(trivial) skip loading model if not exist

loader.py

@@ -108,7 +108,6 @@ def train(samples):
     # NOTE: Automatically continue training the existing model
     # Otherwise, starts a new model if there is no model file found.
     cnn = train_model(
-      # TAOTODO: Should load the correct model
       path_model if os.path.isfile(path_model) else None,
       trainsetX,
       trainsetY,

model/core.py

@@ -25,8 +25,8 @@
 def train_model(path, X, y, X_, y_, image_dim, final_vec_dim, epoch, batch_size):
 
   # Create a new CNN
-  if path is None:
-    print(colored('Creating a new CNN.','green'))
+  if path is None or not os.path.isfile(path + '0'):
+    print(colored('Creating a new CNN.','cyan'))
     cnn = CNN(image_dim, final_vec_dim) 
   else:
     print(colored('Loading model from : {0}'.format(path),'green'))