/*
* Encog(tm) Core v3.4 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2016 Heaton Research, 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.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.platformspecific.j2se.data.image;
import org.encog.ml.data.MLDataPair;
import org.encog.ml.data.basic.BasicMLDataSet;
import org.encog.neural.NeuralNetworkError;
import org.encog.util.downsample.Downsample;
/**
* Store a collection of images for training with a neural network. This class
* collects and then downsamples images for use with a neural network. This is a
* memory based class, so large datasets can run out of memory.
*
* @author jheaton
*/
public class ImageMLDataSet extends BasicMLDataSet {
/**
* The serial id.
*/
private static final long serialVersionUID = 3368190842312829906L;
/**
* Error message to inform the caller that only ImageNeuralData objects can
* be used with this collection.
*/
public static final String MUST_USE_IMAGE
= "This data set only supports ImageNeuralData or Image objects.";
/**
* The downsampler to use.
*/
private final Downsample downsampler;
/**
* The height to downsample to.
*/
private int height;
/**
* The width to downsample to.
*/
private int width;
/**
* Should the bounds be found and cropped.
*/
private final boolean findBounds;
/**
* The high value to normalize to.
*/
private final double hi;
/**
* The low value to normalize to.
*/
private final double lo;
/**
* Construct this class with the specified downsampler.
*
* @param theDownsampler
* The downsampler to use.
* @param theFindBounds
* Should the bounds be found and clipped.
* @param theHi
* The high value to normalize to.
* @param theLo
* The low value to normalize to.
*/
public ImageMLDataSet(final Downsample theDownsampler,
final boolean theFindBounds,
final double theHi, final double theLo) {
this.downsampler = theDownsampler;
this.findBounds = theFindBounds;
this.height = -1;
this.width = -1;
this.hi = theHi;
this.lo = theLo;
}
/**
* Downsample all images and generate training data.
*
* @param theHeight
* The height to downsample to.
* @param theWidth
* the width to downsample to.
*/
public final void downsample(final int theHeight, final int theWidth) {
this.height = theHeight;
this.width = theWidth;
for (final MLDataPair pair : this) {
if (!(pair.getInput() instanceof ImageMLData)) {
throw new NeuralNetworkError(
"Invalid class type found in ImageNeuralDataSet, only "
+ "ImageNeuralData items are allowed.");
}
final ImageMLData input = (ImageMLData) pair.getInput();
input.downsample(this.downsampler, this.findBounds, height, width,
this.hi, this.lo);
}
}
/**
* @return the height
*/
public final int getHeight() {
return this.height;
}
/**
* @return the width
*/
public final int getWidth() {
return this.width;
}
}