train-faceParts.C File Reference

#include "Channels/OrientationChannel.H"
#include "Component/ModelManager.H"
#include "GUI/XWinManaged.H"
#include "Image/CutPaste.H"
#include "Image/DrawOps.H"
#include "Image/ImageSet.H"
#include "Image/MathOps.H"
#include "Image/PyramidOps.H"
#include "Image/ShapeOps.H"
#include "Image/Transforms.H"
#include "Neuro/StdBrain.H"
#include "Neuro/VisualCortex.H"
#include "Raster/Raster.H"
#include "Gist/FFN.H"
#include "Gist/ModelFace.H"

Include dependency graph for train-faceParts.C:

Go to the source code of this file.

Defines
#define	LEARN_RATE   0.5
#define	TRAIN_START_INDEX   277
#define	NUM_TRAIN_SAMPLE   200
#define	TEST_START_INDEX   234
#define	NUM_TEST_SAMPLE   100
Functions
Image< float >	getPartImage (char *iName, Rectangle pr)
Image< float >	getPartImage (Image< float > img, Rectangle pr)
Rectangle	getPartRect (char *iName, char *dName, FacePart part, int opp)
Rectangle	getPartRect (Image< float > img, char *dName, FacePart part, int opp)
void	getFeature (Rectangle r, FacePart part, Image< double > features)
void	getEyeFeature (Rectangle r, Image< double > features)
void	getNoseFeature (Rectangle r, Image< double > features)
void	getMouthFeature (Rectangle r, Image< double > features)
void	train (FeedForwardNetwork *ffn, FacePart part, nub::soft_ref< StdBrain > brain)
void	fillEyeData (int start, std::vector< Image< double > > pData, std::vector< Image< double > >nData, int *pCt, int *nCt)
void	fillNoseData (int start, std::vector< Image< double > > pData, std::vector< Image< double > > nData, int *pCt, int *nCt)
void	fillMouthData (int start, std::vector< Image< double > > pData, std::vector< Image< double > > nData, int *pCt, int *nCt)
bool	within (Rectangle r, int x, int y)
void	printRegion (Image< float > img, int sX, int eX, int dX, int sY, int eY, int dY)
int	main (const int argc, const char **argv)
Variables
CloseButtonListener	wList
XWinManaged *	imgWin
Image< byte >	targetmask
nub::soft_ref< OrientationChannel >	oriChan
Image< float >	currImg
ImageSet< float >	currGaPyr [NUM_DIR]
XWinManaged *	iWin
XWinManaged *	gaWin [NUM_DIR][3]
int	start_win = 1

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Detailed Description

testing Feed Forward Network class for use to train any mapping

Definition in file train-faceParts.C.

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Define Documentation

#define LEARN_RATE   0.5

This class test implementation a simple feedforward network with backpropagation.

Definition at line 61 of file train-faceParts.C.