deeper FC Layers

network/Resnet50.py

@@ -32,13 +32,13 @@ class Resnet50(NetworkBase):
         for layer in base_model.layers:
             layer.trainable = False
 
-        x = GlobalAveragePooling2D()(base_model.output)
-        x = Dropout(0.5)(x)
+        #x = GlobalAveragePooling2D()(base_model.output)
+        x = Flatten()(base_model.output)
+        x = Dropout(0.3)(x)
+        x = Dense(128)(x)
+        x = Dropout(0.3)(x)
         out = Dense(self.NUM_CLASSES, activation='softmax', name='probs')(x)
 
         model = Model(base_model.input, out)
-        
-        #for layer in model.layers[:-39]:
-        #    layer.trainable = False
 
         return model