目录
以下是pcl点云基本操作，后面会慢慢更新。
PCLVisualizer简单的点云可视化
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#include <iostream>
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#include <pcl\io\pcd_io.h>
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#include <pcl\visualization\pcl_visualizer.h>
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using
namespace std;
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int main()
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{
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// 加载数据
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pcl::PointCloud<pcl::PointXYZ>::
Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
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pcl::PCDReader reader;
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if (reader.
read(
".\\models\\horse.pcd", *cloud) <
0)
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{
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PCL_ERROR(
"not exists！\n");
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system(
"pause");
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return
-1;
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}
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// 可视化点云
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boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("viewer_window_name"));
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viewer->
addPointCloud<pcl::PointXYZ>(cloud,
"horse_cloud");
// 将点云附加到视窗中，并对该点云定义唯一的ID“horse_cloud”
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while (!viewer->
wasStopped())
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{
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viewer->
spinOnce(
100);
// 100 ms 刷新一次
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}
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return
0;
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}
createViewPort创建视窗
代码
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#include <pcl/visualization/cloud_viewer.h>
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int main()
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{
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boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("PCL Viewer"));
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viewer->
initCameraParameters();
// 初始化相机默认参数
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// 一个视窗
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//int v1(0);
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//viewer->createViewPort(0.0, 0.0, 1.0, 1.0, v1); // x[0,1], y[0,1]
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//viewer->setBackgroundColor(255, 0, 255, v1);
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// 两个视窗
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//int v1(0), v2(1);
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//viewer->createViewPort(0.0, 0.0, 0.5, 1.0, v1); // x1[0,0.5], y1[0,1]
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//viewer->createViewPort(0.5, 0.0, 1.0, 1.0, v2); // x2[0.5,1], y2[0,1]
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//viewer->setBackgroundColor(255, 0, 255, v1);
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//viewer->setBackgroundColor(0, 255, 255, v2);
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// 三个视窗
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//int v1(0), v2(1), v3(2);
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//viewer->createViewPort(0.0, 0.0, 0.33, 1.0, v1); // x1[0,0.33], y1[0,1]
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//viewer->createViewPort(0.33, 0.0, 0.66, 1.0, v2); // x2[0.33,0.66], y2[0,1]
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//viewer->createViewPort(0.66, 0.0, 1.0, 1.0, v3); // x3[0.66,1], y3[0,1]
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//viewer->setBackgroundColor(255, 0, 255, v1);
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//viewer->setBackgroundColor(0, 255, 255, v2);
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//viewer->setBackgroundColor(255, 255, 0, v3);
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// 四个视窗
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int v1(0), v2(1), v3(2), v4(3);
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viewer->
createViewPort(
0.0,
0.0,
0.5,
0.5, v1);
// x1[0,0.5], y1[0,0.5]
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viewer->
createViewPort(
0.5,
0.0,
1.0,
0.5, v2);
// x2[0.5,1], y2[0,0.5]
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viewer->
createViewPort(
0.0,
0.5,
0.5,
1.0, v3);
// x3[0.,0.5], y3[0.5,1]
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viewer->
createViewPort(
0.5,
0.5,
1.0,
1.0, v4);
// x3[0.5,1], y3[0.5,1]
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viewer->
setBackgroundColor(
255,
0,
255, v1);
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viewer->
setBackgroundColor(
0,
255,
255, v2);
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viewer->
setBackgroundColor(
255,
255,
0, v3);
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viewer->
setBackgroundColor(
255,
0,
0, v4);
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viewer->
addCoordinateSystem();
// 在viewer对象下所有的视窗都可视化坐标系
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viewer->
spin();
// 显示交互界面
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}
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效果
一个视窗。
两个视窗。
三个视窗。
四个视窗。
点云视窗上打印文本信息
使用addText
addText参数说明，注意最后一个参数可以指定在哪个视窗上显示文本。
bool addText (const std::string &text, int xpos, int ypos, int fontsize, double r, double g, double b, const std::string &id = "", int viewport = 0);
view/** \brief Add a text to screen
* \param[in] text the text to add
* \param[in] xpos the X position on screen where the text should be added
* \param[in] ypos the Y position on screen where the text should be added
* \param[in] fontsize the fontsize of the text
* \param[in] r the red color value
* \param[in] g the green color value
* \param[in] b the blue color value
* \param[in] id the text object id (default: equal to the "text" parameter)
* \param[in] viewport the view port (default: all)
*/
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pcl::
visualization::PCLVisualizer viewer("demo");
// 创建可视化对象
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viewer.
createViewPort(
0.0,
0.0,
0.5,
1.0,
0);
// 定义viewport位置. 可以定义多个视角
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viewer.
