|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//#include "traster.h"
|
|
Toshihiro Shimizu |
890ddd |
#include "tcolorutils.h"
|
|
Toshihiro Shimizu |
890ddd |
#include "tmathutil.h"
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#include <set></set>
|
|
Toshihiro Shimizu |
890ddd |
#include <list></list>
|
|
Campbell Barton |
3b0737 |
#include <cmath></cmath>
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
typedef float KEYER_FLOAT;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Shinya Kitaoka |
9f5a1b |
#ifdef _WIN32
|
|
Toshihiro Shimizu |
890ddd |
#define ISNAN _isnan
|
|
Toshihiro Shimizu |
890ddd |
#else
|
|
Michał Janiszewski |
b86749 |
#define ISNAN std::isnan
|
|
Toshihiro Shimizu |
890ddd |
#endif
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//#define CLUSTER_ELEM_CONTAINER_IS_A_SET
|
|
Toshihiro Shimizu |
890ddd |
//#define WITH_ALPHA_IN_STATISTICS
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
class ClusterStatistic {
|
|
Toshihiro Shimizu |
890ddd |
public:
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT sumComponents[3]; // vettore 3x1
|
|
Shinya Kitaoka |
120a6e |
unsigned int elemsCount;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT matrixR[9]; // matrice 3x3 = somma(x * trasposta(x))
|
|
Shinya Kitaoka |
120a6e |
// dove x sono i pixel del cluster
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT covariance[9]; // matrice di covarianza
|
|
Shinya Kitaoka |
120a6e |
TPoint sumCoords;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#ifdef WITH_ALPHA_IN_STATISTICS
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT sumAlpha;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#endif
|
|
Toshihiro Shimizu |
890ddd |
};
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
class ClusterElem {
|
|
Toshihiro Shimizu |
890ddd |
public:
|
|
Shinya Kitaoka |
120a6e |
ClusterElem(unsigned char _r, unsigned char _g, unsigned char _b,
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT _a, unsigned int _x = 0, unsigned int _y = 0)
|
|
Shinya Kitaoka |
120a6e |
: r(toDouble(_r))
|
|
Shinya Kitaoka |
120a6e |
, g(toDouble(_g))
|
|
Shinya Kitaoka |
120a6e |
, b(toDouble(_b))
|
|
Shinya Kitaoka |
120a6e |
, a(_a)
|
|
Shinya Kitaoka |
120a6e |
, x(_x)
|
|
Shinya Kitaoka |
120a6e |
, y(_y)
|
|
Shinya Kitaoka |
120a6e |
, pix32(TPixel32(_r, _g, _b)) {}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
~ClusterElem() {}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
static KEYER_FLOAT toDouble(unsigned char chan) {
|
|
Shinya Kitaoka |
120a6e |
return ((KEYER_FLOAT)chan) * (KEYER_FLOAT)(1.0 / 255.0);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
unsigned int x;
|
|
Shinya Kitaoka |
120a6e |
unsigned int y;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT r;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT g;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT b;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a;
|
|
Shinya Kitaoka |
120a6e |
TPixel32 pix32;
|
|
Toshihiro Shimizu |
890ddd |
};
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#ifdef CLUSTER_ELEM_CONTAINER_IS_A_SET
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
typedef std::set<clusterelem *=""> ClusterElemContainer;</clusterelem>
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#else
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
typedef std::vector<clusterelem *=""> ClusterElemContainer;</clusterelem>
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#endif
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
class Cluster {
|
|
Toshihiro Shimizu |
890ddd |
public:
|
|
Shinya Kitaoka |
120a6e |
Cluster();
|
|
Shinya Kitaoka |
120a6e |
Cluster(const Cluster &rhs);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
~Cluster();
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
void computeCovariance();
|
|
Shinya Kitaoka |
120a6e |
void insert(ClusterElem *elem);
|
|
Shinya Kitaoka |
120a6e |
void computeStatistics();
|
|
Shinya Kitaoka |
120a6e |
void getMeanAxis(KEYER_FLOAT axis[3]);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
ClusterStatistic statistic;
|
|
Shinya Kitaoka |
120a6e |
ClusterElemContainer data;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT eigenVector[3];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT eigenValue;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
private:
|
|
Shinya Kitaoka |
120a6e |
void operator=(const Cluster &);
|
|
Toshihiro Shimizu |
890ddd |
};
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
typedef std::vector<cluster *=""> ClusterContainer;</cluster>
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//----------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
void chooseLeafToClusterize(ClusterContainer::iterator &itRet,
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT &eigenValue, KEYER_FLOAT eigenVector[3],
|
|
Shinya Kitaoka |
120a6e |
ClusterContainer &clusters);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
void split(Cluster *subcluster1, Cluster *subcluster2,
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT eigenVector[3], Cluster *cluster);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
void SolveCubic(KEYER_FLOAT a, /* coefficient of x^3 */
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT b, /* coefficient of x^2 */
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT c, /* coefficient of x */
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT d, /* constant term */
|
|
Shinya Kitaoka |
120a6e |
int *solutions, /* # of distinct solutions */
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT *x); /* array of solutions */
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
unsigned short int calcCovarianceEigenValues(const KEYER_FLOAT covariance[9],
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT eigenValues[3]);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//----------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
void split(Cluster *subcluster1, Cluster *subcluster2,
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT eigenVector[3], Cluster *cluster) {
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT n = (KEYER_FLOAT)cluster->statistic.elemsCount;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT mean[3];
|
|
Shinya Kitaoka |
120a6e |
mean[0] = cluster->statistic.sumComponents[0] / n;
|
|
Shinya Kitaoka |
120a6e |
mean[1] = cluster->statistic.sumComponents[1] / n;
|
|
Shinya Kitaoka |
120a6e |
