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Haar_Feature_Trainning.cpp
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//
// Haar_Feature_Trainning.cpp
// 基于AdaBoost算法的人脸检测
//
// Created by 唧唧歪歪 on 15/2/27.
// Copyright (c) 2015年 唧唧歪歪. All rights reserved.
//
#include "Haar_Feature_Trainning.h"
//训练弱分类器函数；
void Haar_Feature_Trainning::Trainning(Haar_Feature haar,string table_name,int t)
{
//所有特征值已经成功载入；
/*
//载入所有Haar特征下的Haar值；
if(t==0)
{
Get_All(haar, table_name);
}
*/
//创建连接；
MYSQL mycon;
mysql_init(&mycon);
mysql_real_connect(&mycon, "localhost", "root", "", "adaboost", 3306, NULL, 0);
string sql;//SQL语句；
MYSQL_RES *result=NULL;
sql="select * from "+table_name;
mysql_real_query(&mycon, sql.c_str(), sql.length());
result=mysql_store_result(&mycon);
int rowcount=(int)mysql_num_rows(result);
int i;//临时变量；
double min_wrong_rate=50000.000;//作为最小的误差率；
for(i=0;i<rowcount;i++)
{
int H;//弱预测的值；
MYSQL_ROW row=mysql_fetch_row(result);
Weak_Classifier w_c;//临时弱分类器变量；
w_c.threshold=atoi(row[1]);
w_c.haar=haar;
w_c.point1.x_axis=atoi(row[3]);
w_c.point1.y_axis=atoi(row[4]);
w_c.point2.x_axis=atoi(row[5]);
w_c.point2.y_axis=atoi(row[6]);
int num;
//使用p=1作为判断不等式方向的值；
double wrong_rate1=0.0000;//P＝1时，所有特征对应错误率；
for(num=0;num<P_Sample.size();num++)
{
H=Weak_judge(w_c, 1, num, 1);
wrong_rate1+=P_Sample[num].weight*abs(H-1);
}
for(num=0;num<M_Sample.size();num++)
{
H=Weak_judge(w_c, 1, num, 0);
wrong_rate1+=M_Sample[num].weight*H;
}
//使用p=-1作为判断不等式方向的值；
double wrong_rate2=0.0000;//P=0时，所有特征对应错误率；
for(num=0;num<P_Sample.size();num++)
{
H=Weak_judge(w_c,-1, num, 1);
wrong_rate2+=P_Sample[num].weight*abs(H-1);
}
for(num=0;num<M_Sample.size();num++)
{
H=Weak_judge(w_c, -1, num, 0);
wrong_rate2+=M_Sample[num].weight*H;
}
//求解出最小的弱分类器；
if(wrong_rate1<=wrong_rate2)
{
w_c.p=1;//弱分类器不等式方向；
w_c.rate=wrong_rate1;//弱分类器误差率；
}
else
{
w_c.p=-1;
w_c.rate=wrong_rate2;
}
//初始权重；
w_c.weight=0.0000;//弱分类器的权重；
if(w_c.rate<min_wrong_rate)
{
min_wrong_rate=w_c.rate;
w=w_c;
}
}
mysql_close(&mycon);
}
//获取当前特征对应的所有Haar特征值；
void Haar_Feature_Trainning::Get_All(Haar_Feature haar,string table_name)
{
MYSQL mycon;
mysql_init(&mycon);
mysql_real_connect(&mycon, "localhost", "root", "", "adaboost", 3306, NULL, 0);
int num;//临时变量；
int id=1;//纪录特征值的ID；
for(num=0;num<P_Sample.size();num++)
{
int width=P_Sample[num].image.rows-1;
int length=P_Sample[num].image.cols-1;
int i,j;//临时变量；
for(i=1;i<width-haar.s;i++)
{
for(j=1;j<length-haar.t;j++)
{
int w=P_Sample[num].image.rows-i;
w=Low_Integral_Function(w,haar.s);
int l=P_Sample[num].image.cols-j;
l=Low_Integral_Function(l,haar.t);
int x1,y1;
x1=i;
y1=j;
Coordinate A_Point;
A_Point.x_axis=x1;
A_Point.y_axis=y1;
int m,n;//临时变量；
for(m=2;m<=w;m++)
{
int x2,y2;
x2=x1+m*haar.s;
for(n=2;n<=l;n++)
{
y2=y1+n*haar.t;
Coordinate D_Point;
D_Point.x_axis=x2;
D_Point.y_axis=y2;
int integral=get_haar1(haar, A_Point, D_Point, num);
string sql;
sql="insert into "+table_name+" values (";
sql+=Convert(id)+",";
sql+=Convert(integral)+",";
sql+=Convert(1)+",";
sql+=Convert(A_Point.x_axis)+",";
sql+=Convert(A_Point.y_axis)+",";
sql+=Convert(D_Point.x_axis)+",";
sql+=Convert(D_Point.y_axis)+")";
id++;
mysql_real_query(&mycon,sql.c_str(),sql.length());
}
}
}
}
}
for(num=0;num<M_Sample.size();num++)
{
int width=M_Sample[num].image.rows-1;
int length=M_Sample[num].image.cols-1;
int i,j;//临时变量；
for(i=1;i<width-haar.s;i++)
{
