void compute (const pcl::PCLPointCloud2::ConstPtr &input, pcl::PCLPointCloud2 &output, double search_radius, bool sqr_gauss_param_set, double sqr_gauss_param, int polynomial_order) { PointCloud<PointXYZ>::Ptr xyz_cloud_pre (new pcl::PointCloud<PointXYZ> ()), xyz_cloud (new pcl::PointCloud<PointXYZ> ()); fromPCLPointCloud2 (*input, *xyz_cloud_pre); // Filter the NaNs from the cloud for (size_t i = 0; i < xyz_cloud_pre->size (); ++i) if (pcl_isfinite (xyz_cloud_pre->points[i].x)) xyz_cloud->push_back (xyz_cloud_pre->points[i]); xyz_cloud->header = xyz_cloud_pre->header; xyz_cloud->height = 1; xyz_cloud->width = static_cast<uint32_t> (xyz_cloud->size ()); xyz_cloud->is_dense = false; PointCloud<PointNormal>::Ptr xyz_cloud_smoothed (new PointCloud<PointNormal> ()); MovingLeastSquares<PointXYZ, PointNormal> mls; mls.setInputCloud (xyz_cloud); mls.setSearchRadius (search_radius); if (sqr_gauss_param_set) mls.setSqrGaussParam (sqr_gauss_param); mls.setPolynomialOrder (polynomial_order); // mls.setUpsamplingMethod (MovingLeastSquares<PointXYZ, PointNormal>::SAMPLE_LOCAL_PLANE); // mls.setUpsamplingMethod (MovingLeastSquares<PointXYZ, PointNormal>::RANDOM_UNIFORM_DENSITY); // mls.setUpsamplingMethod (MovingLeastSquares<PointXYZ, PointNormal>::VOXEL_GRID_DILATION); mls.setUpsamplingMethod (MovingLeastSquares<PointXYZ, PointNormal>::NONE); mls.setPointDensity (60000 * int (search_radius)); // 300 points in a 5 cm radius mls.setUpsamplingRadius (0.025); mls.setUpsamplingStepSize (0.015); mls.setDilationIterations (2); mls.setDilationVoxelSize (0.01f); search::KdTree<PointXYZ>::Ptr tree (new search::KdTree<PointXYZ> ()); mls.setSearchMethod (tree); mls.setComputeNormals (true); PCL_INFO ("Computing smoothed surface and normals with search_radius %f , sqr_gaussian_param %f, polynomial order %d\n", mls.getSearchRadius(), mls.getSqrGaussParam(), mls.getPolynomialOrder()); TicToc tt; tt.tic (); mls.process (*xyz_cloud_smoothed); print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", xyz_cloud_smoothed->width * xyz_cloud_smoothed->height); print_info (" points]\n"); toPCLPointCloud2 (*xyz_cloud_smoothed, output); }
int main (int argc, char **argv) { /* if (argc != 1) { PCL_ERROR ("Syntax: %s input.pcd output.ply\n", argv[0]); return -1; }*/ PointCloud<PointXYZ>::Ptr cloud (new PointCloud<PointXYZ> ()); io::loadPCDFile (argv[1], *cloud); MovingLeastSquares<PointXYZ, PointXYZ> mls; mls.setInputCloud (cloud); mls.setSearchRadius (4); mls.setPolynomialFit (true); mls.setPolynomialOrder (1); mls.setUpsamplingMethod (MovingLeastSquares<PointXYZ, PointXYZ>::SAMPLE_LOCAL_PLANE); mls.setUpsamplingRadius (1); mls.setUpsamplingStepSize (0.03); PointCloud<PointXYZ>::Ptr cloud_smoothed (new PointCloud<PointXYZ> ()); mls.process (*cloud_smoothed); NormalEstimationOMP<PointXYZ, Normal> ne; ne.setNumberOfThreads (8); ne.setInputCloud (cloud_smoothed); ne.setRadiusSearch (0.8); Eigen::Vector4f centroid; compute3DCentroid (*cloud_smoothed, centroid); ne.setViewPoint (centroid[0], centroid[1], centroid[2]); PointCloud<Normal>::Ptr cloud_normals (new PointCloud<Normal> ()); ne.compute (*cloud_normals); for (size_t i = 0; i < cloud_normals->size (); ++i) { cloud_normals->points[i].normal_x *= -1; cloud_normals->points[i].normal_y *= -1; cloud_normals->points[i].normal_z *= -1; } PointCloud<PointNormal>::Ptr cloud_smoothed_normals (new PointCloud<PointNormal> ()); concatenateFields (*cloud_smoothed, *cloud_normals, *cloud_smoothed_normals); Poisson<pcl::PointNormal> poisson; poisson.setDepth (9); poisson.setInputCloud (cloud_smoothed_normals); PolygonMesh mesh_poisson; poisson.reconstruct (mesh_poisson); pcl::io::savePLYFile("mesh.ply", mesh_poisson); return 0; }
