pcl拟图片中所有直线的代码c++

以下是使用PCL C++实现的代码，用于检测点云中的所有直线：

#include <iostream>
#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/features/normal_3d.h>
#include <pcl/segmentation/sac_segmentation.h>
#include <pcl/visualization/pcl_visualizer.h>

int main (int argc, char** argv)
{
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>);
  pcl::PointCloud<pcl::Normal>::Ptr cloud_normals (new pcl::PointCloud<pcl::Normal>);
  pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients);
  pcl::PointIndices::Ptr inliers (new pcl::PointIndices);
  pcl::SACSegmentationFromNormals<pcl::PointXYZ, pcl::Normal> seg;
  pcl::ExtractIndices<pcl::PointXYZ> extract;
  pcl::ExtractIndices<pcl::Normal> extract_normals;
  pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
  pcl::visualization::PCLVisualizer viewer("Detected Lines");

  // Read in the cloud data
  pcl::PCDReader reader;
  reader.read<pcl::PointXYZ> ("cloud.pcd", *cloud);

  // Downsample the cloud using a Voxel Grid filter
  pcl::VoxelGrid<pcl::PointXYZ> vg;
  vg.setInputCloud (cloud);
  vg.setLeafSize (0.01f, 0.01f, 0.01f);
  vg.filter (*cloud_filtered);

  // Estimate point normals
  pcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> ne;
  ne.setInputCloud (cloud_filtered);
  ne.setSearchMethod (tree);
  ne.setKSearch (50);
  ne.compute (*cloud_normals);

  // Create the segmentation object for the planar model and set all the parameters
  seg.setOptimizeCoefficients (true);
  seg.setModelType (pcl::SACMODEL_NORMAL_PLANE);
  seg.setNormalDistanceWeight (0.1);
  seg.setMethodType (pcl::SAC_RANSAC);
  seg.setMaxIterations (100);
  seg.setDistanceThreshold (0.03);
  seg.setInputCloud (cloud_filtered);
  seg.setInputNormals (cloud_normals);

  // Obtain the plane inliers and coefficients
  seg.segment (*inliers, *coefficients);

  // Extract the planar inliers from the input cloud
  extract.setInputCloud (cloud_filtered);
  extract.setIndices (inliers);
  extract.setNegative (false);

  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_plane (new pcl::PointCloud<pcl::PointXYZ> ());
  extract.filter (*cloud_plane);

  // Remove the planar inliers, extract the rest
  extract.setNegative (true);
  extract.filter (*cloud_filtered);
  extract_normals.setInputCloud (cloud_normals);
  extract_normals.setIndices (inliers);
  extract_normals.setNegative (false);
  pcl::PointCloud<pcl::Normal>::Ptr cloud_normals_plane (new pcl::PointCloud<pcl::Normal> ());
  extract_normals.filter (*cloud_normals_plane);

  // Create the segmentation object for cylinder segmentation and set all the parameters
  seg.setOptimizeCoefficients (true);
  seg.setModelType (pcl::SACMODEL_CYLINDER);
  seg.setMethodType (pcl::SAC_RANSAC);
  seg.setNormalDistanceWeight (0.1);
  seg.setMaxIterations (10000);
  seg.setDistanceThreshold (0.05);
  seg.setRadiusLimits (0.01, 0.2);
  seg.setInputCloud (cloud_filtered);
  seg.setInputNormals (cloud_normals_plane);

  // Obtain the cylinder inliers and coefficients
  std::vector<pcl::ModelCoefficients> cylinder_coefficients;
  std::vector<pcl::PointIndices> cylinder_inliers;
  seg.segment (cylinder_inliers, cylinder_coefficients);

  // Draw the cylinder inliers in red
  for (size_t i = 0; i < cylinder_inliers.size (); i++)
  {
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_cylinder (new pcl::PointCloud<pcl::PointXYZ> ());
    for (size_t j = 0; j < cylinder_inliers[i].indices.size (); j++)
      cloud_cylinder->push_back ((*cloud_filtered)[cylinder_inliers[i].indices[j]]);
    pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> red_color(cloud_cylinder, 255, 0, 0);
    viewer.addPointCloud<pcl::PointXYZ> (cloud_cylinder, red_color, "cylinder" + std::to_string(i));
  }

  // Spin until the user closes the viewer
  viewer.spin();

  return 0;
}

这个代码首先将点云数据读入内存，然后使用体素网格滤波器进行下采样。接着估计点的法线，并使用法线平面模型进行分割。然后使用法线面模型分割后的剩余点云数据，使用圆柱模型进行分割。最后将所有检测到的圆柱绘制在可视化窗口中。