本文整理汇总了C++中cclib::GenericIndexedCloudPersist::enableScalarField方法的典型用法代码示例。如果您正苦于以下问题：C++ GenericIndexedCloudPersist::enableScalarField方法的具体用法？C++ GenericIndexedCloudPersist::enableScalarField怎么用？C++ GenericIndexedCloudPersist::enableScalarField使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类cclib::GenericIndexedCloudPersist的用法示例。
在下文中一共展示了GenericIndexedCloudPersist::enableScalarField方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: ICP
bool ccRegistrationTools::ICP( ccHObject* data,
ccHObject* model,
ccGLMatrix& transMat,
double &finalScale,
double& finalRMS,
unsigned& finalPointCount,
double minRMSDecrease,
unsigned maxIterationCount,
unsigned randomSamplingLimit,
bool removeFarthestPoints,
CCLib::ICPRegistrationTools::CONVERGENCE_TYPE method,
bool adjustScale,
double finalOverlapRatio/*=1.0*/,
bool useDataSFAsWeights/*=false*/,
bool useModelSFAsWeights/*=false*/,
int filters/*=CCLib::ICPRegistrationTools::SKIP_NONE*/,
int maxThreadCount/*=0*/,
QWidget* parent/*=0*/)
{
//progress bar
QScopedPointer<ccProgressDialog> progressDlg;
if (parent)
{
progressDlg.reset(new ccProgressDialog(false, parent));
}
Garbage<CCLib::GenericIndexedCloudPersist> cloudGarbage;
//if the 'model' entity is a mesh, we need to sample points on it
CCLib::GenericIndexedCloudPersist* modelCloud = nullptr;
ccGenericMesh* modelMesh = nullptr;
if (model->isKindOf(CC_TYPES::MESH))
{
modelMesh = ccHObjectCaster::ToGenericMesh(model);
modelCloud = modelMesh->getAssociatedCloud();
}
else
{
modelCloud = ccHObjectCaster::ToGenericPointCloud(model);
}
//if the 'data' entity is a mesh, we need to sample points on it
CCLib::GenericIndexedCloudPersist* dataCloud = nullptr;
if (data->isKindOf(CC_TYPES::MESH))
{
dataCloud = CCLib::MeshSamplingTools::samplePointsOnMesh(ccHObjectCaster::ToGenericMesh(data), s_defaultSampledPointsOnDataMesh, progressDlg.data());
if (!dataCloud)
{
ccLog::Error("[ICP] Failed to sample points on 'data' mesh!");
return false;
}
cloudGarbage.add(dataCloud);
}
else
{
dataCloud = ccHObjectCaster::ToGenericPointCloud(data);
}
//we activate a temporary scalar field for registration distances computation
CCLib::ScalarField* dataDisplayedSF = nullptr;
int oldDataSfIdx = -1, dataSfIdx = -1;
//if the 'data' entity is a real ccPointCloud, we can even create a proper temporary SF for registration distances
if (data->isA(CC_TYPES::POINT_CLOUD))
{
ccPointCloud* pc = static_cast<ccPointCloud*>(data);
dataDisplayedSF = pc->getCurrentDisplayedScalarField();
oldDataSfIdx = pc->getCurrentInScalarFieldIndex();
dataSfIdx = pc->getScalarFieldIndexByName(REGISTRATION_DISTS_SF);
if (dataSfIdx < 0)
dataSfIdx = pc->addScalarField(REGISTRATION_DISTS_SF);
if (dataSfIdx >= 0)
pc->setCurrentScalarField(dataSfIdx);
else
{
ccLog::Error("[ICP] Couldn't create temporary scalar field! Not enough memory?");
return false;
}
}
else
{
if (!dataCloud->enableScalarField())
{
ccLog::Error("[ICP] Couldn't create temporary scalar field! Not enough memory?");
return false;
}
}
//add a 'safety' margin to input ratio
static double s_overlapMarginRatio = 0.2;
finalOverlapRatio = std::max(finalOverlapRatio, 0.01); //1% minimum
//do we need to reduce the input point cloud (so as to be close
//to the theoretical number of overlapping points - but not too
//low so as we are not registered yet ;)
if (finalOverlapRatio < 1.0 - s_overlapMarginRatio)
{
//DGM we can now use 'approximate' distances as SAITO algorithm is exact (but with a coarse resolution)
//level = 7 if < 1.000.000
//level = 8 if < 10.000.000
//level = 9 if > 10.000.000
//.........这里部分代码省略.........
