how to get started with training image labeler?

Question

Shahad 2015-10-29

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https://ww2.mathworks.cn/matlabcentral/answers/251740-how-to-get-started-with-training-image-labeler

评论： raed bou aram 2016-12-2

Hi everyone,

I'm a newbie to Matlab and I need to use "computer vision" for "trainCascadeObjectDetector". I have two options, either to use Cascade trainer or training image labeler app, which one is better? I tried to use training image labeler and I got .mat file exported after but I don't know what is the next step. any help will be appreciated!

When I clicked generate Matlab code I got the following code:

function importfile(fileToRead1)
    %IMPORTFILE(FILETOREAD1)
    %  Imports data from the specified file
    %  FILETOREAD1:  file to read
    
    %  Auto-generated by MATLAB on 29-Oct-2015 19:09:24
    
    % Import the file
    newData1 = load('appleSession-mat', fileToRead1);
    
    % Create new variables in the base workspace from those fields.
    vars = fieldnames(newData1);
    for i = 1:length(vars)
        assignin('base', vars{i}, newData1.(vars{i}));
    end

When I run it I got the following error:

 >> importfile
    Not enough input arguments.
    
    Error in importfile (line 9)
    newData1 = load('appleSession-mat', fileToRead1);

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Answer 1

Dima Lisin 2015-10-29

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https://ww2.mathworks.cn/matlabcentral/answers/251740-how-to-get-started-with-training-image-labeler#answer_197841

Hi Shahad,

If you use the Training Image Labeler app, once you are done labeling the objects, you have to click the "Export ROIs" button. The one with the "checkmark" icon. This will create a variable in your workspace called positiveInstances, which contains the image file names and the bounding boxes that you have labeled. This is one of the inputs into trainCascadeObjectDetector function.

Please see Label Images for Classification Model Training and Train a Cascade Object Detector tutorials for more information.

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Shahad 2015-10-30

在 MATLAB Online 中打开

Thanks Eng.Dima for your fast and helpful reply :)

I need to detect apple, banana, orange and Kiwi. Any advices? I will be glad to gain from you experience.

I'm really happy the following code work perfectly:

load('stopSigns.mat');
imDir = fullfile(matlabroot,'toolbox','vision','visiondata','stopSignImages');
addpath(imDir);
negativeFolder = fullfile(matlabroot,'toolbox','vision','visiondata','nonStopSigns');
trainCascadeObjectDetector('stopSignDetector.xml',data,negativeFolder,'FalseAlarmRate',0.2,'NumCascadeStages',5);
%%Use the newly trained classifier to detect a stop sign in an image
   detector = vision.CascadeObjectDetector('stopSignDetector.xml');
     img = imread('stopSignTest.jpg'); % read the test image
     bbox = step(detector, img); % detect a stop sign
     % Insert bounding box rectangles and return marked image
     detectedImg = insertObjectAnnotation(img, 'rectangle', bbox, 'stop sign You did it :)');
     figure; imshow(detectedImg); % display the detected stop sign
     rmpath(imDir); % remove the image directory from the path

Dima Lisin 2016-4-9

data in the example comes from the .mat file, which the example loads. It must be a struct array containing image file names and bounding boxes. You can create it using Training Image Labeler app.

raed bou aram 2016-12-2

Hi Dima, I am also trying to do trainCascadeObjectDetector to detect blood capillaries ( 15 capillaries) , and use image processing to compare one by one with the same capilar (example: capilar one with capilar 1 centrifuged). Is this viable? any advice? thanks for helping and for this and future advice.

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