1.VS代码实现

声明：代可以在vs2019+pcl1.11.1上直接运行；由于没有RGBA数据，在demo点云文件上增加了RGBA信息，验证了代码的可行性。

#include <pcl/console/parse.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/segmentation/supervoxel_clustering.h>
#include <boost/make_shared.hpp>
#include <vtkPolyLine.h>    //  这句需要添加，否则会报错// Types
typedef pcl::PointXYZRGBA PointT;
typedef pcl::PointCloud<PointT> PointCloudT;
typedef pcl::PointNormal PointNT;
typedef pcl::PointCloud<PointNT> PointNCloudT;
typedef pcl::PointXYZL PointLT;
typedef pcl::PointCloud<PointLT> Pointvoid addSupervoxelConnectionsToViewer(PointT& supervoxel_center, PointCloudT& adjacent_supervoxel_centers,std::string supervoxel_name,boost::shared_ptr<pcl::visualization::PCLVisualizer>& viewer)
{vtkSmartPointer<vtkPoints> points = vtkSmartPointer<vtkPoints>::New();vtkSmartPointer<vtkCellArray> cells = vtkSmartPointer<vtkCellArray>::New();vtkSmartPointer<vtkPolyLine>  polyLine = vtkSmartPointer<vtkPolyLine>::New();//Iterate through all adjacent points, and add a center point to adjacent point pairPointCloudT::iterator adjacent_itr = adjacent_supervoxel_centers.begin();for (; adjacent_itr != adjacent_supervoxel_centers.end(); ++adjacent_itr){points->InsertNextPoint(supervoxel_center.data);points->InsertNextPoint(adjacent_itr->data);}// Create a polydata to store everything invtkSmartPointer<vtkPolyData> polyData = vtkSmartPointer<vtkPolyData>::New();// Add the points to the datasetpolyLine->GetPointIds()->SetNumberOfIds(points->GetNumberOfPoints());for (unsigned int i = 0; i < points->GetNumberOfPoints(); i++)polyLine->GetPointIds()->SetId(i, i);cells->InsertNextCell(polyLine);// Add the lines to the datasetpolyData->SetLines(cells);viewer->addModelFromPolyData(polyData, supervoxel_name);}bool superVoxelClustering()
{std::string cloudPath = "data/table_scene_lms400_sample.pcd";PointCloudT::Ptr cloud (new PointCloudT());pcl::PointCloud<pcl::PointXYZ>::Ptr cloudTmp(new pcl::PointCloud<pcl::PointXYZ>);pcl::console::print_highlight("Loading point cloud...\n");if (pcl::io::loadPCDFile<pcl::PointXYZ>("data/table_scene_lms400_sample.pcd", *cloudTmp)){return (1);}float minZ = 10000000.0, maxZ = -10000;for (int i = 0; i < 11000; i++){if (cloudTmp->at(i).z > maxZ){maxZ = cloudTmp->at(i).z;}if (cloudTmp->at(i).z < minZ){minZ = cloudTmp->at(i).z;}}cloud->resize(11000);for (int i = 0; i < 11000; i++){cloud->at(i).x = cloudTmp->at(i).x;cloud->at(i).y = cloudTmp->at(i).y;cloud->at(i).z = cloudTmp->at(i).z;cloud->at(i).r = (cloudTmp->at(i).z - minZ) / (maxZ - minZ)*255.0;cloud->at(i).g = 0;cloud->at(i).b = 0;cloud->at(i).a = (cloudTmp->at(i).z - minZ) / (maxZ - minZ) * 255.0;}float voxel_resolution = 0.008f;float seed_resolution = 0.1f;float color_importance = 0.2f;float spatial_importance = 0.4f;float normal_importance = 1.0f;bool use_tranform = true;
pcl::SupervoxelClustering<PointT> super(voxel_resolution, seed_resolution);super.setInputCloud(cloud);super.setColorImportance(color_importance);super.setSpatialImportance(spatial_importance);super.setNormalImportance(normal_importance);std::map <uint32_t, pcl::Supervoxel<PointT>::Ptr > supervoxel_clusters;super.extract(supervoxel_clusters);
supervoxel_clusters.size());boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));viewer->setBackgroundColor(0, 0, 0);PointCloudT::Ptr voxel_centroid_cloud = super.getVoxelCentroidCloud();viewer->addPointCloud(voxel_centroid_cloud, "voxel centroids");viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 2.0, "voxel centroids");viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_OPACITY, 0.95, "voxel centroids");PointCloudT::Ptr colored_voxel_cloud = super.getColoredCloud();viewer->addPointCloud(colored_voxel_cloud, "colored voxels");viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_OPACITY, 0.8, "colored voxels");PointNCloudT::Ptr sv_normal_cloud = super.makeSupervoxelNormalCloud(supervoxel_clusters);pcl::console::print_highlight("Getting supervoxel adjacency\n");std::multimap<uint32_t, uint32_t> supervoxel_adjacency;super.getSupervoxelAdjacency(supervoxel_adjacency);std::multimap<uint32_t, uint32_t>::iterator label_itr = supervoxel_adjacency.begin();for (; label_itr != supervoxel_adjacency.end(); ){uint32_t supervoxel_label = label_itr->first;//Now get the supervoxel corresponding to the labelpcl::Supervoxel<PointT>::Ptr supervoxel = supervoxel_clusters.at(supervoxel_label);PointCloudT adjacent_supervoxel_centers;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){pcl::Supervoxel<PointT>::Ptr neighbor_supervoxel = supervoxel_clusters.at(adjacent_itr->second);adjacent_supervoxel_centers.push_back(neighbor_supervoxel->centroid_);}std::stringstream ss;ss << "supervoxel_" << supervoxel_label;addSupervoxelConnectionsToViewer(supervoxel->centroid_, adjacent_supervoxel_centers, ss.str(), viewer);label_itr = supervoxel_adjacency.upper_bound(supervoxel_label);}while (!viewer->wasStopped()){viewer->spinOnce(100);}return true;
}

2.点云数据

3.结果

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PCL超体素分割代码vs2019+pcl1.11.1实现

文章目录

1.VS代码实现

2.点云数据

3.结果

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