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• Capture from multiple streams concurrently, best way to do it and how to reduce CPU usage

  19 juin 2019, par DRONE_6969

  I am currently in the process of writing an application that will capture a lot of RTSP streams(in my case its 12) and display it on the QT widget. The problem arouses when I am going beyond around 6-7 streams, the CPU usage spikes and there is visible stutter.

  The reason why I think that it is not QT draw function is because I have done some checking to measure how much time it takes to draw an incoming image from camera and just sample images I had, it is always a lot less than 33 milliseconds(even if there are 12 widgets being updated).

  I also just ran opencv capture method without drawing and got pretty much the same CPU consumption as if I was drawing the frames (lost like 10% CPU at most and GPU usage went to zero).

  IMPORTANT : I am using RTSP stream which is a h264 stream.

  IF IT MATTERS MY SPECS :

  Intel Core i7-6700 @ 3.40GHZ(8 CPUS)
  Memory : 16gb
  GPU : Intel HD Graphics 530

  (Also I ran my code on a computer with dedicated Graphics card, it did eliminate some stutter but CPU usage is still pretty high)

  I am currently using OPENCV 4.1.0 with GSTREAMER enabled and built, I also have the OPENCV-WORLD version, there is no difference in performance.

  I have created a special class called Camera that holds its frame size constraints and various control functions as well stream function. The stream function is being ran on a separate thread, whenever stream() function is done with current frame it sends ready Mat via onNewFrame event I created which converts to QPixmap and updates widget’s lastImage variable. This way I can update image in a more thread safe way.

  I have tried to manipulate those VideoCapture.set() values, but it didn’t really help.

  This is my stream function (Ignore the bool return, it doesn’t do anything it is a remnant from couple of minutes ago when I was trying to use std::async) :

  bool Camera::stream() {
  
      /* This function is meant to run on a separate thread and fill up the buffer independantly of
  
      main stream thread */
  
      //cv::setNumThreads(100);
  
      /* Rules for these slightly changed! */
  
      Mat pre;  // Grab initial undoctored frame
  
      //pre = Mat::zeros(size, CV_8UC1);
  
      Mat frame; // Final modified frame
  
      frame = Mat::zeros(size, CV_8UC1);
  
      if (!pre.isContinuous()) pre = pre.clone();
  
  
  
      ipCam.open(streamUrl, CAP_FFMPEG);
  
  
  
  
  
      while (ipCam.isOpened() && capture) {
  
          // If camera is opened wel need to capture and process the frame
  
          try {
  
              auto start = std::chrono::system_clock::now();
  
  
  
              ipCam >> pre;
  
  
  
              if (pre.empty()) {
  
                  /* Check for blank frame, return error if there is a blank frame*/
  
                  cerr << id << ": ERROR! blank frame grabbed\n";
  
                  for (FrameListener* i : clients) {
  
                      i->onNotification(1); // Notify clients about this shit
  
                  }
  
                  break;
  
              }
  
  
  
              else {
  
                  // Only continue if frame not empty
  
  
  
                  if (pre.cols != size.width && pre.rows != size.height) {
  
                      resize(pre, frame, size);
  
                      pre.release();
  
                  }
  
                  else {
  
                      frame = pre;
  
                  }
  
  
  
                  dPacket* pack = new dPacket{id,&frame};
  
                  for (auto i : clients) {
  
                      i->onPNewFrame(pack);
  
                  }
  
                  frame.release();
  
                  delete pack;
  
              }
  
          }
  
  
  
          catch (int e) {
  
              cout << endl << "-----Exception during capture process! CODE " << e << endl;
  
          }
  
          // End camera manipulations
  
      }
  
  
  
      cout << "Camera timed out, or connection is closed..." << endl;
  
      if (tryResetConnection) {
  
          cout << "Reconnection flag is set, retrying after 3 seconds..." << endl;
  
          for (FrameListener* i : clients) {
  
              i->onNotification(-1); // Notify clients about this shit
  
          }
  
          this_thread::sleep_for(chrono::milliseconds(3000));
  
          stream();
  
      }
  
  
  
      return true;
  
  }

  This is my onPNewFrame function. The conversion is still being done on camera’s thread because it was called within stream() and therefore is within that scope(and I also checked) :

  void GLWidget::onPNewFrame(dPacket* inPack) {
  
      lastFlag = 0;
  
  
  
      if (bufferEnabled) {
  
          buffer.push(QPixmap::fromImage(toQImageFromPMat(inPack->frame)));
  
      }
  
      else {
  
          if (playing) {
  
              /* Only process if this widget is playing */
  
              frameProcessing = true;
  
              lastImage.convertFromImage(toQImageFromPMat(inPack->frame));
  
              frameProcessing = false;
  
          }
  
      }
  
  
  
      if (lastFlag != -1 && !lastImage.isNull()) {
  
          connecting = false;
  
      }
  
      else {
  
          connecting = true;
  
      }
  
  }

  This is my Mat to QImage :

  QImage GLWidget::toQImageFromPMat(cv::Mat* mat) {
  
  
  
  
  
  
  
      return QImage(mat->data, mat->cols, mat->rows, QImage::Format_RGB888).rgbSwapped();

  NOTE : not converting does not result in CPU boost (at least not a significant one).

  Minimal verifiable example

  This program is large. I am going to paste GLWidget.cpp and GLWidget.h as well as Camera.h and Camera.cpp. You can put GLWidget into anything just as long as you spawn more than 6 of it. Camera relies on the CamUtils, but it is possible to just paste url in videocapture

  I also supplied CamUtils, just in case

  Camera.h :

  #pragma once
  
  #include <iostream>
  
  #include <vector>
  
  #include <fstream>
  
  #include <map>
  
  #include <string>
  
  #include <sstream>
  
  #include <algorithm>
  
  #include "FrameListener.h"
  
  #include 
  
  #include <thread>
  
  #include "CamUtils.h"
  
  #include <ctime>
  
  #include "dPacket.h"
  
  
  
  using namespace std;
  
  using namespace cv;
  
  
  
  class Camera
  
  {
  
  
  
      /*
  
          CLEANED UP!
  
          Camera now is only responsible for streaming and echoing captured frames.
  
          Frames are now wrapped into dPacket struct.
  
      */
  
  
  
  
  
  private:
  
      string id;
  
      vector clients;
  
      VideoCapture ipCam;
  
      string streamUrl;
  
      Size size;
  
      bool tryResetConnection = false;
  
  
  
      //TODO: Remove these as they are not going to be used going on:
  
      bool isPlaying = true;
  
      bool capture = true;
  
  
  
      //SECRET FEATURES:
  
      bool detect = false;
  
  
  
  
  
  public:
  
      Camera(string url, int width = 480, int height = 240, bool detect_=false);
  
      bool stream();
  
      void setReconnectable(bool newReconStatus);
  
      void addListener(FrameListener* client);
  
      vector<bool> getState();    // Returns current state: vector[0] stream state; vector[1] stream state; TODO: Remove this as this is no longer should control behaviour
  
      void killStream();
  
      bool getReconnectable();
  
  };
  
  
  
  </bool></ctime></thread></algorithm></sstream></string></map></fstream></vector></iostream>

  Camera.cpp

  #include "Camera.h"
  
  
  
  
  
  Camera::Camera(string url, int width, int height, bool detect_) // Default 240p
  
  {
  
      streamUrl = url; // Prepare url
  
      size = Size(width, height);
  
      detect = detect_;
  
  
  
  }
  
  
  
  void Camera::addListener(FrameListener* client) {
  
      clients.push_back(client);
  
  }
  
  
  
  
  
  /*
  
                  TEST CAMERAS(Paste into cameras.dViewer):
  
                  {"id":"96a73796-c129-46fc-9c01-40acd8ed7122","ip":"176.57.73.231","password":"null","username":"null"},
  
                  {"id":"96a73796-c129-46fc-9c01-40acd8ed7122","ip":"176.57.73.231","password":"null","username":"null"},
  
                  {"id":"96a73796-c129-46fc-9c01-40acd8ed7144","ip":"172.20.101.13","password":"admin","username":"root"}
  
                  {"id":"96a73796-c129-46fc-9c01-40acd8ed7144","ip":"172.20.101.13","password":"admin","username":"root"}
  
  
  
  */
  
  
  
  
  
  
  
  bool Camera::stream() {
  
      /* This function is meant to run on a separate thread and fill up the buffer independantly of
  
      main stream thread */
  
      //cv::setNumThreads(100);
  
      /* Rules for these slightly changed! */
  
      Mat pre;  // Grab initial undoctored frame
  
      //pre = Mat::zeros(size, CV_8UC1);
  
      Mat frame; // Final modified frame
  
      frame = Mat::zeros(size, CV_8UC1);
  
      if (!pre.isContinuous()) pre = pre.clone();
  
