예제 #1
0
  void fillVisualizerWithLock(pcl::visualization::PCLVisualizer &visualizer, const bool firstRun)
  {
    const std::string centroidname = this->name + "_centroids";
    const std::string coloredvoxelname = this->name + "_voxels_colored";
    const std::string normalsname = this->name + "_supervoxel_normals";

    if(!firstRun)
    {
      visualizer.getPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, pointSize, centroidname);
    }
    visualizer.removeAllPointClouds();
    visualizer.removeAllShapes();
    addCentroids(visualizer, centroidname);
    switch(dispMode)
    {
    case ALL:
      addVoxels(visualizer, coloredvoxelname);
      addAdjacency(visualizer);
      addNormals(visualizer, normalsname);
      break;
    case W_VOXELS:
      addVoxels(visualizer, coloredvoxelname);
      break;
    case W_VA:
      addVoxels(visualizer, coloredvoxelname);
      addAdjacency(visualizer);
      break;
    case W_VN:
      addVoxels(visualizer, coloredvoxelname);
      addNormals(visualizer, normalsname);
      break;
    case W_AN:
      addAdjacency(visualizer);
      addNormals(visualizer, normalsname);
      break;
    case W_ADJACENCY:
      addAdjacency(visualizer);
      break;
    case W_NORMALS:
      addNormals(visualizer, normalsname);
      break;
    case ADJACENCY:
      visualizer.removeAllPointClouds();
      addAdjacency(visualizer);
      break;
    case NONE:
      break;
    case TEST:
      filterAdjacency(visualizer);
      break;
    }
  }
예제 #2
0
void Inspector::pointPickingCallback(const pcl::visualization::PointPickingEvent& event, void* cookie)
{
  if(event.getPointIndex() == -1)
    return;
    
  Point pt;
  event.getPoint(pt.x, pt.y, pt.z);
  cout << "Selected point: " << pt.x << ", " << pt.y << ", " << pt.z << endl;
  pcd_vis_.removeAllShapes();
  
  Point origin(0, 0, 0);
  pcd_vis_.addArrow<Point, Point>(origin, pt, 0.0, 0.0, 0.8, 0.9, 0.9, 0.9, "line");
}
예제 #3
0
void ObstacleVisualizer<PointT>::drawShapes(
    std::vector<ObjectModelPtr> obstacles,
    pcl::visualization::PCLVisualizer& viewer) {
  // Remove all old shapes...
  viewer.removeAllShapes();

  // ...and draw all the new ones.
  ModelDrawer drawer(viewer);
  size_t const sz = obstacles.size();
  for (size_t i = 0; i < sz; ++i) {
    obstacles[i]->accept(drawer);
  }
}
예제 #4
0
  void filterAdjacency(pcl::visualization::PCLVisualizer &visualizer)
  {
    visualizer.removeAllPointClouds();
    visualizer.removeAllShapes();
    std::multimap<uint32_t, uint32_t> supervoxel_adjacency;
    supervoxels->getSupervoxelAdjacency(supervoxel_adjacency);

    pcl::PointCloud< pcl::PointXYZRGBA>::Ptr filtered_supervoxel(new pcl::PointCloud< pcl::PointXYZRGBA>);
    for(std::multimap<uint32_t, uint32_t>::iterator label_itr = supervoxel_adjacency.begin(); label_itr != supervoxel_adjacency.end();)
    {
      //First get the label
      uint32_t supervoxel_label = label_itr->first;
      //Now get the supervoxel corresponding to the label
      pcl::Supervoxel<pcl::PointXYZRGBA>::Ptr supervoxel = supervoxel_clusters.at(supervoxel_label);

      int threshold = 7 - supervoxel->centroid_.z * 0.375;

      int count = supervoxel_adjacency.count(supervoxel_label);
      if(count >= threshold)
      {
        //Now we need to iterate through the adjacent supervoxels and make a point cloud of them
        pcl::PointCloud< pcl::PointXYZRGBA>::Ptr adjacent_supervoxel_centers(new pcl::PointCloud< pcl::PointXYZRGBA>);

        std::multimap<uint32_t, uint32_t>::iterator adjacent_itr = supervoxel_adjacency.equal_range(supervoxel_label).first;
        for(; adjacent_itr != supervoxel_adjacency.equal_range(supervoxel_label).second; ++adjacent_itr)
        {

          uint32_t snd_label = adjacent_itr->second;
          int snd_count = supervoxel_adjacency.count(snd_label);
          pcl::Supervoxel<pcl::PointXYZRGBA>::Ptr neighbor_supervoxel = supervoxel_clusters.at(snd_label);
          int snd_threshold = 7 - neighbor_supervoxel->centroid_.z * 0.375;
          if(snd_count >= snd_threshold)
          {
            adjacent_supervoxel_centers->push_back(neighbor_supervoxel->centroid_);
            filtered_supervoxel->push_back(neighbor_supervoxel->centroid_);
          }
        }
        //Now we make a name for this polygon
        std::stringstream ss;
        ss << "supervoxel_" << supervoxel_label;
        //This function generates a "star" polygon mesh from the points given
        addSupervoxelConnectionsToViewer(supervoxel->centroid_, *adjacent_supervoxel_centers, ss.str(), visualizer);

      }
      label_itr = supervoxel_adjacency.upper_bound(supervoxel_label);
    }
    const std::string foo = "fassdfasdf";
    visualizer.addPointCloud(filtered_supervoxel, foo);
    visualizer.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, pointSize, foo);
  }
예제 #5
0
void Inspector::keyboardCallback(const pcl::visualization::KeyboardEvent& event, void* cookie)
{
  if(event.keyDown()) {
    if(event.getKeyCode() == 'm') {
      toggleModel();
    }
    else if(event.getKeyCode() == 'c') {
      pcd_vis_.removeAllShapes();
    }
    else if(event.getKeyCode() == 27) {
      quitting_ = true;
    }
  }
}
int main (int argc, char** argv)
{
  if(pcl::console::find_switch (argc, argv, "--help") || pcl::console::find_switch (argc, argv, "-h"))
        return print_help();

  // Algorithm parameters:
  std::string svm_filename = "../../people/data/trainedLinearSVMForPeopleDetectionWithHOG.yaml";
  float min_confidence = -1.5;
  float min_height = 1.3;
  float max_height = 2.3;
  float voxel_size = 0.06;
  Eigen::Matrix3f rgb_intrinsics_matrix;
  rgb_intrinsics_matrix << 525, 0.0, 319.5, 0.0, 525, 239.5, 0.0, 0.0, 1.0; // Kinect RGB camera intrinsics

  // Read if some parameters are passed from command line:
  pcl::console::parse_argument (argc, argv, "--svm", svm_filename);
  pcl::console::parse_argument (argc, argv, "--conf", min_confidence);
  pcl::console::parse_argument (argc, argv, "--min_h", min_height);
  pcl::console::parse_argument (argc, argv, "--max_h", max_height);

