Using a trained neural network in app designer for image classification

I am trying to build an app with the app designer for skin tumor image classification. I already trained my CNN and I saved it. My problem is that I'm not sure how can I integrate the trained network in my app so that I can classify new images.

The code from the app designer is this:

classdef app3 < matlab.apps.AppBase

    % Properties that correspond to app components
    properties (Access = public)
        UIFigure                    matlab.ui.Figure
        UploadImageButtonPushed_2   matlab.ui.control.Button
        AnalyzeImageButtonPushed_2  matlab.ui.control.Button
        UIAxes3                     matlab.ui.control.UIAxes
        UIAxes4                     matlab.ui.control.UIAxes
    end

    
    properties (Access = private)
       filepath
        net % neural network
       labels1 
        
    end
    
    methods (Access = private)
        
        function startupfunc(app)
            app.net = load('mini_date2.mat');
            app.net = app.net.net;
            app.filepath = 'E:/LICENTA/BD_Skin_Cancer_Screening/';
            app.filepath = app.filepath.filepath;
           
        end
      
    end
    

    % Callbacks that handle component events
    methods (Access = private)

        % Button pushed function: AnalyzeImageButtonPushed_2
        function AnalyzeImageButtonPushed_2Pushed(app, event)
          imds = imageDatastore(app.filepath);
          [labels]=  classify(app.net,imds);
          imshow([labels, imd],'Parent', app.UIAxes4);   
        end

        % Button pushed function: UploadImageButtonPushed_2
        function UploadImageButtonPushed_2Pushed(app, event)
 
    [filename, app.filepath] = uigetfile({'*.jpg'},'File Selector');
     imagefile = fullfile(app.filepath, filename);
     imd = imread(imagefile);
     imshow(imd, 'Parent', app.UIAxes3);
        end

       end

    % Component initialization
    methods (Access = private)

        % Create UIFigure and components
        function createComponents(app)

            % Create UIFigure and hide until all components are created
            app.UIFigure = uifigure('Visible', 'off');
            app.UIFigure.Position = [100 100 640 480];
            app.UIFigure.Name = 'MATLAB App';

            % Create UploadImageButtonPushed_2
            app.UploadImageButtonPushed_2 = uibutton(app.UIFigure, 'push');
            app.UploadImageButtonPushed_2.ButtonPushedFcn = createCallbackFcn(app, @UploadImageButtonPushed_2Pushed, true);
            app.UploadImageButtonPushed_2.Position = [433 322 162 22];
            app.UploadImageButtonPushed_2.Text = 'UploadImageButtonPushed';

            % Create AnalyzeImageButtonPushed_2
            app.AnalyzeImageButtonPushed_2 = uibutton(app.UIFigure, 'push');
            app.AnalyzeImageButtonPushed_2.ButtonPushedFcn = createCallbackFcn(app, @AnalyzeImageButtonPushed_2Pushed, true);
            app.AnalyzeImageButtonPushed_2.Position = [429 220 170 22];
            app.AnalyzeImageButtonPushed_2.Text = ' AnalyzeImageButtonPushed';

            % Create UIAxes3
            app.UIAxes3 = uiaxes(app.UIFigure);
            title(app.UIAxes3, 'Title')
            xlabel(app.UIAxes3, 'X')
            ylabel(app.UIAxes3, 'Y')
            zlabel(app.UIAxes3, 'Z')
            app.UIAxes3.PlotBoxAspectRatio = [1.93129770992366 1 1];
            app.UIAxes3.ButtonDownFcn = createCallbackFcn(app, @UIAxes3ButtonDown, true);
            app.UIAxes3.Position = [48 233 300 185];

            % Create UIAxes4
            app.UIAxes4 = uiaxes(app.UIFigure);
            title(app.UIAxes4, 'Title')
            xlabel(app.UIAxes4, 'X')
            ylabel(app.UIAxes4, 'Y')
            zlabel(app.UIAxes4, 'Z')
            app.UIAxes4.PlotBoxAspectRatio = [1.93129770992366 1 1];
            app.UIAxes4.Position = [57 36 300 185];

            % Show the figure after all components are created
            app.UIFigure.Visible = 'on';
        end
    end

    % App creation and deletion
    methods (Access = public)

        % Construct app
        function app = app3

            % Create UIFigure and components
            createComponents(app)

            % Register the app with App Designer
            registerApp(app, app.UIFigure)

            if nargout == 0
                clear app
            end
        end

        % Code that executes before app deletion
        function delete(app)

            % Delete UIFigure when app is deleted
            delete(app.UIFigure)
        end
    end
end

Answer 1

[Anshika Chaurasia]

Hi Malina,

Refer to following discussion which are similar to your issue:

https://in.mathworks.com/matlabcentral/answers/444474-neural-network-in-matlab-app-designer#comment_670415

App designer error classify - MATLAB Answers - MATLAB Central (mathworks.com)

Hope it helps!

[Malina Balint]

It helped thank you!

[Yogini Prabhu]

Hi Anshika

I am aware that this comment is to a specific question by another Matlab client ,

however I wanted to reach to u.

I had posted question about NN, and expected Mr. Greg Heath to answer it, but since I dint get any answers, and here was the only place to find you. please oblige

this is the question: "Please let know how is Cross -validation implemented in the the nprtool (Deep Learning Toolbox)?"

OR

"Please let know how is Cross -validation implemented in the the code of classification of patterns at nprtool (Deep Learning Toolbox)?"

Please respond as soon as possible!

thanking you in advance