Building a Keras + deep learning REST API（三部曲之一）

一、基本环境

)

    image = imagenet_utils.preprocess_input(image)

    , ))

            ]:

                r = {"label": label, "probability": float(prob)}

                data["predictions"].append(r)

            # indicate that the request was a success

            data["success"] = True

    # return the data dictionary as a JSON response

    return flask.jsonify(data)