mean[2] = cluster->statistic.sumComponents[2] / n;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
ClusterElemContainer::const_iterator it = cluster->data.begin();
|
|
Shinya Kitaoka |
120a6e |
for (; it != cluster->data.end(); ++it) {
|
|
Shinya Kitaoka |
120a6e |
ClusterElem *elem = *it;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT r = (KEYER_FLOAT)elem->r;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT g = (KEYER_FLOAT)elem->g;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT b = (KEYER_FLOAT)elem->b;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
// cluster->data.erase(it);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
if (eigenVector[0] * r + eigenVector[1] * g + eigenVector[2] * b <=
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] * mean[0] + eigenVector[1] * mean[1] +
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] * mean[2])
|
|
Shinya Kitaoka |
120a6e |
subcluster1->insert(elem);
|
|
Shinya Kitaoka |
120a6e |
else
|
|
Shinya Kitaoka |
120a6e |
subcluster2->insert(elem);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//----------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
void chooseLeafToClusterize(ClusterContainer::iterator &itRet,
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT &eigenValue, KEYER_FLOAT eigenVector[3],
|
|
Shinya Kitaoka |
120a6e |
ClusterContainer &clusters) {
|
|
Shinya Kitaoka |
120a6e |
itRet = clusters.end();
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
ClusterContainer::iterator itFound = clusters.end();
|
|
Shinya Kitaoka |
120a6e |
bool found = false;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT maxEigenValue = 0.0;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
unsigned short int multeplicity = 0;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
ClusterContainer::iterator it = clusters.begin();
|
|
Shinya Kitaoka |
120a6e |
for (; it != clusters.end(); ++it) {
|
|
Shinya Kitaoka |
120a6e |
unsigned short int tmpMulteplicity = 0;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT tmpEigenValue;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
Cluster *cluster = *it;
|
|
Shinya Kitaoka |
120a6e |
// calcola la matrice di covarianza
|
|
Shinya Kitaoka |
120a6e |
const KEYER_FLOAT *clusterCovariance = cluster->statistic.covariance;
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(clusterCovariance[0]));
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
// calcola gli autovalori della matrice di covarianza della statistica
|
|
Shinya Kitaoka |
120a6e |
// del cluster (siccome la matrice e' simmetrica gli autovalori
|
|
Shinya Kitaoka |
120a6e |
// sono tutti reali)
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT eigenValues[3];
|
|
Shinya Kitaoka |
120a6e |
tmpMulteplicity = calcCovarianceEigenValues(clusterCovariance, eigenValues);
|
|
Shinya Kitaoka |
120a6e |
assert(tmpMulteplicity > 0);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
tmpEigenValue = std::max({eigenValues[0], eigenValues[1], eigenValues[2]});
|
|
Shinya Kitaoka |
120a6e |
cluster->eigenValue = tmpEigenValue;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
// eventuale aggiornamento del cluster da cercare
|
|
Shinya Kitaoka |
120a6e |
if (itFound == clusters.end()) {
|
|
Shinya Kitaoka |
120a6e |
itFound = it;
|
|
Shinya Kitaoka |
120a6e |
maxEigenValue = tmpEigenValue;
|
|
Shinya Kitaoka |
120a6e |
multeplicity = tmpMulteplicity;
|
|
Shinya Kitaoka |
120a6e |
found = true;
|
|
Shinya Kitaoka |
120a6e |
} else {
|
|
Shinya Kitaoka |
120a6e |
if (tmpEigenValue > maxEigenValue) {
|
|
Shinya Kitaoka |
120a6e |
itFound = it;
|
|
Shinya Kitaoka |
120a6e |
maxEigenValue = tmpEigenValue;
|
|
Shinya Kitaoka |
120a6e |
multeplicity = tmpMulteplicity;
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
if (found) {
|
|
Shinya Kitaoka |
120a6e |
assert(multeplicity > 0);
|
|
Shinya Kitaoka |
120a6e |
itRet = itFound;
|
|
Shinya Kitaoka |
120a6e |
eigenValue = maxEigenValue;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
// calcola l'autovettore relativo a maxEigenValue
|
|
Shinya Kitaoka |
120a6e |
Cluster *clusterFound = *itFound;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
assert(multeplicity > 0);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT tmpMatrixM[9];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
const KEYER_FLOAT *clusterCovariance = clusterFound->statistic.covariance;
|
|
Shinya Kitaoka |
120a6e |
int i = 0;
|
|
Shinya Kitaoka |
120a6e |
for (; i < 9; ++i) tmpMatrixM[i] = clusterCovariance[i];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[0] -= maxEigenValue;
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[4] -= maxEigenValue;
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[8] -= maxEigenValue;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
for (i = 0; i < 3; ++i) eigenVector[i] = 0.0;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
if (multeplicity == 1) {
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT u11 =
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[4] * tmpMatrixM[8] - tmpMatrixM[5] * tmpMatrixM[5];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT u12 =
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[2] * tmpMatrixM[5] - tmpMatrixM[1] * tmpMatrixM[8];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT u13 =
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[1] * tmpMatrixM[5] - tmpMatrixM[2] * tmpMatrixM[5];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT u22 =
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[0] * tmpMatrixM[8] - tmpMatrixM[2] * tmpMatrixM[2];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT u23 =
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[1] * tmpMatrixM[2] - tmpMatrixM[5] * tmpMatrixM[0];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT u33 =
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[0] * tmpMatrixM[4] - tmpMatrixM[1] * tmpMatrixM[1];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT uMax = std::max({u11, u12, u13, u22, u23, u33});
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
if (uMax == u11) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = u11;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = u12;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = u13;
|
|
Shinya Kitaoka |
120a6e |
} else if (uMax == u12) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = u12;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = u22;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = u23;
