C++ cclib::ReferenceCloud类代码示例

bool ccKdTree::convertCellIndexToRandomColor()
{
	if (!m_associatedGenericCloud || !m_associatedGenericCloud->isA(CC_TYPES::POINT_CLOUD))
		return false;

	//get leaves
	std::vector<Leaf*> leaves;
	if (!getLeaves(leaves) || leaves.empty())
		return false;

	ccPointCloud* pc = static_cast<ccPointCloud*>(m_associatedGenericCloud);
	if (!pc->resizeTheRGBTable())
		return false;

	//for each cell
	for (size_t i=0; i<leaves.size(); ++i)
	{
		colorType col[3];
		ccColor::Generator::Random(col);
		CCLib::ReferenceCloud* subset = leaves[i]->points;
		if (subset)
		{
			for (unsigned j=0; j<subset->size(); ++j)
				pc->setPointColor(subset->getPointGlobalIndex(j),col);
		}
	}

	pc->showColors(true);

	return true;
}

CCLib::ReferenceCloud* ccGenericPointCloud::getTheVisiblePoints()
{
    if (!m_visibilityArray || m_visibilityArray->currentSize()<size())
        return 0;

	unsigned i,count = size();
	assert(count == m_visibilityArray->currentSize());

    //we create an entity with the 'visible' vertices only
    CCLib::ReferenceCloud* rc = new CCLib::ReferenceCloud(this);

    for (i=0;i<count;++i)
        if (m_visibilityArray->getValue(i) > 0)
            rc->addPointIndex(i);

    return rc;
}

void ccAlignDlg::dataSamplingRateChanged(double value)
{
    QString message("An error occured");

    CC_SAMPLING_METHOD method = getSamplingMethod();
    float rate = (float)dataSamplingRate->value()/(float)dataSamplingRate->maximum();
    if(method == SPACE)
        rate = 1.0f-rate;
    dataSample->setSliderPosition((unsigned)((float)dataSample->maximum()*rate));

    switch(method)
    {
        case SPACE:
			{
				CCLib::ReferenceCloud* tmpCloud = getSampledData(); //DGM FIXME: wow! you generate a spatially sampled cloud just to display its size?!
				if (tmpCloud)
				{
					message = QString("distance units (%1 remaining points)").arg(tmpCloud->size());
					delete tmpCloud;
				}
			}
            break;
        case RANDOM:
			{
				message = QString("remaining points (%1%)").arg(rate*100.0f,0,'f',1);
			}
            break;
        case OCTREE:
			{
				CCLib::ReferenceCloud* tmpCloud = getSampledData();  //DGM FIXME: wow! you generate a spatially sampled cloud just to display its size?!
				if (tmpCloud)
				{
					message = QString("%1 remaining points").arg(tmpCloud->size());
					delete tmpCloud;
				}
			}
            break;
        default:
			{
				unsigned remaining = (unsigned)(rate * (float)dataObject->size());
				message = QString("%1 remaining points").arg(remaining);
			}
            break;
    }
    dataRemaining->setText(message);
}

int ccFastMarchingForNormsDirection::updateResolvedTable(ccGenericPointCloud* theCloud,
                                                            GenericChunkedArray<1,uchar> &resolved,
                                                            NormsIndexesTableType* theNorms)
{
	if (!initialized)
		return -1;

	int count=0;
	for (unsigned i=0;i<activeCells.size();++i)
	{
		DirectionCell* aCell = (DirectionCell*)theGrid[activeCells[i]];
		CCLib::ReferenceCloud* Yk = theOctree->getPointsInCell(aCell->cellCode,gridLevel,true);
		if (!Yk)
			continue;

		Yk->placeIteratorAtBegining();
		
		for (unsigned k=0;k<Yk->size();++k)
		{
			unsigned index = Yk->getCurrentPointGlobalIndex();
			resolved.setValue(index,1); //resolvedValue=1

			const normsType& norm = theNorms->getValue(index);
			if (CCVector3::vdot(ccNormalVectors::GetNormal(norm),aCell->N)<0.0)
			{
				PointCoordinateType newN[3];
				const PointCoordinateType* N = ccNormalVectors::GetNormal(norm);
				newN[0]=-N[0];
				newN[1]=-N[1];
				newN[2]=-N[2];
				theNorms->setValue(index,ccNormalVectors::GetNormIndex(newN));
			}

