void PC_to_Mat(PointCloudT::Ptr &cloud, cv::Mat &result){

  if (cloud->isOrganized()) {
    std::cout << "PointCloud is organized..." << std::endl;

    result = cv::Mat(cloud->height, cloud->width, CV_8UC3);

    if (!cloud->empty()) {

      for (int h=0; h<result.rows; h++) {
        for (int w=0; w<result.cols; w++) {
            PointT point = cloud->at(w, h);

            Eigen::Vector3i rgb = point.getRGBVector3i();

            result.at<cv::Vec3b>(h,w)[0] = rgb[2];
            result.at<cv::Vec3b>(h,w)[1] = rgb[1];
            result.at<cv::Vec3b>(h,w)[2] = rgb[0];
        }
      }
    }
  }
}
Beispiel #2
0
void filter_PC_from_BB(PointCloudT::Ptr &cloud, cv::Mat &result, int x, int y, int width, int height){

  const float bad_point = std::numeric_limits<float>::quiet_NaN();

  if (cloud->isOrganized()) {
    std::cout << "PointCloud is organized..." << std::endl;
    result = cv::Mat(cloud->height, cloud->width, CV_8UC3);

    if (!cloud->empty()) {

      for (int h=0; h<result.rows; h++) {
        for (int w=0; w<result.cols; w++) {
            
            // Check if in bounding window
            if ( (h>y && h<(y+height)) && ((w > x) && w < (x+width)) ){
            
              // do nothing

            } else {

              // remove point
              //PointT point = cloud->at(w, h);
              //cloud->at(w, h);
              cloud->at(w, h).x = bad_point;
              cloud->at(w, h).y = bad_point;
              cloud->at(w, h).z = bad_point;
              
              cloud->at(w, h).r = bad_point;
              cloud->at(w, h).g = bad_point;
              cloud->at(w, h).b = bad_point;
            }
        }
      }
    }
  }
}