def test_should_produce_a_multi_modality_input_with_one_channel_train_test(
self):
train_dataset, test_dataset, reconstruction_dataset, reconstruction_augmented_dataset, csv = MRBrainSSegmentationFactory.create_train_test(
self.DATA_PATH, [Modality.T1, Modality.T2_FLAIR], 0, 0.3)
sample = train_dataset[0]
assert_that(sample.x.size(), is_(torch.Size([2, 32, 32, 32])))
plt.imshow(sample.x[0, 16, :, :], cmap="gray")
plt.show()
plt.imshow(sample.x[1, 16, :, :], cmap="gray")
plt.show()
plt.imshow(sample.y[0, 16, :, :], cmap="gray")
plt.show()
def test_should_create_multi_modality_train_test_datasets(self):
train_dataset, test_dataset, reconstruction_dataset, reconstruction_augmented_dataset, csv = MRBrainSSegmentationFactory.create_train_test(
self.DATA_PATH, [Modality.T1, Modality.T2_FLAIR], 0, 0.3)
assert_that(train_dataset, instance_of(Dataset))
assert_that(test_dataset, instance_of(Dataset))
assert_that(reconstruction_dataset, instance_of(Dataset))