code: '''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
  
  lowercase__    :       Union[str, Any]						=			1_8_0
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			str:
  							lowerCAmelCase				=	k_size // 2
  							lowerCAmelCase	,   lowerCAmelCase				=	np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
  							lowerCAmelCase				=	(
  							    1
  							    / (2 * np.pi * sigma)
  							    * np.exp(-(np.square(snake_case__							) + np.square(snake_case__							)) / (2 * np.square(snake_case__							))							)
  							)
  							return g
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__     ,						snake_case__							)  ->			Union[str, Any]:
  							lowerCAmelCase				=	np.zeros(snake_case__							)
  
  							for row in range(1     ,						image_shape[0] - 1							):
  														for col in range(1     ,						image_shape[1] - 1							):
  																					lowerCAmelCase				=	gradient_direction[row, col]
  
  																					if (
  																					    0 <= direction < PI / 8
  																					    or 1_5 * PI / 8 <= direction <= 2 * PI
  																					    or 7 * PI / 8 <= direction <= 9 * PI / 8
  																					):
  																												lowerCAmelCase				=	sobel_grad[row, col - 1]
  																												lowerCAmelCase				=	sobel_grad[row, col + 1]
  																												if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
  																																			lowerCAmelCase				=	sobel_grad[row, col]
  
  																					elif (
  																					    PI / 8 <= direction < 3 * PI / 8
  																					    or 9 * PI / 8 <= direction < 1_1 * PI / 8
  																					):
  																												lowerCAmelCase				=	sobel_grad[row + 1, col - 1]
  																												lowerCAmelCase				=	sobel_grad[row - 1, col + 1]
  																												if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
  																																			lowerCAmelCase				=	sobel_grad[row, col]
  
  																					elif (
  																					    3 * PI / 8 <= direction < 5 * PI / 8
  																					    or 1_1 * PI / 8 <= direction < 1_3 * PI / 8
  																					):
  																												lowerCAmelCase				=	sobel_grad[row - 1, col]
  																												lowerCAmelCase				=	sobel_grad[row + 1, col]
  																												if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
  																																			lowerCAmelCase				=	sobel_grad[row, col]
  
  																					elif (
  																					    5 * PI / 8 <= direction < 7 * PI / 8
  																					    or 1_3 * PI / 8 <= direction < 1_5 * PI / 8
  																					):
  																												lowerCAmelCase				=	sobel_grad[row - 1, col - 1]
  																												lowerCAmelCase				=	sobel_grad[row + 1, col + 1]
  																												if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
  																																			lowerCAmelCase				=	sobel_grad[row, col]
  
  							return destination
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__     ,						snake_case__     ,						snake_case__     ,						snake_case__     ,						snake_case__							)  ->			Optional[int]:
  							for row in range(1     ,						image_shape[0] - 1							):
  														for col in range(1     ,						image_shape[1] - 1							):
  																					if destination[row, col] >= threshold_high:
  																												lowerCAmelCase				=	strong
  																					elif destination[row, col] <= threshold_low:
  																												lowerCAmelCase				=	0
  																					else:
  																												lowerCAmelCase				=	weak
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__     ,						snake_case__     ,						snake_case__							)  ->			Union[str, Any]:
  							for row in range(1     ,						image_shape[0]							):
  														for col in range(1     ,						image_shape[1]							):
  																					if destination[row, col] == weak:
  																												if 2_5_5 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],
  																												):
  																																			lowerCAmelCase				=	strong
  																												else:
  																																			lowerCAmelCase				=	0
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__=1_5     ,						snake_case__=3_0     ,						snake_case__=1_2_8     ,						snake_case__=2_5_5							)  ->			str:
  							# gaussian_filter
  							lowerCAmelCase				=	img_convolve(snake_case__     ,						gen_gaussian_kernel(9     ,						sigma=1.4							)							)
  							# get the gradient and degree by sobel_filter
  							lowerCAmelCase	,   lowerCAmelCase				=	sobel_filter(snake_case__							)
  							lowerCAmelCase				=	PI + np.radadeg(snake_case__							)
  
  							lowerCAmelCase				=	suppress_non_maximum(image.shape     ,						snake_case__     ,						snake_case__							)
  
  							detect_high_low_threshold(
  							    image.shape     ,						snake_case__     ,						snake_case__     ,						snake_case__     ,						snake_case__     ,						snake_case__							)
  
  							track_edge(image.shape     ,						snake_case__     ,						snake_case__     ,						snake_case__							)
  
  							return destination
  
  
  if __name__ == "__main__":
  	# read original image in gray mode
  	lowercase__    :       str						=			cva.imread(R'''../image_data/lena.jpg''', 0)
  	# canny edge detection
  	lowercase__    :       int						=			canny(lena)
  	cva.imshow('''canny''', canny_destination)
  	cva.waitKey(0)
  
  
  
  
style_context: import torch
  
  from accelerate import Accelerator, DistributedType
  
  
  
  
  class      lowercase_						:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	def __enter__(							self       )		->Dict:
  								if self.enabled:
  															lowerCAmelCase				=	self.model.no_sync()
  															self.model_sync_obj.__enter__()
  
  								return self
  
  
  	def __exit__(							self	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE       )		->Any:
  								if self.enabled:
  															# Average all models on exit
  															self._sync_and_avg_model_params()
  															self.model_sync_obj.__exit__(__SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE       )
  
  
  	def __init__(							self	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE = True       )		->Tuple:
  								if accelerator.distributed_type not in [
  								    DistributedType.NO,
  								    DistributedType.MULTI_CPU,
  								    DistributedType.MULTI_GPU,
  								]:
  															raise NotImplementedError('''LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)'''       )
  								lowerCAmelCase				=	enabled and accelerator.distributed_type != DistributedType.NO
  								lowerCAmelCase				=	0
  								if self.enabled:
  															lowerCAmelCase				=	accelerator
  															lowerCAmelCase				=	model
  															lowerCAmelCase				=	local_sgd_steps
  
  
  	def     SCREAMING_SNAKE_CASE_       (							self       )		->List[Any]:
  								self.num_steps += 1
  								if not self.enabled:
  															return
  
  								if self.num_steps % self.local_sgd_steps == 0:
  															self._sync_and_avg_model_params()
  
  
  
  
  	def     SCREAMING_SNAKE_CASE_       (							self       )		->Optional[int]:
  								self.accelerator.wait_for_everyone()
  								with self.accelerator.autocast():
  															for param in self.model.parameters():
  																						lowerCAmelCase				=	self.accelerator.reduce(param.data	,    reduction='''mean'''       )
  
  
  
  