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- # coding=utf-8
- # Copyright 2023 The Intel AIA Team Authors, and 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.
- """
- Processor class for TVP.
- """
- from ...processing_utils import ProcessingKwargs, ProcessorMixin
- class TvpProcessorKwargs(ProcessingKwargs, total=False):
- _defaults = {
- "text_kwargs": {
- "truncation": True,
- "padding": "max_length",
- "pad_to_max_length": True,
- "return_token_type_ids": False,
- },
- }
- class TvpProcessor(ProcessorMixin):
- r"""
- Constructs an TVP processor which wraps a TVP image processor and a Bert tokenizer into a single processor.
- [`TvpProcessor`] offers all the functionalities of [`TvpImageProcessor`] and [`BertTokenizerFast`]. See the
- [`~TvpProcessor.__call__`] and [`~TvpProcessor.decode`] for more information.
- Args:
- image_processor ([`TvpImageProcessor`], *optional*):
- The image processor is a required input.
- tokenizer ([`BertTokenizerFast`], *optional*):
- The tokenizer is a required input.
- """
- attributes = ["image_processor", "tokenizer"]
- image_processor_class = "TvpImageProcessor"
- tokenizer_class = ("BertTokenizer", "BertTokenizerFast")
- def __init__(self, image_processor=None, tokenizer=None, **kwargs):
- super().__init__(image_processor, tokenizer)
- self.video_processor = image_processor
- def post_process_video_grounding(self, logits, video_durations):
- """
- Compute the time of the video.
- Args:
- logits (`torch.Tensor`):
- The logits output of TvpForVideoGrounding.
- video_durations (`float`):
- The video's duration.
- Returns:
- start (`float`):
- The start time of the video.
- end (`float`):
- The end time of the video.
- """
- start, end = (
- round(logits.tolist()[0][0] * video_durations, 1),
- round(logits.tolist()[0][1] * video_durations, 1),
- )
- return start, end
- __all__ = ["TvpProcessor"]
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