org.openimaj.image.model.pixel

Class PixelClassificationModel<Q,T extends Image<Q,T>>

java.lang.Object

org.openimaj.image.model.pixel.PixelClassificationModel<Q,T>

Type Parameters:

Q - Type of pixel

T - Type of image

All Implemented Interfaces:

Serializable, Cloneable, ImageClassificationModel<T>, EstimatableModel<T,FImage>, Model<T,FImage>

Direct Known Subclasses:

MBFPixelClassificationModel

public abstract class PixelClassificationModel<Q,T extends Image<Q,T>>
extends Object
implements ImageClassificationModel<T>

Simple model for classifying pixels. When learning assumes ALL provided sample pixels are positive exemplars, and that anything not given is negative.

Author:

Jonathon Hare

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
PixelClassificationModel()

Method Summary

Methods

Modifier and Type	Method and Description
FImage	classifyImage(T im) Classify the given image and return the corresponding probability map
protected abstract float	classifyPixel(Q pix)
abstract PixelClassificationModel<Q,T>	clone() Clone the model
boolean	estimate(List<? extends IndependentPair<T,FImage>> data) Estimates the model from the observations in the list of data.
protected abstract T[]	getArray(int length)
int	numItemsToEstimate()
FImage	predict(T data) Uses the model to predict dependent data from an independent value.

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.openimaj.image.model.ImageClassificationModel

learnModel

Constructor Detail

PixelClassificationModel

public PixelClassificationModel()

Method Detail

classifyPixel

protected abstract float classifyPixel(Q pix)

classifyImage

public FImage classifyImage(T im)

Description copied from interface: ImageClassificationModel

Classify the given image and return the corresponding probability map

Specified by:

classifyImage in interface ImageClassificationModel<T extends Image<Q,T>>

Parameters:

im - the image to classify

Returns:

the probability map

getArray

protected abstract T[] getArray(int length)

estimate

public boolean estimate(List<? extends IndependentPair<T,FImage>> data)

Description copied from interface: EstimatableModel

Estimates the model from the observations in the list of data. The data must contain at least EstimatableModel.numItemsToEstimate() pairs of dependent and independent data. It may contain more, in which case the estimate method may choose to make use of this data for validation, or obtaining a better model by a least squares method for example.

Specified by:

estimate in interface EstimatableModel<T extends Image<Q,T>,FImage>

Parameters:

data - Data with which to estimate the model

Returns:

true if a successful estimate was made, false otherwise

See Also:

EstimatableModel.numItemsToEstimate()

numItemsToEstimate

public int numItemsToEstimate()

Specified by:

numItemsToEstimate in interface EstimatableModel<T extends Image<Q,T>,FImage>

Returns:

The minimum number of observations required to estimate the model.

predict

public FImage predict(T data)

Description copied from interface: Model

Uses the model to predict dependent data from an independent value.

Specified by:

predict in interface Model<T extends Image<Q,T>,FImage>

Parameters:

data - the data (independent variable)

Returns:

Dependent variable(s) predicted from the independent ones.

clone

public abstract PixelClassificationModel<Q,T> clone()

Description copied from interface: EstimatableModel

Clone the model

Specified by:

clone in interface ImageClassificationModel<T extends Image<Q,T>>

Specified by:

clone in interface EstimatableModel<T extends Image<Q,T>,FImage>

Overrides:

clone in class Object

Returns:

a cloned copy