




# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
	from PIL import Image
class        __snake_case  (_a		):
				lowerCAmelCase__				=     "Salesforce/blip-image-captioning-base"
				lowerCAmelCase__				=     (
				    "This is a tool that generates a description of an image. It takes an input named `image` which should be the "
				    "image to caption, and returns a text that contains the description in English."
				)
				lowerCAmelCase__				=     "image_captioner"
				lowerCAmelCase__				=     AutoModelForVisionaSeq

				lowerCAmelCase__				=     ["image"]
				lowerCAmelCase__				=     ["text"]



				def __init__(      self      :		List[str]		,	*_UpperCAmelCase      :		Optional[int]		,	**_UpperCAmelCase      :		Optional[int]      )  ->    Optional[Any]:





								'''simple docstring'''




								requires_backends(self		,	["""vision"""]      )
								super().__init__(*_UpperCAmelCase		,	**_UpperCAmelCase      )



				def       SCREAMING_SNAKE_CASE       (      self      :		Dict		,	_UpperCAmelCase      :		"Image"      )  ->    Tuple:





								'''simple docstring'''




								return self.pre_processor(images=_UpperCAmelCase		,	return_tensors="""pt"""      )



				def       SCREAMING_SNAKE_CASE       (      self      :		Union[str, Any]		,	_UpperCAmelCase      :		List[Any]      )  ->    Any:





								'''simple docstring'''




								return self.model.generate(**_UpperCAmelCase      )



				def       SCREAMING_SNAKE_CASE       (      self      :		Union[str, Any]		,	_UpperCAmelCase      :		int      )  ->    Tuple:





								'''simple docstring'''




								return self.pre_processor.batch_decode(_UpperCAmelCase		,	skip_special_tokens=_UpperCAmelCase      )[0].strip()







def 							_UpperCAmelCase  (UpperCamelCase_ : str      ,    UpperCamelCase_ : bool = False       ):
				'''simple docstring'''

				if not isinstance(UpperCamelCase_      ,    UpperCamelCase_       ):
								_lowerCAmelCase    :    Tuple										=      F"Expected string as input, found {type(UpperCamelCase_       )}"
								raise ValueError(UpperCamelCase_       )
				if not isinstance(UpperCamelCase_      ,    UpperCamelCase_       ):
								_lowerCAmelCase    :    Optional[Any]										=      F"Expected boolean as use_pascal parameter, found {type(UpperCamelCase_       )}"
								raise ValueError(UpperCamelCase_       )

				_lowerCAmelCase    :    Any										=      input_str.split("""_"""       )

				_lowerCAmelCase    :    str										=      0 if use_pascal else 1

				_lowerCAmelCase    :    Any										=      words[start_index:]

				_lowerCAmelCase    :    List[str]										=      [word[0].upper() + word[1:] for word in words_to_capitalize]

				_lowerCAmelCase    :    Any										=      """""" if use_pascal else words[0]

				return "".join([initial_word, *capitalized_words]       )


if __name__ == "__main__":
	from doctest import testmod

	testmod()

