nice week

features/gradientfeatures/PHOGFeature.cpp~

@@ -1,847 +0,0 @@
-/** 
-* @file PHOGFeature.cpp
-* @brief Implementation of the PHOG-Features and corresponding Kernel as done by Anna Bosch et al.
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-
-#include "PHOGFeature.h"
-
-using namespace std;
-using namespace OBJREC;
-using namespace NICE;
-
-/** protected things*/
-/**
-* @brief Calculates the PHOG-Pyramide for given gradient images (idea of Anna Bosch and Andrew Zisserman)
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-void PHOGFeature::calculate_PHOG_Pyramide(const NICE::Image & gradient_orientations, const NICE::ImageT<float> & gradient_magnitudes, std::vector< std::vector<float> > & PHOG_descriptor)
-{
-	float sum_of_all = 0.0;
-	float sum_of_level = 0.0;
-
-	std::vector<float> one_collecting_vector;
-	one_collecting_vector.clear();
-	std::vector<float> HoG (number_Of_Bins);
-	for (int j = 0; j < gradient_orientations.height(); j++)
-		for (int i = 0; i < gradient_orientations.width(); i++)
-		{
-			int orientation (gradient_orientations(i,j));
-			if (( (orientation<0) || ((uint)orientation>=HoG.size())) && verbose)
-			{
-				cerr << "orientation is " << orientation << " and does not fit to HoG.size(): " << HoG.size() << endl;
-				cerr << "i: " << i << " j: " << j << " gradient_orientations.width() : " <<  gradient_orientations.width() << " gradient_orientations.height() : " << gradient_orientations.height() << endl;
-			}
-			HoG[gradient_orientations(i,j)] += gradient_magnitudes(i,j);
-			sum_of_all += gradient_magnitudes(i,j);
-			sum_of_level += gradient_magnitudes(i,j);
-		}
-		
-	switch(histrogram_concatenation)
-	{
-		case 0:
-		{
-			if (sum_of_level != 0.0)  //normalize the descriptor-entries
-			{
-				for (std::vector<float>::iterator HoG_it = HoG.begin(); HoG_it != HoG.end(); HoG_it++)
-				{
-					*HoG_it /= sum_of_level;
-				}
-			}
-			PHOG_descriptor.push_back(HoG);
-			break;
-		}
-		case 1:
-		{
-			if (sum_of_level != 0.0)  //normalize the descriptor-entries
-			{
-				for (std::vector<float>::iterator HoG_it = HoG.begin(); HoG_it != HoG.end(); HoG_it++)
-				{
-					*HoG_it /= sum_of_level;
-				}
-			}
-			PHOG_descriptor.push_back(HoG);
-			break;
-		}
-		case 2:
-		{
-			one_collecting_vector.insert(one_collecting_vector.begin()+one_collecting_vector.size(), HoG.begin(), HoG.end());
-			break;
-		}
-	}
-	sum_of_all += sum_of_level;
-
-	if (verbose) cerr << "PHOGFeature::calculate_PHOG_Pyramide -- Level 0 calculated, working on finer levels" << endl;
-	if (verbose) cerr << "gradient_orientations.width(): " << gradient_orientations.width() << " gradient_orientations.height(): " << gradient_orientations.height() << endl;
-
-	//further levels
-	for (int level = 1; level < number_of_Levels; level++) 
-	{
-		if (verbose) cerr << "PHOGFeature::calculate_PHOG_Pyramide -- working on level "<< level << endl;
-		if (like_AnnaBosch)
-		{
-			int step_x = (int) floor(gradient_orientations.width() / pow(2,level) );
-			int step_y = (int) floor(gradient_orientations.height() / pow(2,level) );
-
-			vector<float> PHoG_level;
-
-			int run_y = 0;
-			for (int y_counter = 0; y_counter < pow(2.0,level) ; y_counter++) 
-			{
-				int run_x = 0;
-				for (int x_counter = 0; x_counter < pow(2.0,level) ; x_counter++)
-				{
-					vector<float> HoG_local (number_Of_Bins);
-					float sum_of_hog(0.0);
-	
-					//check, wether rectangle lies on the boundary, if so, then correct the max-step
-					int y_max = (run_y + step_y);
-					if (gradient_orientations.height() < y_max)
-						y_max = gradient_orientations.height();
-	
-					int x_max = (run_x + step_x);
-					if (gradient_orientations.width() < x_max)
-						x_max = gradient_orientations.width();
-	
-					for (int j = run_y; j < y_max; j++)
-						for (int i = run_x; i < x_max; i++)
-						{
-							int orientation = 0;
-							try{	orientation = gradient_orientations(i,j);
-							}
-							catch( ... )
-							{
-								cerr << "WARNING: PHOGFeature::calculate_PHOG_Pyramide gradient_orientations(i,j) not possible. (i,j): " << i << " " << j << endl;
-							}
-							float magnitude = 0.0;
-							try{	magnitude = gradient_magnitudes(i,j);
-							}
-							catch( ... )
-							{
-								cerr << "WARNING: PHOGFeature::calculate_PHOG_Pyramide radient_magnitudes(i,j) not possible. (i,j): " << i << " " << j << endl;
-							}
- 							HoG_local[orientation] += magnitude;
-							sum_of_hog += magnitude;
-						}
-
-					sum_of_level += sum_of_hog;
-					
-					switch(histrogram_concatenation)
-					{
-						case 0:
-						{
-							if (sum_of_hog != 0.0)  //normalize the descriptor-entries
-							{