addText(
"Original point cloud\n",
10,
15,
16,
1,
1,
1,
"text_id",
0);
合并多个点云
xyz+xyz
点的类型都是pcl::PointXYZ类型
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#include <pcl/point_types.h>
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#include <pcl/io/file_io.h>
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#include <pcl/io/pcd_io.h>
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#include <pcl/point_cloud.h>
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#include <iostream>
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int
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main
(int argc, char** argv)
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{
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pcl::PointCloud<pcl::PointXYZ> cloud_a, cloud_b;
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pcl::PointCloud<pcl::PointXYZ> cloud_c;
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// 创建点云数据
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cloud_a.width =
3;
// 点数3
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cloud_a.height = cloud_b.height =
1;
// 设置为无序点云
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cloud_a.points.
resize(cloud_a.width * cloud_a.height);
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cloud_b.width =
2;
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cloud_b.points.
resize(cloud_b.width * cloud_b.height);
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// 赋值
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for (
size_t i =
0; i < cloud_a.points.
size(); ++i)
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{
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cloud_a.points[i].x =
1024 *
rand() / (RAND_MAX +
1.0f);
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cloud_a.points[i].y =
1024 *
rand() / (RAND_MAX +
1.0f);
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cloud_a.points[i].z =
1024 *
rand() / (RAND_MAX +
1.0f);
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}
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for (
size_t i =
0; i < cloud_b.points.
size(); ++i)
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{
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cloud_b.points[i].x =
1024 *
rand() / (RAND_MAX +
1.0f);
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cloud_b.points[i].y =
1024 *
rand() / (RAND_MAX +
1.0f);
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cloud_b.points[i].z =
1024 *
rand() / (RAND_MAX +
1.0f);
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}
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cloud_c = cloud_a;
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cloud_c += cloud_b;
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pcl::io::
savePCDFile(
"test.pcd", cloud_c);
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}
结果：
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# .PCD v0
.7 - Point Cloud Data file format
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VERSION
0.7
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FIELDS x y z
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SIZE
4
4
4
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TYPE F F F
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COUNT
1
1
1
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WIDTH
5
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HEIGHT
1
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VIEWPOINT
0
0
0
1
0
0
0
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POINTS
5
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DATA ascii
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1.28125
577.09375
197.9375
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828.125
599.03125
491.375
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358.6875
917.4375
842.5625
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764.5
178.28125
879.53125
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727.53125
525.84375
311.28125
xyz + nxnynz
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#include <pcl/point_types.h>
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#include <pcl/io/file_io.h>
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#include <pcl/io/pcd_io.h>
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#include <pcl/point_cloud.h>
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#include <pcl/visualization/pcl_visualizer.h>
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-
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int
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main
(int argc, char** argv)
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{
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pcl::PointCloud<pcl::PointXYZ> cloud_a;
// 向量a
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pcl::PointCloud<pcl::Normal> n_cloud_b;
// 法向量
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pcl::PointCloud<pcl::PointNormal> p_n_cloud_c;
// xyz + nxnynz = (x,y,z,nx,ny,nz)
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// 创建点云数据
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cloud_a.width =
3;
// 点数3
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cloud_a.height =
1;
// 设置为无序点云
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cloud_a.points.
resize(cloud_a.width * cloud_a.height);
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n_cloud_b.width =
3;
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n_cloud_b.height =
1;
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n_cloud_b.points.
resize(n_cloud_b.width * n_cloud_b.height);
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// 赋值
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for (
size_t i =
0; i < cloud_a.points.
size(); ++i)
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{
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cloud_a.points[i].x =
1024 *
rand() / (RAND_MAX +
1.0f);
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cloud_a.points[i].y =
1024 *
rand() / (RAND_MAX +
1.0f);
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cloud_a.points[i].z =
1024 *
rand() / (RAND_MAX +
1.0f);
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}
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for (
size_t i =
0; i < n_cloud_b.points.
