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Bug fix: the context class was ignored!

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This commit is contained in:
Daniel Girardeau-Montaut
2019-04-05 11:15:57 +02:00
parent 69001ab9d5
commit 7950151cb5
6 changed files with 110 additions and 61 deletions
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ContextBasedFeature.cpp
+82 -36
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@@ -17,6 +17,9 @@
#include "ContextBasedFeature.h"
//Local
#include "q3DMASCTools.h"
//Qt
#include <QMutex>
@@ -36,10 +39,21 @@ bool ContextBasedFeature::checkValidity(QString corePointRole, QString &error) c
return false;
}
unsigned char cloudCount = (cloud1 ? (cloud2 ? 2 : 1) : 0);
if (cloudCount < 2)
if (!cloud1 || !cloud2)
{
error = "at least two clouds are required to compute context-based features";
error = "two clouds are required to compute context-based features";
return false;
}
CCLib::ScalarField* classifSF = Tools::GetClassificationSF(cloud2);
if (!classifSF)
{
error = QString("Context cloud (%1) has no classification field").arg(cloud2Label);
return false;
}
if (classifSF->size() < cloud2->size())
{
error = QString("Context cloud (%1) has an invalid classification field").arg(cloud2Label);
return false;
}
@@ -79,6 +93,15 @@ bool ContextBasedFeature::prepare( const CorePoints& corePoints,
return false;
}
CCLib::ScalarField* classifSF = Tools::GetClassificationSF(cloud2);
if (!classifSF || classifSF->size() < cloud2->size())
{
assert(false);
//already checked by 'checkValidity'
return false;
}
cloud2->setCurrentOutScalarField(cloud2->getScalarFieldIndexByName(classifSF->getName()));
//build the final SF name
QString typeStr = ToString(type);
QString resultSFName = typeStr + "_" + cloud1Label + "_" + cloud2Label + "_" + QString::number(ctxClassLabel);
@@ -104,12 +127,12 @@ bool ContextBasedFeature::prepare( const CorePoints& corePoints,
if (!scaled()) //with 'kNN' neighbors, we can compute the values right away
{
//get the octree
ccOctree::Shared octree = cloud2->getOctree();
if (!octree)
ccOctree::Shared octree2 = cloud2->getOctree();
if (!octree2)
{
ccLog::Print(QString("Computing octree of cloud %1 (%2 points)").arg(cloud2->getName()).arg(cloud2->size()));
octree = cloud2->computeOctree(progressCb);
if (!octree)
octree2 = cloud2->computeOctree(progressCb);
if (!octree2)
{
error = "Failed to compute octree (not enough memory?)";
return false;
@@ -117,7 +140,7 @@ bool ContextBasedFeature::prepare( const CorePoints& corePoints,
}
//now extract the neighborhoods
unsigned char octreeLevel = octree->findBestLevelForAGivenPopulationPerCell(static_cast<unsigned>(std::max(3, kNN)));
unsigned char octreeLevel = octree2->findBestLevelForAGivenPopulationPerCell(static_cast<unsigned>(std::max(3, kNN)));
ccLog::Print(QString("[Initial octree level] level = %1").arg(octreeLevel));
unsigned pointCount = corePoints.size();
@@ -130,6 +153,8 @@ bool ContextBasedFeature::prepare( const CorePoints& corePoints,
ccLog::Print(logMessage);
CCLib::NormalizedProgress nProgress(progressCb, pointCount);
const ScalarType fClass = static_cast<ScalarType>(ctxClassLabel);
QMutex mutex;
bool error = false;
double meanNeighborhoodSize = 0;
@@ -148,46 +173,54 @@ bool ContextBasedFeature::prepare( const CorePoints& corePoints,
ScalarType s = NAN_VALUE;
int neighborhoodSize = 0;
if (octree->findPointNeighbourhood(P, &Yk, static_cast<unsigned>(kNN), octreeLevel, maxSquareDist, 0, &neighborhoodSize) >= static_cast<unsigned>(kNN))
if (octree2->findPointNeighbourhood(P, &Yk, static_cast<unsigned>(kNN), octreeLevel, maxSquareDist, 0, &neighborhoodSize) >= static_cast<unsigned>(kNN))
{
CCVector3d sumQ(0, 0, 0);
unsigned validCount = 0;
for (int k = 0; k < kNN; ++k)
{
//we only consider points with the right class!!!
