Error in matlab code

Question

Maryam Almannaee 2021-11-28

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1597694-error-in-matlab-code

编辑： Image Analyst 2021-11-28

I have the following MATLAB code, but there is an issue. It's not running. Can someone help me with that?

clc;
clear all;
close all;
DatasetPath='C:\Users\4u\OneDrive\Desktop\Jaffedbase'
imds=imageDatastore(DatasetPath,'IncludeSubfolders',true,'LabelSource','foldernames')
tic;
train_data = dir('C:\Users\4u\OneDrive\Desktop\Jaffedbase*.tiff');
trainl=length(train_data);
trainf=[];
v1=[];
%Traing images loop
for trainloop = 1:trainl
    file_train=strcat('C:\Users\4u\OneDrive\Desktop\Jaffedbase',train_data(trainloop).name);
    im_train= (imread(file_train));
    facecet = vision.CascadeObjectDetector(); % face detection in a given image
    bbox=step(facedet,im_train);
    face=imcrop(im_train,bbox);
    Mouthdet= vision.CascadeObjectDetector('Mouth'); % mouth detection in a given face image
    BB==step(Mouthdet,face);
    for i= 1:size(BB,1)
        a=BB(i,:);
        z=a(2);
        if z > 97
            b=face(a(2):a(2)+a(4),a(1):a(1)+a(3));
            figure(1);
            subplot (5,4,trainloop);
            imshow(file_train); 
            figure(2);
            subplot (5,4,trainloop);
            imshow(b);
            [featureVector1,hogVisualization1] = extractHOGFeatures(b); %Extracting featues using HOG
            figure(3);
            subplot (5,4,trainloop);
            plot(hogVisualization1);
            Train_coeff1=featureVector1';
            v1=[v1,Train_coeff1(1:120,1:1)];
            trainfv1';
        end
    end
end
Happy = [trainf(1,:);trainf(3,:);trainf(5,:);trainf(6,:);trainf(15,:);trainf(16,:)];
Surprise = [trainf(2,:);trainf(4,:);trainf(7,:);trainf(8,:);trainf(17,:);trainf(18,:)];
Sad = [trainf(9,:);trainf(10,:);trainf(11,:);trainf(12,:);trainf(19,:)];
Anger = [trainf(13,:);trainf(14,:);trainf(20,:)];
aT1=mean(Happy);
aT2=mean(Surprise);
aT3=mean(Sad);
aT4=mean(Anger);
train_group=[1;2;1;2;1;1;2;2;3;3;3;3;4;4;1;1;2;2;3;4];
Model=fitcknn(trainf,train_group','Distance','euclidean'); % Training the KNN Classifier
test_data = dir('C:\Users\4u\OneDrive\Desktop\Jaffedbase\test1\*.tiff');
testl=length(test_data);
testf=[];
test_group=[1;2;3;2;3;1;4;4;1;2;3;2;4;4;4;1;3;3;2;1];
k=1;
for testloop = 1:testl
    file_test = strcat('C:\Users\4u\OneDrive\Desktop\Jaffedbase\test1\',test_data(testloop).name);
    im_test= imread(file_test);
    facedet1= vision.CascadeObjectDetector(); % face detection in a given image
    bbox=step(facedet1,im_test);
    face1=imcrop(im_test,bbox1);
    Mouthdet1= vision.CascadeObjectDetector('Mouth'); % mouth detection in a given face image
    BB1=step(Mouthdet1,face1);
    y1=size(BB1,1);
    for j = 1:y1
        a1=BB1(j,:);
        z1=a1(2);
        if z1 > 100
            b1=face1(a1(2):a1(2)+a1(4),a1(1):a1(1)+a1(3));
            figure(4);
            subplot(5,4,testloop);
            imshow(file_test); 
            figure(5);
            subplot (5,4,testloop);
            imshow(b1);
            [ffeatureVector2,hogVisualization2] = extractHOGFeatures(b1); %Extracting featues using HOG
            figure(6);
            subplot(5,4,testloop);
            plot(hogVisualization2);
            Train_coeff2=featureVector2';
            tc=Train_coeff2(1:120,1:1);
            tc=tc';
            [llabel,score,cost] = predict(Model,tc);
            TestPredict(k)=round(label);
            if test_group(testloop) == 1
                ref_tc=aT1;
            elseif test_group(testloop) == 2
                ref_tc=aT2;
            elseif test_group(testloop) == 3
                ref_tc=aT3;
            elseif test_group(testloop) == 4
                ref_tc=aT4;
            end
            PSNR_cal(k)=psnr(tc,ref_tc);
            mse_cal(k)=immse(tc,ref_tc);
            entropy_cal(k)=entropy(b1);
            k=k+1;
        end
    end
end
% Accuracy, mean time of executions, PSNR, MSE and Entropy Calculations
cMatf = confusionmat(test_group,TestPredict) %compare test data with new features
acc = 100*(sum(diag(cMatf))/length(TestPredict));
fprintf('Accuracy: ');
fprintf('%d\n', acc);
execution_time=toc
X=[1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20];
figure(7);
plot(X,PSNR_cal,'--bs');
xlabel ('Image Numbers');
ylabel ('Signal to Noise Ratio');
title('PSNR (Peak Signal to Noise Ratio)');
figure(8);
plot(X,mse_cal,'--ro');
xlabel ('Image Numbers');
ylabel ('Mean square error');
title('MSE (Mean Square Error)');
figure(9);
plot(X,entropy_cal,'--ms');
xlabel ('Image Numbers');
ylabel ('Entropy');
title('Entropy');

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Jan 2021-11-28

编辑：Image Analyst 2021-11-28

We cannot run your code due to th missing inputs. Then information "there is an issue" is too vague to bve answered. Please mention, what issue you have. It is much easier to solve a problem than to guess, what the problem is.

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