





from ...processing_utils import ProcessorMixin






class       __A					(					SCREAMING_SNAKE_CASE__				):

			'''simple docstring'''







			lowerCAmelCase_							  =		["""image_processor""", """feature_extractor"""]
			lowerCAmelCase_							  =		"""TvltImageProcessor"""
			lowerCAmelCase_							  =		"""TvltFeatureExtractor"""





			def __init__(					self ,						__lowerCAmelCase ,						__lowerCAmelCase							):



				'''simple docstring'''







				super().__init__(image_processor=snake_case__ ,						feature_extractor=snake_case__							)

				lowerCamelCase__              =	image_processor
				lowerCamelCase__              =	feature_extractor





			def __call__(					self ,						__lowerCAmelCase=None ,						__lowerCAmelCase=None ,						__lowerCAmelCase=None ,						__lowerCAmelCase=None ,						__lowerCAmelCase=False ,						__lowerCAmelCase=False ,						*__lowerCAmelCase ,						**__lowerCAmelCase ,						):



				'''simple docstring'''







				if images is None and audio is None:
					raise ValueError('''You need to specify either an `images` or `audio` input to process.'''							)

				lowerCamelCase__              =	None
				if images is not None:
					lowerCamelCase__              =	self.image_processor(snake_case__ ,						mask_pixel=snake_case__ ,						*snake_case__ ,						**snake_case__							)
				if images_mixed is not None:
					lowerCamelCase__              =	self.image_processor(snake_case__ ,						is_mixed=snake_case__ ,						*snake_case__ ,						**snake_case__							)
				if audio is not None:
					lowerCamelCase__              =	self.feature_extractor(
					    snake_case__ ,						*snake_case__ ,						sampling_rate=snake_case__ ,						mask_audio=snake_case__ ,						**snake_case__							)

				lowerCamelCase__              =	{}
				if audio is not None:
					output_dict.update(snake_case__							)
				if images is not None:
					output_dict.update(snake_case__							)
				if images_mixed_dict is not None:
					output_dict.update(snake_case__							)
				return output_dict





			@property
			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	self.image_processor.model_input_names
				lowerCamelCase__              =	self.feature_extractor.model_input_names
				return list(dict.fromkeys(image_processor_input_names + feature_extractor_input_names							)							)










import warnings

from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor


_a						=   logging.get_logger(__name__)






class       __A					(					lowerCAmelCase				):

			'''simple docstring'''







			def __init__(					self ,						*__lowerCAmelCase ,						**__lowerCAmelCase							):



				'''simple docstring'''







				warnings.warn(
				    '''The class OwlViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
				    ''' use OwlViTImageProcessor instead.''' ,						__lowerCAmelCase ,						)
				super().__init__(*__lowerCAmelCase ,						**__lowerCAmelCase							)



