saberbud/q3DMASC
1
0
Fork 0
mirror of https://github.com/dgirardeau/q3DMASC.git synced 2026-08-29 08:34:48 +08:00
Code Issues Packages Projects Releases Wiki Activity

New training dialog + selection of the most important features

Browse Source
This commit is contained in:
Daniel Girardeau-Montaut
2019-01-20 22:12:20 +01:00
parent 4ec7252b80
commit b5e5597e2d
7 changed files with 419 additions and 111 deletions
Download Patch File Download Diff File Expand all files Collapse all files
Train3DMASCDialog.ui
+93 -39
View File
@@ -6,8 +6,8 @@
<rect>
<x>0</x>
<y>0</y>
<width>397</width>
<height>476</height>
<width>400</width>
<height>500</height>
</rect>
</property>
<property name="windowTitle">
@@ -103,7 +103,7 @@
<item>
<widget class="QGroupBox" name="otherGroupBox">
<property name="title">
<string>Other</string>
<string>Other parameters</string>
</property>
<layout class="QFormLayout" name="formLayout_2">
<item row="0" column="0">
@@ -136,26 +136,96 @@
</widget>
</item>
<item>
<spacer name="verticalSpacer">
<property name="orientation">
<enum>Qt::Vertical</enum>
<widget class="QFrame" name="frame">
<property name="frameShape">
<enum>QFrame::StyledPanel</enum>
</property>
<property name="sizeHint" stdset="0">
<size>
<width>20</width>
<height>40</height>
</size>
<property name="frameShadow">
<enum>QFrame::Raised</enum>
</property>
</spacer>
<layout class="QHBoxLayout" name="horizontalLayout">
<item>
<widget class="QPushButton" name="runPushButton">
<property name="text">
<string>Run</string>
</property>
</widget>
</item>
<item>
<widget class="QPushButton" name="savePushButton">
<property name="enabled">
<bool>false</bool>
</property>
<property name="text">
<string>Save</string>
</property>
</widget>
</item>
<item>
<widget class="QPushButton" name="closePushButton">
<property name="text">
<string>Close</string>
</property>
</widget>
</item>
</layout>
<zorder>runPushButton</zorder>
<zorder>closePushButton</zorder>
<zorder>savePushButton</zorder>
</widget>
</item>
<item>
<widget class="QDialogButtonBox" name="buttonBox">
<property name="orientation">
<enum>Qt::Horizontal</enum>
<widget class="QGroupBox" name="resultGroupBox">
<property name="sizePolicy">
<sizepolicy hsizetype="Preferred" vsizetype="Expanding">
<horstretch>0</horstretch>
<verstretch>0</verstretch>
</sizepolicy>
</property>
<property name="standardButtons">
<set>QDialogButtonBox::Cancel|QDialogButtonBox::Ok</set>
<property name="title">
<string>Results</string>
</property>
<layout class="QVBoxLayout" name="verticalLayout_2">
<item>
<widget class="QLabel" name="resultLabel">
<property name="text">
<string>correct = 0/0 - accuracy = 0.0</string>
</property>
</widget>
</item>
<item>
<widget class="QTableWidget" name="tableWidget">
<property name="verticalScrollBarPolicy">
<enum>Qt::ScrollBarAlwaysOn</enum>
</property>
<property name="showDropIndicator" stdset="0">
<bool>false</bool>
</property>
<property name="dragDropOverwriteMode">
<bool>false</bool>
</property>
<property name="selectionMode">
<enum>QAbstractItemView::NoSelection</enum>
</property>
<attribute name="horizontalHeaderDefaultSectionSize">
<number>170</number>
</attribute>
<attribute name="verticalHeaderVisible">
<bool>false</bool>
</attribute>
<column>
<property name="text">
<string>Feature</string>
</property>
</column>
<column>
<property name="text">
<string>Importance</string>
</property>
</column>
</widget>
</item>
</layout>
</widget>
</item>
</layout>
@@ -163,34 +233,18 @@
<resources/>
<connections>
<connection>
<sender>buttonBox</sender>
<signal>accepted()</signal>
<sender>runPushButton</sender>
<signal>clicked()</signal>
<receiver>Train3DMASCDialog</receiver>
<slot>accept()</slot>
<hints>
<hint type="sourcelabel">
<x>248</x>
<y>254</y>
<x>76</x>
<y>296</y>
</hint>
<hint type="destinationlabel">
<x>157</x>
<y>274</y>
</hint>
</hints>
</connection>
<connection>
<sender>buttonBox</sender>
<signal>rejected()</signal>
<receiver>Train3DMASCDialog</receiver>
<slot>reject()</slot>
<hints>
<hint type="sourcelabel">
<x>316</x>
<y>260</y>
</hint>
<hint type="destinationlabel">
<x>286</x>
<y>274</y>
<x>198</x>
<y>237</y>
</hint>
</hints>
</connection>
q3DMASC.cpp
+184 -68
View File
@@ -162,19 +162,19 @@ void q3DMASCPlugin::doClassifyAction()
corePoints.origin = corePoints.cloud = clouds[mainCloudLabel];
//prepare the main cloud
ccProgressDialog pDlg(true, m_app->getMainWindow());
pDlg.setAutoClose(false); //we don't want the progress dialog to 'pop' for each feature
ccProgressDialog progressDlg(true, m_app->getMainWindow());
progressDlg.setAutoClose(false); //we don't want the progress dialog to 'pop' for each feature
QString error;
SFCollector generatedScalarFields;
if (!masc::Tools::PrepareFeatures(corePoints, features, error, &pDlg, &generatedScalarFields))
if (!masc::Tools::PrepareFeatures(corePoints, features, error, &progressDlg, &generatedScalarFields))
{
m_app->dispToConsole(error, ccMainAppInterface::ERR_CONSOLE_MESSAGE);
generatedScalarFields.clear();
return;
}
pDlg.close();
progressDlg.close();
QCoreApplication::processEvents();
pDlg.setAutoClose(true); //restore the default behavior of the progress dialog
progressDlg.setAutoClose(true); //restore the default behavior of the progress dialog
//apply classifier
{
@@ -193,6 +193,15 @@ void q3DMASCPlugin::doClassifyAction()
}
}
struct FeatureSelection
{
FeatureSelection(masc::Feature::Shared f = masc::Feature::Shared(nullptr)) : feature(f) {}
masc::Feature::Shared feature;
bool selected = true;
bool prepared = false;
float importance = std::numeric_limits<float>::quiet_NaN();
};
void q3DMASCPlugin::doTrainAction()
{
//disclaimer accepted?
@@ -236,8 +245,32 @@ void q3DMASCPlugin::doTrainAction()
group->addChild(pc);
}
ccProgressDialog pDlg(true, m_app->getMainWindow());
if (!corePoints.prepare(&pDlg))
//show the training dialog for the first time
Train3DMASCDialog trainDlg(m_app->getMainWindow());
trainDlg.maxDepthSpinBox->setValue(s_params.rt.maxDepth);
trainDlg.maxTreeCountSpinBox->setValue(s_params.rt.maxTreeCount);
trainDlg.activeVarCountSpinBox->setValue(s_params.rt.activeVarCount);
trainDlg.minSampleCountSpinBox->setValue(s_params.rt.minSampleCount);
trainDlg.testDataRatioSpinBox->setValue(static_cast<int>(s_params.testDataRatio * 100));
//display the loaded features and let the user select the ones to use
trainDlg.setResultText("Select features and press 'Run'");
std::vector<FeatureSelection> originalFeatures;
originalFeatures.reserve(features.size());
for (const masc::Feature::Shared& f : features)
{
originalFeatures.push_back(FeatureSelection(f));
trainDlg.addFeature(f->toString(), originalFeatures.back().importance, originalFeatures.back().selected);
}
if (!trainDlg.exec())
{
return;
}
assert(!trainDlg.shouldSaveClassifier()); //the save button should be disabled at this point
//compute the core points (if necessary)
ccProgressDialog progressDlg(true, m_app->getMainWindow());
if (!corePoints.prepare(&progressDlg))
{
m_app->dispToConsole("Failed to compute/prepare the core points!", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
delete group;
@@ -271,33 +304,64 @@ void q3DMASCPlugin::doTrainAction()
m_app->addToDB(group);
QCoreApplication::processEvents();
pDlg.setAutoClose(false); //we don't want the progress dialog to 'pop' for each feature
QString error;
if (!masc::Tools::PrepareFeatures(corePoints, features, error, &pDlg))
{
m_app->dispToConsole(error, ccMainAppInterface::ERR_CONSOLE_MESSAGE);
delete group;
return;
}
pDlg.setAutoClose(true); //restore the default behavior of the progress dialog
pDlg.close();
QCoreApplication::processEvents();
//train / test subsets
QScopedPointer<CCLib::ReferenceCloud> trainSubset(new CCLib::ReferenceCloud(corePoints.cloud));
QScopedPointer<CCLib::ReferenceCloud> testSubset(new CCLib::ReferenceCloud(corePoints.cloud));
float previousTrainSubsetRatio = -1.0f;
m_app->redrawAll();
while (true)
for (int iteration = 0; ; ++iteration)
{
Train3DMASCDialog trainDlg(m_app->getMainWindow());
trainDlg.maxDepthSpinBox->setValue(s_params.rt.maxDepth);
trainDlg.maxTreeCountSpinBox->setValue(s_params.rt.maxTreeCount);
trainDlg.activeVarCountSpinBox->setValue(s_params.rt.activeVarCount);
trainDlg.minSampleCountSpinBox->setValue(s_params.rt.minSampleCount);
trainDlg.testDataRatioSpinBox->setValue(static_cast<int>(s_params.testDataRatio * 100));
if (!trainDlg.exec())
//look for selected features
features.clear();
masc::Feature::Set toPrepare;
for (size_t i = 0; i < originalFeatures.size(); ++i)
{
return;
originalFeatures[i].selected = trainDlg.isFeatureSelected(i);
//if the feature is selected
if (originalFeatures[i].selected)
{
if (!originalFeatures[i].prepared)
{
//we should prepare it first!
toPrepare.push_back(originalFeatures[i].feature);
}
features.push_back(originalFeatures[i].feature);
}
}
if (features.empty())
{
m_app->dispToConsole("No feature selected!", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
continue;
}
//prepare the features
if (!toPrepare.empty())
{
progressDlg.setAutoClose(false); //we don't want the progress dialog to 'pop' for each feature
QString error;
if (!masc::Tools::PrepareFeatures(corePoints, toPrepare, error, &progressDlg))
{
m_app->dispToConsole(error, ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
progressDlg.setAutoClose(true); //restore the default behavior of the progress dialog
progressDlg.close();
QCoreApplication::processEvents();
m_app->redrawAll();
//flag the prepared features as 'prepared' ;)
for (FeatureSelection& fs : originalFeatures)
{
if (fs.selected && !fs.prepared)
fs.prepared = true;
}
}
masc::Classifier classifier;
//retrieve parameters
s_params.rt.maxDepth = trainDlg.maxDepthSpinBox->value();
s_params.rt.maxTreeCount = trainDlg.maxTreeCountSpinBox->value();
s_params.rt.activeVarCount = trainDlg.activeVarCountSpinBox->value();
@@ -307,64 +371,116 @@ void q3DMASCPlugin::doTrainAction()
{
assert(false);
m_app->dispToConsole("Invalid test data ratio", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
//randomly select the training points
QScopedPointer<CCLib::ReferenceCloud> trainSubset(new CCLib::ReferenceCloud(corePoints.cloud));
QScopedPointer<CCLib::ReferenceCloud> testSubset(new CCLib::ReferenceCloud(corePoints.cloud));
if (!masc::Tools::RandomSubset(corePoints.cloud, s_params.testDataRatio, testSubset.data(), trainSubset.data()))
else
{
m_app->dispToConsole("Not enough memory", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
//train the classifier
masc::Classifier classifier;
{
QString errorMessage;
if (!classifier.train(corePoints.cloud, s_params.rt, features, errorMessage, trainSubset.data(), m_app->getMainWindow()))
if (previousTrainSubsetRatio != s_params.testDataRatio)
{
m_app->dispToConsole(errorMessage, ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
QString outputFilename;
{
QSettings settings;
settings.beginGroup("3DMASC");
QString outputPath = settings.value("FilePath", QCoreApplication::applicationDirPath()).toString();
outputFilename = QFileDialog::getSaveFileName(m_app->getMainWindow(), "Save 3DMASC classifier", outputPath, "*.txt");
if (outputFilename.isNull())
//randomly select the training points
testSubset->clear();
trainSubset->clear();
if (!masc::Tools::RandomSubset(corePoints.cloud, s_params.testDataRatio, testSubset.data(), trainSubset.data()))
{
//process cancelled by the user
m_app->dispToConsole("Not enough memory", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
settings.setValue("FilePath", QFileInfo(outputFilename).absolutePath());
settings.endGroup();
previousTrainSubsetRatio = s_params.testDataRatio;
}
//save the classifier
if (masc::Tools::SaveClassifier(outputFilename, features, classifier, m_app->getMainWindow()))
//train the classifier
{
m_app->dispToConsole("Classifier succesfully saved to " + outputFilename, ccMainAppInterface::STD_CONSOLE_MESSAGE);
QString errorMessage;
if (!classifier.train(corePoints.cloud, s_params.rt, features, errorMessage, trainSubset.data(), m_app, m_app->getMainWindow()))
{
m_app->dispToConsole(errorMessage, ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
trainDlg.setFirstRunDone();
trainDlg.shouldSaveClassifier();
}
//test the trained classifier
{
masc::Classifier::AccuracyMetrics metrics;
QString errorMessage;
if (!classifier.evaluate(features, testSubset.data(), metrics, errorMessage, m_app->getMainWindow()))
{
m_app->dispToConsole(errorMessage, ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
QString resultText = QString("Correct guess = %1 / %2 --> accuracy = %3").arg(metrics.goodGuess).arg(metrics.sampleCount).arg(metrics.ratio);
m_app->dispToConsole(resultText, ccMainAppInterface::STD_CONSOLE_MESSAGE);
trainDlg.setResultText(resultText);
cv::Mat importanceMat = classifier.getVarImportance();
//m_app->dispToConsole(QString("Var importance size = %1 x %2").arg(importanceMat.rows).arg(importanceMat.cols));
assert(static_cast<int>(features.size()) == importanceMat.rows);
int selectedFeatureIndex = 0;
for (size_t i = 0; i < originalFeatures.size(); ++i)
{
if (originalFeatures[i].selected)
{
//m_app->dispToConsole(QString("Feature #%1 importance = %2").arg(i + 1).arg(importanceMat.at<float>(i, 0)));
assert(selectedFeatureIndex < importanceMat.rows);
originalFeatures[i].importance = importanceMat.at<float>(selectedFeatureIndex, 0);
++selectedFeatureIndex;
}
else
{
originalFeatures[i].importance = std::numeric_limits<float>::quiet_NaN();
}
trainDlg.setFeatureImportance(i, originalFeatures[i].importance);
}
}
}
//test classifier
while (true)
{
masc::Classifier::AccuracyMetrics metrics;
QString errorMessage;
if (!classifier.evaluate(features, testSubset.data(), metrics, errorMessage, m_app->getMainWindow()))
if (!trainDlg.exec())
{
m_app->dispToConsole(errorMessage, ccMainAppInterface::ERR_CONSOLE_MESSAGE);
//the dialog can be closed
return;
}
m_app->dispToConsole(QString("Correct = %1 / %2 --> accuracy = %3").arg(metrics.goodGuess).arg(metrics.sampleCount).arg(metrics.ratio), ccMainAppInterface::STD_CONSOLE_MESSAGE);
//if the save button has been clicked
if (trainDlg.shouldSaveClassifier())
{
//ask for the output filename
QString outputFilename;
{
QSettings settings;
settings.beginGroup("3DMASC");
QString outputPath = settings.value("FilePath", QCoreApplication::applicationDirPath()).toString();
outputFilename = QFileDialog::getSaveFileName(m_app->getMainWindow(), "Save 3DMASC classifier", outputPath, "*.txt");
if (outputFilename.isNull())
{
//process cancelled by the user
continue;
}
settings.setValue("FilePath", QFileInfo(outputFilename).absolutePath());
settings.endGroup();
}
//save the classifier
if (masc::Tools::SaveClassifier(outputFilename, features, classifier, m_app->getMainWindow()))
{
m_app->dispToConsole("Classifier succesfully saved to " + outputFilename, ccMainAppInterface::STD_CONSOLE_MESSAGE);
trainDlg.setClassifierSaved();
}
else
{
m_app->dispToConsole("Failed to save classifier file");
}
}
else //we will run the classifier another time
{
//stop the local loop
break;
}
}
break;
//we are going to restart the classification process
}
}
q3DMASCClassifier.cpp
+19 -1
View File
@@ -29,6 +29,9 @@
//qCC_io
#include <LASFields.h>
//qCC_plugins
#include <ccMainAppInterface.h>
//Qt
#include <QCoreApplication>
#include <QProgressDialog>
@@ -360,6 +363,7 @@ bool Classifier::train( const ccPointCloud* cloud,
const Feature::Set& features,
QString& errorMessage,
CCLib::ReferenceCloud* trainSubset/*=nullptr*/,
ccMainAppInterface* app/*=nullptr*/,
QWidget* parentWidget/*=nullptr*/)
{
if (features.empty())
@@ -397,7 +401,10 @@ bool Classifier::train( const ccPointCloud* cloud,
int sampleCount = static_cast<int>(trainSubset ? trainSubset->size() : cloud->size());
int attributesPerSample = static_cast<int>(features.size());
ccLog::Print(QString("[3DMASC] Training data: %1 samples with %2 feature(s)").arg(sampleCount).arg(attributesPerSample));
if (app)
{
app->dispToConsole(QString("[3DMASC] Training data: %1 samples with %2 feature(s)").arg(sampleCount).arg(attributesPerSample));
}
cv::Mat training_data, train_labels;
try
@@ -530,6 +537,17 @@ bool Classifier::train( const ccPointCloud* cloud,
return false;
}
if (app)
{
cv::Mat mat = m_rtrees->getVarImportance();
app->dispToConsole(QString("Var importance size = %1 x %2").arg(mat.rows).arg(mat.cols));
assert(attributesPerSample == mat.rows);
for (int i = 0; i < mat.rows; ++i)
{
app->dispToConsole(QString("Feature #%1 importance = %2").arg(i + 1).arg(mat.at<float>(i, 0)));
}
}
return true;
}
q3DMASCClassifier.h
+10 -1
View File
@@ -31,6 +31,7 @@
#include <opencv2/ml.hpp>
class QWidget;
class ccMainAppInterface;
//! 3DMASC classifier
namespace masc
@@ -43,7 +44,13 @@ namespace masc
Classifier();
//! Train the classifier
bool train(const ccPointCloud* cloud, const RandomTreesParams& params, const Feature::Set& features, QString& errorMessage, CCLib::ReferenceCloud* trainSubset = nullptr, QWidget* parentWidget = nullptr);
bool train( const ccPointCloud* cloud,
const RandomTreesParams& params,
const Feature::Set& features,
QString& errorMessage,
CCLib::ReferenceCloud* trainSubset = nullptr,
ccMainAppInterface* app = nullptr,
QWidget* parentWidget = nullptr);
//! Classifier accuracy metrics
struct AccuracyMetrics
@@ -67,6 +74,8 @@ namespace masc
//! Loads the classifier from file
bool fromFile(QString filename, QWidget* parentWidget = nullptr);
