Iam getting error for svm predection section please help me

clc

close all;

close all;

cd Database

DF=[]

for i=1:45

i

str1=int2str(i);

str2=strcat(str1,'.jpg');

nor=imread(str2);

%color

cmap=rgb2hsv(nor);

H=cmap(:,:,1);

S=cmap(:,:,2);

V=cmap(:,:,3);

Hmean=mean(mean(H));

Hst=std2(H);

Smean=mean(mean(S));

Sst=std2(S);

Vmean=mean(mean(V));

Vst=std2(V);

Hsk=sum(skewness(H));

Ssk=sum(skewness(S));

Vsk=sum(skewness(V));

Hmin=min(imhist(H));

Hmax=max(imhist(H));

Smin=min(imhist(S));

Smax=max(imhist(S));

Vmin=min(imhist(V));

Vmax=max(imhist(V));

%texture

I=rgb2gray(nor);

glcm=graycomatrix(I,'offset',[2 0;0 2]);

stats1=graycoprops(glcm,{'contrast','homogeneity'});

stats2=graycoprops(glcm,{'correlation','energy'});

t1=stats1.Contrast;

t2=stats1.Homogeneity;

t3=stats2.Correlation;

t4=stats2.Energy;

%Shape

FEAT=horzcat(1,[Hmean Hst Smean Sst Vmean Vst Hsk Vsk Ssk Hmin Hmax Smin Smax Vmin Vmax t1 t2 t3 t4]);

DF=[DF;FEAT];

end

cd ..

[fname,path]=uigetfile('.jpg','Provide currency for testing');

filename=strcat(path,fname);

nor=imread(filename);

%color

cmap=rgb2hsv(nor);

H=cmap(:,:,1);

S=cmap(:,:,2);

V=cmap(:,:,3);

Hmean=mean(mean(H));

Hst=std2(H);

Smean=mean(mean(S));

Sst=std2(S);

Vmean=mean(mean(V));

Vst=std2(V);

Hsk=sum(skewness(H));

Ssk=sum(skewness(S));

Vsk=sum(skewness(V));

Hmin=min(imhist(H));

Hmax=max(imhist(H));

Smin=min(imhist(S));

Smax=max(imhist(S));

Vmin=min(imhist(V));

Vmax=max(imhist(V));

%texture

I=rgb2gray(nor);

glcm=graycomatrix(I,'offset',[2 0;0 2]);

stats1=graycoprops(glcm,{'contrast','homogeneity'});

stats2=graycoprops(glcm,{'correlation','energy'});

t1=stats1.Contrast;

t2=stats1.Homogeneity;

t3=stats2.Correlation;

t4=stats2.Energy;

%Shape

QF=horzcat(1,[Hmean Hst Smean Sst Vmean Vst Hsk Vsk Ssk Hmin Hmax Smin Smax Vmin Vmax t1 t2 t3 t4]);

%Multi svm

Trainigset=[DF(1,:);DF(2,:);DF(3,:);DF(4,:);DF(5,:);DF(6,:);DF(7,:);DF(8,:);DF(9,:);DF(10,:);DF(11,:);DF(12,:);DF(13,:);DF(14,:);DF(15,:);DF(16,:);DF(17,:);DF(18,:);DF(19,:);DF(20,:);DF(21,:);DF(22,:);DF(23,:);DF(24,:);DF(25,:);DF(26,:);DF(27,:);DF(28,:);DF(29,:);DF(30,:);DF(31,:);DF(32,:);DF(33,:);DF(34,:);DF(35,:);DF(36,:);DF(37,:);DF(38,:);DF(39,:);DF(40,:);DF(41,:);DF(42,:);DF(43,:);DF(44,:);DF(45,:)];

GroupTrain={'1' '1' '1' '1' '1' '1' '1' '1' '1' '2' '2' '2' '2' '2' '2' '2' '2' '2' '3' '3' '3' '3' '3' '3' '3' '3' '3' '4' '4' '4' '4' '4' '4' '4' '4' '4' '5' '5' '5' '5' '5' '5' '5' '5' '5' };

TestSet=QF;

SVMModels=cell(5,1);

y=GroupTrain

classes=unique(y);

rng(1);

for j=1:numel(classes)

indx=strcmp(y',classes(j));

SVMMOdels{j}=fitcsvm(DF,indx,'ClassNames',[false true],'Standardize',true,'KernelFunction','rbf','BoxConstraint',1);

end

xGrid=QF;

for j=1:numel(classes)

[~,score]=predict(SVMModels{j},xGrid)

Scores(:,j)=score(:,2);

end

[~,maxScore]=max(score,[],2);

result=maxScore;

figure.imshow(nor)

title('input')

if result==1

msgbox('10')

elseif result==2

msgbox('20')

elseif result==3

msgbox('50')

elseif result==4

msgbox('100')

elseif result==5

msgbox('500')

end

Answer 1

[Omega]

Hi Savita,

The error you're encountering is likely due to a typo in your code. You have defined your SVM models using "SVMMOdels" instead of "SVMModels". Therefore, when you try to use "SVMModels" in the prediction section, it's empty, causing the error.

Here's a quick fix: Change "SVMMOdels" to "SVMModels" in the training loop. Here's the corrected section of your code:

for j = 1:numel(classes)
    indx = strcmp(y', classes(j));
    SVMModels{j} = fitcsvm(DF, indx, 'ClassNames', [false true], 'Standardize', true, 'KernelFunction', 'rbf', 'BoxConstraint', 1);
end

Make sure you update the loop where you're creating the SVM models. After this change, your "predict" function should work correctly.