Package gov.nih.mipav.model.algorithms

Class libdt

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.libdt

All Implemented Interfaces:

ActionListener, WindowListener, Runnable, EventListener

public class libdt
extends AlgorithmBase

libdt - OpenCV library for Dynamic Textures - version 1.0 Copyright (c) 2011-2014 Antoni B. Chan, Adeel Mumtaz, City University of Hong Kong All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither name of copyright holders nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Modeling, clustering, and segmenting video with mixtures of dynamic textures. Antoni B. Chan and Nuno Vasconcelos, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 30(5):909-926, May 2008. Clustering Dynamic Textures with the Hierarchical EM Algorithm for Modeling Video. Adeel Mumtaz, Emanuele Coviello, Gert R.G. Lanckriet, and Antoni B. Chan, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 35(7):1606-1621, Jul 2013. [appendix] A Scalable and Accurate Descriptor for Dynamic Textures using Bag of System Trees. Adeel Mumtaz, Emanuele Coviello, Gert R.G. Lanckriet, and Antoni B. Chan, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 37(4):697-712, Apr 2015. [appendix]

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
(package private) class	libdt.ConfigFile
static enum	libdt.cov_reg_type	regularization method.
static enum	libdt.cov_type	type of covariance matrix.
class	libdt.CovMatrix
(package private) class	libdt.DatDescriptor	Structure to represent Dat file Descriptor parameters
class	libdt.Dytex	Dynamic Texture class.
(package private) class	libdt.DytexKalmanFilter	class for running the Kalman filter for dynamic texture inference.
class	libdt.DytexMix
class	libdt.DytexOptions
class	libdt.DytexRegOptions	Class for specifying the regularization methods for a Dytex.
class	libdt.DytexSplitParams
(package private) class	libdt.EMOptions
(package private) class	libdt.Estats
(package private) static enum	libdt.fill_type
class	libdt.HEMOptions
private class	libdt.indexValueComparator
private class	libdt.indexValueItem
static enum	libdt.kf_mode
class	libdt.Mat
(package private) static enum	libdt.norm_type	Normalization mode for each patch.
(package private) class	libdt.PatchBatchExtractor	Class for extracting spatio-temporal patches (cubes) from a video (batch mode).
(package private) class	libdt.PatchExtractor	Class for extracting spatio-temporal patches (cubes) from a video (online mode).
(package private) class	libdt.PatchOptions	Class for specifying spatio-temporal patches (cubes).
(package private) class	libdt.Range
static enum	libdt.Split_crit
static enum	libdt.Split_mode
static enum	libdt.Split_vars
static enum	libdt.Verbose_mode
(package private) class	libdt.VidSegm
(package private) class	libdt.VidSeqSegmParams
static enum	libdt.Ymean_type	Options for modeling the observation mean, Ymean.

Nested classes/interfaces inherited from class java.lang.Thread

Thread.Builder, Thread.State, Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private final byte[]	byteDoubleBuffer	byte array for double *
private final byte[]	byteIntBuffer	byte array for int *
private final byte[]	byteLongBuffer	byte array for long *
private final int	CV_64F
private final int	CV_64FC
private final int	CV_64FC1
private final int	CV_64FC3
private final int	CV_8U
private final int	CV_8UC
private final int	CV_8UC1
private final int	CV_REDUCE_AVG
private final int	CV_REDUCE_MAX
private final int	CV_REDUCE_MIN
private final int	CV_REDUCE_SUM
private boolean	debug
private boolean	endian
private libdt.Mat[][]	g_mask_lut
private double[][]	g_rgbtable
private final int	MAXCOL
private RandomAccessFile	raFile

Fields inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

destFlag, destImage, image25D, mask, maxProgressValue, minProgressValue, multiThreadingEnabled, nthreads, progress, progressModulus, progressStep, runningInSeparateThread, separable, srcImage, threadStopped

Fields inherited from class java.lang.Thread

MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Constructors

Constructor	Description
libdt()

