



'''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   lowercase_	(   lowerCAmelCase__	:  int ):

			"""simple docstring"""





			__UpperCAmelCase   :      Any										=     tmp_path / """text.txt"""
			__UpperCAmelCase   :      List[str]										=     textwrap.dedent(
			    """\
        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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


@pytest.fixture
def   lowercase_	(   lowerCAmelCase__	:  str			,							lowerCAmelCase__	:  str ):

			"""simple docstring"""





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


@pytest.mark.parametrize("""keep_linebreaks"""			,							[True, False] )
def   lowercase_	(   lowerCAmelCase__	:  Dict			,							lowerCAmelCase__	:  List[str] ):

			"""simple docstring"""





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


@require_pil
def   lowercase_	(   lowerCAmelCase__	:  Dict ):

			"""simple docstring"""





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






@pytest.mark.parametrize("""sample_by"""			,							["""line""", """paragraph""", """document"""] )
def   lowercase_	(   lowerCAmelCase__	:  List[Any]			,							lowerCAmelCase__	:  List[Any] ):

			"""simple docstring"""





			with open(lowerCAmelCase__			,							encoding="""utf-8""" ) as f:
						__UpperCAmelCase   :      List[Any]										=     f.read()
			if sample_by == "line":
						__UpperCAmelCase   :      Union[str, Any]										=     expected_content.splitlines()
			elif sample_by == "paragraph":
						__UpperCAmelCase   :      Tuple										=     expected_content.split("""\n\n""" )
			elif sample_by == "document":
						__UpperCAmelCase   :      Tuple										=     [expected_content]
			__UpperCAmelCase   :      List[Any]										=     Text(sample_by=lowerCAmelCase__			,							encoding="""utf-8"""			,							chunksize=100 )
			__UpperCAmelCase   :      Any										=     text._generate_tables([[text_file]] )
			__UpperCAmelCase   :      Dict										=     pa.concat_tables([table for _, table in generator] ).to_pydict()["""text"""]
			assert generated_content == expected_content









'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey



class _A  :





		def __init__(     self ,       __UpperCAmelCase ,       __UpperCAmelCase				)       ->     Union[str, Any]:

					'''simple docstring'''
					__UpperCAmelCase   :      Optional[int]										=     0
					# max greyscale value for #FFFFFF
					__UpperCAmelCase   :      List[Any]										=     int(self.get_greyscale(255 ,       255 ,       255				)				)

					if not self.min_threshold < threshold < self.max_threshold:
								__UpperCAmelCase   :      str										=     f'Factor value should be from 0 to {self.max_threshold}'
								raise ValueError(__UpperCAmelCase				)

					__UpperCAmelCase   :      Tuple										=     input_img
					__UpperCAmelCase   :      Optional[Any]										=     threshold
					__UpperCAmelCase				,  __UpperCAmelCase   :      List[Any]										=     self.input_img.shape[1], self.input_img.shape[0]

					# error table size (+4 columns and +1 row) greater than input image because of
					# lack of if statements
					__UpperCAmelCase   :      Optional[Any]										=     [
					    [0 for _ in range(self.height + 4				)] for __ in range(self.width + 1				)
					]
					__UpperCAmelCase   :      Any										=     np.ones((self.width, self.height, 3) ,       np.uinta				) * 255





		@classmethod
		def 							__A       (     cls ,       __UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase				)       ->     float:

					'''simple docstring'''
					return 0.114 * blue + 0.587 * green + 0.2126 * red





		def 							__A       (     self				)       ->     None:

					'''simple docstring'''
					for y in range(self.height				):
								for x in range(self.width				):
											__UpperCAmelCase   :      Optional[Any]										=     int(self.get_greyscale(*self.input_img[y][x]				)				)
											if self.threshold > greyscale + self.error_table[y][x]:
														__UpperCAmelCase   :      List[Any]										=     (0, 0, 0)
														__UpperCAmelCase   :      Union[str, Any]										=     greyscale + self.error_table[x][y]
											else:
														__UpperCAmelCase   :      Optional[Any]										=     (255, 255, 255)
														__UpperCAmelCase   :      Dict										=     greyscale + self.error_table[x][y] - 255
											self.error_table[y][x + 1] += int(8 / 32 * current_error				)
											self.error_table[y][x + 2] += int(4 / 32 * current_error				)
											self.error_table[y + 1][x] += int(8 / 32 * current_error				)
											self.error_table[y + 1][x + 1] += int(4 / 32 * current_error				)
											self.error_table[y + 1][x + 2] += int(2 / 32 * current_error				)
											self.error_table[y + 1][x - 1] += int(4 / 32 * current_error				)
											self.error_table[y + 1][x - 2] += int(2 / 32 * current_error				)


if __name__ == "__main__":
					# create Burke's instances with original images in greyscale
					_UpperCamelCase											=			[
					    Burkes(imread('''image_data/lena.jpg''', 1), threshold)
					    for threshold in (1, 126, 130, 140)
					]

					for burkes in burkes_instances:
										burkes.process()

					for burkes in burkes_instances:
										imshow(
										    F'Original image with dithering threshold: {burkes.threshold}',
										    burkes.output_img,
										)

					waitKey(0)
					destroyAllWindows()




