point.y = 1024 * rand() / (RAND_MAX + 1.0f); point.z = 1024 * rand() / (RAND_MAX + 1.0f); } /***删除***/ pcl::PointCloud<pcl::PointXYZ>::iterator index = cloud_ptr->begin(); cloud_ptr->erase(index); //删除第1个 index = cloud_ptr->begin() + 5; cloud_ptr->er...
point.x = (w - C_X) * point.z * rgbFocalInvertedX ;//(w - 319.5); //321.075 1024 * rand () / (RAND_MAX + 1.0f) //(w - 319.5) * point.z * rgbFocalInvertedX;point.y = (h - C_Y) * point.z * rgbFocalInvertedY;//248.919//(h - 239.5) * point.z * rgbFocalInver...
cloud.height = 1; cloud.is_dense = false; cloud.points.resize(cloud.height*cloud.width); for ( size_t i=0; i<cloud.points.size(); ++i ) { cloud.points[i].x = 1024* rand()/(RAND_MAX+1.0f); cloud.points[i].y = 1024* rand()/(RAND_MAX+1.0f); cloud.points[i].z = 102...
1. 理解pcl::PointCloud的数据结构和Ptr的含义 pcl::PointCloud<pcl::PointXYZ> 是PCL(Point Cloud Library)中用于表示点云数据的一个模板类,其中pcl::PointXYZ 是一个表示3D点的结构体,包含x、y、z三个坐标值。 pcl::PointCloud<pcl::PointXYZ>::Ptr 是一个智能指针,用于管理pcl::Point...
cloud.points[i].x = 1024 *rand() / (RAND_MAX + 1.0f); cloud.points[i].y = 1024 *rand() / (RAND_MAX + 1.0f); cloud.points[i].z = 1024 *rand() / (RAND_MAX + 1.0f); } //Convert the cloud to ROS message pcl::toROSMsg(cloud, output); ...
cloud.points[i].x = 1024 *rand() / (RAND_MAX + 1.0f); cloud.points[i].y = 1024 *rand() / (RAND_MAX + 1.0f); cloud.points[i].z = 1024 *rand() / (RAND_MAX + 1.0f); } //Convert the cloud to ROS message pcl::toROSMsg(cloud, output); ...
cloud.points[i].x = 1024 * rand () / (RAND_MAX + 1.0f);cloud.points[i].y = 1024 * rand () / (RAND_MAX + 1.0f);cloud.points[i].z = 1024 * rand () / (RAND_MAX + 1.0f);} //Convert the cloud to ROS message pcl::toROSMsg(cloud, output);output.header.frame_id ...
cloud_in->height = 1; cloud_in->is_dense = false; cloud_in->points.resize (cloud_in->width * cloud_in->height); for (size_t i = 0; i < cloud_in->points.size(); ++i) { cloud_in->points[i].x = 1024 * rand () / (RAND_MAX + 1.0f); ...
[i].x=1024*rand()/(RAND_MAX+1.0f);cloud.points[i].y=1024*rand()/(RAND_MAX+1.0f);cloud.points[i].z=1024*rand()/(RAND_MAX+1.0f);}pcl::io::savePCDFileASCII("test_pcd.pcd",cloud);std::cerr<<"Saved"<<cloud.points.size()<<"data points to test_pcd.pcd"<<std::endl;for(...
cloud->height = 1; cloud->is_dense = false; cloud->resize(cloud->width * cloud->height); for (auto& point : *cloud) { point.x = 1024 * rand() / (RAND_MAX + 1.0f); point.y = 1024 * rand() / (RAND_MAX + 1.0f); point.z = 1024 * rand() / (RAND_MAX + 1.0f); ...