-								for (std::vector<float>::iterator hog_it = HoG_local.begin(); hog_it != HoG_local.end(); hog_it++)
-								{
-									*hog_it /= sum_of_hog;
-								}
-							}
-							PHOG_descriptor.push_back(HoG_local);
-							break;
-						}
-						case 1:
-						{
-							for (std::vector<float>::const_iterator foo = HoG_local.begin(); foo != HoG_local.end(); foo++)
-							{
-								PHoG_level.insert(PHoG_level.begin()+PHoG_level.size(), HoG_local.begin(), HoG_local.end());
-							}
-							break;
-						}
-						case 2:
-						{
-								PHoG_level.insert(PHoG_level.begin()+PHoG_level.size(), HoG_local.begin(), HoG_local.end());
-							break;
-						}
-					}
-	
-					run_x = run_x + step_x;
-				}
-				run_y = run_y + step_y;
-			}
-			
-			sum_of_all += sum_of_level;
-			
-			switch(histrogram_concatenation)
-			{
-				case 0:
-				{
-					break;
-				}
-				case 1:
-				{
-					if (sum_of_level != 0.0)  //normalize the descriptor-entries
-					{
-						for (std::vector<float>::iterator Level_it = PHoG_level.begin(); Level_it != PHoG_level.end(); Level_it++)
-						{
-							*Level_it /= sum_of_level;
-						}
-					}
-					PHOG_descriptor.push_back(PHoG_level);
-					break;
-				}
-				case 2:
-				{
-					one_collecting_vector.insert(one_collecting_vector.begin()+one_collecting_vector.size(), PHoG_level.begin(), PHoG_level.end());
-					break;
-				}
-			}
-		}
-		else //better than anna bosch
-		{
-			int step_x = (int) ceil(gradient_orientations.width() / pow(2.0,level) );
-			int step_y = (int) ceil(gradient_orientations.height() / pow(2.0,level) );
-			if (verbose) cerr << "step_x: " << step_x << " step_y: " << step_y << endl;
-
-			std::vector<float> PHoG_level;
-	
-			int run_y = 0;
-			for (int y_counter = 0; y_counter < pow(2,level) ; y_counter++) 
-			{
-				int run_x = 0;
-				if (verbose) cerr << "run_y: " << run_y << endl;
-				for (int x_counter = 0; x_counter < pow(2,level) ; x_counter++)
-				{
-					if (verbose) cerr << "run_x: " << run_x << endl;
-					float sum_of_hog(0.0);
-					vector<float> HoG_local (number_Of_Bins);
-	
-					//check, wether rectangle lies on the boundary, if so, then correct the max-step
-					int y_max = (run_y + step_y);
-					if (gradient_orientations.height() < y_max)
-					{
-						if (verbose) cerr << "y_max old:: " << y_max << " y_max_new: "<<gradient_orientations.height() << endl;
-						y_max = gradient_orientations.height();
-						
-					}
-	
-					int x_max = (run_x + step_x);
-					if (gradient_orientations.width() < x_max)
-					{
-						if (verbose) cerr << "x_max old:: " << x_max << " x_max_new: "<<gradient_orientations.width() << endl;
-						x_max = gradient_orientations.width();
-						
-					}
-			
-					for (int j = run_y; j < y_max; j++)
-						for (int i = run_x; i < x_max; i++)
-						{
-							int orientation = 0;
-							try{	orientation = gradient_orientations.getPixel(i,j);
-							}
-							catch( ... )
-							{
-								cerr << "WARNING: PHOGFeature::calculate_PHOG_Pyramide gradient_orientations(i,j) not possible. (i,j): " << i << " " << j << endl;
-							}
-							float magnitude = 0.0;
-							try{	magnitude = gradient_magnitudes.getPixel(i,j);
-							}
-							catch( ... )
-							{
-								cerr << "WARNING: PHOGFeature::calculate_PHOG_Pyramide gradient_magnitudes(i,j) not possible. (i,j): " << i << " " << j << endl;
-							}
-							if ( (orientation<0) || ((uint)orientation>=HoG_local.size()))
-							{
-								cerr << "orientation is " << orientation << " and does not fit to HoG_local.size(): " << HoG_local.size() << endl;
-								cerr << "i: " << i << " j: " << j << " gradient_orientations.width() : " <<  gradient_orientations.width() << " gradient_orientations.height() : " << gradient_orientations.height() << endl;
-							}
- 							try{
-								HoG_local[orientation] += magnitude;
-							}
-							catch( ... )
-							{
-								cerr << "WARNING: PHOGFeature::calculate_PHOG_Pyramide HoG_local[orientation] += magnitude not possible. orientation: " << orientation << " magnitude " << magnitude << endl;
-							}
-							sum_of_hog += magnitude;
-						}
-					sum_of_level += sum_of_hog;
-					
-					switch(histrogram_concatenation)
-					{
-						case 0:
-						{
-							if (sum_of_hog != 0.0)  //normalize the descriptor-entries
-							{
-								for (std::vector<float>::iterator hog_it = HoG_local.begin(); hog_it != HoG_local.end(); hog_it++)
-								{
-									*hog_it /= sum_of_hog;
-								}
-							}
-							PHOG_descriptor.push_back(HoG_local);
-							break;
-						}
-						case 1:
-						{
-							for (std::vector<float>::const_iterator foo = HoG_local.begin(); foo != HoG_local.end(); foo++)
