feat(data structure):使用通用的数据结构头文件来把DTO和Classes分离。

.vscode/settings.json

@@ -137,6 +137,6 @@
 	// 如果您有 .prettierrc，请务必在其中设置 "useTabs": true, "tabWidth": 4
 	// --- JSON 配置 ---
 	"[json]": {
-		"editor.defaultFormatter": "esbenp.prettier-vscode"
+		"editor.defaultFormatter": "vscode.json-language-features"
 	}
 }

config/config.json

@@ -1,21 +1,35 @@
 {
-    "alarm_rules_path": "alarms.json",
-    "config_base_path": "/app/config/",
-    "data_cache_db_path": "edge_data_cache.db",
-    "data_storage_db_path": "edge_proxy_data.db",
-    "db_database": "smart-car-dev",
-    "db_host": "127.0.0.1",
-    "db_pwd": "forlinx",
-    "db_user": "forlinx",
-    "device_id": "rk3588-proxy-002",
-    "log_level": "info",
-    "mqtt_broker": "tcp://localhost:1883",
-    "mqtt_client_id_prefix": "vehicle-road-counter-",
-    "piper_executable_path": "/usr/bin/piper",
-    "piper_model_path": "/app/models/model.onnx",
-    "tcp_server_ports": [
-        12345
-    ],
-    "video_config_path": "video_config.json",
-    "web_server_port": 8080
+	"alarm_rules_path": "alarms.json",
+	"config_base_path": "/app/config/",
+	"data_cache_db_path": "edge_data_cache.db",
+	"data_storage_db_path": "edge_proxy_data.db",
+	"db_database": "smart-car-dev",
+	"db_host": "127.0.0.1",
+	"db_pwd": "forlinx",
+	"db_user": "forlinx",
+	"device_id": "rk3588-proxy-002",
+	"log_level": "info",
+	"mqtt_broker": "tcp://localhost:1883",
+	"mqtt_client_id_prefix": "vehicle-road-counter-",
+	"piper_executable_path": "/usr/bin/piper",
+	"piper_model_path": "/app/models/model.onnx",
+	"tcp_server_ports": [
+		12345
+	],
+	"video_config_path": "video_config.json",
+	"web_server_port": 8080,
+	"tripwire": {
+		"enable": true,
+		"line": {
+			"p1": {
+				"x": 0.0,
+				"y": 0.8
+			},
+			"p2": {
+				"x": 1.0,
+				"y": 0.8
+			}
+		},
+		"name": "Main_Gate_Line"
+	}
 }

src/DTOs/common_types.hpp

@@ -0,0 +1,57 @@
+#pragma once
+
+#include <opencv2/opencv.hpp>
+#include <string>
+#include <vector>
+
+// 如果 DetectionResult 定义在 yolo_detector.hpp 中，需要包含它
+// 或者，如果 DetectionResult 很简单，建议把它也直接移到这里来
+// #include "yoloDetector/yolo_detector.hpp"
+
+// ===========================
+// 1. 核心检测与追踪数据结构
+// ===========================
+
+// 追踪到的车辆对象
+struct TrackedVehicle {
+	int id;				 // 轨迹ID
+	cv::Rect box;		 // 当前位置
+	float ev_score;		 // 新能源平滑分数
+	int missing_frames;	 // 丢失帧数计数
+	int last_class_id;	 // 最终判定类别 (0: Fuel, 1: Green)
+	std::string label;	 // 显示标签
+
+	// [预留] 如果需要记录车辆经过线条的时间，可以在这里加字段
+	// int64_t cross_line_timestamp = 0;
+};
+
+// 每一帧的数据包（用于线程间传递）
+struct FrameData {
+	long frame_id;						   // 帧序号
+	cv::Mat original_frame;				   // 原始图像
+	std::vector<DetectionResult> results;  // 检测结果
+};
+
+// ===========================
+// 2. 业务配置结构
+// ===========================
+
+// 绊线配置结构 (归一化坐标方案)
+struct TripwireConfig {
+	bool enabled = false;
+	std::string name;  // 例如 "南门出口"
+
+	// 使用 Point2f 存储 0.0-1.0 的归一化坐标
+	cv::Point2f p1_norm;  // 起点
+	cv::Point2f p2_norm;  // 终点
+};
+
+struct DetectionResult {
+	int x;
+	int y;
+	int width;
+	int height;
+	std::string label;
+	float confidence;
+	int class_id;
+};

src/videoService/video_pipeline.hpp

@@ -11,26 +11,10 @@
 #include <thread>
 #include <vector>
 
+#include "DTOs/common_types.hpp"
 #include "spdlog/spdlog.h"
 #include "yoloDetector/yolo_detector.hpp"
 
-// ... TrackedVehicle 结构体保持不变 ...
-struct TrackedVehicle {
-	int id;
-	cv::Rect box;
-	float ev_score;
-	int missing_frames;
-	int last_class_id;
-	std::string label;
-};
-
-// [新增] 每一帧的数据包
-struct FrameData {
-	long frame_id;						   // 帧序号，用于排序
-	cv::Mat original_frame;				   // 原始图像
-	std::vector<DetectionResult> results;  // 检测结果
-};
-
 class VideoPipeline {
 public:
 	VideoPipeline();
@@ -39,6 +23,7 @@ public:
 	void Start(const std::string& inputUrl, const std::string& outputUrl);
 	void StartTest(const std::string& filePath, const std::string& outputUrl);
 	void Stop();
+	void setTripwire(const TripwireConfig& config);
 
 private:
 	void processLoop(std::string inputUrl, std::string outputUrl, bool isFileSource);
@@ -50,6 +35,11 @@ private:
 	void updateTracker(const std::vector<DetectionResult>& detections);
 	float computeIOU(const cv::Rect& box1, const cv::Rect& box2);
 
+	bool isLineCrossed(const cv::Point& p1, const cv::Point& p2, const cv::Point& line_start,
+					   const cv::Point& line_end);
+
+	void processCrossing(const TrackedVehicle& vehicle, const cv::Mat& frame);
+
 private:
 	std::atomic<bool> running_;
 	std::thread processingThread_;	// 主处理线程

src/yoloDetector/yolo_detector.hpp

@@ -7,18 +7,19 @@
 #include <string>
 #include <vector>
 
+#include "DTOs/common_types.hpp"
 #include "postprocess.h"
 #include "rknn_api.h"
 
-struct DetectionResult {
-	int x;
-	int y;
-	int width;
-	int height;
-	std::string label;
-	float confidence;
-	int class_id;
-};
+// struct DetectionResult {
+// 	int x;
+// 	int y;
+// 	int width;
+// 	int height;
+// 	std::string label;
+// 	float confidence;
+// 	int class_id;
+// };
 
 class YoloDetector {
 public: