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Training dialog (to set RT parameters mostly)

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This commit is contained in:
Daniel Girardeau-Montaut
2019-01-19 21:40:38 +01:00
parent ecbdb4973e
commit 80a2ae5064
6 changed files with 358 additions and 49 deletions
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q3DMASC.cpp
+69 -45
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@@ -22,6 +22,7 @@
#include "q3DMASCClassifier.h"
#include "q3DMASCTools.h"
#include "qClassify3DMASCDialog.h"
#include "qTrain3DMASCDialog.h"
#include "q3DMASCCommands.h"
//qCC_db
@@ -198,13 +199,6 @@ void q3DMASCPlugin::doTrainAction()
if (!ShowTrainDisclaimer(m_app))
return;
masc::TrainParameters params;
if (params.testDataRatio < 0 || params.testDataRatio > 0.99f)
{
m_app->dispToConsole("Invalid test data ratio", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
QString inputFilename;
{
QSettings settings;
@@ -220,10 +214,12 @@ void q3DMASCPlugin::doTrainAction()
settings.endGroup();
}
static masc::TrainParameters s_params;
std::vector<ccPointCloud*> loadedClouds;
masc::CorePoints corePoints;
masc::Feature::Set features;
if (!masc::Tools::LoadTrainingFile(inputFilename, features, loadedClouds, corePoints))
if (!masc::Tools::LoadTrainingFile(inputFilename, features, loadedClouds, corePoints, s_params))
{
while (!loadedClouds.empty())
{
@@ -289,58 +285,86 @@ void q3DMASCPlugin::doTrainAction()
m_app->redrawAll();
//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, params.testDataRatio, testSubset.data(), trainSubset.data()))
while (true)
{
m_app->dispToConsole("Not enough memory", ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
//train the classifier
masc::Classifier classifier;
{
QString errorMessage;
if (!classifier.train(corePoints.cloud, params.rt, features, errorMessage, trainSubset.data(), m_app->getMainWindow()))
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())
{
m_app->dispToConsole(errorMessage, ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
QString outputFilename;
s_params.rt.maxDepth = trainDlg.maxDepthSpinBox->value();
s_params.rt.maxTreeCount = trainDlg.maxTreeCountSpinBox->value();
s_params.rt.activeVarCount = trainDlg.activeVarCountSpinBox->value();
s_params.rt.minSampleCount = trainDlg.minSampleCountSpinBox->value();
s_params.testDataRatio = trainDlg.testDataRatioSpinBox->value() / 100.0f;
if (s_params.testDataRatio < 0 || s_params.testDataRatio > 0.99f)
{
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())
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()))
{
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()))
{
//process cancelled by the user
m_app->dispToConsole(errorMessage, ccMainAppInterface::ERR_CONSOLE_MESSAGE);
return;
}
settings.setValue("FilePath", QFileInfo(outputFilename).absolutePath());
settings.endGroup();
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
return;
}
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);
}
}
//save the classifier
if (masc::Tools::SaveClassifier(outputFilename, features, classifier, m_app->getMainWindow()))
//test classifier
{
m_app->dispToConsole("Classifier succesfully saved to " + outputFilename, ccMainAppInterface::STD_CONSOLE_MESSAGE);
}
}
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;
}
//test 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;
m_app->dispToConsole(QString("Correct = %1 / %2 --> accuracy = %3").arg(metrics.goodGuess).arg(metrics.sampleCount).arg(metrics.ratio), ccMainAppInterface::STD_CONSOLE_MESSAGE);
}
m_app->dispToConsole(QString("Correct = %1 / %2 --> accuracy = %3").arg(metrics.goodGuess).arg(metrics.sampleCount).arg(metrics.ratio), ccMainAppInterface::STD_CONSOLE_MESSAGE);
break;
}
}