|
|
Shinya Kitaoka |
120a6e |
} else if (uMax == u13) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = u13;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = u23;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = u33;
|
|
Shinya Kitaoka |
120a6e |
} else if (uMax == u22) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = u12;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = u22;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = u23;
|
|
Shinya Kitaoka |
120a6e |
} else if (uMax == u23) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = u13;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = u23;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = u33;
|
|
Shinya Kitaoka |
120a6e |
} else if (uMax == u33) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = u13;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = u23;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = u33;
|
|
Shinya Kitaoka |
120a6e |
} else {
|
|
Shinya Kitaoka |
120a6e |
assert(false && "impossibile!!");
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
} else if (multeplicity == 2) {
|
|
Shinya Kitaoka |
120a6e |
short int row = -1;
|
|
Shinya Kitaoka |
120a6e |
short int col = -1;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT mMax =
|
|
Shinya Kitaoka |
120a6e |
std::max({tmpMatrixM[0], tmpMatrixM[1], tmpMatrixM[2], tmpMatrixM[4],
|
|
Shinya Kitaoka |
120a6e |
tmpMatrixM[5], tmpMatrixM[8]});
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
if (mMax == tmpMatrixM[0]) {
|
|
Shinya Kitaoka |
120a6e |
row = 1;
|
|
Shinya Kitaoka |
120a6e |
col = 1;
|
|
Shinya Kitaoka |
120a6e |
} else if (mMax == tmpMatrixM[1]) {
|
|
Shinya Kitaoka |
120a6e |
row = 1;
|
|
Shinya Kitaoka |
120a6e |
col = 2;
|
|
Shinya Kitaoka |
120a6e |
} else if (mMax == tmpMatrixM[2]) {
|
|
Shinya Kitaoka |
120a6e |
row = 1;
|
|
Shinya Kitaoka |
120a6e |
col = 3;
|
|
Shinya Kitaoka |
120a6e |
} else if (mMax == tmpMatrixM[4]) {
|
|
Shinya Kitaoka |
120a6e |
row = 2;
|
|
Shinya Kitaoka |
120a6e |
col = 2;
|
|
Shinya Kitaoka |
120a6e |
} else if (mMax == tmpMatrixM[5]) {
|
|
Shinya Kitaoka |
120a6e |
row = 2;
|
|
Shinya Kitaoka |
120a6e |
col = 3;
|
|
Shinya Kitaoka |
120a6e |
} else if (mMax == tmpMatrixM[8]) {
|
|
Shinya Kitaoka |
120a6e |
row = 3;
|
|
Shinya Kitaoka |
120a6e |
col = 3;
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
if (row == 1) {
|
|
Shinya Kitaoka |
120a6e |
if (col == 1 || col == 2) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = -tmpMatrixM[1];
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = tmpMatrixM[0];
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = 0.0;
|
|
Shinya Kitaoka |
120a6e |
} else {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = tmpMatrixM[2];
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = 0.0;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = -tmpMatrixM[0];
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
} else if (row == 2) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = 0.0;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = -tmpMatrixM[5];
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = tmpMatrixM[4];
|
|
Shinya Kitaoka |
120a6e |
} else if (row == 3) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = 0.0;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = -tmpMatrixM[8];
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = tmpMatrixM[5];
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
} else if (multeplicity == 3) {
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] = 1.0;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] = 0.0;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] = 0.0;
|
|
Shinya Kitaoka |
120a6e |
} else {
|
|
Shinya Kitaoka |
120a6e |
assert(false && "impossibile!!");
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
// normalizzazione dell'autovettore calcolato
|
|
Shinya Kitaoka |
120a6e |
/*
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT eigenVectorMagnitude = sqrt(eigenVector[0]*eigenVector[0] +
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1]*eigenVector[1] +
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2]*eigenVector[2]);
|
|
Shinya Kitaoka |
120a6e |
assert(eigenVectorMagnitude > 0);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
eigenVector[0] /= eigenVectorMagnitude;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[1] /= eigenVectorMagnitude;
|
|
Shinya Kitaoka |
120a6e |
eigenVector[2] /= eigenVectorMagnitude;
|
|
Shinya Kitaoka |
120a6e |
*/
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
clusterFound->eigenVector[0] = eigenVector[0];
|
|
Shinya Kitaoka |
120a6e |
clusterFound->eigenVector[1] = eigenVector[1];
|
|
Shinya Kitaoka |
120a6e |
clusterFound->eigenVector[2] = eigenVector[2];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(eigenVector[0]));
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(eigenVector[1]));
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(eigenVector[2]));
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//----------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
unsigned short int calcCovarianceEigenValues(
|
|
Shinya Kitaoka |
120a6e |
const KEYER_FLOAT clusterCovariance[9], KEYER_FLOAT eigenValues[3]) {
|
|
Shinya Kitaoka |
120a6e |
unsigned short int multeplicity = 0;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a11 = clusterCovariance[0];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a12 = clusterCovariance[1];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a13 = clusterCovariance[2];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a22 = clusterCovariance[4];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a23 = clusterCovariance[5];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a33 = clusterCovariance[8];
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT c0 =
|
|
Shinya Kitaoka |
120a6e |
(KEYER_FLOAT)(a11 * a22 * a33 + 2.0 * a12 * a13 * a23 - a11 * a23 * a23 -
|
|
Shinya Kitaoka |
120a6e |
a22 * a13 * a13 - a33 * a12 * a12);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT c1 = (KEYER_FLOAT)(a11 * a22 - a12 * a12 + a11 * a33 - a13 * a13 +
|
|
Shinya Kitaoka |
120a6e |
a22 * a33 - a23 * a23);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT c2 = (KEYER_FLOAT)(a11 + a22 + a33);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
int solutionsCount = 0;
|
|
Shinya Kitaoka |
120a6e |
SolveCubic((KEYER_FLOAT)-1.0, c2, -c1, c0, &solutionsCount, eigenValues);
|
|
Shinya Kitaoka |
120a6e |
