How can I correct this program? I want to read 100 binary images, do some process on them, save the results as 40 length arrays, give a label to each picture and finally train them in SVM classification. This is my first experience to use SVM and I don't know how can I correct the problem?
#include <cxcore.h>
#include <cv.h>
#include <iostream>
#include <highgui.h>
#include <ml.h>
#include <opencv2/opencv.hpp>
#include <vector>
#include <utility>
#include <math.h>
#include <bitset>
#include <cstdlib>
#include <string>
#include <sstream>
using namespace cv;
using namespace std;
int gnum[50][100][41], new_gnum[50][100][41] , child1[50][100][41], child2[50][100][41];
int g0=0, g1=0, g2=0;
int correct=0, total=0;
int number=0; float labels[100];
Mat img;
int response;
int convert(int input_int)
{
int remainder, digits = 0, dividend = input_int;
while(dividend != 0)
{
dividend = dividend / 2;
digits++;
}
int array[digits];
dividend = input_int;
for(int i = digits - 1; i >= 0; i--)
{
remainder = dividend % 2;
array[i] = remainder;
dividend = dividend / 2;
}
/*
for(int j = 0; j < digits; j++)
{
cout << array[j];
}
if(input_int == 0)
cout << 0;
cout << endl;
*/
}
int Y_centroid(int y[])
{
int sum=0; int numb=0;
for(int i=0;i<100 ; i++)
{
int temp=y[i];
if(temp != 0)
{
sum=+y[i];
numb=i;
}
}
int Y_centroid= sum/numb;
gnum[g0][g1][g2]=convert(Y_centroid);
g2++;
}//j1
int X_centroid(int x[])
{
int sum=0; int numb=0;
for(int i=0;i<100 ; i++)
{
int temp=x[i];
if(temp != 0)
{
sum=+x[i];
numb=i;
}
}
int X_centroid= sum/numb;
gnum[g0][g1][g2]=convert(X_centroid);
g2++;
}
int shadowON_y(int y[])
{
int max=0, min=33, Yside_shadow=0;
for(int i=0; i<100; i++)
{
if(y[i]>max)
max=y[i];
}
for(int j=0; j<100; j++)
{
if(y[j]<min)
min=y[j];
}
Yside_shadow= max-min;
gnum[g0][g1][g2]=convert(Yside_shadow);
g2++;
}
int shadowON_x(int x[])
{
int max=0, min=33, Xside_shadow=0;
for(int i=0; i<100; i++)
{
if(x[i]>max)
max=x[i];
}
for(int j=0; j<100; j++)
{
if(x[j]<min)
min=x[j];
}
Xside_shadow= max-min;
gnum[g0][g1][g2]=convert(Xside_shadow);
g2++;
}
int Crossover()
{
int i=0,j=0;
for( i=0; i<100 ; i+2)
{
for( j=0; j<20; j++)
{
child1[g0][i][j]=gnum[g0][i][j];
child2[g0][i][j]=gnum[g0][i+1][j];
}
for(int j=20;j<41; j++ )
{
child1[g0][i][j]=gnum[g0][i][j];
child2[g0][i][j]=gnum[g0][i+1][j];
}
gnum[g0][i][j]=child1[g0][i][j];
gnum[g0][i+1][j]=child2[g0][i][j];
}//i loop
}
int Mutation()
{
srand(time(NULL));
int Random1=(rand() % 100);
int Random2=(rand() % 41);
if(child1[g0][Random1][Random2]==0)
child1[g0][Random1][Random2]=1;
}
int detection(Mat img)
{
int i1=0,j1=0;
int i2=0,j2=0;
int i3=0,j3=0;
