/************************************************************************* * Copyright (C) [2019] by Cambricon, Inc. All rights reserved * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL * THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. *************************************************************************/ #ifndef MODULES_INFERENCE_INCLUDE_PREPROC_HPP_ #define MODULES_INFERENCE_INCLUDE_PREPROC_HPP_ /** * \file preproc.hpp * * This file contains a declaration of class Preproc */ #include #include #include #include #include #include "easyinfer/model_loader.h" #include "cnstream_frame.hpp" #include "cnstream_frame_va.hpp" #include "reflex_object.h" namespace cnstream { /** * @class Preproc * * @brief Preproc is the base class of neural network preprocessing for inference module. */ class Preproc : virtual public ReflexObjectEx { public: /** * @brief Destructs an object. * * @return No return value. */ virtual ~Preproc() {} /** * @brief Creates a preprocess object with the given preprocess's class name. * * @param[in] proc_name The preprocess class name. * * @return Returns the pointer to preprocess object. */ static Preproc* Create(const std::string& proc_name); /** * @brief Initializes preprocessing parameters. * * @param[in] params The preprocessing parameters. * * @return Returns ture for success, otherwise returns false. **/ virtual bool Init(const std::unordered_map ¶ms) { return true; } /** * @brief Executes preprocess on neural network inputs. * * @param[out] net_inputs Neural network inputs. * @param[in] model Model information including input shape and output shape. * @param[in] package Smart pointer of ``CNFrameInfo`` which stores origin data. * * @return Returns 0 if successful, otherwise returns -1. */ virtual int Execute(const std::vector& net_inputs, const std::shared_ptr& model, const CNFrameInfoPtr& package) = 0; }; // class Preproc /** * @class ObjPreproc * * @brief ObjPreproc is the base class of preprocess for object. */ class ObjPreproc : virtual public ReflexObjectEx { public: /** * @brief Destructs an object. * * @return No return value. */ virtual ~ObjPreproc() {} /** * @brief Creates a preprocess object with the given preprocess's class name. * * @param[in] proc_name The preprocess class name. * * @return Returns the pointer to preprocess object. */ static ObjPreproc* Create(const std::string& proc_name); /** * @brief Initializes preprocessing parameters. * * @param[in] params The preprocessing parameters. * * @return Returns ture for success, otherwise returns false. **/ virtual bool Init(const std::unordered_map ¶ms) { return true; } /** * @brief Executes preprocess on neural network inputs. * * @param[out] net_inputs Neural network inputs. * @param[in] model Model information including input shape and output shape. * @param[in] finfo Smart pointer of ``CNFrameInfo`` which stores origin data. * @param[in] obj The deduced object information. * * @return Returns 0 if successful, otherwise returns -1. */ virtual int Execute(const std::vector& net_inputs, const std::shared_ptr& model, const CNFrameInfoPtr& finfo, const std::shared_ptr& pobj) = 0; }; // class ObjPreproc } // namespace cnstream #endif // ifndef MODULES_INFERENCE_INCLUDE_PREPROC_HPP_