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greenhouse/src/Settings.cpp
matlabbe e3b15a7106 Modified parameters' name to reduce the number of pages in the parameters toolbox. 
Added a way to sort (with a prefix number) parameters in toolbox. 
Can now switch between nearest neighbor strategies (kd-trees, k-means, linear).
Added parameters for all FLANN nearest neighbor approaches.
Added likelihood plot (including UPlot from UtiLite library and PdfPlot from RTAB-Map library).
Added general parameter "MirrorView".
Added general parameter "InvertedSearch" to create the  vocabulary from objects descriptor instead of the scene descriptors. We can then compute likelihood of the current scene with all other objects (or another scenes). 
Fixed a crash (in AddObjectDialog) when selecting outside the image.
Added OpenCV version used in AboutDialog.

git-svn-id: http://find-object.googlecode.com/svn/trunk/find_object@109 620bd6b2-0a58-f614-fd9a-1bd335dccda9
2012-08-28 13:44:57 +00:00

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/*
* Copyright (C) 2011, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
*/
#include "Settings.h"
#include "Camera.h"
#include <QtCore/QSettings>
#include <QtCore/QStringList>
#include <QtCore/QDir>
#include <stdio.h>
#include <opencv2/nonfree/features2d.hpp>
#define VERBOSE 0
ParametersMap Settings::defaultParameters_;
ParametersMap Settings::parameters_;
ParametersType Settings::parametersType_;
Settings Settings::dummyInit_;
QString Settings::workingDirectory()
{
#ifdef WIN32
return QString("%1/Documents/%2").arg(QDir::homePath()).arg(PROJECT_NAME);
#else
return QString("%1").arg(QDir::homePath());
#endif
}
QString Settings::iniDefaultPath()
{
#ifdef WIN32
return QString("%1/Documents/%2/%3").arg(QDir::homePath()).arg(PROJECT_NAME).arg(Settings::iniDefaultFileName());
#else
return QString("%1/.%2/%3").arg(QDir::homePath()).arg(PROJECT_PREFIX).arg(Settings::iniDefaultFileName());
#endif
}
void Settings::loadSettings(const QString & fileName, QByteArray * windowGeometry, QByteArray * windowState)
{
QString path = fileName;
if(fileName.isEmpty())
{
path = iniDefaultPath();
}
QSettings ini(path, QSettings::IniFormat);
for(ParametersMap::const_iterator iter = defaultParameters_.begin(); iter!=defaultParameters_.end(); ++iter)
{
const QString & key = iter.key();
QVariant value = ini.value(key, QVariant());
if(value.isValid())
{
setParameter(key, value);
}
}
if(windowGeometry)
{
QVariant value = ini.value("windowGeometry", QVariant());
if(value.isValid())
{
*windowGeometry = value.toByteArray();
}
}
if(windowState)
{
QVariant value = ini.value("windowState", QVariant());
if(value.isValid())
{
*windowState = value.toByteArray();
}
}
printf("Settings loaded from %s\n", path.toStdString().c_str());
}
void Settings::saveSettings(const QString & fileName, const QByteArray & windowGeometry, const QByteArray & windowState)
{
QString path = fileName;
if(fileName.isEmpty())
{
path = iniDefaultPath();
}
QSettings ini(path, QSettings::IniFormat);
for(ParametersMap::const_iterator iter = parameters_.begin(); iter!=parameters_.end(); ++iter)
{
QString type = Settings::getParametersType().value(iter.key());
if(type.compare("float") == 0)
{
ini.setValue(iter.key(), QString::number(iter.value().toFloat(),'g',6));
}
else
{
ini.setValue(iter.key(), iter.value());
}
}
if(!windowGeometry.isEmpty())
{
ini.setValue("windowGeometry", windowGeometry);
}
if(!windowState.isEmpty())
