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/*
* Copyright (c) 2018 Samsung Electronics Co., Ltd. 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
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/**
* @file InferenceInterface.h
* @brief This file contains class for running the actual inference model
* @ingroup COM_AI_RUNTIME
*/
#ifndef __TFLITE_CLASSIFY_INFERENCE_INTERFACE_H__
#define __TFLITE_CLASSIFY_INFERENCE_INTERFACE_H__
#include "tflite/ext/kernels/register.h"
#include "tensorflow/contrib/lite/model.h"
#include "tflite/InterpreterSession.h"
#include "tflite/NNAPISession.h"
#include <iostream>
#include <string>
/**
* @brief Class to define a inference interface for recognizing data
*/
class InferenceInterface
{
public:
/**
* @brief Construct a new InferenceInterface object with parameters
* @param[in] model_file The filepath of the model FlatBuffer protocol buffer
* @param[in] use_nnapi The flag to distinguish between TfLite interpreter and NNFW runtime
*/
InferenceInterface(const std::string &model_file, const bool use_nnapi);
/**
* @brief Destructor an InferenceInterface object
*/
~InferenceInterface();
/**
* @brief Copy the input data into model
* @param[in] input_name The label of the image input node
* @param[in] data The actual data to be copied into input tensor
* @param[in] batch The number of batch size
* @param[in] height The number of height size
* @param[in] width The number of width size
* @param[in] channel The number of channel size
* @return N/A
*/
void feed(const std::string &input_name, const std::vector<float> &data, const int batch,
const int height, const int width, const int channel);
/**
* @brief Run the inference call
* @param[in] output_name The label of the output node
* @return N/A
*/
void run(const std::string &output_name);
/**
* @brief Copy the output tensor back into the output array
* @param[in] output_node The label of the output node
* @param[in] outputs The output data array
* @return N/A
*/
void fetch(const std::string &output_name, std::vector<float> &outputs);
/**
* @brief Get tensor size
* @param[in] name The label of the node
* @result The size of tensor
*/
int getTensorSize(const std::string &name);
private:
std::unique_ptr<tflite::Interpreter> _interpreter;
std::unique_ptr<tflite::FlatBufferModel> _model;
std::shared_ptr<nnfw::tflite::Session> _sess;
};
#endif // __TFLITE_CLASSIFY_INFERENCE_INTERFACE_H__
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