predict.py 文件源码

def predict_mlp(image_file):
    image = cv2.imdecode(np.fromstring(image_file.read(), np.uint8), cv2.CV_LOAD_IMAGE_UNCHANGED)
    if image is not None:
        features = np.array([image_to_feature_vector(image)])
        loaded_model = pickle.load(open(MODEL_PATH + "/mlp_model.sav", 'rb'))
        scaler = pickle.load(open(MODEL_PATH + "/scaler_model.sav", "rb"))
        features = scaler.transform(features)

        return loaded_model.predict(features)[0]
    else:
        raise "Failed"