-							{
-								PHoG_level.insert(PHoG_level.begin()+PHoG_level.size(), HoG_local.begin(), HoG_local.end());
-							}
-							break;
-						}
-						case 2:
-						{
-								PHoG_level.insert(PHoG_level.begin()+PHoG_level.size(), HoG_local.begin(), HoG_local.end());
-							break;
-						}
-					}
-	
-					run_x = run_x + step_x;
-				}
-				run_y = run_y + step_y;
-			}
-			sum_of_all += sum_of_level;
-			
-			switch(histrogram_concatenation)
-			{
-				case 0:
-				{
-					break;
-				}
-				case 1:
-				{
-					if (sum_of_level != 0.0)  //normalize the descriptor-entries
-					{
-						for (std::vector<float>::iterator Level_it = PHoG_level.begin(); Level_it != PHoG_level.end(); Level_it++)
-						{
-							*Level_it /= sum_of_level;
-						}
-					}
-					PHOG_descriptor.push_back(PHoG_level);
-					break;
-				}
-				case 2:
-				{
-					one_collecting_vector.insert(one_collecting_vector.begin()+one_collecting_vector.size(), PHoG_level.begin(), PHoG_level.end());
-					break;
-				}
-			}
-		}
-	}
-	
-	if (histrogram_concatenation == ALL)
-	{
-		if (sum_of_all != 0.0)  //normalize the descriptor-entries
-		{
-			for (std::vector<float>::iterator it = one_collecting_vector.begin(); it != one_collecting_vector.end(); it++)
-			{
-				*it /= sum_of_all;
-			}
-		}
-		PHOG_descriptor.push_back(one_collecting_vector);
-	}
-}
-
-/**
-* @brief Calculates resulting PHOG-Features for the specified ROI in the given image
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-std::vector< std::vector<float> > PHOGFeature::calculate_PHOG_Features(const NICE::Image & orig_Image, const NICE::Rect & roi)
-{
-	if (like_AnnaBosch) //not supported right now!
-	{
-		std::cerr << "PHOGFeature::calculate_PHOG_Features is not supported right now" << std::endl;
-// 		//Canny Edge Detector
-// 		Image canny_Image;
-// 		canny_Image = (*canny(orig_Image, 10,30) );
-// 
-// 		//gradient-calculation
-// 		GrayImage16s* grad_x_Image= sobelX(canny_Image);
-// 		GrayImage16s* grad_y_Image = sobelY(canny_Image);
-// 		if (verbose)	cerr << "gradient-calculation done" << endl;
-// 
-// 		//gradient-orientation-calculation
-// 		NICE::Image gradient_orientations;
-// 		image_tool.calculateGradientOrientations( *grad_x_Image, *grad_y_Image, number_Of_Bins, gradient_orientations, unsignedBins);
-// 		if (verbose)	cerr << "gradient-orientation-calculation done" << endl;
-// 
-// 		//gradient-magnitude-calculation
-// 		//maybe this is not good - implicit cast from int to float in image structure
-// 		NICE::Image* gradient_magnitudes_int = gradientStrength( (*grad_x_Image), (*grad_y_Image) );
-// 		NICE::ImageT<float> gradient_magnitudes(orig_Image.width(), orig_Image.height());
-// 		for (int y = 0; y < orig_Image.height(); y++)
-// 			for (int x = 0; x < orig_Image.width(); x++)
-// 			{
-// 				gradient_magnitudes.setPixel(x,y,(*gradient_magnitudes_int).getPixel(x,y));
-// 			}
-// 		if (verbose)	cerr << "gradient-magnitude-calculation done" << endl;
-// 		
-// 		NICE::Image go_roi (gradient_orientations.subImage(roi));
-// 		NICE::ImageT<float> gm_roi (gradient_magnitudes.subImage(roi));
-// 
-// 	//pyramide-calculation
-// 
-		std::vector< std::vector<float> > PHOG_pyramide;
-// 		calculate_PHOG_Pyramide(go_roi, gm_roi, PHOG_pyramide);
-// 
-// 		if (verbose) cerr << "Pyramide-calculation done" << endl;
-
-		return PHOG_pyramide;
-
-	}
-	else
-	{
-		//gradient-calculation
-		NICE::ImageT<float> grad_x_Image;
-		NICE::ImageT<float> grad_y_Image;
-		image_tool.calculateGradients(orig_Image, grad_x_Image, grad_y_Image );
-		if (verbose)	cerr << "gradient-calculation done" << endl;
-
-		//gradient-orientation-calculation
-		NICE::Image gradient_orientations;
-		image_tool.calculateGradientOrientations(grad_x_Image, grad_y_Image, number_Of_Bins, gradient_orientations, unsignedBins);
-		if (verbose) 	cerr << "gradient-orientation-calculation done" << endl;
-
-		//gradient-magnitude-calculation
-		NICE::ImageT<float> gradient_magnitudes;
-		image_tool.calculateGradientMagnitudes(grad_x_Image, grad_y_Image, gradient_magnitudes);
-		if (verbose) 	cerr << "gradient-magnitude-calculation done" << endl;
-
-		NICE::Image go_roi (gradient_orientations.subImage(roi));
-		NICE::ImageT<float> gm_roi (gradient_magnitudes.subImage(roi));
-
-	//pyramide-calculation
-
-		std::vector< std::vector<float> > PHOG_pyramide;
-		calculate_PHOG_Pyramide(go_roi, gm_roi, PHOG_pyramide);
-
-		if (verbose) cerr << "Pyramide-calculation done" << endl;
-
-		return PHOG_pyramide;
-	}
-}
-//TODO ebenso für Farbbilder, falls das erwünscht ist. Frau Bosch macht einfach nur eine Grauwertkonvertierunt, also auch nicht so schön, wie Dalal und Triggs.!