assert(solutionsCount > 0);
|
|
Shinya Kitaoka |
120a6e |
multeplicity = 4 - solutionsCount;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(eigenValues[0]));
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(eigenValues[1]));
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(eigenValues[2]));
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
assert(multeplicity > 0);
|
|
Shinya Kitaoka |
120a6e |
return multeplicity;
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//----------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
void SolveCubic(KEYER_FLOAT a, /* coefficient of x^3 */
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT b, /* coefficient of x^2 */
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT c, /* coefficient of x */
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT d, /* constant term */
|
|
Shinya Kitaoka |
120a6e |
int *solutions, /* # of distinct solutions */
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT *x) /* array of solutions */
|
|
Toshihiro Shimizu |
890ddd |
{
|
|
Shinya Kitaoka |
120a6e |
static const KEYER_FLOAT epsilon = (KEYER_FLOAT)0.0001;
|
|
Shinya Kitaoka |
120a6e |
if (a != 0 && fabs(b - 0.0) <= epsilon && fabs(c - 0.0) <= epsilon &&
|
|
Shinya Kitaoka |
120a6e |
fabs(d - 0.0) <= epsilon)
|
|
Shinya Kitaoka |
120a6e |
// if(a != 0 && b == 0 && c == 0 && d == 0)
|
|
Shinya Kitaoka |
120a6e |
{
|
|
Shinya Kitaoka |
120a6e |
*solutions = 1;
|
|
Shinya Kitaoka |
120a6e |
x[0] = x[1] = x[2] = 0.0;
|
|
Shinya Kitaoka |
120a6e |
return;
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a1 = (KEYER_FLOAT)(b / a);
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a2 = (KEYER_FLOAT)(c / a);
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT a3 = (KEYER_FLOAT)(d / a);
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT Q = (KEYER_FLOAT)((a1 * a1 - 3.0 * a2) / 9.0);
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT R =
|
|
Shinya Kitaoka |
120a6e |
(KEYER_FLOAT)((2.0 * a1 * a1 * a1 - 9.0 * a1 * a2 + 27.0 * a3) / 54.0);
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT R2_Q3 = (KEYER_FLOAT)(R * R - Q * Q * Q);
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT theta;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT PI = (KEYER_FLOAT)3.1415926535897932384626433832795;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
if (R2_Q3 <= 0) {
|
|
Shinya Kitaoka |
120a6e |
*solutions = 3;
|
|
Shinya Kitaoka |
120a6e |
theta = (KEYER_FLOAT)acos(R / sqrt(Q * Q * Q));
|
|
Shinya Kitaoka |
120a6e |
x[0] = (KEYER_FLOAT)(-2.0 * sqrt(Q) * cos(theta / 3.0) - a1 / 3.0);
|
|
Shinya Kitaoka |
120a6e |
x[1] = (KEYER_FLOAT)(-2.0 * sqrt(Q) * cos((theta + 2.0 * PI) / 3.0) -
|
|
Shinya Kitaoka |
120a6e |
a1 / 3.0);
|
|
Shinya Kitaoka |
120a6e |
x[2] = (KEYER_FLOAT)(-2.0 * sqrt(Q) * cos((theta + 4.0 * PI) / 3.0) -
|
|
Shinya Kitaoka |
120a6e |
a1 / 3.0);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(x[0]));
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(x[1]));
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(x[2]));
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
/*
|
|
Shinya Kitaoka |
120a6e |
long KEYER_FLOAT v;
|
|
Shinya Kitaoka |
120a6e |
v = x[0];
|
|
Shinya Kitaoka |
120a6e |
assert(areAlmostEqual(a*v*v*v+b*v*v+c*v+d, 0.0));
|
|
Shinya Kitaoka |
120a6e |
v = x[1];
|
|
Shinya Kitaoka |
120a6e |
assert(areAlmostEqual(a*v*v*v+b*v*v+c*v+d, 0.0));
|
|
Shinya Kitaoka |
120a6e |
v = x[2];
|
|
Shinya Kitaoka |
120a6e |
assert(areAlmostEqual(a*v*v*v+b*v*v+c*v+d, 0.0));
|
|
Shinya Kitaoka |
120a6e |
*/
|
|
Shinya Kitaoka |
120a6e |
} else {
|
|
Shinya Kitaoka |
120a6e |
*solutions = 1;
|
|
Shinya Kitaoka |
120a6e |
x[0] = (KEYER_FLOAT)pow((float)(sqrt(R2_Q3) + fabs(R)), (float)(1 / 3.0));
|
|
Shinya Kitaoka |
120a6e |
x[0] += (KEYER_FLOAT)(Q / x[0]);
|
|
Shinya Kitaoka |
120a6e |
x[0] *= (KEYER_FLOAT)((R < 0.0) ? 1 : -1);
|
|
Shinya Kitaoka |
120a6e |
x[0] -= (KEYER_FLOAT)(a1 / 3.0);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(x[0]));
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
/*
|
|
Shinya Kitaoka |
120a6e |
long KEYER_FLOAT v;
|
|
Shinya Kitaoka |
120a6e |
v = x[0];
|
|
Shinya Kitaoka |
120a6e |
assert(areAlmostEqual(a*v*v*v+b*v*v+c*v+d, 0.0));
|
|
Shinya Kitaoka |
120a6e |
*/
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//----------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Campbell Barton |
8c6c57 |
static void clusterize(ClusterContainer &clusters, int clustersCount) {
|
|
Shinya Kitaoka |
120a6e |
unsigned int clustersSize = clusters.size();
|
|
Shinya Kitaoka |
120a6e |
assert(clustersSize >= 1);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
// faccio in modo che in clusters ci siano solo e sempre le foglie
|
|
Shinya Kitaoka |
120a6e |
// dell'albero calcolato secondo l'algoritmo TSE descritto da Orchard-Bouman
|
|
Shinya Kitaoka |
120a6e |
// (c.f.r. "Color Quantization of Images" - M.Orchard, C. Bouman)
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
// numero di iterazioni, numero di cluster = numero di iterazioni + 1
|
|
Shinya Kitaoka |
120a6e |
int m = clustersCount - 1;
|
|
Shinya Kitaoka |
120a6e |
int i = 0;
|
|
Shinya Kitaoka |
120a6e |
for (; i < m; ++i) {
|
|
Shinya Kitaoka |
120a6e |
// sceglie la foglia dell'albero dei cluster (ovvero il cluster nel
|
|
Shinya Kitaoka |
120a6e |
// ClusterContainer "clusters") che ha il maggiore autovalore, ovvero
|
|
Shinya Kitaoka |
120a6e |
// il cluster che ha maggiore varainza rispetto all'asse opportuno
|
|
Shinya Kitaoka |
120a6e |
// (che poi e' l'autovettore corrispondente all'autovalore piu' grande)
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT eigenValue = 0.0;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT eigenVector[3] = {0.0, 0.0, 0.0};
|
|
Shinya Kitaoka |
120a6e |
ClusterContainer::iterator itChoosedCluster;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
chooseLeafToClusterize(itChoosedCluster, eigenValue, eigenVector, clusters);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
assert(itChoosedCluster != clusters.end());
|
|
Shinya Kitaoka |
120a6e |
Cluster *choosedCluster = *itChoosedCluster;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#if 0
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
// se il cluster che si e' scelto per la suddivisione contiene un solo
|
|
Toshihiro Shimizu |
890ddd |
// elemento vuol dire che non c'e' piu' niente da suddividere e si esce
|
|
Toshihiro Shimizu |
890ddd |
// dal ciclo.
