基于pcl库使用kruskal最小生成树处理点云ply文件的C++代码

以下是基于PCL库使用Kruskal最小生成树处理点云PLY文件的C++代码示例：

#include <iostream>
#include <pcl/io/ply_io.h>
#include <pcl/point_types.h>
#include <pcl/visualization/cloud_viewer.h>
#include <pcl/common/common.h>
#include <pcl/common/centroid.h>
#include <pcl/common/geometry.h>
#include <pcl/common/transforms.h>

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

struct Subset {
    int parent;
    int rank;
};

class Graph {
private:
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud;
    std::vector<Edge> edges;

public:
    Graph(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud) {
        this->cloud = cloud;
    }

    void addEdge(int src, int dest) {
        float weight = pcl::geometry::distance(cloud->points[src], cloud->points[dest]);
        edges.push_back({src, dest, weight});
    }

    int find(Subset subsets[], int i) {
        if (subsets[i].parent != i)
            subsets[i].parent = find(subsets, subsets[i].parent);

        return subsets[i].parent;
    }

    void Union(Subset subsets[], int x, int y) {
        int xroot = find(subsets, x);
        int yroot = find(subsets, y);

        if (subsets[xroot].rank < subsets[yroot].rank)
            subsets[xroot].parent = yroot;
        else if (subsets[xroot].rank > subsets[yroot].rank)
            subsets[yroot].parent = xroot;
        else {
            subsets[yroot].parent = xroot;
            subsets[xroot].rank++;
        }
    }

    void kruskalMST() {
        std::vector<Edge> result;

        int num_vertices = cloud->size();
        int i = 0, e = 0;

        std::sort(edges.begin(), edges.end(), [](const Edge& a, const Edge& b) {
            return a.weight < b.weight;
        });

        Subset* subsets = new Subset[num_vertices * sizeof(Subset)];

        for (int v = 0; v < num_vertices; v++) {
            subsets[v].parent = v;
            subsets[v].rank = 0;
        }

        while (e < num_vertices - 1 && i < edges.size()) {
            Edge next_edge = edges[i++];

            int x = find(subsets, next_edge.src);
            int y = find(subsets, next_edge.dest);

            if (x != y) {
                result.push_back(next_edge);
                Union(subsets, x, y);
                e++;
            }
        }

        pcl::PointCloud<pcl::PointXYZ>::Ptr result_cloud(new pcl::PointCloud<pcl::PointXYZ>);
        result_cloud->resize(result.size() * 2);

        for (int i = 0; i < result.size(); i++) {
            int src = result[i].src;
            int dest = result[i].dest;

            result_cloud->points[2 * i] = cloud->points[src];
            result_cloud->points[2 * i + 1] = cloud->points[dest];
        }

        pcl::visualization::CloudViewer viewer("Minimum Spanning Tree");
        viewer.showCloud(result_cloud);
        while (!viewer.wasStopped()) {
        }
    }
};

int main() {
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::io::loadPLYFile<pcl::PointXYZ>("input.ply", *cloud);

    Graph graph(cloud);

    // Connect all points in the cloud
    for (int i = 0; i < cloud->size(); i++) {
        for (int j = i + 1; j < cloud->size(); j++) {
            graph.addEdge(i, j);
        }
    }

    graph.kruskalMST();

    return 0;
}

请注意，此代码假设输入PLY文件中的点云是无序的，并且使用Kruskal算法创建最小生成树