  // Read Kinect live stream:
  PointCloudT::Ptr cloud (new PointCloudT);
  bool new_cloud_available_flag = false;
  pcl::Grabber* interface = new pcl::OpenNIGrabber();
  boost::function<void (const pcl::PointCloud<pcl::PointXYZRGBA>::ConstPtr&)> f =
      boost::bind (&cloud_cb_, _1, cloud, &new_cloud_available_flag);
  interface->registerCallback (f);
  interface->start ();

  // Wait for the first frame:
  while(!new_cloud_available_flag) 
    boost::this_thread::sleep(boost::posix_time::milliseconds(1));
  new_cloud_available_flag = false;

  cloud_mutex.lock ();    // for not overwriting the point cloud

  // Display pointcloud:
  pcl::visualization::PointCloudColorHandlerRGBField<PointT> rgb(cloud);
  viewer.addPointCloud<PointT> (cloud, rgb, "input_cloud");
  viewer.setCameraPosition(0,0,-2,0,-1,0,0);

  // Add point picking callback to viewer:
  struct callback_args cb_args;
  PointCloudT::Ptr clicked_points_3d (new PointCloudT);
  cb_args.clicked_points_3d = clicked_points_3d;
  cb_args.viewerPtr = pcl::visualization::PCLVisualizer::Ptr(&viewer);
  viewer.registerPointPickingCallback (pp_callback, (void*)&cb_args);
  std::cout << "Shift+click on three floor points, then press 'Q'..." << std::endl;

  // Spin until 'Q' is pressed:
  viewer.spin();
  std::cout << "done." << std::endl;
  
  cloud_mutex.unlock ();    

  // Ground plane estimation:
  Eigen::VectorXf ground_coeffs;
  ground_coeffs.resize(4);
  std::vector<int> clicked_points_indices;
  for (unsigned int i = 0; i < clicked_points_3d->points.size(); i++)
    clicked_points_indices.push_back(i);
  pcl::SampleConsensusModelPlane<PointT> model_plane(clicked_points_3d);
  model_plane.computeModelCoefficients(clicked_points_indices,ground_coeffs);
  std::cout << "Ground plane: " << ground_coeffs(0) << " " << ground_coeffs(1) << " " << ground_coeffs(2) << " " << ground_coeffs(3) << std::endl;

  // Initialize new viewer:
  pcl::visualization::PCLVisualizer viewer("PCL Viewer");          // viewer initialization
  viewer.setCameraPosition(0,0,-2,0,-1,0,0);

  // Create classifier for people detection:  
  pcl::people::PersonClassifier<pcl::RGB> person_classifier;
  person_classifier.loadSVMFromFile(svm_filename);   // load trained SVM

  // People detection app initialization:
  pcl::people::GroundBasedPeopleDetectionApp<PointT> people_detector;    // people detection object
  people_detector.setVoxelSize(voxel_size);                        // set the voxel size
  people_detector.setIntrinsics(rgb_intrinsics_matrix);            // set RGB camera intrinsic parameters
  people_detector.setClassifier(person_classifier);                // set person classifier
  people_detector.setHeightLimits(min_height, max_height);         // set person classifier
//  people_detector.setSensorPortraitOrientation(true);             // set sensor orientation to vertical

  // For timing:
  static unsigned count = 0;
  static double last = pcl::getTime ();

  // Main loop:
  while (!viewer.wasStopped())
  {
    if (new_cloud_available_flag && cloud_mutex.try_lock ())    // if a new cloud is available
    {
      new_cloud_available_flag = false;

      // Perform people detection on the new cloud:
      std::vector<pcl::people::PersonCluster<PointT> > clusters;   // vector containing persons clusters
      people_detector.setInputCloud(cloud);
      people_detector.setGround(ground_coeffs);                    // set floor coefficients
      people_detector.compute(clusters);                           // perform people detection

      ground_coeffs = people_detector.getGround();                 // get updated floor coefficients

      // Draw cloud and people bounding boxes in the viewer:
      viewer.removeAllPointClouds();
      viewer.removeAllShapes();
      pcl::visualization::PointCloudColorHandlerRGBField<PointT> rgb(cloud);
      viewer.addPointCloud<PointT> (cloud, rgb, "input_cloud");
      unsigned int k = 0;
      for(std::vector<pcl::people::PersonCluster<PointT> >::iterator it = clusters.begin(); it != clusters.end(); ++it)
      {
        if(it->getPersonConfidence() > min_confidence)             // draw only people with confidence above a threshold
        {
          // draw theoretical person bounding box in the PCL viewer:
          it->drawTBoundingBox(viewer, k);
          k++;
        }
      }
      std::cout << k << " people found" << std::endl;
      viewer.spinOnce();

      // Display average framerate:
      if (++count == 30)
      {
        double now = pcl::getTime ();
        std::cout << "Average framerate: " << double(count)/double(now - last) << " Hz" <<  std::endl;
        count = 0;
        last = now;
      }
      cloud_mutex.unlock ();
    }
  }

  return 0;
}
예제 #7
0
파일: PbMapMaker.cpp 프로젝트: DYFeng/mrpt
void PbMapMaker::viz_cb (pcl::visualization::PCLVisualizer& viz)
{
  if (mPbMap.globalMapPtr->empty())
  {
    mrpt::system::sleep(10);
    return;
  }

  { mrpt::synch::CCriticalSectionLocker csl(&CS_visualize);

    // Render the data
    {
      viz.removeAllShapes();
      viz.removeAllPointClouds();

      char name[1024];

      if(graphRepresentation)
      {
        for(size_t i=0; i<mPbMap.vPlanes.size(); i++)
        {
          pcl::PointXYZ center(2*mPbMap.vPlanes[i].v3center[0], 2*mPbMap.vPlanes[i].v3center[1], 2*mPbMap.vPlanes[i].v3center[2]);
          double radius = 0.1 * sqrt(mPbMap.vPlanes[i].areaVoxels);
          sprintf (name, "sphere%u", static_cast<unsigned>(i));
          viz.addSphere (center, radius, ared[i%10], agrn[i%10], ablu[i%10], name);

          if( !mPbMap.vPlanes[i].label.empty() )
              viz.addText3D (mPbMap.vPlanes[i].label, center, 0.1, ared[i%10], agrn[i%10], ablu[i%10], mPbMap.vPlanes[i].label);
          else
          {
            sprintf (name, "P%u", static_cast<unsigned>(i));
            viz.addText3D (name, center, 0.1, ared[i%10], agrn[i%10], ablu[i%10], name);
          }