|
|
Toshihiro Shimizu |
890ddd |
// Questo succede quando si sono chiesti piu' clusters di quanti elementi
|
|
Toshihiro Shimizu |
890ddd |
// ci sono nel cluster iniziale.
|
|
Toshihiro Shimizu |
890ddd |
if(choosedCluster->statistic.elemsCount == 1)
|
|
Toshihiro Shimizu |
890ddd |
break;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#else
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
// un cluster che ha un solo elemento non ha molto senso di esistere,
|
|
Shinya Kitaoka |
120a6e |
// credo crei problemi anche nel calcolo della matrice di covarianza,
|
|
Shinya Kitaoka |
120a6e |
// quindi mi fermo quando il cluster contiene meno di 4 elementi
|
|
Shinya Kitaoka |
120a6e |
if (choosedCluster->statistic.elemsCount == 3) break;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#endif
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
// suddivide il cluster scelto in altri due cluster
|
|
Shinya Kitaoka |
120a6e |
Cluster *subcluster1 = new Cluster();
|
|
Shinya Kitaoka |
120a6e |
Cluster *subcluster2 = new Cluster();
|
|
Shinya Kitaoka |
120a6e |
split(subcluster1, subcluster2, eigenVector, choosedCluster);
|
|
Shinya Kitaoka |
120a6e |
assert(subcluster1);
|
|
Shinya Kitaoka |
120a6e |
assert(subcluster2);
|
|
Shinya Kitaoka |
120a6e |
if ((subcluster1->data.size() == 0) || (subcluster2->data.size() == 0))
|
|
Shinya Kitaoka |
120a6e |
break;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
// calcola la nuova statistica per subcluster1
|
|
Shinya Kitaoka |
120a6e |
subcluster1->computeStatistics();
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
// calcola la nuova statistica per subcluster2
|
|
Shinya Kitaoka |
120a6e |
int j = 0;
|
|
Shinya Kitaoka |
120a6e |
for (; j < 3; ++j) {
|
|
Shinya Kitaoka |
120a6e |
subcluster2->statistic.sumComponents[j] =
|
|
Shinya Kitaoka |
120a6e |
choosedCluster->statistic.sumComponents[j] -
|
|
Shinya Kitaoka |
120a6e |
subcluster1->statistic.sumComponents[j];
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
subcluster2->statistic.sumCoords.x = choosedCluster->statistic.sumCoords.x -
|
|
Shinya Kitaoka |
120a6e |
subcluster1->statistic.sumCoords.x;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
subcluster2->statistic.sumCoords.y = choosedCluster->statistic.sumCoords.y -
|
|
Shinya Kitaoka |
120a6e |
subcluster1->statistic.sumCoords.y;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
subcluster2->statistic.elemsCount = choosedCluster->statistic.elemsCount -
|
|
Shinya Kitaoka |
120a6e |
subcluster1->statistic.elemsCount;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#ifdef WITH_ALPHA_IN_STATISTICS
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
subcluster2->statistic.sumAlpha =
|
|
Shinya Kitaoka |
120a6e |
choosedCluster->statistic.sumAlpha - subcluster1->statistic.sumAlpha;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#endif
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
for (j = 0; j < 9; ++j)
|
|
Shinya Kitaoka |
120a6e |
subcluster2->statistic.matrixR[j] = choosedCluster->statistic.matrixR[j] -
|
|
Shinya Kitaoka |
120a6e |
subcluster1->statistic.matrixR[j];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
subcluster2->computeCovariance();
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
// aggiorna in modo opportuno il ClusterContainer "clusters", cancellando
|
|
Shinya Kitaoka |
120a6e |
// il cluster scelto e inserendo i due appena creati.
|
|
Shinya Kitaoka |
120a6e |
// Facendo cosi' il ClusterContainer "cluster" contiene solo e sempre
|
|
Shinya Kitaoka |
120a6e |
// le foglie dell'albero creato dall'algoritmo TSE.