-
-
-/** public things*/
-
-/** 
-* @brief Simple Default Constructor 
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-PHOGFeature::PHOGFeature()
-{
-	image_tool = OBJREC::Image_tools();
-	number_Of_Bins = 9;
-	unsignedBins = true;
-	number_of_Levels = 3;
-	like_AnnaBosch = false;
-	distances_only_between_levels = true;
-	histrogram_concatenation = NONE;
-	verbose = false;
-}
-
-/** 
-* @brief Recommended Constructor 
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-PHOGFeature::PHOGFeature( const Config *conf, std::string section)
-{
-	image_tool = OBJREC::Image_tools();
-	number_Of_Bins = conf->gI("PHOGFeature", "number_Of_Bins", 9);
-	unsignedBins = conf->gB("PHOGFeature", "unsignedBins", true);
-	number_of_Levels = conf->gI("PHOGFeature", "number_of_Levels", 3);
-	like_AnnaBosch = conf->gB("PHOGFeature", "like_AnnaBosch", false);
-	distances_only_between_levels = conf->gB("PHOGFeature", "distances_only_between_levels", true);
-	switch(conf->gI("PHOGFeature", "histrogram_concatenation", 0) )
-	{
-		case 0:
-		{histrogram_concatenation = NONE; break;}
-		case 1:
-		{histrogram_concatenation = LEVELWISE; break;}
-		case 2:
-		{histrogram_concatenation = ALL; break;}
-	}
-	verbose = conf->gB("PHOGFeature", "verbose", false);
-}
-
-/** 
-* @brief Simple Destructor 
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-PHOGFeature::~PHOGFeature()
-{
-
-}
-
-
-/** 
-* @brief Creating the PHOG-featureVectores of all trainingexamples
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-// std::vector<std::vector< std::vector<float> > >  PHOGFeature::createAllFeatureVectors(const OBJREC::LabeledSet::Permutation & order)
-// {
-// 
-// 	std::vector<std::vector< std::vector<float> > > PHOG_Features_all_images;
-// 
-// 	ProgressBar pb_createFV ("PHOGFeature::createAllFeatureVectors");
-// 	pb_createFV.show();
-// 
-// 	uint k = 0;
-// 	for ( LabeledSet::Permutation::const_iterator i = order.begin(); i != order.end(); i++,k++  )
-// 	{
-// 		string imgfilename = (*i).second->img();
-// 
-// 		NICE::Image img(imgfilename);
-// 
-// 		NICE::Rect roi = NICE::Rect(0,0,img.width(),img.height());
-// 		vector<vector<float> > PHOG = calculate_PHOG_Features(img, roi);
-// 
-// 		PHOG_Features_all_images.push_back ( PHOG );
-// 
-// 		pb_createFV.update ( order.size() );
-// 	}
-// 
-// 	// hide the last progress bar
-// 	pb_createFV.hide();
-// 
-// 	return PHOG_Features_all_images;
-// }
-
-
-/** 
-* @brief Creating the PHOG-featureVectores of all trainingexamples
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-// std::vector<std::vector< std::vector<float> > >  PHOGFeature::createAllFeatureVectors(const OBJREC::LabeledSet::Permutation & order, std::vector< NICE::Image > & gradient_orientations, std::vector<NICE::ImageT<float> > & gradient_magnitudes)
-// {
-// 
-// 	std::vector<std::vector< std::vector<float> > > PHOG_Features_all_images;
-// 
-// 	cerr << "Calculating gradient orientations." << endl;
-// 	gradient_orientations = calculate_gradient_orientations(order);
-// 	cerr << "Calculating gradient magnitudes." << endl;
-// 	gradient_magnitudes = calculate_gradient_magnitudes(order);
-// 
-// 	ProgressBar pb_quantization ("PHOGFeature::createAllFeatureVectors");
-// 	pb_quantization.show();
-// 
-// 	uint k = 0;
-// 	for ( LabeledSet::Permutation::const_iterator i = order.begin(); i != order.end(); i++,k++  )
-// 	{
-// 		std::string imgfilename = (*i).second->img();
-// 
-// 		NICE::Image img(imgfilename);
-// 
-// 		std::vector<std::vector<float> > PHOG;
-// 		calculate_PHOG_Pyramide(gradient_orientations[k], gradient_magnitudes[k], PHOG);
-// 
-// 		PHOG_Features_all_images.push_back ( PHOG );
-// 
-// 		pb_quantization.update ( order.size() );
-// 	}
-// 
-// 	// hide the last progress bar
-// 	pb_quantization.hide();
-// 
-// 	return PHOG_Features_all_images;
-// }
-
-/** 
-* @brief Creating the PHOG-featureVectores of all trainingexamples
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-// // // std::vector<std::vector< std::vector<float> > >  PHOGFeature::createAllFeatureVectors(const OBJREC::LabeledSet::Permutation & order, const std::vector<int> & trainSelection)
-// // // {
