greenhouse/src/Settings.cpp

/*
 * Copyright (C) 2011, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
 */

#include "Settings.h"
#include "Camera.h"
#include "utilite/ULogger.h"
#include <QtCore/QSettings>
#include <QtCore/QStringList>
#include <QtCore/QDir>
#include <stdio.h>
#include <opencv2/nonfree/features2d.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include <opencv2/nonfree/gpu.hpp>
#include <opencv2/gpu/gpu.hpp>

#define VERBOSE 0

ParametersMap Settings::defaultParameters_;
ParametersMap Settings::parameters_;
ParametersType Settings::parametersType_;
DescriptionsMap Settings::descriptions_;
Settings Settings::dummyInit_;
QString Settings::iniPath_;

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
}

QString Settings::iniPath()
{
	if(!iniPath_.isNull())
	{
		return iniPath_;
	}
	return iniDefaultPath();
}

void Settings::init(const QString & fileName)
{
	iniPath_ = fileName;
	if(fileName.isEmpty())
	{
		iniPath_ = iniDefaultPath();
	}
	loadSettings(iniPath_);
}

void Settings::loadSettings(const QString & fileName)
{
	QString path = fileName;
	if(fileName.isEmpty())
	{
		path = iniPath();
	}
	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())
		{
			QString str = value.toString();
			if(str.contains(";") && str.size() != getParameter(key).toString().size())
			{
				// If a string list is modified, update the value
				// (assuming that index < 10... one character for index)
				QChar index = str.at(0);
				str = getParameter(key).toString();
				str[0] = index.toAscii();
				value = QVariant(str);
				UINFO("Updated list of parameter \"%s\"", key.toStdString().c_str());
			}
			setParameter(key, value);
		}
	}

	if(cv::gpu::getCudaEnabledDeviceCount() == 0)
	{
		Settings::setFeature2D_SURF_gpu(false);
		Settings::setFeature2D_Fast_gpu(false);
		Settings::setFeature2D_ORB_gpu(false);
	}

	UINFO("Settings loaded from %s", path.toStdString().c_str());
}

void Settings::loadWindowSettings(QByteArray & windowGeometry, QByteArray & windowState, const QString & fileName)
{
	QString path = fileName;
	if(fileName.isEmpty())
	{
		path = iniPath();
	}

	QSettings ini(path, QSettings::IniFormat);

	QVariant value = ini.value("windowGeometry", QVariant());
	if(value.isValid())
	{
		windowGeometry = value.toByteArray();
	}

	value = ini.value("windowState", QVariant());
	if(value.isValid())
	{
		windowState = value.toByteArray();
	}

	UINFO("Window settings loaded from %s", path.toStdString().c_str());
}

void Settings::saveSettings(const QString & fileName)
{
	QString path = fileName;
	if(fileName.isEmpty())
	{
		path = iniPath();
	}
	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());
		}
	}
	UINFO("Settings saved to %s", path.toStdString().c_str());
}

void Settings::saveWindowSettings(const QByteArray & windowGeometry, const QByteArray & windowState, const QString & fileName)
{
	QString path = fileName;
	if(fileName.isEmpty())
	{
		path = iniPath();
	}
	QSettings ini(path, QSettings::IniFormat);
	if(!windowGeometry.isEmpty())
	{
		ini.setValue("windowGeometry", windowGeometry);
	}
	if(!windowState.isEmpty())
	{
		ini.setValue("windowState", windowState);
	}
	UINFO("Window settings saved to %s", path.toStdString().c_str());
}

class GPUFeature2D
{
public:
	GPUFeature2D() {}
	virtual ~GPUFeature2D() {}

	virtual void detectKeypoints(const cv::Mat & image,
			std::vector<cv::KeyPoint> & keypoints) = 0;

	virtual void computeDescriptors(const cv::Mat & image,
			std::vector<cv::KeyPoint> & keypoints,
			cv::Mat & descriptors) = 0;
};

