修复了一个关闭程序时因为提前释放了全局变量导致SF的问题

src/algorithm/IAnalysisModule.h

@@ -24,4 +24,6 @@ public:
      * @param frame [in/out] 传入原始帧，模块应在此帧上直接绘制结果。
      */
     virtual bool process(cv::Mat& frame) = 0;
+
+    virtual void stop() = 0;
 };

src/algorithm/IntrusionModule.cc

@@ -20,9 +20,6 @@ IntrusionModule::IntrusionModule(std::string model_path,
     }
 }
 
-// 
-// init() 函数: 从 video_service.cc 的 start() 移动而来
-//
 bool IntrusionModule::init() {
     rknn_pool_ = std::make_unique<rknnPool<rkYolov5s, cv::Mat, detect_result_group_t>>(model_path_.c_str(), thread_num_);
     if (rknn_pool_->init() != 0) {
@@ -33,22 +30,17 @@ bool IntrusionModule::init() {
     return true;
 }
 
-// 
-// process() 函数: 从 video_service.cc 的 processing_loop() 移动而来
-//
 bool IntrusionModule::process(cv::Mat& frame) {
     if (frame.empty()) {
         return false;
     }
-    
+
-    // 1. 图像预处理 (来自)
     cv::Mat model_input_image;
     cv::resize(frame, model_input_image, cv::Size(640, 640));
     if (!model_input_image.isContinuous()) {
         model_input_image = model_input_image.clone();
     }   
 
-    // 2. RKNN 推理 (来自)
     if (rknn_pool_->put(model_input_image) != 0) {
         spdlog::error("[IntrusionModule] Failed to put frame into rknnPool.");
         return false;
@@ -60,19 +52,14 @@ bool IntrusionModule::process(cv::Mat& frame) {
         return false;
     }
 
-    // 3. 跟踪与报警 (来自)
     this->update_tracker(detection_results, frame.size());
 
-    // 4. 绘制结果 (来自)
     this->draw_results(frame); // 直接在传入的 frame 上绘制
 
     return true;
 }
 
 
-// 
-// 以下所有函数均从 video_service.cc 完整剪切而来
-//
 
 void IntrusionModule::trigger_alarm(int person_id, const cv::Rect& box) {
     printf("[ALARM] Intrusion detected! Person ID: %d at location (%d, %d, %d, %d)\n",
@@ -88,12 +75,10 @@ double IntrusionModule::get_current_time_seconds() {
 
 void IntrusionModule::update_tracker(detect_result_group_t &detect_result_group, const cv::Size& frame_size)
 {
-    // 如果入侵区域无效，则设置为帧中心的 1/4 区域 (基于原始帧大小)
     if (intrusion_zone_.width <= 0 || intrusion_zone_.height <= 0) {
         intrusion_zone_ = cv::Rect(frame_size.width / 4, frame_size.height / 4, frame_size.width / 2, frame_size.height / 2);
     }
 
-    // --- 缩放比例计算 ---
     const float model_input_width = 640.0f;
     const float model_input_height = 640.0f;
     float scale_x = (float)frame_size.width / model_input_width;
@@ -205,7 +190,7 @@ void IntrusionModule::update_tracker(detect_result_group_t &detect_result_group,
 
 void IntrusionModule::draw_results(cv::Mat& frame)
 {
-    cv::rectangle(frame, this->intrusion_zone_, cv::Scalar(255, 255, 0), 2); // 黄色
+    cv::rectangle(frame, this->intrusion_zone_, cv::Scalar(255, 255, 0), 2); 
 
     for (auto const& [id, person] : this->tracked_persons_) {
         cv::Scalar box_color = person.alarm_triggered ? cv::Scalar(0, 0, 255) : cv::Scalar(0, 255, 0);
@@ -219,4 +204,13 @@ void IntrusionModule::draw_results(cv::Mat& frame)
         cv::putText(frame, label, cv::Point(person.box.x, person.box.y - 10), 
                     cv::FONT_HERSHEY_SIMPLEX, 0.5, box_color, 2);
     }
+}
+void IntrusionModule::stop() {
+    spdlog::info("Stopping IntrusionModule internal threads...");
+    
+    if (rknn_pool_) {
+        rknn_pool_->stop(); // <-- 这会阻塞并等待 rknnPool 的所有线程退出
+    }
+    
+    spdlog::info("IntrusionModule stopped.");
 }

src/algorithm/IntrusionModule.h

@@ -40,18 +40,17 @@ public:
 
     virtual ~IntrusionModule() = default;
 