-// // // 
-// // // 	std::vector<std::vector< std::vector<float> > > PHOG_Features_all_images;
-// // // 
-// // // 	ProgressBar pb_quantization ("PHOGFeature::createAllFeatureVectors");
-// // // 	pb_quantization.show();
-// // // 
-// // // 	uint k = 0;
-// // // 	for ( std::vector<int>::const_iterator i = trainSelection.begin(); i != trainSelection.end(); i++,k++ )
-// // // 	{
-// // // 		if (verbose) cerr << " Image number " << *i << " will be treated now" << endl;
-// // // 		string imgfilename = order[*i].second->img();
-// // // 
-// // // 		NICE::Image img(imgfilename);
-// // // 
-// // // 		NICE::Rect roi = NICE::Rect(0,0,img.width(),img.height());
-// // // 		vector<vector<float> > PHOG = calculate_PHOG_Features(img, roi);
-// // // 
-// // // 		PHOG_Features_all_images.push_back ( PHOG );
-// // // 
-// // // 		pb_quantization.update ( trainSelection.size() );
-// // // 	}
-// // // 
-// // // 	// hide the last progress bar
-// // // 	pb_quantization.hide();
-// // // 
-// // // 	return PHOG_Features_all_images;
-// // // }
-// // 
-// // 
-// // 
-/** 
-* @brief Creating the PHOG-featureVectore for one trainingexample
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-std::vector<std::vector<float> > PHOGFeature::createOneFeatureVector(const std::string & imgfilename, const NICE::Rect & ROI)
-{
-	NICE::Image img(imgfilename);
-
-	std::vector<std::vector<float> > PHOG (calculate_PHOG_Features(img, ROI));
-
-	return PHOG;
-}
-
-/** 
-* @brief Creating the PHOG-featureVectore for one trainingexample
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-std::vector<std::vector<float> > PHOGFeature::createOneFeatureVector(const std::string & imgfilename)
-{
-	NICE::Image img(imgfilename);
-	NICE::Rect ROI(0,0,img.width(), img.height());
-
-	std::vector<std::vector<float> > PHOG (calculate_PHOG_Features(img, ROI));
-
-	return PHOG;
-}
-
-/** 
-* @brief Creating the PHOG-featureVectore for one trainingexample
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-std::vector<std::vector<float> > PHOGFeature::createOneFeatureVector(const NICE::Image img, const NICE::Rect & ROI)
-{
-	std::vector<std::vector<float> > PHOG (calculate_PHOG_Features(img, ROI));
-
-	return PHOG;
-}
-
-/** 
-* @brief Creating the PHOG-featureVectore for one trainingexample
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-std::vector<std::vector<float> > PHOGFeature::createOneFeatureVector(const NICE::Image img)
-{
-	NICE::Rect ROI(0,0,img.width(), img.height());
-	std::vector<std::vector<float> > PHOG (calculate_PHOG_Features(img, ROI));
-
-	return PHOG;
-}
-
-/** 
-* @brief computes the featurevector for the given image, which is already converted to a gradient-image, just considering features in the specified ROI
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-std::vector< std::vector<float> > PHOGFeature::createOneFeatureVectorDirect(NICE::Image & gradient_orientations, NICE::ImageT<float> & gradient_magnitudes, const NICE::Rect & ROI)
-{
-	NICE::Image ROI_go (gradient_orientations.subImage(ROI));
-	NICE::ImageT<float> ROI_gm (gradient_magnitudes.subImage(ROI));
-
-	std::vector< std::vector<float> > PHOG_pyramide;
-	calculate_PHOG_Pyramide(ROI_go, ROI_gm, PHOG_pyramide);
-
-	return PHOG_pyramide;
-}
-
-/** 
-* @brief computes the featurevector for the given image, which is already converted to a gradient-image, considering the whole image
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-std::vector< std::vector<float> > PHOGFeature::createOneFeatureVectorDirect(NICE::Image & gradient_orientations, NICE::ImageT<float> & gradient_magnitudes)
-{
-	NICE::Image ROI_go (gradient_orientations);
-	NICE::ImageT<float> ROI_gm (gradient_magnitudes);
-
-	std::vector< std::vector<float> > PHOG_pyramide;
-	calculate_PHOG_Pyramide(ROI_go, ROI_gm, PHOG_pyramide );
-
-	return PHOG_pyramide;
-}
-// // 
-// // /** 
-// // * @brief computes the gradient-orientation-images of all training-images
-// // * @author Alexander Lütz
-// // * @date 15/11/2011
-// // */
-// // std::vector< NICE::Image> PHOGFeature::calculate_gradient_orientations(const OBJREC::LabeledSet::Permutation & order)
-// // {
