（三）读写PCD文件

写

首先，创建一个名为pcd_write.cpp的文件，并在其中写入以下代码：

#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>

int main ()
{
  pcl::PointCloud<pcl::PointXYZ> cloud;

  // Fill in the cloud data
  cloud.width    = 5;
  cloud.height   = 1;
  cloud.is_dense = false;
  cloud.resize (cloud.width * cloud.height);

  for (auto& point: cloud)
  {
    point.x = 1024 * rand () / (RAND_MAX + 1.0f);
    point.y = 1024 * rand () / (RAND_MAX + 1.0f);
    point.z = 1024 * rand () / (RAND_MAX + 1.0f);
  }

  pcl::io::savePCDFileASCII ("test_pcd.pcd", cloud);
  std::cerr << "Saved " << cloud.size () << " data points to test_pcd.pcd." << std::endl;

  for (const auto& point: cloud)
    std::cerr << "    " << point.x << " " << point.y << " " << point.z << std::endl;

  return (0);
}

代码解释：

#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>

第一个头文件包含PCD I/O操作的定义，第二个头文件包含几个点类型结构的定义，包括我们将使用的pcl::PointXYZ。

 pcl::PointCloud<pcl::PointXYZ> cloud;

描述了我们将创建的模板化的PointCloud结构。每个点的类型都设置为pcl::PointXYZ，这是一个具有x、y和z字段的结构。

  // Fill in the cloud data
  cloud.width    = 5;
  cloud.height   = 1;
  cloud.is_dense = false;
  cloud.resize (cloud.width * cloud.height);

  for (auto& point: cloud)
  {
    point.x = 1024 * rand () / (RAND_MAX + 1.0f);
    point.y = 1024 * rand () / (RAND_MAX + 1.0f);
    point.z = 1024 * rand () / (RAND_MAX + 1.0f);
  }

使用随机值填充PointCloud结构的XYZ，并设置适当的参数（width, height, is_dense）。

 pcl::io::savePCDFileASCII ("test_pcd.pcd", cloud);

将PointCloud数据保存到磁盘中一个名为test_pcd.pcd的文件中

 std::cerr << "Saved " << cloud.size () << " data points to test_pcd.pcd." << std::endl;

  for (const auto& point: cloud)
    std::cerr << "    " << point.x << " " << point.y << " " << point.z << std::endl;

用于打印出生成的数据。

将以下内容添加到CMakeLists.txt：

cmake_minimum_required(VERSION 3.5 FATAL_ERROR)

project(pcd_write)

find_package(PCL 1.2 REQUIRED)

include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})

add_executable (pcd_write pcd_write.cpp)
target_link_libraries (pcd_write ${PCL_LIBRARIES})

得到可执行文件后运行它：

$ ./pcd_write

结果：

Saved 5 data points to test_pcd.pcd.
  0.352222 -0.151883 -0.106395
  -0.397406 -0.473106 0.292602
  -0.731898 0.667105 0.441304
  -0.734766 0.854581 -0.0361733
  -0.4607 -0.277468 -0.916762

检查文件test_pcd.pcd的内容：

$ cat test_pcd.pcd
# .PCD v.5 - Point Cloud Data file format
FIELDS x y z
SIZE 4 4 4
TYPE F F F
WIDTH 5
HEIGHT 1
POINTS 5
DATA ascii
0.35222 -0.15188 -0.1064
-0.39741 -0.47311 0.2926
-0.7319 0.6671 0.4413
-0.73477 0.85458 -0.036173
-0.4607 -0.27747 -0.91676

---

扩展阅读

https://blog.csdn.net/aiyaya333/article/details/111205933

https://blog.csdn.net/gulosityer/article/details/112554056

https://blog.csdn.net/weixin_45867382/article/details/121670492

---

读

#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>

int main ()
{
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);

  if (pcl::io::loadPCDFile<pcl::PointXYZ> ("test_pcd.pcd", *cloud) == -1) //* load the file
  {
    PCL_ERROR ("Couldn't read file test_pcd.pcd \n");
    return (-1);
  }
  std::cout << "Loaded "
            << cloud->width * cloud->height
            << " data points from test_pcd.pcd with the following fields: "
            << std::endl;
  for (const auto& point: *cloud)
    std::cout << "    " << point.x
              << " "    << point.y
              << " "    << point.z << std::endl;

  return (0);
}

代码解释：

  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);

创建PointCloud boost共享指针并初始化它。

  if (pcl::io::loadPCDFile<pcl::PointXYZ> ("test_pcd.pcd", *cloud) == -1) //* load the file
  {
    PCL_ERROR ("Couldn't read file test_pcd.pcd \n");
    return (-1);
  }

将PointCloud数据从磁盘加载到二进制blob中（test_pcd.pcd为上一节得到的数据）。

CMakeLists.txt

cmake_minimum_required(VERSION 3.5 FATAL_ERROR)

project(pcd_read)

find_package(PCL 1.2 REQUIRED)

include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})

add_executable (pcd_read pcd_read.cpp)
target_link_libraries (pcd_read ${PCL_LIBRARIES})

得到可执行文件后运行它：

$ ./pcd_read

结果：

Loaded 5 data points from test_pcd.pcd with the following fields: x y z
  0.35222 -0.15188 -0.1064
  -0.39741 -0.47311 0.2926
  -0.7319 0.6671 0.4413
  -0.73477 0.85458 -0.036173
  -0.4607 -0.27747 -0.91676

---

扩展阅读

https://zhuanlan.zhihu.com/p/336623565

智能指针之共享指针shared_ptr 的理解、使用
https://blog.csdn.net/aishuirenjia/article/details/91986961

---

参考：
https://pcl.readthedocs.io/projects/tutorials/en/master/reading_pcd.html#reading-pcd
https://pcl.readthedocs.io/projects/tutorials/en/master/writing_pcd.html#writing-pcd