			//norm = NormalVectors::getNormIndex(aCell->N);
			//theNorms->setValue(index,&norm);

			theCloud->setPointScalarValue(index,aCell->T);
			//theCloud->setPointScalarValue(index,aCell->v);
			Yk->forwardIterator();
			++count;
		}
	}

	return count;
}

CCLib::ReferenceCloud* ccGenericPointCloud::getTheVisiblePoints() const
{
	unsigned count = size();
	assert(count == m_pointsVisibility->currentSize());

	if (!m_pointsVisibility || m_pointsVisibility->currentSize() != count)
	{
		ccLog::Warning("[ccGenericPointCloud::getTheVisiblePoints] No visibility table instantiated!");
		return 0;
	}

	//count the number of points to copy
	unsigned pointCount = 0;
	{
		for (unsigned i=0; i<count; ++i)
			if (m_pointsVisibility->getValue(i) == POINT_VISIBLE)
				++pointCount;
	}

	if (pointCount == 0)
	{
		ccLog::Warning("[ccGenericPointCloud::getTheVisiblePoints] No point in selection");
		return 0;
	}

	//we create an entity with the 'visible' vertices only
	CCLib::ReferenceCloud* rc = new CCLib::ReferenceCloud(const_cast<ccGenericPointCloud*>(this));
	if (rc->reserve(pointCount))
	{
		for (unsigned i=0; i<count; ++i)
			if (m_pointsVisibility->getValue(i) == POINT_VISIBLE)
				rc->addPointIndex(i); //can't fail (see above)
	}
	else
	{
		delete rc;
		rc = 0;
		ccLog::Error("[ccGenericPointCloud::getTheVisiblePoints] Not enough memory!");
	}

	return rc;
}

bool ccKdTree::convertCellIndexToSF()
{
	if (!m_associatedGenericCloud || !m_associatedGenericCloud->isA(CC_TYPES::POINT_CLOUD))
		return false;

	//get leaves
	std::vector<Leaf*> leaves;
	if (!getLeaves(leaves) || leaves.empty())
		return false;

	ccPointCloud* pc = static_cast<ccPointCloud*>(m_associatedGenericCloud);

	const char c_defaultSFName[] = "Kd-tree indexes";
	int sfIdx = pc->getScalarFieldIndexByName(c_defaultSFName);
	if (sfIdx < 0)
		sfIdx = pc->addScalarField(c_defaultSFName);
	if (sfIdx < 0)
	{
		ccLog::Error("Not enough memory!");
		return false;
	}
	pc->setCurrentScalarField(sfIdx);

	//for each cell
	for (size_t i=0; i<leaves.size(); ++i)
	{
		CCLib::ReferenceCloud* subset = leaves[i]->points;
		if (subset)
		{
			for (unsigned j=0; j<subset->size(); ++j)
				subset->setPointScalarValue(j,(ScalarType)i);
		}
	}

	pc->getScalarField(sfIdx)->computeMinAndMax();
	pc->setCurrentDisplayedScalarField(sfIdx);
	pc->showSF(true);

	return true;
}

void ccAlignDlg::estimateDelta()
{
    unsigned i, nb;
    float meanDensity, meanSqrDensity, dev, value;
    ccProgressDialog pDlg(false,this);

    CCLib::ReferenceCloud *sampledData = getSampledData();
    //we have to work on a copy of the cloud in order to prevent the algorithms from modifying the original cloud.
    CCLib::ChunkedPointCloud* cloud = new CCLib::ChunkedPointCloud();
    cloud->reserve(sampledData->size());
    for(i=0; i<sampledData->size(); i++)
        cloud->addPoint(*sampledData->getPoint(i));
    cloud->enableScalarField();

    CCLib::GeometricalAnalysisTools::computeLocalDensity(cloud, &pDlg);
    nb = 0;
    meanDensity = 0.;
    meanSqrDensity = 0.;
    for(i=0; i<cloud->size(); i++)
    {
        value = cloud->getPointScalarValue(i);
        if(value > ZERO_TOLERANCE)
        {
            value = 1/value;
            meanDensity += value;
            meanSqrDensity += value*value;
            nb++;
        }
    }
    meanDensity /= (float)nb;
    meanSqrDensity /= (float)nb;
    dev = meanSqrDensity-(meanDensity*meanDensity);

    delta->setValue(meanDensity+dev);
    delete sampledData;
    delete cloud;
}

bool ccPointPairRegistrationDlg::convertToSphereCenter(CCVector3d& P, ccHObject* entity, PointCoordinateType& sphereRadius)
{
	sphereRadius = -PC_ONE;
	if (	!entity
		||	!useSphereToolButton->isChecked()
		||	!entity->isKindOf(CC_TYPES::POINT_CLOUD) ) //only works with cloud right now
	{
		//nothing to do
		return true;
	}

