only resnet50

classifier/Resnet50.py

@@ -29,10 +29,7 @@ class Resnet50(NetworkBase):
         if shouldSave:
             base_model.save('data/resnet_50_base_model.h5')
 
-        x = Flatten()(base_model.output)
-        x = Dropout(0.4)(x)
-        x = Dense(128, activation='relu')(x)
-        x = Dropout(0.4)(x)
+        x = GlobalAveragePooling2D(base_model.output)
         out = Dense(self.NUM_CLASSES, activation='softmax', name='probs')(x)
 
         model = Model(base_model.input, out)