Point Cloud Library (PCL)
1.15.1
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pcl
ml
impl
kmeans.hpp
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/*
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* Software License Agreement (BSD License)
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*
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* Point Cloud Library (PCL) - www.pointclouds.org
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*
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of Willow Garage, Inc. nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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* Author : Christian Potthast
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* Email : potthast@usc.edu
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*
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*/
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#pragma once
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#include <pcl/ml/kmeans.h>
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//#include <pcl/common/io.h>
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//#include <stdio.h>
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//#include <stdlib.h>
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//#include <time.h>
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namespace
pcl
{
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template
<
typename
Po
int
T>
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Kmeans<PointT>::Kmeans
() : cluster_field_name_(
""
)
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{}
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template
<
typename
Po
int
T>
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void
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Kmeans<PointT>::cluster
(std::vector<PointIndices>& clusters)
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{
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if
(!initCompute() || (input_ != 0 && input_->points.empty()) ||
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(indices_ != 0 && indices_->empty())) {
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clusters.clear();
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return
;
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}
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pcl::PointCloud<PointT>
point;
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std::vector<pcl::PCLPointField> fields;
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// if no cluster field name is set, check for X Y Z
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if
(strcmp(cluster_field_name_.c_str(),
""
) == 0) {
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int
x_index = -1;
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int
y_index = -1;
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int
z_index = -1;
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x_index =
pcl::getFieldIndex<PointT>
(
"x"
, fields);
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if
(y_index != -1)
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y_index =
pcl::getFieldIndex<PointT>
(
"y"
, fields);
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if
(z_index != -1)
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z_index =
pcl::getFieldIndex<PointT>
(
"z"
, fields);
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if
(x_index == -1 && y_index == -1 && z_index == -1) {
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PCL_ERROR(
"Failed to find match for field 'x y z'\n"
);
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return
;
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}
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PCL_INFO(
"Use X Y Z as input data\n"
);
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// create input data
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/*
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for (std::size_t i = 0; i < input_->size (); i++)
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{
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DataPoint data (3);
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data[0] = (*input_)[i].data[0];
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}
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*/
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std::cout <<
"x index: "
<< x_index << std::endl;
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float
x = 0.0;
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memcpy(&x, &(*input_)[0] +
fields
[x_index].offset,
sizeof
(
float
));
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std::cout <<
"xxx: "
<< x << std::endl;
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// memcpy (&x, reinterpret_cast<float*> (&(*input_)[0]) + x_index, sizeof
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// (float));
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// int rgba_index = 1;
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// pcl::RGB rgb;
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// memcpy (&rgb, reinterpret_cast<const char*>
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// (&(*input_)[index_vector[i].cloud_point_index]) + rgba_index, sizeof (RGB));
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}
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// if cluster field name is set, check if field name is valid
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else
{
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int
user_index =
pcl::getFieldIndex<PointT>
(cluster_field_name_.c_str(),
fields
);
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if
(user_index == -1) {
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PCL_ERROR(
"Failed to find match for field '%s'\n"
, cluster_field_name_.c_str());
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return
;
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}
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}
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/*
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int xyz_index = -1;
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pcl::PointCloud <PointT> point;
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xyz_index = pcl::getFieldIndex<PointT> ("r", fields);
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if (xyz_index == -1 && strcmp (cluster_field_name_.c_str (), "") == 0)
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{
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PCL_ERROR ("Failed to find match for field '%s'\n", cluster_field_name_.c_str ());
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}
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std::cout << "index: " << xyz_index << std::endl;
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std::string t = pcl::getFieldsList (point);
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std::cout << "t: " << t << std::endl;
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*/
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// std::vector <pcl::PCLPointField> fields;
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// pcl::getFieldIndex (*input_, "xyz", fields);
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// std::cout << "field: " << fields[xyz_index].count << std::endl;
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/*
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for (std::size_t i = 0; i < fields[vfh_idx].count; ++i)
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{
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//vfh.second[i] = point[0].histogram[i];
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}
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*/
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deinitCompute();
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}
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}
// namespace pcl
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#define PCL_INSTANTIATE_Kmeans(T) template class PCL_EXPORTS pcl::Kmeans<T>;
pcl::Kmeans
K-means clustering.
Definition
kmeans.h:55
pcl::Kmeans::Kmeans
Kmeans(unsigned int num_points, unsigned int num_dimensions)
Empty constructor.
Definition
kmeans.hpp:52
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition
point_cloud.h:174
pcl::fields
Definition
type_traits.h:60
pcl
Definition
convolution.h:46
pcl::getFieldIndex
int getFieldIndex(const pcl::PointCloud< PointT > &, const std::string &field_name, std::vector< pcl::PCLPointField > &fields)
Definition
io.hpp:52