if (Yk.getCurrentPointScalarValue() != fClass)
continue;
sumQ += CCVector3d::fromArray(Yk.getPoint(k)->u);
++validCount;
}
switch (type)
if (validCount)
{
case DZ:
s = static_cast<ScalarType>(P->z - sumQ.z / kNN);
break;
case DH:
s = static_cast<ScalarType>(sqrt(pow(P->x - sumQ.x / kNN, 2.0) + pow(P->y - sumQ.y / kNN, 2.0)));
break;
switch (type)
{
case DZ:
s = static_cast<ScalarType>(P->z - sumQ.z / validCount);
break;
case DH:
s = static_cast<ScalarType>(sqrt(pow(P->x - sumQ.x / validCount, 2.0) + pow(P->y - sumQ.y / validCount, 2.0)));
break;
}
}
}
if (i && (i % tenth) == 0)
if (i && (i % tenth) == 0)
{
double density = meanNeighborhoodSize / tenth;
if (density < 1.1)
{
double density = meanNeighborhoodSize / tenth;
if (density < 1.1)
{
if (octreeLevel + 1 < CCLib::DgmOctree::MAX_OCTREE_LEVEL)
++octreeLevel;
}
else while (density > 2.9)
{
if (octreeLevel <= 5)
break;
--octreeLevel;
density /= 2.0;
}
ccLog::Print(QString("[Adaptative octree level] Mean neighborhood size: %1 --> new level = %2").arg(meanNeighborhoodSize / tenth).arg(octreeLevel));
meanNeighborhoodSize = 0;
if (octreeLevel + 1 < CCLib::DgmOctree::MAX_OCTREE_LEVEL)
++octreeLevel;
}
else
else while (density > 2.9)
{
meanNeighborhoodSize += neighborhoodSize;
if (octreeLevel <= 5)
break;
--octreeLevel;
density /= 2.0;
}
ccLog::Print(QString("[Adaptative octree level] Mean neighborhood size: %1 --> new level = %2").arg(meanNeighborhoodSize / tenth).arg(octreeLevel));
meanNeighborhoodSize = 0;
}
else
{
meanNeighborhoodSize += neighborhoodSize;
}
sf->setValue(i, s);
@@ -225,19 +258,32 @@ bool ContextBasedFeature::prepare( const CorePoints& corePoints,
bool ContextBasedFeature::computeValue(CCLib::DgmOctree::NeighboursSet& pointsInNeighbourhood, const CCVector3& queryPoint, ScalarType& outputValue) const
{
const ScalarType fClass = static_cast<ScalarType>(ctxClassLabel);
CCVector3d sumQ(0, 0, 0);
unsigned validCount = 0;
for (CCLib::DgmOctree::PointDescriptor& Pd : pointsInNeighbourhood)
{
//we only consider points with the right class!!!
if (cloud2->getPointScalarValue(Pd.pointIndex) != fClass)
continue;
sumQ += CCVector3d::fromArray(Pd.point->u);
++validCount;
}
if (validCount == 0)
{
outputValue = NAN_VALUE;
return true;
}
switch (type)
{
case DZ:
outputValue = static_cast<ScalarType>(queryPoint.z - sumQ.z / kNN);
outputValue = static_cast<ScalarType>(queryPoint.z - sumQ.z / validCount);
break;
case DH:
outputValue = static_cast<ScalarType>(sqrt(pow(queryPoint.x - sumQ.x / kNN, 2.0) + pow(queryPoint.y - sumQ.y / kNN, 2.0)));
outputValue = static_cast<ScalarType>(sqrt(pow(queryPoint.x - sumQ.x / validCount, 2.0) + pow(queryPoint.y - sumQ.y / validCount, 2.0)));
break;
default:
assert(false);