本文整理汇总了C++中Segmentation::segment方法的典型用法代码示例。如果您正苦于以下问题：C++ Segmentation::segment方法的具体用法？C++ Segmentation::segment怎么用？C++ Segmentation::segment使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Segmentation的用法示例。
在下文中一共展示了Segmentation::segment方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: main
int main(int argc, char** argv)
{
pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZRGBA>);
pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloudFiltered (new pcl::PointCloud<pcl::PointXYZRGBA>);
int k=atoi(argv[1]);
double min_mah_dist=atof(argv[2]);
int max_gauss=atoi(argv[3]);
std::vector <Gauss> gaussians_learned;
pcl::PCDReader reader;
reader.read (argv[4], *cloud);
pcl::console::TicToc timer;
timer.tic();
// Filtering
Filtering filtering;
cloudFiltered=filtering.filter(cloud);
// Segmentation
Segmentation segmentation;
std::vector <Surface> surfaces=segmentation.segment (cloudFiltered);
// Colour extraction from point cloud
ExtractColour extractcolour;
cv::Mat samples=extractcolour.pcd2colourRGB(surfaces[0].segmented_cloud);
// Point cloud analysis
ColourAnalysis colouranalysis;
std::vector <Gauss> gaussians = colouranalysis.analyzeColourCluster(k, surfaces[0].segmented_cloud, surfaces[0].b, surfaces[0].d, samples);
// Learning
Learning learning;
gaussians_learned=learning.learnGaussians(gaussians, gaussians_learned, max_gauss);
// ROI
ROI roi;
std::vector<Line> lines=roi.roi(surfaces);
std::vector<int> index=roi.extractIndex(lines);
// Colour extraction from image
std::vector<Matrix_double> colours=extractcolour.indexPCD2VectorRGB(*cloud, index);
// Image analysis
std::vector <int> pixels_labeled=colouranalysis.labelIndex(colours, k, gaussians_learned, min_mah_dist);
// Map reconstruction
Map map;
std::vector<Matrix_double> distancesLabeled=map.mapDistances(index, surfaces[0].a ,surfaces[0].b, surfaces[0].c, surfaces[0].d);
std::cout << "Part 1 finished" << std::endl;
timer.toc_print();
timer.tic();
// Generate image
cv::Mat environment=extractcolour.pcd2image(*cloud);
// Calcule begin and end points for a line
std::vector <LinePoint> linePoints=roi.calculeLinePoints(lines);
// Draw lines
Visualize visualize;
environment=visualize.drawLines (environment, linePoints, "green");
// Print floor
std::vector<int> pixels=colouranalysis.labelPixel(pixels_labeled, index, colours);
environment=visualize.drawFloor (pixels, environment, "cyan");
std::vector <int> kinectIndex=roi.extractFloorIdx(surfaces[0].a, surfaces[0].b, surfaces[0].c, surfaces[0].d, cloud);
environment=visualize.drawFloor (kinectIndex, environment, "blue");
// Reconstruct kinect floor
std::vector <int> kinect (kinectIndex.size(), 1);
std::vector<Matrix_double> distancesKinect=map.mapDistances(kinectIndex, surfaces[0].a ,surfaces[0].b, surfaces[0].c, surfaces[0].d);
pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloudEnhanced=map.mapEnhance(distancesLabeled, index, cloud, pixels_labeled, surfaces[0].a ,surfaces[0].b, surfaces[0].c, surfaces[0].d);
// Generate map reconstruction image
cv::Mat map_reconstruction(cv::Size(400,650),CV_8UC3);
map_reconstruction=cv::Scalar(0,0,0);
map_reconstruction=visualize.mapGeneration(map_reconstruction, pixels_labeled, distancesLabeled, "blue", "white");
map_reconstruction=visualize.mapGeneration(map_reconstruction, kinect, distancesKinect, "red", "yellow");
// Show images on a window
std::string name_window="Floor window";
visualize.visualizeImage (environment, name_window);
name_window="Map window";
visualize.visualizeImage (map_reconstruction, name_window);
visualize.visualizeCloud(cloudEnhanced, "Cloud");
// Save images
Save save;
char name[50]="map.png";
save.saveImage(map_reconstruction, name);
char name2[50]="environment.png";
save.saveImage(environment, name2);
// Save cloud
//.........这里部分代码省略.........