Hu Chunming / src

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Commit a0e58901c398cf4db491af62fff8be77ee7af08a

Authored by Hu Chunming 2022-10-31 10:44:09 +0800

1 parent 31a1e592

去掉CMultiSourceProcess的多GPU参数，多GPU由上一层来设置更为方便简单；去掉多余成员变量；优化代码

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Showing 3 changed files with 24 additions and 75 deletions

FFNvDecoder/FFNvDecoderManager.cpp

View file @a0e5890

	@@ -177,6 +177,7 @@ int FFNvDecoderManager::count()		@@ -177,6 +177,7 @@ int FFNvDecoderManager::count()
177	{	177	{
178	closeAllFinishedDecoder();	178	closeAllFinishedDecoder();
179		179
		180	+ std::lock_guard<std::mutex> l(m_mutex);
180	return decoderMap.size();	181	return decoderMap.size();
181	}	182	}
182		183

tsl_aiplatform/ai_platform/MultiSourceProcess.cpp

View file @a0e5890

 @@ -93,6 +93,7 @@ int CMultiSourceProcess::InitAlgorthim(tsl_aiplatform_param vptParam) {
    m_bfinish = false;
++  // 设置gpuid
    gpu_id_ = to_string(vptParam.gpuid);
    int ret = SUCCESS;
 @@ -113,12 +114,6 @@ int CMultiSourceProcess::InitAlgorthim(tsl_aiplatform_param vptParam) {
    {
      /*初始化全局参数*/
--    mModeSnapshotVideo = "cpu";
--    mModeSnapshotLittle = "cpu";
--
--    taskFinishCallbackFunc = nullptr;
--    taskObjInfoCallbackFunc = nullptr;
--
      set_default_logger(LogLevel(vptParam.log_level), "multi_source_video_process", vptParam.log_path, vptParam.log_mem,
                         vptParam.log_mem);
 @@ -327,35 +322,19 @@ bool CMultiSourceProcess::AddTask(task_param _cur_task_param){
  #endif
      // 启动算法处理线程
--    startProcessByGpuid(gpu_id_);
++    startProcessByGpuid();
  }
  // 启动算法处理线程
--void CMultiSourceProcess::startProcessByGpuid(const string gpuid){
--
--  struct ThreadArg{
--    const string gpu_id;
--    void* opaque;
--  };
--
--  ThreadArg thread_arg = {gpuid, this};
--
--  pthread_t* processThread = gpuProcessthreadMap[gpuid];
--  if(processThread == nullptr){
--      pthread_t* pTread = new pthread_t;
--      pthread_create(pTread,0,
--          [](void* arg)
--          {
--              ThreadArg* ptr=(ThreadArg*)arg;
--              if(ptr != nullptr){
--                CMultiSourceProcess* process = (CMultiSourceProcess*)ptr->opaque ;
--                process->algorthim_process_thread(ptr->gpu_id);
--              }
--              return (void*)0;
--          }
--      ,&thread_arg);
--      gpuProcessthreadMap[gpuid] = pTread;
--  }
++void CMultiSourceProcess::startProcessByGpuid(){
++  pthread_create(&m_gpuProcessthread,0,
++      [](void* arg)
++      {
++          CMultiSourceProcess* process = (CMultiSourceProcess*)arg ;
++          process->algorthim_process_thread();
++          return (void*)0;
++      }
++  ,this);
  }
  void CMultiSourceProcess::post_decode_thread(task_param _cur_task_param, AVFrame * gpuFrame){
 @@ -378,7 +357,7 @@ void CMultiSourceProcess::post_decode_thread(task_param _cur_task_param, AVFrame
          }
          // TODO 本循环需要一个可以手动终止的开关
          m_QueueMtx.lock();
--        if(m_RgbDataList.size() >= (20 * gpuProcessthreadMap.size() + 20)){
++        if(m_RgbDataList.size() >= 40){
            m_QueueMtx.unlock();
            std::this_thread::sleep_for(std::chrono::milliseconds(1));
            continue;
 @@ -390,6 +369,7 @@ void CMultiSourceProcess::post_decode_thread(task_param _cur_task_param, AVFrame
    }
  }
++// 解码线程退出的最后回调的实际任务函数
  void CMultiSourceProcess::decode_finished_thread(task_param t_param){
    // 任务结束，关闭跟踪
    if (!FinishTaskTracker(VPT_Handle_, t_param.task_id))
 @@ -436,7 +416,7 @@ void CMultiSourceProcess::cuda_free_wrap(sy_img &amp;img) {
  }
  // 算法处理函数，由算法线程调用
--void CMultiSourceProcess::algorthim_process_thread(const string gpuid){
++void CMultiSourceProcess::algorthim_process_thread(){
    map<string, int> task_id_to_n_frame;
    while(true){
 @@ -454,16 +434,12 @@ void CMultiSourceProcess::algorthim_process_thread(const string gpuid){
      m_QueueMtx.lock();
      vector<GpuRgbMemory*> vec_gpuMem;
--    for (auto iter = m_RgbDataList.begin(); iter!=m_RgbDataList.end(); ){
++    for (auto iter = m_RgbDataList.begin(); iter!=m_RgbDataList.end(); ++ iter){
        GpuRgbMemory* gpuMem = *iter;
--      if(gpuMem->getGpuId() == gpuid){
--        vec_gpuMem.push_back(gpuMem);
--        iter = m_RgbDataList.erase(iter);
--        if(vec_gpuMem.size() >= 20){
--          break;
--        }
--      } else {
--        ++ iter;
++      vec_gpuMem.push_back(gpuMem);
++      iter = m_RgbDataList.erase(iter);
++      if(vec_gpuMem.size() >= 20){
++        break;
        }
      }
 @@ -1171,7 +1147,6 @@ int CMultiSourceProcess::GetTaskStatus(const string taskID) {
    if (!taskids.empty()) {
      auto json_str = helpers::gen_json::gen_task_status_json(taskids, statues);
--    // mq_manager_->publish(mq_type_t::GET_TASK_MQ, json_str.c_str());
      mq_manager_->publish(mq_type_t::GET_TASK_MQ, json_str.c_str(),true);
    }
 @@ -1226,13 +1201,7 @@ void CMultiSourceProcess::CloseAllTask(){
    FFNvDecoderManager* pDecManager = FFNvDecoderManager::getInstance();
    pDecManager->closeAllDecoder();
--  for (auto it = gpuProcessthreadMap.begin(); it != gpuProcessthreadMap.end(); it++){
--    if(it->second != 0){
--      pthread_join(*(it->second),0);
--      delete it->second;
--    }
--  }
--  gpuProcessthreadMap.clear();
++  pthread_join(m_gpuProcessthread,0);
    m_QueueMtx.lock();
    for (auto iter = m_RgbDataList.begin(); iter!=m_RgbDataList.end(); ){

