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q3DMASC/q3DMASC.cpp
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2018-10-24 11:30:39 +02:00

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//##########################################################################
//# #
//# CLOUDCOMPARE PLUGIN: q3DMASC #
//# #
//# This program is free software; you can redistribute it and/or modify #
//# it under the terms of the GNU General Public License as published by #
//# the Free Software Foundation; version 2 or later of the License. #
//# #
//# This program is distributed in the hope that it will be useful, #
//# but WITHOUT ANY WARRANTY; without even the implied warranty of #
//# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
//# GNU General Public License for more details. #
//# #
//# COPYRIGHT: Dimitri Lague / CNRS / UEB #
//# #
//##########################################################################
#include "q3DMASC.h"
//local
#include "q3DMASCDisclaimerDialog.h"
//qCC_db
#include <ccPointCloud.h>
//Qt
#include <QtGui>
#include <QtCore>
#include <QApplication>
#include <QMessageBox>
#include <QStringList>
q3DMASCPlugin::q3DMASCPlugin(QObject* parent/*=0*/)
: QObject(parent)
, ccStdPluginInterface( ":/CC/plugin/q3DMASCPlugin/info.json" )
, m_classifyAction(0)
, m_trainAction(0)
{
}
void q3DMASCPlugin::onNewSelection(const ccHObject::Container& selectedEntities)
{
if (m_classifyAction)
{
//classification: only one point cloud
m_classifyAction->setEnabled(selectedEntities.size() == 1 && selectedEntities[0]->isA(CC_TYPES::POINT_CLOUD));
}
if (m_trainAction)
{
m_trainAction->setEnabled(m_app && m_app->dbRootObject() && m_app->dbRootObject()->getChildrenNumber() != 0); //need some loaded entities to train the classifier!
}
m_selectedEntities = selectedEntities;
}
QList<QAction*> q3DMASCPlugin::getActions()
{
QList<QAction*> group;
if (!m_trainAction)
{
m_trainAction = new QAction("Train classifier", this);
m_trainAction->setToolTip("Train classifier");
m_trainAction->setIcon(QIcon(QString::fromUtf8(":/CC/plugin/q3DMASCPlugin/iconCreate.png")));
connect(m_trainAction, SIGNAL(triggered()), this, SLOT(doTrainAction()));
}
group.push_back(m_trainAction);
if (!m_classifyAction)
{
m_classifyAction = new QAction("Classify", this);
m_classifyAction->setToolTip("Classify cloud");
m_classifyAction->setIcon(QIcon(QString::fromUtf8(":/CC/plugin/q3DMASCPlugin/iconClassify.png")));
connect(m_classifyAction, SIGNAL(triggered()), this, SLOT(doClassifyAction()));
}
group.push_back(m_classifyAction);
return group;
}
#include <opencv2/ml.hpp>
class IScalarFieldWrapper
{
public:
virtual double pointValue(unsigned index) const = 0;
virtual bool isValid() const = 0;
};
class ScalarFieldWrapper : public IScalarFieldWrapper
{
public:
ScalarFieldWrapper(CCLib::ScalarField* sf)
: m_sf(sf)
{}
virtual inline double pointValue(unsigned index) const override { return m_sf->at(index); }
virtual inline bool isValid() const { return m_sf != nullptr; }
protected:
CCLib::ScalarField* m_sf;
};
class DimScalarFieldWrapper : public IScalarFieldWrapper
{
public:
enum Dim { DimX = 0, DimY = 1, DimZ = 2 };
DimScalarFieldWrapper(ccPointCloud* cloud, Dim dim)
: m_cloud(cloud)
, m_dim(dim)
{}
virtual inline double pointValue(unsigned index) const override { return m_cloud->getPoint(index)->u[m_dim]; }
virtual inline bool isValid() const { return m_cloud != nullptr; }
protected:
ccPointCloud* m_cloud;
Dim m_dim;
};
class ColorScalarFieldWrapper : public IScalarFieldWrapper
{
public:
enum Band { Red = 0, Green = 1, Blue = 2 };
ColorScalarFieldWrapper(ccPointCloud* cloud, Band band)
: m_cloud(cloud)
, m_band(band)
{}
virtual inline double pointValue(unsigned index) const override { return m_cloud->getPointColor(index).rgb[m_band]; }
virtual inline bool isValid() const { return m_cloud != nullptr && m_cloud->hasColors(); }
protected:
ccPointCloud* m_cloud;
Band m_band;
};
#include <LASFields.h>
void q3DMASCPlugin::doClassifyAction()
{
if (!m_app)
{
assert(false);
return;
}
//disclaimer accepted?
