|
|
| import os.path as osp
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| from typing import Callable, Dict, List, Optional, Union
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|
|
| from mmengine.utils import check_file_exist
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|
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| from mmaction.registry import DATASETS
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| from .base import BaseActionDataset
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|
|
|
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| @DATASETS.register_module()
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| class AudioDataset(BaseActionDataset):
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| """Audio dataset for action recognition.
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|
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| The ann_file is a text file with multiple lines, and each line indicates
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| a sample audio or extracted audio feature with the filepath, total frames
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| of the raw video and label, which are split with a whitespace.
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| Example of a annotation file:
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|
|
| .. code-block:: txt
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| some/directory-1.npy 163 1
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| some/directory-2.npy 122 1
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| some/directory-3.npy 258 2
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| some/directory-4.npy 234 2
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| some/directory-5.npy 295 3
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| some/directory-6.npy 121 3
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|
|
| Args:
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| ann_file (str): Path to the annotation file.
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| pipeline (list[dict | callable]): A sequence of data transforms.
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| data_prefix (dict): Path to a directory where
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| audios are held. Defaults to ``dict(audio='')``.
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| multi_class (bool): Determines whether it is a multi-class
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| recognition dataset. Defaults to False.
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| num_classes (int, optional): Number of classes in the dataset.
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| Defaults to None.
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| """
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|
|
| def __init__(self,
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| ann_file: str,
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| pipeline: List[Union[Dict, Callable]],
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| data_prefix: Dict = dict(audio=''),
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| multi_class: bool = False,
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| num_classes: Optional[int] = None,
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| **kwargs) -> None:
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| super().__init__(
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| ann_file,
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| pipeline,
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| data_prefix=data_prefix,
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| multi_class=multi_class,
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| num_classes=num_classes,
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| modality='Audio',
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| **kwargs)
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|
|
| def load_data_list(self) -> List[Dict]:
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| """Load annotation file to get audio information."""
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| check_file_exist(self.ann_file)
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| data_list = []
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| with open(self.ann_file, 'r') as fin:
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| for line in fin:
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| line_split = line.strip().split()
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| video_info = {}
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| idx = 0
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| filename = line_split[idx]
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| if self.data_prefix['audio'] is not None:
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| filename = osp.join(self.data_prefix['audio'], filename)
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| video_info['audio_path'] = filename
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| idx += 1
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|
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| video_info['total_frames'] = int(line_split[idx])
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| idx += 1
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|
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| label = [int(x) for x in line_split[idx:]]
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| assert label, f'missing label in line: {line}'
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| if self.multi_class:
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| assert self.num_classes is not None
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| video_info['label'] = label
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| else:
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| assert len(label) == 1
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| video_info['label'] = label[0]
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| data_list.append(video_info)
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|
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| return data_list
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|
|