{
ini.setValue("windowState", windowState);
}
printf("Settings saved to %s\n", path.toStdString().c_str());
}
cv::FeatureDetector * Settings::createFeaturesDetector()
{
cv::FeatureDetector * detector = 0;
QString str = getDetector_Descriptor_1Detector();
QStringList split = str.split(':');
if(split.size()==2)
{
bool ok = false;
int index = split.first().toInt(&ok);
if(ok)
{
QStringList strategies = split.last().split(';');
if(strategies.size() == 8 && index>=0 && index<8)
{
switch(index)
{
case 0:
if(strategies.at(index).compare("Dense") == 0)
{
detector = new cv::DenseFeatureDetector(
getDetector_Descriptor_Dense_initFeatureScale(),
getDetector_Descriptor_Dense_featureScaleLevels(),
getDetector_Descriptor_Dense_featureScaleMul(),
getDetector_Descriptor_Dense_initXyStep(),
getDetector_Descriptor_Dense_initImgBound(),
getDetector_Descriptor_Dense_varyXyStepWithScale(),
getDetector_Descriptor_Dense_varyImgBoundWithScale());
if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", "Dense");
}
break;
case 1:
if(strategies.at(index).compare("Fast") == 0)
{
detector = new cv::FastFeatureDetector(
getDetector_Descriptor_Fast_threshold(),
getDetector_Descriptor_Fast_nonmaxSuppression());
if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", "Fast");
}
break;
case 2:
if(strategies.at(index).compare("GFTT") == 0)
{
detector = new cv::GFTTDetector(
getDetector_Descriptor_GFTT_maxCorners(),
getDetector_Descriptor_GFTT_qualityLevel(),
getDetector_Descriptor_GFTT_minDistance(),
getDetector_Descriptor_GFTT_blockSize(),
getDetector_Descriptor_GFTT_useHarrisDetector(),
getDetector_Descriptor_GFTT_k());
if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", "GFTT");
}
break;
case 3:
if(strategies.at(index).compare("MSER") == 0)
{
detector = new cv::MSER(
getDetector_Descriptor_MSER_delta(),
getDetector_Descriptor_MSER_minArea(),
getDetector_Descriptor_MSER_maxArea(),
getDetector_Descriptor_MSER_maxVariation(),
getDetector_Descriptor_MSER_minDiversity(),
getDetector_Descriptor_MSER_maxEvolution(),
getDetector_Descriptor_MSER_areaThreshold(),
getDetector_Descriptor_MSER_minMargin(),
getDetector_Descriptor_MSER_edgeBlurSize());
if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", "MSER");
}
break;
case 4:
if(strategies.at(index).compare("ORB") == 0)
{
detector = new cv::ORB(
getDetector_Descriptor_ORB_nFeatures(),
getDetector_Descriptor_ORB_scaleFactor(),
getDetector_Descriptor_ORB_nLevels(),
getDetector_Descriptor_ORB_edgeThreshold(),
getDetector_Descriptor_ORB_firstLevel(),
getDetector_Descriptor_ORB_WTA_K(),
getDetector_Descriptor_ORB_scoreType(),
getDetector_Descriptor_ORB_patchSize());
if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", "ORB");
}
break;
case 5:
if(strategies.at(index).compare("SIFT") == 0)
{
detector = new cv::SIFT(
getDetector_Descriptor_SIFT_nfeatures(),
getDetector_Descriptor_SIFT_nOctaveLayers(),
getDetector_Descriptor_SIFT_contrastThreshold(),
getDetector_Descriptor_SIFT_edgeThreshold(),
getDetector_Descriptor_SIFT_sigma());
if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", "SIFT");
}
break;
case 6:
if(strategies.at(index).compare("Star") == 0)
{
detector = new cv::StarFeatureDetector(
getDetector_Descriptor_Star_maxSize(),
getDetector_Descriptor_Star_responseThreshold(),
getDetector_Descriptor_Star_lineThresholdProjected(),
getDetector_Descriptor_Star_lineThresholdBinarized(),
getDetector_Descriptor_Star_suppressNonmaxSize());
