





import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey



def 		A_				(     _lowerCAmelCase							,   _lowerCAmelCase							,   _lowerCAmelCase							,   _lowerCAmelCase							,   _lowerCAmelCase							,   _lowerCAmelCase     )						-> np.ndarray:

 # prepare kernel
 # the kernel size have to be odd
 if (ksize % 2) == 0:
  UpperCamelCase	:					Union[str, Any]       	=   ksize + 1
 UpperCamelCase	:					str       	=   np.zeros((ksize, ksize)							,   dtype=np.floataa     )

 # each value
 for y in range(_lowerCAmelCase     ):
  for x in range(_lowerCAmelCase     ):
   # distance from center
   UpperCamelCase	:					Any       	=   x - ksize // 2
   UpperCamelCase	:					Any       	=   y - ksize // 2

   # degree to radiant
   UpperCamelCase	:					int       	=   theta / 180 * np.pi
   UpperCamelCase	:					List[Any]       	=   np.cos(_theta     )
   UpperCamelCase	:					Optional[Any]       	=   np.sin(_theta     )

   # get kernel x
   UpperCamelCase	:					Dict       	=   cos_theta * px + sin_theta * py

   # get kernel y
   UpperCamelCase	:					Optional[Any]       	=   -sin_theta * px + cos_theta * py

   # fill kernel
   UpperCamelCase	:					Optional[Any]       	=   np.exp(
       -(_x**2 + gamma**2 * _y**2) / (2 * sigma**2)     ) * np.cos(2 * np.pi * _x / lambd + psi     )

 return gabor


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    # read original image
    __lowerCamelCase       :     Union[str, Any]   =     imread("""../image_data/lena.jpg""")
    # turn image in gray scale value
    __lowerCamelCase       :     Optional[Any]   =     cvtColor(img, COLOR_BGR2GRAY)

    # Apply multiple Kernel to detect edges
    __lowerCamelCase       :     Optional[Any]   =     np.zeros(gray.shape[:2])
    for theta in [0, 30, 60, 90, 120, 150]:
        __lowerCamelCase       :     Optional[Any]   =     gabor_filter_kernel(10, 8, theta, 10, 0, 0)
        out += filteraD(gray, CV_8UC3, kernel_aa)
    __lowerCamelCase       :     Tuple   =     out / out.max() * 255
    __lowerCamelCase       :     Optional[Any]   =     out.astype(np.uinta)

    imshow("""Original""", gray)
    imshow("""Gabor filter with 20x20 mask and 6 directions""", out)

    waitKey(0)

"""simple docstring"""


import math






def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					[]
  _UpperCAmelCase         =					2
  _UpperCAmelCase         =					int(math.sqrt(lowercase						)						)  # Size of every segment
  _UpperCAmelCase         =					[True] * (end + 1)
  _UpperCAmelCase         =					[]

  while start <= end:
    if temp[start] is True:
      in_prime.append(lowercase						)
      for i in range(start * start      ,end + 1      ,lowercase						):
        _UpperCAmelCase         =					False
    start += 1
  prime += in_prime

  _UpperCAmelCase         =					end + 1
  _UpperCAmelCase         =					min(2 * end      ,lowercase						)

  while low <= n:
    _UpperCAmelCase         =					[True] * (high - low + 1)
    for each in in_prime:
      _UpperCAmelCase         =					math.floor(low / each						) * each
      if t < low:
        t += each

      for j in range(lowercase      ,high + 1      ,lowercase						):
        _UpperCAmelCase         =					False

    for j in range(len(lowercase						)						):
      if temp[j] is True:
        prime.append(j + low						)

    _UpperCAmelCase         =					high + 1
    _UpperCAmelCase         =					min(high + end      ,lowercase						)

  return prime

print(sieve(1_0**6))
