test_marching_cubes.cpp
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00001 /*
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00036  * $Id: test_surface.cpp 6579 2012-07-27 18:57:32Z rusu $
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00038  */
00039 
00040 #include <gtest/gtest.h>
00041 
00042 #include <pcl/point_types.h>
00043 #include <pcl/io/pcd_io.h>
00044 #include <pcl/io/vtk_io.h>
00045 #include <pcl/features/normal_3d.h>
00046 #include <pcl/surface/mls.h>
00047 #include <pcl/surface/gp3.h>
00048 #include <pcl/surface/marching_cubes_hoppe.h>
00049 #include <pcl/surface/marching_cubes_rbf.h>
00050 #include <pcl/common/common.h>
00051 
00052 using namespace pcl;
00053 using namespace pcl::io;
00054 using namespace std;
00055 
00056 PointCloud<PointXYZ>::Ptr cloud (new PointCloud<PointXYZ>);
00057 PointCloud<PointNormal>::Ptr cloud_with_normals (new PointCloud<PointNormal>);
00058 search::KdTree<PointXYZ>::Ptr tree;
00059 search::KdTree<PointNormal>::Ptr tree2;
00060 
00061 // add by ktran to test update functions
00062 PointCloud<PointXYZ>::Ptr cloud1 (new PointCloud<PointXYZ>);
00063 PointCloud<PointNormal>::Ptr cloud_with_normals1 (new PointCloud<PointNormal>);
00064 search::KdTree<PointXYZ>::Ptr tree3;
00065 search::KdTree<PointNormal>::Ptr tree4;
00066 
00068 TEST (PCL, MarchingCubesTest)
00069 {
00070   MarchingCubesHoppe<PointNormal> hoppe;
00071   hoppe.setIsoLevel (0);
00072   hoppe.setGridResolution (30, 30, 30);
00073   hoppe.setPercentageExtendGrid (0.3f);
00074   hoppe.setInputCloud (cloud_with_normals);
00075   PointCloud<PointNormal> points;
00076   std::vector<Vertices> vertices;
00077   hoppe.reconstruct (points, vertices);
00078 
00079   EXPECT_NEAR (points.points[points.size()/2].x, -0.042528, 1e-3);
00080   EXPECT_NEAR (points.points[points.size()/2].y, 0.080196, 1e-3);
00081   EXPECT_NEAR (points.points[points.size()/2].z, 0.043159, 1e-3);
00082   EXPECT_EQ (vertices[vertices.size ()/2].vertices[0], 10854);
00083   EXPECT_EQ (vertices[vertices.size ()/2].vertices[1], 10855);
00084   EXPECT_EQ (vertices[vertices.size ()/2].vertices[2], 10856);
00085 
00086 
00087   MarchingCubesRBF<PointNormal> rbf;
00088   rbf.setIsoLevel (0);
00089   rbf.setGridResolution (20, 20, 20);
00090   rbf.setPercentageExtendGrid (0.1f);
00091   rbf.setInputCloud (cloud_with_normals);
00092   rbf.setOffSurfaceDisplacement (0.02f);
00093   rbf.reconstruct (points, vertices);
00094 
00095   EXPECT_NEAR (points.points[points.size()/2].x, -0.033919, 1e-3);
00096   EXPECT_NEAR (points.points[points.size()/2].y, 0.151683, 1e-3);
00097   EXPECT_NEAR (points.points[points.size()/2].z, -0.000086, 1e-3);
00098   EXPECT_EQ (vertices[vertices.size ()/2].vertices[0], 4284);
00099   EXPECT_EQ (vertices[vertices.size ()/2].vertices[1], 4285);
00100   EXPECT_EQ (vertices[vertices.size ()/2].vertices[2], 4286);
00101 }
00102 
00103 
00104 /* ---[ */
00105 int
00106 main (int argc, char** argv)
00107 {
00108   if (argc < 2)
00109   {
00110     std::cerr << "No test file given. Please download `bun0.pcd` and pass its path to the test." << std::endl;
00111     return (-1);
00112   }
00113 
00114   // Load file
00115   pcl::PCLPointCloud2 cloud_blob;
00116   loadPCDFile (argv[1], cloud_blob);
00117   fromPCLPointCloud2 (cloud_blob, *cloud);
00118 
00119   // Create search tree
00120   tree.reset (new search::KdTree<PointXYZ> (false));
00121   tree->setInputCloud (cloud);
00122 
00123   // Normal estimation
00124   NormalEstimation<PointXYZ, Normal> n;
00125   PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
00126   n.setInputCloud (cloud);
00127   //n.setIndices (indices[B);
00128   n.setSearchMethod (tree);
00129   n.setKSearch (20);
00130   n.compute (*normals);
00131 
00132   // Concatenate XYZ and normal information
00133   pcl::concatenateFields (*cloud, *normals, *cloud_with_normals);
00134       
00135   // Create search tree
00136   tree2.reset (new search::KdTree<PointNormal>);
00137   tree2->setInputCloud (cloud_with_normals);
00138 
00139   // Process for update cloud
00140   if(argc == 3){
00141     pcl::PCLPointCloud2 cloud_blob1;
00142     loadPCDFile (argv[2], cloud_blob1);
00143     fromPCLPointCloud2 (cloud_blob1, *cloud1);
00144         // Create search tree
00145     tree3.reset (new search::KdTree<PointXYZ> (false));
00146     tree3->setInputCloud (cloud1);
00147 
00148     // Normal estimation
00149     NormalEstimation<PointXYZ, Normal> n1;
00150     PointCloud<Normal>::Ptr normals1 (new PointCloud<Normal> ());
00151     n1.setInputCloud (cloud1);
00152 
00153     n1.setSearchMethod (tree3);
00154     n1.setKSearch (20);
00155     n1.compute (*normals1);
00156 
00157     // Concatenate XYZ and normal information
00158     pcl::concatenateFields (*cloud1, *normals1, *cloud_with_normals1);
00159     // Create search tree
00160     tree4.reset (new search::KdTree<PointNormal>);
00161     tree4->setInputCloud (cloud_with_normals1);
00162   }
00163 
00164   // Testing
00165   testing::InitGoogleTest (&argc, argv);
00166   return (RUN_ALL_TESTS ());
00167 }
00168 /* ]--- */


pcl
Author(s): Open Perception
autogenerated on Wed Aug 26 2015 15:35:08