if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", "Star");
}
break;
case 7:
if(strategies.at(index).compare("SURF") == 0)
{
detector = new cv::SURF(
getDetector_Descriptor_SURF_hessianThreshold(),
getDetector_Descriptor_SURF_nOctaves(),
getDetector_Descriptor_SURF_nOctaveLayers(),
getDetector_Descriptor_SURF_extended(),
getDetector_Descriptor_SURF_upright());
if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", "SURF");
}
break;
default:
break;
}
}
}
}
if(!detector)
{
printf("ERROR: detector strategy not found !? Using default SURF...\n");
detector = new cv::SURF();
}
return detector;
}
cv::DescriptorExtractor * Settings::createDescriptorsExtractor()
{
cv::DescriptorExtractor * extractor = 0;
QString str = getDetector_Descriptor_2Descriptor();
QStringList split = str.split(':');
if(split.size()==2)
{
bool ok = false;
int index = split.first().toInt(&ok);
if(ok)
{
QStringList strategies = split.last().split(';');
if(strategies.size() == 4 && index>=0 && index<4)
{
switch(index)
{
case 0:
if(strategies.at(index).compare("Brief") == 0)
{
extractor = new cv::BriefDescriptorExtractor(
getDetector_Descriptor_Brief_bytes());
if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", "Brief");
}
break;
case 1:
if(strategies.at(index).compare("ORB") == 0)
{
extractor = new cv::ORB(
getDetector_Descriptor_ORB_nFeatures(),
getDetector_Descriptor_ORB_scaleFactor(),
getDetector_Descriptor_ORB_nLevels(),
getDetector_Descriptor_ORB_edgeThreshold(),
getDetector_Descriptor_ORB_firstLevel(),
getDetector_Descriptor_ORB_WTA_K(),
getDetector_Descriptor_ORB_scoreType(),
getDetector_Descriptor_ORB_patchSize());
if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", "ORB");
}
break;
case 2:
if(strategies.at(index).compare("SIFT") == 0)
{
extractor = new cv::SIFT(
getDetector_Descriptor_SIFT_nfeatures(),
getDetector_Descriptor_SIFT_nOctaveLayers(),
getDetector_Descriptor_SIFT_contrastThreshold(),
getDetector_Descriptor_SIFT_edgeThreshold(),
getDetector_Descriptor_SIFT_sigma());
if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", "SIFT");
}
break;
case 3:
if(strategies.at(index).compare("SURF") == 0)
{
extractor = new cv::SURF(
getDetector_Descriptor_SURF_hessianThreshold(),
getDetector_Descriptor_SURF_nOctaves(),
getDetector_Descriptor_SURF_nOctaveLayers(),
getDetector_Descriptor_SURF_extended(),
getDetector_Descriptor_SURF_upright());
if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", "SURF");
}
break;
default:
break;
}
}
}
}
if(!extractor)
{
printf("ERROR: descriptor strategy not found !? Using default SURF...\n");
extractor = new cv::SURF();
}
return extractor;
}
QString Settings::currentDetectorType()
{
int index = getDetector_Descriptor_1Detector().split(':').first().toInt();
return getDetector_Descriptor_1Detector().split(':').last().split(';').at(index);
}
QString Settings::currentDescriptorType()
{
int index = getDetector_Descriptor_2Descriptor().split(':').first().toInt();
return getDetector_Descriptor_2Descriptor().split(':').last().split(';').at(index);
}
QString Settings::currentNearestNeighborType()
{
int index = getNearestNeighbor_1Strategy().split(':').first().toInt();
return getNearestNeighbor_1Strategy().split(':').last().split(';').at(index);
}
cv::flann::IndexParams * Settings::createFlannIndexParams()
{
cv::flann::IndexParams * params = 0;
QString str = getNearestNeighbor_1Strategy();
QStringList split = str.split(':');
if(split.size()==2)
{
bool ok = false;