for(j=1;j<length-haar.t;j++)
{
int w=M_Sample[num].image.rows-i;
w=Low_Integral_Function(w,haar.s);
int l=M_Sample[num].image.cols-j;
l=Low_Integral_Function(l,haar.t);
int x1=i;
int y1=j;
Coordinate A_Point;
A_Point.x_axis=x1;
A_Point.y_axis=y1;
int m,n;//临时变量；
for(m=2;m<=w;m++)
{
int x2=x1+m*haar.s;
for(n=2;n<=l;n++)
{
int y2=y1+n*haar.t;
Coordinate D_Point;
D_Point.x_axis=x2;
D_Point.y_axis=y2;
int integral=get_haar2(haar,A_Point,D_Point,num);
string sql;
sql="insert into "+table_name+" values (";
sql+=Convert(id)+",";
sql+=Convert(integral)+",";
sql+=Convert(0)+",";
sql+=Convert(A_Point.x_axis)+",";
sql+=Convert(A_Point.y_axis)+",";
sql+=Convert(D_Point.x_axis)+",";
sql+=Convert(D_Point.y_axis)+")";
id++;
mysql_real_query(&mycon,sql.c_str(),sql.length());
}
}
}
}
}
mysql_close(&mycon);
//mysql_query(&mycon,"COMMIT");//执行事务;
}
//使用弱分类器判断当前样本的正负类;
int Haar_Feature_Trainning::Weak_judge(Weak_Classifier w_c,int p,int num,int type)
{
int integral;//当前样本的特征值；
if(type==1)
{
integral=get_haar1(w_c.haar, w_c.point1, w_c.point2, num);
}
else
{
integral=get_haar2(w_c.haar, w_c.point1, w_c.point2, num);
}
int h;//当前样本的种类；
if(p*integral<p*w_c.threshold)
{
h=1;
}
else
{
h=0;
}
return h;
}
//计算正类样本特征值；
int Haar_Feature_Trainning::get_haar1(Haar_Feature haar, Coordinate A_Point, Coordinate D_Point, int num)
{
Coordinate B_Point,C_Point;
int W_Z=0,B_Z=0;
int integral=0;
B_Point.x_axis=A_Point.x_axis;
B_Point.y_axis=D_Point.y_axis;
C_Point.x_axis=D_Point.x_axis;
C_Point.y_axis=A_Point.y_axis;
switch(haar.kind)
{
case 1:
{
Coordinate C1,C2;
C1.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C1.y_axis=A_Point.y_axis;
C2.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C2.y_axis=D_Point.y_axis;
W_Z=P_Sample[num].integral_image[C2.x_axis][C2.y_axis]+P_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-P_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-P_Sample[num].integral_image[C1.x_axis][C1.y_axis];
B_Z=P_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[C2.x_axis][C2.y_axis]-P_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis];
};break;
case 2:
{
Coordinate C1,C2;
C1.x_axis=A_Point.x_axis;
C1.y_axis=(B_Point.y_axis-A_Point.y_axis)/haar.t+A_Point.y_axis;
C2.x_axis=C_Point.x_axis;
C2.y_axis=(D_Point.y_axis-C_Point.y_axis)/haar.t+C_Point.y_axis;
W_Z=P_Sample[num].integral_image[C2.x_axis][C2.y_axis]+P_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis];
B_Z=P_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-P_Sample[num].integral_image[C2.x_axis][C2.y_axis];
};break;
case 3:
{
Coordinate C1,C2,C3,C4;
C1.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C1.y_axis=A_Point.y_axis;
C2.x_axis=(D_Point.x_axis-B_Point.x_axis)/haar.s+B_Point.x_axis;
C2.y_axis=B_Point.y_axis;
C3.x_axis=(C_Point.x_axis-A_Point.x_axis)*(haar.s-1)/haar.s+A_Point.x_axis;
C3.y_axis=A_Point.y_axis;
C4.x_axis=(D_Point.x_axis-B_Point.x_axis)*(haar.s-1)/haar.s+B_Point.x_axis;
C4.y_axis=B_Point.y_axis;
W_Z=P_Sample[num].integral_image[C2.x_axis][C2.y_axis]+P_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]+P_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+P_Sample[num].integral_image[C3.x_axis][C3.y_axis]-P_Sample[num].integral_image[C4.x_axis][C4.y_axis]-P_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis];
B_Z=P_Sample[num].integral_image[C4.x_axis][C4.y_axis]+P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[C2.x_axis][C2.y_axis]-P_Sample[num].integral_image[C4.x_axis][C4.y_axis];
