avalanche.benchmarks.datasets.TinyImagenet

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

Tiny Imagenet Pytorch Dataset

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

Creates an instance of the Tiny Imagenet dataset.

Parameters:

• root – folder in which to download dataset. Defaults to None, which means that the default location for ‘tinyimagenet’ will be used.

• train – True for training set, False for test set.

• transform – Pytorch transformation function for x.

• target_transform – Pytorch transformation function for y.

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

• download (bool) – If True, the dataset will be downloaded if needed.

Methods

__init__([root, train, transform, ...])	Creates an instance of the Tiny Imagenet dataset.
get_test_images_paths(class_name)	Gets the test set image paths
get_train_images_paths(class_name)	Gets the training set image paths.
labels2dict(data_folder)	Returns dictionaries to convert class names into progressive ids and viceversa.
load_data()	Load all images paths and targets.

Attributes

filename
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.