org.deeplearning4j.datasets.iterator.impl

Class LFWDataSetIterator

java.lang.Object

org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator

org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator

All Implemented Interfaces:

Serializable, Iterator<org.nd4j.linalg.dataset.DataSet>, org.nd4j.linalg.dataset.api.iterator.DataSetIterator

public class LFWDataSetIterator
extends RecordReaderDataSetIterator

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator

RecordReaderDataSetIterator.Builder

Field Summary

Fields inherited from class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator

batchNum, batchSize, converter, labelIndex, labelIndexTo, last, maxNumBatches, numPossibleLabels, preProcessor, recordReader, regression, sequenceIter, useCurrent

Constructor Summary

Constructors

Constructor and Description
LFWDataSetIterator(int[] imgDim) Loads subset of images with given imgDim returned by the generator.
LFWDataSetIterator(int batchSize, int numExamples) Loads images with given batchSize, numExamples returned by the generator.
LFWDataSetIterator(int batchSize, int[] imgDim, boolean useSubset) Loads images with given batchSize, imgDim, useSubset, returned by the generator.
LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim) Loads images with given batchSize, numExamples, imgDim returned by the generator.
LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, boolean train, double splitTrainTest) Loads images with given batchSize, numExamples, imgDim, train, & splitTrainTest returned by the generator.
LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, int numLabels, boolean useSubset, boolean train, double splitTrainTest, Random rng) Loads images with given batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator.
LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, int numLabels, boolean useSubset, org.datavec.api.io.labels.PathLabelGenerator labelGenerator, boolean train, double splitTrainTest, org.datavec.image.transform.ImageTransform imageTransform, Random rng) Create LFW data specific iterator
LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, int numLabels, boolean useSubset, org.datavec.api.io.labels.PathLabelGenerator labelGenerator, boolean train, double splitTrainTest, Random rng) Loads images with given batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator.
LFWDataSetIterator(int batchSize, int numExamples, int numLabels, boolean train, double splitTrainTest) Loads images with given batchSize, numExamples, numLabels, train, & splitTrainTest returned by the generator.

Method Summary

Methods inherited from class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator

asyncSupported, batch, cursor, getLabels, getPreProcessor, hasNext, inputColumns, isCollectMetaData, loadFromMetaData, loadFromMetaData, next, next, numExamples, remove, reset, resetSupported, setCollectMetaData, setPreProcessor, totalExamples, totalOutcomes

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface java.util.Iterator

forEachRemaining

Constructor Detail

LFWDataSetIterator

public LFWDataSetIterator(int[] imgDim)

Loads subset of images with given imgDim returned by the generator.

LFWDataSetIterator

public LFWDataSetIterator(int batchSize,
                          int numExamples)

Loads images with given batchSize, numExamples returned by the generator.

LFWDataSetIterator

public LFWDataSetIterator(int batchSize,
                          int numExamples,
                          int[] imgDim)

Loads images with given batchSize, numExamples, imgDim returned by the generator.

LFWDataSetIterator

public LFWDataSetIterator(int batchSize,
                          int[] imgDim,
                          boolean useSubset)

Loads images with given batchSize, imgDim, useSubset, returned by the generator.

LFWDataSetIterator

public LFWDataSetIterator(int batchSize,
                          int numExamples,
                          int[] imgDim,
                          boolean train,
                          double splitTrainTest)

Loads images with given batchSize, numExamples, imgDim, train, & splitTrainTest returned by the generator.

LFWDataSetIterator

public LFWDataSetIterator(int batchSize,
                          int numExamples,
                          int numLabels,
                          boolean train,
                          double splitTrainTest)

Loads images with given batchSize, numExamples, numLabels, train, & splitTrainTest returned by the generator.

LFWDataSetIterator

public LFWDataSetIterator(int batchSize,
                          int numExamples,
                          int[] imgDim,
                          int numLabels,
                          boolean useSubset,
                          boolean train,
                          double splitTrainTest,
                          Random rng)

Loads images with given batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator.

LFWDataSetIterator

public LFWDataSetIterator(int batchSize,
                          int numExamples,
                          int[] imgDim,
                          int numLabels,
                          boolean useSubset,
                          org.datavec.api.io.labels.PathLabelGenerator labelGenerator,
                          boolean train,
                          double splitTrainTest,
                          Random rng)

Loads images with given batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator.

LFWDataSetIterator

public LFWDataSetIterator(int batchSize,
                          int numExamples,
                          int[] imgDim,
                          int numLabels,
                          boolean useSubset,
                          org.datavec.api.io.labels.PathLabelGenerator labelGenerator,
                          boolean train,
                          double splitTrainTest,
                          org.datavec.image.transform.ImageTransform imageTransform,
                          Random rng)

Create LFW data specific iterator

Parameters:

batchSize - the batch size of the examples

numExamples - the overall number of examples

imgDim - an array of height, width and channels

numLabels - the overall number of examples

useSubset - use a subset of the LFWDataSet

labelGenerator - path label generator to use

train - true if use train value

splitTrainTest - the percentage to split data for train and remainder goes to test

imageTransform - how to transform the image

rng - random number to lock in batch shuffling