>> vl_kmeans.c
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vl_kmeans.c
vl_kmeans MEX definition.
** @author Andrea Vedaldi
/* AUTORIGHTS
Copyright (C) 2007-10 Andrea Vedaldi and Brian Fulkerson
This file is part of VLFeat, available under the terms of the
GNU GPLv2, or (at your option) any later version.
#include &vl/kmeans.h&
#include &mexutils.h&
#include &string.h&
opt_max_num_iterations,
opt_algorithm,
opt_distance,
opt_initialization,
opt_num_repetitions,
opt_verbose
INIT_RANDSEL,
INIT_PLUSPLUS
vlmxOption
options [] = {
&MaxNumIterations&,
opt_max_num_iterations
&Algorithm&,
opt_algorithm
&Distance&,
opt_distance
&Verbose&,
opt_verbose
&NumRepetitions&,
opt_num_repetitions,
&Initialization&,
opt_initialization
&Initialisation&,
opt_initialization
}, /* UK spelling */
/* driver */
mexFunction (int nout, mxArray * out[], int nin, const mxArray * in[])
IN_DATA = 0, IN_NUMCENTERS, IN_END
OUT_CENTERS = 0, OUT_ASSIGNMENTS, OUT_ENERGY
int next = IN_END ;
mxArray const
vl_size numC
vl_size numD
void const * data = NULL ;
VlKMeansAlgorithm algorithm = VlKMeansL
VlVectorComparisonType distance = VlDistanceL2 ;
vl_size maxNumIterations = 100 ;
vl_size numRepetitions = 1 ;
int verbosity = 0 ;
int initialization = INIT_PLUSPLUS ;
vl_type dataT
mxClassID classID ;
VlKMeans *
VL_USE_MATLAB_ENV ;
/* -----------------------------------------------------------------
Check the arguments
* -------------------------------------------------------------- */
if (nin & 2) {
vlmxError (vlmxErrInvalidArgument,
&At least two arguments required.&);
else if (nout & 3) {
vlmxError (vlmxErrInvalidArgument,
&Too many output arguments.&);
classID = mxGetClassID (IN(DATA)) ;
switch (classID) {
case mxSINGLE_CLASS: dataType = VL_TYPE_FLOAT ;
case mxDOUBLE_CLASS: dataType = VL_TYPE_DOUBLE ;
vlmxError (vlmxErrInvalidArgument,
&DATA must be of class SINGLE or DOUBLE&) ;
dimension = mxGetM (IN(DATA)) ;
numData = mxGetN (IN(DATA)) ;
if (!vlmxIsPlainScalar(IN(NUMCENTERS)) ||
(numCenters = (vl_size) mxGetScalar(IN(NUMCENTERS))) & 1
numCenters & numData) {
vlmxError (vlmxErrInvalidArgument,
&NUMCENTERS must be a positive integer not greater &
&than the number of data.&) ;
while ((opt = vlmxNextOption (in, nin, options, &next, &optarg)) &= 0) {
char buf [1024] ;
switch (opt) {
case opt_verbose :
case opt_max_num_iterations :
if (!vlmxIsPlainScalar(optarg) || mxGetScalar(optarg) & 0) {
vlmxError (vlmxErrInvalidArgument,
&MAXNUMITERATIONS must be a non-negative integer scalar&) ;
maxNumIterations = (vl_size) mxGetScalar(optarg) ;
case opt_algorithm :
if (!vlmxIsString (optarg, -1)) {
vlmxError (vlmxErrInvalidArgument,
&ALGORITHM must be a string.&) ;
if (mxGetString (optarg, buf, sizeof(buf))) {
vlmxError (vlmxErrInvalidArgument,
&ALGORITHM argument too long.&) ;
if (uStrICmp(&lloyd&, buf) == 0) {
algorithm = VlKMeansL
} else if (uStrICmp(&elkan&, buf) == 0) {
algorithm = VlKMeansE
} else if (uStrICmp(&ann&, buf) == 0) {
algorithm = VlKMeansANN ;
vlmxError (vlmxErrInvalidArgument,
&Invalid value %s for ALGORITHM&, buf) ;
case opt_initialization :
