MATLAB Answers

Splitting Ground Thruth Data

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Hamza Yerlikaya
Hamza Yerlikaya on 30 Oct 2019
I am training a object detector by following along the following tutorial from MathWorks [1]. Instead of detecting from a video I am using a set of images. Images are labeled using ImageLabeller app. My question is how do i split the images in to train/test datasets. `objectDetectorTrainingData` has sampling factor but I believe thats for sampling from video according to docs sampling factor is 1 for images which loads the whole dataset for training. Once the ground truth data is loaded from the mat file generated from ImageLabeller how do i partion it say 80/20?


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Answers (1)

Sai Bhargav Avula
Sai Bhargav Avula on 31 Oct 2019
You can split the data from the mat file generated using Image Labeler by using the imageDatastore function.
The code structure would look like this
DatasetPath = fullfile(matlabroot,'your path');
imds = imageDatastore(DatasetPath,'IncludeSubfolders',true,'FileExtensions','.mat','LabelSource','foldernames','ReadFcn',@loadmydata);
[imdsTrain,imdsTest] = splitEachLabel(imds,0.8,'randomize');
function data = loadmydata(filename)
S = load(filename);
data =;
Hope this helps !


Hamza Yerlikaya
Hamza Yerlikaya on 31 Oct 2019
Thanks for the response. I will try this but in the mean time I have come up with the following solution. Just wanted to make sure if I am on the right track. It seems to to the trick.
PD = 0.20;
cv = cvpartition(size(gTruth.LabelData,1),'HoldOut',PD)
trainGroundTruth = ...
groundTruth(groundTruthDataSource(gTruth.DataSource.Source(,:)), ...
gTruth.LabelDefinitions, ...
testGroundTruth = ...
groundTruth(groundTruthDataSource(gTruth.DataSource.Source(cv.test,:)), ...
gTruth.LabelDefinitions, ...
Sai Bhargav Avula
Sai Bhargav Avula on 1 Nov 2019
Yes, cvpartition is one way. One thing you need to look is the NumTestSets. I think you might have already looked into this. But just attaching the link as reference.

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