# SVIRO #################################################################
def download_sviro(data_dir):
# Original URL: https://sviro.kl.dfki.de
full_path = stage_path(data_dir, "sviro")
download_and_extract(
"https://sviro.kl.dfki.de/?wpdmdl=1731",
os.path.join(data_dir, "sviro_grayscale_rectangle_classification.zip"))
os.rename(os.path.join(data_dir, "SVIRO_DOMAINBED"), full_path)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Download datasets')
parser.add_argument('--data_dir', type=str, required=True)
args = parser.parse_args()
# download_mnist(args.data_dir)
# download_pacs(args.data_dir)
# download_office_home(args.data_dir)
# download_domain_net(args.data_dir)
# download_vlcs(args.data_dir)
# download_terra_incognita(args.data_dir)
# download_sviro(args.data_dir)
Camelyon17Dataset(root_dir=args.data_dir, download=True)
# FMoWDataset(root_dir=args.data_dir, download=True)
def __init__(self, root, test_envs, hparams):
dataset = Camelyon17Dataset(root_dir=root)
super().__init__(dataset, "hospital", test_envs,
hparams['data_augmentation'], hparams)
def get_dataset(dataset, version=None, **dataset_kwargs):
"""
Returns the appropriate WILDS dataset class.
Input:
dataset (str): Name of the dataset
version (str): Dataset version number, e.g., '1.0'.
Defaults to the latest version.
dataset_kwargs: Other keyword arguments to pass to the dataset constructors.
Output:
The specified WILDSDataset class.
"""
if version is not None:
version = str(version)
if dataset not in wilds.supported_datasets:
raise ValueError(
f'The dataset {dataset} is not recognized. Must be one of {wilds.supported_datasets}.'
)
if dataset == 'amazon':
from wilds.datasets.amazon_dataset import AmazonDataset
return AmazonDataset(version=version, **dataset_kwargs)
elif dataset == 'camelyon17':
from wilds.datasets.camelyon17_dataset import Camelyon17Dataset
return Camelyon17Dataset(version=version, **dataset_kwargs)
elif dataset == 'celebA':
from wilds.datasets.celebA_dataset import CelebADataset
return CelebADataset(version=version, **dataset_kwargs)
elif dataset == 'civilcomments':
from wilds.datasets.civilcomments_dataset import CivilCommentsDataset
return CivilCommentsDataset(version=version, **dataset_kwargs)
elif dataset == 'iwildcam':
if version == '1.0':
from wilds.datasets.archive.iwildcam_v1_0_dataset import IWildCamDataset
else:
from wilds.datasets.iwildcam_dataset import IWildCamDataset
return IWildCamDataset(version=version, **dataset_kwargs)
elif dataset == 'waterbirds':
from wilds.datasets.waterbirds_dataset import WaterbirdsDataset
return WaterbirdsDataset(version=version, **dataset_kwargs)
elif dataset == 'yelp':
from wilds.datasets.yelp_dataset import YelpDataset
return YelpDataset(version=version, **dataset_kwargs)
elif dataset == 'ogb-molpcba':
from wilds.datasets.ogbmolpcba_dataset import OGBPCBADataset
return OGBPCBADataset(version=version, **dataset_kwargs)
elif dataset == 'poverty':
if version == '1.0':
from wilds.datasets.archive.poverty_v1_0_dataset import PovertyMapDataset
else:
from wilds.datasets.poverty_dataset import PovertyMapDataset
return PovertyMapDataset(version=version, **dataset_kwargs)
elif dataset == 'fmow':
if version == '1.0':
from wilds.datasets.archive.fmow_v1_0_dataset import FMoWDataset
else:
from wilds.datasets.fmow_dataset import FMoWDataset
return FMoWDataset(version=version, **dataset_kwargs)
elif dataset == 'bdd100k':
from wilds.datasets.bdd100k_dataset import BDD100KDataset
return BDD100KDataset(version=version, **dataset_kwargs)
elif dataset == 'py150':
from wilds.datasets.py150_dataset import Py150Dataset
return Py150Dataset(version=version, **dataset_kwargs)
elif dataset == 'sqf':
from wilds.datasets.sqf_dataset import SQFDataset
return SQFDataset(version=version, **dataset_kwargs)