pcl边界识别

#include 
#include 
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#include 
using namespace std;

int main(int argc, char **argv)
{
        pcl::PointCloud::Ptr cloud (new pcl::PointCloud);
        // if (pcl::io::loadPCDFile("/home/yxg/pcl/pcd/mid.pcd",*cloud) == -1)
        if (pcl::io::loadPCDFile(argv[1],*cloud) == -1)
        {
                PCL_ERROR("COULD NOT READ FILE mid.pcl \n");
                return (-1);
        }
        
        std::cout << "points sieze is:"<< cloud->size()<::Ptr normals (new pcl::PointCloud);
        pcl::PointCloud boundaries;
        pcl::BoundaryEstimation est;
        pcl::search::KdTree::Ptr tree(new pcl::search::KdTree());
        /*
        pcl::KdTreeFLANN kdtree;  //创建一个快速k近邻查询,查询的时候若该点在点云中，则第一个近邻点是其本身
        kdtree.setInputCloud(cloud);
        int k =2;
        float everagedistance =0;
        for (int i =0; i < cloud->size()/2;i++)
        {
                vector nnh ;
                vector squaredistance;
                //  pcl::PointXYZ p;
                //   p = cloud->points[i];
                kdtree.nearestKSearch(cloud->points[i],k,nnh,squaredistance);
                everagedistance += sqrt(squaredistance[1]);
                //   cout<size()/2);
        cout<<"everage distance is : "< normEst;  //其中pcl::PointXYZ表示输入类型数据，pcl::Normal表示输出类型,且pcl::Normal前三项是法向，最后一项是曲率
        normEst.setInputCloud(cloud);
        normEst.setSearchMethod(tree);
        // normEst.setRadiusSearch(2);  //法向估计的半径
        normEst.setKSearch(9);  //法向估计的点数
        normEst.compute(*normals);
        cout<<"normal size is "<< normals->size()<::Ptr (new pcl::search::KdTree));
        est.setSearchMethod (tree);
        est.setKSearch(20);  //一般这里的数值越高，最终边界识别的精度越好
        //  est.setRadiusSearch(everagedistance);  //搜索半径
        est.compute (boundaries);

        //  pcl::PointCloud boundPoints;
        pcl::PointCloud::Ptr boundPoints (new               pcl::PointCloud);
        pcl::PointCloud noBoundPoints;
        int countBoundaries = 0;
        for (int i=0; isize(); i++){
                uint8_t x = (boundaries.points[i].boundary_point);
        int a = static_cast(x); //该函数的功能是强制类型转换
        if ( a == 1)
                {
                        //  boundPoints.push_back(cloud->points[i]);
                        ( *boundPoints).push_back(cloud->points[i]);
                        countBoundaries++;
                }
                else
                        noBoundPoints.push_back(cloud->points[i]);
                
    }
        std::cout<<"boudary size is：" <