semipy.datasets.get_stl10

    semipy.datasets.cifar.get_stl10(num_labelled: int = 5000,
                                    num_unlabelled: int = 100000,
                                    valid_proportion: float = 0.0,
                                    path: str = './data',
                                    augmentation: bool = False,
                                    include_labelled: bool = False) -> dict

Downloads STL10 dataset from torchvision and transforms it into a Semi-Supervised dataset (with labelled and unlabelled samples).

Parameters

• num_labelled (int) - Number of labelled items to include in the dataset. Default: 5 000
• num_unlabelled (int) - Number of unlabelled items to include in the dataset. Default: 100 000
• valid_proportion (float) - Size of the validation set defined by a proportion with respect to the number of labelled items. Default: 0.0
• path (str) - Path to download and store data samples. Default: './data'
• augmentation (bool) - To use augmentation or not when sampling in the dataset. Default: False
• include_labelled (bool) - To include labelled items into unlabelled set as additional data. Default: False