-// // 	std::vector< NICE::Image> gradient_orientations;
-// // 
-// // 	for(OBJREC::LabeledSet::Permutation::const_iterator i = order.begin(); i != order.end(); i++)
-// // 	{
-// // 		string filename = (*i).second->img();
-// // 		NICE::Image img (filename);
-// // 		//gradient-calculation
-// // 		NICE::ImageT<float> grad_x_Image;
-// // 		NICE::ImageT<float> grad_y_Image;
-// // 		image_tool.calculateGradients(img, grad_x_Image, grad_y_Image );
-// // 	
-// // 		//gradient-orientation-calculation
-// // 		NICE::Image gradient_orientation_image;
-// // 		image_tool.calculateGradientOrientations(grad_x_Image, grad_y_Image, number_Of_Bins, gradient_orientation_image, unsignedBins);
-// // 
-// // 		gradient_orientations.push_back(gradient_orientation_image);
-// // 	}
-// // 
-// // 	return gradient_orientations;
-// // }
-// 
-// /** 
-// * @brief computes the gradient-magnitudes-images of all training-images
-// * @author Alexander Lütz
-// * @date 15/11/2011
-// */
-// std::vector< NICE::ImageT<float> > PHOGFeature::calculate_gradient_magnitudes(const OBJREC::LabeledSet::Permutation & order)
-// {
-// 	std::vector< NICE::ImageT<float> > gradient_magnitudes;
-// 
-// 	for(OBJREC::LabeledSet::Permutation::const_iterator i = order.begin(); i != order.end(); i++)
-// 	{
-// 		string filename = (*i).second->img();
-// 		Image img (filename);
-// 		//gradient-calculation
-// 		NICE::ImageT<float> grad_x_Image;
-// 		NICE::ImageT<float> grad_y_Image;
-// 		image_tool.calculateGradients(img, grad_x_Image, grad_y_Image );
-// 	
-// 		//gradient-orientation-calculation
-// 		NICE::ImageT<float> gradient_magnitude_image;
-// 		image_tool.calculateGradientMagnitudes(grad_x_Image, grad_y_Image, gradient_magnitude_image);
-// 
-// 		gradient_magnitudes.push_back(gradient_magnitude_image);
-// 	}
-// 
-// 	return gradient_magnitudes;
-// }
-
-/** 
-* @brief computes the gradient-orientation-images of all training-images
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-NICE::Image PHOGFeature::calculate_gradient_orientations(const std::string & imgfilenam)
-{
-	NICE::Image gradient_orientations;
-
-	NICE::Image img (imgfilenam);
-	//gradient-calculation
-	NICE::ImageT<float> grad_x_Image;
-	NICE::ImageT<float> grad_y_Image;
-	image_tool.calculateGradients(img, grad_x_Image, grad_y_Image );
-
-	//gradient-orientation-calculation
-	NICE::Image gradient_orientation_image;
-	image_tool.calculateGradientOrientations(grad_x_Image, grad_y_Image, number_Of_Bins, gradient_orientation_image, unsignedBins);
-
-	return gradient_orientations;
-}
-
-/** 
-* @brief computes the gradient-magnitudes-images of all training-images
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-NICE::ImageT<float> PHOGFeature::calculate_gradient_magnitudes(const std::string & imgfilename)
-{
-	NICE::ImageT<float> gradient_magnitudes;
-
-	Image img (imgfilename);
-	//gradient-calculation
-	NICE::ImageT<float> grad_x_Image;
-	NICE::ImageT<float> grad_y_Image;
-	image_tool.calculateGradients(img, grad_x_Image, grad_y_Image );
-
-	//gradient-orientation-calculation
-	NICE::ImageT<float> gradient_magnitude_image;
-	image_tool.calculateGradientMagnitudes(grad_x_Image, grad_y_Image, gradient_magnitude_image);
-
-	return gradient_magnitudes;
-}
-
-/** 
-* @brief Compute the resulting kernel measuring the distance between the given feature-vectores
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-void PHOGFeature::calculate_Kernel_from_Features(const std::vector<std::vector< std::vector<float> > > & PHoG_Features, NICE::Matrix & PHoG_Kernel){
-
-// 	ProgressBar pb_kernelcalc ("PHOGFeature::Kernel Calculation");
-// 	pb_kernelcalc.show();
-	PHoG_Kernel = NICE::Matrix(PHoG_Features.size(), PHoG_Features.size(), 0.0);
-	uint ik = 0;
-	for ( std::vector< std::vector < std::vector<float> > >::const_iterator i = PHoG_Features.begin();i != PHoG_Features.end(); i++,ik++ )
-	{
-		uint jk = ik;
-		for ( std::vector< std::vector< std::vector<float> > >::const_iterator j = i; 
-			j != PHoG_Features.end(); j++,jk++ )
-		{
-			double kernelValue (measureDistance(*i,*j));
-		
-			PHoG_Kernel(ik,jk) = kernelValue;
-			PHoG_Kernel(jk,ik) = kernelValue;
-		}
