使用PCL库进行Kruskal最小生成树算法：点云PLY文件最短路径可视化

以下使用PCL库编写Kruskal算法来检测点云PLY文件内点的最短路径并将其可视化的C++代码示例：

#include <pcl/io/ply_io.h>
#include <pcl/point_types.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/common/distances.h>
#include <iostream>
#include <vector>
#include <algorithm>

struct Edge {
    int src, tgt;
    float weight;
};

struct Point {
    float x, y, z;
};

bool compareEdges(const Edge& edge1, const Edge& edge2) {
    return edge1.weight < edge2.weight;
}

int findParent(int i, std::vector<int>& parent) {
    if (parent[i] == i)
        return i;
    return findParent(parent[i], parent);
}

void unionSets(int src, int tgt, std::vector<int>& parent) {
    int srcParent = findParent(src, parent);
    int tgtParent = findParent(tgt, parent);
    parent[srcParent] = tgtParent;
}

void kruskalMST(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, std::vector<Edge>& resultEdges) {
    std::vector<Edge> edges;
    std::vector<int> parent(cloud->size());

    for (int i = 0; i < cloud->size(); i++) {
        parent[i] = i;
        for (int j = i+1; j < cloud->size(); j++) {
            float dist = pcl::euclideanDistance(cloud->at(i), cloud->at(j));
            edges.push_back({i, j, dist});
        }
    }

    std::sort(edges.begin(), edges.end(), compareEdges);

    for (const auto& edge : edges) {
        int srcParent = findParent(edge.src, parent);
        int tgtParent = findParent(edge.tgt, parent);

        if (srcParent != tgtParent) {
            resultEdges.push_back(edge);
            unionSets(srcParent, tgtParent, parent);
        }
    }
}

int main(int argc, char** argv) {
    if (argc < 2) {
        std::cout << "Usage: " << argv[0] << " <input_ply_file>" << std::endl;
        return 1;
    }

    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::io::loadPLYFile(argv[1], *cloud);

    std::vector<Edge> mstEdges;
    kruskalMST(cloud, mstEdges);

    pcl::visualization::PCLVisualizer viewer("Point Cloud Viewer");
    viewer.setBackgroundColor(0, 0, 0);
    viewer.addPointCloud<pcl::PointXYZ>(cloud, "cloud");

    for (const auto& edge : mstEdges) {
        Point src = {cloud->at(edge.src).x, cloud->at(edge.src).y, cloud->at(edge.src).z};
        Point tgt = {cloud->at(edge.tgt).x, cloud->at(edge.tgt).y, cloud->at(edge.tgt).z};
        viewer.addLine<pcl::PointXYZ>(pcl::PointXYZ(src.x, src.y, src.z), pcl::PointXYZ(tgt.x, tgt.y, tgt.z), 0, 255, 0, "line");
    }

    while (!viewer.wasStopped()) {
        viewer.spinOnce(100);
    }

    return 0;
}

请确保已安装PCL库，并在编译时链接PCL库。可以使用以下命令编译代码：

g++ -std=c++11 -o kruskal_mst_kd_tree kruskal_mst_kd_tree.cpp -lpcl_io -lpcl_visualization

然后，运行可执行文件并指定PLY文件作为输入参数：

./kruskal_mst_kd_tree input.ply

这将显示点云及其最短路径的可视化结果。