示例2: ICP
bool ccRegistrationTools::ICP( ccHObject* data,
ccHObject* model,
ccGLMatrix& transMat,
double &finalScale,
double& finalError,
double minErrorDecrease,
unsigned maxIterationCount,
unsigned randomSamplingLimit,
bool removeFarthestPoints,
ConvergenceMethod method,
bool adjustScale,
bool useDataSFAsWeights/*=false*/,
bool useModelSFAsWeights/*=false*/,
QWidget* parent/*=0*/)
{
//progress bar
ccProgressDialog pDlg(false,parent);
//if the 'model' entity is a mesh, we need to sample points on it
CCLib::GenericIndexedCloudPersist* modelCloud = 0;
if (model->isKindOf(CC_TYPES::MESH))
{
modelCloud = CCLib::MeshSamplingTools::samplePointsOnMesh(ccHObjectCaster::ToGenericMesh(model),s_defaultSampledPointsOnModelMesh,&pDlg);
if (!modelCloud)
{
ccLog::Error("[ICP] Failed to sample points on 'model' mesh!");
return false;
}
}
else
{
modelCloud = ccHObjectCaster::ToGenericPointCloud(model);
}
//if the 'data' entity is a mesh, we need to sample points on it
CCLib::GenericIndexedCloudPersist* dataCloud = 0;
if (data->isKindOf(CC_TYPES::MESH))
{
dataCloud = CCLib::MeshSamplingTools::samplePointsOnMesh(ccHObjectCaster::ToGenericMesh(data),s_defaultSampledPointsOnDataMesh,&pDlg);
if (!dataCloud)
{
ccLog::Error("[ICP] Failed to sample points on 'data' mesh!");
return false;
}
}
else
{
dataCloud = ccHObjectCaster::ToGenericPointCloud(data);
}
//we activate a temporary scalar field for registration distances computation
CCLib::ScalarField* dataDisplayedSF = 0;
int oldDataSfIdx=-1, dataSfIdx=-1;
//if the 'data' entity is a real ccPointCloud, we can even create a temporary SF for registration distances
if (data->isA(CC_TYPES::POINT_CLOUD))
{
ccPointCloud* pc = static_cast<ccPointCloud*>(data);
dataDisplayedSF = pc->getCurrentDisplayedScalarField();
oldDataSfIdx = pc->getCurrentInScalarFieldIndex();
dataSfIdx = pc->getScalarFieldIndexByName(REGISTRATION_DISTS_SF);
if (dataSfIdx < 0)
dataSfIdx = pc->addScalarField(REGISTRATION_DISTS_SF);
if (dataSfIdx >= 0)
pc->setCurrentScalarField(dataSfIdx);
else
ccLog::Warning("[ICP] Couldn't create temporary scalar field! Not enough memory?");
}
else
{
dataCloud->enableScalarField();
}
//parameters
CCLib::PointProjectionTools::Transformation transform;
CCLib::ScalarField* modelWeights = 0;
if (useModelSFAsWeights)
{
if (modelCloud == dynamic_cast<CCLib::GenericIndexedCloudPersist*>(model) && model->isA(CC_TYPES::POINT_CLOUD))
{
ccPointCloud* pc = static_cast<ccPointCloud*>(model);
modelWeights = pc->getCurrentDisplayedScalarField();
if (!modelWeights)
ccLog::Warning("[ICP] 'useDataSFAsWeights' is true but model has no displayed scalar field!");
}
else
{
ccLog::Warning("[ICP] 'useDataSFAsWeights' is true but only point clouds scalar fields can be used as weights!");
}
}
CCLib::ScalarField* dataWeights = 0;
if (useDataSFAsWeights)
{
if (!dataDisplayedSF)
{
if (dataCloud == (CCLib::GenericIndexedCloudPersist*)data && data->isA(CC_TYPES::POINT_CLOUD))
ccLog::Warning("[ICP] 'useDataSFAsWeights' is true but data has no displayed scalar field!");
else
//.........这里部分代码省略.........