B_Z=B_Z*2;
};break;
case 4:
{
Coordinate C1,C2,C3,C4;
C1.x_axis=A_Point.x_axis;
C1.y_axis=(B_Point.y_axis-A_Point.y_axis)/haar.t+A_Point.y_axis;
C2.x_axis=A_Point.x_axis;
C2.y_axis=(B_Point.y_axis-A_Point.y_axis)*(haar.t-1)/haar.t+A_Point.y_axis;
C3.x_axis=C_Point.x_axis;
C3.y_axis=(D_Point.x_axis-C_Point.x_axis)/haar.t+C_Point.x_axis;
C4.x_axis=C_Point.x_axis;
C4.y_axis=(D_Point.y_axis-C_Point.y_axis)*(haar.t-1)/haar.t+C_Point.y_axis;
W_Z=P_Sample[num].integral_image[C3.x_axis][C3.y_axis]+P_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis]+P_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+P_Sample[num].integral_image[C2.x_axis][C2.y_axis]-P_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-P_Sample[num].integral_image[C4.x_axis][C4.y_axis];
B_Z=P_Sample[num].integral_image[C4.x_axis][C4.y_axis]+P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[C2.x_axis][C2.y_axis]-P_Sample[num].integral_image[C3.x_axis][C3.y_axis];
B_Z=B_Z*2;
};break;
case 5:
{
Coordinate C1,C2,C3,C4,C5;
C1.x_axis=A_Point.x_axis;
C1.y_axis=(B_Point.y_axis-A_Point.y_axis)/haar.t+A_Point.y_axis;
C2.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C2.y_axis=A_Point.y_axis;
C3.x_axis=C2.x_axis;
C3.y_axis=C1.y_axis;
C4.x_axis=C2.x_axis;
C4.y_axis=B_Point.y_axis;
C5.x_axis=C_Point.x_axis;
C5.y_axis=C1.y_axis;
W_Z=P_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+P_Sample[num].integral_image[C3.x_axis][C3.y_axis]-P_Sample[num].integral_image[C4.x_axis][C4.y_axis]-P_Sample[num].integral_image[C5.x_axis][C5.y_axis]+P_Sample[num].integral_image[C3.x_axis][C3.y_axis]+P_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[C2.x_axis][C2.y_axis];
B_Z=P_Sample[num].integral_image[C5.x_axis][C5.y_axis]+P_Sample[num].integral_image[C2.x_axis][C2.y_axis]-P_Sample[num].integral_image[C3.x_axis][C3.y_axis]-P_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis]+P_Sample[num].integral_image[C4.x_axis][C4.y_axis]+P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-P_Sample[num].integral_image[C3.x_axis][C3.y_axis];
};break;
case 6:
{
Coordinate C1,C2,C3,C4;
C1.x_axis=A_Point.x_axis;
C1.y_axis=(B_Point.y_axis-A_Point.y_axis)/haar.t+A_Point.y_axis;
C2.x_axis=A_Point.x_axis;
C2.y_axis=(B_Point.y_axis-A_Point.y_axis)*(haar.t-1)/haar.t+A_Point.y_axis;
C3.x_axis=C_Point.x_axis;
C3.y_axis=(D_Point.x_axis-C_Point.x_axis)/haar.t+C_Point.x_axis;
C4.x_axis=C_Point.x_axis;
C4.y_axis=(D_Point.y_axis-C_Point.y_axis)*(haar.t-1)/haar.t+C_Point.y_axis;
W_Z=P_Sample[num].integral_image[C4.x_axis][C4.y_axis]+P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[C2.x_axis][C2.y_axis]-P_Sample[num].integral_image[C3.x_axis][C3.y_axis];
B_Z=P_Sample[num].integral_image[C3.x_axis][C3.y_axis]+P_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis]+P_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+P_Sample[num].integral_image[C2.x_axis][C2.y_axis]-P_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-P_Sample[num].integral_image[C4.x_axis][C4.y_axis];
W_Z=W_Z*2;
};break;
case 7:
{
Coordinate C1,C2;
C1.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C1.y_axis=A_Point.y_axis;
C2.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C2.y_axis=D_Point.y_axis;
