
"""simple docstring"""


# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

A_    							=					"""2.13.1"""

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse("""3.7"""):
						raise ImportWarning(
						    """To use `datasets`, Python>=3.7 is required, and the current version of Python doesn't match this condition."""
						)

if version.parse(pyarrow.__version__).major < 8:
						raise ImportWarning(
						    """To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"""
						    """If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."""
						)

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

A_    							=					concatenate_datasets
A_    							=					DownloadConfig
A_    							=					DownloadManager
A_    							=					DownloadMode
A_    							=					DownloadConfig
A_    							=					DownloadMode
A_    							=					DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager









'''simple docstring'''







import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey







class 					_a :





     '''simple docstring'''



     def __init__(				self							,__a							,__a							,__a							)      ->				Tuple:
          if dst_width < 0 or dst_height < 0:
               raise ValueError("""Destination width/height should be > 0"""							)

          snake_case			:      str        =			img
          snake_case			:      str        =			img.shape[1]
          snake_case			:      Union[str, Any]        =			img.shape[0]
          snake_case			:      Optional[int]        =			dst_width
          snake_case			:      List[str]        =			dst_height

          snake_case			:      List[str]        =			self.src_w / self.dst_w
          snake_case			:      int        =			self.src_h / self.dst_h

          snake_case			:      List[Any]        =			(
              np.ones((self.dst_h, self.dst_w, 3)							,np.uinta							) * 255
          )







     def 			snake_case_      (				self							)      ->				int:
          for i in range(self.dst_h							):
               for j in range(self.dst_w							):
                    snake_case			:      Optional[Any]        =			self.img[self.get_y(__a							)][self.get_x(__a							)]







     def 			snake_case_      (				self							,__a							)      ->				int:
          return int(self.ratio_x * x							)







     def 			snake_case_      (				self							,__a							)      ->				int:
          return int(self.ratio_y * y							)


if __name__ == "__main__":
      lowercase,	lowercase      :   Optional[int]      =       800, 600
      lowercase      :   Union[str, Any]      =       imread("""image_data/lena.jpg""", 1)
      lowercase      :   int      =       NearestNeighbour(im, dst_w, dst_h)
      n.process()

      imshow(
          F"""Image resized from: {im.shape[1]}x{im.shape[0]} to {dst_w}x{dst_h}""", n.output
      )
      waitKey(0)
      destroyAllWindows()



