Matlab Help Needed Please

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Anas Bilal
Anas Bilal on 18 Apr 2020
Commented: Anas Bilal on 18 Apr 2020
hello everyne i'm runing this code for testing and training but receiving errors can any please help me to correct this code i shall be very thank full to you for this kindness.
clc
clear all
close all
image=uigetfile(['*.jpg'],'D:\Diabetic retnopathery\DR code');
copyfile('D:\Diabetic retnopathery\DR code','D:\Diabetic retnopathery\DR code\New Folder');
%inp=input('ENTER IMAGE :');
imgg=imread(image);
aa=imgg;
[m n c]=size(aa);
if c==3
b=rgb2gray(aa);
else
b=aa;
end
im =b;
figure,
imshow(aa)
title('input ')
matlabroot='D:\Diabetic retnopathery\DR code'
DatasetPath = fullfile(matlabroot,'fundusdeeplearning','Dataset1');
Data = imageDatastore(DatasetPath, ...
'IncludeSubfolders',true,'LabelSource','foldernames');
CountLabel = Data.countEachLabel;
trainData=Data;
%% Define the Network Layers
% Define the convolutional neural network architecture.
layers = [imageInputLayer([336 448 3])
convolution2dLayer(5,20)
reluLayer
maxPooling2dLayer(2,'Stride',2)
convolution2dLayer(5,20)
reluLayer
maxPooling2dLayer(2,'Stride',2)
fullyConnectedLayer(2)
softmaxLayer
classificationLayer()];
options = trainingOptions('sgdm','MaxEpochs',15, ...
'InitialLearnRate',0.0001);
convnet = trainNetwork(trainData,layers,options);
%% Classify the Images in the Test Data and Compute Accuracy
% Run the trained network on the test set that was not used to train the
% network and predict the image labels (digits).
img =imgg;
img=imresize(img,[336 448]);
size(img)
outt = classify(convnet,img);
tf1=[]
for ii=1:2
st=int2str(ii)
tf = ismember(outt,st);
tf1=[tf1 tf];
end
out=find(tf1==1);
ss=sprintf('THE CLASS IS : %2f ',round((out)));
if out==1
msgbox('NORMAL')
elseif out==2
msgbox('AB NORMAL')
end
  9 Comments
Anas Bilal
Anas Bilal on 18 Apr 2020
ok .i'll try

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