          // Draw edges
          if(!configPbMap.graph_mode) // Nearby neighbors
            for(set<unsigned>::iterator it = mPbMap.vPlanes[i].nearbyPlanes.begin(); it != mPbMap.vPlanes[i].nearbyPlanes.end(); it++)
            {
              if(*it > mPbMap.vPlanes[i].id)
                break;

              sprintf (name, "commonObs%u_%u", static_cast<unsigned>(i), static_cast<unsigned>(*it));
              pcl::PointXYZ center_it(2*mPbMap.vPlanes[*it].v3center[0], 2*mPbMap.vPlanes[*it].v3center[1], 2*mPbMap.vPlanes[*it].v3center[2]);
              viz.addLine (center, center_it, ared[i%10], agrn[i%10], ablu[i%10], name);
            }
          else
            for(map<unsigned,unsigned>::iterator it = mPbMap.vPlanes[i].neighborPlanes.begin(); it != mPbMap.vPlanes[i].neighborPlanes.end(); it++)
            {
              if(it->first > mPbMap.vPlanes[i].id)
                break;

              sprintf (name, "commonObs%u_%u", static_cast<unsigned>(i), static_cast<unsigned>(it->first));
              pcl::PointXYZ center_it(2*mPbMap.vPlanes[it->first].v3center[0], 2*mPbMap.vPlanes[it->first].v3center[1], 2*mPbMap.vPlanes[it->first].v3center[2]);
              viz.addLine (center, center_it, ared[i%10], agrn[i%10], ablu[i%10], name);

              sprintf (name, "edge%u_%u", static_cast<unsigned>(i), static_cast<unsigned>(it->first));
              char commonObs[8];
              sprintf (commonObs, "%u", it->second);
              pcl::PointXYZ half_edge( (center_it.x+center.x)/2, (center_it.y+center.y)/2, (center_it.z+center.z)/2 );
              viz.addText3D (commonObs, half_edge, 0.05, 1.0, 1.0, 1.0, name);
            }

        }
      }
      else
      { // Regular representation

        if (!viz.updatePointCloud (mPbMap.globalMapPtr, "cloud"))
          viz.addPointCloud (mPbMap.globalMapPtr, "cloud");

        if(mpPbMapLocaliser != NULL)
          if(mpPbMapLocaliser->alignedModelPtr){
            if (!viz.updatePointCloud (mpPbMapLocaliser->alignedModelPtr, "model"))
              viz.addPointCloud (mpPbMapLocaliser->alignedModelPtr, "model");}

        sprintf (name, "PointCloud size %u", static_cast<unsigned>( mPbMap.globalMapPtr->size() ) );
        viz.addText(name, 10, 20);

        for(size_t i=0; i<mPbMap.vPlanes.size(); i++)
        {
          Plane &plane_i = mPbMap.vPlanes[i];
          sprintf (name, "normal_%u", static_cast<unsigned>(i));
          pcl::PointXYZ pt1, pt2; // Begin and end points of normal's arrow for visualization
          pt1 = pcl::PointXYZ(plane_i.v3center[0], plane_i.v3center[1], plane_i.v3center[2]);
          pt2 = pcl::PointXYZ(plane_i.v3center[0] + (0.5f * plane_i.v3normal[0]),
                              plane_i.v3center[1] + (0.5f * plane_i.v3normal[1]),
                              plane_i.v3center[2] + (0.5f * plane_i.v3normal[2]));
          viz.addArrow (pt2, pt1, ared[i%10], agrn[i%10], ablu[i%10], false, name);

          // Draw Ppal diretion
//          if( plane_i.elongation > 1.3 )
//          {
//            sprintf (name, "ppalComp_%u", static_cast<unsigned>(i));
//            pcl::PointXYZ pt3 = pcl::PointXYZ ( plane_i.v3center[0] + (0.2f * plane_i.v3PpalDir[0]),
//                                                plane_i.v3center[1] + (0.2f * plane_i.v3PpalDir[1]),
//                                                plane_i.v3center[2] + (0.2f * plane_i.v3PpalDir[2]));
//            viz.addArrow (pt3, plane_i.pt1, ared[i%10], agrn[i%10], ablu[i%10], false, name);
//          }

//          if( !plane_i.label.empty() )
//            viz.addText3D (plane_i.label, pt2, 0.1, ared[i%10], agrn[i%10], ablu[i%10], plane_i.label);
//          else
          {
            sprintf (name, "n%u", static_cast<unsigned>(i));
//            sprintf (name, "n%u_%u", static_cast<unsigned>(i), static_cast<unsigned>(plane_i.semanticGroup));
            viz.addText3D (name, pt2, 0.1, ared[i%10], agrn[i%10], ablu[i%10], name);
          }

//          sprintf (name, "planeRaw_%02u", static_cast<unsigned>(i));
//          viz.addPointCloud (plane_i.planeRawPointCloudPtr, name);// contourPtr, planePointCloudPtr, polygonContourPtr

//          if(!configPbMap.makeClusters)
//          {
//          sprintf (name, "plane_%02u", static_cast<unsigned>(i));
//          pcl::visualization::PointCloudColorHandlerCustom <PointT> color (plane_i.planePointCloudPtr, red[i%10], grn[i%10], blu[i%10]);
////          pcl::visualization::PointCloudColorHandlerCustom <PointT> color (plane_i.planePointCloudPtr, red[plane_i.semanticGroup%10], grn[plane_i.semanticGroup%10], blu[plane_i.semanticGroup%10]);
//          viz.addPointCloud (plane_i.planePointCloudPtr, color, name);
//          viz.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 2, name);
//          }
//          else
//          {
//            sprintf (name, "plane_%02u", static_cast<unsigned>(i));
//            pcl::visualization::PointCloudColorHandlerCustom <PointT> color (plane_i.planePointCloudPtr, red[plane_i.semanticGroup%10], grn[plane_i.semanticGroup%10], blu[plane_i.semanticGroup%10]);
//            viz.addPointCloud (plane_i.planePointCloudPtr, color, name);
//            viz.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 4, name);
//          }

//          sprintf (name, "planeBorder_%02u", static_cast<unsigned>(i));
//          pcl::visualization::PointCloudColorHandlerCustom <PointT> color2 (plane_i.contourPtr, 255, 255, 255);
//          viz.addPointCloud (plane_i.contourPtr, color2, name);// contourPtr, planePointCloudPtr, polygonContourPtr

//          //Edges
//          if(mPbMap.edgeCloudPtr->size() > 0)
//          {
//            sprintf (name, "planeEdge_%02u", static_cast<unsigned>(i));
//            pcl::visualization::PointCloudColorHandlerCustom <PointT> color4 (mPbMap.edgeCloudPtr, 255, 255, 0);
//            viz.addPointCloud (mPbMap.edgeCloudPtr, color4, name);// contourPtr, planePointCloudPtr, polygonContourPtr
//            viz.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 5, name);
//
//            sprintf (name, "edge%u", static_cast<unsigned>(i));
//            viz.addLine (mPbMap.edgeCloudPtr->points.front(), mPbMap.edgeCloudPtr->points.back(), ared[3], agrn[3], ablu[3], name);
//          }

          sprintf (name, "approx_plane_%02d", int (i));
          viz.addPolygon<PointT> (plane_i.polygonContourPtr, 0.5 * red[i%10], 0.5 * grn[i%10], 0.5 * blu[i%10], name);
        }

