




import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil







@pytest.fixture
def 		_A(       UpperCamelCase__							:			Optional[Any]				)    -> str:
							'''simple docstring'''


							__lowercase      =    tmp_path / '''file.csv'''
							__lowercase      =    textwrap.dedent(
							    '''\\n        header1,header2\n        1,2\n        10,20\n        '''				)
							with open(UpperCamelCase__				,       '''w'''				) as f:
														f.write(UpperCamelCase__				)
							return str(UpperCamelCase__				)







@pytest.fixture
def 		_A(       UpperCamelCase__							:			Tuple				)    -> Tuple:
							'''simple docstring'''


							__lowercase      =    tmp_path / '''malformed_file.csv'''
							__lowercase      =    textwrap.dedent(
							    '''\\n        header1,header2\n        1,2\n        10,20,\n        '''				)
							with open(UpperCamelCase__				,       '''w'''				) as f:
														f.write(UpperCamelCase__				)
							return str(UpperCamelCase__				)







@pytest.fixture
def 		_A(       UpperCamelCase__							:			Optional[int]				,       UpperCamelCase__							:			List[str]				)    -> List[str]:
							'''simple docstring'''


							__lowercase      =    tmp_path / '''csv_with_image.csv'''
							__lowercase      =    textwrap.dedent(
							    F'\\n        image\n        {image_file}\n        '				)
							with open(UpperCamelCase__				,       '''w'''				) as f:
														f.write(UpperCamelCase__				)
							return str(UpperCamelCase__				)







@pytest.fixture
def 		_A(       UpperCamelCase__							:			int				)    -> List[str]:
							'''simple docstring'''


							__lowercase      =    tmp_path / '''csv_with_label.csv'''
							__lowercase      =    textwrap.dedent(
							    '''\\n        label\n        good\n        bad\n        good\n        '''				)
							with open(UpperCamelCase__				,       '''w'''				) as f:
														f.write(UpperCamelCase__				)
							return str(UpperCamelCase__				)







@pytest.fixture
def 		_A(       UpperCamelCase__							:			Dict				)    -> str:
							'''simple docstring'''


							__lowercase      =    tmp_path / '''csv_with_int_list.csv'''
							__lowercase      =    textwrap.dedent(
							    '''\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        '''				)
							with open(UpperCamelCase__				,       '''w'''				) as f:
														f.write(UpperCamelCase__				)
							return str(UpperCamelCase__				)







def 		_A(       UpperCamelCase__							:			Dict				,       UpperCamelCase__							:			str				,       UpperCamelCase__							:			Any				)    -> Any:
							'''simple docstring'''


							__lowercase      =    Csv()
							__lowercase      =    csv._generate_tables([[csv_file, malformed_csv_file]]				)
							with pytest.raises(UpperCamelCase__				,       match='''Error tokenizing data'''				):
														for _ in generator:
																					pass
							assert any(
							    record.levelname == '''ERROR'''
							    and '''Failed to read file''' in record.message
							    and os.path.basename(UpperCamelCase__				) in record.message
							    for record in caplog.records				)







@require_pil
def 		_A(       UpperCamelCase__							:			Optional[int]				)    -> Optional[Any]:
							'''simple docstring'''


							with open(UpperCamelCase__				,       encoding='''utf-8'''				) as f:
														__lowercase      =    f.read().splitlines()[1]
							__lowercase      =    Csv(encoding='''utf-8'''				,       features=Features({'''image''': Image()}				)				)
							__lowercase      =    csv._generate_tables([[csv_file_with_image]]				)
							__lowercase      =    pa.concat_tables([table for _, table in generator]				)
							assert pa_table.schema.field('''image'''				).type == Image()()
							__lowercase      =    pa_table.to_pydict()['''image''']
							assert generated_content == [{"path": image_file, "bytes": None}]







def 		_A(       UpperCamelCase__							:			Tuple				)    -> str:
							'''simple docstring'''


