Class LFWDataSetIterator
- java.lang.Object
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- org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
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- org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
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- 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
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Nested Class Summary
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Nested classes/interfaces inherited from class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
RecordReaderDataSetIterator.Builder
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Field Summary
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Fields inherited from class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
batchNum, batchSize, converter, labelIndex, labelIndexTo, last, maxNumBatches, numPossibleLabels, preProcessor, recordReader, regression, sequenceIter, useCurrent
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Constructor Summary
Constructors Constructor 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, 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, ImageTransform imageTransform, Random rng)
Create LFW data specific iteratorLFWDataSetIterator(int batchSize, int numExamples, int numLabels, boolean train, double splitTrainTest)
Loads images with given batchSize, numExamples, numLabels, train, & splitTrainTest returned by the generator.
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Method Summary
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Methods inherited from class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
asyncSupported, batch, getLabels, getPreProcessor, getRecordReader, hasNext, inputColumns, isCollectMetaData, loadFromMetaData, loadFromMetaData, next, next, remove, reset, resetSupported, setCollectMetaData, setPreProcessor, totalOutcomes
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Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface java.util.Iterator
forEachRemaining
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Constructor Detail
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LFWDataSetIterator
public LFWDataSetIterator(int[] imgDim)
Loads subset of images with given imgDim returned by the generator.
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LFWDataSetIterator
public LFWDataSetIterator(int batchSize, int numExamples)
Loads images with given batchSize, numExamples returned by the generator.
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LFWDataSetIterator
public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim)
Loads images with given batchSize, numExamples, imgDim returned by the generator.
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LFWDataSetIterator
public LFWDataSetIterator(int batchSize, int[] imgDim, boolean useSubset)
Loads images with given batchSize, imgDim, useSubset, returned by the generator.
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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.
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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.
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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.
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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.
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LFWDataSetIterator
public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, int numLabels, boolean useSubset, org.datavec.api.io.labels.PathLabelGenerator labelGenerator, boolean train, double splitTrainTest, ImageTransform imageTransform, Random rng)
Create LFW data specific iterator- Parameters:
batchSize
- the batch size of the examplesnumExamples
- the overall number of examplesimgDim
- an array of height, width and channelsnumLabels
- the overall number of examplesuseSubset
- use a subset of the LFWDataSetlabelGenerator
- path label generator to usetrain
- true if use train valuesplitTrainTest
- the percentage to split data for train and remainder goes to testimageTransform
- how to transform the imagerng
- random number to lock in batch shuffling
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