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Remove inline sorting algorithms from core headers

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This commit is contained in:
Andrey Kamaev
2013-03-28 16:12:13 +04:00
parent 20534c9beb
commit cc6bdfb045
19 changed files with 139 additions and 577 deletions
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26
apps/traincascade/boost.cpp
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@@ -18,12 +18,14 @@ logRatio( double val )
return log( val/(1. - val) );
}
#define CV_CMP_FLT(i,j) (i < j)
static CV_IMPLEMENT_QSORT_EX( icvSortFlt, float, CV_CMP_FLT, const float* )
#define CV_CMP_NUM_IDX(i,j) (aux[i] < aux[j])
static CV_IMPLEMENT_QSORT_EX( icvSortIntAux, int, CV_CMP_NUM_IDX, const float* )
static CV_IMPLEMENT_QSORT_EX( icvSortUShAux, unsigned short, CV_CMP_NUM_IDX, const float* )
template<typename T, typename Idx>
class LessThanIdx
{
public:
LessThanIdx( const T* _arr ) : arr(_arr) {}
bool operator()(Idx a, Idx b) const { return arr[a] < arr[b]; }
const T* arr;
};
#define CV_THRESHOLD_EPS (0.00001F)
@@ -722,7 +724,7 @@ void CvCascadeBoostTrainData::get_ord_var_data( CvDTreeNode* n, int vi, float* o
sampleValues[i] = (*featureEvaluator)( vi, sampleIndices[i]);
}
}
icvSortIntAux( sortedIndicesBuf, nodeSampleCount, &sampleValues[0] );
std::sort(sortedIndicesBuf, sortedIndicesBuf + nodeSampleCount, LessThanIdx<float, int>(&sampleValues[0]) );
for( int i = 0; i < nodeSampleCount; i++ )
ordValuesBuf[i] = (&sampleValues[0])[sortedIndicesBuf[i]];
*sortedIndices = sortedIndicesBuf;
@@ -791,9 +793,9 @@ struct FeatureIdxOnlyPrecalc
*(idst + fi*sample_count + si) = si;
}
if ( is_buf_16u )
icvSortUShAux( udst + fi*sample_count, sample_count, valCachePtr );
std::sort(udst + fi*sample_count, udst + (fi + 1)*sample_count, LessThanIdx<float, unsigned short>(valCachePtr) );
else
icvSortIntAux( idst + fi*sample_count, sample_count, valCachePtr );
std::sort(idst + fi*sample_count, idst + (fi + 1)*sample_count, LessThanIdx<float, int>(valCachePtr) );
}
}
const CvFeatureEvaluator* featureEvaluator;
@@ -827,9 +829,9 @@ struct FeatureValAndIdxPrecalc
*(idst + fi*sample_count + si) = si;
}
if ( is_buf_16u )
icvSortUShAux( udst + fi*sample_count, sample_count, valCache->ptr<float>(fi) );
std::sort(idst + fi*sample_count, idst + (fi + 1)*sample_count, LessThanIdx<float, unsigned short>(valCache->ptr<float>(fi)) );
else
icvSortIntAux( idst + fi*sample_count, sample_count, valCache->ptr<float>(fi) );
std::sort(idst + fi*sample_count, idst + (fi + 1)*sample_count, LessThanIdx<float, int>(valCache->ptr<float>(fi)) );
}
}
const CvFeatureEvaluator* featureEvaluator;
@@ -1602,7 +1604,7 @@ bool CvCascadeBoost::isErrDesired()
if( ((CvCascadeBoostTrainData*)data)->featureEvaluator->getCls( i ) == 1.0F )
eval[numPos++] = predict( i, true );
icvSortFlt( &eval[0], numPos, 0 );
std::sort(&eval[0], &eval[0] + numPos);
int thresholdIdx = (int)((1.0F - minHitRate) * numPos);