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#pragma once
#ifndef __CVTT_ENDPOINTSELECTOR_H__
#define __CVTT_ENDPOINTSELECTOR_H__
#include "ConvectionKernels_ParallelMath.h"
#include "ConvectionKernels_UnfinishedEndpoints.h"
#include "ConvectionKernels_PackedCovarianceMatrix.h"
namespace cvtt
{
namespace Internal
{
static const int NumEndpointSelectorPasses = 3;
template<int TVectorSize, int TIterationCount>
class EndpointSelector
{
public:
typedef ParallelMath::Float MFloat;
EndpointSelector()
{
for (int ch = 0; ch < TVectorSize; ch++)
{
m_centroid[ch] = ParallelMath::MakeFloatZero();
m_direction[ch] = ParallelMath::MakeFloatZero();
}
m_weightTotal = ParallelMath::MakeFloatZero();
m_minDist = ParallelMath::MakeFloat(FLT_MAX);
m_maxDist = ParallelMath::MakeFloat(-FLT_MAX);
}
void ContributePass(const MFloat *value, int pass, const MFloat &weight)
{
if (pass == 0)
ContributeCentroid(value, weight);
else if (pass == 1)
ContributeDirection(value, weight);
else if (pass == 2)
ContributeMinMax(value);
}
void FinishPass(int pass)
{
if (pass == 0)
FinishCentroid();
else if (pass == 1)
FinishDirection();
}
UnfinishedEndpoints<TVectorSize> GetEndpoints(const float channelWeights[TVectorSize]) const
{
MFloat unweightedBase[TVectorSize];
MFloat unweightedOffset[TVectorSize];
for (int ch = 0; ch < TVectorSize; ch++)
{
MFloat min = m_centroid[ch] + m_direction[ch] * m_minDist;
MFloat max = m_centroid[ch] + m_direction[ch] * m_maxDist;
float safeWeight = channelWeights[ch];
if (safeWeight == 0.f)
safeWeight = 1.0f;
unweightedBase[ch] = min / channelWeights[ch];
unweightedOffset[ch] = (max - min) / channelWeights[ch];
}
return UnfinishedEndpoints<TVectorSize>(unweightedBase, unweightedOffset);
}
private:
void ContributeCentroid(const MFloat *value, const MFloat &weight)
{
for (int ch = 0; ch < TVectorSize; ch++)
m_centroid[ch] = m_centroid[ch] + value[ch] * weight;
m_weightTotal = m_weightTotal + weight;
}
void FinishCentroid()
{
MFloat denom = m_weightTotal;
ParallelMath::MakeSafeDenominator(denom);
for (int ch = 0; ch < TVectorSize; ch++)
m_centroid[ch] = m_centroid[ch] / denom;
}
void ContributeDirection(const MFloat *value, const MFloat &weight)
{
MFloat diff[TVectorSize];
for (int ch = 0; ch < TVectorSize; ch++)
diff[ch] = value[ch] - m_centroid[ch];
m_covarianceMatrix.Add(diff, weight);
}
void FinishDirection()
{
MFloat approx[TVectorSize];
for (int ch = 0; ch < TVectorSize; ch++)
approx[ch] = ParallelMath::MakeFloat(1.0f);
for (int i = 0; i < TIterationCount; i++)
{
MFloat product[TVectorSize];
m_covarianceMatrix.Product(product, approx);
MFloat largestComponent = product[0];
for (int ch = 1; ch < TVectorSize; ch++)
largestComponent = ParallelMath::Max(largestComponent, product[ch]);
// product = largestComponent*newApprox
ParallelMath::MakeSafeDenominator(largestComponent);
for (int ch = 0; ch < TVectorSize; ch++)
approx[ch] = product[ch] / largestComponent;
}
// Normalize
MFloat approxLen = ParallelMath::MakeFloatZero();
for (int ch = 0; ch < TVectorSize; ch++)
approxLen = approxLen + approx[ch] * approx[ch];
approxLen = ParallelMath::Sqrt(approxLen);
ParallelMath::MakeSafeDenominator(approxLen);
for (int ch = 0; ch < TVectorSize; ch++)
m_direction[ch] = approx[ch] / approxLen;
}
void ContributeMinMax(const MFloat *value)
{
MFloat dist = ParallelMath::MakeFloatZero();
for (int ch = 0; ch < TVectorSize; ch++)
dist = dist + m_direction[ch] * (value[ch] - m_centroid[ch]);
m_minDist = ParallelMath::Min(m_minDist, dist);
m_maxDist = ParallelMath::Max(m_maxDist, dist);
}
ParallelMath::Float m_centroid[TVectorSize];
ParallelMath::Float m_direction[TVectorSize];
PackedCovarianceMatrix<TVectorSize> m_covarianceMatrix;
ParallelMath::Float m_weightTotal;
ParallelMath::Float m_minDist;
ParallelMath::Float m_maxDist;
};
}
}
#endif
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