






import logging
import os
import threading
import time


try:
				import warnings
except ImportError:
				a_		:						Dict             =    None

try:
				import msvcrt
except ImportError:
				a_		:						Union[str, Any]             =    None

try:
				import fcntl
except ImportError:
				a_		:						str             =    None


# Backward compatibility
# ------------------------------------------------
try:
				TimeoutError
except NameError:
				a_		:						Optional[int]             =    OSError


# Data
# ------------------------------------------------
a_		:						List[str]             =    [
    'Timeout',
    'BaseFileLock',
    'WindowsFileLock',
    'UnixFileLock',
    'SoftFileLock',
    'FileLock',
]

a_		:						Union[str, Any]             =    '3.0.12'


a_		:						List[str]             =    None






def 				lowerCamelCase__				():
			global _logger
			SCREAMING_SNAKE_CASE						= _logger or logging.getLogger(__name__)
			return _logger

class 		_snake_case  (  A__					):






			def __init__(       self		,					a)      ->       Any:
						SCREAMING_SNAKE_CASE						= lock_file
						return None







			def __str__(       self)      ->       Any:
						SCREAMING_SNAKE_CASE						= f'''The file lock \'{self.lock_file}\' could not be acquired.'''
						return temp



class 		_snake_case  :






			def __init__(       self		,					a)      ->       Optional[int]:
						SCREAMING_SNAKE_CASE						= lock
						return None






			def __enter__(       self)      ->       Tuple:
						return self.lock







			def __exit__(       self		,					a		,					a		,					a)      ->       Any:
						self.lock.release()
						return None



class 		_snake_case  :






			def __init__(       self		,					a		,					a=-1		,					a=None)      ->       Tuple:
						SCREAMING_SNAKE_CASE						= max_filename_length if max_filename_length is not None else 255
						# Hash the filename if it's too long
						SCREAMING_SNAKE_CASE						= self.hash_filename_if_too_long(a		,					a)
						# The path to the lock file.
						SCREAMING_SNAKE_CASE						= lock_file

						# The file descriptor for the *_lock_file* as it is returned by the
						# os.open() function.
						# This file lock is only NOT None, if the object currently holds the
						# lock.
						SCREAMING_SNAKE_CASE						= None

						# The default timeout value.
						SCREAMING_SNAKE_CASE						= timeout

						# We use this lock primarily for the lock counter.
						SCREAMING_SNAKE_CASE						= threading.Lock()

						# The lock counter is used for implementing the nested locking
						# mechanism. Whenever the lock is acquired, the counter is increased and
						# the lock is only released, when this value is 0 again.
						SCREAMING_SNAKE_CASE						= 0
						return None






			@property
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Any:
						return self._lock_file






			@property
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Optional[Any]:
						return self._timeout






			@timeout.setter
			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       str:
						SCREAMING_SNAKE_CASE						= float(a)
						return None






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[Any]:
						raise NotImplementedError()






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[Any]:
						raise NotImplementedError()






			@property
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Dict:
						return self._lock_file_fd is not None






			def    SCREAMING_SNAKE_CASE__    (       self		,					a=None		,					a=0.05)      ->       Tuple:
						# Use the default timeout, if no timeout is provided.
						if timeout is None:
									SCREAMING_SNAKE_CASE						= self.timeout

						# Increment the number right at the beginning.
						# We can still undo it, if something fails.
						with self._thread_lock:
									self._lock_counter += 1

						SCREAMING_SNAKE_CASE						= id(self)
						SCREAMING_SNAKE_CASE						= self._lock_file
						SCREAMING_SNAKE_CASE						= time.time()
						try:
									while True:
												with self._thread_lock:
															if not self.is_locked:
																		logger().debug(f'''Attempting to acquire lock {lock_id} on {lock_filename}''')
																		self._acquire()

												if self.is_locked:
															logger().debug(f'''Lock {lock_id} acquired on {lock_filename}''')
															break
												elif timeout >= 0 and time.time() - start_time > timeout:
															logger().debug(f'''Timeout on acquiring lock {lock_id} on {lock_filename}''')
															raise Timeout(self._lock_file)
												else:
															logger().debug(
															    f'''Lock {lock_id} not acquired on {lock_filename}, waiting {poll_intervall} seconds ...''')
															time.sleep(a)
						except:  # noqa
									# Something did go wrong, so decrement the counter.
									with self._thread_lock:
												SCREAMING_SNAKE_CASE						= max(0		,					self._lock_counter - 1)

									raise
						return _Acquire_ReturnProxy(lock=self)






			def    SCREAMING_SNAKE_CASE__    (       self		,					a=False)      ->       str:
						with self._thread_lock:
									if self.is_locked:
												self._lock_counter -= 1

												if self._lock_counter == 0 or force:
															SCREAMING_SNAKE_CASE						= id(self)
															SCREAMING_SNAKE_CASE						= self._lock_file