	//we'll now try to detect the sphere
	double searchRadius = radiusDoubleSpinBox->value();
	double maxRMSPercentage = maxRmsSpinBox->value() / 100.0;
	ccGenericPointCloud* cloud = static_cast<ccGenericPointCloud*>(entity);
	assert(cloud);

	//crop points inside a box centered on the current point
	ccBBox box;
	box.add(CCVector3::fromArray((P - CCVector3d(1,1,1)*searchRadius).u));
	box.add(CCVector3::fromArray((P + CCVector3d(1,1,1)*searchRadius).u));
	CCLib::ReferenceCloud* part = cloud->crop(box,true);

	bool success = false;
	if (part && part->size() > 16)
	{
		PointCoordinateType radius;
		CCVector3 C;
		double rms;
		ccProgressDialog pDlg(true, this);
		//first roughly search for the sphere
		if (CCLib::GeometricalAnalysisTools::detectSphereRobust(part,0.5,C,radius,rms,&pDlg,0.9))
		{
			if (radius / searchRadius < 0.5 || radius / searchRadius > 2.0)
			{
				ccLog::Warning(QString("[ccPointPairRegistrationDlg] Detected sphere radius (%1) is too far from search radius!").arg(radius));
			}
			else
			{
				//now look again (more precisely)
				{
					delete part;
					box.clear();
					box.add(C - CCVector3(1,1,1)*radius*static_cast<PointCoordinateType>(1.05)); //add 5%
					box.add(C + CCVector3(1,1,1)*radius*static_cast<PointCoordinateType>(1.05)); //add 5%
					part = cloud->crop(box,true);
					if (part && part->size() > 16)
						CCLib::GeometricalAnalysisTools::detectSphereRobust(part,0.5,C,radius,rms,&pDlg,0.99);
				}
				ccLog::Print(QString("[ccPointPairRegistrationDlg] Detected sphere radius = %1 (rms = %2)").arg(radius).arg(rms));
				if (radius / searchRadius < 0.5 || radius / searchRadius > 2.0)
				{
					ccLog::Warning("[ccPointPairRegistrationDlg] Sphere radius is too far from search radius!");
				}
				else if (rms / searchRadius >= maxRMSPercentage)
				{
					ccLog::Warning("[ccPointPairRegistrationDlg] RMS is too high!");
				}
				else
				{
					sphereRadius = radius;
					P = CCVector3d::fromArray(C.u);
					success = true;
				}
			}
		}
		else
		{
			ccLog::Warning("[ccPointPairRegistrationDlg] Failed to fit a sphere around the picked point!");
		}
	}
	else
	{
		//not enough memory? No points inside the 
		ccLog::Warning("[ccPointPairRegistrationDlg] Failed to crop points around the picked point?!");
	}

	if (part)
		delete part;

	return success;
}

//.........这里部分代码省略.........
		{
			ccLog::Error("Failed to determine the max (overlap) distance (not enough memory?)");
			return false;
		}

		//determine the max distance that (roughly) corresponds to the input overlap ratio
		ScalarType maxSearchDist = 0;
		{
			unsigned count = dataCloud->size();
			std::vector<ScalarType> distances;
			try
			{
				distances.resize(count);
			}
			catch (const std::bad_alloc&)
			{
				ccLog::Error("Not enough memory!");
				return false;
			}
			for (unsigned i=0; i<count; ++i)
			{
				distances[i] = dataCloud->getPointScalarValue(i);
			}
			
			ParallelSort(distances.begin(), distances.end());
			
			//now look for the max value at 'finalOverlapRatio+margin' percent
			maxSearchDist = distances[static_cast<unsigned>(std::max(1.0,count*(finalOverlapRatio+s_overlapMarginRatio)))-1];
		}