tsl_aiplatform/ai_platform/MultiSourceProcess.h

View file @a0e5890

 @@ -155,7 +155,7 @@ public:
  public:
    // 生成线程的内部接口，外部勿调用
--  void algorthim_process_thread(const string gpuid);  // 算法处理线程
++  void algorthim_process_thread();  // 算法处理线程
    void post_decode_thread(task_param _cur_task_param, AVFrame * gpuFrame);  // 解码数据处理函数，在解码线程中执行
    void decode_finished_thread(task_param _cur_task_param);  // 解码线程结束后处理函数，在解码线程中执行
 @@ -164,7 +164,7 @@ public:
  #endif
  private:
--  void startProcessByGpuid(const string gpuid);
++  void startProcessByGpuid();
    bool task_has_vpt_algor(const std::string &task_id);
    bool task_has_face_algor(const std::string &task_id);
    void cuda_free_wrap(sy_img &img);
 @@ -202,7 +202,7 @@ private:
    int everyframe_process(vector<string> &task_in_play_id, sy_img *images, vector<onelevel_det_result> &ol_det_result);
  private:
--  map<string, pthread_t*> gpuProcessthreadMap;  // 本想做个多GPU的，但是原版的多GPU设置由上层来做，而且似乎可以更好
++  pthread_t m_gpuProcessthread;
    list<GpuRgbMemory*> m_RgbDataList;
    std::mutex m_QueueMtx;
    bool m_bfinish;
 @@ -215,27 +215,6 @@ private:
    int licence_status_;
    string gpu_id_;
--
--  // vector<onelevel_det_result> VPTResult;
--  std::atomic<bool> ProcessFlag;
--  bool SourceFlag;
--  unsigned char *imgDataDevice;
--  void *FrameTemp;
--  char *mModeSnapshotVideo;
--  char *mModeSnapshotLittle;
--  string viewTaskID;
--
--  map<int, set<int>> objDelete;
--
--  FINISH_CALLBACK taskFinishCallbackFunc;
--  OBJECT_INFO_CALLBACK taskObjInfoCallbackFunc;
--
--  bool beginSaveSnapshot;
--  boost::thread_group saveSnapshotsThreadGroup;
--  std::mutex taskMutex;
--  std::condition_variable taskCondVar;
--  bool AttributionAnalysis; // 用于控制，每帧分析只进行一个二次属性分析
--
    snapshot_reprocessing *m_snapshot_reprocessing{nullptr};
    task_param_manager *m_task_param_manager{nullptr};