W_Z=P_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+P_Sample[num].integral_image[C1.x_axis][C1.y_axis]-P_Sample[num].integral_image[C2.x_axis][C2.y_axis]-P_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis];
B_Z=P_Sample[num].integral_image[C2.x_axis][C2.y_axis]+P_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-P_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-P_Sample[num].integral_image[C1.x_axis][C1.y_axis];
};break;
}
integral=W_Z-B_Z;
return integral;
}
//计算负类样本特征值；
int Haar_Feature_Trainning::get_haar2(Haar_Feature haar,Coordinate A_Point,Coordinate D_Point,int num)
{
Coordinate B_Point,C_Point;
int W_Z=0,B_Z=0;
int integral=0;
B_Point.x_axis=A_Point.x_axis;
B_Point.y_axis=D_Point.y_axis;
C_Point.x_axis=D_Point.x_axis;
C_Point.y_axis=A_Point.y_axis;
switch(haar.kind)
{
case 1:
{
Coordinate C1,C2;
C1.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C1.y_axis=A_Point.y_axis;
C2.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C2.y_axis=D_Point.y_axis;
W_Z=M_Sample[num].integral_image[C2.x_axis][C2.y_axis]+M_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-M_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-M_Sample[num].integral_image[C1.x_axis][C1.y_axis];
B_Z=M_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[C2.x_axis][C2.y_axis]-M_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis];
};break;
case 2:
{
Coordinate C1,C2;
C1.x_axis=A_Point.x_axis;
C1.y_axis=(B_Point.y_axis-A_Point.y_axis)/haar.t+A_Point.y_axis;
C2.x_axis=C_Point.x_axis;
C2.y_axis=(D_Point.y_axis-C_Point.y_axis)/haar.t+C_Point.y_axis;
W_Z=M_Sample[num].integral_image[C2.x_axis][C2.y_axis]+M_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis];
B_Z=M_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-M_Sample[num].integral_image[C2.x_axis][C2.y_axis];
};break;
case 3:
{
Coordinate C1,C2,C3,C4;
C1.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C1.y_axis=A_Point.y_axis;
C2.x_axis=(D_Point.x_axis-B_Point.x_axis)/haar.s+B_Point.x_axis;
C2.y_axis=B_Point.y_axis;
C3.x_axis=(C_Point.x_axis-A_Point.x_axis)*(haar.s-1)/haar.s+A_Point.x_axis;
C3.y_axis=A_Point.y_axis;
C4.x_axis=(D_Point.x_axis-B_Point.x_axis)*(haar.s-1)/haar.s+B_Point.x_axis;
C4.y_axis=B_Point.y_axis;
W_Z=M_Sample[num].integral_image[C2.x_axis][C2.y_axis]+M_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]+M_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+M_Sample[num].integral_image[C3.x_axis][C3.y_axis]-M_Sample[num].integral_image[C4.x_axis][C4.y_axis]-M_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis];
B_Z=M_Sample[num].integral_image[C4.x_axis][C4.y_axis]+M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[C2.x_axis][C2.y_axis]-M_Sample[num].integral_image[C4.x_axis][C4.y_axis];
B_Z=B_Z*2;
};break;
case 4:
{
Coordinate C1,C2,C3,C4;
C1.x_axis=A_Point.x_axis;
C1.y_axis=(B_Point.y_axis-A_Point.y_axis)/haar.t+A_Point.y_axis;
C2.x_axis=A_Point.x_axis;
C2.y_axis=(B_Point.y_axis-A_Point.y_axis)*(haar.t-1)/haar.t+A_Point.y_axis;
C3.x_axis=C_Point.x_axis;
C3.y_axis=(D_Point.x_axis-C_Point.x_axis)/haar.t+C_Point.x_axis;
C4.x_axis=C_Point.x_axis;
C4.y_axis=(D_Point.y_axis-C_Point.y_axis)*(haar.t-1)/haar.t+C_Point.y_axis;
W_Z=M_Sample[num].integral_image[C3.x_axis][C3.y_axis]+M_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis]+M_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+M_Sample[num].integral_image[C2.x_axis][C2.y_axis]-M_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-M_Sample[num].integral_image[C4.x_axis][C4.y_axis];
