Table of Contents
Shortcuts

# Source code for mmseg.datasets.dataset_wrappers

    from torch.utils.data.dataset import ConcatDataset as _ConcatDataset

    from .builder import DATASETS

    @DATASETS.register_module()
    class ConcatDataset(_ConcatDataset):
        """A wrapper of concatenated dataset.

        Same as :obj:`torch.utils.data.dataset.ConcatDataset`, but
        concat the group flag for image aspect ratio.

        Args:
            datasets (list[:obj:`Dataset`]): A list of datasets.
        """

        def __init__(self, datasets):
            super(ConcatDataset, self).__init__(datasets)
            self.CLASSES = datasets[0].CLASSES
            self.PALETTE = datasets[0].PALETTE

    @DATASETS.register_module()
    class RepeatDataset(object):
        """A wrapper of repeated dataset.

        The length of repeated dataset will be `times` larger than the original
        dataset. This is useful when the data loading time is long but the dataset
        is small. Using RepeatDataset can reduce the data loading time between
        epochs.

        Args:
            dataset (:obj:`Dataset`): The dataset to be repeated.
            times (int): Repeat times.
        """

        def __init__(self, dataset, times):
            self.dataset = dataset
            self.times = times
            self.CLASSES = dataset.CLASSES
            self.PALETTE = dataset.PALETTE
            self._ori_len = len(self.dataset)

        def __getitem__(self, idx):
            """Get item from original dataset."""
            return self.dataset[idx % self._ori_len]

        def __len__(self):
            """The length is multiplied by ``times``"""
            return self.times * self._ori_len