帮我用c++写一个pcl181可以运行的ransac拟合中心直线void函数输出的是DDIANYUNWENJIANJIAransac拟合直线_plyply拟合的直线颜色设置为红色并且进行可视化。

下面是一个使用PCL 1.8.1库的RANSAC拟合中心直线的C++代码示例。该代码将点云数据拟合为一条直线，并将拟合结果可视化保存为PLY文件。

#include <iostream>
#include <pcl/io/ply_io.h>
#include <pcl/point_types.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/sample_consensus/ransac.h>
#include <pcl/sample_consensus/sac_model_line.h>

void ransacLineFitting(const pcl::PointCloud<pcl::PointXYZ>::Ptr& cloud)
{
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_inliers(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_outliers(new pcl::PointCloud<pcl::PointXYZ>);

    // Create the segmentation object
    pcl::SampleConsensusModelLine<pcl::PointXYZ>::Ptr model(new pcl::SampleConsensusModelLine<pcl::PointXYZ>(cloud));

    pcl::RandomSampleConsensus<pcl::PointXYZ> ransac(model);
    ransac.setDistanceThreshold(0.01);
    ransac.computeModel();
    ransac.getInliers(*cloud_inliers);
    ransac.getOutliers(*cloud_outliers);

    pcl::visualization::PCLVisualizer viewer("RANSAC Line Fitting");
    viewer.setBackgroundColor(0, 0, 0);
    viewer.addPointCloud<pcl::PointXYZ>(cloud, "cloud");
    viewer.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_COLOR, 1.0, 1.0, 1.0, "cloud");

    viewer.addPointCloud<pcl::PointXYZ>(cloud_inliers, "inliers");
    viewer.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_COLOR, 1.0, 0.0, 0.0, "inliers");

    viewer.addPointCloud<pcl::PointXYZ>(cloud_outliers, "outliers");
    viewer.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_COLOR, 0.0, 1.0, 0.0, "outliers");

    viewer.spin();

    pcl::io::savePLYFileASCII("D:\\DIANYUNWENJIANJIA\\ransac拟合直线_ply.ply", *cloud_inliers);
}

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

    // Load point cloud data from file
    if (pcl::io::loadPLYFile<pcl::PointXYZ>("your_point_cloud.ply", *cloud) == -1)
    {
        std::cerr << "Failed to load point cloud data." << std::endl;
        return -1;
    }

    ransacLineFitting(cloud);

    return 0;
}

请注意将代码中的your_point_cloud.ply替换为你自己的点云数据文件路径。此外，你可能需要在编译时链接PCL库