generated from zhangwei/Train_Identify
92 lines
4.1 KiB
C++
92 lines
4.1 KiB
C++
/**
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* 选取最优结果Engine
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* */
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#ifndef SELECTBESTENGINE_H
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#define SELECTBESTENGINE_H
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#include "AppCommon.h"
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#include "MyYaml.h"
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#include "EngineBase.h"
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#include "EngineFactory.h"
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class SelectBestEngine : public ai_matrix::EngineBase
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{
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public:
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SelectBestEngine();
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~SelectBestEngine();
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APP_ERROR Init() override;
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APP_ERROR DeInit() override;
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APP_ERROR Process() override;
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private:
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//初始化车号参数信息
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void InitNumParam();
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//初始化属性参数信息
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void InitProParam();
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//初始化车头参数信息
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void InitHeadParam();
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//初始化参数信息
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void InitParam();
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//获取最优长度
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int GetBestLength(std::vector<TransInfo> &vecAllTransInfo, TargetMaxLen iMaxLen);
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//获取最优结果
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std::string GetBest(std::vector<TransInfo> &vecAllTransInfo, TargetMaxLen iMaxLen);
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//车号数据加入到待选优集合中
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void NumAddSelectBestMap(std::shared_ptr<ProcessData> pProcessData, TransSubData &transSubData);
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//属性数据加入到待选优集合中
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void ProAddSelectBestMap(std::shared_ptr<ProcessData> pProcessData, TransSubData &transSubData);
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//车头数据加入到待选优集合中
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void HeadAddSelectBestMap(std::shared_ptr<ProcessData> pProcessData, TransSubData &transSubData);
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//汇总车头
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bool GetHeadBest(std::shared_ptr<ProcessData> pProcessData);
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void GetNumBest(TrainNum &trainNum, std::shared_ptr<ProcessData> pProcessData);
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void GetProBest(TrainPro &trainPro, std::shared_ptr<ProcessData> pProcessData);
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//汇总车厢
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void GetTrainBest(std::shared_ptr<ProcessData> pProcessData);
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//拷贝最优图片到最优路径下
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void CopyBestImgToBestPath(const std::shared_ptr<Train> &pTrain);
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//push数据到队列，队列满时则休眠一段时间再push
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void PushData(const std::string &strPort, const std::shared_ptr<Train> &pTrain);
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std::string strPort0_;
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std::string strPort1_;
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int iSelectBestMode_; //选优模式
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std::string strResultPath_;
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std::string strBestPath_;
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int iNumIndex_ = 1; //当前车号所属车厢号
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int iProIndex_ = 1; //当前属性所属车厢号
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std::map<int, std::vector<TransInfo>> mapNumInfo_; //车号待选优集合 key [0:车型; 1:编号]
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float fMaxScoreSumNum_; //当前车厢车号最高得分
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std::string strBestNumImg_; //当前车厢车号最高分的图片名
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uint64_t i64TimeStampNum_ = 0; //当前车厢车号最高分的图片时间戳
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Step1Location step1LocationBestNum_; //当前车厢车号最高分的图片大框坐标
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std::map<int, int> mapTrainTypeId_; //车厢类型ID集合 [key:车厢类型ID; value:识别到次数] (标识哪种类型的车，根据车号大框区分)
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uint32_t iDataSourceNum_ = 0;
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std::map<int, std::vector<TransInfo>> mapProInfo_; //属性待选优集合 key [0:载重; 1:自重; 2:容积; 3:换长; 4:容量记表]
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float fMaxScoreSumPro_; //当前车厢属性最高得分
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std::string strBestProImg_; //当前车厢属性最高分的图片名
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uint64_t i64TimeStampPro_ = 0; //当前车厢属性最高分的图片时间戳
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Step1Location step1LocationBestPro_; //当前车厢属性最高分的图片大框坐标
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uint32_t iDataSourcePro_ = 0;
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std::map<int, std::vector<TransInfo>> mapHeadInfo_; //车头待选优集合 key [0:车头型号; 1:车头编号]
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float fMaxScoreSumHead_; //车头最高得分
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std::string strBestHeadImg_; //车头最高分的图片名
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uint64_t i64TimeStampHead_ = 0; //车头最高分的图片时间戳
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Step1Location step1LocationBestHead_; //车头最高分的图片大框坐标
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uint32_t iDataSourceHead_ = 0;
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std::map<int, bool> mapDataSourceIsEnd_; //[key-数据源id, value-数据是否结束]
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};
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ENGINE_REGIST(SelectBestEngine)
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#endif
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