





'''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

_lowerCamelCase				:	Optional[int]				    =       180




def    __a (     UpperCAmelCase       ,			UpperCAmelCase    )      ->int:



	"""simple docstring"""







	A							  =      k_size // 2
	A  ,    A							  =      np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
	A							  =      (
	    1
	    / (2 * np.pi * sigma)
	    * np.exp(-(np.square(UpperCAmelCase    ) + np.square(UpperCAmelCase    )) / (2 * np.square(UpperCAmelCase    ))    )
	)
	return g




def    __a (     UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )      ->Optional[int]:



	"""simple docstring"""







	A							  =      np.zeros(UpperCAmelCase    )

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

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

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

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

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

	return destination




def    __a (     UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )      ->Tuple:



	"""simple docstring"""







	for row in range(1       ,			image_shape[0] - 1    ):
		for col in range(1       ,			image_shape[1] - 1    ):
			if destination[row, col] >= threshold_high:
				A							  =      strong
			elif destination[row, col] <= threshold_low:
				A							  =      0
			else:
				A							  =      weak




def    __a (     UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )      ->str:



	"""simple docstring"""







	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],
				):
					A							  =      strong
				else:
					A							  =      0




def    __a (     UpperCAmelCase       ,			UpperCAmelCase=15       ,			UpperCAmelCase=30       ,			UpperCAmelCase=128       ,			UpperCAmelCase=255    )      ->int:



	"""simple docstring"""







	A							  =      img_convolve(UpperCAmelCase       ,			gen_gaussian_kernel(9       ,			sigma=1.4    )    )
	# get the gradient and degree by sobel_filter
	A  ,    A							  =      sobel_filter(UpperCAmelCase    )
	A							  =      PI + np.radadeg(UpperCAmelCase    )

	A							  =      suppress_non_maximum(image.shape       ,			UpperCAmelCase       ,			UpperCAmelCase    )

	detect_high_low_threshold(
	    image.shape       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )

	track_edge(image.shape       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )

	return destination


if __name__ == "__main__":
				# read original image in gray mode
				_lowerCamelCase				:	List[str]				    =       cva.imread(R'../image_data/lena.jpg', 0)
				# canny edge detection
				_lowerCamelCase				:	Tuple				    =       canny(lena)
				cva.imshow('canny', canny_destination)
				cva.waitKey(0)








'''simple docstring'''


from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_lowerCamelCase				:	int				    =       logging.get_logger(__name__)



class 							__UpperCAmelCase  (       A__						):







		'''simple docstring'''







		__lowerCAmelCase 				=    ['''input_ids''', '''attention_mask''']







		def __init__(self						:      Tuple      ,      _lowerCAmelCase						:      str="[PAD]"      ,      _lowerCAmelCase						:      Dict="[BOS]"      ,      _lowerCAmelCase						:      Any="[EOS]"      ,      _lowerCAmelCase						:      List[Any]="[MASK]"      ,      _lowerCAmelCase						:      int="[CLS]"      ,      _lowerCAmelCase						:      Optional[Any]="[SEP]"      ,      _lowerCAmelCase						:      List[str]=2048      ,      **_lowerCAmelCase						:      Dict      ,      ):
			A							  =      AddedToken(_lowerCAmelCase      ,      lstrip=_lowerCAmelCase      ,      rstrip=_lowerCAmelCase      ) if isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ) else pad_token
			A							  =      AddedToken(_lowerCAmelCase      ,      lstrip=_lowerCAmelCase      ,      rstrip=_lowerCAmelCase      ) if isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ) else bos_token
			A							  =      AddedToken(_lowerCAmelCase      ,      lstrip=_lowerCAmelCase      ,      rstrip=_lowerCAmelCase      ) if isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ) else eos_token
			A							  =      AddedToken(_lowerCAmelCase      ,      lstrip=_lowerCAmelCase      ,      rstrip=_lowerCAmelCase      ) if isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ) else mask_token
			A							  =      AddedToken(_lowerCAmelCase      ,      lstrip=_lowerCAmelCase      ,      rstrip=_lowerCAmelCase      ) if isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ) else cls_token
			A							  =      AddedToken(_lowerCAmelCase      ,      lstrip=_lowerCAmelCase      ,      rstrip=_lowerCAmelCase      ) if isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ) else sep_token

			super().__init__(
			    pad_token=_lowerCAmelCase      ,      bos_token=_lowerCAmelCase      ,      eos_token=_lowerCAmelCase      ,      mask_token=_lowerCAmelCase      ,      cls_token=_lowerCAmelCase      ,      sep_token=_lowerCAmelCase      ,      model_max_length=_lowerCAmelCase      ,      **_lowerCAmelCase      ,      )