															logger().debug(f'''Attempting to release lock {lock_id} on {lock_filename}''')
															self._release()
															SCREAMING_SNAKE_CASE						= 0
															logger().debug(f'''Lock {lock_id} released on {lock_filename}''')

						return None






			def __enter__(       self)      ->       Union[str, Any]:
						self.acquire()
						return self






			def __exit__(       self		,					a		,					a		,					a)      ->       int:
						self.release()
						return None






			def __del__(       self)      ->       Union[str, Any]:
						self.release(force=a)
						return None







			def    SCREAMING_SNAKE_CASE__    (       self		,					a		,					a)      ->       str:
						SCREAMING_SNAKE_CASE						= os.path.basename(a)
						if len(a) > max_length and max_length > 0:
									SCREAMING_SNAKE_CASE						= os.path.dirname(a)
									SCREAMING_SNAKE_CASE						= str(hash(a))
									SCREAMING_SNAKE_CASE						= filename[: max_length - len(a) - 8] + '...' + hashed_filename + '.lock'
									return os.path.join(a		,					a)
						else:
									return path



class 		_snake_case  (  A__					):






			def __init__(       self		,					a		,					a=-1		,					a=None)      ->       Union[str, Any]:
						from .file_utils import relative_to_absolute_path

						super().__init__(a		,					timeout=a		,					max_filename_length=a)
						SCREAMING_SNAKE_CASE						= '\\\\?\\' + relative_to_absolute_path(self.lock_file)






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Any:
						SCREAMING_SNAKE_CASE						= os.O_RDWR | os.O_CREAT | os.O_TRUNC

						try:
									SCREAMING_SNAKE_CASE						= os.open(self._lock_file		,					a)
						except OSError:
									pass
						else:
									try:
												msvcrt.locking(a		,					msvcrt.LK_NBLCK		,					1)
									except OSError:
												os.close(a)
									else:
												SCREAMING_SNAKE_CASE						= fd
						return None







			def    SCREAMING_SNAKE_CASE__    (       self)      ->       str:
						SCREAMING_SNAKE_CASE						= self._lock_file_fd
						SCREAMING_SNAKE_CASE						= None
						msvcrt.locking(a		,					msvcrt.LK_UNLCK		,					1)
						os.close(a)

						try:
									os.remove(self._lock_file)
						# Probably another instance of the application
						# that acquired the file lock.
						except OSError:
									pass
						return None



class 		_snake_case  (  A__					):






			def __init__(       self		,					a		,					a=-1		,					a=None)      ->       Dict:
						SCREAMING_SNAKE_CASE						= os.statvfs(os.path.dirname(a)).f_namemax
						super().__init__(a		,					timeout=a		,					max_filename_length=a)






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[Any]:
						SCREAMING_SNAKE_CASE						= os.O_RDWR | os.O_CREAT | os.O_TRUNC
						SCREAMING_SNAKE_CASE						= os.open(self._lock_file		,					a)

						try:
									fcntl.flock(a		,					fcntl.LOCK_EX | fcntl.LOCK_NB)
						except OSError:
									os.close(a)
						else:
									SCREAMING_SNAKE_CASE						= fd
						return None







			def    SCREAMING_SNAKE_CASE__    (       self)      ->       int:
						# Do not remove the lockfile:
						#
						#   https://github.com/benediktschmitt/py-filelock/issues/31
						#   https://stackoverflow.com/questions/17708885/flock-removing-locked-file-without-race-condition
						SCREAMING_SNAKE_CASE						= self._lock_file_fd
						SCREAMING_SNAKE_CASE						= None
						fcntl.flock(a		,					fcntl.LOCK_UN)
						os.close(a)
						return None



class 		_snake_case  (  A__					):






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[Any]:
						SCREAMING_SNAKE_CASE						= os.O_WRONLY | os.O_CREAT | os.O_EXCL | os.O_TRUNC
						try:
									SCREAMING_SNAKE_CASE						= os.open(self._lock_file		,					a)
						except OSError:
									pass
						else:
									SCREAMING_SNAKE_CASE						= fd
						return None







			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Union[str, Any]:
						os.close(self._lock_file_fd)
						SCREAMING_SNAKE_CASE						= None

						try:
									os.remove(self._lock_file)
						# The file is already deleted and that's what we want.
						except OSError:
									pass
						return None



a_		:						List[str]             =    None

if msvcrt:
				a_		:						Dict             =    WindowsFileLock
elif fcntl:
				a_		:						Dict             =    UnixFileLock
else:
				a_		:						Optional[int]             =    SoftFileLock

				if warnings is not None:
								warnings.warn('only soft file lock is available')












from typing import Any, Dict, List, Union

from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
				from ..image_utils import load_image


if is_torch_available():
				import torch

				from ..models.auto.modeling_auto import MODEL_FOR_OBJECT_DETECTION_MAPPING, MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING

a_		:						str             =    logging.get_logger(__name__)


a_		:						List[Any]             =    Dict[str, Any]
a_		:						Optional[int]             =    List[Prediction]