//if(configPbMap.makeClusters)
//  for(map<unsigned, std::vector<unsigned> >::iterator it=clusterize->groups.begin(); it != clusterize->groups.end(); it++)
//    for(size_t i=0; i < it->second.size(); i++)
//    {
//      unsigned planeID = it->second[i];
//      Plane &plane_i = mPbMap.vPlanes[planeID];
//      sprintf (name, "plane_%02u", static_cast<unsigned>(planeID));
//      pcl::visualization::PointCloudColorHandlerCustom <PointT> color (plane_i.planePointCloudPtr, red[planeID%10], grn[planeID%10], blu[planeID%10]);
//      viz.addPointCloud (plane_i.planePointCloudPtr, color, name);// contourPtr, planePointCloudPtr, polygonContourPtr
//      viz.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, name);
//    }

        // Draw recognized plane labels
        if(mpPbMapLocaliser != NULL)
          for(map<string, pcl::PointXYZ>::iterator it = mpPbMapLocaliser->foundPlaces.begin(); it != mpPbMapLocaliser->foundPlaces.end(); it++)
            viz.addText3D (it->first, it->second, 0.3, 0.9, 0.9, 0.9, it->first);

      }
    }
  }
}
    void
    process ()
    {
      std::cout << "threshold: " << threshold_ << std::endl;
      std::cout << "depth dependent: " << (depth_dependent_ ? "true\n" : "false\n");
      unsigned char red [6] = {255,   0,   0, 255, 255,   0};
      unsigned char grn [6] = {  0, 255,   0, 255,   0, 255};
      unsigned char blu [6] = {  0,   0, 255,   0, 255, 255};

      pcl::IntegralImageNormalEstimation<PointT, pcl::Normal> ne;
      ne.setNormalEstimationMethod (ne.COVARIANCE_MATRIX);
      ne.setMaxDepthChangeFactor (0.02f);
      ne.setNormalSmoothingSize (20.0f);
      
      typename pcl::PlaneRefinementComparator<PointT, pcl::Normal, pcl::Label>::Ptr refinement_compare (new pcl::PlaneRefinementComparator<PointT, pcl::Normal, pcl::Label> ());
      refinement_compare->setDistanceThreshold (threshold_, depth_dependent_);
      
      pcl::OrganizedMultiPlaneSegmentation<PointT, pcl::Normal, pcl::Label> mps;
      mps.setMinInliers (5000);
      mps.setAngularThreshold (0.017453 * 3.0); //3 degrees
      mps.setDistanceThreshold (0.03); //2cm
      mps.setRefinementComparator (refinement_compare);
      
      std::vector<pcl::PlanarRegion<PointT>, Eigen::aligned_allocator<pcl::PlanarRegion<PointT> > > regions;
      typename pcl::PointCloud<PointT>::Ptr contour (new pcl::PointCloud<PointT>);
      typename pcl::PointCloud<PointT>::Ptr approx_contour (new pcl::PointCloud<PointT>);
      char name[1024];

      typename pcl::PointCloud<pcl::Normal>::Ptr normal_cloud (new pcl::PointCloud<pcl::Normal>);
      double normal_start = pcl::getTime ();
      ne.setInputCloud (cloud);
      ne.compute (*normal_cloud);
      double normal_end = pcl::getTime ();
      std::cout << "Normal Estimation took " << double (normal_end - normal_start) << std::endl;

      double plane_extract_start = pcl::getTime ();
      mps.setInputNormals (normal_cloud);
      mps.setInputCloud (cloud);
      if (refine_)
        mps.segmentAndRefine (regions);
      else
        mps.segment (regions);
      double plane_extract_end = pcl::getTime ();
      std::cout << "Plane extraction took " << double (plane_extract_end - plane_extract_start) << " with planar regions found: " << regions.size () << std::endl;
      std::cout << "Frame took " << double (plane_extract_end - normal_start) << std::endl;

      typename pcl::PointCloud<PointT>::Ptr cluster (new pcl::PointCloud<PointT>);

      viewer.removeAllPointClouds (0);
      viewer.removeAllShapes (0);
      pcl::visualization::PointCloudColorHandlerCustom<PointT> single_color (cloud, 0, 255, 0);
      viewer.addPointCloud<PointT> (cloud, single_color, "cloud");
      
      pcl::PlanarPolygon<PointT> approx_polygon;
      //Draw Visualization
      for (size_t i = 0; i < regions.size (); i++)
      {
        Eigen::Vector3f centroid = regions[i].getCentroid ();
        Eigen::Vector4f model = regions[i].getCoefficients ();
        pcl::PointXYZ pt1 = pcl::PointXYZ (centroid[0], centroid[1], centroid[2]);
        pcl::PointXYZ pt2 = pcl::PointXYZ (centroid[0] + (0.5f * model[0]),
                                           centroid[1] + (0.5f * model[1]),
                                           centroid[2] + (0.5f * model[2]));
        sprintf (name, "normal_%d", unsigned (i));
        viewer.addArrow (pt2, pt1, 1.0, 0, 0, std::string (name));

        contour->points = regions[i].getContour ();        
        sprintf (name, "plane_%02d", int (i));
        pcl::visualization::PointCloudColorHandlerCustom <PointT> color (contour, red[i], grn[i], blu[i]);
        viewer.addPointCloud (contour, color, name);

        pcl::approximatePolygon (regions[i], approx_polygon, threshold_, polygon_refinement_);
        approx_contour->points = approx_polygon.getContour ();
        std::cout << "polygon: " << contour->size () << " -> " << approx_contour->size () << std::endl;
        typename pcl::PointCloud<PointT>::ConstPtr approx_contour_const = approx_contour;
        
//        sprintf (name, "approx_plane_%02d", int (i));
//        viewer.addPolygon<PointT> (approx_contour_const, 0.5 * red[i], 0.5 * grn[i], 0.5 * blu[i], name);
        for (unsigned idx = 0; idx < approx_contour->points.size (); ++idx)
        {
          sprintf (name, "approx_plane_%02d_%03d", int (i), int(idx));
          viewer.addLine (approx_contour->points [idx], approx_contour->points [(idx+1)%approx_contour->points.size ()], 0.5 * red[i], 0.5 * grn[i], 0.5 * blu[i], name);
        }
      }
    }
int main (int argc, char** argv)
{

  //ROS Initialization
  ros::init(argc, argv, "detecting_people");
  ros::NodeHandle nh;
  ros::Rate rate(13);

  ros::Subscriber state_sub = nh.subscribe("followme_state", 5, &stateCallback);
  ros::Publisher people_pub = nh.advertise<frmsg::people>("followme_people", 5);
  frmsg::people pub_people_;

  CloudConverter* cc_ = new CloudConverter();

  while (!cc_->ready_xyzrgb_)
  {
    ros::spinOnce();
    rate.sleep();
    if (!ros::ok())
    {
      printf("Terminated by Control-c.\n");
      return -1;
    }
  }

