fix yolo network occasinally preditcting a match out side of image bounds

yolo.cpp

@@ -181,14 +181,33 @@ std::vector<Yolo::Detection> Yolo::runInference(const cv::Mat &input)
 
 		result.className = classes[result.class_id].first;
 		result.priority = classes[result.class_id].second;
+		clampBox(boxes[idx], input.size());
 		result.box = boxes[idx];
-
 		detections.push_back(result);
 	}
 
 	return detections;
 }
 
+
+void Yolo::clampBox(cv::Rect& box, const cv::Size& size)
+{
+	if(box.x < 0)
+	{
+		box.width += box.x;
+		box.x = 0;
+	}
+	if(box.y < 0)
+	{
+		box.height += box.y;
+		box.y = 0;
+	}
+	if(box.x+box.width > size.width)
+		box.width = size.width - box.x;
+	if(box.y+box.height > size.height)
+		box.height = size.height - box.y;
+}
+
 void Yolo::loadClasses(const std::string& classesStr)
 {
 	std::vector<std::string> candidateClasses = tokenizeBinaryIgnore(classesStr, '\n', '"', '\\');

yolo.h

@@ -27,19 +27,16 @@ private:
 	static constexpr float modelScoreThreshold = 0.45;
 	static constexpr float modelNMSThreshold = 0.50;
 
+	std::string modelPath;
+	std::vector<std::pair<std::string, int>> classes;
+	cv::Size2f modelShape;
+	bool letterBoxForSquare = true;
+	cv::dnn::Net net;
+
 	void loadClasses(const std::string& classes);
 	void loadOnnxNetwork(const std::filesystem::path& path);
 	cv::Mat formatToSquare(const cv::Mat &source);
-
+	static void clampBox(cv::Rect& box, const cv::Size& size);
-	std::string modelPath;
-
-	std::vector<std::pair<std::string, int>> classes;
-
-	cv::Size2f modelShape;
-
-	bool letterBoxForSquare = true;
-
-	cv::dnn::Net net;
 
 public:
 	Yolo(const std::filesystem::path &onnxModelPath = "", const cv::Size& modelInputShape = {640, 480},