B_Z=M_Sample[num].integral_image[C4.x_axis][C4.y_axis]+M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[C2.x_axis][C2.y_axis]-M_Sample[num].integral_image[C3.x_axis][C3.y_axis];
B_Z=B_Z*2;
};break;
case 5:
{
Coordinate C1,C2,C3,C4,C5;
C1.x_axis=A_Point.x_axis;
C1.y_axis=(B_Point.y_axis-A_Point.y_axis)/haar.t+A_Point.y_axis;
C2.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C2.y_axis=A_Point.y_axis;
C3.x_axis=C2.x_axis;
C3.y_axis=C1.y_axis;
C4.x_axis=C2.x_axis;
C4.y_axis=B_Point.y_axis;
C5.x_axis=C_Point.x_axis;
C5.y_axis=C1.y_axis;
W_Z=M_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+M_Sample[num].integral_image[C3.x_axis][C3.y_axis]-M_Sample[num].integral_image[C4.x_axis][C4.y_axis]-M_Sample[num].integral_image[C5.x_axis][C5.y_axis]+M_Sample[num].integral_image[C3.x_axis][C3.y_axis]+M_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[C2.x_axis][C2.y_axis];
B_Z=M_Sample[num].integral_image[C5.x_axis][C5.y_axis]+M_Sample[num].integral_image[C2.x_axis][C2.y_axis]-M_Sample[num].integral_image[C3.x_axis][C3.y_axis]-M_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis]+M_Sample[num].integral_image[C4.x_axis][C4.y_axis]+M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-M_Sample[num].integral_image[C3.x_axis][C3.y_axis];
};break;
case 6:
{
Coordinate C1,C2,C3,C4;
C1.x_axis=A_Point.x_axis;
C1.y_axis=(B_Point.y_axis-A_Point.y_axis)/haar.t+A_Point.y_axis;
C2.x_axis=A_Point.x_axis;
C2.y_axis=(B_Point.y_axis-A_Point.y_axis)*(haar.t-1)/haar.t+A_Point.y_axis;
C3.x_axis=C_Point.x_axis;
C3.y_axis=(D_Point.x_axis-C_Point.x_axis)/haar.t+C_Point.x_axis;
C4.x_axis=C_Point.x_axis;
C4.y_axis=(D_Point.y_axis-C_Point.y_axis)*(haar.t-1)/haar.t+C_Point.y_axis;
W_Z=M_Sample[num].integral_image[C4.x_axis][C4.y_axis]+M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[C2.x_axis][C2.y_axis]-M_Sample[num].integral_image[C3.x_axis][C3.y_axis];
B_Z=M_Sample[num].integral_image[C3.x_axis][C3.y_axis]+M_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis]+M_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+M_Sample[num].integral_image[C2.x_axis][C2.y_axis]-M_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-M_Sample[num].integral_image[C4.x_axis][C4.y_axis];
W_Z=W_Z*2;
};break;
case 7:
{
Coordinate C1,C2;
C1.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C1.y_axis=A_Point.y_axis;
C2.x_axis=(C_Point.x_axis-A_Point.x_axis)/haar.s+A_Point.x_axis;
C2.y_axis=D_Point.y_axis;
W_Z=M_Sample[num].integral_image[D_Point.x_axis][D_Point.y_axis]+M_Sample[num].integral_image[C1.x_axis][C1.y_axis]-M_Sample[num].integral_image[C2.x_axis][C2.y_axis]-M_Sample[num].integral_image[C_Point.x_axis][C_Point.y_axis];
B_Z=M_Sample[num].integral_image[C2.x_axis][C2.y_axis]+M_Sample[num].integral_image[A_Point.x_axis][A_Point.y_axis]-M_Sample[num].integral_image[B_Point.x_axis][B_Point.y_axis]-M_Sample[num].integral_image[C1.x_axis][C1.y_axis];
};break;
}
integral=W_Z-B_Z;
return integral;
}
//将整形类型转换为字符串类型；
string Haar_Feature_Trainning::Convert(int temp)
{
stringstream ss;
string s;
ss<<temp;
ss>>s;
return s;
}
//将浮点型转换为字符串类型；
string Haar_Feature_Trainning::Convert(double temp)
{
stringstream ss;
string s;
ss<<temp;
ss>>s;
return s;
}
//取下整函数；
int Haar_Feature_Trainning::Low_Integral_Function(int x1,int x2)
{
if(x1%x2==0)
{
return x1/x2-1;
}
else
{
return x1/x2;
}
}