inline cv::Mat getVarImportance() const { return m_rtrees->getVarImportance(); }
protected:
//! Random trees (OpenCV)
q3DMASCTools.cpp
+1 -2
View File
@@ -632,7 +632,7 @@ static bool LoadFileCommon( const QString& filename,
std::vector<double> scales;
QTextStream stream(&file);
for (int lineNumber = 0; ; ++lineNumber)
for (int lineNumber = 1; ; ++lineNumber)
{
QString line = stream.readLine();
if (line.isNull())
@@ -640,7 +640,6 @@ static bool LoadFileCommon( const QString& filename,
//eof
break;
}
++lineNumber;
if (line.startsWith("#"))
{
qTrain3DMASCDialog.cpp
+87
View File
@@ -17,9 +17,96 @@
#include "qTrain3DMASCDialog.h"
//Qt
#include <QTableWidgetItem>
#include <QMessageBox>
//System
#include <assert.h>
Train3DMASCDialog::Train3DMASCDialog(QWidget* parent/*=nullptr*/)
: QDialog(parent)
, Ui::Train3DMASCDialog()
, classifierSaved(false)
, saveRequested(false)
{
setupUi(this);
connect(closePushButton, SIGNAL(clicked()), this, SLOT(onClose()));
connect(savePushButton, SIGNAL(clicked()), this, SLOT(onSave()));
}
void Train3DMASCDialog::clearResults()
{
resultLabel->clear();
tableWidget->clear();
}
int Train3DMASCDialog::addFeature(QString name, float importance, bool isChecked/*=true*/)
{
int index = tableWidget->rowCount();
tableWidget->setRowCount(index + 1);
QTableWidgetItem* nameItem = new QTableWidgetItem(name);
nameItem->setCheckState(isChecked ? Qt::Checked : Qt::Unchecked);
tableWidget->setItem(index, 0, nameItem);
QTableWidgetItem* importanceItem = new QTableWidgetItem(std::isnan(importance) ? QString() : QString::number(importance));
tableWidget->setItem(index, 1, importanceItem);
return index;
}
void Train3DMASCDialog::setResultText(QString text)
{
resultLabel->setText(text);
}
void Train3DMASCDialog::setFirstRunDone()
{
runPushButton->setText(tr("Retry"));
savePushButton->setEnabled(true);
}
bool Train3DMASCDialog::isFeatureSelected(size_t index) const
{
if (static_cast<int>(index) >= tableWidget->rowCount())
{
assert(false);
return false;
}
return (tableWidget->item(static_cast<int>(index), 0)->checkState() == Qt::Checked);
}
void Train3DMASCDialog::setFeatureImportance(size_t index, float importance)
{
if (static_cast<int>(index) >= tableWidget->rowCount())
{
assert(false);
return;
}
if (!std::isnan(importance))
{
tableWidget->item(static_cast<int>(index), 1)->setText(QString::number(importance));
}
else
{
tableWidget->item(static_cast<int>(index), 1)->setText(QString());
}
}
void Train3DMASCDialog::onClose()
{
if (!classifierSaved && QMessageBox::question(this, "Classifier not saved", "Classifier not saved. Do you confirm you want to close the tool?", QMessageBox::Yes, QMessageBox::No) == QMessageBox::No)
return;
reject();
}
void Train3DMASCDialog::onSave()
{
saveRequested = true;
accept();
}
qTrain3DMASCDialog.h
+25
View File
@@ -32,4 +32,29 @@ public:
//! Default constructor
Train3DMASCDialog(QWidget* parent = nullptr);
void clearResults();
//! Adds a feature (entry) to the results table
/** \return the row index
**/
int addFeature(QString name, float importance, bool isChecked = true);
void setResultText(QString text);
void setFirstRunDone();
inline void setClassifierSaved() { classifierSaved = true; saveRequested = false; }
bool isFeatureSelected(size_t index) const;
void setFeatureImportance(size_t index, float importance);
inline bool shouldSaveClassifier() const { return saveRequested; }
protected slots:
void onClose();
void onSave();
protected: //members
bool classifierSaved;
bool saveRequested;
};