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