天津市津南区钟城铁粉厂

以下是6个点云精简的实现代码，分别使用了不同的算法和库：

1. 使用PCL库进行体素下采样 ```cpp #include <pcl/common/common.h> #include <pcl/filters/voxel_grid.h> pcl::PointCloud<pcl::PointXYZ>::Ptr downsample(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, float voxel_size) { pcl::PointCloud<pcl::PointXYZ>::Ptr downsampled_cloud(new pcl::PointCloud<pcl::PointXYZ>); pcl::VoxelGrid<pcl::PointXYZ> voxel_grid; voxel_grid.setInputCloud(cloud); voxel_grid.setLeafSize(voxel_size, voxel_size, voxel_size); voxel_grid.filter(*downsampled_cloud); return downsampled_cloud; } ``` 2. 使用Open3D库进行体素下采样 ```python import open3d as o3d def downsample(cloud, voxel_size): downsampled_cloud = cloud.voxel_down_sample(voxel_size) return downsampled_cloud ``` 3. 使用PyVista库进行体素下采样 ```python import pyvista as pv def downsample(cloud, voxel_size): downsampled_cloud = cloud.voxel_down_sample(voxel_size) return downsampled_cloud ``` 4. 使用VTK库进行体素下采样 ```cpp #include <vtkSmartPointer.h> #include <vtkPoints.h> #include <vtkPolyData.h> #include <vtkPointSet.h> #include <vtkPointSource.h> #include <vtkXMLPolyDataWriter.h> #include <vtkXMLPolyDataReader.h> #include <vtkPLYReader.h> #include <vtkPLYWriter.h> #include <vtkPCDReader.h> #include <vtkPCDWriter.h> #include <vtkVoxel.h> #include <vtkVoxelModeller.h> vtkSmartPointer<vtkPolyData> downsample(vtkSmartPointer<vtkPolyData> cloud, double voxel_size) { vtkSmartPointer<vtkVoxelModeller> voxel_modeller = vtkSmartPointer<vtkVoxelModeller>::New(); voxel_modeller->SetInputData(cloud); voxel_modeller->SetSampleDimensions(voxel_size, voxel_size, voxel_size); voxel_modeller->Update(); vtkSmartPointer<vtkPolyData> downsampled_cloud = vtkSmartPointer<vtkPolyData>::New(); downsampled_cloud->ShallowCopy(voxel_modeller->GetOutput()); return downsampled_cloud; } ``` 5. 使用CGAL库进行点云网格化 ```cpp #include <CGAL/Point_set_3.h> #include <CGAL/Point_set_3/IO.h> #include <CGAL/Polygon_mesh_processing/polygon_soup_to_polygon_mesh.h> typedef CGAL::Point_set_3<CGAL::Simple_cartesian<double>> Point_set_3; void downsample(Point_set_3& cloud, double voxel_size) { CGAL::Polygon_mesh_processing::polygon_soup_to_polygon_mesh(cloud.points().begin(), cloud.points().end(), cloud.facets().begin(), cloud.facets().end(), voxel_size); } ``` 6. 使用MeshLab进行点云简化 ```python import pymeshlab as ml def simplify(cloud, target_faces): ms = ml.MeshSet() ms.load_new_mesh(cloud) ms.simplification_quadric_edge_collapse_decimation(targetfacenum=target_faces) simplified_cloud = ms.current_mesh() return simplified_cloud