
from __future__ import annotations

from collections.abc import Iterable
from dataclasses import dataclass
from typing import Any


class 							lowerCamelCase       :



  """simple docstring"""





  lowerCAmelCase_								=		("""_front""", """_back""", """_len""")


  @dataclass
  class 							lowerCamelCase       :



    """simple docstring"""





    lowerCAmelCase_								=		None
    lowerCAmelCase_								=		None
    lowerCAmelCase_								=		None



  class 							lowerCamelCase       :



    """simple docstring"""





    lowerCAmelCase_								=		("""_cur""",)

    def __init__(					self						,    __UpperCamelCase					):
        A_								=					cur

    def __iter__(					self					):
        return self

    def 					lowercase_						(					self					):
        if self._cur is None:
            # finished iterating
            raise StopIteration
        A_								=					self._cur.val
        A_								=					self._cur.next_node

        return val



  def __init__(					self						,    __UpperCamelCase = None					):
      A_								=					None
      A_								=					None
      A_								=					0

      if iterable is not None:
          # append every value to the deque
          for val in iterable:
              self.append(__UpperCamelCase					)

  def 					lowercase_						(					self						,    __UpperCamelCase					):
      A_								=					self._Node(__UpperCamelCase						,    __UpperCamelCase						,    __UpperCamelCase					)
      if self.is_empty():
          # front = back
          A_								=					A_								=					node
          A_								=					1
      else:
          # connect nodes
          A_								=					node
          A_								=					self._back
          A_								=					node  # assign new back to the new node

          self._len += 1

          # make sure there were no errors
          assert not self.is_empty(), "Error on appending value."

  def 					lowercase_						(					self						,    __UpperCamelCase					):
      A_								=					self._Node(__UpperCamelCase						,    __UpperCamelCase						,    __UpperCamelCase					)
      if self.is_empty():
          # front = back
          A_								=					A_								=					node
          A_								=					1
      else:
          # connect nodes
          A_								=					self._front
          A_								=					node
          A_								=					node  # assign new front to the new node

          self._len += 1

          # make sure there were no errors
          assert not self.is_empty(), "Error on appending value."

  def 					lowercase_						(					self						,    __UpperCamelCase					):
      for val in iterable:
          self.append(__UpperCamelCase					)

  def 					lowercase_						(					self						,    __UpperCamelCase					):
      for val in iterable:
          self.appendleft(__UpperCamelCase					)

  def 					lowercase_						(					self					):
      assert not self.is_empty(), "Deque is empty."

      A_								=					self._back
      A_								=					self._back.prev_node  # set new back
      # drop the last node - python will deallocate memory automatically
      A_								=					None

      self._len -= 1

      return topop.val

  def 					lowercase_						(					self					):
      assert not self.is_empty(), "Deque is empty."

      A_								=					self._front
      A_								=					self._front.next_node  # set new front and drop the first node
      A_								=					None

      self._len -= 1

      return topop.val

  def 					lowercase_						(					self					):
      return self._front is None

  def __len__(					self					):
      return self._len

  def __eq__(					self						,    __UpperCamelCase					):

      if not isinstance(__UpperCamelCase						,    __UpperCamelCase					):
          return NotImplemented

      A_								=					self._front
      A_								=					other._front

      # if the length of the dequeues are not the same, they are not equal
      if len(self					) != len(__UpperCamelCase					):
          return False

      while me is not None and oth is not None:
          # compare every value
          if me.val != oth.val:
              return False
          A_								=					me.next_node
          A_								=					oth.next_node

      return True

  def __iter__(					self					):
      return Deque._Iterator(self._front					)

  def __repr__(					self					):
      A_								=					[]
      A_								=					self._front
      while aux is not None:
          # append the values in a list to display
          values_list.append(aux.val					)
          A_								=					aux.next_node

      return f'[{", ".join(repr(__UpperCamelCase					) for val in values_list					)}]'


if __name__ == "__main__":
     import doctest

     doctest.testmod()








'''simple docstring'''







import cva
import numpy as np

from digital_image_processing.filters.convolve import img_convolve
from digital_image_processing.filters.sobel_filter import sobel_filter

_snake_case					: Union[str, Any]     			=					180



def       _a		(						_SCREAMING_SNAKE_CASE		: Optional[int]						,      _SCREAMING_SNAKE_CASE		: Dict	):
						_SCREAMING_SNAKE_CASE					=			k_size // 2
						_SCREAMING_SNAKE_CASE,				_SCREAMING_SNAKE_CASE					=			np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
						_SCREAMING_SNAKE_CASE					=			(
						    1
						    / (2 * np.pi * sigma)
						    * np.exp(-(np.square(_SCREAMING_SNAKE_CASE	) + np.square(_SCREAMING_SNAKE_CASE	)) / (2 * np.square(_SCREAMING_SNAKE_CASE	))	)
						)
						return g



def       _a		(						_SCREAMING_SNAKE_CASE		: int						,      _SCREAMING_SNAKE_CASE		: Tuple						,      _SCREAMING_SNAKE_CASE		: Dict	):
						_SCREAMING_SNAKE_CASE					=			np.zeros(_SCREAMING_SNAKE_CASE	)

