"""simple docstring"""







import itertools
from dataclasses import dataclass
from io import StringIO
from typing import Optional

import pyarrow as pa

import datasets
from datasets.features.features import require_storage_cast
from datasets.table import table_cast


_a	:	str=					datasets.utils.logging.get_logger(__name__)

@dataclass
class 						UpperCamelCase     (       datasets.BuilderConfig		):
				UpperCAmelCase							: Optional[datasets.Features]       =						None
				UpperCAmelCase							: str       =						"utf-8"
				UpperCAmelCase							: Optional[str]       =						None
				UpperCAmelCase							: int       =						10 << 20  # 10MB
				UpperCAmelCase							: bool       =						False
				UpperCAmelCase							: str       =						"line"







class 						UpperCamelCase     (       datasets.ArrowBasedBuilder		):
				UpperCAmelCase							: List[Any]       =						TextConfig



				def    _lowercase	(self							: Any)       ->      Optional[int]:
					return datasets.DatasetInfo(features=self.config.features)



				def    _lowercase	(self							: Dict      ,    _A							: Optional[Any])       ->      Dict:
					if not self.config.data_files:
						raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
					__snake_case     :				Any 						=					dl_manager.download_and_extract(self.config.data_files)
					if isinstance(_A      ,    (str, list, tuple)):
						__snake_case     :				Optional[Any] 						=					data_files
						if isinstance(_A      ,    _A):
							__snake_case     :				List[str] 						=					[files]
						__snake_case     :				Any 						=					[dl_manager.iter_files(_A) for file in files]
						return [datasets.SplitGenerator(name=datasets.Split.TRAIN      ,    gen_kwargs={'files': files})]
					__snake_case     :				int 						=					[]
					for split_name, files in data_files.items():
						if isinstance(_A      ,    _A):
							__snake_case     :				Dict 						=					[files]
						__snake_case     :				int 						=					[dl_manager.iter_files(_A) for file in files]
						splits.append(datasets.SplitGenerator(name=_A      ,    gen_kwargs={'files': files}))
					return splits



				def    _lowercase	(self							: Dict      ,    _A							: pa.Table)       ->      pa.Table:
					if self.config.features is not None:
						__snake_case     :				Tuple 						=					self.config.features.arrow_schema
						if all(not require_storage_cast(_A) for feature in self.config.features.values()):
							# cheaper cast
							__snake_case     :				List[Any] 						=					pa_table.cast(_A)
						else:
							# more expensive cast; allows str <-> int/float or str to Audio for example
							__snake_case     :				Tuple 						=					table_cast(_A      ,    _A)
						return pa_table
					else:
						return pa_table.cast(pa.schema({'text': pa.string()}))






				def    _lowercase	(self							: List[str]      ,    _A							: Union[str, Any])       ->      List[Any]:
					__snake_case     :				Tuple 						=					list(self.config.features) if self.config.features is not None else ['text']
					for file_idx, file in enumerate(itertools.chain.from_iterable(_A)):
						# open in text mode, by default translates universal newlines ("\n", "\r\n" and "\r") into "\n"
						with open(_A      ,    encoding=self.config.encoding      ,    errors=self.config.errors) as f:
							if self.config.sample_by == "line":
								__snake_case     :				Tuple 						=					0
								while True:
									__snake_case     :				int 						=					f.read(self.config.chunksize)
									if not batch:
										break
									batch += f.readline()  # finish current line
									# StringIO.readlines, by default splits only on "\n" (and keeps line breaks)
									__snake_case     :				Union[str, Any] 						=					StringIO(_A).readlines()
									if not self.config.keep_linebreaks:
										__snake_case     :				Tuple 						=					[line.rstrip('\n') for line in batch]
									__snake_case     :				str 						=					pa.Table.from_arrays([pa.array(_A)]      ,    names=_A)
									# Uncomment for debugging (will print the Arrow table size and elements)
									# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
									# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
									yield (file_idx, batch_idx), self._cast_table(_A)
									batch_idx += 1
							elif self.config.sample_by == "paragraph":
								__snake_case     :				List[str] 						=					0
								__snake_case     :				Union[str, Any] 						=					''
								while True:
									__snake_case     :				Dict 						=					f.read(self.config.chunksize)
									if not new_batch:
										break
									batch += new_batch
									batch += f.readline()  # finish current line
									__snake_case     :				Union[str, Any] 						=					batch.split('\n\n')
									__snake_case     :				Dict 						=					pa.Table.from_arrays(
									    [pa.array([example for example in batch[:-1] if example])]      ,    names=_A)
									# Uncomment for debugging (will print the Arrow table size and elements)
									# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
									# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
									yield (file_idx, batch_idx), self._cast_table(_A)
									batch_idx += 1
									__snake_case     :				List[str] 						=					batch[-1]
								if batch:
									__snake_case     :				int 						=					pa.Table.from_arrays([pa.array([batch])]      ,    names=_A)
									yield (file_idx, batch_idx), self._cast_table(_A)
							elif self.config.sample_by == "document":
								__snake_case     :				Tuple 						=					f.read()
								__snake_case     :				Union[str, Any] 						=					pa.Table.from_arrays([pa.array([text])]      ,    names=_A)
								yield file_idx, self._cast_table(_A)






