//extrait les composantes connexes d'un nuage
//--> version avec des ReferenceCloud (uniquement des références vers les points)
//pour permettre une récupération au niveau de l'application cliente
//des couleurs, normales, etc.
bool AutoSegmentationTools::extractConnectedComponents(GenericIndexedCloudPersist* theCloud, ReferenceCloudContainer& cc)
{
if (!theCloud)
return false;
unsigned numberOfPoints = theCloud->size();
if (numberOfPoints<1)
return false;
//on admet que "labelConnectedComponents" a bien déjà été appelé
//les labels des CCs sont alors stockées dans le champ scalaire "courant"
cc.clear();
//theCloud->placeIteratorAtBegining();
for (unsigned i=0;i<numberOfPoints;++i)
{
int ccLabel=(int)theCloud->getPointScalarValue(i)-1; //les labels commencent à 1 !
//on remplit le vecteur de "CCs" vides jusqu'à arriver au bon numéro de CC
//on s'occupera en théorie des autres plus tard
while (ccLabel>=(int)cc.size())
cc.push_back(new ReferenceCloud(theCloud));
//on rajoute le point à la CC courante
cc[ccLabel]->addPointIndex(i);
}
return true;
}
bool AutoSegmentationTools::extractConnectedComponents(GenericIndexedCloudPersist* theCloud, ReferenceCloudContainer& cc)
{
unsigned numberOfPoints = (theCloud ? theCloud->size() : 0);
if (numberOfPoints == 0)
{
return false;
}
//components should have already been labeled and labels should have been stored in the active scalar field!
if (!theCloud->isScalarFieldEnabled())
{
return false;
}
//empty the input vector if necessary
while (!cc.empty())
{
delete cc.back();
cc.pop_back();
}
for (unsigned i = 0; i < numberOfPoints; ++i)
{
ScalarType slabel = theCloud->getPointScalarValue(i);
if (slabel >= 1) //labels start from 1! (this test rejects NaN values as well)
{
int ccLabel = static_cast<int>(theCloud->getPointScalarValue(i)) - 1;
//we fill the components vector with empty components until we reach the current label
//(they will be "used" later)
try
{
while (static_cast<size_t>(ccLabel) >= cc.size())
{
cc.push_back(new ReferenceCloud(theCloud));
}
}
catch (const std::bad_alloc&)
{
//not enough memory
cc.clear();
return false;
}
//add the point to the current component
if (!cc[ccLabel]->addPointIndex(i))
{
//not enough memory
while (!cc.empty())
{
delete cc.back();
cc.pop_back();
}
return false;
}
}
}
return true;
}
bool AutoSegmentationTools::frontPropagationBasedSegmentation(GenericIndexedCloudPersist* theCloud,
ScalarType minSeedDist,
uchar octreeLevel,
ReferenceCloudContainer& theSegmentedLists,
GenericProgressCallback* progressCb,
DgmOctree* inputOctree,
bool applyGaussianFilter,
float alpha)
{
unsigned numberOfPoints = (theCloud ? theCloud->size() : 0);
if (numberOfPoints == 0)
return false;
//compute octree if none was provided
DgmOctree* theOctree = inputOctree;
if (!theOctree)
{
theOctree = new DgmOctree(theCloud);
if (theOctree->build(progressCb)<1)
{
delete theOctree;
return false;
}
}
//on calcule le gradient (va ecraser le champ des distances)
if (ScalarFieldTools::computeScalarFieldGradient(theCloud,true,true,progressCb,theOctree) < 0)
{
if (!inputOctree)
delete theOctree;
return false;
}
//et on lisse le resultat
if (applyGaussianFilter)
{
uchar level = theOctree->findBestLevelForAGivenPopulationPerCell(NUMBER_OF_POINTS_FOR_GRADIENT_COMPUTATION);
PointCoordinateType cellSize = theOctree->getCellSize(level);
ScalarFieldTools::applyScalarFieldGaussianFilter(static_cast<float>(cellSize/3),theCloud,-1,progressCb,theOctree);
}
unsigned seedPoints = 0;
unsigned numberOfSegmentedLists = 0;
