


'''simple docstring'''




from __future__ import annotations

from collections import deque
from enum import Enum
from math import atana, degrees
from sys import maxsize




class  _lowercase   (  __lowercase       ):
   _SCREAMING_SNAKE_CASE     :     Optional[int]									=  1
   _SCREAMING_SNAKE_CASE     :     Optional[int]									=  2
   _SCREAMING_SNAKE_CASE     :     Optional[Any]									=  3
   def __repr__(	self					:			Dict			)   ->       List[Any]:
        return f'{self.__class__.__name__}.{self.name}'





def      _a		(lowercase__ :      tuple[int, int]       ,      lowercase__ :      int       ,      lowercase__ :      int	) -> float:






     """simple docstring"""
     __snake_case			,					__snake_case    			=	point
     return degrees(atana(y - miny       ,      x - minx	)	)





def      _a		(lowercase__ :      tuple[int, int]       ,      lowercase__ :      tuple[int, int]       ,      lowercase__ :      tuple[int, int]	) -> Direction:






     """simple docstring"""
     __snake_case			,					__snake_case    			=	starting
     __snake_case			,					__snake_case    			=	via
     __snake_case			,					__snake_case    			=	target
     __snake_case    			=	degrees(atana(ya - ya       ,      xa - xa	)	)
     via_angle %= 3_6_0
     __snake_case    			=	degrees(atana(ya - ya       ,      xa - xa	)	)
     target_angle %= 3_6_0
     # t-
     #  \ \
     #   \ v
     #    \|
     #     s
     # via_angle is always lower than target_angle, if direction is left.
     # If they are same, it means they are on a same line of convex hull.
     if target_angle > via_angle:
          return Direction.left
     elif target_angle == via_angle:
          return Direction.straight
     else:
          return Direction.right





def      _a		(lowercase__ :      list[tuple[int, int]]	) -> list[tuple[int, int]]:






     """simple docstring"""

     if len(lowercase__	) <= 2:
          # There is no convex hull
          raise ValueError('graham_scan: argument must contain more than 3 points.'	)
     if len(lowercase__	) == 3:
          return points
     # find the lowest and the most left point
     __snake_case    			=	0
     __snake_case			,					__snake_case    			=	maxsize, maxsize
     for i, point in enumerate(lowercase__	):
          __snake_case    			=	point[0]
          __snake_case    			=	point[1]
          if y < miny:
               __snake_case    			=	y
               __snake_case    			=	x
               __snake_case    			=	i
          if y == miny and x < minx:
               __snake_case    			=	x
               __snake_case    			=	i

    # remove the lowest and the most left point from points for preparing for sort
     points.pop(lowercase__	)

     __snake_case    			=	sorted(lowercase__       ,      key=lambda lowercase__	: angle_comparer(lowercase__       ,      lowercase__       ,      lowercase__	)	)
     # This insert actually costs complexity,
     # and you should instead add (minx, miny) into stack later.
     # I'm using insert just for easy understanding.
     sorted_points.insert(0       ,      (minx, miny)	)

     __snake_case    			=	deque()
     stack.append(sorted_points[0]	)
     stack.append(sorted_points[1]	)
     stack.append(sorted_points[2]	)
     # In any ways, the first 3 points line are towards left.
     # Because we sort them the angle from minx, miny.
     __snake_case    			=	Direction.left

     for i in range(3       ,      len(lowercase__	)	):
          while True:
               __snake_case    			=	stack[-2]
               __snake_case    			=	stack[-1]
               __snake_case    			=	sorted_points[i]
               __snake_case    			=	check_direction(lowercase__       ,      lowercase__       ,      lowercase__	)

               if next_direction == Direction.left:
                    __snake_case    			=	Direction.left
                    break
               if next_direction == Direction.straight:
                    if current_direction == Direction.left:
                         # We keep current_direction as left.
                         # Because if the straight line keeps as straight,
                         # we want to know if this straight line is towards left.
                         break
                    elif current_direction == Direction.right:
                         # If the straight line is towards right,
                         # every previous points on those straigh line is not convex hull.
                         stack.pop()
               if next_direction == Direction.right:
                    stack.pop()
          stack.append(sorted_points[i]	)
     return list(lowercase__	)








'''simple docstring'''




import numpy as np
from PIL import Image





def      _a		(lowercase__ :      np.array	) -> np.array:






     """simple docstring"""
     __snake_case			,					__snake_case			,					__snake_case    			=	rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
     return 0.29_89 * r + 0.58_70 * g + 0.11_40 * b





def      _a		(lowercase__ :      np.array	) -> np.array:






     """simple docstring"""
     return (gray > 1_2_7) & (gray <= 2_5_5)





def      _a		(lowercase__ :      np.array       ,      lowercase__ :      np.array	) -> np.array:






     """simple docstring"""
     __snake_case    			=	np.zeros_like(lowercase__	)
     __snake_case    			=	np.zeros(
         (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)	)

     # Copy image to padded image
     __snake_case    			=	image

     # Iterate over image & apply kernel
     for x in range(image.shape[1]	):
          for y in range(image.shape[0]	):
               __snake_case    			=	(
                   kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
               ).sum()
               __snake_case    			=	int(summation == 5	)
     return output


# kernel to be applied
_a      :      Tuple       				=      np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])

if __name__ == "__main__":
       # read original image
       _a      :      Any       				=      np.array(Image.open(R"..\image_data\lena.jpg"))
       # Apply erosion operation to a binary image
       _a      :      List[Any]       				=      erosion(grayabinary(rgbagray(image)), structuring_element)
       # Save the output image
       _a      :      int       				=      Image.fromarray(output).convert("RGB")
       pil_img.save("result_erosion.png")




