def test_MODEL_predictionAugmentated_2D(self):
data_aug = Data_Augmentation()
pp = Preprocessor(self.data_io2D,
batch_size=2,
data_aug=data_aug,
analysis="fullimage")
nn = Neural_Network(preprocessor=pp)
for sample in self.sample_list2D:
predictions = nn.predict_augmentated(sample)
self.assertEqual(len(predictions), 2)
for pred in predictions:
self.assertEqual(pred.shape, (16, 16, 3))
def test_MODEL_predictionAugmentated_3D(self):
data_aug = Data_Augmentation()
pp = Preprocessor(self.data_io3D,
batch_size=1,
patch_shape=(8, 8, 8),
data_aug=data_aug,
analysis="patchwise-crop")
nn = Neural_Network(preprocessor=pp,
architecture=UNet_standard(depth=2))
for sample in self.sample_list3D:
predictions = nn.predict_augmentated(sample)
self.assertEqual(len(predictions), 3)
for pred in predictions:
self.assertEqual(pred.shape, (16, 16, 16, 3))