						for row in range(1						,      image_shape[0] - 1	):
												for col in range(1						,      image_shape[1] - 1	):
																		_SCREAMING_SNAKE_CASE					=			gradient_direction[row, col]

																		if (
																		    0 <= direction < PI / 8
																		    or 15 * PI / 8 <= direction <= 2 * PI
																		    or 7 * PI / 8 <= direction <= 9 * PI / 8
																		):
																								_SCREAMING_SNAKE_CASE					=			sobel_grad[row, col - 1]
																								_SCREAMING_SNAKE_CASE					=			sobel_grad[row, col + 1]
																								if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
																														_SCREAMING_SNAKE_CASE					=			sobel_grad[row, col]

																		elif (
																		    PI / 8 <= direction < 3 * PI / 8
																		    or 9 * PI / 8 <= direction < 11 * PI / 8
																		):
																								_SCREAMING_SNAKE_CASE					=			sobel_grad[row + 1, col - 1]
																								_SCREAMING_SNAKE_CASE					=			sobel_grad[row - 1, col + 1]
																								if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
																														_SCREAMING_SNAKE_CASE					=			sobel_grad[row, col]

																		elif (
																		    3 * PI / 8 <= direction < 5 * PI / 8
																		    or 11 * PI / 8 <= direction < 13 * PI / 8
																		):
																								_SCREAMING_SNAKE_CASE					=			sobel_grad[row - 1, col]
																								_SCREAMING_SNAKE_CASE					=			sobel_grad[row + 1, col]
																								if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
																														_SCREAMING_SNAKE_CASE					=			sobel_grad[row, col]

																		elif (
																		    5 * PI / 8 <= direction < 7 * PI / 8
																		    or 13 * PI / 8 <= direction < 15 * PI / 8
																		):
																								_SCREAMING_SNAKE_CASE					=			sobel_grad[row - 1, col - 1]
																								_SCREAMING_SNAKE_CASE					=			sobel_grad[row + 1, col + 1]
																								if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
																														_SCREAMING_SNAKE_CASE					=			sobel_grad[row, col]

						return destination



def       _a		(						_SCREAMING_SNAKE_CASE		: List[str]						,      _SCREAMING_SNAKE_CASE		: int						,      _SCREAMING_SNAKE_CASE		: List[str]						,      _SCREAMING_SNAKE_CASE		: Any						,      _SCREAMING_SNAKE_CASE		: Any						,      _SCREAMING_SNAKE_CASE		: List[str]	):
						for row in range(1						,      image_shape[0] - 1	):
												for col in range(1						,      image_shape[1] - 1	):
																		if destination[row, col] >= threshold_high:
																								_SCREAMING_SNAKE_CASE					=			strong
																		elif destination[row, col] <= threshold_low:
																								_SCREAMING_SNAKE_CASE					=			0
																		else:
																								_SCREAMING_SNAKE_CASE					=			weak



def       _a		(						_SCREAMING_SNAKE_CASE		: List[Any]						,      _SCREAMING_SNAKE_CASE		: Dict						,      _SCREAMING_SNAKE_CASE		: Dict						,      _SCREAMING_SNAKE_CASE		: Any	):
						for row in range(1						,      image_shape[0]	):
												for col in range(1						,      image_shape[1]	):
																		if destination[row, col] == weak:
																								if 255 in (
																								    destination[row, col + 1],
																								    destination[row, col - 1],
																								    destination[row - 1, col],
																								    destination[row + 1, col],
																								    destination[row - 1, col - 1],
																								    destination[row + 1, col - 1],
																								    destination[row - 1, col + 1],
																								    destination[row + 1, col + 1],
																								):
																														_SCREAMING_SNAKE_CASE					=			strong
																								else:
																														_SCREAMING_SNAKE_CASE					=			0



def       _a		(						_SCREAMING_SNAKE_CASE		: Dict						,      _SCREAMING_SNAKE_CASE		: List[str]=15						,      _SCREAMING_SNAKE_CASE		: List[Any]=30						,      _SCREAMING_SNAKE_CASE		: Optional[int]=128						,      _SCREAMING_SNAKE_CASE		: List[Any]=255	):
						# gaussian_filter
						_SCREAMING_SNAKE_CASE					=			img_convolve(_SCREAMING_SNAKE_CASE						,      gen_gaussian_kernel(9						,      sigma=1.4	)	)
						# get the gradient and degree by sobel_filter
						_SCREAMING_SNAKE_CASE,				_SCREAMING_SNAKE_CASE					=			sobel_filter(_SCREAMING_SNAKE_CASE	)
						_SCREAMING_SNAKE_CASE					=			PI + np.radadeg(_SCREAMING_SNAKE_CASE	)

						_SCREAMING_SNAKE_CASE					=			suppress_non_maximum(image.shape						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE	)

						detect_high_low_threshold(
						    image.shape						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE	)

						track_edge(image.shape						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE	)

						return destination


if __name__ == "__main__":
						# read original image in gray mode
						_snake_case					: Any     			=					cva.imread(R"""../image_data/lena.jpg""", 0)
						# canny edge detection
						_snake_case					: int     			=					canny(lena)
						cva.imshow("""canny""", canny_destination)
						cva.waitKey(0)