  
  
      ipCam.open(streamUrl, CAP_FFMPEG);
  
  
  
      while (ipCam.isOpened() && capture) {
  
          // If camera is opened wel need to capture and process the frame
  
          try {
  
              auto start = std::chrono::system_clock::now();
  
  
  
              ipCam >> pre;
  
  
  
              if (pre.empty()) {
  
                  /* Check for blank frame, return error if there is a blank frame*/
  
                  cerr << id << ": ERROR! blank frame grabbed\n";
  
                  for (FrameListener* i : clients) {
  
                      i->onNotification(1); // Notify clients about this shit
  
                  }
  
                  break;
  
              }
  
  
  
              else {
  
                  // Only continue if frame not empty
  
  
  
                  if (pre.cols != size.width && pre.rows != size.height) {
  
                      resize(pre, frame, size);
  
                      pre.release();
  
                  }
  
                  else {
  
                      frame = pre;
  
                  }
  
  
  
                  auto end = std::chrono::system_clock::now();
  
                  std::time_t ts = std::chrono::system_clock::to_time_t(end);
  
                  dPacket* pack = new dPacket{ id,&frame};
  
                  for (auto i : clients) {
  
                      i->onPNewFrame(pack);
  
                  }
  
                  frame.release();
  
                  delete pack;
  
              }
  
          }
  
  
  
          catch (int e) {
  
              cout << endl << "-----Exception during capture process! CODE " << e << endl;
  
          }
  
          // End camera manipulations
  
      }
  
  
  
      cout << "Camera timed out, or connection is closed..." << endl;
  
      if (tryResetConnection) {
  
          cout << "Reconnection flag is set, retrying after 3 seconds..." << endl;
  
          for (FrameListener* i : clients) {
  
              i->onNotification(-1); // Notify clients about this shit
  
          }
  
          this_thread::sleep_for(chrono::milliseconds(3000));
  
          stream();
  
      }
  
  
  
      return true;
  
  }
  
  
  
  
  
  void Camera::killStream(){
  
      tryResetConnection = false;
  
      capture = false;
  
      ipCam.release();
  
  }
  
  
  
  void Camera::setReconnectable(bool reconFlag) {
  
      tryResetConnection = reconFlag;
  
  }
  
  
  
  bool Camera::getReconnectable() {
  
      return tryResetConnection;
  
  }
  
  
  
  vector<bool> Camera::getState() {
  
      vector<bool> states;
  
      states.push_back(isPlaying);
  
      states.push_back(ipCam.isOpened());
  
      return states;
  
  }
  
  
  
  
  
  
  
  </bool></bool>

  GLWidget.h :

  #ifndef GLWIDGET_H
  
  #define GLWIDGET_H
  
  
  
  #include <qopenglwidget>
  
  #include <qmouseevent>
  
  #include "FrameListener.h"
  
  #include "Camera.h"
  
  #include "FrameListener.h"
  
  #include 
  
  #include "Camera.h"
  
  #include "CamUtils.h"
  
  #include 
  
  #include "dPacket.h"
  
  #include <chrono>
  
  #include <ctime>
  
  #include 
  
  #include "FullScreenVideo.h"
  
  #include <qmovie>
  
  #include "helper.h"
  
  #include <iostream>
  
  #include <qpainter>
  
  #include <qtimer>
  
  
  
  class Helper;
  
  
  
  class GLWidget : public QOpenGLWidget, public FrameListener
  
  {
  
      Q_OBJECT
  
  
  
  public:
  
      GLWidget(std::string camId, CamUtils *cUtils, int width, int height, bool denyFullScreen_ = false, bool detectFlag_=false, QWidget* parent = nullptr);
  
      void killStream();
  
      ~GLWidget();
  
  
  
  public slots:
  
      void animate();
  
      void setBufferEnabled(bool setState);
  
      void setCameraRetryConnection(bool setState);
  
      void GLUpdate();            // Call to update the widget
  
      void onRightClickMenu(const QPoint&amp; point);
  
  
  
  protected:
  
      void paintEvent(QPaintEvent* event) override;
  
      void onPNewFrame(dPacket* frame);
  
      void onNotification(int alert_code);
  
  
  
  
  
  private:
  
      // Objects and resourses
  
      Helper* helper;
  
      Camera* cam;
  
      CamUtils* camUtils;
  
      QTimer* timer; // Keep track of update
  
      QPixmap lastImage;
  
      QMovie* connMov;
  
      QMovie* test;
  
  
  
      QPixmap logo;
  
  
  
      // Control fields
  
      int width;
  
      int height;
  
      int camUtilsAddr;
  
      int elapsed;
  
      std::thread* camThread;
  
      std::string camId;
  
      bool denyFullScreen = false;
  
      bool playing = true;
  
      bool streaming = true;
  
      bool debug = false;
  
      bool connecting = true;
  
      int lastFlag = 0;
  
  
  
  
  
      // Debug fields
  
      std::chrono::high_resolution_clock::time_point lastFrameAt;
  
      std::chrono::high_resolution_clock::time_point now;
  
      std::chrono::duration<double> painTime; // time took to draw last frame
  
  
  
      //Buffer stuff
  
      std::queue<qpixmap> buffer;
  
      bool bufferEnabled = false;
  
      bool initialBuffer = false;
  
      bool buffering = true;
  
      bool frameProcessing = false;
  
  
  
  
  
  
  
      //Functions
  
      QImage toQImageFromPMat(cv::Mat* inFrame);
  
      void mousePressEvent(QMouseEvent* event) override;
  
      void drawImageGLLatest(QPainter* painter, QPaintEvent* event, int elapsed);
  
      void drawOnPaused(QPainter* painter, QPaintEvent* event, int elapsed);
  
      void drawOnStatus(int statusFlag, QPainter* painter, QPaintEvent* event, int elapsed);
  
  };
  
  
  
  #endif
  
  
  
  </qpixmap></double></qtimer></qpainter></iostream></qmovie></ctime></chrono></qmouseevent></qopenglwidget>

  GLWidget.cpp :

  #include "glwidget.h"
  
  #include <future>
  
  
  
  
  
  FullScreenVideo* fullScreen;
  
  
  
  GLWidget::GLWidget(std::string camId_, CamUtils* cUtils, int width_, int height_,  bool denyFullScreen_, bool detectFlag_, QWidget* parent)
  
      : QOpenGLWidget(parent), helper(helper)
  
  {
  
      cout &lt;&lt; "Player for CAMERA " &lt;&lt; camId_ &lt;&lt; endl;
  
  
  
      /* Underlying properties */
  
      camUtils = cUtils;
  
      cout &lt;&lt; "GLWidget Incoming CamUtils addr " &lt;&lt; camUtils &lt;&lt; endl;
  
      cout &lt;&lt; "GLWidget Set CamUtils addr " &lt;&lt; camUtils &lt;&lt; endl;
  
      camId = camId_;
  
      elapsed = 0;
  
      width = width_ + 5;
  
      height = height_ + 5;
  
      helper = new Helper();
  
      setFixedSize(width, height);
  
      denyFullScreen = denyFullScreen_;
  
  
  
      /* Camera capture thread */
  
      cam = new Camera(camUtils->getCameraStreamURL(camId), width_, height_, detectFlag_);
  
      cam->addListener(this);
  
  
  
      /* Sync states */
  
      vector<bool> initState = cam->getState();
  
      playing = initState[0];
  
      streaming = initState[1];
  
      cout &lt;&lt; "Initial states: " &lt;&lt; playing &lt;&lt; " " &lt;&lt; streaming &lt;&lt; endl;
  
      camThread = new std::thread(&amp;Camera::stream, cam);
  
      cout &lt;&lt; "================================================" &lt;&lt; endl;
  
  
  
      // Right click set up
  
      setContextMenuPolicy(Qt::CustomContextMenu);
  
  
  
  
  
      /* Loading gif */
  
      connMov = new QMovie("establishingConnection.gif");
  
      connMov->start();
  
      QString url = R"(RLC-logo.png)";
  
      logo = QPixmap(url);
  
      QTimer* timer = new QTimer(this);
  
      connect(timer, SIGNAL(timeout()), this, SLOT(GLUpdate()));
  
      timer->start(1000/30);
  
      playing = true;
  
  
  
  }
  
  
  
  /* SYSTEM */
  
  void GLWidget::animate()
  
  {
  
      elapsed = (elapsed + qobject_cast(sender())->interval()) % 1000;
  
      std::cout &lt;&lt; elapsed &lt;&lt; "\n";
  
  }
  
  
  
