from __future__ import annotations

from random import random
from typing import Generic, TypeVar

_lowerCamelCase					:   List[str]							=		TypeVar('''KT''')
_lowerCamelCase					:   Dict							=		TypeVar('''VT''')


class 						lowercase    (     Generic[KT, VT]     ):




							def __init__(						self   :					Tuple	,							_UpperCamelCase   :					Dict = "root"	,							_UpperCamelCase   :					List[Any] = None      )					->				Dict:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       key
												SCREAMING_SNAKE_CASE    			=       value
												SCREAMING_SNAKE_CASE    			=       []




							def __repr__(						self   :					str      )					->				str:



												'''simple docstring'''

												return F"Node({self.key}: {self.value})"





							@property
							def 	__snake_case(						self   :					List[str]      )					->				int:



												'''simple docstring'''

												return len(self.forward      )



class 						lowercase    (     Generic[KT, VT]     ):




							def __init__(						self   :					List[Any]	,							_UpperCamelCase   :					Optional[int] = 0.5	,							_UpperCamelCase   :					Optional[int] = 16      )					->				int:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       Node[KT, VT]()
												SCREAMING_SNAKE_CASE    			=       0
												SCREAMING_SNAKE_CASE    			=       p
												SCREAMING_SNAKE_CASE    			=       max_level




							def __str__(						self   :					str      )					->				str:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       list(self      )

												if len(__A      ) == 0:
																	return F"SkipList(level={self.level})"

												SCREAMING_SNAKE_CASE    			=       max((len(str(__A      )      ) for item in items)	,							default=4      )
												SCREAMING_SNAKE_CASE    			=       max(__A	,							4      ) + 4

												SCREAMING_SNAKE_CASE    			=       self.head
												SCREAMING_SNAKE_CASE    			=       []

												SCREAMING_SNAKE_CASE    			=       node.forward.copy()
												lines.append(F"[{node.key}]".ljust(__A	,							"-"      ) + "* " * len(__A      )      )
												lines.append(" " * label_size + "| " * len(__A      )      )

												while len(node.forward      ) != 0:
																	SCREAMING_SNAKE_CASE    			=       node.forward[0]

																	lines.append(
																	    F"[{node.key}]".ljust(__A	,							"-"      )
																	    + " ".join(str(n.key      ) if n.key == node.key else "|" for n in forwards      )      )
																	lines.append(" " * label_size + "| " * len(__A      )      )
																	SCREAMING_SNAKE_CASE    			=       node.forward

												lines.append("None".ljust(__A      ) + "* " * len(__A      )      )
												return F"SkipList(level={self.level})\n" + "\n".join(__A      )




							def __iter__(						self   :					Optional[int]      )					->				int:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.head

												while len(node.forward      ) != 0:
																	yield node.forward[0].key
																	SCREAMING_SNAKE_CASE    			=       node.forward[0]




							def 	__snake_case(						self   :					Union[str, Any]      )					->				int:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       1
												while random() < self.p and level < self.max_level:
																	level += 1

												return level




							def 	__snake_case(						self   :					str	,							_UpperCamelCase   :					Union[str, Any]      )					->				tuple[Node[KT, VT] | None, list[Node[KT, VT]]]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       []

												SCREAMING_SNAKE_CASE    			=       self.head

												for i in reversed(range(self.level      )      ):
																	# i < node.level - When node level is lesser than `i` decrement `i`.
																	# node.forward[i].key < key - Jumping to node with key value higher
																	#                             or equal to searched key would result
																	#                             in skipping searched key.
																	while i < node.level and node.forward[i].key < key:
																						SCREAMING_SNAKE_CASE    			=       node.forward[i]
																	# Each leftmost node (relative to searched node) will potentially have to
																	# be updated.
																	update_vector.append(__A      )

												update_vector.reverse()  # Note that we were inserting values in reverse order.