"""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

_a	:	int=					180
def     __UpperCAmelCase							(       UpperCAmelCase_       :							str     ,				UpperCAmelCase_       :							Tuple    )				->     Union[str, Any]:

	'''simple docstring'''





	__snake_case     :				Optional[Any] 						=					k_size // 2
	__snake_case						,							__snake_case     :				Union[str, Any] 						=					np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
	__snake_case     :				List[Any] 						=					(
	    1
	    / (2 * np.pi * sigma)
	    * np.exp(-(np.square(UpperCAmelCase_    ) + np.square(UpperCAmelCase_    )) / (2 * np.square(UpperCAmelCase_    ))    )
	)
	return g
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Tuple     ,				UpperCAmelCase_       :							int     ,				UpperCAmelCase_       :							Optional[int]    )				->     List[str]:

	'''simple docstring'''





	__snake_case     :				List[Any] 						=					np.zeros(UpperCAmelCase_    )

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

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

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

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

			elif (
			    5 * PI / 8 <= direction < 7 * PI / 8
			    or 13 * PI / 8 <= direction < 15 * PI / 8
			):
				__snake_case     :				Optional[int] 						=					sobel_grad[row - 1, col - 1]
				__snake_case     :				Union[str, Any] 						=					sobel_grad[row + 1, col + 1]
				if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
					__snake_case     :				List[str] 						=					sobel_grad[row, col]

	return destination
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Tuple     ,				UpperCAmelCase_       :							List[str]     ,				UpperCAmelCase_       :							Optional[Any]     ,				UpperCAmelCase_       :							Optional[Any]     ,				UpperCAmelCase_       :							List[str]     ,				UpperCAmelCase_       :							List[Any]    )				->     Any:

	'''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:
				__snake_case     :				str 						=					strong
			elif destination[row, col] <= threshold_low:
				__snake_case     :				int 						=					0
			else:
				__snake_case     :				Tuple 						=					weak
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Union[str, Any]     ,				UpperCAmelCase_       :							Tuple     ,				UpperCAmelCase_       :							List[Any]     ,				UpperCAmelCase_       :							int    )				->     List[Any]:

	'''simple docstring'''





	for row in range(1     ,				image_shape[0]    ):
		for col in range(1     ,				image_shape[1]    ):
			if destination[row, col] == weak:
				if 2_55 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],
				):
					__snake_case     :				Tuple 						=					strong
				else:
					__snake_case     :				Tuple 						=					0
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Union[str, Any]     ,				UpperCAmelCase_       :							Any=15     ,				UpperCAmelCase_       :							int=30     ,				UpperCAmelCase_       :							Optional[Any]=1_28     ,				UpperCAmelCase_       :							Dict=2_55    )				->     Optional[Any]:

	'''simple docstring'''





	__snake_case     :				Tuple 						=					img_convolve(UpperCAmelCase_     ,				gen_gaussian_kernel(9     ,				sigma=1.4    )    )
	# get the gradient and degree by sobel_filter
	__snake_case						,							__snake_case     :				str 						=					sobel_filter(UpperCAmelCase_    )
	__snake_case     :				str 						=					PI + np.radadeg(UpperCAmelCase_    )

	__snake_case     :				int 						=					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
	_a	:	List[Any]=					cva.imread(R"../image_data/lena.jpg", 0)
	# canny edge detection
	_a	:	Optional[int]=					canny(lena)
	cva.imshow("canny", canny_destination)
	cva.waitKey(0)