class GPUSURF : public GPUFeature2D
{
public:
	GPUSURF(double hessianThreshold,
            int nOctaves,
            int nOctaveLayers,
            bool extended,
            float keypointsRatio,
            bool upright) :
	surf_(hessianThreshold,
		  nOctaves,
		  nOctaveLayers,
		  extended,
		  keypointsRatio,
		  upright)
	{
	}
	virtual ~GPUSURF() {}

    void detectKeypoints(const cv::Mat & image, std::vector<cv::KeyPoint> & keypoints)
    {
    	cv::gpu::GpuMat imgGpu(image);
		try
		{
			surf_(imgGpu, cv::gpu::GpuMat(), keypoints);
		}
		catch(cv::Exception &e)
		{
			UERROR("GPUSURF error: %s \n(If something about layer_rows, parameter nOctaves=%d of SURF "
					"is too high for the size of the image (%d,%d).)",
					e.msg.c_str(),
					surf_.nOctaves,
					image.cols,
					image.rows);
		}
    }

    void computeDescriptors( const cv::Mat& image,
    		std::vector<cv::KeyPoint>& keypoints,
    		cv::Mat& descriptors)
    {
    	std::vector<float> d;
		cv::gpu::GpuMat imgGpu(image);
		cv::gpu::GpuMat descriptorsGPU;
		try
		{
			surf_(imgGpu, cv::gpu::GpuMat(), keypoints, descriptorsGPU, true);
    	}
		catch(cv::Exception &e)
		{
			UERROR("GPUSURF error: %s \n(If something about layer_rows, parameter nOctaves=%d of SURF "
					"is too high for the size of the image (%d,%d).)",
					e.msg.c_str(),
					surf_.nOctaves,
					image.cols,
					image.rows);
		}

		// Download descriptors
		if (descriptorsGPU.empty())
			descriptors = cv::Mat();
		else
		{
			Q_ASSERT(descriptorsGPU.type() == CV_32F);
			descriptors = cv::Mat(descriptorsGPU.size(), CV_32F);
			descriptorsGPU.download(descriptors);
		}
    }
private:
    cv::gpu::SURF_GPU surf_; // HACK: static because detectImpl() is const!
};

class GPUFAST : public GPUFeature2D
{
public:
	GPUFAST(int threshold=Settings::defaultFeature2D_Fast_threshold(),
			bool nonmaxSuppression=Settings::defaultFeature2D_Fast_nonmaxSuppression(),
			double keypointsRatio=Settings::defaultFeature2D_Fast_keypointsRatio()) :
		fast_(threshold,
			  nonmaxSuppression,
			  keypointsRatio)
	{
	}
	virtual ~GPUFAST() {}

protected:
	void detectKeypoints(const cv::Mat & image, std::vector<cv::KeyPoint> & keypoints)
    {
    	cv::gpu::GpuMat imgGpu(image);
    	fast_(imgGpu, cv::gpu::GpuMat(), keypoints);
    }
	void computeDescriptors( const cv::Mat& image,
		std::vector<cv::KeyPoint>& keypoints,
		cv::Mat& descriptors)
	{
		UERROR("GPUFAST:computeDescriptors() Should not be used!");
	}

private:
    cv::gpu::FAST_GPU fast_;
};