  
  
  void GLWidget::GLUpdate() {
  
      /* Process descisions before update call */
  
      if (bufferEnabled) {
  
          /* Process buffer before update */
  
          now = chrono::high_resolution_clock::now();
  
          std::chrono::duration timeSinceLastUpdate = now - lastFrameAt;
  
          if (timeSinceLastUpdate.count() > 25) {
  
              if (buffer.size() > 1 &amp;&amp; playing) {
  
                  lastImage.swap(buffer.front());
  
                  buffer.pop();
  
                  lastFrameAt = chrono::high_resolution_clock::now();
  
              }
  
          }
  
          //update(); // Update
  
      }
  
      else {
  
          /* No buffer */
  
      }
  
      repaint();
  
  }
  
  
  
  
  
  /* EVENTS */
  
  void GLWidget::onRightClickMenu(const QPoint&amp; point) {
  
      cout &lt;&lt; "Right click request got" &lt;&lt; endl;
  
  
  
      QPoint globPos = this->mapToGlobal(point);
  
      QMenu myMenu;
  
  
  
      if (!denyFullScreen) {
  
          myMenu.addAction("Open Full Screen");
  
      }
  
      myMenu.addAction("Toggle Debug Info");
  
  
  
  
  
      QAction* selected = myMenu.exec(globPos);
  
  
  
      if (selected) {
  
          string optiontxt = selected->text().toStdString();
  
  
  
          if (optiontxt == "Open Full Screen") {
  
              cout &lt;&lt; "Chose to open full screen of " &lt;&lt; camId &lt;&lt; endl;
  
              fullScreen = new FullScreenVideo(bufferEnabled, this);
  
              fullScreen->setUpView(camUtils, camId);
  
              fullScreen->show();
  
              playing = false;
  
          }
  
  
  
          if (optiontxt == "Toggle Debug Info") {
  
              cout &lt;&lt; "Chose to toggle debug of " &lt;&lt; camId &lt;&lt; endl;
  
              debug = !debug;
  
          }
  
      }
  
      else {
  
          cout &lt;&lt; "Chose nothing!" &lt;&lt; endl;
  
      }
  
  
  
  
  
  }
  
  
  
  
  
  
  
  void GLWidget::onPNewFrame(dPacket* inPack) {
  
      lastFlag = 0;
  
  
  
      if (bufferEnabled) {
  
          buffer.push(QPixmap::fromImage(toQImageFromPMat(inPack->frame)));
  
      }
  
      else {
  
          if (playing) {
  
              /* Only process if this widget is playing */
  
              frameProcessing = true;
  
              lastImage.convertFromImage(toQImageFromPMat(inPack->frame));
  
              frameProcessing = false;
  
          }
  
      }
  
  
  
      if (lastFlag != -1 &amp;&amp; !lastImage.isNull()) {
  
          connecting = false;
  
      }
  
      else {
  
          connecting = true;
  
      }
  
  }
  
  
  
  
  
  void GLWidget::onNotification(int alert) {
  
      lastFlag = alert;   
  
  }
  
  
  
  
  
  /* Paint events*/
  
  
  
  
  
  void GLWidget::paintEvent(QPaintEvent* event)
  
  {
  
      QPainter painter(this);
  
  
  
          if (lastFlag != 0 || connecting) {
  
              drawOnStatus(lastFlag, &amp;painter, event, elapsed);
  
          }
  
          else {
  
  
  
              /* Actual frame drawing */
  
              if (playing) {
  
                  if (!frameProcessing) {
  
                      drawImageGLLatest(&amp;painter, event, elapsed);
  
                  }
  
              }
  
              else {
  
                  drawOnPaused(&amp;painter, event, elapsed);
  
              }
  
          }
  
      painter.end();
  
  
  
  }
  
  
  
  
  
  /* DRAWING STUFF */
  
  
  
  void GLWidget::drawOnStatus(int statusFlag, QPainter* bgPaint, QPaintEvent* event, int elapsed) {
  
  
  
      QString str;
  
      QFont font("times", 15);
  
      bgPaint->eraseRect(QRect(0, 0, width, height));
  
      if (!lastImage.isNull()) {
  
          bgPaint->drawPixmap(QRect(0, 0, width, height), lastImage);
  
      }
  
      /* Test background painting */
  
      if (connecting) {
  
          string k = "Connecting to " + camUtils->getIp(camId);
  
          str.append(k.c_str());
  
      }
  
      else {
  
          switch (statusFlag) {
  
          case 1:
  
              str = "Blank frame received...";
  
              break;
  
  
  
          case -1:
  
              if (cam->getReconnectable()) {
  
                  str = "Connection lost, will try to reconnect.";
  
                  bgPaint->setOpacity(0.3);
  
              }
  
              else {
  
                  str = "Connection lost...";
  
                  bgPaint->setOpacity(0.3);
  
              }
  
  
  
              break;
  
          }
  
      }
  
  
  
      bgPaint->drawPixmap(QRect(0, 0, width, height), QPixmap::fromImage(connMov->currentImage()));
  
      bgPaint->setPen(Qt::red);
  
      bgPaint->setFont(font);
  
      QFontMetrics fm(font);
  
      const QRect kek(0, 0, fm.width(str), fm.height());
  
      QRect bound;
  
      bgPaint->setOpacity(1);
  
      bgPaint->drawText(bgPaint->viewport().width()/2 - kek.width()/2, bgPaint->viewport().height()/2 - kek.height(), str);
  
  
  
      bgPaint->drawPixmap(bgPaint->viewport().width() / 2 - logo.width()/2, height - logo.width() - 15, logo);
  
  
  
  }
  
  
  
  
  
  
  
  void GLWidget::drawOnPaused(QPainter* painter, QPaintEvent* event, int elapsed) {
  
      painter->eraseRect(0, 0, width, height);
  
      QFont font = painter->font();
  
      font.setPointSize(18);
  
      painter->setPen(Qt::red);
  
      QFontMetrics fm(font);
  
      QString str("Paused");
  
      painter->drawPixmap(QRect(0, 0, width, height),lastImage);
  
      painter->drawText(QPoint(painter->viewport().width() - fm.width(str), 50), str);
  
  
  
      if (debug) {
  
          QFont font = painter->font();
  
          font.setPointSize(25);
  
          painter->setPen(Qt::red);
  
          string camMess = "CAMID: " + camId;
  
          QString mess(camMess.c_str());
  
          string camIp = "IP: " + camUtils->getIp(camId);
  
          QString ipMess(camIp.c_str());
  
          QString bufferSize("Buffer size: " + QString::number(buffer.size()));
  
          QString lastFrameText("Last frame draw time: " + QString::number(painTime.count()) + "s");
  
          painter->drawText(QPoint(10, 50), mess);
  
          painter->drawText(QPoint(10, 60), ipMess);
  
          QString bufferState;
  
          if (bufferEnabled) {
  
              bufferState = QString("Experimental BUFFER is enabled!");
  
              QString currentBufferSize("Current buffer load: " + QString::number(buffer.size()));
  
              painter->drawText(QPoint(10, 80), currentBufferSize);
  
          }
  
          else {
  
              bufferState = QString("Experimental BUFFER is disabled!");
  
          }
  
          painter->drawText(QPoint(10, 70), bufferState);
  
          painter->drawText(QPoint(10, height - 25), lastFrameText);
  
      }
  
  }
  
  
  
  
  
  void GLWidget::drawImageGLLatest(QPainter* painter, QPaintEvent* event, int elapsed) {
  
      auto start = chrono::high_resolution_clock::now();
  
      painter->drawPixmap(QRect(0, 0, width, height), lastImage);
  
      if (debug) {
  
          QFont font = painter->font();
  
          font.setPointSize(25);
  
          painter->setPen(Qt::red);
  
          string camMess = "CAMID: " + camId;
  
          QString mess(camMess.c_str());
  
          string camIp = "IP: " + camUtils->getIp(camId);
  
          QString ipMess(camIp.c_str());
  
          QString bufferSize("Buffer size: " + QString::number(buffer.size()));
  
          QString lastFrameText("Last frame draw time: " + QString::number(painTime.count()) + "s");
  
          painter->drawText(QPoint(10, 50), mess);
  
          painter->drawText(QPoint(10, 60), ipMess);
  
          QString bufferState;
  
          if(bufferEnabled){
  
              bufferState = QString("Experimental BUFFER is enabled!");
  
              QString currentBufferSize("Current buffer load: " + QString::number(buffer.size()));
  
              painter->drawText(QPoint(10,80), currentBufferSize);
  
          }
  
          else {
  
              bufferState = QString("Experimental BUFFER is disabled!");
  
              QString currentBufferSize("Current buffer load: " + QString::number(buffer.size()));
  
              painter->drawText(QPoint(10, 80), currentBufferSize);
  
          }
  
          painter->drawText(QPoint(10, 70), bufferState);
  
          painter->drawText(QPoint(10, height - 25), lastFrameText);
  
  
  
