Java Deep Learning Cookbook

How to do it...

1. Use FileSplit to define the range of files to load into the neural network:

FileSplit fileSplit = new FileSplit(parentDir, NativeImageLoader.ALLOWED_FORMATS,new Random(42)); int numLabels = fileSplit.getRootDir().listFiles(File::isDirectory).length;

2. Use ParentPathLabelGenerator and BalancedPathFilter to sample the labeled dataset and split it into train/test sets:

ParentPathLabelGenerator parentPathLabelGenerator = new ParentPathLabelGenerator(); BalancedPathFilter balancedPathFilter = new BalancedPathFilter(new Random(42),NativeImageLoader.ALLOWED_FORMATS,parentPathLabelGenerator); InputSplit[] inputSplits = fileSplit.sample(balancedPathFilter,trainSetRatio,testSetRatio);