Method Summary

Modifier and Type	Method	Description
(package private) boolean	addFrames(libdt.PatchExtractor pe, libdt.Mat[] invid)
(package private) void	annotateVideos()
(package private) void	calculate(libdt.CovMatrix cov, libdt.Mat data, boolean use_unbiased)
(package private) int	checkOptionInStr(String str, String opt)
libdt.Mat	clone(libdt.Mat A)
libdt.Mat	col(libdt.Mat A, int colNum)
(package private) void	colorMask(libdt.Mat[] img, libdt.Mat[] mask, libdt.Mat oimg, int border)
private void	computeAggregateStats(libdt.Estats Estat, libdt.Mat W)
private void	computeEll(libdt.Estats Estat)
(package private) void	computePrecisionRecall()
(package private) double	computeVariance3dDouble(libdt.Mat[] input)
(package private) libdt.Mat	convertmovie(libdt.Mat[] Y, int[] sx, int[] sy, int[] sc, int[] cnorm)
private void	copyFromSrcColRange(libdt.Mat A, libdt.Mat B, int inclusiveStart, int exclusiveEnd)
private void	copyTo(libdt.Mat[] A, libdt.Mat[] B)
private void	copyTo(libdt.Mat A, libdt.Mat B)
private void	copyToDstColRange(libdt.Mat A, libdt.Mat B, int inclusiveStart, int exclusiveEnd)
int	countNonZero(libdt.Mat A)
private libdt.Mat[]	create(int frames, int rows, int cols, int type)
libdt.Mat	divide(libdt.Mat A, double q)
libdt.Mat	divide(libdt.Mat A, libdt.Mat B)
(package private) void	dumpMatSize(libdt.Mat[] m)
void	dytex_kalman(libdt.Mat[] Y2, libdt.Dytex dt, String opt, Vector<libdt.Mat> xt, libdt.Mat[] Vt, libdt.Mat[] Vt1, libdt.Mat L)
private void	dytex_mix_split(libdt.DytexMix dtm, libdt.DytexSplitParams splitopt, int[] ctg, int[] csp)
private void	dytex_perturb(libdt.Dytex dtp, double pert, libdt.Split_mode mode, libdt.Split_vars vars)
libdt.Mat	elementTimes(libdt.Mat A, libdt.Mat B)
(package private) Vector<libdt.Mat>	extractY(libdt.Mat[] Yin, Vector<Integer> inds)
private libdt.Mat	frame(libdt.Mat vid, int f)
void	getClasses(libdt.DytexMix dtm, Vector<libdt.Mat> Y, libdt.Mat LLm)
void	getClasses(libdt.DytexMix dtm, Vector<libdt.Mat> Y, Vector<Integer> classes)
libdt.cov_reg_type	getCov_reg_type(int cov_reg_code)
libdt.cov_type	getCov_type(int cov_code)
final double	getDouble(boolean bigEndian)	Reads eight unsigned bytes from file.
final int	getInt(boolean bigEndian)	Reads four signed bytes from file.
libdt.norm_type	getNorm_type(int norm_code)
(package private) Vector<libdt.Mat[]>	getPatches(libdt.PatchExtractor pe)
(package private) Vector<Integer>	getTagVids(Vector<Integer> trainVidIds, String tag, Vector<Vector<String>> annlist)
private String	getTime()
libdt.Ymean_type	getYmean_type(int Ymean_code)
private libdt.Dytex	init_multiple_dt(libdt.DytexMix dtm)
(package private) libdt.Dytex	initcluster_doretto(Vector<libdt.Mat> Y, libdt.DytexOptions param)
private boolean	inp_minbnd(double[][] arr, double min_bnd)
private boolean	inp_minbnd(double[] arr, double min_bnd)
(package private) libdt.CovMatrix	inv(libdt.CovMatrix cov)
(package private) void	learnBaseDTM()
(package private) void	learnBaseDTMBoS()
(package private) void	learnDTM(libdt.VidSegm tvs, String vpath, boolean dosegm)
(package private) void	learnLeastSquares(libdt.Dytex mydt, Vector<libdt.Mat> videos)