		//evntually select the points with distance below 'maxSearchDist'
		//(should roughly correspond to 'finalOverlapRatio + margin' percent)
		{
			CCLib::ReferenceCloud* refCloud = new CCLib::ReferenceCloud(dataCloud);
			cloudGarbage.add(refCloud);
			unsigned countBefore = dataCloud->size();
			unsigned baseIncrement = static_cast<unsigned>(std::max(100.0,countBefore*finalOverlapRatio*0.05));
			for (unsigned i=0; i<countBefore; ++i)
			{
				if (dataCloud->getPointScalarValue(i) <= maxSearchDist)
				{
					if (	refCloud->size() == refCloud->capacity()
						&&	!refCloud->reserve(refCloud->size() + baseIncrement) )
					{
						ccLog::Error("Not enough memory!");
						return false;
					}
					refCloud->addPointIndex(i);
				}
			}
			refCloud->resize(refCloud->size());
			dataCloud = refCloud;

			unsigned countAfter = dataCloud->size();
			double keptRatio = static_cast<double>(countAfter)/countBefore;
			ccLog::Print(QString("[ICP][Partial overlap] Selecting %1 points out of %2 (%3%) for registration").arg(countAfter).arg(countBefore).arg(static_cast<int>(100*keptRatio)));

			//update the relative 'final overlap' ratio
			finalOverlapRatio /= keptRatio;
		}
	}

	//weights
	CCLib::ScalarField* modelWeights = nullptr;
	CCLib::ScalarField* dataWeights = nullptr;
	{

CCLib::ReferenceCloud* qHPR::removeHiddenPoints(CCLib::GenericIndexedCloudPersist* theCloud, const CCVector3d& viewPoint, double fParam)
{
	assert(theCloud);

	unsigned nbPoints = theCloud->size();
	if (nbPoints == 0)
		return 0;

	//less than 4 points? no need for calculation, we return the whole cloud
	if (nbPoints < 4)
	{
		CCLib::ReferenceCloud* visiblePoints = new CCLib::ReferenceCloud(theCloud);
		if (!visiblePoints->addPointIndex(0,nbPoints)) //well even for less than 4 points we never know ;)
		{
			//not enough memory!
			delete visiblePoints;
			visiblePoints = 0;
		}
		return visiblePoints;
	}

	double maxRadius = 0;

	//convert point cloud to an array of double triplets (for qHull)
	coordT* pt_array = new coordT[(nbPoints+1)*3];
	{
		coordT* _pt_array = pt_array;

		for (unsigned i=0; i<nbPoints; ++i)
		{
			CCVector3d P = CCVector3d::fromArray(theCloud->getPoint(i)->u) - viewPoint;
			*_pt_array++ = static_cast<coordT>(P.x);
			*_pt_array++ = static_cast<coordT>(P.y);
			*_pt_array++ = static_cast<coordT>(P.z);

			//we keep track of the highest 'radius'
			double r2 = P.norm2();
			if (maxRadius < r2)
				maxRadius = r2;
		}
		
		//we add the view point (Cf. HPR)
		*_pt_array++ = 0;
		*_pt_array++ = 0;
		*_pt_array++ = 0;

		maxRadius = sqrt(maxRadius);
	}

	//apply spherical flipping
	{
		maxRadius *= pow(10.0,fParam) * 2;
	
		coordT* _pt_array = pt_array;
		for (unsigned i=0; i<nbPoints; ++i)
		{
			CCVector3d P = CCVector3d::fromArray(theCloud->getPoint(i)->u) - viewPoint;

			double r = (maxRadius/P.norm()) - 1.0;
			*_pt_array++ *= r;
			*_pt_array++ *= r;
			*_pt_array++ *= r;
		}
	}

	//array to flag points on the convex hull
	std::vector<bool> pointBelongsToCvxHull;

	static char qHullCommand[] = "qhull QJ Qci";
	if (!qh_new_qhull(3,nbPoints+1,pt_array,False,qHullCommand,0,stderr))
	{
		try
		{
			pointBelongsToCvxHull.resize(nbPoints+1,false);
		}
		catch (const std::bad_alloc&)
		{
			//not enough memory!
			delete[] pt_array;
			return 0;
		}

		vertexT *vertex = 0,**vertexp = 0;
		facetT *facet = 0;

		FORALLfacets
		{
			//if (!facet->simplicial)
			//	error("convhulln: non-simplicial facet"); // should never happen with QJ

			setT* vertices = qh_facet3vertex(facet);
			FOREACHvertex_(vertices)
			{
				pointBelongsToCvxHull[qh_pointid(vertex->point)] = true;
			}
			qh_settempfree(&vertices);
		}
	}

	delete[] pt_array;
//.........这里部分代码省略.........

