Java example source code file (LFWDataSetIterator.java)

This example Java source code file (LFWDataSetIterator.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" ^TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

imagetransform, lfwdatasetiterator, lfwloader, pathlabelgenerator, random, recordreaderdatasetiterator, util

The LFWDataSetIterator.java Java example source code

/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://www.apache.org/licenses/LICENSE-2.0
 *  *
 *  *    Unless required by applicable law or agreed to in writing, software
 *  *    distributed under the License is distributed on an "AS IS" BASIS,
 *  *    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  *    See the License for the specific language governing permissions and
 *  *    limitations under the License.
 *
 */

package org.deeplearning4j.datasets.iterator.impl;

import org.canova.api.io.labels.PathLabelGenerator;
import org.canova.image.loader.LFWLoader;
import org.canova.image.transform.ImageTransform;
import org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator;

import java.util.Random;


public class LFWDataSetIterator extends RecordReaderDataSetIterator {

	/** Loads subset of images with given imgDim returned by the generator. */
	public LFWDataSetIterator(int[] imgDim) {
		this(LFWLoader.SUB_NUM_IMAGES, LFWLoader.SUB_NUM_IMAGES, imgDim, LFWLoader.SUB_NUM_LABELS, false, null, true, 1, null, 0, new Random(System.currentTimeMillis()));
	}

	/** Loads images with given  batchSize, numExamples returned by the generator. */
	public LFWDataSetIterator(int batchSize, int numExamples) {
        this(batchSize, numExamples, new int[] {LFWLoader.HEIGHT, LFWLoader.WIDTH, LFWLoader.CHANNELS}, LFWLoader.NUM_LABELS, false, LFWLoader.LABEL_PATTERN, true, 1, null, 0, new Random(System.currentTimeMillis()));
	}

	/** Loads images with given  batchSize, numExamples, imgDim returned by the generator. */
	public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim) {
        this(batchSize, numExamples, imgDim, LFWLoader.NUM_LABELS, false, LFWLoader.LABEL_PATTERN, true, 1, null, 0, new Random(System.currentTimeMillis()));
	}

    /** Loads images with given  batchSize, imgDim, useSubset, returned by the generator. */
    public LFWDataSetIterator(int batchSize, int[] imgDim, boolean useSubset)  {
        this(batchSize, useSubset ? LFWLoader.SUB_NUM_IMAGES :LFWLoader.NUM_IMAGES, imgDim, useSubset ? LFWLoader.SUB_NUM_LABELS : LFWLoader.NUM_LABELS, useSubset, LFWLoader.LABEL_PATTERN, true, 1, null, 0, new Random(System.currentTimeMillis()));
    }

    /** Loads images with given  batchSize, numExamples, imgDim, train, & splitTrainTest returned by the generator. */
	public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, boolean train, double splitTrainTest) {
        this(batchSize, numExamples, imgDim, LFWLoader.NUM_LABELS, false, LFWLoader.LABEL_PATTERN, train, splitTrainTest, null, 0, new Random(System.currentTimeMillis()));
	}

	/** Loads images with given  batchSize, numExamples, numLabels, train, & splitTrainTest returned by the generator. */
	public LFWDataSetIterator(int batchSize, int numExamples, int numLabels, boolean train, double splitTrainTest) {
        this(batchSize, numExamples, new int[] {LFWLoader.HEIGHT, LFWLoader.WIDTH, LFWLoader.CHANNELS}, numLabels, false, null, train, splitTrainTest, null, 0, new Random(System.currentTimeMillis()));
	}

	/** Loads images with given  batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator. */
    public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, int numLabels, boolean useSubset, boolean train,  double splitTrainTest,  Random rng) {
        this(batchSize, numExamples, imgDim, numLabels, useSubset, LFWLoader.LABEL_PATTERN, train, splitTrainTest, null, 0, rng);
    }

    /** Loads images with given  batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator. */
    public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, int numLabels, boolean useSubset, PathLabelGenerator labelGenerator, boolean train, double splitTrainTest,  Random rng) {
        this(batchSize, numExamples, imgDim, numLabels, useSubset, labelGenerator, train, splitTrainTest, null, 0, rng);
    }

	/**
	 * Create LFW data specific iterator
	 * @param batchSize the batch size of the examples
     * @param numExamples the overall number of examples
	 * @param imgDim an array of height, width and channels
	 * @param numLabels the overall number of examples
     * @param useSubset use a subset of the LFWDataSet
     * @param labelGenerator path label generator to use
     * @param train true if use train value
     * @param splitTrainTest the percentage to split data for train and remainder goes to test
     * @param imageTransform how to transform the image
     * @param normalizeValue value to divide pixels by to normalize
     * @param rng random number to lock in batch shuffling
	 * */
	public LFWDataSetIterator(int batchSize, int numExamples, int[] imgDim, int numLabels, boolean useSubset, PathLabelGenerator labelGenerator, boolean train, double splitTrainTest, ImageTransform imageTransform, int normalizeValue, Random rng) {
		super(new LFWLoader(imgDim, imageTransform, normalizeValue, useSubset).getRecordReader(numExamples, batchSize, imgDim, numLabels, labelGenerator, train, splitTrainTest, rng), batchSize, 1, numLabels);
	}

}