109 lines
4.1 KiB
C++
109 lines
4.1 KiB
C++
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#include "VideoEngine.h"
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using namespace std;
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using namespace cv;
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using namespace ai_matrix;
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VideoEngine::VideoEngine() {}
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VideoEngine::~VideoEngine() {}
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APP_ERROR VideoEngine::Init()
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{
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LogInfo << "engineId_:" << engineId_ << " VideoEngine Init start";
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strPort0_ = engineName_ + "_" + std::to_string(engineId_) + "_0";
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dataSourceConfig_ = MyYaml::GetIns()->GetDataSourceConfigById(engineId_); //获取摄像机参数
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width_ = IMAGE_WIDTH, height_ = IMAGE_HEIGHT;
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LogInfo << "engineId_:" << engineId_ << " VideoEngine Init ok";
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return APP_ERR_OK;
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}
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APP_ERROR VideoEngine::DeInit()
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{
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LogInfo << "engineId_:" << engineId_ << " VideoEngine DeInit ok";
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return APP_ERR_OK;
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}
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APP_ERROR VideoEngine::Process()
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{
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int iRet = APP_ERR_OK;
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uint64_t u64count_num = 0;
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// if (MyYaml::GetIns()->GetStringValue("gc_data_source") != "camera")
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// {
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// LogDebug << "engineId_:" << engineId_ << " gc_data_source no camera";
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// return iRet;
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// }
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VideoCapture capture;
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/*****************************************************************************************
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Gstream解码
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硬件解码方式:1.nvv4l2decoder 2.omxh264dec
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使用nvv4l2decoder解码时enable-max-performance和enable-frame-type-reporting才可以使用
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enable-max-performance=1 开启最大效率模式
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enable-frame-type-reporting=1 使能帧数据汇报模式
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*****************************************************************************************/
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//从摄像头RTSP拉流
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const std::string videoStreamAddress = std::string("rtspsrc location=") + dataSourceConfig_.strUrl.c_str() + " latency=10 ! \
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rtph264depay ! h264parse ! nvv4l2decoder enable-max-performance=1 enable-frame-type-reporting=1 ! nvvidconv ! video/x-raw, format=(string)BGRx ! videoconvert ! appsink";
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// while(!capture.open(dataSourceConfig_.strUrl.c_str())){
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while(!capture.open(videoStreamAddress)){
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std::cerr<<"Opening video stream or file failed!!!" <<std::endl;
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std::cout<<"Restart Opening video stream or file ..."<<std::endl;
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sleep(1);
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}
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std::cout<<"Opening video stream or file Success"<<std::endl;
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int frameW = capture.get(3);
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int frameH = capture.get(4);
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std::cout << dataSourceConfig_.strUrl.c_str() << ";"<< "frameW:" << frameW << " frameH:" << frameH << std::endl;
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while (!isStop_)
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{
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std::cout << dataSourceConfig_.strUrl.c_str() << ";"<< "frameW:" << frameW << " frameH:" << frameH << std::endl;
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// std::cout<<"Enter VideoEngine Thread "<<++u64count_num<<" Times!"<<std::endl;
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// std::cout<<"VideoEngine Thread ID: "<<std::this_thread::get_id()<<std::endl;
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//构造BGR数据
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void* pBGRBuffer = nullptr;
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unsigned int pBGRBuffer_Size = width_*height_*3;
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pBGRBuffer = new uint8_t[pBGRBuffer_Size];
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std::shared_ptr<FrameData> pBGRFrameData = std::make_shared<FrameData>();
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cv::Mat frame(frameH, frameW, CV_8UC3, pBGRBuffer);
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// clock_t start, end;
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// start = clock();
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if(!capture.read(frame)) {
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std::cerr << "no frame" << std::endl;
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waitKey();
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}
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// end = clock();
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// printf("read 1 frame time is %.8f ms\n", (double)(end-start)/CLOCKS_PER_SEC*1000);
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//压入OpenCV RTSP所拉的H264解码BRG后的数据
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//组织数据
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pBGRFrameData->iDataSource = engineId_;
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pBGRFrameData->iSize = pBGRBuffer_Size;
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pBGRFrameData->pData.reset(pBGRBuffer, [](void* data){if(data) {delete[] data; data = nullptr;}}); //智能指针管理内存
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// pBGRFrameData->pData.reset(pBGRBuffer, Deleter); //智能指针管理内存
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pBGRFrameData->i64TimeStamp = MyUtils::getins()->GetCurrentTimeMillis();
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iRet = outputQueMap_[strPort0_]->push(std::static_pointer_cast<void>(pBGRFrameData));
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if (iRet != APP_ERR_OK){
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LogError << "push the bgr frame data failed...";
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std::cerr<<"push the bgr frame data failed..."<<std::endl;
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}else{
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// std::cout<<"push the bgr frame data success!"<<std::endl;
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}
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// usleep(30*1000); //读取文件时模拟30帧
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}
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}
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