nip.image_classification.data.TorchVisionDatasetWrapper#
- class nip.image_classification.data.TorchVisionDatasetWrapper(root: str | Path, train: bool = True, transform: callable | None = None, target_transform: callable | None = None, download: bool = False)[source]#
A wrapper for TorchVision datasets, implementing a common interface.
Derived classes should defined the class attributes below.
Class attributes#
- data_classtype[VisionDataset]
The TorchVision dataset class.
- num_channelsint
The number of channels of the images in the dataset.
- widthint
The width of the images in the dataset.
- heightint
The height of the images in the dataset.
- selected_classestuple[int, int]
When selecting two classes from the original dataset, the default two to select.
- binarification_seedint
The seed used when doing a randomised binarification.
Methods Summary
__init__
(root[, train, transform, ...])Attributes
binarification_seed
selected_classes
num_channels
width
height
Methods