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from torch.utils.data import DataLoader
from torchio.data import ImageSampler
from torchio import ImagesDataset, Queue, DATA
from torchio.utils import create_dummy_dataset
from ..utils import TorchioTestCase
class TestQueue(TorchioTestCase):
"""Tests for `queue` module."""
def setUp(self):
super().setUp()
self.subjects_list = create_dummy_dataset(
num_images=10,
size_range=(10, 20),
directory=self.dir,
suffix='.nii',
force=False,
)
def test_queue(self):
subjects_dataset = ImagesDataset(self.subjects_list)
queue_dataset = Queue(
subjects_dataset,
max_length=6,
samples_per_volume=2,
patch_size=10,
sampler_class=ImageSampler,
num_workers=0,
verbose=True,
_ = str(queue_dataset)
batch_loader = DataLoader(queue_dataset, batch_size=4)
for batch in batch_loader:
_ = batch['one_modality'][DATA]
_ = batch['segmentation'][DATA]
fepegar /
torchio
