




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_80


def 							__SCREAMING_SNAKE_CASE						(    snake_case_			,					snake_case_		):

						'''simple docstring'''


						_UpperCAmelCase									=  k_size // 2
						_UpperCAmelCase							,				_UpperCAmelCase									=  np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
						_UpperCAmelCase									=  (
						    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_		):

						'''simple docstring'''


						_UpperCAmelCase									=  np.zeros(snake_case_		)

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

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

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

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

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

						return destination


def 							__SCREAMING_SNAKE_CASE						(    snake_case_			,					snake_case_			,					snake_case_			,					snake_case_			,					snake_case_			,					snake_case_		):

						'''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:
																								_UpperCAmelCase									=  strong
																		elif destination[row, col] <= threshold_low:
																								_UpperCAmelCase									=  0
																		else:
																								_UpperCAmelCase									=  weak


def 							__SCREAMING_SNAKE_CASE						(    snake_case_			,					snake_case_			,					snake_case_			,					snake_case_		):

						'''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],
																								):
																														_UpperCAmelCase									=  strong
																								else:
																														_UpperCAmelCase									=  0


def 							__SCREAMING_SNAKE_CASE						(    snake_case_			,					snake_case_=15			,					snake_case_=30			,					snake_case_=128			,					snake_case_=255		):

						'''simple docstring'''


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

						_UpperCAmelCase									=  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_			:       int						       =				cva.imread(r'../image_data/lena.jpg', 0)
				# canny edge detection
				lowercase_			:       List[str]						       =				canny(lena)
				cva.imshow('canny', canny_destination)
				cva.waitKey(0)










from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowercase_			:       List[str]						       =				{
    'configuration_rwkv': ['RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RwkvConfig', 'RwkvOnnxConfig'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_			:       Any						       =				[
				    'RWKV_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'RwkvForCausalLM',
				    'RwkvModel',
				    'RwkvPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_rwkv import (
								    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
								    RwkvForCausalLM,
								    RwkvModel,
								    RwkvPreTrainedModel,
								)
else:
				import sys

				lowercase_			:       Union[str, Any]						       =				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