												# len(node.forward) != 0 - If current node doesn't contain any further
												#                          references then searched key is not present.
												# node.forward[0].key == key - Next node key should be equal to search key
												#                              if key is present.
												if len(node.forward      ) != 0 and node.forward[0].key == key:
																	return node.forward[0], update_vector
												else:
																	return None, update_vector




							def 	__snake_case(						self   :					Any	,							_UpperCamelCase   :					List[Any]      )					->				int:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       self._locate_node(__A      )

												if node is not None:
																	for i, update_node in enumerate(__A      ):
																						# Remove or replace all references to removed node.
																						if update_node.level > i and update_node.forward[i].key == key:
																											if node.level > i:
																																SCREAMING_SNAKE_CASE    			=       node.forward[i]
																											else:
																																SCREAMING_SNAKE_CASE    			=       update_node.forward[:i]




							def 	__snake_case(						self   :					str	,							_UpperCamelCase   :					Union[str, Any]	,							_UpperCamelCase   :					List[str]      )					->				Tuple:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       self._locate_node(__A      )
												if node is not None:
																	SCREAMING_SNAKE_CASE    			=       value
												else:
																	SCREAMING_SNAKE_CASE    			=       self.random_level()

																	if level > self.level:
																						# After level increase we have to add additional nodes to head.
																						for _ in range(self.level - 1	,							__A      ):
																											update_vector.append(self.head      )
																						SCREAMING_SNAKE_CASE    			=       level

																	SCREAMING_SNAKE_CASE    			=       Node(__A	,							__A      )

																	for i, update_node in enumerate(update_vector[:level]      ):
																						# Change references to pass through new node.
																						if update_node.level > i:
																											new_node.forward.append(update_node.forward[i]      )

																						if update_node.level < i + 1:
																											update_node.forward.append(__A      )
																						else:
																											SCREAMING_SNAKE_CASE    			=       new_node





							def 	__snake_case(						self   :					List[Any]	,							_UpperCamelCase   :					Any      )					->				VT | None:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       self._locate_node(__A      )

												if node is not None:
																	return node.value

												return None





def 	__lowerCamelCase							():
					SCREAMING_SNAKE_CASE    			=       SkipList()
					skip_list.insert("Key1"      , 3  )
					skip_list.insert("Key2"      , 1_2  )
					skip_list.insert("Key3"      , 4_1  )
					skip_list.insert("Key4"      , -1_9  )

					SCREAMING_SNAKE_CASE    			=       skip_list.head
					SCREAMING_SNAKE_CASE    			=       {}
					while node.level != 0:
										SCREAMING_SNAKE_CASE    			=       node.forward[0]
										SCREAMING_SNAKE_CASE    			=       node.value

					assert len(a__  ) == 4
					assert all_values["Key1"] == 3
					assert all_values["Key2"] == 1_2
					assert all_values["Key3"] == 4_1
					assert all_values["Key4"] == -1_9





def 	__lowerCamelCase							():
					SCREAMING_SNAKE_CASE    			=       SkipList()
					skip_list.insert("Key1"      , 1_0  )
					skip_list.insert("Key1"      , 1_2  )

					skip_list.insert("Key5"      , 7  )
					skip_list.insert("Key7"      , 1_0  )
					skip_list.insert("Key10"      , 5  )

					skip_list.insert("Key7"      , 7  )
					skip_list.insert("Key5"      , 5  )
					skip_list.insert("Key10"      , 1_0  )

					SCREAMING_SNAKE_CASE    			=       skip_list.head
					SCREAMING_SNAKE_CASE    			=       {}
					while node.level != 0:
										SCREAMING_SNAKE_CASE    			=       node.forward[0]
										SCREAMING_SNAKE_CASE    			=       node.value

					if len(a__  ) != 4:
										print()
					assert len(a__  ) == 4
					assert all_values["Key1"] == 1_2
					assert all_values["Key7"] == 7
					assert all_values["Key5"] == 5
					assert all_values["Key10"] == 1_0





def 	__lowerCamelCase							():
					SCREAMING_SNAKE_CASE    			=       SkipList()
					assert skip_list.find("Some key"  ) is None





def 	__lowerCamelCase							():
					SCREAMING_SNAKE_CASE    			=       SkipList()

					skip_list.insert("Key2"      , 2_0  )
					assert skip_list.find("Key2"  ) == 2_0