int i4=0,j4=0;
int i5=0,j5=0;
int i6=0,j6=0;
int i7=0,j7=0;
int i8=0,j8=0;
int iq1=0,jq1=0;
int iq2=0,jq2=0;
int iq3=0,jq3=0;
int iq4=0,jq4=0;
int num1_1=0, num2_1=0;
int num1_2=0, num2_2=0;
int num1_3=0, num2_3=0;
int num1_4=0, num2_4=0;
int num1_5=0, num2_5=0;
int num1_6=0, num2_6=0;
int num1_7=0, num2_7=0;
int num1_8=0, num2_8=0;
int num3_1=0, num4_1=0;
int num3_2=0, num4_2=0;
int num3_3=0, num4_3=0;
int num3_4=0, num4_4=0;
int y1[100],x1[100];
int y2[100],x2[100];
int y3[100],x3[100];
int y4[100],x4[100];
int y5[100],x5[100];
int y6[100],x6[100];
int y7[100],x7[100];
int y8[100],x8[100];
int yq1[100],xq1[100];
int yq2[100],xq2[100];
int yq3[100],xq3[100];
int yq4[100],xq4[100];
for(int sh=0; sh<100; sh++){y1[sh]=0;}
for(int sh=0; sh<100; sh++){y2[sh]=0;}
for(int sh=0; sh<100; sh++){y3[sh]=0;}
for(int sh=0; sh<100; sh++){y4[sh]=0;}
for(int sh=0; sh<100; sh++){y5[sh]=0;}
for(int sh=0; sh<100; sh++){y6[sh]=0;}
for(int sh=0; sh<100; sh++){y7[sh]=0;}
for(int sh=0; sh<100; sh++){y8[sh]=0;}
for(int sh=0; sh<100; sh++){x1[sh]=0;}
for(int sh=0; sh<100; sh++){x2[sh]=0;}
for(int sh=0; sh<100; sh++){x3[sh]=0;}
for(int sh=0; sh<100; sh++){x4[sh]=0;}
for(int sh=0; sh<100; sh++){x5[sh]=0;}
for(int sh=0; sh<100; sh++){x6[sh]=0;}
for(int sh=0; sh<100; sh++){x7[sh]=0;}
for(int sh=0; sh<100; sh++){x8[sh]=0;}
for(int sh=0; sh<100; sh++){xq1[sh]=0;}
for(int sh=0; sh<100; sh++){xq2[sh]=0;}
for(int sh=0; sh<100; sh++){xq3[sh]=0;}
for(int sh=0; sh<100; sh++){xq4[sh]=0;}
for(int sh=0; sh<100; sh++){yq1[sh]=0;}
for(int sh=0; sh<100; sh++){yq2[sh]=0;}
for(int sh=0; sh<100; sh++){yq3[sh]=0;}
for(int sh=0; sh<100; sh++){yq4[sh]=0;}
vector<Vec3f> circles;
HoughCircles(img, circles, CV_HOUGH_GRADIENT,1,img.rows/10,200,100,0,0 );
//GaussianBlur( img, img, Size(9, 9), 2, 2 );
/*
for(size_t i=0; i< circles.size(); i++)
{
Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
int radius = cvRound(circles[i][2]);
// circle center
circle( img, center, 30, Scalar(0,255,0), -1, 8, 0 );
// circle outline
circle( img, center, radius, Scalar(0,0,255), 3, 8, 0 );
}
namedWindow("win", WINDOW_AUTOSIZE);
imshow("win", img);
*/
if(circles.size()<20)
{
gnum[g0][g1][39]=0;
}else{gnum[g0][g1][39]=1;}
//region num1
for(i1=0; i1<15; i1++)
{
for(int j1=(i1+1);j1<16;j1++)
{
int pix_val=(int)img.at<uchar>(i1,j1);
if(pix_val<15)
{
pix_val=0;
y1[num1_1]=i1;
x1[num2_1]=j1;
num2_1++;
}
}num1_1++;
}
shadowON_y(y1);
shadowON_x(x1);
Y_centroid(y1);
X_centroid(x1);
//region num2
for(i2=1; i2<16; i2++)
{
for(j2=0; j2<(i2+1)-1; j2++)
{
int pix_val=(int)img.at<uchar>(i2,j2);
if(pix_val<15)
{
pix_val=0;
y2[num1_2]=i2;
x2[num2_2]=j2;
num2_2++;