-// 		pb_kernelcalc.update ( PHoG_Features.size() );
-	}
-}
-
-/** 
-* @brief function which computes the exp^(-Chi^2)-kernel of two PHOG-feature-vectores a and b
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-double PHOGFeature::measureDistance ( const std::vector<std::vector<float> > & a, const std::vector<std::vector<float> > & b )
-{
-	double expChi_value = 0.0;
-
-	if (a.size() != b.size() ) {
-		cerr << "a.size(): " << a.size() << " and b.size(): " << b.size() << endl;
-		fthrow(IOException, "Sizes of PHOG-Feature-vectores do not fit!");
-	}
-
-	for (uint i = 0; i < a.size(); i++)  //run over every HoG-Level 
-	{
-		std::vector<float> a_intern = a[i];
-		std::vector<float> b_intern = b[i];
-
-		double chi_value = 0.0;
-
-		if (a_intern.size() != b_intern.size() )  {
-			cerr << "a_intern.size(): " << a_intern.size() << " and b_intern.size(): " << b_intern.size() << endl;
-			fthrow(IOException, "Sizes of PHOG-Feature-vectores do not fit!");
-		}
-
-		for (uint j = 0; j < a_intern.size(); j++) //run over every HoG-entry of this level
-		{
-			float u = a_intern[j];
-			float v = b_intern[j];
-			float s = ( u + v );
-			if ( fabs(s) < 10e-6 ) continue;
-			float d = u-v;
-			chi_value += d*d / s;
-		}
-
-		chi_value *= 0.5;
-		expChi_value += exp(-chi_value);
-	}
-	expChi_value /= a.size(); //normalize to be in between zero and one
-
-	return expChi_value;
-}
-
-/** 
-* @brief Simply set the verbose-flag
-* @author Alexander Lütz
-* @date 15/11/2011
-*/
-void PHOGFeature::set_verbose(const bool & new_verbose){
-	verbose = new_verbose;
-}

features/gradientfeatures/PHOGFeature.h~

@@ -1,89 +0,0 @@
-/** 
-* @file PHOGFeature.h
-* @author Alexander Lütz
-* @date 15/11/2011
-
-*/
-#ifndef _NICE_OBJREC_PHOGFEATUREINCLUDE
-#define _NICE_OBJREC_PHOGFEATUREINCLUDE
-
-#include "vislearning/baselib/Config.h"
-// #include "vislearning/cbaselib/MultiDataset.h"
-#include "Image_tools.h"
-
-namespace OBJREC {
-  
-/** @class PHOGFeature
- * Implementation of the PHOG-Features and corresponding Kernel as done by Anna Bosch et al.
- *
- * @author Alexander Lütz
- */
-
-
-class PHOGFeature
-{
-
-	public:
-		enum Histrogram_concatenation{NONE=0, LEVELWISE=1, ALL=2};
-
-	protected:
-		
-	Image_tools image_tool;
-	int number_Of_Bins;
-	bool unsignedBins;
-	int number_of_Levels;
-	bool like_AnnaBosch;
-	bool distances_only_between_levels;
-	Histrogram_concatenation histrogram_concatenation;
-	bool verbose;
-
-	/** Calculates the PHOG-Pyramide for given gradient images (idea of Anna Bosch and Andrew Zisserman)*/
-	void calculate_PHOG_Pyramide(const NICE::Image & gradient_orientations, const NICE::ImageT<float> & gradient_magnitudes,std::vector< std::vector<float> > & PHOG_descriptor);
-
-	/** Calculates resulting PHOG-Features for the specified ROI in the given image*/
-	std::vector< std::vector<float> > calculate_PHOG_Features(const NICE::Image & orig_Image, const NICE::Rect & roi);
-
-    public:
-		PHOGFeature();
-
-		/** recommended constructor */
-		PHOGFeature( const OBJREC::Config *conf, string section = "PHOGFeature");
-
-		/** simple destructor */
-		virtual ~PHOGFeature();
-
-//  		std::vector<std::vector< std::vector<float> > > createAllFeatureVectors(const OBJREC::LabeledSet::Permutation & order);
-// 
-// 		std::vector<std::vector< std::vector<float> > > createAllFeatureVectors(const OBJREC::LabeledSet::Permutation & order, std::vector< NICE::Image > & gradient_orientations, std::vector< NICE::ImageT<float> > & gradient_magnitudes);
-// 
-// 		std::vector<std::vector< std::vector<float> > > createAllFeatureVectors(const OBJREC::LabeledSet::Permutation & order, const std::vector<int> & trainSelection);
-
-
-		std::vector< std::vector<float> > createOneFeatureVector(const std::string & imgfilename, const NICE::Rect & ROI);
-		std::vector< std::vector<float> > createOneFeatureVector(const NICE::Image img, const NICE::Rect & ROI);
-		std::vector< std::vector<float> > createOneFeatureVector(const std::string & imgfilename);
-		std::vector< std::vector<float> > createOneFeatureVector(const NICE::Image img);
-
-		/** computes the featurevector for the given image, which is already converted to a gradient-image*/