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
Cluster *cluster = *itChoosedCluster;
|
|
Shinya Kitaoka |
120a6e |
assert(cluster);
|
|
Shinya Kitaoka |
120a6e |
cluster->data.clear();
|
|
Shinya Kitaoka |
120a6e |
// clearPointerContainer(cluster->data);
|
|
Shinya Kitaoka |
120a6e |
assert(cluster->data.size() == 0);
|
|
Shinya Kitaoka |
120a6e |
delete cluster;
|
|
Shinya Kitaoka |
120a6e |
clusters.erase(itChoosedCluster);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
clusters.push_back(subcluster1);
|
|
Shinya Kitaoka |
120a6e |
clusters.push_back(subcluster2);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
Cluster::Cluster() {}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
Cluster::Cluster(const Cluster &rhs) : statistic(rhs.statistic) {
|
|
Shinya Kitaoka |
120a6e |
ClusterElemContainer::const_iterator it = rhs.data.begin();
|
|
Shinya Kitaoka |
120a6e |
for (; it != rhs.data.end(); ++it) data.push_back(new ClusterElem(**it));
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
Cluster::~Cluster() { clearPointerContainer(data); }
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
void Cluster::computeCovariance() {
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT sumComponentsMatrix[9];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT sumR = statistic.sumComponents[0];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT sumG = statistic.sumComponents[1];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT sumB = statistic.sumComponents[2];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
sumComponentsMatrix[0] = sumR * sumR;
|
|
Shinya Kitaoka |
120a6e |
sumComponentsMatrix[1] = sumR * sumG;
|
|
Shinya Kitaoka |
120a6e |
sumComponentsMatrix[2] = sumR * sumB;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
sumComponentsMatrix[3] = sumComponentsMatrix[1];
|
|
Shinya Kitaoka |
120a6e |
sumComponentsMatrix[4] = sumG * sumG;
|
|
Shinya Kitaoka |
120a6e |
sumComponentsMatrix[5] = sumG * sumB;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
sumComponentsMatrix[6] = sumComponentsMatrix[2];
|
|
Shinya Kitaoka |
120a6e |
sumComponentsMatrix[7] = sumComponentsMatrix[5];
|
|
Shinya Kitaoka |
120a6e |
sumComponentsMatrix[8] = sumB * sumB;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT n = (KEYER_FLOAT)statistic.elemsCount;
|
|
Shinya Kitaoka |
120a6e |
assert(n > 0);
|
|
Shinya Kitaoka |
120a6e |
int i = 0;
|
|
Shinya Kitaoka |
120a6e |
for (; i < 9; ++i) {
|
|
Shinya Kitaoka |
120a6e |
statistic.covariance[i] = statistic.matrixR[i] - sumComponentsMatrix[i] / n;
|
|
Shinya Kitaoka |
120a6e |
assert(!ISNAN(statistic.matrixR[i]));
|
|
Shinya Kitaoka |
120a6e |
// assert(statistic.covariance[i] >= 0.0);
|
|
Shinya Kitaoka |
120a6e |
// instabilita' numerica ???
|
|
Shinya Kitaoka |
120a6e |
if (statistic.covariance[i] < 0.0) statistic.covariance[i] = 0.0;
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
void Cluster::insert(ClusterElem *elem) {
|
|
Toshihiro Shimizu |
890ddd |
#ifdef CLUSTER_ELEM_CONTAINER_IS_A_SET
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
data.insert(elem);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#else
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
data.push_back(elem);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#endif
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
void Cluster::computeStatistics() {
|
|
Shinya Kitaoka |
120a6e |
// inizializza a zero la statistica del cluster
|
|
Shinya Kitaoka |
120a6e |
statistic.elemsCount = 0;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
statistic.sumCoords = TPoint(0, 0);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
int i = 0;
|
|
Shinya Kitaoka |
120a6e |
for (; i < 3; ++i) statistic.sumComponents[i] = 0.0;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
for (i = 0; i < 9; ++i) statistic.matrixR[i] = 0.0;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
// calcola la statistica del cluster
|
|
Shinya Kitaoka |
120a6e |
ClusterElemContainer::const_iterator it = data.begin();
|
|
Shinya Kitaoka |
120a6e |
for (; it != data.end(); ++it) {
|
|
Shinya Kitaoka |
120a6e |
const ClusterElem *elem = *it;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#ifdef WITH_ALPHA_IN_STATISTICS
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT alpha = elem->a;
|
|
Toshihiro Shimizu |
890ddd |
#endif
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT r = (KEYER_FLOAT)elem->r;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT g = (KEYER_FLOAT)elem->g;
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT b = (KEYER_FLOAT)elem->b;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
statistic.sumComponents[0] += r;
|
|
Shinya Kitaoka |
120a6e |
statistic.sumComponents[1] += g;
|
|
Shinya Kitaoka |
120a6e |
statistic.sumComponents[2] += b;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#ifdef WITH_ALPHA_IN_STATISTICS
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
statistic.sumAlpha += alpha;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#endif
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
// prima riga della matrice R
|
|
Shinya Kitaoka |
120a6e |
statistic.matrixR[0] += r * r;
|
|
Shinya Kitaoka |
120a6e |
statistic.matrixR[1] += r * g;
|
|
Shinya Kitaoka |
120a6e |