      }
  
      auto end = chrono::high_resolution_clock::now();
  
      painTime = end - start;
  
  }
  
  
  
  
  
  
  
  /* END DRAWING STUFF */
  
  
  
  
  
  
  
  /* UI EVENTS */
  
  
  
  void GLWidget::mousePressEvent(QMouseEvent* e) {
  
  
  
      if (e->button() == Qt::LeftButton) {
  
          if (fullScreen == nullptr || !fullScreen->isVisible()) { // Do not unpause if window is opened
  
              playing = !playing;
  
          }
  
      }
  
  
  
      if (e->button() == Qt::RightButton) {
  
          onRightClickMenu(e->pos());
  
      }
  
  }
  
  
  
  
  
  
  
  /* Utilities */
  
  QImage GLWidget::toQImageFromPMat(cv::Mat* mat) {
  
  
  
  
  
  
  
      return QImage(mat->data, mat->cols, mat->rows, QImage::Format_RGB888).rgbSwapped();
  
  
  
  
  
  
  
  }
  
  
  
  /* State control */
  
  
  
  void GLWidget::killStream() {
  
      cam->killStream();
  
      camThread->join();
  
  }
  
  
  
  void GLWidget::setBufferEnabled(bool newBufferState) {
  
      cout &lt;&lt; "Player: " &lt;&lt; camId &lt;&lt; ", buffer state updated: " &lt;&lt; newBufferState &lt;&lt; endl;
  
      bufferEnabled = newBufferState;
  
      buffer.empty();
  
  }
  
  
  
  void GLWidget::setCameraRetryConnection(bool newState) {
  
      cam->setReconnectable(newState);
  
  }
  
  
  
  /* Destruction */
  
  GLWidget::~GLWidget() {
  
      cam->killStream();
  
      camThread->join();
  
  }
  
  </bool></future>

  CamUtils.h :

  #pragma once
  
  #include <iostream>
  
  #include <vector>
  
  #include <fstream>
  
  #include <map>
  
  #include <string>
  
  #include <sstream>
  
  #include <algorithm>
  
  #include <nlohmann></nlohmann>json.hpp>
  
  
  
  using namespace std;
  
  using json = nlohmann::json;
  
  
  
  class CamUtils
  
  {
  
  private:
  
  
  
      string camDb = "cameras.dViewer";
  
      map> cameraList; // Legacy
  
      json cameras;
  
      ofstream dbFile;
  
      bool dbExists(); // Always hard coded
  
  
  
      /* Old IMPLEMENTATION */
  
      void writeLineToDb_(const string&amp; content, bool append = false);
  
      void loadCameras_();
  
  
  
      /* JSON based */
  
      void loadCameras();
  
  
  
  public:
  
      CamUtils();
  
      string generateRandomString(size_t length);
  
      string getCameraStreamURL(string cameraId) const;
  
      string saveCamera(string ip, string username, string pass); // Return generated id
  
      vector<string> listAllCameraIds();
  
      string getIp(string cameraId);
  
  };
  
  
  
  
  
  </string></algorithm></sstream></string></map></fstream></vector></iostream>

  CamUtils.cpp :

  #include "CamUtils.h"
  
  #pragma comment(lib, "rpcrt4.lib")  // UuidCreate - Minimum supported OS Win 2000
  
  #include 
  
  #include <iostream>
  
  
  
  CamUtils::CamUtils()
  
  {
  
      if (!dbExists()) {
  
          ofstream dbFile;
  
          dbFile.open(camDb);
  
          cameras["cameras"] = json::array();
  
          dbFile &lt;&lt; cameras &lt;&lt; std::endl;
  
          dbFile.close();
  
  
  
      }
  
      else {
  
          loadCameras();
  
      }
  
  }
  
  
  
  
  
  
  
  
  
  vector<string> CamUtils::listAllCameraIds() {
  
      vector<string> ids;
  
      cout &lt;&lt; "IN LIST " &lt;&lt; endl;
  
      for (auto&amp; cam : cameras["cameras"]) {
  
          ids.push_back(cam["id"].get<string>());
  
          //cout &lt;&lt; cam["id"].get<string>() &lt;&lt; std::endl;
  
      }
  
      return ids;
  
  }
  
  
  
  string CamUtils::getIp(string id) {
  
      vector<string> camDetails = cameraList[id];
  
      string ip = "NO IP WILL DISPLAYED UNTIL I FIGURE OUT A BUG";
  
      for (auto&amp; cam : cameras["cameras"]) {
  
          if (id == cam["id"]) {
  
              ip = cam["ip"].get<string>();
  
          }
  
      }
  
  
  
      return ip;
  
  }
  
  
  
  string CamUtils::getCameraStreamURL(string id) const {
  
      string url = "err"; // err is the default, it will be overwritten in case id is found, dont forget to check for it
  
  
  
      for (auto&amp; cam : cameras["cameras"]) {
  
          if (id == cam["id"]) {
  
              if (cam["username"].get<string>() == "null") {
  
                  url = "rtsp://" + cam["ip"].get<string>() + ":554/axis-media/media.amp?tcp";
  
              }
  
              else {
  
                  url = "rtsp://" + cam["username"].get<string>() + ":" + cam["password"].get<string>() + "@" + cam["ip"].get<string>() + ":554/axis-media/media.amp?streamprofile=720_30";
  
              }
  
          }
  
      }
  
  
  
      return url;  // Dont forget to check for err when using this shit
  
  }
  
  
  
  
  
  string CamUtils::saveCamera(string ip, string username, string password) {
  
      UUID uid;
  
      UuidCreate(&amp;uid);
  
      char* str;
  
      UuidToStringA(&amp;uid, (RPC_CSTR*)&amp;str);
  
      string id = str;
  
      cout &lt;&lt; "GEN: " &lt;&lt; id &lt;&lt; endl;
  
      json cam = json({}); //Create emtpy object
  
      cam["id"] = id;
  
      cam["ip"] = ip;
  
      cam["username"] = username;
  
      cam["password"] = password;
  
      cameras["cameras"].push_back(cam);
  
      std::ofstream out(camDb);
  
      out &lt;&lt; cameras &lt;&lt; std::endl;
  
      cout &lt;&lt; cameras["cameras"] &lt;&lt; endl;
  
  
  
      cout &lt;&lt; "Saved camera as " &lt;&lt; id &lt;&lt; endl;
  
      return id;
  
  }
  
  
  
  
  
  bool CamUtils::dbExists() {
  
      ifstream dbFile(camDb);
  
      return (bool)dbFile;
  
  }
  
  
  
  
  
  
  
  
  
  
  
  void CamUtils::loadCameras() {
  
      cout &lt;&lt; "Load call" &lt;&lt; endl;
  
      ifstream dbFile(camDb);
  
      string line;
  
      string wholeFile;
  
  
  
      while (std::getline(dbFile, line)) {
  
          cout &lt;&lt; line &lt;&lt; endl;
  
          wholeFile += line;
  
      }
  
      try {
  
          cameras = json::parse(wholeFile);
  
          //cout &lt;&lt; cameras["cameras"] &lt;&lt; endl;
  
  
  
      }
  
      catch (exception e) {
  
          cout &lt;&lt; e.what() &lt;&lt; endl;
  
      }
  
      dbFile.close();
  
  }
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  /*
  
      LEGACY CODE, TO BE REMOVED!
  
  
  
  */
  
  
  
  
  
  
  
  void CamUtils::loadCameras_() {
  
      /* 
  
          LEGACY CODE:
  
          This used to be the way to load cameras, but I moved on to JSON based configuration so this is no longer needed and will be removed soon
  
      */
  
  
  
      ifstream dbFile(camDb);
  
      string line;
  
      while (std::getline(dbFile, line)) {
  
          /*
  
              This function load camera data to the map:
  
              The order MUST be the following: 0:ID, 1:IP, 2:USERNAME, 3:PASSWORD.
  
              Always delimited with | no spaces between!
  
