





from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
    center_crop,
    convert_to_rgb,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    OPENAI_CLIP_MEAN,
    OPENAI_CLIP_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


A      = logging.get_logger(__name__)


if is_vision_available():
    import PIL


class     lowercase__  (					__SCREAMING_SNAKE_CASE		):
  A__=  ['pixel_values']






  def __init__(					self      :					List[Any]		,						_lowercase      :					Dict = True		,						_lowercase      :					List[str] = None		,						_lowercase      :					Optional[Any] = PILImageResampling.BICUBIC		,						_lowercase      :					Dict = True		,						_lowercase      :					Any = None		,						_lowercase      :					List[str] = True		,						_lowercase      :					Tuple = 1 / 2_55		,						_lowercase      :					Optional[Any] = True		,						_lowercase      :					Tuple = None		,						_lowercase      :					Union[str, Any] = None		,						_lowercase      :					Dict = True		,						**_lowercase      :					Optional[int]		,						):




         """simple docstring"""







         super().__init__(**__lowerCAmelCase )
         UpperCAmelCase__										=     size if size is not None else {"shortest_edge": 2_24}
         UpperCAmelCase__										=     get_size_dict(__lowerCAmelCase		,						default_to_square=__lowerCAmelCase )
         UpperCAmelCase__										=     crop_size if crop_size is not None else {"height": 2_24, "width": 2_24}
         UpperCAmelCase__										=     get_size_dict(__lowerCAmelCase		,						default_to_square=__lowerCAmelCase		,						param_name="crop_size" )

         UpperCAmelCase__										=     do_resize
         UpperCAmelCase__										=     size
         UpperCAmelCase__										=     resample
         UpperCAmelCase__										=     do_center_crop
         UpperCAmelCase__										=     crop_size
         UpperCAmelCase__										=     do_rescale
         UpperCAmelCase__										=     rescale_factor
         UpperCAmelCase__										=     do_normalize
         UpperCAmelCase__										=     image_mean if image_mean is not None else OPENAI_CLIP_MEAN
         UpperCAmelCase__										=     image_std if image_std is not None else OPENAI_CLIP_STD
         UpperCAmelCase__										=     do_convert_rgb






  def 			_UpperCAmelCase  (					self      :					Any		,						_lowercase      :					int		,						_lowercase      :					Any		,						_lowercase      :					Optional[int] = PILImageResampling.BICUBIC		,						_lowercase      :					List[str] = None		,						**_lowercase      :					Any		,						):




         """simple docstring"""







         UpperCAmelCase__										=     get_size_dict(__lowerCAmelCase		,						default_to_square=__lowerCAmelCase )
         if "shortest_edge" not in size:
                raise ValueError(F"""The `size` parameter must contain the key `shortest_edge`. Got {size.keys()}""" )
         UpperCAmelCase__										=     get_resize_output_image_size(__lowerCAmelCase		,						size=size["shortest_edge"]		,						default_to_square=__lowerCAmelCase )
         return resize(__lowerCAmelCase		,						size=__lowerCAmelCase		,						resample=__lowerCAmelCase		,						data_format=__lowerCAmelCase		,						**__lowerCAmelCase )






  def 			_UpperCAmelCase  (					self      :					Dict		,						_lowercase      :					str		,						_lowercase      :					Tuple		,						_lowercase      :					Optional[Any] = None		,						**_lowercase      :					Union[str, Any]		,						):




         """simple docstring"""







         UpperCAmelCase__										=     get_size_dict(__lowerCAmelCase )
         if "height" not in size or "width" not in size:
                raise ValueError(F"""The `size` parameter must contain the keys (height, width). Got {size.keys()}""" )
         return center_crop(__lowerCAmelCase		,						size=(size["height"], size["width"])		,						data_format=__lowerCAmelCase		,						**__lowerCAmelCase )






  def 			_UpperCAmelCase  (					self      :					Tuple		,						_lowercase      :					int		,						_lowercase      :					Dict		,						_lowercase      :					List[str] = None		,						**_lowercase      :					str		,						):




         """simple docstring"""







         return rescale(__lowerCAmelCase		,						scale=__lowerCAmelCase		,						data_format=__lowerCAmelCase		,						**__lowerCAmelCase )






  def 			_UpperCAmelCase  (					self      :					Optional[int]		,						_lowercase      :					List[str]		,						_lowercase      :					int		,						_lowercase      :					Tuple		,						_lowercase      :					Union[str, Any] = None		,						**_lowercase      :					Tuple		,						):




         """simple docstring"""







         return normalize(__lowerCAmelCase		,						mean=__lowerCAmelCase		,						std=__lowerCAmelCase		,						data_format=__lowerCAmelCase		,						**__lowerCAmelCase )






  def 			_UpperCAmelCase  (					self      :					List[str]		,						_lowercase      :					List[str]		,						_lowercase      :					int = None		,						_lowercase      :					Optional[int] = None		,						_lowercase      :					Tuple = None		,						_lowercase      :					Tuple = None		,						_lowercase      :					Any = None		,						_lowercase      :					Dict = None		,						_lowercase      :					Union[str, Any] = None		,						_lowercase      :					List[Any] = None		,						_lowercase      :					List[Any] = None		,						_lowercase      :					List[str] = None		,						_lowercase      :					Any = None		,						_lowercase      :					Dict = None		,						_lowercase      :					Dict = ChannelDimension.FIRST		,						**_lowercase      :					Optional[Any]		,						):




         """simple docstring"""







         UpperCAmelCase__										=     do_resize if do_resize is not None else self.do_resize
         UpperCAmelCase__										=     size if size is not None else self.size
         UpperCAmelCase__										=     get_size_dict(__lowerCAmelCase		,						param_name="size"		,						default_to_square=__lowerCAmelCase )
         UpperCAmelCase__										=     resample if resample is not None else self.resample
         UpperCAmelCase__										=     do_center_crop if do_center_crop is not None else self.do_center_crop
         UpperCAmelCase__										=     crop_size if crop_size is not None else self.crop_size
         UpperCAmelCase__										=     get_size_dict(__lowerCAmelCase		,						param_name="crop_size"		,						default_to_square=__lowerCAmelCase )
         UpperCAmelCase__										=     do_rescale if do_rescale is not None else self.do_rescale
         UpperCAmelCase__										=     rescale_factor if rescale_factor is not None else self.rescale_factor
         UpperCAmelCase__										=     do_normalize if do_normalize is not None else self.do_normalize
         UpperCAmelCase__										=     image_mean if image_mean is not None else self.image_mean
         UpperCAmelCase__										=     image_std if image_std is not None else self.image_std
         UpperCAmelCase__										=     do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

         UpperCAmelCase__										=     make_list_of_images(__lowerCAmelCase )

         if not valid_images(__lowerCAmelCase ):
                raise ValueError(
                    "Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
                    "torch.Tensor, tf.Tensor or jax.ndarray." )

         if do_resize and size is None:
                raise ValueError("Size must be specified if do_resize is True." )

         if do_center_crop and crop_size is None:
                raise ValueError("Crop size must be specified if do_center_crop is True." )

         if do_rescale and rescale_factor is None:
                raise ValueError("Rescale factor must be specified if do_rescale is True." )

         if do_normalize and (image_mean is None or image_std is None):
                raise ValueError("Image mean and std must be specified if do_normalize is True." )

         # PIL RGBA images are converted to RGB
         if do_convert_rgb:
                UpperCAmelCase__										=     [convert_to_rgb(__lowerCAmelCase ) for image in images]

         # All transformations expect numpy arrays.
         UpperCAmelCase__										=     [to_numpy_array(__lowerCAmelCase ) for image in images]

         if do_resize:
                UpperCAmelCase__										=     [self.resize(image=__lowerCAmelCase		,						size=__lowerCAmelCase		,						resample=__lowerCAmelCase ) for image in images]

         if do_center_crop:
                UpperCAmelCase__										=     [self.center_crop(image=__lowerCAmelCase		,						size=__lowerCAmelCase ) for image in images]

         if do_rescale:
                UpperCAmelCase__										=     [self.rescale(image=__lowerCAmelCase		,						scale=__lowerCAmelCase ) for image in images]

         if do_normalize:
                UpperCAmelCase__										=     [self.normalize(image=__lowerCAmelCase		,						mean=__lowerCAmelCase		,						std=__lowerCAmelCase ) for image in images]

         UpperCAmelCase__										=     [to_channel_dimension_format(__lowerCAmelCase		,						__lowerCAmelCase ) for image in images]

         UpperCAmelCase__										=     {"pixel_values": images}
         return BatchFeature(data=__lowerCAmelCase		,						tensor_type=__lowerCAmelCase )









class     lowercase__  :






  def __init__(					self      :					List[str]		,						_lowercase      :					list ):




         """simple docstring"""







         UpperCAmelCase__										=     set_counts
         UpperCAmelCase__										=     max(_lowercase )
         UpperCAmelCase__										=     len(_lowercase )
         UpperCAmelCase__										=     [1] * num_sets
         UpperCAmelCase__										=     list(range(_lowercase ) )






  def 			_UpperCAmelCase  (					self      :					Dict		,						_lowercase      :					int		,						_lowercase      :					int ):




         """simple docstring"""







         UpperCAmelCase__										=     self.get_parent(_lowercase )
         UpperCAmelCase__										=     self.get_parent(_lowercase )

         if src_parent == dst_parent:
                return False

         if self.ranks[dst_parent] >= self.ranks[src_parent]:
                self.set_counts[dst_parent] += self.set_counts[src_parent]
                UpperCAmelCase__										=     0
                UpperCAmelCase__										=     dst_parent
                if self.ranks[dst_parent] == self.ranks[src_parent]:
                       self.ranks[dst_parent] += 1
                UpperCAmelCase__										=     self.set_counts[dst_parent]
         else:
                self.set_counts[src_parent] += self.set_counts[dst_parent]
                UpperCAmelCase__										=     0
                UpperCAmelCase__										=     src_parent
                UpperCAmelCase__										=     self.set_counts[src_parent]

         UpperCAmelCase__										=     max(self.max_set		,						_lowercase )
         return True






  def 			_UpperCAmelCase  (					self      :					Optional[Any]		,						_lowercase      :					int ):




         """simple docstring"""







         if self.parents[disj_set] == disj_set:
                return disj_set
         UpperCAmelCase__										=     self.get_parent(self.parents[disj_set] )
         return self.parents[disj_set]





