task2.cpp File Reference

#include <string>
#include <vector>
#include <fstream>
#include <cassert>
#include <iostream>
#include <cmath>
#include <limits>
#include "classifier.h"
#include "EasyBMP.h"
#include "linear.h"
#include "argvparser.h"
#include "Usable.h"
#include "timer.h"

Include dependency graph for task2.cpp:

Typedefs
typedef vector< pair< BMP *, int > >	TDataSet
typedef vector< pair< string, int > >	TFileList
typedef vector< pair< vector< float >, int > >	TFeatures

Functions
void	LoadFileList (const string &data_file, TFileList *file_list)
void	LoadImages (const TFileList &file_list, TDataSet *data_set)
void	SavePredictions (const TFileList &file_list, const TLabels &labels, const string &prediction_file)
std::vector< double >	calcHistogramHog (const Matrix< double > &square, const Matrix< double > &abs, const Matrix< double > &angles)
	assume same-sized matrixes as params
void	normaliseHist (vector< double > &hist)
	normalize histogram of dubles
std::vector< float >	calculateHog (BMP &img)
void	ExtractFeatures (const TDataSet &data_set, TFeatures *features)
void	ClearDataset (TDataSet *data_set)
void	TrainClassifier (const string &data_file, const string &model_file)
void	PredictData (const string &data_file, const string &model_file, const string &prediction_file)
int	main (int argc, char **argv)

Variables
constexpr uint8_t	N_SQUARES_PER_LINE = 8
	source image will be splited to thet number of squares
constexpr uint8_t	HIST_SZ = 8
	size of histogram (number of sections in 2pi interval)

Detailed Description

Author

Mikhail Agranovskiy, 321, cs msu

Function Documentation

std::vector<float> calculateHog

(

BMP &

img

)

Calculate HOG descriptor for source image.

SSE intrinsics are used in implementation.

Parameters

img	source image

Returns

HOG descriptor

gradients absolute values

gradients directions

void ExtractFeatures	(	const TDataSet &	data_set,
		TFeatures *	features
	)

Extract features from dataset.

Parameters

data_set	vector of pairs <image, lable>
features	vector of gistograms and lables for images from data_set. The main aim of the function is to construct that vector.