          */
  
          if (!line.empty()) {
  
              stringstream ss(line);
  
              string item;
  
              vector<string> splitString;
  
  
  
              while (std::getline(ss, item, '|')) {
  
                  splitString.push_back(item);
  
              }
  
              if (splitString.size() > 0) {
  
                  /* Dont even parse if the program didnt split right*/
  
                  //cout &lt;&lt; "Split string: " &lt;&lt; splitString.size() &lt;&lt; "\n";
  
                  for (int i = 0; i &lt; (splitString.size()); i++) cameraList[splitString[0]].push_back(splitString[i]);
  
              }
  
          }
  
      }
  
  }
  
  
  
  
  
  
  
  void CamUtils::writeLineToDb_(const string &amp; content, bool append) {
  
      ofstream dbFile;
  
      cout &lt;&lt; "Creating?";
  
      if (append) {
  
          dbFile.open(camDb, ios_base::app);
  
      }
  
      else {
  
          dbFile.open(camDb);
  
      }
  
  
  
      dbFile &lt;&lt; content.c_str() &lt;&lt; "\r\n";
  
      dbFile.flush();
  
  }
  
  
  
  /* JSON Reworx */
  
  
  
  
  
  
  
  
  
  string CamUtils::generateRandomString(size_t length)
  
  {
  
      const char* charmap = "ABCDEFGHIJKLMNOPQRSTUVWXYZ";
  
      const size_t charmapLength = strlen(charmap);
  
      auto generator = [&amp;]() { return charmap[rand() % charmapLength]; };
  
      string result;
  
      result.reserve(length);
  
      generate_n(back_inserter(result), length, generator);
  
      return result;
  
  }
  
  </string></string></string></string></string></string></string></string></string></string></string></string></iostream>

  End of example

  How would I go about decreasing CPU usage when dealing with large amount of streams ?

• CCPA vs GDPR : Understanding Their Impact on Data Analytics

  19 mars, par Alex Carmona

  With over 400 million internet users in Europe and 331 million in the US (11% of which reside in California alone), understanding the nuances of privacy laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) is crucial for compliant and ethical consumer data collection.

  Navigating this compliance landscape can be challenging for businesses serving European and Californian markets.

  This guide explores the key differences between CCPA and GDPR, their impact on data analytics, and how to ensure your business meets these essential privacy requirements.

  What is the California Consumer Privacy Act (CCPA) ?

  The California Consumer Privacy Act (CCPA) is a data privacy law that gives California consumers control over their personal information. It applies to for-profit businesses operating in California that meet specific criteria related to revenue, data collection and sales.

  Origins and purpose

  The CCPA addresses growing concerns about data privacy and how businesses use personal information in California. The act passed in 2018 and went into effect on 1 January 2020.

  Key features

  • Grants consumers the right to know what personal information is collected
  • Provides the right to delete personal information
  • Allows consumers to opt out of the sale of their personal information
  • Prohibits discrimination against consumers who exercise their CCPA rights

  Key definitions under the CCPA framework

  • Business : A for-profit entity doing business in California and meeting one or more of these conditions :
    • Has annual gross revenues over $25 million ;
    • Buys, receives, sells or shares 50,000 or more consumers’ personal information ; or
    • Derives 50% or more of its annual revenues from selling consumers’ personal information
  • Consumer : A natural person who is a California resident
  • Personal Information : Information that could be linked to, related to or used to identify a consumer or household, such as online identifiers, IP addresses, email addresses, social security numbers, cookie identifiers and more

  What is the General Data Protection Regulation (GDPR) ?

  The General Data Protection Regulation (GDPR) is a data privacy and protection law passed by the European Union (EU). It’s one of the strongest and most influential data privacy laws worldwide and applies to all organisations that process the personal data of individuals in the EU.

  Origins and purpose

  The GDPR was passed in 2016 and went into effect on 25 May 2018. It aims to harmonise data privacy laws in Europe and give people in the European Economic Area (EEA) privacy rights and control over their data.

  Key features

  • Applies to all organisations that process the personal data of individuals in the EEA
  • Grants individuals a wide range of privacy rights over their data
  • Requires organisations to obtain explicit and informed consent for most data processing
  • Mandates appropriate security measures to protect personal data
  • Imposes significant fines and penalties for non-compliance

  Key definitions under the GDPR framework

  • Data Subject : An identified or identifiable person
  • Personal Data : Any information relating to a data subject
  • Data Controller : The entity or organisation that determines how personal data is processed and what for
  • Data Processor : The entity or organisation that processes the data on behalf of the controller

  CCPA vs. GDPR : Key similarities

  The CCPA and GDPR enhance consumer privacy rights and give individuals greater control over their data.

  Dimension	CCPA	GDPR
  Purpose	Protect consumer privacy	Protect individual data rights
  Key Rights	Right to access, delete and opt out of sale	Right to access, rectify, erase and restrict processing
  Transparency	Requires transparency around data collection and use	Requires transparency about data collection, processing and use

  CCPA vs. GDPR : Key differences

  While they have similar purposes, the CCPA and GDPR differ significantly in their scope, approach and specific requirements.

  Dimension	CCPA	GDPR
  Scope	For-profit businesses only	All organisations processing EU consumer data
  Territorial Reach	California-based natural persons	All data subjects within the EEA
  Consent	Opt-out system	Opt-in system
  Penalties	Per violation based on its intentional or negligent nature	Case-by-case based on comprehensive assessment
  Individual Rights	Narrower (relative to GDPR)	Broader (relative to CCPA)

  CCPA vs. GDPR : A multi-dimensional comparison

  The previous sections gave a broad overview of the similarities and differences between CCPA and GDPR. Let’s now examine nine key dimensions where these regulations converge or diverge and discuss their impact on data analytics.

  

  #1. Scope and territorial reach

  The GDPR has a much broader scope than the CCPA. It applies to all organisations that process the personal data of individuals in the EEA, regardless of their business model, purpose or physical location.

  The CCPA applies to medium and large for-profit businesses that derive a substantial portion of their earnings from selling Californian consumers’ personal information. It doesn’t apply to non-profits, government agencies or smaller for-profit companies.

  Impact on data analytics

  The difference in scope significantly impacts data analytics practices. Smaller businesses may not need to comply with either regulation, some may only need to follow the CCPA, while most global businesses must comply with both. This often requires different methods for collecting and processing data in California, Europe, and elsewhere.

  #2. Penalties and fines for non-compliance

  Both the CCPA and GDPR impose penalties for non-compliance, but the severity of fines differs significantly :

  CCPA	Maximum penalty
  	$2,500 per unintentional violation $7,500 per intentional violation

  “Per violation” means per violation per impacted consumer. For example, three intentional CCPA violations affecting 1,000 consumers would result in 3,000 total violations and a $22.5 million maximum penalty (3,000 × $7,500).

  

  The largest CCPA fine to date was Zoom’s $85 million settlement in 2021.

  

  In contrast, the GDPR has resulted in 2,248 fines totalling almost €6.6 billion since 2018 — €2.4 billion of which were for non-compliance.

  GDPR	Maximum penalty
  	€20 million or 4% of all revenue earned the previous year

  So far, the biggest fine imposed under the GDPR was Meta’s €1.2 billion fine in May 2023 — 15 times more than Zoom had to pay California.

  Impact on data analytics

  The significant difference in potential fines demonstrates the importance of regulatory compliance for data analytics professionals. Non-compliance can have severe financial consequences, directly affecting budget allocation and business operations.

  Businesses must ensure their data collection, storage and processing practices comply with regulations in both Europe and California.

  Choosing privacy-first, compliance-ready analytics platforms like Matomo is instrumental for mitigating non-compliance risks.

  #3. Data subject rights and consumer rights

  The CCPA and GDPR give people similar rights over their data, but their limitations and details differ.

  Rights common to the CCPA and GDPR

  • Right to Access/Know : People can access their personal information and learn what data is collected, its source, its purpose and how it’s shared
  • Right to Delete/Erasure : People can request the deletion of their personal information, with some exceptions
  • Right to Non-Discrimination : Businesses can’t discriminate against people who exercise their privacy rights

  Consumer rights unique to the CCPA

  • Right to Opt Out of Sale : Consumers can prohibit the sale of their personal information
  • Right to Notice : Businesses must inform consumers about data collection practices
  • Right to Disclosure : Consumers can request specific information collected about them

  Data subject rights unique to the GDPR

  • Right to be Informed : Broader transparency requirements encompass data retention, automated decision-making and international transfers
  • Right to Rectification : Data subjects may request the correction of inaccurate data
  • Right to Restrict Processing : Consumers may limit data use in certain situations
  • Right to Data Portability : Businesses must provide individual consumer data in a secure, portable format when requested
  • Right to Withdraw Consent : Consumers may withdraw previously granted consent to data processing

  	CCPA	GDPR
  Right to Access or Know	✓	✓
  Right to Delete or Erase	✓	✓
  Right to Non-Discrimination	✓	✓
  Right to Opt-Out	✓
  Right to Notice	✓
  Right to Disclosure	✓
  Right to be Informed		✓
  Right to Rectification		✓
  Right to Restrict Processing		✓
  Right to Data Portability		✓
  Right to Withdraw Consent		✓

  Impact on data analytics

  Data analysts must understand these rights and ensure compliance with both regulations, which could potentially require separate data handling processes for EU and California consumers.

  #4. Opt-out vs. opt-in

  The CCPA generally follows an opt-out model, while the GDPR requires explicit consent from individuals before processing their data.

