def _download_and_prepare(self, dataset_dir, scratch_dir, split):
train = split == "train"
def download_fcn(download_dir):
return torchvision.datasets.FashionMNIST(download_dir,
train=train,
download=True)
get_class_labels_fcn = _parse_classification_labels
sample_parser = foud.ImageClassificationSampleParser()
return _download_and_prepare(
dataset_dir,
scratch_dir,
download_fcn,
get_class_labels_fcn,
sample_parser,
)
def _download_and_prepare(self, dataset_dir, _, split):
# Ensure that the source files have been manually downloaded
foui.ensure_imagenet_manual_download(dataset_dir, split)
if split == "validation":
_split = "val"
else:
_split = split
def download_fcn(_):
return torchvision.datasets.ImageNet(dataset_dir, split=_split)
get_class_labels_fcn = _parse_classification_labels
sample_parser = foud.ImageClassificationSampleParser()
return _download_and_prepare(
dataset_dir,
None,
download_fcn,
get_class_labels_fcn,
sample_parser,
)
