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locator.cpp File Reference

#include "common.h"
#include "locator.h"
#include <dirent.h>
#include <stdlib.h>
#include <math.h>
#include <time.h>

Functions
void	getNNinputData (GrayImage &image, int x, int y, double *input_pixels)
bool	training_done (annie::TrainingSet &ts, annie::TwoLayerNetwork &other_net)
void	newTrain (annie::TrainingSet &ts, unsigned int hidden)
void	trainNN (string NonFaceDir, annie::TrainingSet &all, annie::TrainingSet &ts, string fileName, int hidden)
bool	training_set_guess (string FaceDir, string NonFaceDir, string fileName, int num_images)
bool	add_non_training_set (string NonFaceDir, annie::TrainingSet &T)
annie::TrainingSet *	make_face_training_set (string FaceDir, string fileName)
Variables
unsigned int	start_stop [INPUT_HEIGHT *2]

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Function Documentation

bool add_non_training_set (  string    NonFaceDir, annie::TrainingSet &    T )

void getNNinputData (  GrayImage &    image, int    x, int    y, double *    input_pixels )

this is a special function that will do all of the nessisary image preprocessing for the neural network face locator. This is based off of ImageMagick`s histogram equalization code Parameters: image  the image to get this info from x  the x value of the upper left hand corner of the image to be processed y  the y value of the upper left hand corner of the image to be processed input_pixels  a pointer to the array of input values to the neural network, note that this is how values are returned

annie::TrainingSet* make_face_training_set (  string    FaceDir, string    fileName )

the first step in training the network is to compile all of the faces into a training set to train the network with Parameters: FaceDir  a directory containing image files of faces. the faces should be INPUT_WIDTH by INPUT_HEIGHT fileName  the name of the file to save the training set data to Returns: true if no errors were encountered else false

void newTrain (  annie::TrainingSet &    ts, unsigned int    hidden )

bool training_done (  annie::TrainingSet &    ts, annie::TwoLayerNetwork &    other_net )

bool training_set_guess (  string    FaceDir, string    NonFaceDir, string    fileName, int    num_images )

the first step in training the network is to compile all of the images into a training set to train the network with, this is a tool that will guess at a subset of the complete set to start training with Parameters: FaceDir  a directory containing image files of faces. the faces should be INPUT_WIDTH by INPUT_HEIGHT NonFaceDir  the directory containing images with no faces at all in them. fileName  the name of the file to save the training set data to num_images, the  maximum number of images to be added into the training set Returns: true if no errors were encountered else false

void trainNN (  string    NonFaceDir, annie::TrainingSet &    all, annie::TrainingSet &    ts, string    fileName, int    hidden )

train the network in an interesting way

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Variable Documentation

unsigned int start_stop[INPUT_HEIGHT*2]

Initial value: {8,10 ,5,13 ,4,14 ,3,15 ,2,16 ,2,16 ,1,17 ,1,17 ,0,18 ,0,18 ,0,18 ,0,18 ,0,18 ,0,18 ,0,18 ,1,17 ,1,17 ,1,17 ,2,16 ,2,16 ,3,15 ,4,14 ,6,12} this is an array that holds the start and stop values for each line in a face image. as a function looks fo pixles that are part of a face it will only take those that inclusively fall within the numbers that this array holds

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