draugr.torch_utilities.datasets.supervised.vision_datasets.dict_dataset.DictDatasetFolder¶
- class draugr.torch_utilities.datasets.supervised.vision_datasets.dict_dataset.DictDatasetFolder(root: ~pathlib.Path, loader: ~torch.utils.data.dataloader.DataLoader, extensions: ~typing.Optional[~typing.Iterable] = None, transform: ~typing.Optional[callable] = None, target_transform: ~typing.Optional[callable] = None, is_valid_file: callable = <function has_file_allowed_extension>)[source]¶
Bases:
VisionDataset
A generic data loader where the samples are arranged in this way:
root/class_x/xxx.ext root/class_x/xxy.ext root/class_x/xxz.ext
root/class_y/123.ext root/class_y/nsdf3.ext root/class_y/asd932_.ext
Args: root (string): Root directory path. loader (callable): A function to load a sample given its path. extensions (tuple[string]): A list of allowed extensions.
both extensions and is_valid_file should not be passed.
- transform (callable, optional): A function/transform that takes in
a sample and returns a transformed version. E.g,
transforms.RandomCrop
for images.- target_transform (callable, optional): A function/transform that takes
in the target and transforms it.
- is_valid_file (callable, optional): A function that takes path of a file
and check if the file is a valid file (used to check of corrupt files) both extensions and is_valid_file should not be passed.
Attributes: _categories (list): List of the class names sorted alphabetically. _data (list): List of (sample path, class_index) tuples
- __init__(root: ~pathlib.Path, loader: ~torch.utils.data.dataloader.DataLoader, extensions: ~typing.Optional[~typing.Iterable] = None, transform: ~typing.Optional[callable] = None, target_transform: ~typing.Optional[callable] = None, is_valid_file: callable = <function has_file_allowed_extension>)[source]¶
Methods
__init__
(root, loader[, extensions, ...])extra_repr
()sample
(target, index)description