ImageRecognition/ClassifyDectect.h

#include<iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui_c.h>
#include <iostream>
#include <vector>
#include <algorithm>
#include <cstdlib>
#include <fstream>
//#include "MeterRead.h"

using namespace std;

//using namespace cv::dnn;
#define YOLO_P6 false //是否使用P6模型

struct Output {
	int id;             //结果类别id
	float confidence;   //结果置信度
	cv::Rect box;       //矩形框
};

class ClassifyDectect {
public:
	ClassifyDectect() {
	}
	~ClassifyDectect() {}
	bool Init(bool isCuda);
	bool Detect(cv::Mat& SrcImg, std::vector<Output>& output);
	void drawPred(cv::Mat& img, std::vector<Output> result);
	void modifyConfidenceParameter(float boxThreshold, float classThreshold, float nmsThreshold);

private:
	 cv::dnn::Net net;

#if(defined YOLO_P6 && YOLO_P6==true)
	const float netAnchors[4][6] = { { 19,27, 44,40, 38,94 },{ 96,68, 86,152, 180,137 },{ 140,301, 303,264, 238,542 },{ 436,615, 739,380, 925,792 } };

	const int netWidth = 1280;  //ONNX图片输入宽度
	const int netHeight = 1280; //ONNX图片输入高度

	const int strideSize = 4;  //stride size
#else
	const float netAnchors[3][6] = { { 10,13, 16,30, 33,23 },{ 30,61, 62,45, 59,119 },{ 116,90, 156,198, 373,326 } };

	const int netWidth = 640;   //ONNX图片输入宽度
	const int netHeight = 640;  //ONNX图片输入高度

	const int strideSize = 3;   //stride size
#endif // YOLO_P6

	const float netStride[4] = { 8, 16.0,32,64 };

	float boxThreshold = 0.35;
	float classThreshold = 0.35;

	float nmsThreshold = 0.55;
	float nmsScoreThreshold = boxThreshold * classThreshold;
public:
	const std::vector<std::string> className = {
			   "disconnector",
			   "oil_level",
			   "meter",
			   "changeover_switch",
			   "pressplate",
			   "disconnector_state",
			   "light",
			   "air_switch",
			   "character",
			   "indoor_disconnector",
			   "triangle_disconnector",
			   "electron_plate",
			   "contact",
			   "instructions",
			   "operating_handle",
			   "person"
			   };
	const std::string instructionsName = "instructions";

};