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Source code for mmflow.datasets.pipelines.compose

# Copyright (c) OpenMMLab. All rights reserved.
import collections
from typing import Sequence

from mmcv.utils import build_from_cfg

from ..builder import PIPELINES


[docs]@PIPELINES.register_module() class Compose: """Compose multiple transforms sequentially. Args: transforms (Sequence[dict | callable]): Sequence of transform object or config dict to be composed. """ def __init__(self, transforms: Sequence) -> None: assert isinstance(transforms, collections.abc.Sequence) self.transforms = [] for transform in transforms: if isinstance(transform, dict): transform = build_from_cfg(transform, PIPELINES) self.transforms.append(transform) elif callable(transform): self.transforms.append(transform) else: raise TypeError('transform must be callable or a dict') def __call__(self, data: dict) -> dict: """Call function to apply transforms sequentially. Args: data (dict): A result dict contains the data to transform. Returns: dict: Transformed data. """ for t in self.transforms: data = t(data) if data is None: return None return data def __repr__(self): format_string = self.__class__.__name__ + '(' for t in self.transforms: format_string += '\n' format_string += f' {t}' format_string += '\n)' return format_string
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