87 lines
2.5 KiB
C++
87 lines
2.5 KiB
C++
/**
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* 动态检测推理engine
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* */
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#ifndef MOVEENGINE_H
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#define MOVEENGINE_H
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#include "AppCommon.h"
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#include "EngineBase.h"
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#include "EngineFactory.h"
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#include "yolov8_inference.h"
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#define STEP0_INPUT_SIZE STEP0_BATCH_SIZE*STEP0_INPUT_CHANNEL*STEP0_INPUT_W*STEP0_INPUT_H
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#define STEP0_OUTPUT_ARRAY 5
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#define STEP0_OUTPUT_SIZE 1 * STEP0_OUTPUT_ARRAY * 2 // BOX
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//#define STEP0_CLEAR_NUM 0
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//#define STEP0_CLASS_NUM 5
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class MoveEngine : public ai_matrix::EngineBase
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{
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public:
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MoveEngine();
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~MoveEngine();
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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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//初始化识别模型
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APP_ERROR InitModel();
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//获取模型配置
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APP_ERROR ReadModelInfo();
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//参数初始化
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void InitParam();
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//使用单device处理
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void SingleDeviceProcess(std::shared_ptr<ProcessData> pProcessData, int iType);
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std::string intTrainStage_2_str(int iTrainStage);
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ai_matrix::ModelConfig modelConfig_;
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ai_matrix::IdentifyConfig identifyConfig_;
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ai_matrix::BaseConfig baseConfig_;
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std::string strPort0_;
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std::string strPort1_;
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YoloV8Inference yolov8model;
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int iStepInter_ = 0; //(0:不识别; 1:开始识别; 2:结束识别)
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std::map<int, int> mapMoveDataNO_ = {{0,1}, {1,1}}; //动态检测数据编号
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int iType[2] = {MONITOR_MODEL_INIT_STATE,MONITOR_MODEL_INIT_STATE};
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bool bHaveTrain_[2] = {false, false};
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int iHasTrainNum_ = 0; //有车的图象数
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std::string strTrainDate_;
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std::string strTrainTime_;
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std::string strTrainName_;
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ai_matrix::DataSourceConfig dataSourceConfig_;
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std::string INPUT_BLOB_NAME = "images"; // deploy文件中定义的输入层名称
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std::string OUTPUT_BLOB_NAME = "output0"; // deploy文件中定义的输出层名称
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unsigned int img_width = IMAGE_WIDTH;
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unsigned int img_height = IMAGE_HEIGHT;
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unsigned int model_width = STEP0_INPUT_W;
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unsigned int model_height = STEP0_INPUT_H;
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// unsigned int clear_num = STEP0_CLEAR_NUM;
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// unsigned int class_num = STEP0_CLASS_NUM;
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unsigned int input_size = STEP0_INPUT_SIZE;
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unsigned int output_size = STEP0_OUTPUT_SIZE;
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// unsigned int det_size = STEP0_CLASS_NUM + STEP0_CLEAR_NUM + 5;
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unsigned int batch_size = STEP0_BATCH_SIZE;
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float score_threshold = STEP1_SCORE_THRESH;
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float nms_threshold = STEP1_NMS_THRESH;
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YoloV5ModelInfo modelinfo;
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std::queue<std::shared_ptr<ProcessData>> queProcessData_;
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bool getIsHaveTrain();
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bool isNewTrain();
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};
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ENGINE_REGIST(MoveEngine)
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#endif
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