MATLAB: How to split an image datastore for cross-validation

Question

Hello,

The method

splitEachLabel

of an

imageDatastore

object splits an image data store into proportions per category label. How can one split an image data store for training using cross-validation and using the

trainImageCategoryCalssifier

class?

I.e. it's easy to split it in N partitions, but then some sort of mergeEachLabel functionality is needed to be able to train a classifier using cross-validation. Or is there another way of achieving that?

Regards, Elena

Answer 1

[imd1 imd2 imd3 imd4 imd5 imd6 imd7 imd8 imd9 imd10] = splitEachLabel(imds,0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1,'randomize');
partStores{1} = imd1.Files ;
partStores{2} = imd2.Files ;
partStores{3} = imd3.Files ;
partStores{4} = imd4.Files ;
partStores{5} = imd5.Files ;
partStores{6} = imd6.Files ;
partStores{7} = imd7.Files ;
partStores{8} = imd8.Files ;
partStores{9} = imd9.Files ;
partStores{10} = imd10.Files; 
for i = 1 :k
    i
    test_idx = (idx == i);
    train_idx = ~test_idx;
      imdsTest = imageDatastore(partStores{test_idx}, 'IncludeSubfolders', true,'FileExtensions','.jpeg', 'LabelSource', 'foldernames');
      imdsTrain = imageDatastore(cat(1, partStores{train_idx}), 'IncludeSubfolders', true,'FileExtensions','.jpeg', 'LabelSource', 'foldernames');
  %%%%%%%%%%%%%%%%%%%%%%%%%


  %%%%%%%%%%%%%%%%%%%%%%%%%
  %%%%%%%%%%%%%%%%%%%%%%%%%
  %%%%%Write your classification task
  %%%%hamzamehboob103@gmail.com for any further help. 
  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  }