CamVidDataModule¶

class torch_uncertainty.datamodules.segmentation.CamVidDataModule(root, batch_size, val_split=None, num_workers=1, pin_memory=True, persistent_workers=True)[source]¶

DataModule for the CamVid dataset.

Parameters:

root (str or Path) – Root directory of the datasets.
batch_size (int) – Number of samples per batch.
val_split (float or None, optional) – Share of training samples to use for validation. Defaults to None.
num_workers (int, optional) – Number of dataloaders to use. Defaults to 1.
pin_memory (bool, optional) – Whether to pin memory. Defaults to True.
persistent_workers (bool, optional) – Whether to use persistent workers. Defaults to True.

Note

This datamodule injects the following transforms into the training and validation/test datasets:

from torchvision.transforms import v2

v2.Compose(
    [
        v2.Resize((360, 480)),
        v2.ToDtype(
            dtype={
                tv_tensors.Image: torch.float32,
                tv_tensors.Mask: torch.int64,
                "others": None,
            },
            scale=True,
        ),
    ]
)

This behavior can be modified by overriding self.train_transform and self.test_transform after initialization.