class GPUORB : public GPUFeature2D
{
public:
	GPUORB(int nFeatures = Settings::defaultFeature2D_ORB_nFeatures(),
			float scaleFactor = Settings::defaultFeature2D_ORB_scaleFactor(),
			int nLevels = Settings::defaultFeature2D_ORB_nLevels(),
			int edgeThreshold = Settings::defaultFeature2D_ORB_edgeThreshold(),
            int firstLevel = Settings::defaultFeature2D_ORB_firstLevel(),
            int WTA_K = Settings::defaultFeature2D_ORB_WTA_K(),
            int scoreType = Settings::defaultFeature2D_ORB_scoreType(),
            int patchSize = Settings::defaultFeature2D_ORB_patchSize(),
            int fastThreshold = Settings::defaultFeature2D_Fast_threshold(),
            bool fastNonmaxSupression = Settings::defaultFeature2D_Fast_nonmaxSuppression()) :
		orb_(nFeatures,
			 scaleFactor,
			 nLevels,
			 edgeThreshold ,
			 firstLevel,
			 WTA_K,
			 scoreType,
			 patchSize)
	{
		orb_.setFastParams(fastThreshold, fastNonmaxSupression);
	}
	virtual ~GPUORB() {}

protected:
	void detectKeypoints(const cv::Mat & image, std::vector<cv::KeyPoint> & keypoints)
    {
    	cv::gpu::GpuMat imgGpu(image);
    	try
    	{
    		orb_(imgGpu, cv::gpu::GpuMat(), keypoints);
    	}
    	catch(cv::Exception &e)
		{
    		UERROR("GPUORB error: %s \n(If something about matrix size, the image/object may be too small (%d,%d).)",
					e.msg.c_str(),
					image.cols,
					image.rows);
		}
    }

    void computeDescriptors( const cv::Mat& image,
        		std::vector<cv::KeyPoint>& keypoints,
        		cv::Mat& descriptors)
	{
		std::vector<float> d;
		cv::gpu::GpuMat imgGpu(image);
		cv::gpu::GpuMat descriptorsGPU;
		try
		{
			orb_(imgGpu, cv::gpu::GpuMat(), keypoints, descriptorsGPU); // No option to use provided keypoints!?
		}
		catch(cv::Exception &e)
		{
			UERROR("GPUORB error: %s \n(If something about matrix size, the image/object may be too small (%d,%d).)",
					e.msg.c_str(),
					image.cols,
					image.rows);
		}
		// Download descriptors
		if (descriptorsGPU.empty())
			descriptors = cv::Mat();
		else
		{
			Q_ASSERT(descriptorsGPU.type() == CV_8U);
			descriptors = cv::Mat(descriptorsGPU.size(), CV_8U);
			descriptorsGPU.download(descriptors);
		}
	}
private:
    cv::gpu::ORB_GPU orb_;
};