void qHPR::doAction()
{
	assert(m_app);
	if (!m_app)
		return;

	const ccHObject::Container& selectedEntities = m_app->getSelectedEntities();
	size_t selNum = selectedEntities.size();
	if (	selNum != 1
		||	!selectedEntities.front()->isA(CC_TYPES::POINT_CLOUD))
	{
		m_app->dispToConsole("Select only one cloud!",ccMainAppInterface::ERR_CONSOLE_MESSAGE);
		return;
	}

	ccPointCloud* cloud = static_cast<ccPointCloud*>(selectedEntities[0]);

	ccGLWindow* win = m_app->getActiveGLWindow();
	if (!win)
	{
		m_app->dispToConsole("No active window!",ccMainAppInterface::ERR_CONSOLE_MESSAGE);
		return;
	}

	//display parameters
	const ccViewportParameters& params =  win->getViewportParameters();
	if (!params.perspectiveView)
	{
		m_app->dispToConsole("Perspective mode only!",ccMainAppInterface::ERR_CONSOLE_MESSAGE);
		return;
	}

	ccHprDlg dlg(m_app->getMainWindow());
	if (!dlg.exec())
		return;

	//progress dialog
	ccProgressDialog progressCb(false,m_app->getMainWindow());

	//unique parameter: the octree subdivision level
	int octreeLevel = dlg.octreeLevelSpinBox->value();
	assert(octreeLevel >= 0 && octreeLevel <= CCLib::DgmOctree::MAX_OCTREE_LEVEL);

	//compute octree if cloud hasn't any
	ccOctree::Shared theOctree = cloud->getOctree();
	if (!theOctree)
	{
		theOctree = cloud->computeOctree(&progressCb);
		if (theOctree && cloud->getParent())
		{
			m_app->addToDB(cloud->getOctreeProxy());
		}
	}

	if (!theOctree)
	{
		m_app->dispToConsole("Couldn't compute octree!",ccMainAppInterface::ERR_CONSOLE_MESSAGE);
		return;
	}

	CCVector3d viewPoint = params.cameraCenter;
	if (params.objectCenteredView)
	{
		CCVector3d PC = params.cameraCenter - params.pivotPoint;
		params.viewMat.inverse().apply(PC);
		viewPoint = params.pivotPoint + PC;
	}

	//HPR
	CCLib::ReferenceCloud* visibleCells = 0;
	{
		QElapsedTimer eTimer;
		eTimer.start();

		CCLib::ReferenceCloud* theCellCenters = CCLib::CloudSamplingTools::subsampleCloudWithOctreeAtLevel(	cloud,
																											static_cast<unsigned char>(octreeLevel),
																											CCLib::CloudSamplingTools::NEAREST_POINT_TO_CELL_CENTER,
																											&progressCb,
																											theOctree.data());
		if (!theCellCenters)
		{
			m_app->dispToConsole("Error while simplifying point cloud with octree!",ccMainAppInterface::ERR_CONSOLE_MESSAGE);
			return;
		}

		visibleCells = removeHiddenPoints(theCellCenters,viewPoint,3.5);
	
		m_app->dispToConsole(QString("[HPR] Cells: %1 - Time: %2 s").arg(theCellCenters->size()).arg(eTimer.elapsed()/1.0e3));

		//warning: after this, visibleCells can't be used anymore as a
		//normal cloud (as it's 'associated cloud' has been deleted).
		//Only its indexes are valid! (they are corresponding to octree cells)
		delete theCellCenters;
		theCellCenters = 0;
	}

	if (visibleCells)
	{
		//DGM: we generate a new cloud now, instead of playing with the points visiblity! (too confusing for the user)
		/*if (!cloud->isVisibilityTableInstantiated() && !cloud->resetVisibilityArray())
//.........这里部分代码省略.........

bool ccKdTreeForFacetExtraction::FuseCells(	ccKdTree* kdTree,
											double maxError,
											CCLib::DistanceComputationTools::ERROR_MEASURES errorMeasure,
											double maxAngle_deg,
											PointCoordinateType overlapCoef/*=1*/,
											bool closestFirst/*=true*/,
											CCLib::GenericProgressCallback* progressCb/*=0*/)
{
	if (!kdTree)
		return false;

	ccGenericPointCloud* associatedGenericCloud = kdTree->associatedGenericCloud();
	if (!associatedGenericCloud || !associatedGenericCloud->isA(CC_TYPES::POINT_CLOUD) || maxError < 0.0)
		return false;