(package private) void	learnTagDTM()
(package private) void	learnWithSplitting(libdt.DytexMix dtm, Vector<libdt.Mat[]> Yin, libdt.EMOptions emopt)
(package private) libdt.Mat[]	loaddat(String filename, String opt)
(package private) libdt.DatDescriptor	loaddatinfo(String filename, int verbose)
(package private) double	logdetiid(libdt.Mat Q, double r, int C)
(package private) libdt.Mat	logtrick(libdt.Mat lA)
(package private) libdt.Mat	mask2Border(libdt.Mat mask, int border, byte[] mask_flag)
(package private) libdt.Mat[]	maxvotefilt(libdt.Mat[] I, int sx, int sy, int sz, int numclass)
(package private) double	meanOfStdVector(Vector<Double> v)
(package private) double	minOfStdVector(Vector<Double> v)
libdt.Mat	minus(libdt.Mat A, double b)
libdt.Mat	minus(libdt.Mat A, libdt.Mat B)
(package private) void	mulTransposed(libdt.Mat src, libdt.Mat dst, boolean transposeFirst)
(package private) double	norm2(libdt.Mat[] vid)
libdt.Mat	plus(libdt.Mat A, double b)
libdt.Mat	plus(libdt.Mat A, libdt.Mat B)
(package private) Vector<Double>	plus(Vector<Double> a, Vector<Double> b)
(package private) void	postmultiply(libdt.CovMatrix cov, libdt.Mat src, libdt.Mat dst)
private void	ppertC(libdt.Mat C, libdt.Mat S0, double pert)
(package private) void	printResults()
(package private) void	processNextPatch(libdt.PatchExtractor pe)
(package private) void	processVideoTesting(libdt.Dytex dt, libdt.Mat vin, libdt.Mat Yout)
(package private) void	processVideoTraining(libdt.Dytex mydt, libdt.Mat vin, libdt.Mat Yout, libdt.Mat Yout_mean)
void	read(libdt.CovMatrix cm)
void	read(libdt.Dytex dt)
void	read(libdt.DytexMix dtm)
void	read(libdt.DytexOptions opt)
void	read(String name, boolean[] val)
void	read(String name, byte[] val)
void	read(String name, double[] val)
void	read(String name, int[] val)
void	read(String name, libdt.Mat mtx)
void	read(String name, Vector<Integer> vec)
void	read(javax.vecmath.Point3i p)
(package private) void	readGtruthFile(String fpath, Vector<String> vlist, Vector<Vector<String>> annlist, Vector<String> taglist)
void	readHeader(String str)
(package private) void	readTrialInfo(String fpath, Vector<Vector<Integer>> trainVidIds, Vector<Vector<Integer>> testVidIds)
(package private) void	readVecDouble(String name, Vector<Double> vec)
void	readVectorString(String name, Vector<String> vec)
(package private) void	readVecVecDouble(String name, Vector<Vector<Double>> vec)
private void	reduce(libdt.Mat[] vid, libdt.Mat out, int reduceOp)
private void	reduce(libdt.Mat src, libdt.Mat dst, int dim, int rtype)
private libdt.DytexMix	reduceWithSplitting(libdt.DytexMix dtm, libdt.HEMOptions hopt)
private void	regularize(libdt.CovMatrix cov)
private void	regularize(libdt.Dytex dy, boolean regA)
libdt.Mat[]	repeat(libdt.Mat img, int nf)
void	repeat(libdt.Mat src, int ny, int nx, libdt.Mat dst)
private void	resize(Vector<libdt.Mat> matVec, int n)
private void	resizeDouble(Vector<Double> doubleVec, int n)
