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/**
* Copyright (c) 2022 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.
*/
#ifndef __OBJECT_DETECTION_H__
#define __OBJECT_DETECTION_H__
#include <queue>
#include <thread>
#include <mutex>
#include <atomic>
#include <mv_common.h>
#include <mv_inference_type.h>
#include "mv_private.h"
#include "EngineConfig.h"
#include "inference_engine_common_impl.h"
#include "Inference.h"
#include "object_detection_type.h"
#include "MetaParser.h"
#include "ObjectDetectionParser.h"
#include "MvMlConfig.h"
#include "MvMlPreprocess.h"
#include "IObjectDetection.h"
#include "AsyncManager.h"
namespace mediavision
{
namespace machine_learning
{
template<typename T> class ObjectDetection : public IObjectDetection
{
private:
ObjectDetectionTaskType _task_type { ObjectDetectionTaskType::OBJECT_DETECTION_TASK_NONE };
std::unique_ptr<AsyncManager<T, ObjectDetectionResult> > _async_manager;
ObjectDetectionResult _current_result;
void loadLabel();
void getEngineList();
void getDeviceList(const std::string &engine_type);
void configurePreprocess();
std::shared_ptr<MetaInfo> getInputMetaInfo();
protected:
std::unique_ptr<mediavision::inference::Inference> _inference;
std::shared_ptr<Config> _config;
std::vector<std::string> _labels;
std::vector<std::string> _valid_backends;
std::vector<std::string> _valid_devices;
Preprocess _preprocess;
void getOutputNames(std::vector<std::string> &names);
void getOutputTensor(std::string target_name, std::vector<float> &tensor);
void inference(std::vector<std::vector<T> > &inputVectors);
virtual ObjectDetectionResult &result() = 0;
public:
explicit ObjectDetection(ObjectDetectionTaskType task_type, std::shared_ptr<Config> config);
virtual ~ObjectDetection() = default;
void preDestroy() override;
ObjectDetectionTaskType getTaskType() override;
void setUserModel(std::string model_file, std::string meta_file, std::string label_file);
void setEngineInfo(std::string engine_type_name, std::string device_type_name) override;
unsigned int getNumberOfEngines() override;
const std::string &getEngineType(unsigned int engine_index) override;
unsigned int getNumberOfDevices(const std::string &engine_type) override;
const std::string &getDeviceType(const std::string &engine_type, unsigned int device_index) override;
void configure() override;
void prepare() override;
void perform(mv_source_h &mv_src) override;
void performAsync(ObjectDetectionInput &input) override;
ObjectDetectionResult &getOutput() override;
ObjectDetectionResult &getOutputCache() override;
};
} // machine_learning
} // mediavision
#endif
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