  Impact on data analytics

  For CCPA compliance, businesses can collect data by default if they provide opt-out mechanisms. Failing to process opt-out requests can result in severe penalties, like Sephora’s $1.2 million fine.

  Under GDPR, organisations must obtain explicit consent before collecting any data, which can limit the amount of data available for analysis.

  #5. Parental consent

  The CCPA and GDPR have provisions regarding parental consent for processing children’s data. The CCPA requires parental consent for children under 13, while the GDPR sets the age at 16, though member states can lower it to 13.

  Impact on data analytics

  This requirement significantly impacts businesses targeting younger audiences. In Europe and the US, companies must implement different methods to verify users’ ages and obtain parental consent when necessary.

  The California Attorney General’s Office recently fined Tilting Point Media LLC $500,000 for sharing children’s data without parental consent.

  #6. Data security requirements

  Both regulations require businesses to implement adequate security measures to protect personal data. However, the GDPR has more prescriptive requirements, outlining specific security measures and emphasising a risk-based approach.

  Impact on data analytics

  Data analytics professionals must ensure that data is processed and stored securely to avoid breaches and potential fines.

  #7. International data transfers

  Both the CCPA and GDPR address international data transfers. Under the CCPA, businesses must only inform consumers about international transfers. The GDPR has stricter requirements, including ensuring adequate data protection safeguards for transfers outside the EEA.

  

  Other rules, like the Payment Services Directive 2 (PSD2), also affect international data transfers, especially in the financial industry.

  PSD2 requires strong customer authentication and secure communication channels for payment services. This adds complexity to cross-border data flows.

  Impact on data analytics

  The primary impact is on businesses serving European residents from outside Europe. Processing data within the European Union is typically advisable. Meta’s record-breaking €1.2 billion fine was specifically for transferring data from the EEA to the US without sufficient safeguards.

  Choosing the right analytics platform helps avoid these issues.

  For example, Matomo offers a free, open-source, self-hosted analytics platform you can deploy anywhere. You can also choose a managed, GDPR-compliant cloud analytics solution with all data storage and processing servers within the EU (in Germany), ensuring your data never leaves the EEA.

  #8. Enforcement mechanisms

  The California Attorney General is responsible for enforcing CCPA requirements, while in Europe, the Data Protection Authority (DPA) in each EU member state enforces GDPR requirements.

  Impact on data analytics

  Data analytics professionals should be familiar with their respective enforcement bodies and their powers to support compliance efforts and minimise the risk of fines and penalties.

  #9. Legal basis for personal data processing

  The GDPR outlines six legal grounds for processing personal data :

  • Consent
  • Contract
  • Legal obligation
  • Vital interests
  • Public task
  • Legitimate interests

  The CCPA doesn’t explicitly define lawful bases but focuses on consumer rights and transparency in general.

  Impact on data analytics

  Businesses subject to the GDPR must identify and document a valid lawful basis for each processing activity.

  Compliance rules under CCPA and GDPR

  Complying with the CCPA and GDPR requires a comprehensive approach to data privacy. Here’s a summary of the essential compliance rules for each framework :

  

  CCPA compliance rules

  • Create clear and concise privacy policies outlining data collection and use practices
  • Give consumers the right to opt-out
  • Respond to consumer requests to access, delete and correct their personal information
  • Implement reasonable security measures for consumers’ personal data protection
  • Never discriminate against consumers who exercise their CCPA rights

  GDPR compliance rules

  • Obtain explicit and informed consent for data processing activities
  • Implement technical and organisational controls to safeguard personal data
  • Designate a Data Protection Officer (DPO) if necessary
  • Perform data protection impact assessments (DPIAs) for high-risk processing activities
  • Maintain records of processing activities
  • Promptly report data breaches to supervisory authorities

  Navigating the CCPA and GDPR with confidence

  Understanding the nuances of the CCPA and GDPR is crucial for businesses operating in the US and Europe. These regulations significantly impact data collection and analytics practices.

  Implementing robust data security practices and prioritising privacy and compliance are essential to avoid severe penalties and build trust with today’s privacy-conscious consumers.

  Privacy-centric analytics platforms like Matomo enable businesses to collect, analyse and use data responsibly and transparently, extracting valuable insights while maintaining compliance with both CCPA and GDPR requirements.

  Start your 21-day free trial today !

  no credit card required

• ffmpeg produces duplicate pts with "wallclock_as_timestamps 1" option on MKV

  15 avril 2024, par Jax2171

  I need to get real time reference of every keyframe captured by an IP camera. The -wallclock_as_timestamps 1 option seems to do the trick for us, however we are forced to replace the TS output container with MKV to get a correct PTS epoch value 1712996356.833000.

  


  Here is the ffmpeg command used :

  


  ffmpeg -report -use_wallclock_as_timestamps 1 -rtsp_transport tcp -i rtsp://user:password1@192.168.5.21/cam/realmonitor?channel=1channel1[1]=1subtype=0 -c:v copy -c:a aac -copyts -f matroska -y rec.mkv


  


  The capture process runs without any relevant worning or error messages.

  


  However, playing the captured video with any player shows very short and evident but very annoying lags. Upon investigation I discovered that many frame PTSs have the same value. The command I used to show duplicate PTSs is as follows :

  


  ffprobe -v error -show_entries frame=pkt_pts_time -select_streams v -of csv=p=0 rec.mkv | sort | uniq -d


  


  On a recording of about 10 minutes the result of the duplicate PTS is the following :

  


  1713086493.367000
1713086493.368000
1713086493.370000
1713086493.372000
1713086543.714000
1713086558.793000
1713086558.817000
1713086558.872000
1713086561.780000
1713086564.642000
1713086564.657000
1713086564.778000
1713086565.794000
...


  


  I'm not sure if the lag problem is caused by this, however the problem does not occur with the TS container, which however I cannot use due to the PTS values being roundly 33 bit.

  


  The -vsync 0 or -vsync 2 options on input or output didn't help.

  


  This is the log using the -report option :

  


      ffmpeg started on 2024-04-15 at 09:04:38
Report written to "ffmpeg-20240415-090438.log"
Log level: 48
Command line:
ffmpeg -report -stats -hide_banner -use_wallclock_as_timestamps 1 -rtsp_transport tcp -i "rtsp://user:password1@192.168.5.21/cam/realmonitor?channel=1channel1[1]=1subtype=0" -c:v copy -c:a aac -copyts -f matroska -y rec.mkv
Splitting the commandline.
Reading option '-report' ... matched as option 'report' (generate a report) with argument '1'.
Reading option '-stats' ... matched as option 'stats' (print progress report during encoding) with argument '1'.
Reading option '-hide_banner' ... matched as option 'hide_banner' (do not show program banner) with argument '1'.
Reading option '-use_wallclock_as_timestamps' ... matched as AVOption 'use_wallclock_as_timestamps' with argument '1'.
Reading option '-rtsp_transport' ... matched as AVOption 'rtsp_transport' with argument 'tcp'.
Reading option '-i' ... matched as input url with argument 'rtsp://user:password1@192.168.5.21/cam/realmonitor?channel=1channel1[1]=1subtype=0'.
Reading option '-c:v' ... matched as option 'c' (codec name) with argument 'copy'.
Reading option '-c:a' ... matched as option 'c' (codec name) with argument 'aac'.
Reading option '-copyts' ... matched as option 'copyts' (copy timestamps) with argument '1'.
Reading option '-f' ... matched as option 'f' (force format) with argument 'matroska'.
Reading option '-y' ... matched as option 'y' (overwrite output files) with argument '1'.
Reading option 'rec.mkv' ... matched as output url.
Finished splitting the commandline.
Parsing a group of options: global .
Applying option report (generate a report) with argument 1.
Applying option stats (print progress report during encoding) with argument 1.
Applying option hide_banner (do not show program banner) with argument 1.
Applying option copyts (copy timestamps) with argument 1.
Applying option y (overwrite output files) with argument 1.
Successfully parsed a group of options.
Parsing a group of options: input url rtsp://user:password1@192.168.5.21/cam/realmonitor?channel=1channel1[1]=1subtype=0.
Successfully parsed a group of options.
Opening an input file: rtsp://user:password1@192.168.5.21/cam/realmonitor?channel=1channel1[1]=1subtype=0.
[tcp @ 0x1646660] No default whitelist set
[tcp @ 0x1646660] Original list of addresses:
[tcp @ 0x1646660] Address 192.168.5.21 port 554
[tcp @ 0x1646660] Interleaved list of addresses:
[tcp @ 0x1646660] Address 192.168.5.21 port 554
[tcp @ 0x1646660] Starting connection attempt to 192.168.5.21 port 554
[tcp @ 0x1646660] Successfully connected to 192.168.5.21 port 554
[rtsp @ 0x1645e70] SDP:
v=0
o=- 2251950012 2251950012 IN IP4 0.0.0.0
s=Media Server
c=IN IP4 0.0.0.0
t=0 0
a=control:*
a=packetization-supported:DH
a=rtppayload-supported:DH
a=range:npt=now-
a=x-packetization-supported:IV
a=x-rtppayload-supported:IV
m=video 0 RTP/AVP 96
a=control:trackID=0
a=framerate:25.000000
a=rtpmap:96 H264/90000
a=fmtp:96 packetization-mode=1;profile-level-id=4D4028;sprop-parameter-sets=Z01AKKaAeAIn5ZuAgICgAAADACAAAAZQgAA=,aO48gAA=
a=recvonly
m=audio 0 RTP/AVP 97
a=control:trackID=1
a=rtpmap:97 MPEG4-GENERIC/16000
a=fmtp:97 streamtype=5;profile-level-id=1;mode=AAC-hbr;sizelength=13;indexlength=3;indexdeltalength=3;config=1408
a=recvonly

