def prepare_data_SingleDomainTarget():
dataloaders = {}
train_transform = data_utils.get_transform(True)
test_transform = data_utils.get_transform(False)
with open(os.path.join(cfg.DATASET.DATAROOT, 'category.txt'), 'r') as f:
classes = f.readlines()
classes = [c.strip() for c in classes]
assert(len(classes) == cfg.DATASET.NUM_CLASSES)
target = cfg.DATASET.TARGET_NAME
dataroot_T = os.path.join(cfg.DATASET.DATAROOT, target)
batch_size = cfg.TRAIN.TARGET_BATCH_SIZE
dataset_type = 'SingleDataset'
dataloaders[target] = CustomDatasetDataLoader(
dataset_root=dataroot_T, dataset_type=dataset_type,
batch_size=batch_size, transform=train_transform,
train=True, num_workers=cfg.NUM_WORKERS,
classnames=classes)
batch_size = cfg.TEST.BATCH_SIZE
dataset_type = cfg.TEST.DATASET_TYPE
test_domain = cfg.TEST.DOMAIN if cfg.TEST.DOMAIN != "" else target
dataroot_test = os.path.join(cfg.DATASET.DATAROOT, test_domain)
dataloaders['test'] = CustomDatasetDataLoader(
dataset_root=dataroot_test, dataset_type=dataset_type,
batch_size=batch_size, transform=test_transform,
train=False, num_workers=cfg.NUM_WORKERS,
classnames=classes)
return dataloaders
def prepare_data():
test_transform = data_utils.get_transform(False)
target = cfg.TEST.DOMAIN
dataroot_T = os.path.join(cfg.DATASET.DATAROOT, target)
with open(os.path.join(cfg.DATASET.DATAROOT, 'category.txt'), 'r') as f:
classes = f.readlines()
classes = [c.strip() for c in classes]
assert (len(classes) == cfg.DATASET.NUM_CLASSES)
dataloader = None
dataset_type = cfg.TEST.DATASET_TYPE
batch_size = cfg.TEST.BATCH_SIZE
dataloader = CustomDatasetDataLoader(dataset_root=dataroot_T,
dataset_type=dataset_type,
batch_size=batch_size,
transform=test_transform,
train=False,
num_workers=cfg.NUM_WORKERS,
classnames=classes)
return dataloader
def prepare_data_CAN():
dataloaders = {}
train_transform = data_utils.get_transform(True)
test_transform = data_utils.get_transform(False)
source = cfg.DATASET.SOURCE_NAME
target = cfg.DATASET.TARGET_NAME
dataroot_S = os.path.join(cfg.DATASET.DATAROOT, source)
dataroot_T = os.path.join(cfg.DATASET.DATAROOT, target)
with open(os.path.join(cfg.DATASET.DATAROOT, 'category.txt'), 'r') as f:
classes = f.readlines()
classes = [c.strip() for c in classes]
assert(len(classes) == cfg.DATASET.NUM_CLASSES)
# for clustering
batch_size = cfg.CLUSTERING.SOURCE_BATCH_SIZE
dataset_type = 'SingleDataset'
print('Building clustering_%s dataloader...' % source)
dataloaders['clustering_' + source] = CustomDatasetDataLoader(
dataset_root=dataroot_S, dataset_type=dataset_type,
batch_size=batch_size, transform=train_transform,
train=False, num_workers=cfg.NUM_WORKERS,
classnames=classes)
batch_size = cfg.CLUSTERING.TARGET_BATCH_SIZE
dataset_type = cfg.CLUSTERING.TARGET_DATASET_TYPE
print('Building clustering_%s dataloader...' % target)
dataloaders['clustering_' + target] = CustomDatasetDataLoader(
dataset_root=dataroot_T, dataset_type=dataset_type,
batch_size=batch_size, transform=train_transform,
train=False, num_workers=cfg.NUM_WORKERS,
classnames=classes)
# class-agnostic source dataloader for supervised training
batch_size = cfg.TRAIN.SOURCE_BATCH_SIZE
dataset_type = 'SingleDataset'
print('Building %s dataloader...' % source)
dataloaders[source] = CustomDatasetDataLoader(
dataset_root=dataroot_S, dataset_type=dataset_type,
batch_size=batch_size, transform=train_transform,
train=True, num_workers=cfg.NUM_WORKERS,
classnames=classes)
# initialize the categorical dataloader
dataset_type = 'CategoricalSTDataset'
source_batch_size = cfg.TRAIN.SOURCE_CLASS_BATCH_SIZE
target_batch_size = cfg.TRAIN.TARGET_CLASS_BATCH_SIZE
print('Building categorical dataloader...')
dataloaders['categorical'] = ClassAwareDataLoader(
dataset_type=dataset_type,
source_batch_size=source_batch_size,
target_batch_size=target_batch_size,
source_dataset_root=dataroot_S,
transform=train_transform,
classnames=classes,
num_workers=cfg.NUM_WORKERS,
drop_last=True, sampler='RandomSampler')
batch_size = cfg.TEST.BATCH_SIZE
dataset_type = cfg.TEST.DATASET_TYPE
test_domain = cfg.TEST.DOMAIN if cfg.TEST.DOMAIN != "" else target
dataroot_test = os.path.join(cfg.DATASET.DATAROOT, test_domain)
dataloaders['test'] = CustomDatasetDataLoader(
dataset_root=dataroot_test, dataset_type=dataset_type,
batch_size=batch_size, transform=test_transform,
train=False, num_workers=cfg.NUM_WORKERS,
classnames=classes)
return dataloaders