@add_end_docstrings(A__					)
class 		_snake_case  (  A__					):






			def __init__(       self		,					*a		,					**a)      ->       int:
						super().__init__(*a		,					**a)

						if self.framework == "tf":
									raise ValueError(f'''The {self.__class__} is only available in PyTorch.''')

						requires_backends(self		,					'vision')
						self.check_model_type(
						    dict(MODEL_FOR_OBJECT_DETECTION_MAPPING.items() + MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING.items()))






			def    SCREAMING_SNAKE_CASE__    (       self		,					**a)      ->       int:
						SCREAMING_SNAKE_CASE						= {}
						if "threshold" in kwargs:
									SCREAMING_SNAKE_CASE						= kwargs['threshold']
						return {}, {}, postprocess_kwargs






			def __call__(       self		,					*a		,					**a)      ->       Union[Predictions, List[Prediction]]:
						return super().__call__(*a		,					**a)






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       List[str]:
						SCREAMING_SNAKE_CASE						= load_image(a)
						SCREAMING_SNAKE_CASE						= torch.IntTensor([[image.height, image.width]])
						SCREAMING_SNAKE_CASE						= self.image_processor(images=[image]		,					return_tensors='pt')
						if self.tokenizer is not None:
									SCREAMING_SNAKE_CASE						= self.tokenizer(text=inputs['words']		,					boxes=inputs['boxes']		,					return_tensors='pt')
						SCREAMING_SNAKE_CASE						= target_size
						return inputs






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       int:
						SCREAMING_SNAKE_CASE						= model_inputs.pop('target_size')
						SCREAMING_SNAKE_CASE						= self.model(**a)
						SCREAMING_SNAKE_CASE						= outputs.__class__({'target_size': target_size, **outputs})
						if self.tokenizer is not None:
									SCREAMING_SNAKE_CASE						= model_inputs['bbox']
						return model_outputs






			def    SCREAMING_SNAKE_CASE__    (       self		,					a		,					a=0.9)      ->       Dict:
						SCREAMING_SNAKE_CASE						= model_outputs['target_size']
						if self.tokenizer is not None:
									# This is a LayoutLMForTokenClassification variant.
									# The OCR got the boxes and the model classified the words.
									SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						= target_size[0].tolist()

									def unnormalize(a):
												return self._get_bounding_box(
												    torch.Tensor(
												        [
												            (width * bbox[0] / 1000),
												            (height * bbox[1] / 1000),
												            (width * bbox[2] / 1000),
												            (height * bbox[3] / 1000),
												        ]))

									SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						= model_outputs['logits'].squeeze(0).softmax(dim=-1).max(dim=-1)
									SCREAMING_SNAKE_CASE						= [self.model.config.idalabel[prediction] for prediction in classes.tolist()]
									SCREAMING_SNAKE_CASE						= [unnormalize(a) for bbox in model_outputs['bbox'].squeeze(0)]
									SCREAMING_SNAKE_CASE						= ['score', 'label', 'box']
									SCREAMING_SNAKE_CASE						= [dict(zip(a		,					a)) for vals in zip(scores.tolist()		,					a		,					a) if vals[0] > threshold]
						else:
									# This is a regular ForObjectDetectionModel
									SCREAMING_SNAKE_CASE						= self.image_processor.post_process_object_detection(a		,					a		,					a)
									SCREAMING_SNAKE_CASE						= raw_annotations[0]
									SCREAMING_SNAKE_CASE						= raw_annotation['scores']
									SCREAMING_SNAKE_CASE						= raw_annotation['labels']
									SCREAMING_SNAKE_CASE						= raw_annotation['boxes']

									SCREAMING_SNAKE_CASE						= scores.tolist()
									SCREAMING_SNAKE_CASE						= [self.model.config.idalabel[label.item()] for label in labels]
									SCREAMING_SNAKE_CASE						= [self._get_bounding_box(a) for box in boxes]

									# {"scores": [...], ...} --> [{"score":x, ...}, ...]
									SCREAMING_SNAKE_CASE						= ['score', 'label', 'box']
									SCREAMING_SNAKE_CASE						= [
									    dict(zip(a		,					a))
									    for vals in zip(raw_annotation['scores']		,					raw_annotation['labels']		,					raw_annotation['boxes'])
									]

						return annotation







			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       Dict[str, int]:
						if self.framework != "pt":
									raise ValueError('The ObjectDetectionPipeline is only available in PyTorch.')
						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						= box.int().tolist()
						SCREAMING_SNAKE_CASE						= {
						    'xmin': xmin,
						    'ymin': ymin,
						    'xmax': xmax,
						    'ymax': ymax,
						}
						return bbox




