帮我写一段c++函数,利用pcl,输入对齐的深度图与RGB图,构建点云,完成点云可视化,并保存
时间: 2024-03-12 20:49:29 浏览: 70
pcl库实现点云的压缩并可视化
好的,以下是一个利用PCL库构建点云、可视化并保存的C++函数:
```c++
#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/console/parse.h>
#include <opencv2/opencv.hpp>
using namespace std;
using namespace cv;
void createPointCloud(Mat depth_image, Mat rgb_image, string output_file) {
pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
float fx = 525.0f;
float fy = 525.0f;
float cx = 319.5f;
float cy = 239.5f;
for (int row = 0; row < depth_image.rows; row++) {
for (int col = 0; col < depth_image.cols; col++) {
ushort d = depth_image.at<ushort>(row, col);
if (d == 0) continue;
pcl::PointXYZRGB p;
p.z = float(d) / 1000.0;
p.x = (col - cx) * p.z / fx;
p.y = (row - cy) * p.z / fy;
Vec3b bgr = rgb_image.at<Vec3b>(row, col);
p.b = bgr[0];
p.g = bgr[1];
p.r = bgr[2];
cloud->push_back(p);
}
}
pcl::io::savePCDFileBinary(output_file, *cloud);
pcl::visualization::PCLVisualizer viewer("Point Cloud Viewer");
viewer.addPointCloud<pcl::PointXYZRGB>(cloud, "cloud");
viewer.setBackgroundColor(0.0, 0.0, 0.0);
while (!viewer.wasStopped()) {
viewer.spinOnce();
}
}
int main(int argc, char** argv) {
if (argc < 4) {
cout << "Usage: ./createPointCloud depth_image rgb_image output_file" << endl;
return -1;
}
Mat depth_image = imread(argv[1], CV_LOAD_IMAGE_UNCHANGED);
Mat rgb_image = imread(argv[2], CV_LOAD_IMAGE_COLOR);
createPointCloud(depth_image, rgb_image, argv[3]);
return 0;
}
```
这个函数接受三个参数:深度图像、RGB图像和输出文件路径。它首先使用深度和RGB图像中的像素信息构建点云,然后将点云保存到指定的输出文件中,并使用PCL可视化库显示点云。
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