超体聚类+LCCP实现

pcl的官方教程中有实现的代码，但之前一直得不到分割后带标记的点云，输出点云的label全部是0。最后发现，getlabelcloud()函数是可以得到有label且不为0的点云的，但是这个点云不可以使用pcl中的pcl::savePCDFile来保存成pcd文件，这样保存的pcd文件的label都是0，又没找到可视化的工具，所以就新建一个pcl::PointXYZRGB类型的点云，重新对其赋值，进而得到可以用pcl::savePCDFile的点云文件。最终输出4个点云文件，分别是超体聚类后有xyz和label的.txt文件、为了在视觉上更容易区分根据不同label给随机颜色的.pcd文件；以及在LCCP之后，数据类型为xyz和label的.txt文件、为了在视觉上更容易区分根据不同label给随机颜色的.pcd文件。

本来实时性就不够好，为了给不同label的点赋上随机颜色，循环里又套了一个循环，所以运行时间有点长。参数根据数据得更改，代码如下：

//超体聚类+LCCP#include "stdafx.h"#include <stdlib.h>  #include <cmath>  #include <limits.h>  #include <boost/format.hpp>  #include <fstream> #include <pcl/console/parse.h>  #include <pcl/io/pcd_io.h>  #include <pcl/visualization/pcl_visualizer.h>  #include <pcl/visualization/point_cloud_color_handlers.h>  #include <pcl/visualization/cloud_viewer.h>#include <pcl/filters/passthrough.h>  #include <pcl/segmentation/supervoxel_clustering.h>  #include <pcl/segmentation/lccp_segmentation.h>  #define Random(x) (rand() % x)typedef pcl::PointXYZRGBA PointT;typedef pcl::LCCPSegmentation<PointT>::SupervoxelAdjacencyList SuperVoxelAdjacencyList;int main(int argc, char ** argv){//输入点云  pcl::PointCloud<PointT>::Ptr input_cloud_ptr(new pcl::PointCloud<PointT>);pcl::PCLPointCloud2 input_pointcloud2;if (pcl::io::loadPCDFile("xyzrgb.pcd", input_pointcloud2)){PCL_ERROR("ERROR: Could not read input point cloud ");return (3);}pcl::fromPCLPointCloud2(input_pointcloud2, *input_cloud_ptr);PCL_INFO("Done making cloud\n");float voxel_resolution = 0.3f;float seed_resolution = 1.2f;float color_importance = 0.0f;float spatial_importance = 1.0f;float normal_importance = 0.0f;bool use_single_cam_transform = false;bool use_supervoxel_refinement = false;unsigned int k_factor = 0;pcl::SupervoxelClustering<PointT> super(voxel_resolution, seed_resolution);super.setUseSingleCameraTransform(use_single_cam_transform);super.setInputCloud(input_cloud_ptr);  super.setColorImportance(color_importance);super.setSpatialImportance(spatial_importance);super.setNormalImportance(normal_importance);std::map<uint32_t, pcl::Supervoxel<PointT>::Ptr> supervoxel_clusters;PCL_INFO("Extracting supervoxels\n");super.extract(supervoxel_clusters);PCL_INFO("Getting supervoxel adjacency\n");std::multimap<uint32_t, uint32_t> supervoxel_adjacency;super.getSupervoxelAdjacency(supervoxel_adjacency);pcl::PointCloud<pcl::PointXYZL>::Ptr overseg = super.getLabeledCloud();ofstream outFile1("过分割3.txt", std::ios_base::out);for (int i = 0; i < overseg->size(); i++) {outFile1 << overseg->points[i].x << "\t" << overseg->points[i].y << "\t" << overseg->points[i].z << "\t" << overseg->points[i].label << endl;}int label_max1 = 0;for (int i = 0;i< overseg->size(); i++) {if (overseg->points[i].label>label_max1)label_max1 = overseg->points[i].label;}pcl::PointCloud<pcl::PointXYZRGB>::Ptr ColoredCloud1(new pcl::PointCloud<pcl::PointXYZRGB>);ColoredCloud1->height = 1;ColoredCloud1->width = overseg->size();ColoredCloud1->resize(overseg->size());for (int i = 0; i < label_max1; i++) {int color_R = Random(255);int color_G = Random(255);int color_B = Random(255);for (int j = 0; j < overseg->size(); j++) {if (overseg->points[j].label == i) {ColoredCloud1->points[j].x = overseg->points[j].x;ColoredCloud1->points[j].y = overseg->points[j].y;ColoredCloud1->points[j].z = overseg->points[j].z;ColoredCloud1->points[j].r = color_R;ColoredCloud1->points[j].g = color_G;ColoredCloud1->points[j].b = color_B;}}}pcl::io::savePCDFileASCII("过分割3.pcd", *ColoredCloud1);//LCCP分割  float concavity_tolerance_threshold = 10;float smoothness_threshold = 0.1;uint32_t min_segment_size = 0;bool use_extended_convexity = false;bool use_sanity_criterion = false;PCL_INFO("Starting Segmentation\n");pcl::LCCPSegmentation<PointT> lccp;lccp.setConcavityToleranceThreshold(concavity_tolerance_threshold);lccp.setSmoothnessCheck(true, voxel_resolution, seed_resolution, smoothness_threshold);lccp.setKFactor(k_factor);lccp.setInputSupervoxels(supervoxel_clusters, supervoxel_adjacency);lccp.setMinSegmentSize(min_segment_size);lccp.segment();PCL_INFO("Interpolation voxel cloud -> input cloud and relabeling\n");pcl::PointCloud<pcl::PointXYZL>::Ptr sv_labeled_cloud = super.getLabeledCloud();pcl::PointCloud<pcl::PointXYZL>::Ptr lccp_labeled_cloud = sv_labeled_cloud->makeShared();lccp.relabelCloud(*lccp_labeled_cloud);SuperVoxelAdjacencyList sv_adjacency_list;lccp.getSVAdjacencyList(sv_adjacency_list);ofstream outFile2("分割后合并3.txt", std::ios_base::out);for (int i = 0; i < lccp_labeled_cloud->size();i++) {outFile2 << lccp_labeled_cloud->points[i].x << "\t" << lccp_labeled_cloud->points[i].y << "\t" << lccp_labeled_cloud->points[i].z << "\t" << lccp_labeled_cloud->points[i].label << endl;}int label_max2 = 0;for (int i = 0; i< lccp_labeled_cloud->size(); i++) {if (lccp_labeled_cloud->points[i].label>label_max2)label_max2 = lccp_labeled_cloud->points[i].label;}pcl::PointCloud<pcl::PointXYZRGB>::Ptr ColoredCloud2(new pcl::PointCloud<pcl::PointXYZRGB>);ColoredCloud2->height = 1;ColoredCloud2->width = lccp_labeled_cloud->size();ColoredCloud2->resize(lccp_labeled_cloud->size());for (int i = 0; i < label_max2; i++) {int color_R = Random(255);int color_G = Random(255);int color_B = Random(255);for (int j = 0; j < lccp_labeled_cloud->size(); j++) {if (lccp_labeled_cloud->points[j].label == i) {ColoredCloud2->points[j].x = lccp_labeled_cloud->points[j].x;ColoredCloud2->points[j].y = lccp_labeled_cloud->points[j].y;ColoredCloud2->points[j].z = lccp_labeled_cloud->points[j].z;ColoredCloud2->points[j].r = color_R;ColoredCloud2->points[j].g = color_G;ColoredCloud2->points[j].b = color_B;}}}pcl::io::savePCDFileASCII("分割后合并3.pcd", *ColoredCloud2);return 0;}