PCL—点云的可视化（二）

最新推荐文章于 2025-06-08 16:02:17 发布

马少爷

最新推荐文章于 2025-06-08 16:02:17 发布

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分类专栏：学术三维视觉文章标签：计算机视觉

本文链接：https://blog.youkuaiyun.com/qq_27353621/article/details/126379688

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本文介绍了如何使用PCL库进行点云数据的简单可视化，包括在独立线程中查看点云和实时更新，以及深度图像的创建与显示。通过示例代码展示了PCLVisualizer类的使用，以及如何设置背景色、添加点云、坐标系等。

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1、简单点云可视化

#include<pcl/visualization/cloud_viewer.h>
#include <pcl/io/pcd_io.h>   //打开关闭pcd类定义头文件
#include<pcl/point_cloud.h>

int main(int argc, char** argv)
{
	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
	if (pcl::io::loadPCDFile<pcl::PointXYZ>("bun.pcd", *cloud) == -1) //加载文件
	{
		PCL_ERROR("Couldn't read file  \n");
		system("PAUSE");
		return (-1);
	}
	pcl::visualization::CloudViewer viewer ("Cloud Viewer");  //Cloud Viewer 是显示窗口栏的名称 
    
    viewer.showCloud(cloud);
	while (!viewer.wasStopped ())
    {

    }
	system("PAUSE");
	return (0);
}

效果如下：
在这里插入图片描述
2、在可视化线程中查看点云

#include <pcl/visualization/cloud_viewer.h>
#include <iostream>
#include <pcl/io/io.h>
#include <pcl/io/pcd_io.h>
    
int user_data;

void viewerOneOff (pcl::visualization::PCLVisualizer& viewer)
{
    viewer.setBackgroundColor (1.0, 0.5, 1.0);
    pcl::PointXYZ o;
    o.x = 1.0;
    o.y = 0;
    o.z = 0;
    viewer.addSphere (o, 0.25, "sphere", 0);
    std::cout << "i only run once" << std::endl; 
}
    
void viewerPsycho (pcl::visualization::PCLVisualizer& viewer)
{
    static unsigned count = 0;
    std::stringstream ss;
    ss << "Once per viewer loop: " << count++;
    viewer.removeShape ("text", 0);
    viewer.addText (ss.str(), 200, 300, "text", 0);
    //FIXME: possible race condition here:
    user_data++;
}
    
int main ()
{
    pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZRGBA>);
    pcl::io::loadPCDFile ("maize.pcd", *cloud);
    pcl::visualization::CloudViewer viewer("Cloud Viewer");    
    //showCloud函数是同步的，在此处等待直到渲染显示为止
    viewer.showCloud(cloud);
    //该注册函数在可视化时只调用一次
    viewer.runOnVisualizationThreadOnce (viewerOneOff);
    //该注册函数在渲染输出时每次都调用
    viewer.runOnVisualizationThread (viewerPsycho);
    while (!viewer.wasStopped ())
    {
		//在此处可以添加其他处理
		user_data++;
    }
    return 0;
}

运行效果如下：
在这里插入图片描述
3、可视化深度图像

#include <iostream>
#include <boost/thread/thread.hpp>
#include <pcl/common/common_headers.h>
#include <pcl/common/common_headers.h>
#include <pcl/range_image/range_image.h>
#include <pcl/io/pcd_io.h>
#include <pcl/visualization/range_image_visualizer.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/console/parse.h>

typedef pcl::PointXYZ PointType;
// 全局参数
float angular_resolution = 0.5f;
pcl::RangeImage::CoordinateFrame coordinate_frame = pcl::RangeImage::CAMERA_FRAME;
bool live_update = false;
// -----打印帮助-----
void 
printUsage (const char* progName)
{
  std::cout << "\n\nUsage: "<<progName<<" [options] <scene.pcd>\n\n"
            << "Options:\n"
            << "-------------------------------------------\n"
            << "-r <float>   angular resolution in degrees (default "<<angular_resolution<<")\n"
            << "-c <int>     coordinate frame (default "<< (int)coordinate_frame<<")\n"
            << "-l           live update - update the range image according to the selected view in the 3D viewer.\n"
            << "-h           this help\n"
            << "\n\n";
}

void 
setViewerPose (pcl::visualization::PCLVisualizer& viewer, const Eigen::Affine3f& viewer_pose)
{
  Eigen::Vector3f pos_vector = viewer_pose * Eigen::Vector3f(0, 0, 0);
  Eigen::Vector3f look_at_vector = viewer_pose.rotation () * Eigen::Vector3f(0, 0, 1) + pos_vector;
  Eigen::Vector3f up_vector = viewer_pose.rotation () * Eigen::Vector3f(0, -1, 0);
  viewer.camera_.pos[0] = pos_vector[0];
  viewer.camera_.pos[1] = pos_vector[1];
  viewer.camera_.pos[2] = pos_vector[2];
  viewer.camera_.focal[0] = look_at_vector[0];
  viewer.camera_.focal[1] = look_at_vector[1];
  viewer.camera_.focal[2] = look_at_vector[2];
  viewer.camera_.view[0] = up_vector[0];
  viewer.camera_.view[1] = up_vector[1];
  viewer.camera_.view[2] = up_vector[2];
  viewer.updateCamera();
}

