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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2010-2012, Willow Garage, 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.
*
* $Id$
*
*/
#include <pcl/test/gtest.h>
#include <pcl/point_cloud.h>
#include <pcl/pcl_tests.h>
#include <pcl/features/normal_3d_omp.h>
#include <pcl/io/pcd_io.h>
#include <pcl/features/board.h>
using namespace pcl;
using namespace pcl::test;
using namespace pcl::io;
using KdTreePtr = search::KdTree<PointXYZ>::Ptr;
PointCloud<PointXYZ> cloud;
pcl::Indices indices;
KdTreePtr tree;
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (PCL, BOARDLocalReferenceFrameEstimation)
{
PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
PointCloud<ReferenceFrame> bunny_LRF;
pcl::IndicesPtr indicesptr (new pcl::Indices (indices));
// Compute normals
NormalEstimation<PointXYZ, Normal> ne;
ne.setRadiusSearch (0.01);
ne.setViewPoint (1, 1, 10);
ne.setInputCloud (cloud.makeShared ());
ne.setSearchMethod (tree);
ne.setIndices (indicesptr);
ne.compute (*normals);
// Compute BOARD LRF
BOARDLocalReferenceFrameEstimation<PointXYZ, Normal, ReferenceFrame> lrf_estimator;
float meshRes = 0.001f;
lrf_estimator.setFindHoles (true);
lrf_estimator.setRadiusSearch (15 * meshRes);
lrf_estimator.setTangentRadius (15 * meshRes);
lrf_estimator.setInputCloud (cloud.makeShared ());
lrf_estimator.setInputNormals (normals);
lrf_estimator.setSearchMethod (tree);
lrf_estimator.setIndices (indicesptr);
lrf_estimator.compute (bunny_LRF);
// TESTS
EXPECT_EQ (indices.size (), bunny_LRF.size ());
EXPECT_FALSE (bunny_LRF.is_dense);
//EXPECT_EQ (std::numeric_limits<float>::max (), bunny_LRF.at (24).confidence);
EXPECT_TRUE (std::isnan (bunny_LRF.at (24).x_axis[0]));
// Expected Results
//float point_15_conf = -9.06301;
Eigen::Vector3f point_15_x (-0.784923f, 0.208529f, 0.583448f);
Eigen::Vector3f point_15_y (0.334206f, -0.650436f, 0.682085f);
Eigen::Vector3f point_15_z (0.52173f, 0.730376f, 0.440851f);
//float point_45_conf = -9.55398;
Eigen::Vector3f point_45_x (0.909111f, 0.30943f, 0.278874f);
Eigen::Vector3f point_45_y (-0.362239f, 0.917811f, 0.162501f);
Eigen::Vector3f point_45_z (-0.205671f, -0.248751f, 0.946479f);
//float point_163_conf = -9.04891;
Eigen::Vector3f point_163_x (-0.443962f, -0.890073f, -0.103285f);
Eigen::Vector3f point_163_y (0.746929f, -0.30394f, -0.591369f);
Eigen::Vector3f point_163_z (0.494969f, -0.339693f, 0.799759f);
//float point_253_conf = -9.09443;
Eigen::Vector3f point_253_x (-0.616855f, 0.757286f, -0.214495f);
Eigen::Vector3f point_253_y (-0.661937f, -0.646584f, -0.379168f);
Eigen::Vector3f point_253_z (-0.425827f, -0.0919098f, 0.900124f);
//Test Results
//EXPECT_NEAR (point_15_conf,bunny_LRF.at (15).confidence, 1E-3);
//EXPECT_NEAR_VECTORS (point_15_x, bunny_LRF.at (15).x_axis.getNormalVector3fMap (), 1E-3);
//EXPECT_NEAR_VECTORS (point_15_y, bunny_LRF.at (15).y_axis.getNormalVector3fMap (), 1E-3);
//EXPECT_NEAR_VECTORS (point_15_z, bunny_LRF.at (15).z_axis.getNormalVector3fMap (), 1E-3);
for (int d = 0; d < 3; ++d)
{
EXPECT_NEAR (point_15_x[d], bunny_LRF.at (15).x_axis[d], 1E-3);
EXPECT_NEAR (point_15_y[d], bunny_LRF.at (15).y_axis[d], 1E-3);
EXPECT_NEAR (point_15_z[d], bunny_LRF.at (15).z_axis[d], 1E-3);
EXPECT_NEAR (point_45_x[d], bunny_LRF.at (45).x_axis[d], 1E-3);
EXPECT_NEAR (point_45_y[d], bunny_LRF.at (45).y_axis[d], 1E-3);
EXPECT_NEAR (point_45_z[d], bunny_LRF.at (45).z_axis[d], 1E-3);
EXPECT_NEAR (point_163_x[d], bunny_LRF.at (163).x_axis[d], 1E-3);
EXPECT_NEAR (point_163_y[d], bunny_LRF.at (163).y_axis[d], 1E-3);
EXPECT_NEAR (point_163_z[d], bunny_LRF.at (163).z_axis[d], 1E-3);
EXPECT_NEAR (point_253_x[d], bunny_LRF.at (253).x_axis[d], 1E-3);
EXPECT_NEAR (point_253_y[d], bunny_LRF.at (253).y_axis[d], 1E-3);
EXPECT_NEAR (point_253_z[d], bunny_LRF.at (253).z_axis[d], 1E-3);
}
}
/* ---[ */
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);
}
if (loadPCDFile<PointXYZ> (argv[1], cloud) < 0)
{
std::cerr << "Failed to read test file. Please download `bun0.pcd` and pass its path to the test." << std::endl;
return (-1);
}
indices.resize (cloud.size ());
for (std::size_t i = 0; i < indices.size (); ++i)
indices[i] = static_cast<int> (i);
tree.reset (new search::KdTree<PointXYZ> (false));
tree->setInputCloud (cloud.makeShared ());
testing::InitGoogleTest (&argc, argv);
return (RUN_ALL_TESTS ());
}
/* ]--- */
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