-		std::vector< std::vector<float> > createOneFeatureVectorDirect(NICE::Image & gradient_orientations, NICE::ImageT<float> & gradient_magnitudes, const NICE::Rect & ROI);
-		std::vector< std::vector<float> > createOneFeatureVectorDirect(NICE::Image & gradient_orientations, NICE::ImageT<float> & gradient_magnitudes);
-
-// 		std::vector< NICE::Image> calculate_gradient_orientations(const OBJREC::LabeledSet::Permutation & order);
-// 		std::vector< NICE::ImageT<float> > calculate_gradient_magnitudes(const OBJREC::LabeledSet::Permutation &
-		NICE::Image calculate_gradient_orientations(const std::string & imgfilename);
-		NICE::ImageT<float> calculate_gradient_magnitudes(const std::string & imgfilename);
-
-		/**Compute the resulting kernel measuring the distance between the given feature-vectores*/
-		void calculate_Kernel_from_Features(const std::vector<std::vector< std::vector<float> > > & PHoG_Features, NICE::Matrix & PHoG_Kernel);
-
-		virtual double measureDistance ( const std::vector< std::vector<float> > & a, const std::vector< std::vector<float> > & b  );
-
-		virtual void sayYourName() {std::cerr << "I'm the PHOG-Feature." << std::endl;};
-
-		void set_verbose(const bool & new_verbose);
-		void set_histrogram_concatenation(const Histrogram_concatenation & _histrogram_concatenation){histrogram_concatenation = _histrogram_concatenation; std::cerr << "histrogram_concatenation: " << histrogram_concatenation << endl;};
-};
-
-}
-
-#endif

features/gradientfeatures/progs/testPHOGFeatures.cpp~

@@ -1,82 +0,0 @@
-#include <iostream>
-#include "vislearning/baselib/Config.h"
-#include "vislearning/features/gradientfeatures/PHOGFeature.h"
-
-using namespace std;
-using namespace NICE;
-using namespace OBJREC;
-
-int main(int argc, char **argv)
-{	
-	Config *conf;
-	std::string imgfilename ("/progs/square_black.jpg");
-	if(argc < 1)
-	{
-		std::cerr << "No config file given, use default config and ./progs/square_black.jpg instaed" << std::endl;
-		conf = new Config();
-		
-		char path_c[512];
-		getcwd(path_c, 512);
-
-		if (path_c == NULL)
-		{ 
-			std::cerr << "default image is not readable. Aborting." << std::endl; 
-			return -1 ;
-		}
-		std::string path(path_c);
-		imgfilename = path + imgfilename;
-	}
-	else
-	{
-		conf = new Config( argc, argv );
-
-		imgfilename = conf->gS("main", "imgfilename", "");
-		if (imgfilename.compare("") == 0)
-		{
-			std::cerr << "No input image given. Aborting!" << std::endl;
-			return -1;
-		}
-	}
-
-	PHOGFeature PHOG(conf);
-	
-	PHOG.sayYourName();
-	
-	std::cerr << "Without concatenating any histogram resulting in \sum_{i=0}{level} 4^i histograms." << std::endl;
-	PHOG.set_histrogram_concatenation(OBJREC::PHOGFeature::NONE);
-	std::vector<std::vector<float> > resulting_feature = PHOG.createOneFeatureVector(imgfilename);
-	for (std::vector<std::vector<float> >::const_iterator i = resulting_feature.begin(); i != resulting_feature.end(); i++)
-	{
-		for (std::vector<float>::const_iterator j = (*i).begin(); j != (*i).end(); j++)
-		{
-			std::cerr << *j << " ";
-		}
-		std::cerr << std::endl << std::endl;
-	}
-	
-	std::cerr << "Concatenating histograms LEVELWISE resulting in #level histograms." << std::endl;
-	PHOG.set_histrogram_concatenation(OBJREC::PHOGFeature::LEVELWISE);
-	resulting_feature = PHOG.createOneFeatureVector(imgfilename);
-	for (std::vector<std::vector<float> >::const_iterator i = resulting_feature.begin(); i != resulting_feature.end(); i++)
-	{
-		for (std::vector<float>::const_iterator j = (*i).begin(); j != (*i).end(); j++)
-		{
-			std::cerr << *j << " ";
-		}
-		std::cerr << std::endl << std::endl;
-	}
-	
-	std::cerr << "Concatenating ALL histograms resulting in 1 final histogram." << std::endl;
-	PHOG.set_histrogram_concatenation(OBJREC::PHOGFeature::ALL);
-	resulting_feature = PHOG.createOneFeatureVector(imgfilename);
-	for (std::vector<std::vector<float> >::const_iterator i = resulting_feature.begin(); i != resulting_feature.end(); i++)
-	{
-		for (std::vector<float>::const_iterator j = (*i).begin(); j != (*i).end(); j++)
-		{
-			std::cerr << *j << " ";
-		}
-		std::cerr << std::endl << std::endl;
-	}
-
-	return 0;
-}