-    // --- 实现 IAnalysisModule 接口 ---
     virtual bool init() override;
     virtual bool process(cv::Mat& frame) override;
+    virtual void stop() override;
 
 private:
-    // --- 以下函数从 video_service.cc 移动到这里 ---
     void update_tracker(detect_result_group_t &detect_result_group, const cv::Size& frame_size);
     void draw_results(cv::Mat& frame);
     void trigger_alarm(int person_id, const cv::Rect& box);
     double get_current_time_seconds();
 
-    // --- 以下成员变量从 video_service.h 移动到这里 ---
+
     std::string model_path_;
     int thread_num_;
     std::unique_ptr<rknnPool<rkYolov5s, cv::Mat, detect_result_group_t>> rknn_pool_;

src/rknn/postprocess.cc

@@ -98,8 +98,18 @@ int readLines(const char *fileName, char *lines[], int max_line)
 int loadLabelName(const char *locationFilename, char *label[])
 {
 	printf("loadLabelName %s\n", locationFilename);
-	readLines(locationFilename, label, OBJ_CLASS_NUM);
+	int ret = readLines(locationFilename, label, OBJ_CLASS_NUM);
-	return 0;
+    if (ret < 0)
+    {
+        printf("readLines failed!\n");
+        return -1; // <--- 返回错误
+    }
+    if (ret == 0)
+    {
+        printf("No labels read from %s. File is empty or invalid.\n", locationFilename);
+        return -1; // <--- 返回错误
+    }
+	return 0; // 只有成功才返回 0
 }
 
 static float CalculateOverlap(float xmin0, float ymin0, float xmax0, float ymax0, float xmin1, float ymin1, float xmax1,

src/rknn/rkYolov5s.cc

@@ -281,7 +281,7 @@ detect_result_group_t rkYolov5s::infer(const cv::Mat &orig_img)
 
 rkYolov5s::~rkYolov5s()
 {
-    deinitPostProcess();
+    // deinitPostProcess();
 
     ret = rknn_destroy(ctx);
 

src/rknn/rknnPool.hpp

@@ -7,8 +7,9 @@
 #include <mutex>
 #include <queue>
 #include <memory>
+#include <atomic>
+#include "spdlog/spdlog.h"
 
-// rknnModel模型类, inputType模型输入类型, outputType模型输出类型
 template <typename rknnModel, typename inputType, typename outputType>
 class rknnPool
 {
@@ -22,6 +23,8 @@ private:
     std::queue<std::future<outputType>> futs;
     std::vector<std::shared_ptr<rknnModel>> models;
 
+    std::atomic<bool> is_stopped{false};
+
 protected:
     int getModelId();
 
@@ -32,6 +35,9 @@ public:
     int put(inputType inputData);
     // 获取推理结果/Get the results of your inference
     int get(outputType &outputData);
+
+    void stop();
+
     ~rknnPool();
 };
 