					skip_list.insert("Some Key"      , 1_0  )
					skip_list.insert("Key2"      , 8  )
					skip_list.insert("V"      , 1_3  )

					assert skip_list.find("Y"  ) is None
					assert skip_list.find("Key2"  ) == 8
					assert skip_list.find("Some Key"  ) == 1_0
					assert skip_list.find("V"  ) == 1_3





def 	__lowerCamelCase							():
					SCREAMING_SNAKE_CASE    			=       SkipList()
					skip_list.delete("Some key"  )

					assert len(skip_list.head.forward  ) == 0





def 	__lowerCamelCase							():
					SCREAMING_SNAKE_CASE    			=       SkipList()

					skip_list.insert("Key1"      , 1_2  )
					skip_list.insert("V"      , 1_3  )
					skip_list.insert("X"      , 1_4  )
					skip_list.insert("Key2"      , 1_5  )

					skip_list.delete("V"  )
					skip_list.delete("Key2"  )

					assert skip_list.find("V"  ) is None
					assert skip_list.find("Key2"  ) is None





def 	__lowerCamelCase							():
					SCREAMING_SNAKE_CASE    			=       SkipList()

					skip_list.insert("Key1"      , 1_2  )
					skip_list.insert("V"      , 1_3  )
					skip_list.insert("X"      , 1_4  )
					skip_list.insert("Key2"      , 1_5  )

					skip_list.delete("V"  )
					assert skip_list.find("V"  ) is None
					assert skip_list.find("X"  ) == 1_4
					assert skip_list.find("Key1"  ) == 1_2
					assert skip_list.find("Key2"  ) == 1_5

					skip_list.delete("X"  )
					assert skip_list.find("V"  ) is None
					assert skip_list.find("X"  ) is None
					assert skip_list.find("Key1"  ) == 1_2
					assert skip_list.find("Key2"  ) == 1_5

					skip_list.delete("Key1"  )
					assert skip_list.find("V"  ) is None
					assert skip_list.find("X"  ) is None
					assert skip_list.find("Key1"  ) is None
					assert skip_list.find("Key2"  ) == 1_5

					skip_list.delete("Key2"  )
					assert skip_list.find("V"  ) is None
					assert skip_list.find("X"  ) is None
					assert skip_list.find("Key1"  ) is None
					assert skip_list.find("Key2"  ) is None





def 	__lowerCamelCase							():
					SCREAMING_SNAKE_CASE    			=       SkipList()

					skip_list.insert("Key1"      , 1_2  )
					skip_list.insert("V"      , 1_3  )
					skip_list.insert("X"      , 1_4_2  )
					skip_list.insert("Key2"      , 1_5  )

					skip_list.delete("X"  )

					def traverse_keys(UpperCAmelCase__     :							List[Any]  ):
										yield node.key
										for forward_node in node.forward:
															yield from traverse_keys(a__  )

					assert len(set(traverse_keys(skip_list.head  )  )  ) == 4





def 	__lowerCamelCase							():






					def is_sorted(UpperCAmelCase__     :							Union[str, Any]  ):
										return all(next_item >= item for item, next_item in zip(a__      , lst[1:]  )  )

					SCREAMING_SNAKE_CASE    			=       SkipList()
					for i in range(1_0  ):
										skip_list.insert(a__      , a__  )
					assert is_sorted(list(a__  )  )
					skip_list.delete(5  )
					skip_list.delete(8  )
					skip_list.delete(2  )
					assert is_sorted(list(a__  )  )
					skip_list.insert(-1_2      , -1_2  )
					skip_list.insert(7_7      , 7_7  )
					assert is_sorted(list(a__  )  )





def 	__lowerCamelCase							():






					for _ in range(1_0_0  ):
										# Repeat test 100 times due to the probabilistic nature of skip list
										# random values == random bugs
										test_insert()
										test_insert_overrides_existing_value()

										test_searching_empty_list_returns_none()
										test_search()

										test_deleting_item_from_empty_list_do_nothing()
										test_deleted_items_are_not_founded_by_find_method()
										test_delete_removes_only_given_key()
										test_delete_doesnt_leave_dead_nodes()

										test_iter_always_yields_sorted_values()





def 	__lowerCamelCase							():
					SCREAMING_SNAKE_CASE    			=       SkipList()
					skip_list.insert(2      , "2"  )
					skip_list.insert(4      , "4"  )
					skip_list.insert(6      , "4"  )
					skip_list.insert(4      , "5"  )
					skip_list.insert(8      , "4"  )
					skip_list.insert(9      , "4"  )

					skip_list.delete(4  )

					print(a__  )


