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/*
* Copyright (c) 2022 Arm Limited. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*
* 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.
*/
#ifndef BASE_PROCESSING_HPP
#define BASE_PROCESSING_HPP
#include "Model.hpp"
namespace arm {
namespace app {
/**
* @brief Base class exposing pre-processing API.
* Use cases should provide their own PreProcessing class that inherits from this one.
* All steps required to take raw input data and populate tensors ready for inference
* should be handled.
*/
class BasePreProcess {
public:
virtual ~BasePreProcess() = default;
/**
* @brief Should perform pre-processing of 'raw' input data and load it into
* TFLite Micro input tensors ready for inference
* @param[in] input Pointer to the data that pre-processing will work on.
* @param[in] inputSize Size of the input data.
* @return true if successful, false otherwise.
**/
virtual bool DoPreProcess(const void* input, size_t inputSize) = 0;
};
/**
* @brief Base class exposing post-processing API.
* Use cases should provide their own PostProcessing class that inherits from this one.
* All steps required to take inference output and populate results vectors should be handled.
*/
class BasePostProcess {
public:
virtual ~BasePostProcess() = default;
/**
* @brief Should perform post-processing of the result of inference then populate
* populate result data for any later use.
* @return true if successful, false otherwise.
**/
virtual bool DoPostProcess() = 0;
};
} /* namespace app */
} /* namespace arm */
#endif /* BASE_PROCESSING_HPP */