}num1_2++;
}
}
shadowON_y(y2);
shadowON_x(x2);
Y_centroid(y2);
X_centroid(x2);
//region num3
for(i3=16; i3<31; i3++)
{
for(j3=0; j3<(31-i3); j3++)
{
int pix_val=(int)img.at<uchar>(i3,j3);
if(pix_val<15)
{
pix_val=0;
y3[num1_3]=i3;
x3[num2_3]=j3;
num2_3++;
}num1_3++;
}
}
shadowON_y(y3);
shadowON_x(x3);
Y_centroid(y3);
X_centroid(x3);
//region num4
for(i4=17; i4<32; i4++)
{
for(j4=(32-i4); j4<16 ;j4++)
{
int pix_val=(int)img.at<uchar>(i4,j4);
if(pix_val<15)
{
pix_val=0;
y4[num1_4]=i4;
x4[num2_4]=j4;
num2_4++;
}num1_4++;
}
}
shadowON_y(y4);
shadowON_x(x4);
Y_centroid(y4);
X_centroid(x4);
//region num5
for(i5=0; i5<15; i5++)
{
for(j5=16; j5<(31-i5); j5++)
{
int pix_val=(int)img.at<uchar>(i5,j5);
if(pix_val<15)
{
pix_val=0;
y5[num1_5]=i5;
x5[num2_5]=j5;
num2_5++;
}num1_5++;
}
}
shadowON_y(y5);
shadowON_x(x5);
Y_centroid(y5);
X_centroid(x5);
//region num6
for(i6=1; i6<16; i6++)
{
for(j6=(32-i6);j6<32;j6++)
{
int pix_val=(int)img.at<uchar>(i6,j6);
if(pix_val<15)
{
pix_val=0;
y6[num1_6]=i6;
x6[num2_6]=j6;
num2_6++;
}num1_6++;
}
}
shadowON_y(y6);
shadowON_x(x6);
Y_centroid(y6);
X_centroid(x6);
//region num7
for(i7=17; i7<32; i7++)
{
for(j7=16; j7<i7; j7++)
{
int pix_val=(int)img.at<uchar>(i7,j7);
if(pix_val<15)
{
pix_val=0;
y7[num1_7]=i7;
x7[num2_7]=j7;
num2_7++;
}num1_7++;
}
}
shadowON_y(y7);
shadowON_x(x7);
Y_centroid(y7);
X_centroid(x7);
//region num8
for(i8=16; i8<31; i8++)
{
for(j8=(33-i8); j8<32; j8++)
{
int pix_val=(int)img.at<uchar>(i8,j8);
if(pix_val<15)
{
pix_val=0;
y8[num1_8]=i8;
x8[num2_8]=j8;
num2_8++;
}num1_8++;
}
}
shadowON_y(y8);
shadowON_x(x8);
Y_centroid(y8);
X_centroid(x8);
//quad region1
int number=0;
for(iq1=0; iq1<16; iq1++)
{
for(jq1=0; jq1<16; jq1++)
{
int pix_val=(int)img.at<uchar>(iq1,jq1);
if(pix_val<15)
{
pix_val=0;
yq1[num3_1]=iq1;
xq1[num4_1]=jq1;
num4_1++;
}num3_1++;
}
}
int y_dist1=0; int x_dist1=0; int max1_dist1=0; int max1_dist2=0;
for(int sh=0; sh<100; sh++)
{
y_dist1=yq1[sh]; x_dist1=xq1[sh];
int dist=cvRound(sqrt(((y_dist1)*(y_dist1))+((x_dist1)*(x_dist1))));
if(x_dist1>max1_dist1){max1_dist1=y_dist1;}
if(dist>max1_dist2)
max1_dist2=dist;
}
gnum[g0][g1][g2]=max1_dist2;
g2++;
gnum[g0][g1][g2]=max1_dist1;
g2++;
//quad region2
for(iq2=16; iq2<32; iq2++)
{
for(jq2=0; jq2<16; jq2++)
{
int pix_val=(int)img.at<uchar>(iq2,jq2);
if(pix_val<15)
{
pix_val=0;
yq2[num3_1]=iq2;
xq2[num4_1]=jq2;
num4_2++;
}
}num3_2++;
}
int y_dist2=0; int x_dist2=0; int max2_dist1=0; int max2_dist2=0;
for(int sh=0; sh<100; sh++)
{
y_dist2=yq2[sh]; x_dist2=xq2[sh];
int dist=sqrt(((y_dist2 - 31)*(y_dist2 - 31))+((x_dist2)*(x_dist2)));
if(x_dist2>max2_dist2){max2_dist2=x_dist2;}