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							main()

from typing import Dict, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_pytesseract_available, is_vision_available, logging, requires_backends


if is_vision_available():
							import PIL

# soft dependency
if is_pytesseract_available():
							import pytesseract

_lowerCamelCase					:   Union[str, Any]							=		logging.get_logger(__name__)





def 	__lowerCamelCase							(UpperCAmelCase__     :							List[Any]      , UpperCAmelCase__     :							List[Any]      , UpperCAmelCase__     :							Optional[Any]  ):
					return [
					    int(1_0_0_0 * (box[0] / width)  ),
					    int(1_0_0_0 * (box[1] / height)  ),
					    int(1_0_0_0 * (box[2] / width)  ),
					    int(1_0_0_0 * (box[3] / height)  ),
					]





def 	__lowerCamelCase							(UpperCAmelCase__     :							np.ndarray      , UpperCAmelCase__     :							Optional[str]      , UpperCAmelCase__     :							Optional[str] = None  ):
					SCREAMING_SNAKE_CASE    			=       tesseract_config if tesseract_config is not None else ""

					# apply OCR
					SCREAMING_SNAKE_CASE    			=       to_pil_image(UpperCAmelCase__  )
					SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       pil_image.size
					SCREAMING_SNAKE_CASE    			=       pytesseract.image_to_data(UpperCAmelCase__      , lang=UpperCAmelCase__      , output_type="dict"      , config=UpperCAmelCase__  )
					SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       data["text"], data["left"], data["top"], data["width"], data["height"]

					# filter empty words and corresponding coordinates
					SCREAMING_SNAKE_CASE    			=       [idx for idx, word in enumerate(UpperCAmelCase__  ) if not word.strip()]
					SCREAMING_SNAKE_CASE    			=       [word for idx, word in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]
					SCREAMING_SNAKE_CASE    			=       [coord for idx, coord in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]
					SCREAMING_SNAKE_CASE    			=       [coord for idx, coord in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]
					SCREAMING_SNAKE_CASE    			=       [coord for idx, coord in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]
					SCREAMING_SNAKE_CASE    			=       [coord for idx, coord in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]

					# turn coordinates into (left, top, left+width, top+height) format
					SCREAMING_SNAKE_CASE    			=       []
					for x, y, w, h in zip(UpperCAmelCase__      , UpperCAmelCase__      , UpperCAmelCase__      , UpperCAmelCase__  ):
										SCREAMING_SNAKE_CASE    			=       [x, y, x + w, y + h]
										actual_boxes.append(UpperCAmelCase__  )

					# finally, normalize the bounding boxes
					SCREAMING_SNAKE_CASE    			=       []
					for box in actual_boxes:
										normalized_boxes.append(normalize_box(UpperCAmelCase__      , UpperCAmelCase__      , UpperCAmelCase__  )  )

					assert len(UpperCAmelCase__  ) == len(UpperCAmelCase__  ), "Not as many words as there are bounding boxes"

					return words, normalized_boxes


class 						lowercase    (     a     ):
							lowercase__						:       Optional[int]								=							["""pixel_values"""]




							def __init__(						self   :					int	,							_UpperCamelCase   :					bool = True	,							_UpperCamelCase   :					Dict[str, int] = None	,							_UpperCamelCase   :					PILImageResampling = PILImageResampling.BILINEAR	,							_UpperCamelCase   :					bool = True	,							_UpperCamelCase   :					Optional[str] = None	,							_UpperCamelCase   :					Optional[str] = ""	,							**_UpperCamelCase   :					Optional[int]	,							)					->				None:



												'''simple docstring'''

												super().__init__(**_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       size if size is not None else {"height": 224, "width": 224}
												SCREAMING_SNAKE_CASE    			=       get_size_dict(_UpperCamelCase      )

												SCREAMING_SNAKE_CASE    			=       do_resize
												SCREAMING_SNAKE_CASE    			=       size
												SCREAMING_SNAKE_CASE    			=       resample
												SCREAMING_SNAKE_CASE    			=       apply_ocr
												SCREAMING_SNAKE_CASE    			=       ocr_lang
												SCREAMING_SNAKE_CASE    			=       tesseract_config




							def 	__snake_case(						self   :					List[Any]	,							_UpperCamelCase   :					np.ndarray	,							_UpperCamelCase   :					Dict[str, int]	,							_UpperCamelCase   :					PILImageResampling = PILImageResampling.BILINEAR	,							_UpperCamelCase   :					Optional[Union[str, ChannelDimension]] = None	,							**_UpperCamelCase   :					Any	,							)					->				np.ndarray:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       get_size_dict(_UpperCamelCase      )
												if "height" not in size or "width" not in size:
																	raise ValueError(F"The size dictionary must contain the keys 'height' and 'width'. Got {size.keys()}"      )
												SCREAMING_SNAKE_CASE    			=       (size["height"], size["width"])
												return resize(_UpperCamelCase	,							size=_UpperCamelCase	,							resample=_UpperCamelCase	,							data_format=_UpperCamelCase	,							**_UpperCamelCase      )





							def 	__snake_case(						self   :					Tuple	,							_UpperCamelCase   :					ImageInput	,							_UpperCamelCase   :					bool = None	,							_UpperCamelCase   :					Dict[str, int] = None	,							_UpperCamelCase   :					PILImageResampling = None	,							_UpperCamelCase   :					bool = None	,							_UpperCamelCase   :					Optional[str] = None	,							_UpperCamelCase   :					Optional[str] = None	,							_UpperCamelCase   :					Optional[Union[str, TensorType]] = None	,							_UpperCamelCase   :					ChannelDimension = ChannelDimension.FIRST	,							**_UpperCamelCase   :					str	,							)					->				PIL.Image.Image:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       do_resize if do_resize is not None else self.do_resize
												SCREAMING_SNAKE_CASE    			=       size if size is not None else self.size
												SCREAMING_SNAKE_CASE    			=       get_size_dict(_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       resample if resample is not None else self.resample
												SCREAMING_SNAKE_CASE    			=       apply_ocr if apply_ocr is not None else self.apply_ocr
												SCREAMING_SNAKE_CASE    			=       ocr_lang if ocr_lang is not None else self.ocr_lang
												SCREAMING_SNAKE_CASE    			=       tesseract_config if tesseract_config is not None else self.tesseract_config

												SCREAMING_SNAKE_CASE    			=       make_list_of_images(_UpperCamelCase      )

												if not valid_images(_UpperCamelCase      ):
																	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."      )

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

												if apply_ocr:
																	requires_backends(self	,							"pytesseract"      )
																	SCREAMING_SNAKE_CASE    			=       []
																	SCREAMING_SNAKE_CASE    			=       []
																	for image in images:
																						SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       apply_tesseract(_UpperCamelCase	,							_UpperCamelCase	,							_UpperCamelCase      )
																						words_batch.append(_UpperCamelCase      )
																						boxes_batch.append(_UpperCamelCase      )

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

												# flip color channels from RGB to BGR (as Detectron2 requires this)
												SCREAMING_SNAKE_CASE    			=       [flip_channel_order(_UpperCamelCase      ) for image in images]
												SCREAMING_SNAKE_CASE    			=       [to_channel_dimension_format(_UpperCamelCase	,							_UpperCamelCase      ) for image in images]

												SCREAMING_SNAKE_CASE    			=       BatchFeature(data={"pixel_values": images}	,							tensor_type=_UpperCamelCase      )

												if apply_ocr:
																	SCREAMING_SNAKE_CASE    			=       words_batch
																	SCREAMING_SNAKE_CASE    			=       boxes_batch
												return data




