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|
| from typing import Dict
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|
|
| from mmengine.model import BaseDataPreprocessor, ModuleDict
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|
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| from mmaction.registry import MODELS
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|
|
|
|
| @MODELS.register_module()
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| class MultiModalDataPreprocessor(BaseDataPreprocessor):
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| """Multi-Modal data pre-processor for action recognition tasks."""
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|
|
| def __init__(self, preprocessors: Dict) -> None:
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| super().__init__()
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| self.preprocessors = ModuleDict()
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| for name, pre_cfg in preprocessors.items():
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| assert 'type' in pre_cfg, (
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| 'Each data preprocessor should contain the key type, '
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| f'but got {pre_cfg}')
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| self.preprocessors[name] = MODELS.build(pre_cfg)
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|
|
| def forward(self, data: Dict, training: bool = False) -> Dict:
|
| """Preprocesses the data into the model input format.
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|
|
| Args:
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| data (dict): Data returned by dataloader.
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| training (bool): Whether to enable training time augmentation.
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|
|
| Returns:
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| dict: Data in the same format as the model input.
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| """
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| data = self.cast_data(data)
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| inputs, data_samples = data['inputs'], data['data_samples']
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| for modality, modality_data in inputs.items():
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| preprocessor = self.preprocessors[modality]
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| modality_data, data_samples = preprocessor.preprocess(
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| modality_data, data_samples, training)
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| inputs[modality] = modality_data
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|
|
| data['inputs'] = inputs
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| data['data_samples'] = data_samples
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| return data
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|
|