[rtsp @ 0x1645e70] video codec set to: h264
[rtsp @ 0x1645e70] RTP Packetization Mode: 1
[rtsp @ 0x1645e70] RTP Profile IDC: 4d Profile IOP: 40 Level: 28
[rtsp @ 0x1645e70] Extradata set to 0x164af98 (size: 39)
[rtsp @ 0x1645e70] audio codec set to: aac
[rtsp @ 0x1645e70] audio samplerate set to: 16000
[rtsp @ 0x1645e70] audio channels set to: 1
[rtsp @ 0x1645e70] setting jitter buffer size to 0
[rtsp @ 0x1645e70] setting jitter buffer size to 0
[rtsp @ 0x1645e70] hello state=0
Failed to parse interval end specification ''
[h264 @ 0x164ab30] nal_unit_type: 7(SPS), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 8(PPS), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 7(SPS), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 8(PPS), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 7(SPS), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 8(PPS), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 5(IDR), nal_ref_idc: 3
[h264 @ 0x164ab30] Format yuvj420p chosen by get_format().
[h264 @ 0x164ab30] Reinit context to 1920x1088, pix_fmt: yuvj420p
[h264 @ 0x164ab30] nal_unit_type: 1(Coded slice of a non-IDR picture), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 1(Coded slice of a non-IDR picture), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 1(Coded slice of a non-IDR picture), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 1(Coded slice of a non-IDR picture), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 1(Coded slice of a non-IDR picture), nal_ref_idc: 3
[h264 @ 0x164ab30] nal_unit_type: 1(Coded slice of a non-IDR picture), nal_ref_idc: 3
[rtsp @ 0x1645e70] All info found
Input #0, rtsp, from 'rtsp://user:password1@192.168.5.21/cam/realmonitor?channel=1channel1[1]=1subtype=0':
  Metadata:
    title           : Media Server
  Duration: N/A, start: 1713164678.794625, bitrate: N/A
    Stream #0:0, 22, 1/90000: Video: h264 (Main), yuvj420p(pc, bt709, progressive), 1920x1080, 25 fps, 25 tbr, 90k tbn, 50 tbc
    Stream #0:1, 15, 1/16000: Audio: aac (LC), 16000 Hz, mono, fltp
Successfully opened the file.
Parsing a group of options: output url rec.mkv.
Applying option c:v (codec name) with argument copy.
Applying option c:a (codec name) with argument aac.
Applying option f (force format) with argument matroska.
Successfully parsed a group of options.
Opening an output file: rec.mkv.
[file @ 0x1699f30] Setting default whitelist 'file,crypto,data'
Successfully opened the file.
Stream mapping:
  Stream #0:0 -> #0:0 (copy)
  Stream #0:1 -> #0:1 (aac (native) -> aac (native))
Press [q] to stop, [?] for help
cur_dts is invalid st:0 (0) [init:1 i_done:0 finish:0] (this is harmless if it occurs once at the start per stream)
cur_dts is invalid st:1 (0) [init:0 i_done:0 finish:0] (this is harmless if it occurs once at the start per stream)
detected 4 logical cores
[graph_0_in_0_1 @ 0x1682bb0] Setting 'time_base' to value '1/16000'
[graph_0_in_0_1 @ 0x1682bb0] Setting 'sample_rate' to value '16000'
[graph_0_in_0_1 @ 0x1682bb0] Setting 'sample_fmt' to value 'fltp'
[graph_0_in_0_1 @ 0x1682bb0] Setting 'channel_layout' to value '0x4'
[graph_0_in_0_1 @ 0x1682bb0] tb:1/16000 samplefmt:fltp samplerate:16000 chlayout:0x4
[format_out_0_1 @ 0x187f2e0] Setting 'sample_fmts' to value 'fltp'
[format_out_0_1 @ 0x187f2e0] Setting 'sample_rates' to value '96000|88200|64000|48000|44100|32000|24000|22050|16000|12000|11025|8000|7350'
[AVFilterGraph @ 0x164fd70] query_formats: 4 queried, 9 merged, 0 already done, 0 delayed
[matroska @ 0x169c330] get_metadata_duration returned: 0
Output #0, matroska, to 'rec.mkv':
  Metadata:
    title           : Media Server
    encoder         : Lavf58.45.100
    Stream #0:0, 0, 1/1000: Video: h264 (Main) (H264 / 0x34363248), yuvj420p(pc, bt709, progressive), 1920x1080, q=2-31, 25 fps, 25 tbr, 1k tbn, 90k tbc
    Stream #0:1, 0, 1/1000: Audio: aac (LC) ([255][0][0][0] / 0x00FF), 16000 Hz, mono, fltp, 69 kb/s
    Metadata:
      encoder         : Lavc58.91.100 aac
cur_dts is invalid st:0 (0) [init:1 i_done:0 finish:0] (this is harmless if it occurs once at the start per stream)
cur_dts is invalid st:1 (0) [init:1 i_done:0 finish:0] (this is harmless if it occurs once at the start per stream)
cur_dts is invalid st:0 (0) [init:1 i_done:0 finish:0] (this is harmless if it occurs once at the start per stream)
[matroska @ 0x169c330] Starting new cluster with timestamp 1713164678731 at offset 770 bytes
[matroska @ 0x169c330] Writing block of size 581 with pts 1713164678731, dts 1713164678731, duration 64 at relative offset 14 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 517 with pts 1713164678795, dts 1713164678795, duration 64 at relative offset 602 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 376900 with pts 1713164678872, dts 1713164678872, duration 40 at relative offset 1126 in cluster at offset 770. TrackNumber 1, keyframe 1
[matroska @ 0x169c330] Writing block of size 8172 with pts 1713164678912, dts 1713164678912, duration 40 at relative offset 378034 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 672 with pts 1713164678912, dts 1713164678912, duration 64 at relative offset 386213 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 550 with pts 1713164679177, dts 1713164679177, duration 64 at relative offset 386892 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7654 with pts 1713164679178, dts 1713164679178, duration 40 at relative offset 387449 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 7483 with pts 1713164679213, dts 1713164679213, duration 40 at relative offset 395110 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 7703 with pts 1713164679242, dts 1713164679242, duration 40 at relative offset 402600 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 565 with pts 1713164679242, dts 1713164679242, duration 64 at relative offset 410310 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7650 with pts 1713164679271, dts 1713164679271, duration 40 at relative offset 410882 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 585 with pts 1713164679271, dts 1713164679271, duration 64 at relative offset 418539 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 8682 with pts 1713164679301, dts 1713164679301, duration 40 at relative offset 419131 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 8888 with pts 1713164679330, dts 1713164679330, duration 40 at relative offset 427820 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 506 with pts 1713164679330, dts 1713164679330, duration 64 at relative offset 436715 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 8019 with pts 1713164679360, dts 1713164679360, duration 40 at relative offset 437228 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 7919 with pts 1713164679361, dts 1713164679361, duration 40 at relative offset 445254 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 7822 with pts 1713164679361, dts 1713164679361, duration 40 at relative offset 453180 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 699 with pts 1713164679361, dts 1713164679361, duration 64 at relative offset 461009 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 619 with pts 1713164679361, dts 1713164679361, duration 64 at relative offset 461715 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7768 with pts 1713164679362, dts 1713164679362, duration 40 at relative offset 462341 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 8469 with pts 1713164679362, dts 1713164679362, duration 40 at relative offset 470116 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 601 with pts 1713164679362, dts 1713164679362, duration 64 at relative offset 478592 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 559 with pts 1713164679363, dts 1713164679363, duration 64 at relative offset 479200 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 8265 with pts 1713164679366, dts 1713164679366, duration 40 at relative offset 479766 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 7766 with pts 1713164679406, dts 1713164679406, duration 40 at relative offset 488038 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 531 with pts 1713164679415, dts 1713164679415, duration 64 at relative offset 495811 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7753 with pts 1713164679446, dts 1713164679446, duration 40 at relative offset 496349 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 8274 with pts 1713164679486, dts 1713164679486, duration 40 at relative offset 504109 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 569 with pts 1713164679496, dts 1713164679496, duration 64 at relative offset 512390 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 8445 with pts 1713164679526, dts 1713164679526, duration 40 at relative offset 512966 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 522 with pts 1713164679535, dts 1713164679535, duration 64 at relative offset 521418 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7922 with pts 1713164679566, dts 1713164679566, duration 40 at relative offset 521947 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 7954 with pts 1713164679606, dts 1713164679606, duration 40 at relative offset 529876 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 503 with pts 1713164679615, dts 1713164679615, duration 64 at relative offset 537837 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 11167 with pts 1713164679646, dts 1713164679646, duration 40 at relative offset 538347 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 503 with pts 1713164679655, dts 1713164679655, duration 64 at relative offset 549521 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 10534 with pts 1713164679686, dts 1713164679686, duration 40 at relative offset 550031 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 7607 with pts 1713164679726, dts 1713164679726, duration 40 at relative offset 560572 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 478 with pts 1713164679772, dts 1713164679772, duration 64 at relative offset 568186 in cluster at offset 770. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7842 with pts 1713164679774, dts 1713164679774, duration 40 at relative offset 568671 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 9862 with pts 1713164679806, dts 1713164679806, duration 40 at relative offset 576520 in cluster at offset 770. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Starting new cluster with timestamp 1713164679815 at offset 587166 bytes