int index = split.first().toInt(&ok);
if(ok)
{
QStringList strategies = split.last().split(';');
if(strategies.size() == 6 && index>=0 && index<6)
{
switch(index)
{
case 0:
if(strategies.at(index).compare("Linear") == 0)
{
if(VERBOSE)printf("Settings::getFlannIndexParams() type=%s\n", "Linear");
params = new cv::flann::LinearIndexParams();
}
break;
case 1:
if(strategies.at(index).compare("KDTree") == 0)
{
if(VERBOSE)printf("Settings::getFlannIndexParams() type=%s\n", "KDTree");
params = new cv::flann::KDTreeIndexParams(
getNearestNeighbor_KDTree_trees());
}
break;
case 2:
if(strategies.at(index).compare("KMeans") == 0)
{
cvflann::flann_centers_init_t centers_init = cvflann::FLANN_CENTERS_RANDOM;
QString str = getNearestNeighbor_KMeans_centers_init();
QStringList split = str.split(':');
if(split.size()==2)
{
bool ok = false;
int index = split.first().toInt(&ok);
if(ok)
{
centers_init = (cvflann::flann_centers_init_t)index;
}
}
if(VERBOSE)printf("Settings::getFlannIndexParams() type=%s\n", "KMeans");
params = new cv::flann::KMeansIndexParams(
getNearestNeighbor_KMeans_branching(),
getNearestNeighbor_KMeans_iterations(),
centers_init,
getNearestNeighbor_KMeans_cb_index());
}
break;
case 3:
if(strategies.at(index).compare("Composite") == 0)
{
cvflann::flann_centers_init_t centers_init = cvflann::FLANN_CENTERS_RANDOM;
QString str = getNearestNeighbor_Composite_centers_init();
QStringList split = str.split(':');
if(split.size()==2)
{
bool ok = false;
int index = split.first().toInt(&ok);
if(ok)
{
centers_init = (cvflann::flann_centers_init_t)index;
}
}
if(VERBOSE)printf("Settings::getFlannIndexParams() type=%s\n", "Composite");
params = new cv::flann::CompositeIndexParams(
getNearestNeighbor_Composite_trees(),
getNearestNeighbor_Composite_branching(),
getNearestNeighbor_Composite_iterations(),
centers_init,
getNearestNeighbor_Composite_cb_index());
}
break;
case 4:
if(strategies.at(index).compare("Autotuned") == 0)
{
if(VERBOSE)printf("Settings::getFlannIndexParams() type=%s\n", "Autotuned");
params = new cv::flann::AutotunedIndexParams(
getNearestNeighbor_Autotuned_target_precision(),
getNearestNeighbor_Autotuned_build_weight(),
getNearestNeighbor_Autotuned_memory_weight(),
getNearestNeighbor_Autotuned_sample_fraction());
}
break;
case 5:
if(strategies.at(index).compare("Lsh") == 0)
{
if(VERBOSE)printf("Settings::getFlannIndexParams() type=%s\n", "Lsh");
params = new cv::flann::LshIndexParams(
getNearestNeighbor_Lsh_table_number(),
getNearestNeighbor_Lsh_key_size(),
getNearestNeighbor_Lsh_multi_probe_level());
}
break;
default:
break;
}
}
}
}
if(!params)
{
printf("ERROR: NN strategy not found !? Using default KDTRee...\n");
params = new cv::flann::KDTreeIndexParams();
}
return params ;
}
cvflann::flann_distance_t Settings::getFlannDistanceType()
{
cvflann::flann_distance_t distance = cvflann::FLANN_DIST_L2;
QString str = getNearestNeighbor_2Distance_type();
QStringList split = str.split(':');
if(split.size()==2)
{
bool ok = false;
int index = split.first().toInt(&ok);
if(ok)
{
QStringList strategies = split.last().split(';');
if(strategies.size() == 8 && index>=0 && index<8)
{
distance = (cvflann::flann_distance_t)(index+1);
}
}
}
if(VERBOSE)printf("Settings::getFlannDistanceType() distance=%d\n", distance);
return distance;
}
cv::flann::SearchParams Settings::getFlannSearchParams()
{
return cv::flann::SearchParams();
}
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