def predict(facade_data):
  features = fe.processSample(facade_data)
  X = normalizer.transform(np.array([features]))
  pred = clf.predict(X)
  return pred
def predict(facade_data):
  features = fe.processSample(facade_data)
  X = np.array([features])
  pred = clf.predict(X)[0].item()
  return pred