Class Cifar10DataSetIterator
- java.lang.Object
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- org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
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- org.deeplearning4j.datasets.iterator.impl.Cifar10DataSetIterator
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- All Implemented Interfaces:
Serializable
,Iterator<org.nd4j.linalg.dataset.DataSet>
,org.nd4j.linalg.dataset.api.iterator.DataSetIterator
public class Cifar10DataSetIterator 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
Fields Modifier and Type Field Description protected org.nd4j.linalg.dataset.api.DataSetPreProcessor
preProcessor
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Fields inherited from class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
batchNum, batchSize, converter, labelIndex, labelIndexTo, last, maxNumBatches, numPossibleLabels, recordReader, regression, sequenceIter, useCurrent
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Constructor Summary
Constructors Constructor Description Cifar10DataSetIterator(int batchSize)
Create an iterator for the training set, with random iteration order (RNG seed fixed to 123)Cifar10DataSetIterator(int batchSize, int[] imgDim, DataSetType set)
Get the Tiny ImageNet iterator with specified train/test set, with random iteration order (RNG seed fixed to 123)Cifar10DataSetIterator(int batchSize, int[] imgDim, DataSetType set, ImageTransform imageTransform, long rngSeed)
Get the Tiny ImageNet iterator with specified train/test set and (optional) custom transform.Cifar10DataSetIterator(int batchSize, DataSetType set)
* Create an iterator for the training or test set, with random iteration order (RNG seed fixed to 123)
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method Description static List<String>
getLabels(boolean categories)
Get the labels - either in "categories" (imagenet synsets format, "n01910747" or similar) or human-readable format, such as "jellyfish"-
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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Cifar10DataSetIterator
public Cifar10DataSetIterator(int batchSize)
Create an iterator for the training set, with random iteration order (RNG seed fixed to 123)- Parameters:
batchSize
- Minibatch size for the iterator
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Cifar10DataSetIterator
public Cifar10DataSetIterator(int batchSize, DataSetType set)
* Create an iterator for the training or test set, with random iteration order (RNG seed fixed to 123)- Parameters:
batchSize
- Minibatch size for the iteratorset
- The dataset (train or test)
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Cifar10DataSetIterator
public Cifar10DataSetIterator(int batchSize, int[] imgDim, DataSetType set)
Get the Tiny ImageNet iterator with specified train/test set, with random iteration order (RNG seed fixed to 123)- Parameters:
batchSize
- Size of each patchimgDim
- Dimensions of desired output - for example, {64, 64}set
- Train, test, or validation
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Cifar10DataSetIterator
public Cifar10DataSetIterator(int batchSize, int[] imgDim, DataSetType set, ImageTransform imageTransform, long rngSeed)
Get the Tiny ImageNet iterator with specified train/test set and (optional) custom transform.- Parameters:
batchSize
- Size of each patchimgDim
- Dimensions of desired output - for example, {64, 64}set
- Train, test, or validationimageTransform
- Additional image transform for outputrngSeed
- random number generator seed to use when shuffling examples
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Method Detail
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getLabels
public static List<String> getLabels(boolean categories)
Get the labels - either in "categories" (imagenet synsets format, "n01910747" or similar) or human-readable format, such as "jellyfish"- Parameters:
categories
- If true: return category/synset format; false: return "human readable" label format- Returns:
- Labels
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