KeypointDetector * Settings::createKeypointDetector()
{
	cv::FeatureDetector * detector = 0;
	GPUFeature2D * detectorGPU = 0;
	QString str = getFeature2D_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() == 9 && index>=0 && index<9)
			{
				switch(index)
				{
				case 0:
					if(strategies.at(index).compare("Dense") == 0)
					{
						detector = new cv::DenseFeatureDetector(
								getFeature2D_Dense_initFeatureScale(),
								getFeature2D_Dense_featureScaleLevels(),
								getFeature2D_Dense_featureScaleMul(),
								getFeature2D_Dense_initXyStep(),
								getFeature2D_Dense_initImgBound(),
								getFeature2D_Dense_varyXyStepWithScale(),
								getFeature2D_Dense_varyImgBoundWithScale());
						if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				case 1:
					if(strategies.at(index).compare("Fast") == 0)
					{
						if(getFeature2D_Fast_gpu() && cv::gpu::getCudaEnabledDeviceCount())
						{
							detectorGPU = new GPUFAST(
									getFeature2D_Fast_threshold(),
									getFeature2D_Fast_nonmaxSuppression());
							if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s GPU\n", strategies.at(index).toStdString().c_str());
						}
						else
						{
							detector = new cv::FastFeatureDetector(
									getFeature2D_Fast_threshold(),
									getFeature2D_Fast_nonmaxSuppression());
							if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", strategies.at(index).toStdString().c_str());
						}
					}
					break;
				case 2:
					if(strategies.at(index).compare("GFTT") == 0)
					{
						detector = new cv::GFTTDetector(
								getFeature2D_GFTT_maxCorners(),
								getFeature2D_GFTT_qualityLevel(),
								getFeature2D_GFTT_minDistance(),
								getFeature2D_GFTT_blockSize(),
								getFeature2D_GFTT_useHarrisDetector(),
								getFeature2D_GFTT_k());
						if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				case 3:
					if(strategies.at(index).compare("MSER") == 0)
					{
						detector = new cv::MSER(
								getFeature2D_MSER_delta(),
								getFeature2D_MSER_minArea(),
								getFeature2D_MSER_maxArea(),
								getFeature2D_MSER_maxVariation(),
								getFeature2D_MSER_minDiversity(),
								getFeature2D_MSER_maxEvolution(),
								getFeature2D_MSER_areaThreshold(),
								getFeature2D_MSER_minMargin(),
								getFeature2D_MSER_edgeBlurSize());
						if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				case 4:
					if(strategies.at(index).compare("ORB") == 0)
					{
						if(getFeature2D_ORB_gpu() && cv::gpu::getCudaEnabledDeviceCount())
						{
							detectorGPU = new GPUORB(
									getFeature2D_ORB_nFeatures(),
									getFeature2D_ORB_scaleFactor(),
									getFeature2D_ORB_nLevels(),
									getFeature2D_ORB_edgeThreshold(),
									getFeature2D_ORB_firstLevel(),
									getFeature2D_ORB_WTA_K(),
									getFeature2D_ORB_scoreType(),
									getFeature2D_ORB_patchSize(),
									getFeature2D_Fast_threshold(),
									getFeature2D_Fast_nonmaxSuppression());
							if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s (GPU)\n", strategies.at(index).toStdString().c_str());
						}
						else
						{
							detector = new cv::ORB(
									getFeature2D_ORB_nFeatures(),
									getFeature2D_ORB_scaleFactor(),
									getFeature2D_ORB_nLevels(),
									getFeature2D_ORB_edgeThreshold(),
									getFeature2D_ORB_firstLevel(),
									getFeature2D_ORB_WTA_K(),
									getFeature2D_ORB_scoreType(),
									getFeature2D_ORB_patchSize());
							if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", strategies.at(index).toStdString().c_str());
						}
					}
					break;
				case 5:
					if(strategies.at(index).compare("SIFT") == 0)
					{
						detector = new cv::SIFT(
								getFeature2D_SIFT_nfeatures(),
								getFeature2D_SIFT_nOctaveLayers(),
								getFeature2D_SIFT_contrastThreshold(),
								getFeature2D_SIFT_edgeThreshold(),
								getFeature2D_SIFT_sigma());
						if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				case 6:
					if(strategies.at(index).compare("Star") == 0)
					{
						detector = new cv::StarFeatureDetector(
								getFeature2D_Star_maxSize(),
								getFeature2D_Star_responseThreshold(),
								getFeature2D_Star_lineThresholdProjected(),
								getFeature2D_Star_lineThresholdBinarized(),
								getFeature2D_Star_suppressNonmaxSize());
						if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				case 7:
					if(strategies.at(index).compare("SURF") == 0)
					{
						if(getFeature2D_SURF_gpu() && cv::gpu::getCudaEnabledDeviceCount())
						{
							detectorGPU = new GPUSURF(
									getFeature2D_SURF_hessianThreshold(),
									getFeature2D_SURF_nOctaves(),
									getFeature2D_SURF_nOctaveLayers(),
									getFeature2D_SURF_extended(),
									getFeature2D_SURF_keypointsRatio(),
									getFeature2D_SURF_upright());
							if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s (GPU)\n", strategies.at(index).toStdString().c_str());
						}
						else
						{
							detector = new cv::SURF(
								getFeature2D_SURF_hessianThreshold(),
								getFeature2D_SURF_nOctaves(),
								getFeature2D_SURF_nOctaveLayers(),
								getFeature2D_SURF_extended(),
								getFeature2D_SURF_upright());
							if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", strategies.at(index).toStdString().c_str());
						}
					}
					break;
				case 8:
					if(strategies.at(index).compare("BRISK") == 0)
					{
						detector = new cv::BRISK(
								getFeature2D_BRISK_thresh(),
								getFeature2D_BRISK_octaves(),
								getFeature2D_BRISK_patternScale());
						if(VERBOSE)printf("Settings::createFeaturesDetector() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				default:
					break;
				}
			}
		}
	}

