Source code for mmaction.datasets.base

# Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta
from typing import Callable, List, Optional, Union

import torch
from mmengine.dataset import BaseDataset

from mmaction.utils import ConfigType

[docs]class BaseActionDataset(BaseDataset, metaclass=ABCMeta): """Base class for datasets. Args: ann_file (str): Path to the annotation file. pipeline (List[Union[dict, ConfigDict, Callable]]): A sequence of data transforms. data_prefix (dict or ConfigDict, optional): Path to a directory where videos are held. Defaults to None. test_mode (bool): Store True when building test or validation dataset. Defaults to False. multi_class (bool): Determines whether the dataset is a multi-class dataset. Defaults to False. num_classes (int, optional): Number of classes of the dataset, used in multi-class datasets. Defaults to None. start_index (int): Specify a start index for frames in consideration of different filename format. However, when taking videos as input, it should be set to 0, since frames loaded from videos count from 0. Defaults to 0. modality (str): Modality of data. Support ``RGB``, ``Flow``, ``Pose``, ``Audio``. Defaults to ``RGB``. """ def __init__(self, ann_file: str, pipeline: List[Union[ConfigType, Callable]], data_prefix: Optional[ConfigType] = dict(prefix=''), test_mode: bool = False, multi_class: bool = False, num_classes: Optional[int] = None, start_index: int = 0, modality: str = 'RGB', **kwargs) -> None: self.multi_class = multi_class self.num_classes = num_classes self.start_index = start_index self.modality = modality super().__init__( ann_file, pipeline=pipeline, data_prefix=data_prefix, test_mode=test_mode, **kwargs)
[docs] def get_data_info(self, idx: int) -> dict: """Get annotation by index.""" data_info = super().get_data_info(idx) data_info['modality'] = self.modality data_info['start_index'] = self.start_index if self.multi_class: onehot = torch.zeros(self.num_classes) onehot[data_info['label']] = 1. data_info['label'] = onehot return data_info
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