public class LFWDataSetIterator extends RecordReaderDataSetIterator
batchNum, batchSize, converter, labelIndex, labelIndexTo, last, maxNumBatches, numPossibleLabels, preProcessor, recordReader, regression, sequenceIter, useCurrent
Constructor and Description |
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LFWDataSetIterator(int[] imgDim)
Loads subset of images with given imgDim returned by the generator.
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LFWDataSetIterator(int batchSize,
int numExamples)
Loads images with given batchSize, numExamples returned by the generator.
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LFWDataSetIterator(int batchSize,
int[] imgDim,
boolean useSubset)
Loads images with given batchSize, imgDim, useSubset, returned by the generator.
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LFWDataSetIterator(int batchSize,
int numExamples,
int[] imgDim)
Loads images with given batchSize, numExamples, imgDim returned by the generator.
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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(int batchSize,
int numExamples,
int[] imgDim,
int numLabels,
boolean useSubset,
boolean train,
double splitTrainTest,
java.util.Random rng)
Loads images with given batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator.
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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,
java.util.Random rng)
Create LFW data specific iterator
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LFWDataSetIterator(int batchSize,
int numExamples,
int[] imgDim,
int numLabels,
boolean useSubset,
org.datavec.api.io.labels.PathLabelGenerator labelGenerator,
boolean train,
double splitTrainTest,
java.util.Random rng)
Loads images with given batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator.
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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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asyncSupported, batch, cursor, getLabels, hasNext, inputColumns, loadFromMetaData, loadFromMetaData, next, next, numExamples, remove, reset, resetSupported, setPreProcessor, totalExamples, totalOutcomes
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
public LFWDataSetIterator(int[] imgDim)
public LFWDataSetIterator(int batchSize, int numExamples)
public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim)
public LFWDataSetIterator(int batchSize, int[] imgDim, boolean useSubset)
public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, boolean train, double splitTrainTest)
public LFWDataSetIterator(int batchSize, int numExamples, int numLabels, boolean train, double splitTrainTest)
public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, int numLabels, boolean useSubset, boolean train, double splitTrainTest, java.util.Random rng)
public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, int numLabels, boolean useSubset, org.datavec.api.io.labels.PathLabelGenerator labelGenerator, boolean train, double splitTrainTest, java.util.Random rng)
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, java.util.Random rng)
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