Why I cannot get results when I detect multiple labels

after I train FasterRCNN object detector, and use the detector to detect multiple labels, the results did not shown

I cannot figure out why the results not shown in the table. so that I cannot calculate the average precision.

I showed my code

%%
trainingData = apple

numClasses = 3;
numClassesPlusBackground = numClasses + 1;

%%
inputLayer = imageInputLayer([32 32 3]);
filterSize = [3 3];
numFilters = 32;
middleLayers = [             
    convolution2dLayer(filterSize, numFilters, 'Padding', 1)   
    reluLayer()     
    convolution2dLayer(filterSize, numFilters, 'Padding', 1)  
    reluLayer() 
    maxPooling2dLayer(3, 'Stride',2)    
    ];
finalLayers = [
    fullyConnectedLayer(4)
    reluLayer
    fullyConnectedLayer(width(trainingData))
    softmaxLayer
    classificationLayer
    ];

layers = [
    inputLayer
    middleLayers
    finalLayers
    ]


options = trainingOptions('sgdm', ...
      'MiniBatchSize', 1, ...
      'InitialLearnRate', 1e-3, ...
      'MaxEpochs', 10, ...
      'VerboseFrequency', 200, ...
      'CheckpointPath', tempdir);

detector = trainFasterRCNNObjectDetector(trainingData, layers, ...
        'NegativeOverlapRange',[0 0.3], ...
        'PositiveOverlapRange',[0.6 1]);
%%
numImages = height(trainingData);

% Run detector on each image in the test set and collect results.
results = table('Size',[numImages 3],...
       'VariableTypes',{'cell','cell','cell'},...
       'VariableNames',{'Boxes','Scores','Labels'});  



for i = 1:numImages

    %ds = imageDatastore(trainingData.imageFilename{i});
    % Read the image.
    I = imread(trainingData.imageFilename{i});

    % Run the detector.
    [bboxes,scores,labels] = detect(detector, I);
    
    I=insertObjectAnnotation(I, 'rectangle', bboxes, scores);
    
    % Collect the results.
    results.Boxes{i,1} = bboxes;
    results.Scores{i,1} = scores;
    results.Labels{i,1} = labels;

end
results=struct2table(resultsStruct);

 expectedResults = trainingData(:, 2:4);


[ap, recall, precision] = evaluateDetectionPrecision(results,expectedResults);
figure
xlabel('unripeRecall')
ylabel('unripePrecision')
plot(recall, precision)
grid ON
title(sprintf('Average Precision = %.2f', ap));

[Zaime Ali]

Im also stuck in this issue can you please help me too if you found the error

Answer 1

[Image Analyst]

What function did you call to show the regions? Did you use insertObjectAnnotation()?

After you read this link,

post your script.

Answer 2

[Image Analyst]

You ARE getting results. trainindData is not your results - that is the image datastore used to train your detector. Your results are bboxes.

What table are you talking about?

[Carla Shaw]

I am trying to store the answers in a table, but when I used the detect function, the bboxes does not shown in the table, I felt confuse about this.

[Image Analyst]

Since bboxes contains a different number of boxes, it will have to be in a cell. So let's say column 1 of results should contain the cell for that image. You'll need to say

results{i, 1} = {bboxes};

That way, that location of results, the first column in row "i", will be a cell because encasing bboxes in braces puts bboxes into a cell.

Please read the FAQ for a better explanation of what a cell is and how to use it.

FAQ: What is a cell array?

[Carla Shaw]

I tried but still not work, I cannot fogure out why.

[Image Analyst]

Can youi give the complete script, and tell me what kind of image datastore I need to have?