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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2012-, Open Perception, Inc.
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the copyright holder(s) nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* $Id: test_surface.cpp 6579 2012-07-27 18:57:32Z rusu $
*
*/
#include <pcl/test/gtest.h>
#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/io/vtk_io.h>
#include <pcl/features/normal_3d.h>
#include <pcl/surface/mls.h>
#include <pcl/surface/gp3.h>
#include <pcl/surface/marching_cubes_hoppe.h>
#include <pcl/surface/marching_cubes_rbf.h>
#include <pcl/common/common.h>
using namespace pcl;
using namespace pcl::io;
PointCloud<PointXYZ>::Ptr cloud (new PointCloud<PointXYZ>);
PointCloud<PointNormal>::Ptr cloud_with_normals (new PointCloud<PointNormal>);
search::KdTree<PointXYZ>::Ptr tree;
search::KdTree<PointNormal>::Ptr tree2;
// add by ktran to test update functions
PointCloud<PointXYZ>::Ptr cloud1 (new PointCloud<PointXYZ>);
PointCloud<PointNormal>::Ptr cloud_with_normals1 (new PointCloud<PointNormal>);
search::KdTree<PointXYZ>::Ptr tree3;
search::KdTree<PointNormal>::Ptr tree4;
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (PCL, MarchingCubesTest)
{
MarchingCubesHoppe<PointNormal> hoppe;
hoppe.setIsoLevel (0);
hoppe.setGridResolution (30, 30, 30);
hoppe.setPercentageExtendGrid (0.3f);
hoppe.setInputCloud (cloud_with_normals);
PointCloud<PointNormal> points;
std::vector<Vertices> vertices;
hoppe.reconstruct (points, vertices);
EXPECT_NEAR (points[points.size()/2].x, -0.037143, 1e-3);
EXPECT_NEAR (points[points.size()/2].y, 0.098213, 1e-3);
EXPECT_NEAR (points[points.size()/2].z, -0.044911, 1e-3);
EXPECT_EQ (vertices[vertices.size ()/2].vertices[0], 11202);
EXPECT_EQ (vertices[vertices.size ()/2].vertices[1], 11203);
EXPECT_EQ (vertices[vertices.size ()/2].vertices[2], 11204);
MarchingCubesRBF<PointNormal> rbf;
rbf.setIsoLevel (0);
rbf.setGridResolution (20, 20, 20);
rbf.setPercentageExtendGrid (0.1f);
rbf.setInputCloud (cloud_with_normals);
rbf.setOffSurfaceDisplacement (0.02f);
rbf.reconstruct (points, vertices);
EXPECT_NEAR (points[points.size()/2].x, -0.025630, 1e-3);
EXPECT_NEAR (points[points.size()/2].y, 0.135228, 1e-3);
EXPECT_NEAR (points[points.size()/2].z, 0.035766, 1e-3);
EXPECT_EQ (vertices[vertices.size ()/2].vertices[0], 4275);
EXPECT_EQ (vertices[vertices.size ()/2].vertices[1], 4276);
EXPECT_EQ (vertices[vertices.size ()/2].vertices[2], 4277);
}
/* ---[ */
int
main (int argc, char** argv)
{
if (argc < 2)
{
std::cerr << "No test file given. Please download `bun0.pcd` and pass its path to the test." << std::endl;
return (-1);
}
// Load file
pcl::PCLPointCloud2 cloud_blob;
loadPCDFile (argv[1], cloud_blob);
fromPCLPointCloud2 (cloud_blob, *cloud);
// Create search tree
tree.reset (new search::KdTree<PointXYZ> (false));
tree->setInputCloud (cloud);
// Normal estimation
NormalEstimation<PointXYZ, Normal> n;
PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
n.setInputCloud (cloud);
//n.setIndices (indices[B);
n.setSearchMethod (tree);
n.setKSearch (20);
n.compute (*normals);
// Concatenate XYZ and normal information
pcl::concatenateFields (*cloud, *normals, *cloud_with_normals);
// Create search tree
tree2.reset (new search::KdTree<PointNormal>);
tree2->setInputCloud (cloud_with_normals);
// Process for update cloud
if(argc == 3){
pcl::PCLPointCloud2 cloud_blob1;
loadPCDFile (argv[2], cloud_blob1);
fromPCLPointCloud2 (cloud_blob1, *cloud1);
// Create search tree
tree3.reset (new search::KdTree<PointXYZ> (false));
tree3->setInputCloud (cloud1);
// Normal estimation
NormalEstimation<PointXYZ, Normal> n1;
PointCloud<Normal>::Ptr normals1 (new PointCloud<Normal> ());
n1.setInputCloud (cloud1);
n1.setSearchMethod (tree3);
n1.setKSearch (20);
n1.compute (*normals1);
// Concatenate XYZ and normal information
pcl::concatenateFields (*cloud1, *normals1, *cloud_with_normals1);
// Create search tree
tree4.reset (new search::KdTree<PointNormal>);
tree4->setInputCloud (cloud_with_normals1);
}
// Testing
testing::InitGoogleTest (&argc, argv);
return (RUN_ALL_TESTS ());
}
/* ]--- */
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