@@ -41,11 +47,13 @@ rknnPool<rknnModel, inputType, outputType>::rknnPool(const std::string modelPath
     this->modelPath = modelPath;
     this->threadNum = threadNum;
     this->id = 0;
+    this->is_stopped = false;
 }
 
 template <typename rknnModel, typename inputType, typename outputType>
 int rknnPool<rknnModel, inputType, outputType>::init()
 {
+    
     try
     {
         this->pool = std::make_unique<dpool::ThreadPool>(this->threadNum);
@@ -80,6 +88,10 @@ int rknnPool<rknnModel, inputType, outputType>::getModelId()
 template <typename rknnModel, typename inputType, typename outputType>
 int rknnPool<rknnModel, inputType, outputType>::put(inputType inputData)
 {
+    if (is_stopped) {
+        return -1; // Or handle as an error
+    }
+
     std::lock_guard<std::mutex> lock(queueMtx);
     futs.push(pool->submit(&rknnModel::infer, models[this->getModelId()], inputData));
     return 0;
@@ -88,22 +100,53 @@ int rknnPool<rknnModel, inputType, outputType>::put(inputType inputData)
 template <typename rknnModel, typename inputType, typename outputType>
 int rknnPool<rknnModel, inputType, outputType>::get(outputType &outputData)
 {
-    std::lock_guard<std::mutex> lock(queueMtx);
+    std::future<outputType> future_to_get;
-    if(futs.empty() == true)
+
-        return 1;
+    { 
-    outputData = futs.front().get();
+        std::lock_guard<std::mutex> lock(queueMtx);
-    futs.pop();
+        if (futs.empty() == true)
+            return 1; 
+
+        future_to_get = std::move(futs.front());
+        futs.pop();
+    } 
+
+    outputData = future_to_get.get();
     return 0;
 }
 
+template <typename rknnModel, typename inputType, typename outputType>
+void rknnPool<rknnModel, inputType, outputType>::stop()
+{
+
+    spdlog::critical("!!! [RKNN_POOL_STOP_CALLED] Shutdown sequence initiated. !!!");
+    if (is_stopped.exchange(true)) {
+        return;
+    }
+
+    while (true)
+    {
+        std::future<outputType> future_to_get;
+        {
+            std::lock_guard<std::mutex> lock(queueMtx);
+            if (futs.empty()) {
+                break; 
+            }
+            future_to_get = std::move(futs.front());
+            futs.pop();
+        }
+        
+        future_to_get.get(); 
+    }
+
+    pool.reset(); 
+
+}
+
 template <typename rknnModel, typename inputType, typename outputType>
 rknnPool<rknnModel, inputType, outputType>::~rknnPool()
 {
-    while (!futs.empty())
+    stop();
-    {
-        outputType temp = futs.front().get();
-        futs.pop();
-    }
 }
 
 #endif

src/rknn/video_service.cc

@@ -2,33 +2,17 @@
 #include "video_service.h"
 #include <stdio.h>
 #include "opencv2/imgproc/imgproc.hpp" 
-// #include "rknn/rkYolov5s.hpp"      // <-- 移除
-// #include "rknn/rknnPool.hpp"       // <-- 移除
 #include "spdlog/spdlog.h"
-// #include <chrono>                  // <-- 移除 (已移至 IntrusionModule)
-// #include <algorithm>               // <-- 移除 (已移至 IntrusionModule)
 
-//
-// !!! 关键: trigger_alarm, get_current_time_seconds, update_tracker, draw_results
-// !!! 所有这些函数 都已被剪切并移动到 IntrusionModule.cc
-//
-
-// 构造函数：修改为接收 module
 VideoService::VideoService(std::unique_ptr<IAnalysisModule> module,
                            std::string input_url, 
                            std::string output_rtsp_url)
-    : module_(std::move(module)), // <-- 关键：接收模块所有权
+    : module_(std::move(module)),
       input_url_(input_url),
       output_rtsp_url_(output_rtsp_url),
       running_(false) 
 {
     log_prefix_ = "[VideoService: " + input_url + "]"; 
-
-    // !!! 移除所有AI相关的初始化 !!!
-    // next_track_id_ = 1;
-    // intrusion_time_threshold_ = 3.0; 
-    // intrusion_zone_ = cv::Rect(0, 0, 0, 0); 
-
     spdlog::info("{} Created. Input: {}, Output: {}", log_prefix_, input_url_.c_str(), output_rtsp_url_.c_str());
 }
 