// -----Main-----
int 
main (int argc, char** argv)
{
  //解析命令行参数
  //argv[0] = "-h";	
  if (pcl::console::find_argument (argc, argv, "-h") >= 0)
  {
    printUsage (argv[0]);
    return 0;
  }
  //argv[0] = "-l";	
  printUsage (argv[0]);
  if (pcl::console::find_argument (argc, argv, "-l") >= 0)
  {
    live_update = true;
    std::cout << "Live update is on.\n";
  }

  if (pcl::console::parse (argc, argv, "-r", angular_resolution) >= 0)
    std::cout << "Setting angular resolution to "<<angular_resolution<<"deg.\n";
  int tmp_coordinate_frame;
  if (pcl::console::parse (argc, argv, "-c", tmp_coordinate_frame) >= 0)
  {
    coordinate_frame = pcl::RangeImage::CoordinateFrame (tmp_coordinate_frame);
    std::cout << "Using coordinate frame "<< (int)coordinate_frame<<".\n";
  }
  angular_resolution = pcl::deg2rad (angular_resolution);
  
  // 读取给定的pcd点云文件或者自行创建随机点云
  pcl::PointCloud<PointType>::Ptr point_cloud_ptr (new pcl::PointCloud<PointType>);
  pcl::PointCloud<PointType>& point_cloud = *point_cloud_ptr;
  Eigen::Affine3f scene_sensor_pose (Eigen::Affine3f::Identity ());
  std::vector<int> pcd_filename_indices = pcl::console::parse_file_extension_argument (argc, argv, "pcd");

  if (pcl::io::loadPCDFile ("room_scan1.pcd", point_cloud) == -1)
{
	std::cout << "Was not able to open file \""<<"room_scan1.pcd"<<"\".\n";
	printUsage (argv[0]);
	return 0;
}
scene_sensor_pose = Eigen::Affine3f (Eigen::Translation3f (point_cloud.sensor_origin_[0],
															point_cloud.sensor_origin_[1],
															point_cloud.sensor_origin_[2])) *
					Eigen::Affine3f (point_cloud.sensor_orientation_);
  //从点云创建深度图像对象
  float noise_level = 0.0;
  float min_range = 0.0f;
  int border_size = 1;
  boost::shared_ptr<pcl::RangeImage> range_image_ptr(new pcl::RangeImage);
  pcl::RangeImage& range_image = *range_image_ptr;   
  range_image.createFromPointCloud (point_cloud, angular_resolution, pcl::deg2rad (360.0f), pcl::deg2rad (180.0f), scene_sensor_pose, coordinate_frame, noise_level, min_range, border_size);
  //创建3D视图并且添加点云进行显示
  pcl::visualization::PCLVisualizer viewer ("3D Viewer");
  viewer.setBackgroundColor (1, 1, 1);
  pcl::visualization::PointCloudColorHandlerCustom<pcl::PointWithRange> range_image_color_handler (range_image_ptr, 0, 0, 0);
  viewer.addPointCloud (range_image_ptr, range_image_color_handler, "range image");
  viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "range image");
  //viewer.addCoordinateSystem (1.0f);
  //PointCloudColorHandlerCustom<PointType> point_cloud_color_handler (point_cloud_ptr, 150, 150, 150);
  //viewer.addPointCloud (point_cloud_ptr, point_cloud_color_handler, "original point cloud");
  viewer.initCameraParameters ();
  setViewerPose(viewer, range_image.getTransformationToWorldSystem ());
  //显示深度图像
  pcl::visualization::RangeImageVisualizer range_image_widget ("Range image");
  range_image_widget.showRangeImage (range_image);
    //主循环
  while (!viewer.wasStopped ())
  {
    range_image_widget.spinOnce ();
    viewer.spinOnce ();
    //pcl_sleep(0.01);
    if (live_update)
    {
      scene_sensor_pose = viewer.getViewerPose();
      range_image.createFromPointCloud (point_cloud, angular_resolution, pcl::deg2rad (360.0f), pcl::deg2rad (180.0f), scene_sensor_pose, pcl::RangeImage::LASER_FRAME, noise_level, min_range, border_size);
      range_image_widget.showRangeImage (range_image);
    }
  }
}

在这里插入图片描述

效果如下:
在这里插入图片描述

在这里插入图片描述

4、PCL Visualizer可视化类

#include <pcl/io/pcd_io.h>
#include <pcl/io/io.h>
#include <pcl/io/pcd_io.h>
#include <pcl/visualization/pcl_visualizer.h>

int main(int argc, char **argv) {
//XYZ点云文件的导入
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::io::loadPCDFile("bun.pcd", *cloud);
//XYZRGB点云文件的导入
    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_milk(new pcl::PointCloud<pcl::PointXYZRGB>);
    pcl::io::loadPCDFile("maize.pcd", *cloud_milk);

    // 创建PCLVisualizer
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer (new pcl::visualization::PCLVisualizer ("3D Viewer"));

    // 设置背景色为灰色（非必须）
    viewer->setBackgroundColor (0.05, 0.05, 0.05, 0);

    // 添加一个普通点云 (可以设置指定颜色，也可以去掉single_color参数不设置)
    pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> single_color(cloud, 0, 255, 0);
    viewer->addPointCloud<pcl::PointXYZ> (cloud, single_color, "sample cloud");
    viewer->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 2, "sample cloud");

    //// 再添加一个彩色点云及配置
    //pcl::visualization::PointCloudColorHandlerRGBField<pcl::PointXYZRGB> rgb(cloud_milk);
    //viewer->addPointCloud<pcl::PointXYZRGB> (cloud_milk, rgb, "sample cloud milk");
    //viewer->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "sample cloud milk");

    // 添加一个0.5倍缩放的坐标系（非必须）
    viewer->addCoordinateSystem (0.5);

    // 直到窗口关闭才结束循环
    while (!viewer->wasStopped()) {
        // 每次循环调用内部的重绘函数
        viewer->spinOnce();
    }
    return 0;
}

效果如下：
在这里插入图片描述