	//get leaves
	std::vector<ccKdTree::Leaf*> leaves;
	if (!kdTree->getLeaves(leaves) || leaves.empty())
		return false;

	//progress notification
	CCLib::NormalizedProgress nProgress(progressCb, static_cast<unsigned>(leaves.size()));
	if (progressCb)
	{
		progressCb->update(0);
		if (progressCb->textCanBeEdited())
		{
			progressCb->setMethodTitle("Fuse Kd-tree cells");
			progressCb->setInfo(qPrintable(QString("Cells: %1\nMax error: %2").arg(leaves.size()).arg(maxError)));
		}
		progressCb->start();
	}

	ccPointCloud* pc = static_cast<ccPointCloud*>(associatedGenericCloud);

	//sort cells based on their population size (we start by the biggest ones)
	SortAlgo(leaves.begin(), leaves.end(), DescendingLeafSizeComparison);

	//set all 'userData' to -1 (i.e. unfused cells)
	{
		for (size_t i=0; i<leaves.size(); ++i)
		{
			leaves[i]->userData = -1;
			//check by the way that the plane normal is unit!
			assert(static_cast<double>(fabs(CCVector3(leaves[i]->planeEq).norm2()) - 1.0) < 1.0e-6);
		}
	}

	// cosine of the max angle between fused 'planes'
	const double c_minCosNormAngle = cos(maxAngle_deg * CC_DEG_TO_RAD);

	//fuse all cells, starting from the ones with the best error
	const int unvisitedNeighborValue = -1;
	bool cancelled = false;
	int macroIndex = 1; //starts at 1 (0 is reserved for cells already above the max error)
	{
		for (size_t i=0; i<leaves.size(); ++i)
		{
			ccKdTree::Leaf* currentCell = leaves[i];
			if (currentCell->error >= maxError)
				currentCell->userData = 0; //0 = special group for cells already above the user defined threshold!

			//already fused?
			if (currentCell->userData != -1)
			{
				if (progressCb && !nProgress.oneStep()) //process canceled by user
				{
					cancelled = true;
					break;
				}
				continue;
			}

			//we create a new "macro cell" index
			currentCell->userData = macroIndex++;

			//we init the current set of 'fused' points with the cell's points
			CCLib::ReferenceCloud* currentPointSet = currentCell->points;
			//get current fused set centroid and normal
			CCVector3 currentCentroid = *CCLib::Neighbourhood(currentPointSet).getGravityCenter();
			CCVector3 currentNormal(currentCell->planeEq);

			//visited neighbors
			ccKdTree::LeafSet visitedNeighbors;
			//set of candidates
			std::list<Candidate> candidates;

			//we are going to iteratively look for neighbor cells that could be fused to this one
			ccKdTree::LeafVector cellsToTest;
			cellsToTest.push_back(currentCell);

			if (progressCb && !nProgress.oneStep()) //process canceled by user
			{
				cancelled = true;
				break;
			}

			while (!cellsToTest.empty() || !candidates.empty())
			{
				//get all neighbors around the 'waiting' cell(s)
//.........这里部分代码省略.........

ccHObject* qFacets::createFacets(	ccPointCloud* cloud,
								CCLib::ReferenceCloudContainer& components,
								unsigned minPointsPerComponent,
								double maxEdgeLength,
								bool randomColors,
								bool& error)
{
	if (!cloud)
		return 0;

	//we create a new group to store all input CCs as 'facets'
	ccHObject* ccGroup = new ccHObject(cloud->getName()+QString(" [facets]"));
	ccGroup->setDisplay(cloud->getDisplay());
	ccGroup->setVisible(true);

	bool cloudHasNormal = cloud->hasNormals();

	//number of input components
	size_t componentCount = components.size();

	//progress notification
	ccProgressDialog pDlg(true,m_app->getMainWindow());
	pDlg.setMethodTitle("Facets creation");
	pDlg.setInfo(qPrintable(QString("Components: %1").arg(componentCount)));
	pDlg.setMaximum(static_cast<int>(componentCount));
	pDlg.show();
	QApplication::processEvents();

	//for each component
	error = false;
	while (!components.empty())
	{
		CCLib::ReferenceCloud* compIndexes = components.back();
		components.pop_back();

