46 lines
		
	
	
	
		
			1.2 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			46 lines
		
	
	
	
		
			1.2 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
| #pragma once
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| 
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| #include <fstream>
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| #include <vector>
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| #include <string>
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| #include <random>
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| #include <filesystem>
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| #include <opencv2/imgproc.hpp>
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| #include <opencv2/opencv.hpp>
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| #include <opencv2/dnn.hpp>
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| 
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| class Yolo
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| {
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| public:
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| 	struct Detection
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| 	{
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| 		int class_id = 0;
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| 		std::string className;
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| 		float confidence = 0.0;
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| 		int priority = -1;
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| 		cv::Scalar color;
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| 		cv::Rect box;
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| 	};
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| 
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| private:
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| 	static constexpr float modelConfidenceThreshold = 0.25;
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| 	static constexpr float modelScoreThreshold = 0.45;
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| 	static constexpr float modelNMSThreshold = 0.50;
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| 
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| 	std::string modelPath;
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| 	std::vector<std::pair<std::string, int>> classes;
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| 	cv::Size2f modelShape;
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| 	bool letterBoxForSquare = true;
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| 	cv::dnn::Net net;
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| 
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| 	void loadClasses(const std::string& classes);
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| 	void loadOnnxNetwork(const std::filesystem::path& path);
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| 	cv::Mat formatToSquare(const cv::Mat &source);
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| 	static void clampBox(cv::Rect& box, const cv::Size& size);
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| 
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| public:
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| 	Yolo(const std::filesystem::path &onnxModelPath = "", const cv::Size& modelInputShape = {640, 480},
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| 		const std::filesystem::path& classesTxtFilePath = "", bool runWithOCl = true);
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| 	std::vector<Detection> runInference(const cv::Mat &input);
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| 	int getClassForStr(const std::string& str) const;
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| };
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