
'''simple docstring'''

import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Image
from datasets.packaged_modules.text.text import Text

from ..utils import require_pil







@pytest.fixture
def      A   (					UpperCamelCase_    :   Any					)    ->				Dict:







			'''simple docstring'''



			lowerCAmelCase__									=							tmp_path / "text.txt"
			lowerCAmelCase__									=							textwrap.dedent(
			    "\\n        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.\n        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.\n        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.\n        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.\n\n        Second paragraph:\n        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.\n        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.\n        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.\n        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.\n        "					)
			with open(UpperCamelCase_  ,		"w"  ,		encoding="utf-8"					) as f:
						f.write(UpperCamelCase_					)
			return str(UpperCamelCase_					)







@pytest.fixture
def      A   (					UpperCamelCase_    :   List[Any]  ,		UpperCamelCase_    :   str					)    ->				str:







			'''simple docstring'''



			lowerCAmelCase__									=							tmp_path / "text_with_image.txt"
			with open(UpperCamelCase_  ,		"w"  ,		encoding="utf-8"					) as f:
						f.write(UpperCamelCase_					)
			return str(UpperCamelCase_					)







@pytest.mark.parametrize("keep_linebreaks"  ,		[True, False]					)
def      A   (					UpperCamelCase_    :   Any  ,		UpperCamelCase_    :   Any					)    ->				Optional[Any]:







			'''simple docstring'''



			with open(UpperCamelCase_  ,		encoding="utf-8"					) as f:
						lowerCAmelCase__									=							f.read().splitlines(keepends=UpperCamelCase_					)
			lowerCAmelCase__									=							Text(keep_linebreaks=UpperCamelCase_  ,		encoding="utf-8"					)
			lowerCAmelCase__									=							text._generate_tables([[text_file]]					)
			lowerCAmelCase__									=							pa.concat_tables([table for _, table in generator]					).to_pydict()["text"]
			assert generated_content == expected_content







@require_pil
def      A   (					UpperCamelCase_    :   Any					)    ->				Dict:







			'''simple docstring'''



			with open(UpperCamelCase_  ,		encoding="utf-8"					) as f:
						lowerCAmelCase__									=							f.read().splitlines()[0]
			lowerCAmelCase__									=							Text(encoding="utf-8"  ,		features=Features({"image": Image()}					)					)
			lowerCAmelCase__									=							text._generate_tables([[text_file_with_image]]					)
			lowerCAmelCase__									=							pa.concat_tables([table for _, table in generator]					)
			assert pa_table.schema.field("image"					).type == Image()()
			lowerCAmelCase__									=							pa_table.to_pydict()["image"]
			assert generated_content == [{"path": image_file, "bytes": None}]







@pytest.mark.parametrize("sample_by"  ,		["line", "paragraph", "document"]					)
def      A   (					UpperCamelCase_    :   Any  ,		UpperCamelCase_    :   Dict					)    ->				int:







			'''simple docstring'''



			with open(UpperCamelCase_  ,		encoding="utf-8"					) as f:
						lowerCAmelCase__									=							f.read()
			if sample_by == "line":
						lowerCAmelCase__									=							expected_content.splitlines()
			elif sample_by == "paragraph":
						lowerCAmelCase__									=							expected_content.split("\n\n"					)
			elif sample_by == "document":
						lowerCAmelCase__									=							[expected_content]
			lowerCAmelCase__									=							Text(sample_by=UpperCamelCase_  ,		encoding="utf-8"  ,		chunksize=1_00					)
			lowerCAmelCase__									=							text._generate_tables([[text_file]]					)
			lowerCAmelCase__									=							pa.concat_tables([table for _, table in generator]					).to_pydict()["text"]
			assert generated_content == expected_content












"""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_     :      Any								=1_8_0





def SCREAMING_SNAKE_CASE_   (       snake_case   :					Dict						,  snake_case   :					Any		)->		Tuple:
       _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   :					Optional[int]						,  snake_case   :					int						,  snake_case   :					Dict		)->		Optional[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 15 * 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 < 11 * 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 11 * PI / 8 <= direction < 13 * 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 13 * PI / 8 <= direction < 15 * 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   :					List[Any]						,  snake_case   :					List[Any]						,  snake_case   :					int						,  snake_case   :					int						,  snake_case   :					List[str]						,  snake_case   :					str		)->		Tuple:
       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   :					Union[str, Any]						,  snake_case   :					Optional[int]						,  snake_case   :					Dict						,  snake_case   :					Tuple		)->		Optional[int]:
       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],
                            ):
                                   _lowerCamelCase    	=					strong
                            else:
                                   _lowerCamelCase    	=					0





def SCREAMING_SNAKE_CASE_   (       snake_case   :					Dict						,  snake_case   :					Union[str, Any]=15						,  snake_case   :					Optional[int]=30						,  snake_case   :					int=128						,  snake_case   :					str=255		)->		List[Any]:
       # 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
      A_     :      Optional[Any]								=cva.imread(R"""../image_data/lena.jpg""", 0)
      # canny edge detection
      A_     :      Optional[Any]								=canny(lena)
      cva.imshow("""canny""", canny_destination)
      cva.waitKey(0)