if (!ShowClassifyDisclaimer(m_app))
{
return;
}
if (m_selectedEntities.empty() || !m_selectedEntities.front()->isA(CC_TYPES::POINT_CLOUD))
{
m_app->dispToConsole("Select one and only one point cloud!", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
ccPointCloud* cloud = static_cast<ccPointCloud*>(m_selectedEntities.front());
//look for the classification field
int classifSFIdx = cloud->getScalarFieldIndexByName(LAS_FIELD_NAMES[LAS_CLASSIFICATION]); //LAS_FIELD_NAMES[LAS_CLASSIFICATION] = "Classification"
if (!classifSFIdx)
{
m_app->dispToConsole("Missing 'Classification' field", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
CCLib::ScalarField* classifSF = cloud->getScalarField(classifSFIdx);
if (!classifSF || classifSF->size() < cloud->size())
{
assert(false);
return;
}
struct RTParams
{
int maxDepth = 25; //To be left as a parameter of the training plugin (default 25)
int minSampleCount = 1; //To be left as a parameter of the training plugin (default 1)
int maxCategories = 0; //Normally not important as theres no categorical variable
const bool calcVarImportance = true; //Must be true
int activeVarCount = 0; //USE 0 as the default parameter (works best)
int maxTreeCount = 100; //Left as a parameter of the training plugin (default: 100)
};
RTParams params;
struct Feature
{
enum Source
{
ScalarField, DimX, DimY, DimZ, Red, Green, Blue
};
Feature(Source p_source, QString p_name)
: source(p_source)
, name(p_name)
{}
Source source;
QString name; //especially for scalar fields
};
std::vector<Feature> features;
features.push_back(Feature(Feature::DimZ, "Z"));
features.push_back(Feature(Feature::ScalarField, "Intensity"));
features.push_back(Feature(Feature::ScalarField, "Intensity"));
int sampleCount = static_cast<int>(cloud->size());
int attributesPerSample = static_cast<int>(features.size());
//NUMBER_OF_TRAINING_SAMPLES = number of points
//ATTRIBUTES_PER_SAMPLE = number of scalar fields
cv::Mat training_data, train_labels;
try
{
training_data.create(sampleCount, attributesPerSample, CV_32FC1);
train_labels.create(attributesPerSample, 1, CV_8U);
}
catch (const cv::Exception& cvex)
{
ccLog::Error(cvex.msg.c_str());
return;
}
//fill the classification labels vector
{
for (unsigned i = 0; i < cloud->size(); ++i)
{
ScalarType pointClass = classifSF->getValue(i);
int iClass = static_cast<int>(pointClass);
if (iClass < 0 || iClass > 255)
{
m_app->dispToConsole("Classification values out of range (0-255)", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
train_labels.at<unsigned char>(i) = static_cast<unsigned char>(iClass);
}
}
//fill the training data matrix
for (int fIndex = 0; fIndex < attributesPerSample; ++fIndex)
{
QScopedPointer<IScalarFieldWrapper> source(nullptr);
const Feature& f = features[fIndex];
switch (f.source)
{
case Feature::ScalarField:
{
int sfIdx = cloud->getScalarFieldIndexByName(qPrintable(f.name));
if (sfIdx >= 0)
{
source.reset(new ScalarFieldWrapper(cloud->getScalarField(sfIdx)));
}
else
{
ccLog::Error(QString("Internal error: unknwon scalar field '%1'").arg(f.name));
return;
}
}
break;
case Feature::DimX:
source.reset(new DimScalarFieldWrapper(cloud, DimScalarFieldWrapper::DimX));
break;
case Feature::DimY:
source.reset(new DimScalarFieldWrapper(cloud, DimScalarFieldWrapper::DimY));
break;
case Feature::DimZ:
source.reset(new DimScalarFieldWrapper(cloud, DimScalarFieldWrapper::DimZ));
break;
case Feature::Red:
source.reset(new ColorScalarFieldWrapper(cloud, ColorScalarFieldWrapper::Red));
break;
case Feature::Green:
source.reset(new ColorScalarFieldWrapper(cloud, ColorScalarFieldWrapper::Green));
break;
case Feature::Blue:
source.reset(new ColorScalarFieldWrapper(cloud, ColorScalarFieldWrapper::Blue));
break;
}
if (!source || !source->isValid())
{
assert(false);
ccLog::Error(QString("Internal error: invalid source '%1'").arg(f.name));
}
for (unsigned i = 0; i < cloud->size(); ++i)
{
double value = source->pointValue(i);
training_data.at<float>(i, fIndex) = static_cast<float>(value);
}
}
cv::Ptr<cv::ml::RTrees> rtrees;
rtrees = cv::ml::RTrees::create();
rtrees->setMaxDepth(params.maxDepth);
rtrees->setMinSampleCount(params.minSampleCount);
rtrees->setCalculateVarImportance(params.calcVarImportance);
rtrees->setActiveVarCount(params.activeVarCount);
cv::TermCriteria terminationCriteria(cv::TermCriteria::MAX_ITER, params.maxTreeCount, std::numeric_limits<double>::epsilon());
rtrees->setTermCriteria(terminationCriteria);
//rtrees->setRegressionAccuracy(0);
//rtrees->setUseSurrogates(false);
//rtrees->setMaxCategories(params.maxCategories); //not important?
//rtrees->setPriors(cv::Mat());
rtrees->train(training_data, cv::ml::ROW_SAMPLE, train_labels);
}
//OpenCV
void q3DMASCPlugin::doTrainAction()
{
//disclaimer accepted?
if (!ShowTrainDisclaimer(m_app))
return;
//if (m_selectedEntities.size() != 2
// || !m_selectedEntities[0]->isA(CC_TYPES::POINT_CLOUD)
// || !m_selectedEntities[1]->isA(CC_TYPES::POINT_CLOUD))
//{
// m_app->dispToConsole("Select two point clouds!",ccMainAppInterface::ERR_CONSOLE_MESSAGE);
// return;
//}
//
//ccPointCloud* cloud1 = static_cast<ccPointCloud*>(m_selectedEntities[0]);
//ccPointCloud* cloud2 = static_cast<ccPointCloud*>(m_selectedEntities[1]);
}
void q3DMASCPlugin::registerCommands(ccCommandLineInterface* cmd)
{
if (!cmd)
{
assert(false);
return;
}
//cmd->registerCommand(ccCommandLineInterface::Command::Shared(new CommandCanupoClassif));
}