 1   )]

  for i in range(2		,       limit + 1   ):
    if phi[i] == i - 1:
      for j in range(2 * i		,       limit + 1		,       snake_case__   ):
        phi[j] -= phi[j] // i

  return sum(phi[2 : limit + 1]   )


if __name__ == "__main__":
     print(solution())