  // Input parameter from the .yaml
  std::string package_path_ = ros::package::getPath("detecting_people") + "/";
  cv::FileStorage* fs_ = new cv::FileStorage(package_path_ + "parameters.yml", cv::FileStorage::READ);

  // Algorithm parameters:
  std::string svm_filename = package_path_ + "trainedLinearSVMForPeopleDetectionWithHOG.yaml";
  std::cout << svm_filename << std::endl;

  float min_confidence = -1.5;
  float min_height = 1.3;
  float max_height = 2.3;
  float voxel_size = 0.06;
  Eigen::Matrix3f rgb_intrinsics_matrix;
  rgb_intrinsics_matrix << 525, 0.0, 319.5, 0.0, 525, 239.5, 0.0, 0.0, 1.0; // Kinect RGB camera intrinsics
  
  // Read if some parameters are passed from command line:
  pcl::console::parse_argument (argc, argv, "--svm", svm_filename);
  pcl::console::parse_argument (argc, argv, "--conf", min_confidence);
  pcl::console::parse_argument (argc, argv, "--min_h", min_height);
  pcl::console::parse_argument (argc, argv, "--max_h", max_height);


  // Read Kinect live stream:
  PointCloudT::Ptr cloud_people (new PointCloudT);
  cc_->ready_xyzrgb_ = false;
  while ( !cc_->ready_xyzrgb_ )
  {
    ros::spinOnce();
    rate.sleep();
  }
  pcl::PointCloud<pcl::PointXYZRGB>::ConstPtr cloud = cc_->msg_xyzrgb_;

  // Display pointcloud:
  pcl::visualization::PointCloudColorHandlerRGBField<PointT> rgb(cloud);
  viewer.addPointCloud<PointT> (cloud, rgb, "input_cloud");
  viewer.setCameraPosition(0,0,-2,0,-1,0,0);

  // Add point picking callback to viewer:
  struct callback_args cb_args;
  PointCloudT::Ptr clicked_points_3d (new PointCloudT);
  cb_args.clicked_points_3d = clicked_points_3d;
  cb_args.viewerPtr = pcl::visualization::PCLVisualizer::Ptr(&viewer);
  viewer.registerPointPickingCallback (pp_callback, (void*)&cb_args);
  std::cout << "Shift+click on three floor points, then press 'Q'..." << std::endl;

  // Spin until 'Q' is pressed:
  viewer.spin();
  std::cout << "done." << std::endl;
  
  //cloud_mutex.unlock ();    

  // Ground plane estimation:
  Eigen::VectorXf ground_coeffs;
  ground_coeffs.resize(4);
  std::vector<int> clicked_points_indices;
  for (unsigned int i = 0; i < clicked_points_3d->points.size(); i++)
    clicked_points_indices.push_back(i);
  pcl::SampleConsensusModelPlane<PointT> model_plane(clicked_points_3d);
  model_plane.computeModelCoefficients(clicked_points_indices,ground_coeffs);
  std::cout << "Ground plane: " << ground_coeffs(0) << " " << ground_coeffs(1) << " " << ground_coeffs(2) << " " << ground_coeffs(3) << std::endl;

  // Initialize new viewer:
  pcl::visualization::PCLVisualizer viewer("PCL Viewer");          // viewer initialization
  viewer.setCameraPosition(0,0,-2,0,-1,0,0);

  // Create classifier for people detection:  
  pcl::people::PersonClassifier<pcl::RGB> person_classifier;
  person_classifier.loadSVMFromFile(svm_filename);   // load trained SVM

  // People detection app initialization:
  pcl::people::GroundBasedPeopleDetectionApp<PointT> people_detector;    // people detection object
  people_detector.setVoxelSize(voxel_size);                        // set the voxel size
  people_detector.setIntrinsics(rgb_intrinsics_matrix);            // set RGB camera intrinsic parameters
  people_detector.setClassifier(person_classifier);                // set person classifier
  people_detector.setHeightLimits(min_height, max_height);         // set person classifier
//  people_detector.setSensorPortraitOrientation(true);             // set sensor orientation to vertical

  // For timing:
  static unsigned count = 0;
  static double last = pcl::getTime ();
  
  int people_count = 0;
  histogram* first_hist;

  int max_people_num = (int)fs_->getFirstTopLevelNode()["max_people_num"];
  // Main loop:
  while (!viewer.wasStopped() && ros::ok() )
  {
    if ( current_state == 1 )
    {
      if ( cc_->ready_xyzrgb_ )    // if a new cloud is available
      {
    //    std::cout << "In state 1!!!!!!!!!!" << std::endl;

        std::vector<float> x;
        std::vector<float> y;
        std::vector<float> depth;

        cloud = cc_->msg_xyzrgb_;
        PointCloudT::Ptr cloud_new(new PointCloudT(*cloud));
        cc_->ready_xyzrgb_ = false;

        // Perform people detection on the new cloud:
        std::vector<pcl::people::PersonCluster<PointT> > clusters;   // vector containing persons clusters
        people_detector.setInputCloud(cloud_new);
        people_detector.setGround(ground_coeffs);                    // set floor coefficients
        people_detector.compute(clusters);                           // perform people detection

        ground_coeffs = people_detector.getGround();                 // get updated floor coefficients

        // Draw cloud and people bounding boxes in the viewer:
        viewer.removeAllPointClouds();
        viewer.removeAllShapes();
        pcl::visualization::PointCloudColorHandlerRGBField<PointT> rgb(cloud);
        viewer.addPointCloud<PointT> (cloud, rgb, "input_cloud");
        unsigned int k = 0;
        std::vector<pcl::people::PersonCluster<PointT> >::iterator it;
        std::vector<pcl::people::PersonCluster<PointT> >::iterator it_min;

        float min_z = 10.0;

        float histo_dist_min = 2.0;
        int id = -1;

        for(it = clusters.begin(); it != clusters.end(); ++it)
        {
          if(it->getPersonConfidence() > min_confidence)             // draw only people with confidence above a threshold
          {

