VFSGroupDataset<FImage> dataset = new VFSGroupDataset<FImage>(
"zip:file:/Users/nhnguyen/Data/newArchive.zip",
ImageUtilities.FIMAGE_READER);
int nTraining = 50;
int nTesting = 5;
GroupedRandomSplitter<String, FImage> splits =
new GroupedRandomSplitter<String, FImage>(dataset, nTraining, 0, nTesting);
GroupedDataset<String, ListDataset<FImage>, FImage> training = splits.getTrainingDataset();
GroupedDataset<String, ListDataset<FImage>, FImage> testing = splits.getTestDataset();
List<FImage> basisImages = DatasetAdaptors.asList(training);
int nEigenvectors = 100;
EigenImages eigen = new EigenImages(nEigenvectors);
eigen.train(basisImages);
I have the above code to test the EigenImages tutorial with my own set of data. What I am stuck at is that it would throw Exception with Matrix if in my data set, images are varies of dimension, say 92x112 and 100x100 and so on... When I do a batch resize to a same size then it work, however, these distort the image a little bit which I worried will affect the accuracy. Is there away to train the eigen recognize to accept input with various dimension?