-
Notifications
You must be signed in to change notification settings - Fork 433
/
NeighborClassifierFilter.cpp
199 lines (173 loc) · 6.49 KB
/
NeighborClassifierFilter.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
/******************************************************************************
* Copyright (c) 2017, Hobu Inc., info@hobu.co
*
* 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 Hobu, Inc. or Flaxen Geo Consulting 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.
****************************************************************************/
#include "NeighborClassifierFilter.hpp"
#include <pdal/PipelineManager.hpp>
#include <pdal/StageFactory.hpp>
#include <pdal/util/ProgramArgs.hpp>
#include "private/DimRange.hpp"
#include <iostream>
#include <utility>
namespace pdal
{
static PluginInfo const s_info = PluginInfo(
"filters.neighborclassifier",
"Re-assign some point attributes based KNN voting",
"http://pdal.io/stages/filters.neighborclassifier.html" );
CREATE_STATIC_PLUGIN(1, 0, NeighborClassifierFilter, Filter, s_info)
NeighborClassifierFilter::NeighborClassifierFilter() : m_dim(Dimension::Id::Classification)
{}
NeighborClassifierFilter::~NeighborClassifierFilter()
{}
void NeighborClassifierFilter::addArgs(ProgramArgs& args)
{
args.add("domain", "Selects which points will be subject to KNN-based assignmenassignment",
m_domainSpec);
args.add("k", "Number of nearest neighbors to consult",
m_k).setPositional();
//args.add("dimension", "Dimension on to be updated", m_dimName).setPositional();
Arg& candidate = args.add("candidate", "candidate file name",
m_candidateFile);
}
void NeighborClassifierFilter::initialize()
{
for (auto const& r : m_domainSpec)
{
try
{
DimRange range;
range.parse(r);
m_domain.push_back(range);
}
catch (const DimRange::error& err)
{
throwError("Invalid 'domain' option: '" + r + "': " + err.what());
}
}
if (m_k < 1)
throwError("Invalid 'k' option: " + std::to_string(m_k) + ", must be > 0");
}
void NeighborClassifierFilter::prepared(PointTableRef table)
{
PointLayoutPtr layout(table.layout());
for (auto& r : m_domain)
{
r.m_id = layout->findDim(r.m_name);
if (r.m_id == Dimension::Id::Unknown)
throwError("Invalid dimension name in 'domain' option: '" +
r.m_name + "'.");
}
std::sort(m_domain.begin(), m_domain.end());
//m_dim = layout->findDim(m_dimName);
//if (m_dim == Dimension::Id::Unknown)
// throwError("Dimension '" + m_dimName + "' not found.");
}
void NeighborClassifierFilter::doOneNoDomain(PointRef &point, PointRef &temp, KD3Index &kdi)
{
std::vector<PointId> iSrc = kdi.neighbors(point, m_k);
double thresh = iSrc.size()/2.0;
//std::cout << "iSrc.size() " << iSrc.size() << " thresh " << thresh << std::endl;
// vote NNs
std::map<double, unsigned int> counts;
for (PointId id : iSrc)
{
temp.setPointId(id);
double votefor = temp.getFieldAs<double>(m_dim);
counts[votefor]++;
}
// pick winner of the vote
auto pr = *std::max_element(counts.begin(), counts.end(),
[](const std::pair<int, int>& p1, const std::pair<int, int>& p2) {
return p1.second < p2.second; });
// update point
auto oldclass = point.getFieldAs<double>(m_dim);
auto newclass = pr.first;
//std::cout << oldclass << " --> " << newclass << " count " << pr.second << std::endl;
if (pr.second > thresh && oldclass != newclass)
{
point.setField(m_dim, newclass);
}
}
bool NeighborClassifierFilter::doOne(PointRef& point, PointRef &temp, KD3Index &kdi)
{ // update point. kdi and temp both reference the NN point cloud
if (m_domain.empty()) // No domain, process all points
doOneNoDomain(point, temp, kdi);
for (DimRange& r : m_domain)
{ // process only points that satisfy a domain condition
if (r.valuePasses(point.getFieldAs<double>(r.m_id)))
{
doOneNoDomain(point, temp, kdi);
break;
}
}
return true;
}
PointViewPtr NeighborClassifierFilter::loadSet(const std::string& filename,
PointTable& table)
{
PipelineManager mgr;
Stage& reader = mgr.makeReader(filename, "");
reader.prepare(table);
PointViewSet viewSet = reader.execute(table);
assert(viewSet.size() == 1);
return *viewSet.begin();
}
void NeighborClassifierFilter::filter(PointView& view)
{
PointRef point_src(view, 0);
if (m_candidateFile.empty())
{ // No candidate file so NN comes from src file
KD3Index kdiSrc(view);
kdiSrc.build();
PointRef point_nn(view, 0);
for (PointId id = 0; id < view.size(); ++id)
{
point_src.setPointId(id);
doOne(point_src, point_nn, kdiSrc);
}
}
else
{ // NN comes from candidate file
PointTable candTable;
PointViewPtr candView = loadSet(m_candidateFile, candTable);
KD3Index kdiCand(*candView);
kdiCand.build();
PointRef point_nn(*candView, 0);
for (PointId id = 0; id < view.size(); ++id)
{
point_src.setPointId(id);
doOne(point_src, point_nn, kdiCand);
}
}
}
} // namespace pdal