			A							  =      2**8  # utf is 8 bits

			# define special tokens dict
			A							  =      {
			    self.pad_token: 0,
			    self.bos_token: 1,
			    self.eos_token: 2,
			    self.mask_token: 3,
			    self.cls_token: 4,
			    self.sep_token: 5,
			}
			A							  =      len(self.special_tokens_encoder      )
			A							  =      {v: k for k, v in self.special_tokens_encoder.items()}







		def        A     (self						:      Tuple      ):
			A							  =      self.special_tokens_encoder.copy()
			vocab.update(self.added_tokens_encoder      )
			for i in range(self._utf_vocab_size      ):
				A							  =      chr(_lowerCAmelCase      )
				A							  =      i + len(self.special_tokens_encoder      )
			return vocab







		@property
		def        A     (self						:      Tuple      ):
			return self._utf_vocab_size + self._num_special_tokens







		def        A     (self						:      Union[str, Any]      ,      _lowerCAmelCase						:      List[int]      ,      _lowerCAmelCase						:      Optional[List[int]] = None      ,      _lowerCAmelCase						:      bool = False      ):
			if already_has_special_tokens:
				return super().get_special_tokens_mask(
				    token_ids_a=_lowerCAmelCase      ,      token_ids_a=_lowerCAmelCase      ,      already_has_special_tokens=_lowerCAmelCase      )

			# normal case: some special tokens
			if token_ids_a is None:
				return [1] + [0] * len(_lowerCAmelCase      ) + [1]
			return [1] + ([0] * len(_lowerCAmelCase      )) + [1] + ([0] * len(_lowerCAmelCase      )) + [1]







		def        A     (self						:      List[Any]      ,      _lowerCAmelCase						:      List[int]      ,      _lowerCAmelCase						:      Optional[List[int]] = None      ):
			if token_ids_a is None:
				return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
			else:
				return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]







		def        A     (self						:      str      ,      _lowerCAmelCase						:      str      ):
			A							  =      [chr(_lowerCAmelCase      ) for i in text.encode("""utf-8"""      )]
			return tokens







		def        A     (self						:      int      ,      _lowerCAmelCase						:      List[str]      ):
			if token in self.special_tokens_encoder:
				A							  =      self.special_tokens_encoder[token]
			elif token in self.added_tokens_encoder:
				A							  =      self.added_tokens_encoder[token]
			elif len(_lowerCAmelCase      ) != 1:
				A							  =      self.unk_token_id
			else:
				A							  =      ord(_lowerCAmelCase      ) + self._num_special_tokens
			return token_id







		def        A     (self						:      Optional[int]      ,      _lowerCAmelCase						:      Any      ):
			if index in self.special_tokens_decoder:
				A							  =      self.special_tokens_decoder[index]
			elif index in self.added_tokens_decoder:
				A							  =      self.added_tokens_decoder[index]
			else:
				A							  =      chr(index - self._num_special_tokens      )
			return token







		def        A     (self						:      Dict      ,      _lowerCAmelCase						:      List[str]      ):
			A							  =      b""""""
			for token in tokens:
				if token in self.special_tokens_decoder:
					A							  =      self.special_tokens_decoder[token].encode("""utf-8"""      )
				elif token in self.added_tokens_decoder:
					A							  =      self.special_tokens_decoder[token].encode("""utf-8"""      )
				elif token in self.special_tokens_encoder:
					A							  =      token.encode("""utf-8"""      )
				elif token in self.added_tokens_encoder:
					A							  =      token.encode("""utf-8"""      )
				else:
					A							  =      bytes([ord(_lowerCAmelCase      )]      )
				bstring += tok_string
			A							  =      bstring.decode("""utf-8"""      ,      errors="""replace"""      )
			return string







		def        A     (self						:      Tuple      ,      _lowerCAmelCase						:      str      ,      _lowerCAmelCase						:      Optional[str] = None      ):
			return ()

