avalanche.benchmarks.datasets.CORe50Dataset

class avalanche.benchmarks.datasets.CORe50Dataset(root: typing.Optional[typing.Union[str, pathlib.Path]] = None, *, train=True, transform=None, target_transform=None, loader=<function default_loader>, download=True, mini=False, object_level=True)[source]

CORe50 Pytorch Dataset

__init__(root: typing.Optional[typing.Union[str, pathlib.Path]] = None, *, train=True, transform=None, target_transform=None, loader=<function default_loader>, download=True, mini=False, object_level=True)[source]

Creates an instance of the CORe50 dataset.

Parameters
  • root – root for the datasets data. Defaults to None, which means that the default location for ‘core50’ will be used.

  • train – train or test split.

  • transform – eventual transformations to be applied.

  • target_transform – eventual transformation to be applied to the targets.

  • loader – the procedure to load the instance from the storage.

  • download – boolean to automatically download data. Default to True.

  • mini – boolean to use the 32x32 version instead of the 128x128. Default to False.

  • object_level – if the classification is objects based or category based: 50 or 10 way classification problem. Default to True (50-way object classification problem)

Methods

__init__([root, train, transform, ...])

Creates an instance of the CORe50 dataset.

Attributes