Class LFWDataSetIterator

    • 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,
                                  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