


'''simple docstring'''



from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


_lowercase      :      List[str]            =					logging.get_logger(__name__)


_lowercase      :      int            =					TypeVar("""DatasetType""", Dataset, IterableDataset)


def 				lowerCamelCase__				(	A       :      List[DatasetType]				,       A       :      Optional[List[float]] = None				,       A       :      Optional[int] = None				,       A       :      Optional[DatasetInfo] = None				,       A       :      Optional[NamedSplit] = None				,       A       :      Literal["first_exhausted", "all_exhausted"] = "first_exhausted"				,       ):




						'''simple docstring'''






						from .arrow_dataset import Dataset
						from .iterable_dataset import IterableDataset

						if not datasets:
												raise ValueError('''Unable to interleave an empty list of datasets.'''					)
						for i, dataset in enumerate(A					):
												if not isinstance(A				,       (Dataset, IterableDataset)					):
																		if isinstance(A				,       (DatasetDict, IterableDatasetDict)					):
																								if not dataset:
																														raise ValueError(
																														    f"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} """
																														    '''is an empty dataset dictionary.'''					)
																								raise ValueError(
																								    f"""Dataset at position {i} has at least one split: {list(A					)}\n"""
																								    f"""Please pick one to interleave with the other datasets, for example: dataset['{next(iter(A					)					)}']"""					)
																		raise ValueError(
																		    f"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(A					).__name__}."""					)
												if i == 0:
																		UpperCAmelCase    ,    UpperCAmelCase					    =     (
																		    (Dataset, IterableDataset) if isinstance(A				,       A					) else (IterableDataset, Dataset)
																		)
												elif not isinstance(A				,       A					):
																		raise ValueError(
																		    f"""Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."""					)
						if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
												raise ValueError(f"""{stopping_strategy} is not supported. Please enter a valid stopping_strategy."""					)
						if dataset_type is Dataset:
												return _interleave_map_style_datasets(
												    A				,       A				,       A				,       info=A				,       split=A				,       stopping_strategy=A					)
						else:
												return _interleave_iterable_datasets(
												    A				,       A				,       A				,       info=A				,       split=A				,       stopping_strategy=A					)




def 				lowerCamelCase__				(	A       :      List[DatasetType]				,       A       :      Optional[DatasetInfo] = None				,       A       :      Optional[NamedSplit] = None				,       A       :      int = 0				,       ):




						'''simple docstring'''






						if not dsets:
												raise ValueError('''Unable to concatenate an empty list of datasets.'''					)
						for i, dataset in enumerate(A					):
												if not isinstance(A				,       (Dataset, IterableDataset)					):
																		if isinstance(A				,       (DatasetDict, IterableDatasetDict)					):
																								if not dataset:
																														raise ValueError(
																														    f"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} """
																														    '''is an empty dataset dictionary.'''					)
																								raise ValueError(
																								    f"""Dataset at position {i} has at least one split: {list(A					)}\n"""
																								    f"""Please pick one to interleave with the other datasets, for example: dataset['{next(iter(A					)					)}']"""					)
																		raise ValueError(
																		    f"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(A					).__name__}."""					)
												if i == 0:
																		UpperCAmelCase    ,    UpperCAmelCase					    =     (
																		    (Dataset, IterableDataset) if isinstance(A				,       A					) else (IterableDataset, Dataset)
																		)
												elif not isinstance(A				,       A					):
																		raise ValueError(
																		    f"""Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."""					)
						if dataset_type is Dataset:
												return _concatenate_map_style_datasets(A				,       info=A				,       split=A				,       axis=A					)
						else:
												return _concatenate_iterable_datasets(A				,       info=A				,       split=A				,       axis=A					)









'''simple docstring'''



import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey


def 				lowerCamelCase__				(	A       :      int				,       A       :      int				,       A       :      int				,       A       :      int				,       A       :      int				,       A       :      int					):




						'''simple docstring'''






						if (ksize % 2) == 0:
												UpperCAmelCase					    =     ksize + 1
						UpperCAmelCase					    =     np.zeros((ksize, ksize)				,       dtype=np.floataa					)

						# each value
						for y in range(A					):
												for x in range(A					):
																		# distance from center
																		UpperCAmelCase					    =     x - ksize // 2
																		UpperCAmelCase					    =     y - ksize // 2

																		# degree to radiant
																		UpperCAmelCase					    =     theta / 1_80 * np.pi
																		UpperCAmelCase					    =     np.cos(_theta					)
																		UpperCAmelCase					    =     np.sin(_theta					)

																		# get kernel x
																		UpperCAmelCase					    =     cos_theta * px + sin_theta * py

																		# get kernel y
																		UpperCAmelCase					    =     -sin_theta * px + cos_theta * py

																		# fill kernel
																		UpperCAmelCase					    =     np.exp(
																		    -(_x**2 + gamma**2 * _y**2) / (2 * sigma**2)					) * np.cos(2 * np.pi * _x / lambd + psi					)

						return gabor


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	# read original image
	_lowercase      :      Tuple            =					imread("""../image_data/lena.jpg""")
	# turn image in gray scale value
	_lowercase      :      int            =					cvtColor(img, COLOR_BGR2GRAY)

	# Apply multiple Kernel to detect edges
	_lowercase      :      List[str]            =					np.zeros(gray.shape[:2])
	for theta in [0, 30, 60, 90, 120, 150]:
		_lowercase      :      List[Any]            =					gabor_filter_kernel(10, 8, theta, 10, 0, 0)
		out += filteraD(gray, CV_8UC3, kernel_aa)
	_lowercase      :      Optional[int]            =					out / out.max() * 255
	_lowercase      :      Optional[int]            =					out.astype(np.uinta)

	imshow("""Original""", gray)
	imshow("""Gabor filter with 20x20 mask and 6 directions""", out)

	waitKey(0)





