为什么这段代码会给我这个错误：“列车数据必须是浮点矩阵”。 [英] Why this code gives me this error: "train data must be floating-point matrix"
本文介绍了为什么这段代码会给我这个错误：“列车数据必须是浮点矩阵”。的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
如何更正此程序？
我想读取100个二进制图像，对它们进行一些处理，将结果保存为40个长度数组，为每个图片添加标签并最终训练它们在SVM分类中。这是我第一次使用SVM的经历，我不知道如何解决问题？
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(100, 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;
}推荐答案
First of all, why do you post hundreds lines of code in a quick question. Do your really expect people to read your entire program?
The error message obviously comes from the SVM.train call in your svm function. So that would have been all you should have posted.
Now, if you read the error message, it appears to me to be pretty clear. The CvSVM train function expects a matrix of floating point type in its first argument, and not an integer matrix. Your mistake appears to be in the two lines
First of all, why do you post hundreds lines of code in a quick question. Do your really expect people to read your entire program?
The error message obviously comes from the SVM.train call in your svm function. So that would have been all you should have posted.
Now, if you read the error message, it appears to me to be pretty clear. The CvSVM train function expects a matrix of floating point type in its first argument, and not an integer matrix. Your mistake appears to be in the two lines
Mat img(32, 32, CV_32FC1);
img=imread(format("/home/chris/bang/bn%04d%d.bmp",g1,number ),
CV_LOAD_IMAGE_GRAYSCALE);
The second line does not convert the image to the floating point format, as you might have expected, but discards your pre-allocated matrix and assigns the image to it, which is of course in integer format. Use one of the conversions to do that.
The second line does not convert the image to the floating point format, as you might have expected, but discards your pre-allocated matrix and assigns the image to it, which is of course in integer format. Use one of the conversions to do that.
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