							with open(UpperCamelCase__				,       encoding='''utf-8'''				) as f:
														__lowercase      =    f.read().splitlines()[1:]
							__lowercase      =    Csv(encoding='''utf-8'''				,       features=Features({'''label''': ClassLabel(names=['''good''', '''bad''']				)}				)				)
							__lowercase      =    csv._generate_tables([[csv_file_with_label]]				)
							__lowercase      =    pa.concat_tables([table for _, table in generator]				)
							assert pa_table.schema.field('''label'''				).type == ClassLabel(names=['''good''', '''bad''']				)()
							__lowercase      =    pa_table.to_pydict()['''label''']
							assert generated_content == [ClassLabel(names=['''good''', '''bad''']				).straint(UpperCamelCase__				) for label in labels]







def 		_A(       UpperCamelCase__							:			Dict				)    -> Tuple:
							'''simple docstring'''


							__lowercase      =    Csv(encoding='''utf-8'''				,       sep=''','''				,       converters={'''int_list''': lambda UpperCamelCase__				: [int(UpperCamelCase__				) for i in x.split()]}				)
							__lowercase      =    csv._generate_tables([[csv_file_with_int_list]]				)
							__lowercase      =    pa.concat_tables([table for _, table in generator]				)
							assert pa.types.is_list(pa_table.schema.field('''int_list'''				).type				)
							__lowercase      =    pa_table.to_pydict()['''int_list''']
							assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]







import cva
import numpy as np







class a :
						"""simple docstring"""

						def __init__( self :     Dict				,							lowerCamelCase__ :     float				,							lowerCamelCase__ :     int				)    ->						Dict:
													"""simple docstring"""


													if k in (0.0_4, 0.0_6):
																				__lowercase      =    k
																				__lowercase      =    window_size
													else:
																				raise ValueError('''invalid k value'''				)






						def __str__( self :     int				)    ->						str:
													"""simple docstring"""


													return str(self.k				)






						def     UpperCAmelCase_      ( self :     Dict				,							lowerCamelCase__ :     str				)    ->						tuple[cva.Mat, list[list[int]]]:
													"""simple docstring"""


													__lowercase      =    cva.imread(lowerCamelCase__				,							0				)
													__lowercase     ,     __lowercase      =    img.shape
													__lowercase      =    []
													__lowercase      =    img.copy()
													__lowercase      =    cva.cvtColor(lowerCamelCase__				,							cva.COLOR_GRAY2RGB				)
													__lowercase     ,     __lowercase      =    np.gradient(lowerCamelCase__				)
													__lowercase      =    dx**2
													__lowercase      =    dy**2
													__lowercase      =    dx * dy
													__lowercase      =    0.0_4
													__lowercase      =    self.window_size // 2
													for y in range(lowerCamelCase__				,							h - offset				):
																				for x in range(lowerCamelCase__				,							w - offset				):
																											__lowercase      =    ixx[
																											    y - offset : y + offset + 1, x - offset : x + offset + 1
																											].sum()
																											__lowercase      =    iyy[
																											    y - offset : y + offset + 1, x - offset : x + offset + 1
																											].sum()
																											__lowercase      =    ixy[
																											    y - offset : y + offset + 1, x - offset : x + offset + 1
																											].sum()

																											__lowercase      =    (wxx * wyy) - (wxy**2)
																											__lowercase      =    wxx + wyy
																											__lowercase      =    det - k * (trace**2)
																											# Can change the value
																											if r > 0.5:
																																		corner_list.append([x, y, r]				)
																																		color_img.itemset((y, x, 0)				,							0				)
																																		color_img.itemset((y, x, 1)				,							0				)
																																		color_img.itemset((y, x, 2)				,							255				)
													return color_img, corner_list


if __name__ == "__main__":
			UpperCAmelCase__				     = HarrisCorner(0.04, 3)
			UpperCAmelCase__     ,							UpperCAmelCase__				     = edge_detect.detect("path_to_image")
			cva.imwrite("detect.png", color_img)