statistic.matrixR[2] += r * b;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
// seconda riga della matrice R
|
|
Shinya Kitaoka |
120a6e |
statistic.matrixR[3] += r * g;
|
|
Shinya Kitaoka |
120a6e |
statistic.matrixR[4] += g * g;
|
|
Shinya Kitaoka |
120a6e |
statistic.matrixR[5] += g * b;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
// terza riga della matrice R
|
|
Shinya Kitaoka |
120a6e |
statistic.matrixR[6] += r * b;
|
|
Shinya Kitaoka |
120a6e |
statistic.matrixR[7] += b * g;
|
|
Shinya Kitaoka |
120a6e |
statistic.matrixR[8] += b * b;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
statistic.sumCoords.x += elem->x;
|
|
Shinya Kitaoka |
120a6e |
statistic.sumCoords.y += elem->y;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
++statistic.elemsCount;
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
assert(statistic.elemsCount > 0);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
computeCovariance();
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
void Cluster::getMeanAxis(KEYER_FLOAT axis[3]) {
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT n = (KEYER_FLOAT)statistic.elemsCount;
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#if 1
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
axis[0] = (KEYER_FLOAT)(sqrt(statistic.covariance[0]) / n);
|
|
Shinya Kitaoka |
120a6e |
axis[1] = (KEYER_FLOAT)(sqrt(statistic.covariance[4]) / n);
|
|
Shinya Kitaoka |
120a6e |
axis[2] = (KEYER_FLOAT)(sqrt(statistic.covariance[8]) / n);
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#else
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT I[3];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT J[3];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT K[3];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
I[0] = statistic.covariance[0];
|
|
Shinya Kitaoka |
120a6e |
I[1] = statistic.covariance[1];
|
|
Shinya Kitaoka |
120a6e |
I[2] = statistic.covariance[2];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
J[0] = statistic.covariance[3];
|
|
Shinya Kitaoka |
120a6e |
J[1] = statistic.covariance[4];
|
|
Shinya Kitaoka |
120a6e |
J[2] = statistic.covariance[5];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
K[0] = statistic.covariance[6];
|
|
Shinya Kitaoka |
120a6e |
K[1] = statistic.covariance[7];
|
|
Shinya Kitaoka |
120a6e |
K[2] = statistic.covariance[8];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT magnitudeI = I[0] * I[0] + I[1] * I[1] + I[2] * I[2];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT magnitudeJ = J[0] * J[0] + J[1] * J[1] + J[2] * I[2];
|
|
Shinya Kitaoka |
120a6e |
KEYER_FLOAT magnitudeK = K[0] * K[0] + K[1] * K[1] + K[2] * I[2];
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
if (magnitudeI >= magnitudeJ && magnitudeI >= magnitudeK) {
|
|
Shinya Kitaoka |
120a6e |
axis[0] = sqrt(I[0] / n);
|
|
Shinya Kitaoka |
120a6e |
axis[1] = sqrt(I[1] / n);
|
|
Shinya Kitaoka |
120a6e |
axis[2] = sqrt(I[2] / n);
|
|
Shinya Kitaoka |
120a6e |
} else if (magnitudeJ >= magnitudeI && magnitudeJ >= magnitudeK) {
|
|
Shinya Kitaoka |
120a6e |
axis[0] = sqrt(J[0] / n);
|
|
Shinya Kitaoka |
120a6e |
axis[1] = sqrt(J[1] / n);
|
|
Shinya Kitaoka |
120a6e |
axis[2] = sqrt(J[2] / n);
|
|
Shinya Kitaoka |
120a6e |
} else if (magnitudeK >= magnitudeI && magnitudeK >= magnitudeJ) {
|
|
Shinya Kitaoka |
120a6e |
axis[0] = sqrt(K[0] / n);
|
|
Shinya Kitaoka |
120a6e |
axis[1] = sqrt(K[1] / n);
|
|
Shinya Kitaoka |
120a6e |
axis[2] = sqrt(K[2] / n);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
#endif
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//#define METODO_USATO_SU_TOONZ46
|
|
Toshihiro Shimizu |
890ddd |
|
|
Campbell Barton |
8c6c57 |
static void buildPaletteForBlendedImages(std::set<tpixel32> &palette,</tpixel32>
|
|
Campbell Barton |
8c6c57 |
const TRaster32P &raster, int maxColorCount) {
|
|
Shinya Kitaoka |
120a6e |
int lx = raster->getLx();
|
|
Shinya Kitaoka |
120a6e |
int ly = raster->getLy();
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
ClusterContainer clusters;
|
|
Shinya Kitaoka |
120a6e |
Cluster *cluster = new Cluster;
|
|
Shinya Kitaoka |
120a6e |
raster->lock();
|
|
Shinya Kitaoka |
120a6e |
for (int y = 0; y < ly; ++y) {
|
|
Shinya Kitaoka |
120a6e |
TPixel32 *pix = raster->pixels(y);
|
|
Shinya Kitaoka |
120a6e |
for (int x = 0; x < lx; ++x) {
|
|
Shinya Kitaoka |
120a6e |
TPixel32 color = *(pix + x);
|
|
Shinya Kitaoka |
120a6e |
ClusterElem *ce =
|
|
Shinya Kitaoka |
120a6e |
new ClusterElem(color.r, color.g, color.b, (float)(color.m / 255.0));
|
|
Shinya Kitaoka |
120a6e |
cluster->insert(ce);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
raster->unlock();
|
|
Shinya Kitaoka |
120a6e |
cluster->computeStatistics();
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
clusters.push_back(cluster);
|
|
Shinya Kitaoka |
120a6e |
clusterize(clusters, maxColorCount);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
palette.clear();
|
|
Shinya Kitaoka |
120a6e |
// palette.reserve( clusters.size());
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
for (UINT i = 0; i < clusters.size(); ++i) {
|
|
Shinya Kitaoka |
120a6e |
ClusterStatistic &stat = clusters[i]->statistic;
|
|
Shinya Kitaoka |
120a6e |
TPixel32 col((int)(stat.sumComponents[0] / stat.elemsCount * 255),
