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def test_MODEL_prediction2D(self):
nn = Neural_Network(preprocessor=self.pp2D)
nn.predict(self.sample_list2D)
for index in self.sample_list2D:
sample = self.data_io2D.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_MODEL_create(self):
nn2D = Neural_Network(preprocessor=self.pp2D)
self.assertIsInstance(nn2D, Neural_Network)
self.assertFalse(nn2D.three_dim)
self.assertIsNotNone(nn2D.model)
nn3D = Neural_Network(preprocessor=self.pp3D)
self.assertIsInstance(nn3D, Neural_Network)
self.assertTrue(nn3D.three_dim)
self.assertIsNotNone(nn3D.model)
def test_MODEL_create(self):
nn2D = Neural_Network(preprocessor=self.pp2D)
self.assertIsInstance(nn2D, Neural_Network)
self.assertFalse(nn2D.three_dim)
self.assertIsNotNone(nn2D.model)
nn3D = Neural_Network(preprocessor=self.pp3D)
self.assertIsInstance(nn3D, Neural_Network)
self.assertTrue(nn3D.three_dim)
self.assertIsNotNone(nn3D.model)
def test_MODEL_validation3D(self):
nn = Neural_Network(preprocessor=self.pp3D)
history = nn.evaluate(self.sample_list3D[0:4], self.sample_list3D[4:6],
epochs=3)
self.assertIsNotNone(history)
# Initialize Dictionary IO Interface
io_interface = Dictionary_interface(self.dataset, classes=3,
three_dim=False)
# Initialize temporary directory
self.tmp_dir = tempfile.TemporaryDirectory(prefix="tmp.miscnn.")
tmp_batches = os.path.join(self.tmp_dir.name, "batches")
# Initialize Data IO
self.data_io = Data_IO(io_interface,
input_path=os.path.join(self.tmp_dir.name),
output_path=os.path.join(self.tmp_dir.name),
batch_path=tmp_batches, delete_batchDir=False)
# Initialize Preprocessor
self.pp = Preprocessor(self.data_io, batch_size=2,
data_aug=None, analysis="fullimage")
# Initialize Neural Network
self.model = Neural_Network(self.pp)
# Get sample list
self.sample_list = self.data_io.get_indiceslist()
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_loading(self):
nn = Neural_Network(preprocessor=self.pp3D)
model_path = os.path.join(self.tmp_dir3D.name, "my_model.hdf5")
nn.dump(model_path)
nn_new = Neural_Network(preprocessor=self.pp3D)
nn_new.load(model_path)
def test_MODEL_resetWeights(self):
nn = Neural_Network(preprocessor=self.pp3D)
nn.reset_weights()