//on va faire la propagation avec le FastMarching();
FastMarchingForPropagation* fm = new FastMarchingForPropagation();
fm->setJumpCoef(50.0);
fm->setDetectionThreshold(alpha);
int result = fm->init(theCloud,theOctree,octreeLevel);
int octreeLength = OCTREE_LENGTH(octreeLevel)-1;
if (result<0)
{
if (!inputOctree)
delete theOctree;
delete fm;
return false;
}
if (progressCb)
{
progressCb->reset();
progressCb->setMethodTitle("FM Propagation");
char buffer[256];
sprintf(buffer,"Octree level: %i\nNumber of points: %u",octreeLevel,numberOfPoints);
progressCb->setInfo(buffer);
progressCb->start();
}
ScalarField* theDists = new ScalarField("distances");
{
ScalarType d = theCloud->getPointScalarValue(0);
if (!theDists->resize(numberOfPoints,true,d))
{
if (!inputOctree)
delete theOctree;
return false;
}
}
unsigned maxDistIndex = 0, begin = 0;
CCVector3 startPoint;
while (true)
{
ScalarType maxDist = NAN_VALUE;
//on cherche la premiere distance superieure ou egale a "minSeedDist"
while (begin<numberOfPoints)
{
const CCVector3 *thePoint = theCloud->getPoint(begin);
const ScalarType& theDistance = theDists->getValue(begin);
++begin;
//FIXME DGM: what happens if SF is negative?!
if (theCloud->getPointScalarValue(begin) >= 0 && theDistance >= minSeedDist)
{
maxDist = theDistance;
startPoint = *thePoint;
maxDistIndex = begin;
break;
}
}
//il n'y a plus de point avec des distances suffisamment grandes !
if (maxDist<minSeedDist)
break;
//on finit la recherche du max
for (unsigned i=begin; i<numberOfPoints; ++i)
{
const CCVector3 *thePoint = theCloud->getPoint(i);
const ScalarType& theDistance = theDists->getValue(i);
if ((theCloud->getPointScalarValue(i)>=0.0)&&(theDistance > maxDist))
{
maxDist = theDistance;
startPoint = *thePoint;
maxDistIndex = i;
}
}
int pos[3];
theOctree->getTheCellPosWhichIncludesThePoint(&startPoint,pos,octreeLevel);
//clipping (important!)
pos[0] = std::min(octreeLength,pos[0]);
pos[1] = std::min(octreeLength,pos[1]);
pos[2] = std::min(octreeLength,pos[2]);
fm->setSeedCell(pos);
++seedPoints;
int result = fm->propagate();
//if the propagation was successful
if (result >= 0)
{
//we extract the corresponding points
ReferenceCloud* newCloud = new ReferenceCloud(theCloud);
if (fm->extractPropagatedPoints(newCloud) && newCloud->size() != 0)
{
theSegmentedLists.push_back(newCloud);
++numberOfSegmentedLists;
}
else
{
//not enough memory?!
delete newCloud;
newCloud = 0;
}
if (progressCb)
progressCb->update(float(numberOfSegmentedLists % 100));
fm->cleanLastPropagation();
//break;
}
if (maxDistIndex == begin)
++begin;
}
if (progressCb)
progressCb->stop();
for (unsigned i=0; i<numberOfPoints; ++i)
theCloud->setPointScalarValue(i,theDists->getValue(i));
delete fm;
fm = 0;
theDists->release();
theDists = 0;
if (!inputOctree)
delete theOctree;
return true;
}
bool AutoSegmentationTools::frontPropagationBasedSegmentation(GenericIndexedCloudPersist* theCloud,
bool signedSF,
DistanceType minSeedDist,
uchar octreeLevel,
ReferenceCloudContainer& theSegmentedLists,
GenericProgressCallback* progressCb,
DgmOctree* _theOctree,
bool applyGaussianFilter,
float alpha)
{
if (!theCloud)
return false;
unsigned numberOfPoints = theCloud->size();
if (numberOfPoints<1)
return false;
//on calcule l'octree
DgmOctree* theOctree = _theOctree;
if (!theOctree)
{
theOctree = new DgmOctree(theCloud);
if (theOctree->build(progressCb)<1)
{
delete theOctree;
return false;
}
}
ScalarField* theDists = new ScalarField("distances",true);