void	runAlgorithm()	#include #include #include #include #include #includeinvalid input: '<'math.h> #include #include "opencv/cv.h" #include "opencv/cxcore.h" #include "opencv/highgui.h" #include "options.h" #include "utils/libutils.h" #include "stats/libstats.h" #include "video/libvideo.h" #include "dytex/libdytex.h" #include "platInd/platInd.hpp" #include "bufferer/Bufferer.hpp" using namespace cv; using namespace std;
(package private) void	runEM(libdt.DytexMix dtm, Vector<libdt.Mat[]> Yin, libdt.EMOptions emopt)
private void	runHEM(libdt.DytexMix dtm, libdt.DytexMix hembest, libdt.HEMOptions hopt, Vector<Integer> classes)
(package private) void	scaleRows(libdt.Mat m, libdt.Mat w)
(package private) libdt.Mat[]	segm_mask(libdt.PatchBatchExtractor pbe, Vector<Integer> oldclasses)
(package private) libdt.Mat[]	segm_mask(libdt.VidSegm vs)
(package private) libdt.Mat[]	segmentVideo(libdt.VidSegm vs, libdt.Mat[] vid, int stepxy, int stepz, int filtxy, int filtz, libdt.Mat[] osmaskout)
void	segmentVideoSequence(libdt.VidSegm vs, Vector<String> paths, int stepxy, int stepz, int filtxy, int filtz, String vidPath2)
private void	setRegularizer(libdt.CovMatrix cov, libdt.cov_reg_type regopt, double regval)
private void	setRegularizer(libdt.Dytex dy, libdt.DytexRegOptions dtreg)
(package private) void	setupKFB(libdt.DytexMix dtm, int tau)
(package private) String[]	strtok2(String str, String del)
(package private) libdt.Mat[]	subvid(libdt.Mat[] vid, int frange_start_inclusive, int frange_end_exclusive)
(package private) libdt.Mat[]	subvid(libdt.Mat[] vid, int zstart, int zend, int ystart, int yend, int xstart, int xend)
(package private) libdt.Mat[]	subvid(libdt.Mat[] vid, libdt.Range box_z, libdt.Range box_y, libdt.Range box_x)
double	sum(libdt.Mat A)
void	test_BoSClassification()
void	test_HEM()
void	test_HEMDTM()
int	test_videoSegm(String paramFile)
libdt.Mat[]	times(libdt.Mat[] A, double q)
libdt.Mat	times(libdt.Mat A, double q)
libdt.Mat	times(libdt.Mat A, libdt.Mat B)
(package private) libdt.Mat	toFullMatrix(libdt.CovMatrix cov)
(package private) long	total(libdt.Mat vid)
(package private) long	total(libdt.Mat[] vid)
double	trace(libdt.Mat A)
libdt.Mat	transpose(libdt.Mat A)
(package private) libdt.Mat	vectorize(libdt.Mat vid, boolean flag_col)
void	write(libdt.CovMatrix cm)
void	write(libdt.Dytex dt)
void	write(libdt.DytexMix dtm)
void	write(libdt.DytexOptions opt)
void	write(String name, boolean val)
void	write(String name, byte val)
void	write(String name, double val)
void	write(String name, int val)
void	write(String name, libdt.Mat mtx)
void	write(String name, Vector<Integer> vec)
void	write(javax.vecmath.Point3i p)
final void	writeDouble(double data, boolean bigEndian)	Writes a double as eight bytes to a file.
long	writeHeader(String str)
final void	writeInt(int data, boolean bigEndian)	Writes an int as four bytes to a file.
final void	writeLong(long data, boolean bigEndian)	Writes a long as eight bytes to a file.
void	writeSize(long spos)
void	writeVecDouble(String name, Vector<Double> vec)
void	writeVecVecDouble(String name, Vector<Vector<Double>> vec)
private double	zabs(double zr, double zi)	zabs computes the absolute value or magnitude of a double precision complex variable zr + j*zi.