[matroska @ 0x169c330] Writing block of size 449 with pts 1713164679815, dts 1713164679815, duration 64 at relative offset 14 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 379456 with pts 1713164679870, dts 1713164679870, duration 40 at relative offset 470 in cluster at offset 587166. TrackNumber 1, keyframe 1
[matroska @ 0x169c330] Writing block of size 415 with pts 1713164679903, dts 1713164679903, duration 64 at relative offset 379934 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7008 with pts 1713164679905, dts 1713164679905, duration 40 at relative offset 380356 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 6917 with pts 1713164679925, dts 1713164679925, duration 40 at relative offset 387371 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 513 with pts 1713164679935, dts 1713164679935, duration 64 at relative offset 394295 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7111 with pts 1713164679966, dts 1713164679966, duration 40 at relative offset 394815 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 753 with pts 1713164679975, dts 1713164679975, duration 64 at relative offset 401933 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7091 with pts 1713164680006, dts 1713164680006, duration 40 at relative offset 402693 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 7045 with pts 1713164680045, dts 1713164680045, duration 40 at relative offset 409791 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 659 with pts 1713164680055, dts 1713164680055, duration 64 at relative offset 416843 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6983 with pts 1713164680086, dts 1713164680086, duration 40 at relative offset 417509 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 6932 with pts 1713164680127, dts 1713164680127, duration 40 at relative offset 424499 in cluster at offset 587166. TrackNumber 1, keyframe 0
frame=   35 fps=0.0 q=-1.0 size=     512kB time=475879:04:40.20 bitrate=   0.0kbits/s speed=3.35e+09x    
[matroska @ 0x169c330] Writing block of size 691 with pts 1713164680135, dts 1713164680135, duration 64 at relative offset 431438 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6990 with pts 1713164680166, dts 1713164680166, duration 40 at relative offset 432136 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 651 with pts 1713164680176, dts 1713164680176, duration 64 at relative offset 439133 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7046 with pts 1713164680206, dts 1713164680206, duration 40 at relative offset 439791 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 7130 with pts 1713164680246, dts 1713164680246, duration 40 at relative offset 446844 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 601 with pts 1713164680255, dts 1713164680255, duration 64 at relative offset 453981 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 7205 with pts 1713164680286, dts 1713164680286, duration 40 at relative offset 454589 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 561 with pts 1713164680295, dts 1713164680295, duration 64 at relative offset 461801 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6936 with pts 1713164680326, dts 1713164680326, duration 40 at relative offset 462369 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 6822 with pts 1713164680366, dts 1713164680366, duration 40 at relative offset 469312 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 621 with pts 1713164680375, dts 1713164680375, duration 64 at relative offset 476141 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6845 with pts 1713164680405, dts 1713164680405, duration 40 at relative offset 476769 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 6848 with pts 1713164680445, dts 1713164680445, duration 40 at relative offset 483621 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 588 with pts 1713164680455, dts 1713164680455, duration 64 at relative offset 490476 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6828 with pts 1713164680486, dts 1713164680486, duration 40 at relative offset 491071 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 546 with pts 1713164680495, dts 1713164680495, duration 64 at relative offset 497906 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6845 with pts 1713164680526, dts 1713164680526, duration 40 at relative offset 498459 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 6924 with pts 1713164680566, dts 1713164680566, duration 40 at relative offset 505311 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 508 with pts 1713164680576, dts 1713164680576, duration 64 at relative offset 512242 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6844 with pts 1713164680606, dts 1713164680606, duration 40 at relative offset 512757 in cluster at offset 587166. TrackNumber 1, keyframe 0
frame=   48 fps= 47 q=-1.0 size=     512kB time=475879:04:40.72 bitrate=   0.0kbits/s speed=1.66e+09x    
[matroska @ 0x169c330] Writing block of size 587 with pts 1713164680615, dts 1713164680615, duration 64 at relative offset 519608 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6859 with pts 1713164680645, dts 1713164680645, duration 40 at relative offset 520202 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 6855 with pts 1713164680686, dts 1713164680686, duration 40 at relative offset 527068 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 573 with pts 1713164680695, dts 1713164680695, duration 64 at relative offset 533930 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6881 with pts 1713164680726, dts 1713164680726, duration 40 at relative offset 534510 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 10773 with pts 1713164680766, dts 1713164680766, duration 40 at relative offset 541398 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 520 with pts 1713164680775, dts 1713164680775, duration 64 at relative offset 552178 in cluster at offset 587166. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6923 with pts 1713164680805, dts 1713164680805, duration 40 at relative offset 552705 in cluster at offset 587166. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Starting new cluster with timestamp 1713164680815 at offset 1146808 bytes
[matroska @ 0x169c330] Writing block of size 580 with pts 1713164680815, dts 1713164680815, duration 64 at relative offset 14 in cluster at offset 1146808. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 380085 with pts 1713164680864, dts 1713164680864, duration 40 at relative offset 601 in cluster at offset 1146808. TrackNumber 1, keyframe 1
[matroska @ 0x169c330] Writing block of size 9916 with pts 1713164680896, dts 1713164680896, duration 40 at relative offset 380694 in cluster at offset 1146808. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 541 with pts 1713164680901, dts 1713164680901, duration 64 at relative offset 390617 in cluster at offset 1146808. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 5877 with pts 1713164680925, dts 1713164680925, duration 40 at relative offset 391165 in cluster at offset 1146808. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] Writing block of size 529 with pts 1713164680935, dts 1713164680935, duration 64 at relative offset 397049 in cluster at offset 1146808. TrackNumber 2, keyframe 1
[matroska @ 0x169c330] Writing block of size 6661 with pts 1713164680966, dts 1713164680966, duration 40 at relative offset 397585 in cluster at offset 1146808. TrackNumber 1, keyframe 0
[matroska @ 0x169c330] end duration = 1713164681006
[matroska @ 0x169c330] stream 0 end duration = 1713164681006
[matroska @ 0x169c330] stream 1 end duration = 1713164680999
frame=   54 fps= 42 q=-1.0 Lsize=    1515kB time=475879:04:40.99 bitrate=   0.0kbits/s speed=1.33e+09x    
video:1493kB audio:20kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.099897%
Input file #0 (rtsp://user:password1@192.168.5.21/cam/realmonitor?channel=1channel1[1]=1subtype=0):
  Input stream #0:0 (video): 54 packets read (1529156 bytes); 
  Input stream #0:1 (audio): 35 packets read (9268 bytes); 35 frames decoded (35840 samples); 
  Total: 89 packets (1538424 bytes) demuxed
Output file #0 (rec.mkv):
  Output stream #0:0 (video): 54 packets muxed (1529156 bytes); 
  Output stream #0:1 (audio): 35 frames encoded (35840 samples); 36 packets muxed (20446 bytes); 
  Total: 90 packets (1549602 bytes) muxed
35 frames successfully decoded, 0 decoding errors
[AVIOContext @ 0x1667620] Statistics: 2 seeks, 7 writeouts
[aac @ 0x1673880] Qavg: 142.738
Exiting normally, received signal 15.


  


  In this short 3 second capture the duplicate timestamps are 1713164679.361000 and 1713164679.362000.

  


  How can I solve this problem ? What different approach could I use to achieve this goal ?

  


  Thanks in advance.