            x.push_back((it->getTCenter())[0]);
            y.push_back((it->getTCenter())[1]);
            depth.push_back(it->getDistance());
            // draw theoretical person bounding box in the PCL viewer:
            /*pcl::copyPointCloud( *cloud, it->getIndices(), *cloud_people);
            if ( people_count == 0 )
            {
              first_hist = calc_histogram_a( cloud_people );
              people_count++;
              it->drawTBoundingBox(viewer, k);
            }
            else if ( people_count <= 10 )
            {
              histogram* hist_tmp = calc_histogram_a( cloud_people );
              add_hist( first_hist, hist_tmp );
              it->drawTBoundingBox(viewer, k);
              people_count++;
            }*/
            pcl::copyPointCloud( *cloud, it->getIndices(), *cloud_people);
            if ( people_count < 11 )
            {
              if ( it->getDistance() < min_z )
              {
                it_min = it;
                min_z = it->getDistance();
              }
            }
            else if ( people_count == 11 )
            {
              normalize_histogram( first_hist );
              people_count++;
              histogram* hist_tmp = calc_histogram( cloud_people );
              float tmp = histo_dist_sq( first_hist, hist_tmp );
              std::cout << "The histogram distance is " << tmp << std::endl;
              histo_dist_min = tmp;
              it_min = it;
              id = k;
            }
            else
            {
              histogram* hist_tmp = calc_histogram( cloud_people );
              float tmp = histo_dist_sq( first_hist, hist_tmp );
              std::cout << "The histogram distance is " << tmp << std::endl;
              if ( tmp < histo_dist_min )
              {
                histo_dist_min = tmp;
                it_min = it;
                id = k;
              }
            }
            k++;
            //std::cout << "The data of the center is " << cloud->points [(cloud->width >> 1) * (cloud->height + 1)].x << "  " << cloud->points [(cloud->width >> 1) * (cloud->height + 1)].y << " " << cloud->points [(cloud->width >> 1) * (cloud->height + 1)].z << std::endl;
            //std::cout << "The size of the people cloud is " <<  cloud_people->points.size() << std::endl;
            std::cout << "The " << k << " person's distance is " << it->getDistance() << std::endl;
          }
        }
        pub_people_.x = x;
        pub_people_.y = y;
        pub_people_.depth = depth;
        if ( k > 0 )
        {
          if ( people_count <= 11 )
          {
            pcl::copyPointCloud( *cloud, it_min->getIndices(), *cloud_people);
            if ( people_count == 0)
            {
              first_hist = calc_histogram_a( cloud_people );
              people_count++;
              it_min->drawTBoundingBox(viewer, 1);
            }
            else if ( people_count < 11 )
            {
              histogram* hist_tmp = calc_histogram_a( cloud_people );
              add_hist( first_hist, hist_tmp );
              it_min->drawTBoundingBox(viewer, 1);
              people_count++;
            }
          }
          else
          {
            pub_people_.id = k-1;
            if ( histo_dist_min < 1.3 )
            {
              it_min->drawTBoundingBox(viewer, 1);
              std::cout << "The minimum distance of the histogram is " << histo_dist_min << std::endl;
              std::cout << "The vector is " << it_min->getTCenter() << std::endl << "while the elements are " << (it_min->getTCenter())[0] << " " << (it_min->getTCenter())[1] << std::endl;
            }
            else
            {
              pub_people_.id = -1;
            }
          }
        }
        else
        {
          pub_people_.id = -1;
        }
        pub_people_.header.stamp = ros::Time::now();
        people_pub.publish(pub_people_);
        
        std::cout << k << " people found" << std::endl;
        viewer.spinOnce();
        ros::spinOnce();

        // Display average framerate:
        if (++count == 30)
        {
          double now = pcl::getTime ();
          std::cout << "Average framerate: " << double(count)/double(now - last) << " Hz" <<  std::endl;
          count = 0;
          last = now;
        }
        //cloud_mutex.unlock ();
      }
    }
    else
    {
      viewer.spinOnce();
      ros::spinOnce();
      // std::cout << "In state 0!!!!!!!!!" << std::endl;
    }
  }

  return 0;
}
예제 #10
0
void PbMapVisualizer::viz_cb (pcl::visualization::PCLVisualizer& viz)
{
  if (pbmap.globalMapPtr->empty())
  {
    mrpt::system::sleep(10);
    return;
  }

  // Render the data
  {
    viz.removeAllShapes();
    viz.removeAllPointClouds();

    char name[1024];

    if(graphRepresentation)
    {
//      cout << "show graphRepresentation\n";
      for(size_t i=0; i<pbmap.vPlanes.size(); i++)
      {
        pcl::PointXYZ center(2*pbmap.vPlanes[i].v3center[0], 2*pbmap.vPlanes[i].v3center[1], 2*pbmap.vPlanes[i].v3center[2]);
        double radius = 0.1 * sqrt(pbmap.vPlanes[i].areaVoxels);
//        cout << "radius " << radius << endl;
        sprintf (name, "sphere%u", static_cast<unsigned>(i));
        viz.addSphere (center, radius, ared[i%10], agrn[i%10], ablu[i%10], name);

        if( !pbmap.vPlanes[i].label.empty() )
            viz.addText3D (pbmap.vPlanes[i].label, center, 0.1, ared[i%10], agrn[i%10], ablu[i%10], pbmap.vPlanes[i].label);
        else
        {
          sprintf (name, "P%u", static_cast<unsigned>(i));
          viz.addText3D (name, center, 0.1, ared[i%10], agrn[i%10], ablu[i%10], name);
        }

        // Draw edges
//        for(set<unsigned>::iterator it = pbmap.vPlanes[i].nearbyPlanes.begin(); it != pbmap.vPlanes[i].nearbyPlanes.end(); it++)
//        {
//          if(*it > pbmap.vPlanes[i].id)
//            break;
//
//          sprintf (name, "commonObs%u_%u", static_cast<unsigned>(i), static_cast<unsigned>(*it));
//          pcl::PointXYZ center_it(2*pbmap.vPlanes[*it].v3center[0], 2*pbmap.vPlanes[*it].v3center[1], 2*pbmap.vPlanes[*it].v3center[2]);
//          viz.addLine (center, center_it, ared[i%10], agrn[i%10], ablu[i%10], name);
//        }
        for(map<unsigned,unsigned>::iterator it = pbmap.vPlanes[i].neighborPlanes.begin(); it != pbmap.vPlanes[i].neighborPlanes.end(); it++)
        {
          if(it->first > pbmap.vPlanes[i].id)
            break;

          sprintf (name, "commonObs%u_%u", static_cast<unsigned>(i), static_cast<unsigned>(it->first));
          pcl::PointXYZ center_it(2*pbmap.vPlanes[it->first].v3center[0], 2*pbmap.vPlanes[it->first].v3center[1], 2*pbmap.vPlanes[it->first].v3center[2]);
          viz.addLine (center, center_it, ared[i%10], agrn[i%10], ablu[i%10], name);

          sprintf (name, "edge%u_%u", static_cast<unsigned>(i), static_cast<unsigned>(it->first));
          char commonObs[8];
          sprintf (commonObs, "%u", it->second);
          pcl::PointXYZ half_edge( (center_it.x+center.x)/2, (center_it.y+center.y)/2, (center_it.z+center.z)/2 );
          viz.addText3D (commonObs, half_edge, 0.05, 1.0, 1.0, 1.0, name);
        }
      }
    }
    else
    { // Regular representation
      if (!viz.updatePointCloud (pbmap.globalMapPtr, "cloud"))
        viz.addPointCloud (pbmap.globalMapPtr, "cloud");

      sprintf (name, "PointCloud size %u", static_cast<unsigned>( pbmap.globalMapPtr->size() ) );
      viz.addText(name, 10, 20);