Methods inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, finalize, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, generateProgressValues, getDestImage, getElapsedTime, getMask, getMaxProgressValue, getMinProgressValue, getNumberOfThreads, getProgress, getProgressChangeListener, getProgressChangeListeners, getProgressModulus, getProgressStep, getProgressValues, getSrcImage, isCompleted, isImage25D, isMultiThreadingEnabled, isRunningInSeparateThread, isThreadStopped, linkProgressToAlgorithm, linkProgressToAlgorithm, makeProgress, notifyListeners, removeListener, removeProgressChangeListener, run, setCompleted, setImage25D, setMask, setMaxProgressValue, setMinProgressValue, setMultiThreadingEnabled, setNumberOfThreads, setProgress, setProgressModulus, setProgressStep, setProgressValues, setProgressValues, setRunningInSeparateThread, setSrcImage, setStartTime, setThreadStopped, startMethod, windowActivated, windowClosed, windowClosing, windowDeactivated, windowDeiconified, windowIconified, windowOpened

Methods inherited from class java.lang.Thread

activeCount, checkAccess, clone, countStackFrames, currentThread, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, isVirtual, join, join, join, join, ofPlatform, ofVirtual, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, sleep, start, startVirtualThread, stop, suspend, threadId, toString, yield

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Details

raFile

private RandomAccessFile raFile

endian

private boolean endian

byteIntBuffer

private final byte[] byteIntBuffer

byte array for int *

byteDoubleBuffer

private final byte[] byteDoubleBuffer

byte array for double *

byteLongBuffer

private final byte[] byteLongBuffer

byte array for long *

CV_8U

private final int CV_8U

See Also:

• Constant Field Values

CV_8UC1

private final int CV_8UC1

See Also:

• Constant Field Values

CV_8UC

private final int CV_8UC

See Also:

• Constant Field Values

CV_64F

private final int CV_64F

See Also:

• Constant Field Values

CV_64FC1

private final int CV_64FC1

See Also:

• Constant Field Values

CV_64FC

private final int CV_64FC

See Also:

• Constant Field Values

CV_64FC3

private final int CV_64FC3

See Also:

• Constant Field Values

CV_REDUCE_SUM

private final int CV_REDUCE_SUM

See Also:

• Constant Field Values

CV_REDUCE_AVG

private final int CV_REDUCE_AVG

See Also:

• Constant Field Values

CV_REDUCE_MAX

private final int CV_REDUCE_MAX

See Also:

• Constant Field Values

CV_REDUCE_MIN

private final int CV_REDUCE_MIN

See Also:

• Constant Field Values

MAXCOL

private final int MAXCOL

See Also:

• Constant Field Values

g_mask_lut

private libdt.Mat[][] g_mask_lut

g_rgbtable

private double[][] g_rgbtable

debug

private boolean debug

Constructor Details

libdt

public libdt()

Method Details

runAlgorithm

public void runAlgorithm()

#include #include #include #include #include #includeinvalid input: '<'math.h> #include #include "opencv/cv.h" #include "opencv/cxcore.h" #include "opencv/highgui.h" #include "options.h" #include "utils/libutils.h" #include "stats/libstats.h" #include "video/libvideo.h" #include "dytex/libdytex.h" #include "platInd/platInd.hpp" #include "bufferer/Bufferer.hpp" using namespace cv; using namespace std;

Specified by:

runAlgorithm in class AlgorithmBase

getTime

private String getTime()

test_HEM

public void test_HEM()

reduceWithSplitting

private libdt.DytexMix reduceWithSplitting(libdt.DytexMix dtm,
 libdt.HEMOptions hopt)

runHEM

private void runHEM(libdt.DytexMix dtm,
 libdt.DytexMix hembest,
 libdt.HEMOptions hopt,
 Vector<Integer> classes)

computeAggregateStats

private void computeAggregateStats(libdt.Estats Estat,
 libdt.Mat W)

logtrick

libdt.Mat logtrick(libdt.Mat lA)

computeEll

private void computeEll(libdt.Estats Estat)

subvid

libdt.Mat[] subvid(libdt.Mat[] vid,
 int zstart,
 int zend,
 int ystart,
 int yend,
 int xstart,
 int xend)

subvid

libdt.Mat[] subvid(libdt.Mat[] vid,
 libdt.Range box_z,
 libdt.Range box_y,
 libdt.Range box_x)

subvid

libdt.Mat[] subvid(libdt.Mat[] vid,
 int frange_start_inclusive,
 int frange_end_exclusive)

reduce

private void reduce(libdt.Mat src,
 libdt.Mat dst,
 int dim,
 int rtype)

reduce

private void reduce(libdt.Mat[] vid,
 libdt.Mat out,
 int reduceOp)

logdetiid

double logdetiid(libdt.Mat Q,
 double r,
 int C)

frame

private libdt.Mat frame(libdt.Mat vid,
 int f)

create

private libdt.Mat[] create(int frames,
 int rows,
 int cols,
 int type)

setRegularizer

private void setRegularizer(libdt.Dytex dy,
 libdt.DytexRegOptions dtreg)

setRegularizer

private void setRegularizer(libdt.CovMatrix cov,
 libdt.cov_reg_type regopt,
 double regval)

regularize

private void regularize(libdt.Dytex dy,
 boolean regA)

zabs

private double zabs(double zr,
 double zi)

zabs computes the absolute value or magnitude of a double precision complex variable zr + j*zi.

