VTrain/engine/Step1InferenceEngine/ContainerStep1InferenceEngi...

65 lines
1.9 KiB
C++

/**
* 集装箱第一步推理前预处理
* */
#ifndef CONTAINERSTEP1INFERENCEENGINE_H
#define CONTAINERSTEP1INFERENCEENGINE_H
#include "AppCommon.h"
#include "EngineBase.h"
#include "EngineFactory.h"
#include "yolov5_clearity_inference.h"
class ContainerStep1InferenceEngine : public ai_matrix::EngineBase
{
public:
ContainerStep1InferenceEngine();
~ContainerStep1InferenceEngine();
APP_ERROR Init() override;
APP_ERROR DeInit() override;
APP_ERROR Process() override;
private:
//初始化识别模型
APP_ERROR initModel();
//过滤无效信息
void filterInvalidInfo(std::vector<stDetection> &vecInferenceResult,
std::shared_ptr<VTrainStep1Data> &pVTrainStep1Data);
void getMaxScoreResult(std::vector<stDetection> &vecInferenceResult);
void getTargetType(SingleData &singleData);
std::string strPort0_;
ai_matrix::ModelConfig modelConfig_;
ai_matrix::DataSourceConfig dataSourceConfig_;
ai_matrix::IdentifyConfig identifyConfig_;
YoloV5ClearityInference yolov5model;
bool bStepOneImgSaveFlag_;
const char* INPUT_BLOB_NAME = "images"; //输入层名称
const char* OUTPUT_BLOB_NAME = "output"; //输出层名称
unsigned int img_width = IMAGE_WIDTH;
unsigned int img_height = IMAGE_HEIGHT;
unsigned int model_width = STEP1_INPUT_W;
unsigned int model_height = STEP1_INPUT_H;
unsigned int clear_num = STEP1_CLEAR_NUM;
unsigned int class_num = STEP1_CLASS_NUM;
unsigned int input_size = STEP1_INPUT_SIZE;
unsigned int output_size = STEP1_OUTPUT_SIZE;
unsigned int det_size = STEP1_CLASS_NUM + STEP1_CLEAR_NUM + 5;
unsigned int batch_size = STEP1_BATCH_SIZE;
float score_threshold = STEP1_SCORE_THRESH;
float nms_threshold = STEP1_NMS_THRESH;
YoloV5ClearityModelInfo modelinfo;
};
ENGINE_REGIST(ContainerStep1InferenceEngine)
#endif