      for(size_t i=0; i<pbmap.vPlanes.size(); i++)
      {
        Plane &plane_i = pbmap.vPlanes[i];
//        sprintf (name, "normal_%u", static_cast<unsigned>(i));
        name[0] = *(mrpt::format("normal_%u", static_cast<unsigned>(i)).c_str());
        pcl::PointXYZ pt1, pt2; // Begin and end points of normal's arrow for visualization
        pt1 = pcl::PointXYZ(plane_i.v3center[0], plane_i.v3center[1], plane_i.v3center[2]);
        pt2 = pcl::PointXYZ(plane_i.v3center[0] + (0.5f * plane_i.v3normal[0]),
                            plane_i.v3center[1] + (0.5f * plane_i.v3normal[1]),
                            plane_i.v3center[2] + (0.5f * plane_i.v3normal[2]));
        viz.addArrow (pt2, pt1, ared[i%10], agrn[i%10], ablu[i%10], false, name);

        if( !plane_i.label.empty() )
          viz.addText3D (plane_i.label, pt2, 0.1, ared[i%10], agrn[i%10], ablu[i%10], plane_i.label);
        else
        {
          sprintf (name, "n%u", static_cast<unsigned>(i));
          viz.addText3D (name, pt2, 0.1, ared[i%10], agrn[i%10], ablu[i%10], name);
        }

        sprintf (name, "approx_plane_%02d", int (i));
        viz.addPolygon<PointT> (plane_i.polygonContourPtr, 0.5 * red[i%10], 0.5 * grn[i%10], 0.5 * blu[i%10], name);
      }
    }
  }
}
예제 #11
0
void run(pcl::RFFaceDetectorTrainer & fdrf, typename pcl::PointCloud<PointInT>::Ptr & scene_vis, pcl::visualization::PCLVisualizer & vis, bool heat_map,
    bool show_votes, const std::string & filename)
{
  pcl::PointCloud<pcl::PointXYZ>::Ptr scene (new pcl::PointCloud<pcl::PointXYZ>);
  pcl::copyPointCloud (*scene_vis, *scene);

  fdrf.setInputCloud (scene);

  if (heat_map)
  {
    pcl::PointCloud<pcl::PointXYZI>::Ptr intensity_cloud (new pcl::PointCloud<pcl::PointXYZI>);
    fdrf.setFaceHeatMapCloud (intensity_cloud);
  }

  fdrf.detectFaces ();

  typedef typename pcl::traits::fieldList<PointInT>::type FieldListM;

  double rgb_m;
  bool exists_m;
  pcl::for_each_type < FieldListM > (pcl::CopyIfFieldExists<PointInT, double> (scene_vis->points[0], "rgb", exists_m, rgb_m));

  std::cout << "Color exists:" << static_cast<int> (exists_m) << std::endl;
  if (exists_m)
  {
    pcl::PointCloud<pcl::PointXYZRGB>::Ptr to_visualize (new pcl::PointCloud<pcl::PointXYZRGB>);
    pcl::copyPointCloud (*scene_vis, *to_visualize);

    pcl::visualization::PointCloudColorHandlerRGBField < pcl::PointXYZRGB > handler_keypoints (to_visualize);
    vis.addPointCloud < pcl::PointXYZRGB > (to_visualize, handler_keypoints, "scene_cloud");
  } else
  {
    vis.addPointCloud (scene_vis, "scene_cloud");
  }

  if (heat_map)
  {
    pcl::PointCloud<pcl::PointXYZI>::Ptr intensity_cloud (new pcl::PointCloud<pcl::PointXYZI>);
    fdrf.getFaceHeatMap (intensity_cloud);

    pcl::visualization::PointCloudColorHandlerGenericField < pcl::PointXYZI > handler_keypoints (intensity_cloud, "intensity");
    vis.addPointCloud < pcl::PointXYZI > (intensity_cloud, handler_keypoints, "heat_map");
  }

  if (show_votes)
  {
    //display votes_
    /*pcl::PointCloud<pcl::PointXYZ>::Ptr votes_cloud(new pcl::PointCloud<pcl::PointXYZ>());
     fdrf.getVotes(votes_cloud);
     pcl::visualization::PointCloudColorHandlerCustom < pcl::PointXYZ > handler_votes(votes_cloud, 255, 0, 0);
     vis.addPointCloud < pcl::PointXYZ > (votes_cloud, handler_votes, "votes_cloud");
     vis.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 14, "votes_cloud");
     vis.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_OPACITY, 0.5, "votes_cloud");
     vis.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_OPACITY, 0.75, "votes_cloud");*/

    pcl::PointCloud<pcl::PointXYZI>::Ptr votes_cloud (new pcl::PointCloud<pcl::PointXYZI> ());
    fdrf.getVotes2 (votes_cloud);
    pcl::visualization::PointCloudColorHandlerGenericField < pcl::PointXYZI > handler_votes (votes_cloud, "intensity");
    vis.addPointCloud < pcl::PointXYZI > (votes_cloud, handler_votes, "votes_cloud");
    vis.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 14, "votes_cloud");
  }

  vis.addCoordinateSystem (0.1, "global");

  std::vector<Eigen::VectorXd> heads;
  fdrf.getDetectedFaces (heads);
  face_detection_apps_utils::displayHeads (heads, vis);

  if (SHOW_GT)
  {
    //check if there is ground truth data
    std::string pose_file (filename);
    boost::replace_all (pose_file, ".pcd", "_pose.txt");

    Eigen::Matrix4d pose_mat;
    pose_mat.setIdentity (4, 4);
    bool result = face_detection_apps_utils::readMatrixFromFile (pose_file, pose_mat);

    if (result)
    {
      Eigen::Vector3d ea = pose_mat.block<3, 3> (0, 0).eulerAngles (0, 1, 2);
      Eigen::Vector3d trans_vector = Eigen::Vector3d (pose_mat (0, 3), pose_mat (1, 3), pose_mat (2, 3));
      std::cout << ea << std::endl;
      std::cout << trans_vector << std::endl;

      pcl::PointXYZ center_point;
      center_point.x = trans_vector[0];
      center_point.y = trans_vector[1];
      center_point.z = trans_vector[2];
      vis.addSphere (center_point, 0.05, 255, 0, 0, "sphere");

      pcl::ModelCoefficients cylinder_coeff;
      cylinder_coeff.values.resize (7); // We need 7 values
      cylinder_coeff.values[0] = center_point.x;
      cylinder_coeff.values[1] = center_point.y;
      cylinder_coeff.values[2] = center_point.z;

      cylinder_coeff.values[3] = ea[0];
      cylinder_coeff.values[4] = ea[1];
      cylinder_coeff.values[5] = ea[2];

