tlt.datasets.image_classification.torchvision_image_classification_dataset.TorchvisionImageClassificationDataset

class tlt.datasets.image_classification.torchvision_image_classification_dataset.TorchvisionImageClassificationDataset(dataset_dir, dataset_name, split=['train'], download=True, num_workers=0, shuffle_files=True, **kwargs)

An image classification dataset from the torchvision catalog

__init__(dataset_dir, dataset_name, split=['train'], download=True, num_workers=0, shuffle_files=True, **kwargs)

Class constructor

Methods

__init__(dataset_dir, dataset_name[, split, ...])	Class constructor
get_batch([subset])	Get a single batch of images and labels from the dataset.
get_inc_dataloaders()
preprocess([image_size, batch_size, add_aug])	Preprocess the dataset to resize, normalize, and batch the images.
shuffle_split([train_pct, val_pct, ...])	Randomly split the dataset into train, validation, and test subsets with a pseudo-random seed option.

Attributes

class_names	Returns the list of class names
data_loader	A data loader object corresponding to the dataset
dataset	Returns the framework dataset object (torch.utils.data.Dataset)
dataset_catalog	The string name of the dataset catalog (or None)
dataset_dir	Host directory containing the dataset files
dataset_name	Name of the dataset
info	Returns a dictionary of information about the dataset
test_loader	A data loader object corresponding to the test subset
test_subset	A subset of the dataset held out for final testing/evaluation
train_loader	A data loader object corresponding to the training subset
train_subset	A subset of the dataset used for training
validation_loader	A data loader object corresponding to the validation subset
validation_subset	A subset of the dataset used for validation/evaluation