for testing and deploying your application
for finding and fixing issues
for empowering human code reviews
import torch
import torchio
from torchio.data import WeightedSampler
from ...utils import TorchioTestCase
class TestWeightedSampler(TorchioTestCase):
"""Tests for `WeightedSampler` class."""
def test_label_sampler(self):
sample = self.get_sample((7, 7, 7))
sampler = WeightedSampler(5, 'prob')
patch = next(iter(sampler(sample)))
self.assertEqual(tuple(patch['index_ini']), (1, 1, 1))
def get_sample(self, image_shape):
t1 = torch.rand(*image_shape)
prob = torch.zeros_like(t1)
prob[3, 3, 3] = 1
subject = torchio.Subject(
t1=torchio.Image(tensor=t1),
prob=torchio.Image(tensor=prob),
)
sample = torchio.ImagesDataset([subject])[0]
return sample
fepegar /
torchio