void compute (const sensor_msgs::PointCloud2::ConstPtr &input, sensor_msgs::PointCloud2 &output, double search_radius, bool sqr_gauss_param_set, double sqr_gauss_param, bool use_polynomial_fit, int polynomial_order) { PointCloud<PointXYZ>::Ptr xyz_cloud_pre (new pcl::PointCloud<PointXYZ> ()), xyz_cloud (new pcl::PointCloud<PointXYZ> ()); fromROSMsg (*input, *xyz_cloud_pre); // Filter the NaNs from the cloud for (size_t i = 0; i < xyz_cloud_pre->size (); ++i) if (pcl_isfinite (xyz_cloud_pre->points[i].x)) xyz_cloud->push_back (xyz_cloud_pre->points[i]); xyz_cloud->header = xyz_cloud_pre->header; xyz_cloud->height = 1; xyz_cloud->width = xyz_cloud->size (); xyz_cloud->is_dense = false; // io::savePCDFile ("test.pcd", *xyz_cloud); PointCloud<PointXYZ>::Ptr xyz_cloud_smoothed (new PointCloud<PointXYZ> ()); MovingLeastSquares<PointXYZ, Normal> mls; mls.setInputCloud (xyz_cloud); mls.setSearchRadius (search_radius); if (sqr_gauss_param_set) mls.setSqrGaussParam (sqr_gauss_param); mls.setPolynomialFit (use_polynomial_fit); mls.setPolynomialOrder (polynomial_order); // mls.setUpsamplingMethod (MovingLeastSquares<PointXYZ, Normal>::SAMPLE_LOCAL_PLANE); mls.setUpsamplingMethod (MovingLeastSquares<PointXYZ, Normal>::UNIFORM_DENSITY); // mls.setUpsamplingMethod (MovingLeastSquares<PointXYZ, Normal>::FILL_HOLES); // mls.setUpsamplingMethod (MovingLeastSquares<PointXYZ, Normal>::NONE); mls.setFillingStepSize (0.02); mls.setPointDensity (50000*search_radius); // 300 points in a 5 cm radius mls.setUpsamplingRadius (0.025); mls.setUpsamplingStepSize (0.015); search::KdTree<PointXYZ>::Ptr tree (new search::KdTree<PointXYZ> ()); mls.setSearchMethod (tree); PointCloud<Normal>::Ptr mls_normals (new PointCloud<Normal> ()); mls.setOutputNormals (mls_normals); PCL_INFO ("Computing smoothed surface and normals with search_radius %f , sqr_gaussian_param %f, polynomial fitting %d, polynomial order %d\n", mls.getSearchRadius(), mls.getSqrGaussParam(), mls.getPolynomialFit(), mls.getPolynomialOrder()); TicToc tt; tt.tic (); mls.reconstruct (*xyz_cloud_smoothed); print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", xyz_cloud_smoothed->width * xyz_cloud_smoothed->height); print_info (" points]\n"); sensor_msgs::PointCloud2 output_positions, output_normals; // printf ("sizes: %d %d %d\n", xyz_cloud_smoothed->width, xyz_cloud_smoothed->height, xyz_cloud_smoothed->size ()); toROSMsg (*xyz_cloud_smoothed, output_positions); toROSMsg (*mls_normals, output_normals); concatenateFields (output_positions, output_normals, output); PointCloud<PointXYZ> xyz_vg; VoxelGrid<PointXYZ> vg; vg.setInputCloud (xyz_cloud_smoothed); vg.setLeafSize (0.005, 0.005, 0.005); vg.filter (xyz_vg); sensor_msgs::PointCloud2 xyz_vg_2; toROSMsg (xyz_vg, xyz_vg_2); pcl::io::savePCDFile ("cloud_vg.pcd", xyz_vg_2, Eigen::Vector4f::Zero (), Eigen::Quaternionf::Identity (), true); }