if (!theDists->reserve(numberOfPoints))
{
if (!_theOctree)
delete theOctree;
return false;
}
theCloud->placeIteratorAtBegining();
unsigned k=0;
DistanceType d = theCloud->getPointScalarValue(k);
for (;k<numberOfPoints;++k)
theDists->addElement(d);
//on calcule le gradient (va écraser le champ des distances)
if (ScalarFieldTools::computeScalarFieldGradient(theCloud,signedSF,true,true,progressCb,theOctree)<0)
{
if (!_theOctree)
delete theOctree;
return false;
}
//et on lisse le résultat
if (applyGaussianFilter)
{
uchar level = theOctree->findBestLevelForAGivenPopulationPerCell(NUMBER_OF_POINTS_FOR_GRADIENT_COMPUTATION);
float cellSize = theOctree->getCellSize(level);
ScalarFieldTools::applyScalarFieldGaussianFilter(cellSize*0.33f,theCloud,signedSF,-1,progressCb,theOctree);
}
DistanceType maxDist;
unsigned seedPoints = 0;
unsigned numberOfSegmentedLists = 0;
//on va faire la propagation avec le FastMarching();
FastMarchingForPropagation* fm = new FastMarchingForPropagation();
fm->setJumpCoef(50.0);
fm->setDetectionThreshold(alpha);
int result = fm->init(theCloud,theOctree,octreeLevel);
int octreeLength = OCTREE_LENGTH(octreeLevel)-1;
if (result<0)
{
if (!_theOctree)
delete theOctree;
delete fm;
return false;
}
if (progressCb)
{
progressCb->reset();
progressCb->setMethodTitle("FM Propagation");
char buffer[256];
sprintf(buffer,"Octree level: %i\nNumber of points: %i",octreeLevel,numberOfPoints);
progressCb->setInfo(buffer);
progressCb->start();
}
unsigned maxDistIndex=0,begin = 0;
CCVector3 startPoint;
while (true)
{
maxDist = HIDDEN_VALUE;
//on cherche la première distance supérieure ou égale à "minSeedDist"
while (begin<numberOfPoints)
{
const CCVector3 *thePoint = theCloud->getPoint(begin);
const DistanceType& theDistance = theDists->getValue(begin);
++begin;
if ((theCloud->getPointScalarValue(begin)>=0.0)&&(theDistance >= minSeedDist))
{
maxDist = theDistance;
startPoint = *thePoint;
maxDistIndex = begin;
break;
}
}
//il n'y a plus de point avec des distances suffisamment grandes !
if (maxDist<minSeedDist)
break;
//on finit la recherche du max
for (unsigned i=begin;i<numberOfPoints;++i)
{
const CCVector3 *thePoint = theCloud->getPoint(i);
const DistanceType& theDistance = theDists->getValue(i);
if ((theCloud->getPointScalarValue(i)>=0.0)&&(theDistance > maxDist))
{
maxDist = theDistance;
startPoint = *thePoint;
maxDistIndex = i;
}
}
//on lance la propagation à partir du point de distance maximale
//propagateFromPoint(aList,_GradientNorms,maxDistIndex,octreeLevel,_gui);
int pos[3];
theOctree->getTheCellPosWhichIncludesThePoint(&startPoint,pos,octreeLevel);
//clipping (important !)
pos[0] = std::min(octreeLength,pos[0]);
pos[1] = std::min(octreeLength,pos[1]);
pos[2] = std::min(octreeLength,pos[2]);
fm->setSeedCell(pos);
++seedPoints;
int result = fm->propagate();
//si la propagation s'est bien passée
if (result>=0)
{
//on la termine (i.e. on extrait les points correspondant)
ReferenceCloud* newCloud = fm->extractPropagatedPoints();
//si la liste convient
//on la rajoute au groupe des listes segmentées
theSegmentedLists.push_back(newCloud);
++numberOfSegmentedLists;
if (progressCb)
progressCb->update(float(numberOfSegmentedLists % 100));
fm->endPropagation();
//break;
}
if (maxDistIndex == begin)
++begin;
}
if (progressCb)
progressCb->stop();
for (unsigned i=0;i<numberOfPoints;++i)
theCloud->setPointScalarValue(i,theDists->getValue(i));
delete fm;
theDists->release();
theDists=0;
if (!_theOctree)
delete theOctree;
return true;
}