@@ -40,23 +24,18 @@ VideoService::~VideoService() {
 
 
 bool VideoService::start() {
-    // 1. (修改) 初始化AI模块
     if (!module_ || !module_->init()) {
         spdlog::error("{} Failed to initialize analysis module!", log_prefix_);
         return false;
     }
     spdlog::info("{} Analysis module initialized successfully.", log_prefix_);
 
-    // 2. (移除) RKNN Pool 初始化
-    // rknn_pool_ = std::make_unique<...>();
-    // ...
-
-    // 3. (不变) GStreamer 输入管线初始化
     std::string gst_input_pipeline = 
         "rtspsrc location=" + input_url_ + " latency=0 protocols=tcp ! "
         "rtph265depay ! "
         "h265parse ! "
         "mppvideodec format=16 ! "     
+        "videoconvert ! "
         "video/x-raw,format=BGR ! " 
         "appsink";
 
@@ -98,18 +77,17 @@ bool VideoService::start() {
         } else {
             spdlog::error("{} Failed to read first frame to determine size. Aborting.", log_prefix_);
             capture_.release();
-            return false; // 提前中止
+            return false; 
         }
     }
 
     printf("RTSP stream opened successfully! (%dx%d @ %.2f FPS)\n", frame_width_, frame_height_, frame_fps_);
 
-    // 4. (不变) GStreamer 输出管线初始化
     std::string gst_pipeline =
     "appsrc ! "
     "queue max-size-buffers=2 leaky=downstream ! "
     "video/x-raw,format=BGR ! " 
-    "videoconvert ! "           
+    "videoconvert ! "         
     "video/x-raw,format=NV12 ! " 
     "mpph265enc gop=25 rc-mode=fixqp qp-init=26 ! " 
     "h265parse ! "
@@ -130,7 +108,6 @@ bool VideoService::start() {
     }
     printf("VideoWriter opened successfully.\n");
 
-    // 5. (不变) 启动线程
     running_ = true;
     reading_thread_ = std::thread(&VideoService::reading_loop, this);
     processing_thread_ = std::thread(&VideoService::processing_loop, this);
@@ -144,7 +121,6 @@ void VideoService::stop() {
     printf("Stopping VideoService...\n");
     running_ = false; 
 
-    // 唤醒可能在 frame_cv_.wait() 处等待的线程
     frame_cv_.notify_all(); 
 
     if (reading_thread_.joinable()) {
@@ -162,17 +138,12 @@ void VideoService::stop() {
     if (writer_.isOpened()) {
         writer_.release();
     }
-
+    module_->stop();
-    // (可选) 确保模块资源被释放 (虽然unique_ptr析构时会自动处理)
+    module_.reset();
-    module_.reset(); 
 
     printf("VideoService stopped.\n");
 }
 
-
-//
-// reading_loop() 函数: 完全不变
-//
 void VideoService::reading_loop() {
     cv::Mat frame;
     spdlog::info("Reading thread started.");
@@ -202,12 +173,8 @@ void VideoService::reading_loop() {
 }
 
 
-//
-// processing_loop() 函数: 极大简化 (关键修改)
-//
 void VideoService::processing_loop() {
     cv::Mat frame;
-    // detect_result_group_t detection_results; // <-- 移除
     
     while (running_) {
         {
@@ -229,16 +196,10 @@ void VideoService::processing_loop() {
         if (frame.empty()) {
             continue;
         }
-
-        // 2. (关键修改) 调用AI模块处理
-        // --- 移除所有 resize, put, get, update_tracker, draw_results ---
         if (!module_->process(frame)) {
             // 模块报告处理失败
             spdlog::warn("{} Module failed to process frame. Skipping.", log_prefix_);
         }
-        // 此时 'frame' 已经被 module_->process() 修改（例如，绘制了框）
-
-        // 3. (不变) 写入输出流
         if (writer_.isOpened()) {
             writer_.write(frame);
         }