dataeval.utils.dataset.read_dataset

dataeval.utils.dataset.read_dataset(dataset)

Extract information from a dataset at each index into individual lists of each information position

Parameters:

dataset (torch.utils.data.Dataset) – Input dataset

Returns:

All objects in individual lists based on return position from dataset

Return type:

List[List[Any]]

Warning

No type checking is done between lists or data inside lists

See also

torch.utils.data.Dataset

Examples

>>> import numpy as np
>>> data = np.ones((10, 1, 3, 3))
>>> labels = np.ones((10,))
>>> class ICDataset:
...     def __init__(self, data, labels):
...         self.data = data
...         self.labels = labels
...
...     def __getitem__(self, idx):
...         return self.data[idx], self.labels[idx]

>>> ds = ICDataset(data, labels)

>>> result = read_dataset(ds)
>>> len(result)  # images and labels
2
>>> np.asarray(result[0]).shape  # images
(10, 1, 3, 3)
>>> np.asarray(result[1]).shape  # labels
(10,)