if(dist>max2_dist2)
max2_dist2=dist;
}
gnum[g0][g1][g2]=max2_dist2;
g2++;
gnum[g0][g1][g2]=max2_dist1;
g2++;
//quad region3
for(iq3=0; iq3<16; iq3++)
{
for(jq3=16; jq3<32; jq3++)
{
int pix_val=(int)img.at<uchar>(iq3,jq3);
if(pix_val<15)
{
pix_val=0;
yq3[num3_3]=iq3;
xq3[num4_3]=jq3;
num4_3++;
}
}num3_3++;
}
int y_dist3=0; int x_dist3=31; int min3_dist1=0; int max3_dist2=0;
for(int sh=0; sh<100; sh++)
{
y_dist3=yq2[sh]; x_dist3=xq2[sh];
int dist=sqrt(((y_dist3)*(y_dist3))+((x_dist3 -31)*(x_dist3 - 31)));
if(x_dist3<min3_dist1){min3_dist1=x_dist3;}
if(dist>max3_dist2)
max3_dist2=dist;
}
gnum[g0][g1][g2]=max3_dist2;
g2++;
gnum[g0][g1][g2]=min3_dist1;
g2++;
//quad region4
for(iq4=16; iq4<32; iq4++)
{
for(jq4=16; jq4<32; jq4++)
{
int pix_val=(int)img.at<uchar>(iq4,jq4);
if(pix_val<15)
{
pix_val=0;
yq4[num3_4]=iq4;
xq4[num4_4]=jq4;
num4_4++;
}
}num3_4++;
}
int y_dist4=0; int x_dist4=0; int min4_dist1=0; int max4_dist2=0;
for(int sh=0; sh<100; sh++)
{
y_dist4=yq2[sh]; x_dist4=xq2[sh];
int dist=sqrt(((y_dist4)*(y_dist4))+((x_dist4)*(x_dist4)));
if(x_dist4>max4_dist2){max4_dist2=x_dist4;}
if(dist>max4_dist2)
max4_dist2=dist;
}
gnum[g0][g1][g2]=max4_dist2;
g2++;
gnum[g0][g1][g2]=min4_dist1;
g2++;
if(number==0)
{
labels[g1]=0;
}
if(number==1)
{
labels[g1]=1;
}
if(number==2)
{
labels[g1]=2;
}
if(number==3)
{
labels[g1]=3;
}
if(number==4)
{
labels[g1]=4;
}
if(number==5)
{
labels[g1]=5;
}
if(number==6)
{
labels[g1]=6;
}
if(number==7)
{
labels[g1]=7;
}
if(number==8)
{
labels[g1]=8;
}
if(number==9)
{
labels[g1]=9;
}
//}//second for loop
//}//first for loop
} //detection
//SVM classification (Our fitness function)
int svm()
{
CvSVM SVM;
for(g1=0; g1<100; g1++)
{
for(number=0; number<10; number++)
{
Mat img(32, 32, CV_32FC1);
img=imread(format("/home/chris/bang/bn%04d%d.bmp",g1,number ), CV_LOAD_IMAGE_GRAYSCALE);
detection(img);
Mat labelsMat(41, 1, CV_32FC1, labels);
CvSVMParams params;
params.svm_type = CvSVM::C_SVC;
params.kernel_type = CvSVM::RBF;
params.gamma=0.5;
SVM.train(img, labelsMat, Mat(), Mat(), params);
}
srand(time(NULL));
int random=(rand() % 6000);
Mat image=imread(format("/home/chris/bang/bn%05d",random), CV_LOAD_IMAGE_GRAYSCALE);
detection(image);
response= SVM.predict(image);
return response;
}
}
int selection()
{
for(g0=0; g0<50; g0++)
{
svm();
if(response>=0 && response<10)
{
Crossover();
Mutation();
new_gnum[g0][g1][g2]=gnum[g0][g1][g2];
correct++;
}
total++;
gnum[g0][g1][g2]=new_gnum[g0][g1][g2];
}
}
int main()
{
float percent=0;
svm();
percent=(correct*100)/total;
cout<<"The percentage of GA algorithm recognition for bangala digits is: "<<percent;
return 0;
}
