def test_MODEL_prediction3D(self):
nn = Neural_Network(preprocessor=self.pp3D)
nn.predict(self.sample_list3D)
for index in self.sample_list3D:
sample = self.data_io3D.sample_loader(index,
load_seg=True,
load_pred=True)
self.assertIsNotNone(sample.pred_data)
def test_MODEL_prediction_activationOutput(self):
nn = Neural_Network(preprocessor=self.pp2D)
pred_list = nn.predict(self.sample_list2D,
return_output=True,
activation_output=True)
for pred in pred_list:
self.assertIsNotNone(pred)
self.assertEqual(pred.shape, (16, 16, 3))
def test_ARCHITECTURES_UNET_standard(self):
model2D = Neural_Network(self.pp2D, architecture=UNet_standard())
model2D.predict(self.sample_list2D)
model3D = Neural_Network(self.pp3D, architecture=UNet_standard())
model3D.predict(self.sample_list3D)