Parameters:

zr - double

zi - double

Returns:

double

regularize

private void regularize(libdt.CovMatrix cov)

inp_minbnd

private boolean inp_minbnd(double[] arr,
 double min_bnd)

inp_minbnd

private boolean inp_minbnd(double[][] arr,
 double min_bnd)

init_multiple_dt

private libdt.Dytex init_multiple_dt(libdt.DytexMix dtm)

dytex_mix_split

private void dytex_mix_split(libdt.DytexMix dtm,
 libdt.DytexSplitParams splitopt,
 int[] ctg,
 int[] csp)

dytex_perturb

private void dytex_perturb(libdt.Dytex dtp,
 double pert,
 libdt.Split_mode mode,
 libdt.Split_vars vars)

ppertC

private void ppertC(libdt.Mat C,
 libdt.Mat S0,
 double pert)

copyTo

private void copyTo(libdt.Mat[] A,
 libdt.Mat[] B)

copyTo

private void copyTo(libdt.Mat A,
 libdt.Mat B)

copyToDstColRange

private void copyToDstColRange(libdt.Mat A,
 libdt.Mat B,
 int inclusiveStart,
 int exclusiveEnd)

copyFromSrcColRange

private void copyFromSrcColRange(libdt.Mat A,
 libdt.Mat B,
 int inclusiveStart,
 int exclusiveEnd)

getYmean_type

public libdt.Ymean_type getYmean_type(int Ymean_code)

getCov_type

public libdt.cov_type getCov_type(int cov_code)

getCov_reg_type

public libdt.cov_reg_type getCov_reg_type(int cov_reg_code)

toFullMatrix

libdt.Mat toFullMatrix(libdt.CovMatrix cov)

inv

libdt.CovMatrix inv(libdt.CovMatrix cov)

postmultiply

void postmultiply(libdt.CovMatrix cov,
 libdt.Mat src,
 libdt.Mat dst)

plus

public libdt.Mat plus(libdt.Mat A,
 libdt.Mat B)

plus

public libdt.Mat plus(libdt.Mat A,
 double b)

divide

public libdt.Mat divide(libdt.Mat A,
 libdt.Mat B)

minus

public libdt.Mat minus(libdt.Mat A,
 libdt.Mat B)

minus

public libdt.Mat minus(libdt.Mat A,
 double b)

elementTimes

public libdt.Mat elementTimes(libdt.Mat A,
 libdt.Mat B)

times

public libdt.Mat times(libdt.Mat A,
 libdt.Mat B)

times

public libdt.Mat[] times(libdt.Mat[] A,
 double q)

times

public libdt.Mat times(libdt.Mat A,
 double q)

divide

public libdt.Mat divide(libdt.Mat A,
 double q)

transpose

public libdt.Mat transpose(libdt.Mat A)

col

public libdt.Mat col(libdt.Mat A,
 int colNum)

sum

public double sum(libdt.Mat A)

countNonZero

public int countNonZero(libdt.Mat A)

clone

public libdt.Mat clone(libdt.Mat A)

trace

public double trace(libdt.Mat A)

repeat

public libdt.Mat[] repeat(libdt.Mat img,
 int nf)

repeat

public void repeat(libdt.Mat src,
 int ny,
 int nx,
 libdt.Mat dst)

scaleRows

void scaleRows(libdt.Mat m,
 libdt.Mat w)

read

public void read(libdt.DytexMix dtm)

write

public void write(libdt.DytexMix dtm)

read

public void read(String name,
 Vector<Integer> vec)

readVecDouble

void readVecDouble(String name,
 Vector<Double> vec)

writeVecDouble

public void writeVecDouble(String name,
 Vector<Double> vec)

readVecVecDouble

void readVecVecDouble(String name,
 Vector<Vector<Double>> vec)

writeVecVecDouble

public void writeVecVecDouble(String name,
 Vector<Vector<Double>> vec)

readVectorString

public void readVectorString(String name,
 Vector<String> vec)

write

public void write(String name,
 Vector<Integer> vec)

read

public void read(libdt.Dytex dt)

write

public void write(libdt.Dytex dt)

read

public void read(libdt.CovMatrix cm)

write

public void write(libdt.CovMatrix cm)

read

public void read(String name,
 double[] val)

write

public void write(String name,
 double val)

writeDouble

public final void writeDouble(double data,
 boolean bigEndian)
                       throws IOException

