avalanche.benchmarks.datasets.TinyImagenet
- class avalanche.benchmarks.datasets.TinyImagenet(root: str | ~pathlib.Path | None = None, *, train: bool = True, transform=None, target_transform=None, loader=<function default_loader>, download=True)[source]
Tiny Imagenet Pytorch Dataset
- __init__(root: str | ~pathlib.Path | None = None, *, train: bool = True, transform=None, target_transform=None, loader=<function default_loader>, download=True)[source]
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