PCL学习笔记（4）：创建点云文件、加载点云文件

PCL（point cloud library）系列笔记：http://blog.csdn.net/chentravelling/article/category/2876349

//先上代码：

bool saveThePointCloud()
{
	 pcl::PointCloud<pcl::PointXYZ> Cloud;      //定义点云对象，类型PointXYZ
	    // 创建点云
	Cloud.width=30;
	Cloud.height=1;
	Cloud.is_dense=false;
	Cloud.points.resize(Cloud.width*Cloud.height);
	srand(unsigned(int(NULL)));
	for(size_t i=0;i<Cloud.points.size();++i)
	{//RAND_MAX = 32767
		if(i<10)
		{
			Cloud.points[i].x = 1024*rand()/(RAND_MAX+1.0f);
			Cloud.points[i].y = 0.0f;
			Cloud.points[i].z = 0.0f;
		}
		else if(i<20)
		{
			Cloud.points[i].x = 0.0f;
			Cloud.points[i].y = 1024*rand()/(RAND_MAX+1.0f);
			Cloud.points[i].z = 0.0f;
		}
		else
		{
			Cloud.points[i].x = 0.0f;
			Cloud.points[i].y = 0.0f;
			Cloud.points[i].z = 1024*rand()/(RAND_MAX+1.0f);
		}
	}
 	 // pcl::io::savePCDFile("pointCloudValueFile.pcd",Cloud);
	  pcl::io::savePCDFileASCII("pointCloudFile.pcd",Cloud);//这两种save的结果貌似是一样的。
	  return true;
}

然后在调用此函数即可。

完整程序：

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

//int user_data;
//Initialize the viewer including the backgroundcolor,coordinate axis,and others.
void viewerOneOff (pcl::visualization::PCLVisualizer& viewer)
{
	//set the backgroundcolor:R,G,B
     viewer.setBackgroundColor (1.0, 1.0, 1.0);//背景为白色

  /*  pcl::PointXYZ o;
    o.x = 0;
    o.y = 0;
    o.z = 0;

    viewer.addSphere (o, 5, "sphere",0);*/
	//viewer.addLine(o,"line",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++;
//}

//Accomplish loading a PCDFile,creating a viewer,and show the cloud at the viewer.
void showTheCloud()
{
	pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZRGBA>);
	//load
    pcl::io::loadPCDFile ("my_point_cloud.pcd", *cloud); 

    pcl::visualization::CloudViewer viewer("Cloud Viewer");

    //blocks until the cloud is actually rendered
    viewer.showCloud(cloud);

    //use the following functions to get access to the underlying more advanced/powerful
    //PCLVisualizer

    //This will only get called once
    viewer.runOnVisualizationThreadOnce (viewerOneOff);

    //This will get called once per visualization iteration
     //viewer.runOnVisualizationThread (viewerPsycho);
    while (!viewer.wasStopped ())
    {
        //you can also do cool processing here
        //FIXME: Note that this is running in a separate thread from viewerPsycho
        //and you should guard against race conditions yourself...
        //user_data++;
    }
}
//Create a point-cloud object,and generate a PCD File to save the point cloud object.
bool saveThePointCloud()
{
	 pcl::PointCloud<pcl::PointXYZ> Cloud;      //定义点云对象
	    // 创建点云
	Cloud.width=30;
	Cloud.height=1;
	Cloud.is_dense=false;
	Cloud.points.resize(Cloud.width*Cloud.height);
	srand(unsigned(int(NULL)));
	for(size_t i=0;i<Cloud.points.size();++i)
	{//RAND_MAX = 32767
		if(i<10)
		{
			Cloud.points[i].x = 1024*rand()/(RAND_MAX+1.0f);
			Cloud.points[i].y = 0.0f;
			Cloud.points[i].z = 0.0f;
		}
		else if(i<20)
		{
			Cloud.points[i].x = 0.0f;
			Cloud.points[i].y = 1024*rand()/(RAND_MAX+1.0f);
			Cloud.points[i].z = 0.0f;
		}
		else
		{
			Cloud.points[i].x = 0.0f;
			Cloud.points[i].y = 0.0f;
			Cloud.points[i].z = 1024*rand()/(RAND_MAX+1.0f);
		}
	}
 	  pcl::io::savePCDFile("pointCloudValueFile.pcd",Cloud);
	  pcl::io::savePCDFileASCII("pointCloudFile.pcd",Cloud);
	  return true;
}
int main ()
{
	if(saveThePointCloud())
	{
		showTheCloud();
	}
	else
	{
		std::cout<<"Failed"<<endl;
	}
    return 0;
}

效果图：

这样，在工程目录下会多一个pointCloudFile.pcd文件。用记事本打开就可以看到数据。【PCD格式说明请阅读本人学习笔记】

至于命令窗口显示的Failed to find match for failed ‘rgba‘，是因为PCD文件一般的格式中是：

FIELDS x y z rgb

SIZE 4 4 4 4

TYPE F F F F

COUNT 1 1 1 1

而我们获得的pcd文件里并没有第四列数据。初步估计是因为生成点云时，我们并没有给每一个point设置rgb参数。