Writes a double as eight bytes to a file.

Parameters:

data - Data to be written to file.

bigEndian - true indicates big endian byte order, false indicates little endian.

Throws:

IOException - if there is an error writing the file

writeLong

public final void writeLong(long data,
 boolean bigEndian)
                     throws IOException

Writes a long as eight bytes to a file.

Parameters:

data - Data to be written to file.

bigEndian - true indicates big endian byte order, false indicates little endian.

Throws:

IOException - if there is an error writing the file

read

public void read(String name,
 libdt.Mat mtx)

write

public void write(String name,
 libdt.Mat mtx)

read

public void read(javax.vecmath.Point3i p)

write

public void write(javax.vecmath.Point3i p)

read

public void read(String name,
 boolean[] val)

write

public void write(String name,
 boolean val)

read

public void read(libdt.DytexOptions opt)

write

public void write(libdt.DytexOptions opt)

read

public void read(String name,
 int[] val)

write

public void write(String name,
 int val)

writeSize

public void writeSize(long spos)

read

public void read(String name,
 byte[] val)

write

public void write(String name,
 byte val)

readHeader

public void readHeader(String str)

writeHeader

public long writeHeader(String str)

writeInt

public final void writeInt(int data,
 boolean bigEndian)
                    throws IOException

Writes an int as four bytes to a file.

Parameters:

data - Data to be written to file.

bigEndian - true indicates big endian byte order, false indicates little endian.

Throws:

IOException - if there is an error writing the file

resize

private void resize(Vector<libdt.Mat> matVec,
 int n)

resizeDouble

private void resizeDouble(Vector<Double> doubleVec,
 int n)

getInt

public final int getInt(boolean bigEndian)
                 throws IOException

Reads four signed bytes from file.

Parameters:

bigEndian - true indicates big endian byte order, false indicates little endian.

Returns:

The value of the integer read from the file.

Throws:

IOException - if there is an error reading the file

getDouble

public final double getDouble(boolean bigEndian)
                       throws IOException

Reads eight unsigned bytes from file.

Parameters:

bigEndian - true indicates big endian byte order, false indicates little endian.

Returns:

The value of the double read from the file.

Throws:

IOException - if there is an error reading the file

test_videoSegm

public int test_videoSegm(String paramFile)

getNorm_type

public libdt.norm_type getNorm_type(int norm_code)

learnDTM

void learnDTM(libdt.VidSegm tvs,
 String vpath,
 boolean dosegm)

loaddat

libdt.Mat[] loaddat(String filename,
 String opt)

checkOptionInStr

int checkOptionInStr(String str,
 String opt)

loaddatinfo

libdt.DatDescriptor loaddatinfo(String filename,
 int verbose)

strtok2

String[] strtok2(String str,
 String del)

getPatches

Vector<libdt.Mat[]> getPatches(libdt.PatchExtractor pe)

addFrames

boolean addFrames(libdt.PatchExtractor pe,
 libdt.Mat[] invid)

processNextPatch

void processNextPatch(libdt.PatchExtractor pe)

norm2

double norm2(libdt.Mat[] vid)

total

long total(libdt.Mat vid)

total

long total(libdt.Mat[] vid)

computeVariance3dDouble

double computeVariance3dDouble(libdt.Mat[] input)

dumpMatSize

void dumpMatSize(libdt.Mat[] m)

meanOfStdVector

double meanOfStdVector(Vector<Double> v)

minOfStdVector

double minOfStdVector(Vector<Double> v)

