





'''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__							:  Dict    ='''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__							:  Union[str, Any]    =concatenate_datasets
A__							:  List[str]    =DownloadConfig
A__							:  Tuple    =DownloadManager
A__							:  List[str]    =DownloadMode
A__							:  List[Any]    =DownloadConfig
A__							:  int    =DownloadMode
A__							:  str    =DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager













'''simple docstring'''






import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

A__							:  List[str]    =imread(r'''digital_image_processing/image_data/lena_small.jpg''')
A__							:  Union[str, Any]    =cvtColor(img, COLOR_BGR2GRAY)
def   UpperCamelCase__ (						):





      """simple docstring"""


      _lowerCAmelCase					=				cn.convert_to_negative(lowerCAmelCase    )
      # assert negative_img array for at least one True
      assert negative_img.any()
def   UpperCamelCase__ (						):





      """simple docstring"""


      with Image.open("""digital_image_processing/image_data/lena_small.jpg"""    ) as img:
            # Work around assertion for response
            assert str(cc.change_contrast(lowerCAmelCase				,      1_10    )    ).startswith(
                """<PIL.Image.Image image mode=RGB size=100x100 at"""    )
def   UpperCamelCase__ (						):





      """simple docstring"""


      _lowerCAmelCase					=				canny.gen_gaussian_kernel(9				,      sigma=1.4    )
      # Assert ambiguous array
      assert resp.all()
def   UpperCamelCase__ (						):





      """simple docstring"""


      _lowerCAmelCase					=				imread("""digital_image_processing/image_data/lena_small.jpg"""				,      0    )
      # assert ambiguous array for all == True
      assert canny_img.all()
      _lowerCAmelCase					=				canny.canny(lowerCAmelCase    )
      # assert canny array for at least one True
      assert canny_array.any()
def   UpperCamelCase__ (						):





      """simple docstring"""


      assert gg.gaussian_filter(lowerCAmelCase				,      5				,      sigma=0.9    ).all()
def   UpperCamelCase__ (						):





      """simple docstring"""


      _lowerCAmelCase					=				array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]    )
      _lowerCAmelCase					=				conv.img_convolve(lowerCAmelCase				,      lowerCAmelCase    ).astype(lowerCAmelCase    )
      assert res.any()
def   UpperCamelCase__ (						):





      """simple docstring"""


      assert med.median_filter(lowerCAmelCase				,      3    ).any()
def   UpperCamelCase__ (						):





      """simple docstring"""


      _lowerCAmelCase	,				_lowerCAmelCase					=				sob.sobel_filter(lowerCAmelCase    )
      assert grad.any() and theta.any()
def   UpperCamelCase__ (						):





      """simple docstring"""


      _lowerCAmelCase					=				sp.make_sepia(lowerCAmelCase				,      20    )
      assert sepia.all()
def   UpperCamelCase__ (						lowerCAmelCase = "digital_image_processing/image_data/lena_small.jpg"    ):





      """simple docstring"""


      _lowerCAmelCase					=				bs.Burkes(imread(lowerCAmelCase				,      1    )				,      1_20    )
      burkes.process()
      assert burkes.output_img.any()
def   UpperCamelCase__ (						lowerCAmelCase = "digital_image_processing/image_data/lena_small.jpg"				,      ):





      """simple docstring"""


      _lowerCAmelCase					=				rs.NearestNeighbour(imread(lowerCAmelCase				,      1    )				,      4_00				,      2_00    )
      nn.process()
      assert nn.output.any()





def   UpperCamelCase__ (						):





      """simple docstring"""


      _lowerCAmelCase					=				"""digital_image_processing/image_data/lena.jpg"""

      # Reading the image and converting it to grayscale.
      _lowerCAmelCase					=				imread(lowerCAmelCase				,      0    )

      # Test for get_neighbors_pixel function() return not None
      _lowerCAmelCase					=				0
      _lowerCAmelCase					=				0
      _lowerCAmelCase					=				image[x_coordinate][y_coordinate]

      _lowerCAmelCase					=				lbp.get_neighbors_pixel(
          lowerCAmelCase				,      lowerCAmelCase				,      lowerCAmelCase				,      lowerCAmelCase    )

      assert neighbors_pixels is not None

      # Test for local_binary_pattern function()
      # Create a numpy array as the same height and width of read image
      _lowerCAmelCase					=				np.zeros((image.shape[0], image.shape[1])    )

      # Iterating through the image and calculating the local binary pattern value
      # for each pixel.
      for i in range(0				,      image.shape[0]    ):
            for j in range(0				,      image.shape[1]    ):
                  _lowerCAmelCase					=				lbp.local_binary_value(lowerCAmelCase				,      lowerCAmelCase				,      lowerCAmelCase    )

      assert lbp_image.any()