		//if it has enough points
		if (compIndexes && compIndexes->size() >= minPointsPerComponent)
		{
			ccPointCloud* facetCloud = cloud->partialClone(compIndexes);
			if (!facetCloud)
			{
				//not enough  memory!
				error = true;
				delete facetCloud;
				facetCloud = 0;
			}
			else
			{
				ccFacet* facet = ccFacet::Create(facetCloud,static_cast<PointCoordinateType>(maxEdgeLength),true);
				if (facet)
				{
					QString facetName = QString("facet %1 (rms=%2)").arg(ccGroup->getChildrenNumber()).arg(facet->getRMS());
					facet->setName(facetName);
					if (facet->getPolygon())
					{
						facet->getPolygon()->enableStippling(false);
						facet->getPolygon()->showNormals(false);
					}
					if (facet->getContour())
					{
						facet->getContour()->setGlobalScale(facetCloud->getGlobalScale());
						facet->getContour()->setGlobalShift(facetCloud->getGlobalShift());
					}

					//check the facet normal sign
					if (cloudHasNormal)
					{
						CCVector3 N = ccOctree::ComputeAverageNorm(compIndexes,cloud);

						if (N.dot(facet->getNormal()) < 0)
							facet->invertNormal();
					}

#ifdef _DEBUG
					facet->showNormalVector(true);
#endif

					//shall we colorize it with a random color?
					ccColor::Rgb col, darkCol;
					if (randomColors)
					{
						col = ccColor::Generator::Random();
						assert(c_darkColorRatio <= 1.0);
						darkCol.r = static_cast<ColorCompType>(static_cast<double>(col.r) * c_darkColorRatio);
						darkCol.g = static_cast<ColorCompType>(static_cast<double>(col.g) * c_darkColorRatio);
						darkCol.b = static_cast<ColorCompType>(static_cast<double>(col.b) * c_darkColorRatio);
					}
					else
					{
						//use normal-based HSV coloring
						CCVector3 N = facet->getNormal();
						PointCoordinateType dip, dipDir;
						ccNormalVectors::ConvertNormalToDipAndDipDir(N, dip, dipDir);
						FacetsClassifier::GenerateSubfamilyColor(col,dip,dipDir,0,1,&darkCol);
					}
					facet->setColor(col);
					if (facet->getContour())
					{
						facet->getContour()->setColor(darkCol);
						facet->getContour()->setWidth(2);
//.........这里部分代码省略.........

int Cropper::compute()
{

    ccHObject::Container outcrops = vombat::theInstance()->getAllObjectsSelectedBySPCDti(&spc::VirtualOutcrop::Type);

    if (outcrops.size() > 1) {
        LOG(INFO) << "please select only one virtual outcrop on which to operate";
        return 1;
    }

    else if (outcrops.size() == 1) {
        m_root_outcrop = dynamic_cast<ccVirtualOutcrop*>(outcrops.at(0));
    }
    else
        m_root_outcrop = new ccVirtualOutcrop();

    ccHObject::Container selections = m_dialog->getSelections();

    //    ccHObject::Container clouds = m_dialog->getClouds();

    ccHObject::Container croppables = m_dialog->getCroppables();

    LOG(INFO) << "found " << selections.size() << " to be processed";
    //    LOG(INFO) << "Found " << clouds.size() << " point clouds to be analyzed";
    LOG(INFO) << "Found " << croppables.size() << " polylines";

    //    if (m_dialog->generateRegions())

    // first create selections out of regions
    for (ccHObject* obj : selections) {

        ccPlanarSelection* sel = dynamic_cast<ccPlanarSelection*>(obj);

        for (ccHObject* to_crop : croppables) {
            if (to_crop->isA(CC_TYPES::POLY_LINE)) {
//                if (to_crop->isA(CC_TYPES::POINT_CLOUD)) {
                ccPolyline* pline = ccHObjectCaster::ToPolyline(to_crop);

                ccPointCloud* vertices = dynamic_cast<ccPointCloud*>(pline->getAssociatedCloud());

                ccPointCloud* cropped_vertices = sel->crop(vertices);

                if (cropped_vertices) {
                    ccPolyline* cropped_pline = new ccPolyline(cropped_vertices);

                    cropped_pline->addPointIndex(0, cropped_vertices->size() - 1);
                    cropped_pline->setVisible(true);
                    //                    if (m_dialog->cropStrataTraces())
                    sel->addChild(cropped_pline);
                }
            }

            else if (to_crop->isA(CC_TYPES::POINT_CLOUD)) {

				LOG(INFO) << "cropping point cloud with name " << to_crop->getName().toStdString();

                ccPointCloud* cloud = ccHObjectCaster::ToPointCloud(to_crop);

                spc::PointCloudBase::Ptr asspc = spcCCPointCloud::fromccPointCloud(cloud);

                spc::SelectionExtractor<Eigen::Vector3f, int> ext;
                ext.setInputSet(asspc);
                ext.setSelection(sel->getSPCElement<spc::SelectionBase<Eigen::Vector3f> >());
                ext.compute();

                std::vector<int> inside = ext.getInsideIds();

                if (inside.size() == 0)
				{
					LOG(WARNING) << "the selection did not find anything inside it. Skipping";
                    continue;
				}

