Initial setup for CLion

2026-03-28 16:54:11 +11:00
parent 239cc02591
commit 7b4134133c
1136 changed files with 811916 additions and 0 deletions
--- a/ANSODEngine/ANSYOLOOD.h
+++ b/ANSODEngine/ANSYOLOOD.h
@@ -0,0 +1,64 @@
+#ifndef ANSYOLOOD_H
+#define ANSYOLOOD_H
+#pragma once
+#include "ANSEngineCommon.h"
+#include <onnxruntime_cxx_api.h>
+//#define   USEOPENCVDNN
+namespace ANSCENTER {
+    class ANSENGINE_API YOLOOD :public ANSODBase {
+    public:
+        virtual bool Initialize(std::string licenseKey, ModelConfig modelConfig, const std::string& modelZipFilePath, const std::string& modelZipPassword, std::string& labelMap) override;
+        virtual bool LoadModel(const std::string& modelZipFilePath, const std::string& modelZipPassword)override;
+        virtual bool LoadModelFromFolder(std::string licenseKey, ModelConfig modelConfig, std::string modelName, std::string className, const std::string& modelFolder, std::string& labelMap)override;
+        virtual bool OptimizeModel(bool fp16, std::string& optimizedModelFolder);
+        std::vector<Object> RunInference(const cv::Mat& input);
+        std::vector<Object> RunInference(const cv::Mat& input, const std::string& camera_id);   
+
+        bool Destroy();
+        ~YOLOOD();
+    private:
+        std::shared_ptr<cv::dnn::Net> _net;
+        std::string     _modelFilePath;
+        bool            _letterBoxForSquare{ true };
+        bool            _isDarkNet{false};
+        std::vector<float> _blob;  // Reusable buffer
+        cv::Mat _frameBuffer;  // Reusable buffer for color conversion
+
+    private:
+        std::vector<Object> RunInferenceFromONNX(const cv::Mat& input, const std::string& camera_id);
+        std::vector<Object> RunInferenceFromYoloV5(const cv::Mat& input, const std::string& camera_id);
+        std::vector<Object> RunInferenceFromYoloV11(const cv::Mat& input, const std::string& camera_id);
+        std::vector<Object> RunInferenceFromDarkNet(const cv::Mat& input, const std::string& camera_id);
+		std::vector<Object> RunInferenceFromYoloV8(const cv::Mat& input, const std::string& camera_id);// OpenCV Style
+        void LoadOnnxNetwork();  
+        void LoadDarknetNetwork();
+        void SetEngineType();
+    private: 
+        Ort::Env env{ nullptr };
+        Ort::SessionOptions sessionOptions{ nullptr };
+        Ort::Session session{ nullptr };
+        bool loadYoloModel(const std::string& modelPath,const bool& isGPU = true,const cv::Size& inputSize = cv::Size(640, 640));
+        std::vector<Object> detect(cv::Mat& image, const float& confThreshold, const float& iouThreshold);
+        void preprocessing(const cv::Mat& image,std::vector<float>& blob,std::vector<int64_t>& inputTensorShape);
+        //cv::Mat preprocessv11(const cv::Mat& image, float*& blob, std::vector<int64_t>& inputTensorShape);
+        cv::Mat preprocessv11(const cv::Mat& image, std::vector<float>& blob, std::vector<int64_t>& inputTensorShape);
+        std::vector<Object> postprocessing(const cv::Size& resizedImageShape,const cv::Size& originalImageShape,std::vector<Ort::Value>& outputTensors,
+                                           const float& confThreshold, const float& iouThreshold);
+        std::vector<Object> postprocessv11(const cv::Size& originalImageSize,const cv::Size& resizedImageShape,const std::vector<Ort::Value>& outputTensors,float confThreshold,float iouThreshold);
+        BoundingBox scaleCoordsv11(const cv::Size& imageShape, BoundingBox coords,const cv::Size& imageOriginalShape, bool p_Clip);
+        std::vector<const char*> inputNodeNames;
+        std::vector<const char*> outputNodeNames;
+        bool isDynamicInputShape{};
+        cv::Size inputImageShape;                      // Expected input image shape for the model
+        float resizeScales;//letterbox scale
+        float m_imgWidth = 0;
+        float m_imgHeight = 0;
+		std::vector<Object> detectv11(const cv::Mat& image, float confThreshold, float iouThreshold);
+		//ultility functions
+        void getBestClassInfo(std::vector<float>::iterator it, const int& numClasses,float& bestConf, int& bestClassId);
+        void letterbox(const cv::Mat& image, cv::Mat& outImage,const cv::Size& newShape,const cv::Scalar& color,bool auto_,bool scaleFill,bool scaleUp,int stride);
+        void scaleCoords(const cv::Size& imageShape, cv::Rect& box, const cv::Size& imageOriginalShape);
+        size_t vectorProduct(const std::vector<int64_t>& vector);
+    };
+}
+#endif