|
|
Shinya Kitaoka |
120a6e |
(int)(stat.sumComponents[1] / stat.elemsCount * 255),
|
|
Shinya Kitaoka |
120a6e |
(int)(stat.sumComponents[2] / stat.elemsCount * 255), 255);
|
|
Shinya Kitaoka |
120a6e |
palette.insert(col);
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
clearPointerContainer(clusters[i]->data);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
clearPointerContainer(clusters);
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
namespace {
|
|
Toshihiro Shimizu |
890ddd |
#define DISTANCE 3
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
bool inline areNear(const TPixel &c1, const TPixel &c2) {
|
|
Shinya Kitaoka |
120a6e |
if (abs(c1.r - c2.r) > DISTANCE) return false;
|
|
Shinya Kitaoka |
120a6e |
if (abs(c1.g - c2.g) > DISTANCE) return false;
|
|
Shinya Kitaoka |
120a6e |
if (abs(c1.b - c2.b) > DISTANCE) return false;
|
|
Shinya Kitaoka |
120a6e |
if (abs(c1.m - c2.m) > DISTANCE) return false;
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
return true;
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
bool find(const std::set<tpixel32> &palette, const TPixel &color) {</tpixel32>
|
|
Shinya Kitaoka |
120a6e |
std::set<tpixel32>::const_iterator it = palette.begin();</tpixel32>
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
while (it != palette.end()) {
|
|
Shinya Kitaoka |
120a6e |
if (areNear(*it, color)) return true;
|
|
Shinya Kitaoka |
120a6e |
++it;
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
return false;
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Shinya Kitaoka |
120a6e |
} // namespace
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
/*-- 似ている色をまとめて1つのStyleにする --*/
|
|
Shinya Kitaoka |
120a6e |
void TColorUtils::buildPalette(std::set<tpixel32> &palette,</tpixel32>
|
|
Shinya Kitaoka |
120a6e |
const TRaster32P &raster, int maxColorCount) {
|
|
Shinya Kitaoka |
120a6e |
int lx = raster->getLx();
|
|
Shinya Kitaoka |
120a6e |
int ly = raster->getLy();
|
|
Shinya Kitaoka |
120a6e |
int wrap = raster->getWrap();
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
int x, y;
|
|
Shinya Kitaoka |
120a6e |
TPixel old = TPixel::Black;
|
|
Shinya Kitaoka |
120a6e |
int solidColors = 0;
|
|
Shinya Kitaoka |
120a6e |
int count = maxColorCount;
|
|
Shinya Kitaoka |
120a6e |
raster->lock();
|
|
Shinya Kitaoka |
120a6e |
for (y = 1; y < ly - 1 && count > 0; y++) {
|
|
Shinya Kitaoka |
120a6e |
TPixel *pix = raster->pixels(y);
|
|
Shinya Kitaoka |
120a6e |
for (x = 1; x < lx - 1 && count > 0; x++, pix++) {
|
|
Shinya Kitaoka |
120a6e |
TPixel color = *pix;
|
|
Shinya Kitaoka |
120a6e |
if (areNear(color, *(pix - 1)) && areNear(color, *(pix + 1)) &&
|
|
Shinya Kitaoka |
120a6e |
areNear(color, *(pix - wrap)) && areNear(color, *(pix + wrap)) &&
|
|
Shinya Kitaoka |
120a6e |
areNear(color, *(pix - wrap - 1)) &&
|
|
Shinya Kitaoka |
120a6e |
areNear(color, *(pix - wrap + 1)) &&
|
|
Shinya Kitaoka |
120a6e |
areNear(color, *(pix + wrap - 1)) &&
|
|
Shinya Kitaoka |
120a6e |
areNear(color, *(pix + wrap + 1))) {
|
|
Shinya Kitaoka |
120a6e |
solidColors++;
|
|
Shinya Kitaoka |
120a6e |
if (!areNear(*pix, old) && !find(palette, *pix)) {
|
|
Shinya Kitaoka |
120a6e |
old = color;
|
|
Shinya Kitaoka |
120a6e |
count--;
|
|
Shinya Kitaoka |
120a6e |
palette.insert(color);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
raster->unlock();
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
if (solidColors < lx * ly / 2) {
|
|
Shinya Kitaoka |
120a6e |
palette.clear();
|
|
Shinya Kitaoka |
120a6e |
buildPaletteForBlendedImages(palette, raster, maxColorCount);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
/*-- 全ての異なるピクセルの色を別のStyleにする --*/
|
|
Shinya Kitaoka |
120a6e |
void TColorUtils::buildPrecisePalette(std::set<tpixel32> &palette,</tpixel32>
|
|
Shinya Kitaoka |
120a6e |
const TRaster32P &raster,
|
|
Shinya Kitaoka |
120a6e |
int maxColorCount) {
|
|
Shinya Kitaoka |
120a6e |
int lx = raster->getLx();
|
|
Shinya Kitaoka |
120a6e |
int ly = raster->getLy();
|
|
Shinya Kitaoka |
120a6e |
int wrap = raster->getWrap();
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
int x, y;
|
|
Shinya Kitaoka |
120a6e |
int count = maxColorCount;
|
|
Shinya Kitaoka |
120a6e |
raster->lock();
|
|
Shinya Kitaoka |
120a6e |
for (y = 1; y < ly - 1 && count > 0; y++) {
|
|
Shinya Kitaoka |
120a6e |
TPixel *pix = raster->pixels(y);
|
|
Shinya Kitaoka |
120a6e |
for (x = 1; x < lx - 1 && count > 0; x++, pix++) {
|
|
Shinya Kitaoka |
120a6e |
if (!find(palette, *pix)) {
|
|
Shinya Kitaoka |
120a6e |
TPixel color = *pix;
|
|
Shinya Kitaoka |
120a6e |
count--;
|
|
Shinya Kitaoka |
120a6e |
palette.insert(color);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
raster->unlock();
|
|
Shinya Kitaoka |
120a6e |
|
|
Shinya Kitaoka |
120a6e |
/*-- 色数が最大値を超えたら、似ている色をまとめて1つのStyleにする手法を行う
|
|
Shinya Kitaoka |
120a6e |
* --*/
|
|
Shinya Kitaoka |
120a6e |
if (count == 0) {
|
|
Shinya Kitaoka |
120a6e |
palette.clear();
|
|
Shinya Kitaoka |
120a6e |
buildPalette(palette, raster, maxColorCount);
|
|
Shinya Kitaoka |
120a6e |
}
|
|
Toshihiro Shimizu |
890ddd |
}
|
|
Toshihiro Shimizu |
890ddd |
|
|
Toshihiro Shimizu |
890ddd |
//------------------------------------------------------------------------------
|