65 lines
2.0 KiB
C
65 lines
2.0 KiB
C
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/**
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* 车号属性第一步推理前预处理
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* */
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#ifndef TRAINSTEPONEENGINE_H
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#define TRAINSTEPONEENGINE_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 "yolov5_clearity_inference.h"
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class TrainStep1InferenceEngine : public ai_matrix::EngineBase
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{
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public:
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TrainStep1InferenceEngine();
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~TrainStep1InferenceEngine();
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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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//过滤无效信息
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void filterInvalidInfo(std::vector<stDetection> &vecInferenceResult,
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std::shared_ptr<VTrainStep1Data> &pVTrainStep1Data);
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void getMaxScoreResult(std::vector<stDetection> &vecInferenceResult);
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void getTargetType(SingleData &singleData);
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std::string strPort_;
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std::string strPort0_;
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ai_matrix::ModelConfig modelConfig_;
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ai_matrix::DataSourceConfig dataSourceConfig_;
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ai_matrix::IdentifyConfig identifyConfig_;
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YoloV5ClearityInference yolov5model;
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const char* INPUT_BLOB_NAME = "images"; //输入层名称
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const char* OUTPUT_BLOB_NAME = "output"; //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 = STEP1_INPUT_W;
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unsigned int model_height = STEP1_INPUT_H;
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unsigned int clear_num = STEP1_CLEAR_NUM;
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unsigned int class_num = STEP1_CLASS_NUM;
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unsigned int input_size = STEP1_INPUT_SIZE;
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unsigned int output_size = STEP1_OUTPUT_SIZE;
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unsigned int det_size = STEP1_CLASS_NUM + STEP1_CLEAR_NUM + 5;
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unsigned int batch_size = STEP1_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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YoloV5ClearityModelInfo modelinfo;
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// std::map<int, ai_matrix::DataSourceConfig> mapDataSourceCfg_; //[key-数据源id, value-数据源参数配置信息]
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// std::map<int, int> mapSameSideFlatcarSid_; //[key-数据源id, value-同侧识别平车数据源id]
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};
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ENGINE_REGIST(TrainStep1InferenceEngine)
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#endif
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