      Eigen::Vector3d vec = Eigen::Vector3d::UnitZ () * -1.;
      Eigen::Matrix3d matrixxx;

      matrixxx = Eigen::AngleAxisd (ea[0], Eigen::Vector3d::UnitX ()) * Eigen::AngleAxisd (ea[1], Eigen::Vector3d::UnitY ())
          * Eigen::AngleAxisd (ea[2], Eigen::Vector3d::UnitZ ());

      //matrixxx = pose_mat.block<3,3>(0,0);
      vec = matrixxx * vec;

      cylinder_coeff.values[3] = vec[0];
      cylinder_coeff.values[4] = vec[1];
      cylinder_coeff.values[5] = vec[2];

      cylinder_coeff.values[6] = 0.01;
      vis.addCylinder (cylinder_coeff, "cylinder");
    }
  }

  vis.setRepresentationToSurfaceForAllActors ();

  if (VIDEO)
  {
    vis.spinOnce (50, true);
  } else
  {
    vis.spin ();
  }

  vis.removeAllPointClouds ();
  vis.removeAllShapes ();
}
예제 #12
0
  void fillVisualizerWithLock(pcl::visualization::PCLVisualizer &visualizer, const bool firstRun)
  {
    const std::string &cloudname = this->name;

    if(firstRun)
    {
      visualizer.addPointCloud(cloud, cloudname);
      visualizer.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, pointSize, cloudname);
    }
    else
    {
      visualizer.updatePointCloud(cloud, cloudname);
      visualizer.getPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, pointSize, cloudname);
      visualizer.removeAllShapes();
    }

    visualizer.addLine(pcl::PointXYZ(0, 0, 0), pcl::PointXYZ(0.2, 0, 0), 1, 0, 0, "X");
    visualizer.addLine(pcl::PointXYZ(0, 0, 0), pcl::PointXYZ(0, 0.2, 0), 0, 1, 0, "Y");
    visualizer.addLine(pcl::PointXYZ(0, 0, 0), pcl::PointXYZ(0, 0, 0.2), 0, 0, 1, "Z");

    tf::Vector3 origin = worldToCam * tf::Vector3(0, 0, 0);
    tf::Vector3 lineX = worldToCam * tf::Vector3(0.2, 0, 0);
    tf::Vector3 lineY = worldToCam * tf::Vector3(0, 0.2, 0);
    tf::Vector3 lineZ = worldToCam * tf::Vector3(0, 0, 0.2);

    pcl::PointXYZ pclOrigin(origin.x(), origin.y(), origin.z());
    pcl::PointXYZ pclLineX(lineX.x(), lineX.y(), lineX.z());
    pcl::PointXYZ pclLineY(lineY.x(), lineY.y(), lineY.z());
    pcl::PointXYZ pclLineZ(lineZ.x(), lineZ.y(), lineZ.z());

    visualizer.addLine(pcl::PointXYZ(0, 0, 0), pclOrigin, 1, 1, 1, "line");
    visualizer.addLine(pclOrigin, pclLineX, 1, 0, 0, "lineX");
    visualizer.addLine(pclOrigin, pclLineY, 0, 1, 0, "lineY");
    visualizer.addLine(pclOrigin, pclLineZ, 0, 0, 1, "lineZ");

    for(int i = 0; i < regions.size(); ++i)
    {
      const Region &region = regions[i];
      tf::Transform transform = worldToCam * region.transform;

      std::ostringstream oss;
      oss << "region_" << i;

      tf::Vector3 originB = transform * tf::Vector3(0, 0, 0);
      tf::Vector3 lineXB = transform * tf::Vector3(0.2, 0, 0);
      tf::Vector3 lineYB = transform * tf::Vector3(0, 0.2, 0);
      tf::Vector3 lineZB = transform * tf::Vector3(0, 0, 0.2);

      pcl::PointXYZ pclOriginB(originB.x(), originB.y(), originB.z());
      pcl::PointXYZ pclLineXB(lineXB.x(), lineXB.y(), lineXB.z());
      pcl::PointXYZ pclLineYB(lineYB.x(), lineYB.y(), lineYB.z());
      pcl::PointXYZ pclLineZB(lineZB.x(), lineZB.y(), lineZB.z());

      visualizer.addLine(pclOrigin, pclOriginB, 1, 1, 1, "line_" + oss.str());
      visualizer.addLine(pclOriginB, pclLineXB, 1, 0, 0, "lineX_" + oss.str());
      visualizer.addLine(pclOriginB, pclLineYB, 0, 1, 0, "lineY_" + oss.str());
      visualizer.addLine(pclOriginB, pclLineZB, 0, 0, 1, "lineZ_" + oss.str());

      Eigen::Vector3d translation;
      Eigen::Quaterniond rotation;

      tf::vectorTFToEigen(transform.getOrigin(), translation);
      tf::quaternionTFToEigen(transform.getRotation(), rotation);

      visualizer.addCube(translation.cast<float>(), rotation.cast<float>(), region.width, region.height, region.depth, oss.str());
    }
  }
예제 #13
0
파일: show_pts.cpp 프로젝트: fxia22/tinker
int main(int argc, char** argv)
{
    int total_frame = 0;

    ros::init(argc, argv, "pub_pcl");
    ros::NodeHandle nh;
    ros::Publisher pub = nh.advertise<PointCloudT>("/openni/points2", 1);

    // Read
    PointCloudT::Ptr cloud(new PointCloudT);
    bool new_cloud_avaliable_flag = false;
    pcl::Grabber* interface = new pcl::OpenNIGrabber();
    boost::function<void (const PointCloudT::ConstPtr&)> f = boost::bind(&cloud_cb_, _1, cloud, &new_cloud_avaliable_flag);
    interface->registerCallback(f);
    interface->start();

    // Wait for the first frame
    while (!new_cloud_avaliable_flag)
    {
        boost::this_thread::sleep(boost::posix_time::milliseconds(1));
    }
    cloud_mutex.lock();     // for not overwriting the point cloud

    // Display
    printf("frame %d\n", ++total_frame);
    pcl::visualization::PointCloudColorHandlerRGBField<PointT> rgb(cloud);
    viewer.addPointCloud<PointT>(cloud, rgb, "input_cloud");
    viewer.setCameraPosition(0, 0, -2, 0, -1, 0, 0);

    cloud_mutex.unlock();

    ros::Rate loop_rate(4);
    while (nh.ok())
    {
        ros::Time scan_time = ros::Time::now();
        
        // Get & publish new cloud
        if (new_cloud_avaliable_flag && cloud_mutex.try_lock())
        {
            new_cloud_avaliable_flag = false;
            pub.publish(cloud);

            printf("frame %d\n", ++total_frame);
            viewer.removeAllPointClouds();
            viewer.removeAllShapes();
            pcl::visualization::PointCloudColorHandlerRGBField<PointT> rgb(cloud);
            viewer.addPointCloud<PointT>(cloud, rgb, "input_cloud");

            cloud_mutex.unlock();
        }
        else
        {
            printf("no %d\n", total_frame);
        }

        ros::spinOnce();
        loop_rate.sleep();
    }

    return 0;
}