fixed bug with model which affected performance. Results should be improved

Former-commit-id: 12ea2fe

Author: PolarBean

DeepSlice/neural_network/neural_network.py

@@ -39,12 +39,11 @@ def initialise_network(xception_weights: str, weights: str) -> Sequential:
     base_model = Xception(include_top=True, weights=xception_weights)
     base_model._layers.pop()
     base_model._layers.pop()
-    inputs = Input(shape=(299, 299, 3))
-    base_model_layer = base_model(inputs, training=True)
-    dense1_layer = Dense(256, activation="relu")(base_model_layer)
-    dense2_layer = Dense(256, activation="relu")(dense1_layer)
-    output_layer = Dense(9, activation="linear")(dense2_layer)
-    model = Model(inputs=inputs, outputs=output_layer)
+    model = Sequential()
+    model.add(base_model)
+    model.add(Dense(256, activation="relu"))
+    model.add(Dense(256, activation="relu"))
+    model.add(Dense(9, activation="linear"))
     if weights != None:
         model.load_weights(weights)
     return model