if (!vlmxIsString (optarg, -1)) {
vlmxError (vlmxErrInvalidArgument,
&INITLAIZATION must be a string.&) ;
if (mxGetString (optarg, buf, sizeof(buf))) {
vlmxError (vlmxErrInvalidArgument,
&INITIALIZATION argument too long.&) ;
if (uStrICmp(&plusplus&, buf) == 0 ||
uStrICmp(&++&, buf) == 0) {
initialization = VlKMeansPlusP
} else if (uStrICmp(&randsel&, buf) == 0) {
initialization = VlKMeansRandomS
vlmxError (vlmxErrInvalidArgument,
&Invalid value %s for INITIALISATION.&, buf) ;
case opt_distance :
if (!vlmxIsString (optarg, -1)) {
vlmxError (vlmxErrInvalidArgument,
&DISTANCE must be a string.&) ;
if (mxGetString (optarg, buf, sizeof(buf))) {
vlmxError (vlmxErrInvalidArgument,
&DISTANCE argument too long.&) ;
if (uStrICmp(&l2&, buf) == 0) {
distance = VlDistanceL2 ;
} else if (uStrICmp(&l1&, buf) == 0) {
distance = VlDistanceL1 ;
} else if (uStrICmp(&chi2&, buf) == 0) {
distance = VlDistanceChi2 ;
vlmxError (vlmxErrInvalidArgument,
&Invalid value %s for DISTANCE&, buf) ;
case opt_num_repetitions :
if (!vlmxIsPlainScalar (optarg)) {
vlmxError (vlmxErrInvalidArgument,
&NUMREPETITIONS must be a scalar.&) ;
if (mxGetScalar (optarg) & 1) {
vlmxError (vlmxErrInvalidArgument,
&NUMREPETITIONS must be larger than or equal to 1.&) ;
numRepetitions = (vl_size) mxGetScalar (optarg) ;
/* -----------------------------------------------------------------
Do the job
* -------------------------------------------------------------- */
data = mxGetPr(IN(DATA)) ;
kmeans = vl_kmeans_new (dataType, distance) ;
vl_kmeans_set_verbosity (kmeans, verbosity) ;
vl_kmeans_set_num_repetitions (kmeans, numRepetitions) ;
vl_kmeans_set_algorithm (kmeans, algorithm) ;
vl_kmeans_set_initialization (kmeans, initialization) ;
vl_kmeans_set_max_num_iterations (kmeans, maxNumIterations) ;
if (verbosity) {
char const * algorithmName = 0 ;
char const * initializationName = 0 ;
switch (vl_kmeans_get_algorithm(kmeans)) {
case VlKMeansLloyd: algorithmName = &Lloyd& ;
case VlKMeansElkan: algorithmName = &Elkan& ;
case VlKMeansANN:
algorithmName = &ANN& ;
default : abort() ;
switch (vl_kmeans_get_initialization(kmeans)) {
case VlKMeansPlusPlus : initializationName = &plusplus& ;
case VlKMeansRandomSelection : initializationName = &randsel& ;
default: abort() ;
mexPrintf(&kmeans: Initialization = %s\n&, initializationName) ;
mexPrintf(&kmeans: Algorithm = %s\n&, algorithmName) ;
mexPrintf(&kmeans: MaxNumIterations = %d\n&, vl_kmeans_get_max_num_iterations(kmeans)) ;
mexPrintf(&kmeans: NumRepetitions = %d\n&, vl_kmeans_get_num_repetitions(kmeans)) ;
mexPrintf(&kmeans: data type = %s\n&, vl_get_type_name(vl_kmeans_get_data_type(kmeans))) ;
mexPrintf(&kmeans: distance = %s\n&, vl_get_vector_comparison_type_name(vl_kmeans_get_distance(kmeans))) ;
mexPrintf(&kmeans: data dimension = %d\n&, dimension) ;
mexPrintf(&kmeans: num. data points = %d\n&, numData) ;
mexPrintf(&kmeans: num. centers = %d\n&, numCenters) ;
mexPrintf(&\n&) ;
/* -------------------------------------------------------------- */
Clustering and quantization */
