avalanche.benchmarks.datasets.CUB200

class avalanche.benchmarks.datasets.CUB200(root: ~pathlib.Path | str | None = None, *, train=True, transform=None, target_transform=None, loader=<function default_loader>, download=True)[source]

Basic CUB200 PathsDataset to be used as a standard PyTorch Dataset. A classic continual learning benchmark built on top of this dataset can be found in ‘benchmarks.classic’, while for more custom benchmark design please use the ‘benchmarks.generators’.

__init__(root: ~pathlib.Path | str | None = None, *, train=True, transform=None, target_transform=None, loader=<function default_loader>, download=True)[source]

Parameters:

root – root dir where the dataset can be found or downloaded. Defaults to None, which means that the default location for ‘CUB_200_2011’ will be used.
train – train or test subset of the original dataset. Default to True.
transform – eventual input data transformations to apply. Default to None.
target_transform – eventual target data transformations to apply. Default to None.
loader – method to load the data from disk. Default to torchvision default_loader.
download – default set to True. If the data is already downloaded it will skip the download.

Methods

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

param root:: root dir where the dataset can be found or downloaded.

Attributes

`filename`
`gdrive_url`
`images_folder`
`official_url`
`tgz_md5`
`root`	The path to the dataset.
`download`	If True, the dataset will be downloaded (only if needed).
`verbose`	If True, some info about the download process will be printed.