	Q_ASSERT(detectorGPU!=0 || detector!=0);
	if(detectorGPU)
	{
		return new KeypointDetector(detectorGPU);
	}
	else
	{
		return new KeypointDetector(detector);
	}
}

DescriptorExtractor * Settings::createDescriptorExtractor()
{
	cv::DescriptorExtractor * extractor = 0;
	GPUFeature2D * extractorGPU = 0;
	QString str = getFeature2D_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() == 6 && index>=0 && index<6)
			{
				switch(index)
				{
				case 0:
					if(strategies.at(index).compare("Brief") == 0)
					{
						extractor = new cv::BriefDescriptorExtractor(
								getFeature2D_Brief_bytes());
						if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				case 1:
					if(strategies.at(index).compare("ORB") == 0)
					{
						if(getFeature2D_ORB_gpu() && cv::gpu::getCudaEnabledDeviceCount())
						{
							extractorGPU = new GPUORB(
									getFeature2D_ORB_nFeatures(),
									getFeature2D_ORB_scaleFactor(),
									getFeature2D_ORB_nLevels(),
									getFeature2D_ORB_edgeThreshold(),
									getFeature2D_ORB_firstLevel(),
									getFeature2D_ORB_WTA_K(),
									getFeature2D_ORB_scoreType(),
									getFeature2D_ORB_patchSize(),
									getFeature2D_Fast_threshold(),
									getFeature2D_Fast_nonmaxSuppression());
							if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s (GPU)\n", strategies.at(index).toStdString().c_str());
						}
						else
						{
							extractor = new cv::ORB(
									getFeature2D_ORB_nFeatures(),
									getFeature2D_ORB_scaleFactor(),
									getFeature2D_ORB_nLevels(),
									getFeature2D_ORB_edgeThreshold(),
									getFeature2D_ORB_firstLevel(),
									getFeature2D_ORB_WTA_K(),
									getFeature2D_ORB_scoreType(),
									getFeature2D_ORB_patchSize());
							if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", strategies.at(index).toStdString().c_str());
						}
					}
					break;
				case 2:
					if(strategies.at(index).compare("SIFT") == 0)
					{
						extractor = new cv::SIFT(
								getFeature2D_SIFT_nfeatures(),
								getFeature2D_SIFT_nOctaveLayers(),
								getFeature2D_SIFT_contrastThreshold(),
								getFeature2D_SIFT_edgeThreshold(),
								getFeature2D_SIFT_sigma());
						if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				case 3:
					if(strategies.at(index).compare("SURF") == 0)
					{
						if(getFeature2D_SURF_gpu() && cv::gpu::getCudaEnabledDeviceCount())
						{
							extractorGPU = new GPUSURF(
									getFeature2D_SURF_hessianThreshold(),
									getFeature2D_SURF_nOctaves(),
									getFeature2D_SURF_nOctaveLayers(),
									getFeature2D_SURF_extended(),
									getFeature2D_SURF_keypointsRatio(),
									getFeature2D_SURF_upright());
							if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s (GPU)\n", strategies.at(index).toStdString().c_str());
						}
						else
						{
							extractor = new cv::SURF(
									getFeature2D_SURF_hessianThreshold(),
									getFeature2D_SURF_nOctaves(),
									getFeature2D_SURF_nOctaveLayers(),
									getFeature2D_SURF_extended(),
									getFeature2D_SURF_upright());
							if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", strategies.at(index).toStdString().c_str());
						}
					}
					break;
				case 4:
					if(strategies.at(index).compare("BRISK") == 0)
					{
						extractor = new cv::BRISK(
								getFeature2D_BRISK_thresh(),
								getFeature2D_BRISK_octaves(),
								getFeature2D_BRISK_patternScale());
						if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				case 5:
					if(strategies.at(index).compare("FREAK") == 0)
					{
						extractor = new cv::FREAK(
								getFeature2D_FREAK_orientationNormalized(),
								getFeature2D_FREAK_scaleNormalized(),
								getFeature2D_FREAK_patternScale(),
								getFeature2D_FREAK_nOctaves());
						if(VERBOSE)printf("Settings::createDescriptorsExtractor() type=%s\n", strategies.at(index).toStdString().c_str());
					}
					break;
				default:
					break;
				}
			}
		}
	}

