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