                CCLib::ReferenceCloud* ref = new CCLib::ReferenceCloud(cloud);
                for (int i : inside) {
                    ref->addPointIndex(i);
                }

                ccPointCloud* outcloud = cloud->partialClone(ref);

				LOG(INFO) << "done with cropping, calling add child on object: " << sel->getName().toStdString();
                sel->addChild(outcloud);
                newEntity(outcloud);
            }
        }
    }


    return 1;
}

CCLib::ReferenceCloud* qHPR::removeHiddenPoints(CCLib::GenericIndexedCloudPersist* theCloud, float viewPoint[], float fParam)
{
	assert(theCloud);

	unsigned i,nbPoints = theCloud->size();

	if (nbPoints==0)
		return 0;

	CCLib::ReferenceCloud* newCloud = new CCLib::ReferenceCloud(theCloud);

	//less than 4 points ? no need for calculation, we return the whole cloud
	if (nbPoints<4)
	{
		if (!newCloud->reserve(nbPoints)) //well, we never know ;)
		{
			//not enough memory!
			delete newCloud;
			return 0;
		}
		newCloud->addPointIndex(0,nbPoints);
		return newCloud;
	}

	//view point
	coordT Cx = viewPoint[0];
	coordT Cy = viewPoint[1];
	coordT Cz = viewPoint[2];

	float* radius = new float[nbPoints];
	if (!radius)
	{
		//not enough memory!
		delete newCloud;
		return 0;
	}
	float r,maxRadius = 0.0;

	//table of points
	coordT* pt_array = new coordT[(nbPoints+1)*3];
	coordT* _pt_array = pt_array;
	theCloud->placeIteratorAtBegining();

//#define BACKUP_PROJECTED_CLOUDS
#ifdef BACKUP_PROJECTED_CLOUDS
	FILE* fp = fopen("output_centered.asc","wt");
#endif
	double x,y,z;
	for (i=0;i<nbPoints;++i)
	{
		const CCVector3* P = theCloud->getNextPoint();
		*(_pt_array++)=x=coordT(P->x)-Cx;
		*(_pt_array++)=y=coordT(P->y)-Cy;
		*(_pt_array++)=z=coordT(P->z)-Cz;
		//we pre-compute the radius ...
		r = (float)sqrt(x*x+y*y+z*z);
		//in order to determine the max radius
		if (maxRadius<r)
			maxRadius = r;
		radius[i] = r;
#ifdef BACKUP_PROJECTED_CLOUDS
		fprintf(fp,"%f %f %f %f\n",x,y,z,r);
#endif
	}
	//we add the view point (Cf. HPR)
	*(_pt_array++)=0.0;
	*(_pt_array++)=0.0;
	*(_pt_array++)=0.0;
#ifdef BACKUP_PROJECTED_CLOUDS
	fprintf(fp,"%f %f %f %f\n",0,0,0,0);
	fclose(fp);
#endif

	maxRadius *= 2.0f*pow(10.0f,fParam);

	_pt_array = pt_array;
#ifdef BACKUP_PROJECTED_CLOUDS
	fp = fopen("output_transformed.asc","wt");
#endif
	for (i=0;i<nbPoints;++i)
	{
		//Spherical flipping
		r = maxRadius/radius[i]-1.0f;
#ifndef BACKUP_PROJECTED_CLOUDS
		*(_pt_array++) *= double(r);
		*(_pt_array++) *= double(r);
		*(_pt_array++) *= double(r);
#else
		x = *_pt_array * double(r);
		*(_pt_array++) = x;
		y = *_pt_array * double(r);
		*(_pt_array++) = y;
		z = *_pt_array * double(r);
		*(_pt_array++) = z;
		fprintf(fp,"%f %f %f %f\n",x,y,z,r);
#endif
	}
#ifdef BACKUP_PROJECTED_CLOUDS
	fclose(fp);
#endif
//.........这里部分代码省略.........