/* -------------------------------------------------------------- */
energy = vl_kmeans_cluster(kmeans, data, dimension, numData, numCenters) ;
/* copy centers */
OUT(CENTERS) = mxCreateNumericMatrix (dimension, numCenters, classID, mxREAL) ;
memcpy (mxGetData(OUT(CENTERS)),
vl_kmeans_get_centers (kmeans),
vl_get_type_size (dataType) * dimension * vl_kmeans_get_num_centers(kmeans)) ;
/* optionally qunatize */
if (nout & 1) {
vl_uint32 *
OUT(ASSIGNMENTS) = mxCreateNumericMatrix (1, numData, mxUINT32_CLASS, mxREAL) ;
assignments = mxGetData (OUT(ASSIGNMENTS)) ;
vl_kmeans_quantize (kmeans, assignments, NULL, data, numData) ;
/* use MATLAB indexing convention */
for (j = 0 ; j & numD ++j) {
assignments[j] += 1 ;
/* optionally return energy */
if (nout & 2) {
OUT(ENERGY) = vlmxCreatePlainScalar (energy) ;
vl_kmeans_delete (kmeans) ;
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1.53 kB19-07-11 22:21
474.00 B19-07-11 22:21
802.00 B19-07-11 22:21
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2.50 kB21-07-11 19:09
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95.00 B19-07-11 22:21
525.00 B19-07-11 22:21
1.74 kB19-07-11 22:21
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796.00 B19-07-11 22:21
1.31 kB19-07-11 22:21
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437.00 B19-07-11 22:21
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1.79 kB19-07-11 22:21
514.00 B19-07-11 22:21
2.57 kB19-07-11 22:21
2.39 kB19-07-11 22:21
2.70 kB19-07-11 22:21
1.03 kB19-07-11 22:21
2.79 kB19-07-11 22:21
549.00 B19-07-11 22:21
1.29 kB19-07-11 22:21
1.13 kB19-07-11 22:21
1.35 kB19-07-11 22:21
20.91 kB19-07-11 22:21
2.99 kB19-07-11 22:21
5.34 kB19-07-11 22:21
2.38 kB19-07-11 22:21
24.23 kB19-07-11 22:21
10.74 kB19-07-11 22:21
float.th1.50 kB19-07-11 22:21
29.54 kB19-07-11 22:21
10.25 kB19-07-11 22:21
8.95 kB19-07-11 22:21
1.43 kB19-07-11 22:21
13.31 kB19-07-11 22:21
7.46 kB19-07-11 22:21
4.21 kB19-07-11 22:21
16.54 kB19-07-11 22:21
2.08 kB19-07-11 22:21
13.86 kB19-07-11 22:21
15.75 kB19-07-11 22:21
6.32 kB19-07-11 22:21
4.36 kB19-07-11 22:21
ikmeans_elkan.tc10.19 kB19-07-11 22:21
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22.89 kB19-07-11 22:21
3.78 kB19-07-11 22:21
7.42 kB19-07-11 22:21
1.68 kB19-07-11 22:21
22.64 kB19-07-11 22:21
7.33 kB19-07-11 22:21
49.17 kB19-07-11 22:21
9.38 kB19-07-11 22:21
8.50 kB19-07-11 22:21
1.00 kB19-07-11 22:21
11.58 kB19-07-11 22:21
14.63 kB19-07-11 22:21
7.97 kB19-07-11 22:21
1.45 kB19-07-11 22:21
28.71 kB19-07-11 22:21
13.24 kB19-07-11 22:21
12.71 kB19-07-11 22:21
1.71 kB19-07-11 22:21
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2.39 kB19-07-11 22:21
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6.33 kB19-07-11 22:21
3.86 kB19-07-11 22:21
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759.00 B19-07-11 22:21
2.44 kB19-07-11 22:21
70.77 kB19-07-11 22:21
11.52 kB19-07-11 22:21
10.69 kB19-07-11 22:21
1.64 kB19-07-11 22:21
vlfeat.sln877.00 B19-07-11 22:21
vlfeat.vcproj9.80 kB19-07-11 22:21
project.pbxproj89.43 kB19-07-11 22:21
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