






'''simple docstring'''
from __future__ import annotations

from typing import Any





def        _a(     UpperCamelCase__ :  list							):




      '''simple docstring'''






      if not postfix_notation:
            return 0

      SCREAMING_SNAKE_CASE__   : Union[str, Any]													={'''+''', '''-''', '''*''', '''/'''}
      SCREAMING_SNAKE_CASE__   : Optional[int]													=[]

      for token in postfix_notation:
            if token in operations:
                  SCREAMING_SNAKE_CASE__						,		SCREAMING_SNAKE_CASE__   : Union[str, Any]													=stack.pop(), stack.pop()
                  if token == "+":
                        stack.append(a + b							)
                  elif token == "-":
                        stack.append(a - b							)
                  elif token == "*":
                        stack.append(a * b							)
                  else:
                        if a * b < 0 and a % b != 0:
                              stack.append(a // b + 1							)
                        else:
                              stack.append(a // b							)
            else:
                  stack.append(int(A__							)							)

      return stack.pop()


if __name__ == "__main__":
  import doctest

  doctest.testmod()


import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def      a      (			A__	:   int      ,   A__	:   int      ,   A__	:   int      ,   A__	:   int      ,   A__	:   int      ,   A__	:   int     )    ->      np.ndarray:





      """simple docstring"""



      if (ksize % 2) == 0:
            _lowercase	       =ksize + 1
      _lowercase	       =np.zeros((ksize, ksize)      ,   dtype=np.floataa     )

      # each value
      for y in range(A__     ):
            for x in range(A__     ):
                  # distance from center
                  _lowercase	       =x - ksize // 2
                  _lowercase	       =y - ksize // 2

                  # degree to radiant
                  _lowercase	       =theta / 180 * np.pi
                  _lowercase	       =np.cos(_theta     )
                  _lowercase	       =np.sin(_theta     )

                  # get kernel x
                  _lowercase	       =cos_theta * px + sin_theta * py

                  # get kernel y
                  _lowercase	       =-sin_theta * px + cos_theta * py

                  # fill kernel
                  _lowercase	       =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
  lowercase_									=   imread('../image_data/lena.jpg')
  # turn image in gray scale value
  lowercase_									=   cvtColor(img, COLOR_BGR2GRAY)

  # Apply multiple Kernel to detect edges
  lowercase_									=   np.zeros(gray.shape[:2])
  for theta in [0, 3_0, 6_0, 9_0, 1_2_0, 1_5_0]:
    lowercase_									=   gabor_filter_kernel(1_0, 8, theta, 1_0, 0, 0)
    out += filteraD(gray, CV_8UC3, kernel_aa)
  lowercase_									=   out / out.max() * 2_5_5
  lowercase_									=   out.astype(np.uinta)

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

  waitKey(0)


