PCL读入含颜色信息的点云

写在前面

• PCL(Point Cloud Library):是一个开源的算法库，用C++编写，是当前点云处理的得力工具；
• 在使用PCL处理3D相机输出的点云中，可能遇到问题，因此编写此文章；
• 知微传感Dkam系列3D相机可以应用于定位分拣、焊接焊缝提取、逆向建模、检测测量等领域
• 未尽问题欢迎与我深入交流：Liu_Gump_

PCL在线读入Dkam系列3D相机含有RGB信息的点云

• PCL配置方法另请查阅
• PCL在线读入点云的例程可以参考作者的其他文章
• 本例程基于WIN10+VisualStudio2019+DkamSDK_1.6.72+PCL1.12.0,采用C++语言

// Dkam_PCL_Con.cpp : 此文件包含 "main" 函数。程序执行将在此处开始并结束。 #include <iostream> #include<cstring> //DkamSDK #include"dkam_discovery.h" #include"dkam_gige_camera.h" #include"dkam_gige_stream.h" //PCL #include <pcl/io/pcd_io.h> #include <pcl/point_types.h> #include <pcl/visualization/pcl_visualizer.h> int main() { std::cout << "Hello Zhisensor!" << std::endl; std::cout << "Hello liu_sensor!" << std::endl; std::vector<DiscoveryInfo> discovery_info; Discovery discovery; GigeCamera camera; GigeStream* pointgigestream = NULL; GigeStream* graygigestream = NULL; GigeStream* rgbgigestream = NULL; std::vector<DiscoveryInfo>().swap(discovery_info); //********************************************查询相机**************************************************** //查询局域网内的3D相机 int camer_num = discovery.DiscoverCamera(&discovery_info); std::cout << "局域网内共有" << camer_num << "台相机" << std::endl; //显示局域网内相机的IP for (int i = 0; i < camer_num; i++) { std::cout << "局域网内相机的IP为:" << discovery.ConvertIpIntToString(discovery_info[i].camera_ip) << std::endl; } //********************************************连接相机**************************************************** //选定相机 int k = -1; for (int i = 0; i < camer_num; i++) { if (strcmp((discovery.ConvertIpIntToString(discovery_info[i].camera_ip)), "192.168.30.127") == 0) { k = i; std::cout << "将连接第" << k + 1 << "台相机" << std::endl; } else { std::cout << "局域网内无该IP的相机" << std::endl; } } //********************************************采集数据**************************************************** int connect = camera.CameraConnect(&discovery_info[k]); if (connect == 0) { //获取当前红外相机的宽和高 int width = -1; int height = -1; std::cout << "获取相机红外图的宽和高。。。" << std::endl; int height_gray = camera.GetCameraHeight(&height, 0); int width_gray = camera.GetCameraWidth(&width, 0); std::cout << "camera Grey width:" << width << "---Grey height:" << height << std::endl; //获取当前RGB相机的宽和高 int width_RGB = -1; int height_RGB = -1; std::cout << "获取相机RGB图的宽和高。。。" << std::endl; int height_rgb = camera.GetCameraHeight(&height_RGB, 1); int width_rgb = camera.GetCameraWidth(&width_RGB, 1); std::cout << "camera RGB width:" << width_RGB << "-----RGB height:" << height_RGB << std::endl; //定义点云数据大小 PhotoInfo* point_data = new PhotoInfo; point_data->pixel = new char[width * height * 6]; memset(point_data->pixel, 0, width * height * 6); //定义RGB数据大小 PhotoInfo* RGB_data = new PhotoInfo; RGB_data->pixel = new char[width_RGB * height_RGB * 3]; memset(RGB_data->pixel, 0, width_RGB * height_RGB * 3); //开启数据流通道(0:红外 1:点云 2:RGB) int stream_point = camera.StreamOn(1, &pointgigestream); if (stream_point == 0) { std::cout << "点云通道打开成功！" << std::endl; } else { std::cout << "点云通道打开失败！！！" << std::endl; } //打开RGB数据流通道 int stream_RGB = camera.StreamOn(2, &rgbgigestream); if (stream_RGB == 0) { std::cout << "RGB图通道打开成功！" << std::endl; } else { std::cout << "RGB图通道打开失败！！！" << std::endl; } //开始接受数据 int acquistion = camera.AcquisitionStart(); if (acquistion == 0) { std::cout << "可以开始接受数据！" << std::endl; } //刷新缓冲区数据 pointgigestream->FlushBuffer(); graygigestream->FlushBuffer(); rgbgigestream->FlushBuffer(); //**********************************************采集数据*************************************** //采集点云 int capturePoint = -1; capturePoint = pointgigestream->TimeoutCapture(point_data, 3000000); if (capturePoint == 0) { std::cout << "点云接收成功！" << std::endl; } else { std::cout << "点云接收失败！！！" << std::endl; std::cout << "失败代号：" << capturePoint << std::endl; } //采集RGB int captureRGB = -1; captureRGB = rgbgigestream->TimeoutCapture(RGB_data, 3000000); if (captureRGB == 0) { std::cout << "RGB接收成功！" << std::endl; } else { std::cout << "RGB接收失败！！！" << std::endl; std::cout << "失败代号：" << capturePoint << std::endl; } //**********************************************融合RGB和点云*************************************** std::cout << "融合点云和RGB信息..." << std::endl; // 开辟内存，存放融合后的数据 float* rgb_cloud = (float*)malloc(width * height * 6 * sizeof(float)); //融合，该API由知微传感提供 int pointRGB = camera.FusionImageTo3D(*RGB_data, *point_data, rgb_cloud); //****************************************将相机数据转化为PCL中可读********************************** std::cout << "将相据转化为PCL中可读..." << std::endl; // 定义pcl数据 pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloudRGB(new pcl::PointCloud<pcl::PointXYZRGB>); for (int i = 0; i < (int)(point_data->pixel_width * point_data->pixel_height); i++) { pcl::PointXYZRGB temp; temp.x = rgb_cloud[6 * i + 0]; temp.y = rgb_cloud[6 * i + 1]; temp.z = rgb_cloud[6 * i + 2]; temp.r = rgb_cloud[6 * i + 3]; temp.g = rgb_cloud[6 * i + 4]; temp.b = rgb_cloud[6 * i + 5]; cloudRGB->push_back(temp); } //保存点云 std::cout << "保存含RGB信息的点云..." << std::endl; pcl::io::savePCDFile("D:/Zhisensor/Works/3DCode/Dkam_PCL_PcRgb/Output/PcRgb.pcd", *cloudRGB); //****************************************显示含RGB的点云********************************** std::cout << "显示含RGB信息的点云..." << std::endl; pcl::visualization::PCLVisualizer::Ptr RGBViewer(new pcl::visualization::PCLVisualizer("3D Viewer")); pcl::visualization::PointCloudColorHandlerRGBField<pcl::PointXYZRGB> rgb(cloudRGB); //创建一个颜色处理对象 RGBViewer->setBackgroundColor(0, 0, 0); RGBViewer->addPointCloud<pcl::PointXYZRGB>(cloudRGB, rgb, "rgb cloud"); RGBViewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "rgb cloud"); RGBViewer->addCoordinateSystem(1.0); RGBViewer->initCameraParameters(); while (!RGBViewer->wasStopped()) { RGBViewer->spin(); } //**********************************************结束工作*************************************** memset(point_data->pixel, 0, width * height * 6); memset(RGB_data->pixel, 0, width_RGB * height_RGB * 3); //释放内存 delete[] point_data->pixel; delete point_data; delete[] RGB_data->pixel; delete RGB_data; //关闭数据流通道 int streamoff_point = camera.StreamOff(1, pointgigestream); int streamoff_rgb = camera.StreamOff(2, rgbgigestream); //断开相机连接 int disconnect = camera.CameraDisconnect(); std::cout << "工作结束！！！！！！" << std::endl; } return 0; }

运行结果

• 可以实现点云和RGB的融合，并且成功导入到PCL中，并显示
  

后记

• 知微传感Dkam系列3D相机可以应用于定位分拣、焊接引导、逆向建模、检测测量等领域