learnWithSplitting

void learnWithSplitting(libdt.DytexMix dtm,
 Vector<libdt.Mat[]> Yin,
 libdt.EMOptions emopt)

runEM

void runEM(libdt.DytexMix dtm,
 Vector<libdt.Mat[]> Yin,
 libdt.EMOptions emopt)

convertmovie

libdt.Mat convertmovie(libdt.Mat[] Y,
 int[] sx,
 int[] sy,
 int[] sc,
 int[] cnorm)

extractY

Vector<libdt.Mat> extractY(libdt.Mat[] Yin,
 Vector<Integer> inds)

initcluster_doretto

libdt.Dytex initcluster_doretto(Vector<libdt.Mat> Y,
 libdt.DytexOptions param)

learnLeastSquares

void learnLeastSquares(libdt.Dytex mydt,
 Vector<libdt.Mat> videos)

processVideoTraining

void processVideoTraining(libdt.Dytex mydt,
 libdt.Mat vin,
 libdt.Mat Yout,
 libdt.Mat Yout_mean)

vectorize

libdt.Mat vectorize(libdt.Mat vid,
 boolean flag_col)

calculate

void calculate(libdt.CovMatrix cov,
 libdt.Mat data,
 boolean use_unbiased)

mulTransposed

void mulTransposed(libdt.Mat src,
 libdt.Mat dst,
 boolean transposeFirst)

dytex_kalman

public void dytex_kalman(libdt.Mat[] Y2,
 libdt.Dytex dt,
 String opt,
 Vector<libdt.Mat> xt,
 libdt.Mat[] Vt,
 libdt.Mat[] Vt1,
 libdt.Mat L)

setupKFB

void setupKFB(libdt.DytexMix dtm,
 int tau)

processVideoTesting

void processVideoTesting(libdt.Dytex dt,
 libdt.Mat vin,
 libdt.Mat Yout)

segm_mask

libdt.Mat[] segm_mask(libdt.PatchBatchExtractor pbe,
 Vector<Integer> oldclasses)

maxvotefilt

libdt.Mat[] maxvotefilt(libdt.Mat[] I,
 int sx,
 int sy,
 int sz,
 int numclass)

colorMask

void colorMask(libdt.Mat[] img,
 libdt.Mat[] mask,
 libdt.Mat oimg,
 int border)

mask2Border

libdt.Mat mask2Border(libdt.Mat mask,
 int border,
 byte[] mask_flag)

segmentVideoSequence

public void segmentVideoSequence(libdt.VidSegm vs,
 Vector<String> paths,
 int stepxy,
 int stepz,
 int filtxy,
 int filtz,
 String vidPath2)

segmentVideo

libdt.Mat[] segmentVideo(libdt.VidSegm vs,
 libdt.Mat[] vid,
 int stepxy,
 int stepz,
 int filtxy,
 int filtz,
 libdt.Mat[] osmaskout)

getClasses

public void getClasses(libdt.DytexMix dtm,
 Vector<libdt.Mat> Y,
 libdt.Mat LLm)

getClasses

public void getClasses(libdt.DytexMix dtm,
 Vector<libdt.Mat> Y,
 Vector<Integer> classes)

segm_mask

libdt.Mat[] segm_mask(libdt.VidSegm vs)

test_HEMDTM

public void test_HEMDTM()

learnBaseDTM

void learnBaseDTM()

learnTagDTM

void learnTagDTM()

readGtruthFile

void readGtruthFile(String fpath,
 Vector<String> vlist,
 Vector<Vector<String>> annlist,
 Vector<String> taglist)

readTrialInfo

void readTrialInfo(String fpath,
 Vector<Vector<Integer>> trainVidIds,
 Vector<Vector<Integer>> testVidIds)

getTagVids

Vector<Integer> getTagVids(Vector<Integer> trainVidIds,
 String tag,
 Vector<Vector<String>> annlist)

annotateVideos

void annotateVideos()

computePrecisionRecall

void computePrecisionRecall()

printResults

void printResults()

plus

Vector<Double> plus(Vector<Double> a,
 Vector<Double> b)

test_BoSClassification

public void test_BoSClassification()

learnBaseDTMBoS

void learnBaseDTMBoS()