	Q_ASSERT(extractorGPU!=0 || extractor!=0);
	if(extractorGPU)
	{
		return new DescriptorExtractor(extractorGPU);
	}
	else
	{
		return new DescriptorExtractor(extractor);
	}
}

QString Settings::currentDetectorType()
{
	int index = getFeature2D_1Detector().split(':').first().toInt();
	return getFeature2D_1Detector().split(':').last().split(';').at(index);
}

QString Settings::currentDescriptorType()
{
	int index = getFeature2D_2Descriptor().split(':').first().toInt();
	return getFeature2D_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)
	{
		UERROR("NN strategy not found !? Using default KDTRee...");
		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() == 9 && 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(
			getNearestNeighbor_7search_checks(),
			getNearestNeighbor_8search_eps(),
			getNearestNeighbor_9search_sorted());
}

int Settings::getHomographyMethod()
{
	int method = cv::RANSAC;
	QString str = getHomography_method();
	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() == 2 && index>=0 && index<2)
			{
				switch(method)
				{
				case 0:
					method = cv::LMEDS;
					break;
				default:
					method = cv::RANSAC;
					break;
				}
			}
		}
	}
	if(VERBOSE)printf("Settings::getHomographyMethod() method=%d\n", method);
	return method;
}

KeypointDetector::KeypointDetector(cv::FeatureDetector * featureDetector) :
	featureDetector_(featureDetector),
	gpuFeature2D_(0)
{
	Q_ASSERT(featureDetector_!=0);
}
KeypointDetector::KeypointDetector(GPUFeature2D * gpuFeature2D) :
	featureDetector_(0),
	gpuFeature2D_(gpuFeature2D)
{
	Q_ASSERT(gpuFeature2D_!=0);
}
void KeypointDetector::detect(const cv::Mat & image, std::vector<cv::KeyPoint> & keypoints)
{
	if(featureDetector_)
	{
		featureDetector_->detect(image, keypoints);
	}
	else // assume GPU
	{
		gpuFeature2D_->detectKeypoints(image, keypoints);
	}
}

DescriptorExtractor::DescriptorExtractor(cv::DescriptorExtractor * descriptorExtractor) :
	descriptorExtractor_(descriptorExtractor),
	gpuFeature2D_(0)
{
	Q_ASSERT(descriptorExtractor_!=0);
}
DescriptorExtractor::DescriptorExtractor(GPUFeature2D * gpuFeature2D) :
	descriptorExtractor_(0),
	gpuFeature2D_(gpuFeature2D)
{
	Q_ASSERT(gpuFeature2D_!=0);
}
void DescriptorExtractor::compute(const cv::Mat & image,
		std::vector<cv::KeyPoint> & keypoints,
		cv::Mat & descriptors)
{
	if(descriptorExtractor_)
	{
		descriptorExtractor_->compute(image, keypoints, descriptors);
	}
	else // assume GPU
	{
		gpuFeature2D_->computeDescriptors(image, keypoints, descriptors);
	}
}