size(); ++i)
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{
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n_cloud_b.points[i].normal[
0] =
1024 *
rand() / (RAND_MAX +
1.0f);
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n_cloud_b.points[i].normal[
1] =
1024 *
rand() / (RAND_MAX +
1.0f);
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n_cloud_b.points[i].normal[
2] =
1024 *
rand() / (RAND_MAX +
1.0f);
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}
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pcl::
concatenateFields(cloud_a, n_cloud_b, p_n_cloud_c);
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pcl::io::
savePCDFile(
"test.pcd", p_n_cloud_c);
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}
结果：
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# .PCD v0
.7 - Point Cloud Data file format
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VERSION
0.7
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FIELDS x y z normal_x normal_y normal_z curvature
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SIZE
4
4
4
4
4
4
4
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TYPE F F F F F F F
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COUNT
1
1
1
1
1
1
1
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WIDTH
3
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HEIGHT
1
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VIEWPOINT
0
0
0
1
0
0
0
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POINTS
3
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DATA ascii
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1.28125
577.09375
197.9375
764.5
178.28125
879.53125
0
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828.125
599.03125
491.375
727.53125
525.84375
311.28125
0
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358.6875
917.4375
842.5625
15.34375
93.59375
373.1875
0
新建自己的Point类型
步骤：先定义结构体，再注册。
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#include <pcl/point_types.h>
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#include <pcl/point_cloud.h>
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#include <pcl/io/pcd_io.h>
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struct
MyPointType
// 定义点类型说明
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{
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PCL_ADD_POINT4D;
// 该点类型有4个元素
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float val;
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EIGEN_MAKE_ALIGNED_OPERATOR_NEW
// 确保new操作符对齐操作
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}EIGEN_ALIGN16;
// 强制SSE对齐
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POINT_CLOUD_REGISTER_POINT_STRUCT(
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MyPointType,
// 注册点类型宏
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(
float, x, x)
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(
float, y, y)
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(
float, z, z)
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(
float, val, val)
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)
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int
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main
(int argc, char** argv)
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{
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// 创建1行2列的点云
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pcl::PointCloud<MyPointType> cloud;
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cloud.points.
resize(
2);
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cloud.width =
2;
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cloud.height =
1;
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// 对每个点赋值
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cloud.points[
0].val =
1;
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cloud.points[
0].x = cloud.points[
0].y = cloud.points[
0].z =
0;
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cloud.points[
1].val =
2;
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cloud.points[
1].x = cloud.points[
1].y = cloud.points[
1].z =
3;
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pcl::io::
savePCDFile(
"test.pcd", cloud);
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}
保存的test.pcd文件内容如下。
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# .PCD v0.7 - Point Cloud Data file format
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VERSION 0.7
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FIELDS x y z val
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SIZE 4 4 4 4
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TYPE F F F F
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COUNT 1 1 1 1
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WIDTH 2
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HEIGHT 1
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VIEWPOINT 0 0 0 1 0 0 0
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POINTS 2
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DATA ascii
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0 0 0 1
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3 3 3 2
点云的刚体变换（旋转+平移）
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#include <pcl/point_types.h>
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#include <pcl/io/file_io.h>
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#include <pcl/io/pcd_io.h>
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#include <pcl/point_cloud.h>
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#include <pcl/visualization/pcl_visualizer.h>
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#include <pcl/kdtree/kdtree_flann.h>
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#include <pcl/filters/voxel_grid.h>
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#include <iostream>
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#include <pcl/registration/ndt.h>
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#include <pcl/registration/icp.h>
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#include <iostream>
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-
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int main()
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{
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pcl::PointCloud<pcl::PointXYZ>::
Ptr cloud_in(new pcl::PointCloud<pcl::PointXYZ>);
// 原始点云
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pcl::PointCloud<pcl::PointXYZ>::
Ptr cloud_rotate(new pcl::PointCloud<pcl::PointXYZ>);
// 只是旋转
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pcl::PointCloud<pcl::PointXYZ>::
Ptr cloud_rotate_shift(new pcl::PointCloud<pcl::PointXYZ>);
// 旋转加平移
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if (pcl::io::
loadPCDFile(
"E:\\code\\c++\\PCL_demo\\PCL_demo\\models\\rabbit.pcd", *cloud_in) <
0)
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{
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PCL_ERROR(
"Error loading cloud %s.\n");
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return (
-1);
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}
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// 旋转
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rigid_transformation(cloud_in, cloud_rotate, M_PI /
4,
"x",
0,
0,
0);
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rigid_transformation(cloud_in, cloud_rotate_shift, M_PI /
4,
"x",
0,
5,
0);
-
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// 可视化
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boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("Trans viewer"));
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viewer->
initCameraParameters();
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int v1(0), v2(1);
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viewer->
createViewPort(
0.0,
0.0,
0.5,
1.0, v1);
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viewer->
createViewPort(
0.5,
0.0,
1.0,
1.0, v2);
-
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viewer->
addCoordinateSystem(
1);
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pcl::
visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> cloud_in_color_r(cloud_in, 128, 128, 0);
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pcl::
visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> cloud_in_color_b(cloud_rotate, 128, 0, 128);
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viewer->
addPointCloud(cloud_in, cloud_in_color_r,
"orig1", v1);
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viewer->
addPointCloud(cloud_rotate, cloud_in_color_b,
"trans1", v1);
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viewer->
addPointCloud(cloud_in, cloud_in_color_r,
"orig2", v2);
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viewer->
addPointCloud(cloud_rotate_shift, cloud_in_color_b,
"trans2", v2);
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-
viewer->
spin();
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}
转载：https://blog.csdn.net/jizhidexiaoming/article/details/128399020
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