generic-library/opencv
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Replaced most of the usages of parallel_for with that of parallel_for_.

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This should allow many algorithms to take advantage of more parallelization
technologies.
This commit is contained in:
Roman Donchenko
2013-05-30 18:44:33 +04:00
parent 37091b086c
commit 29b13ec1de
24 changed files with 232 additions and 352 deletions
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30
apps/traincascade/boost.cpp
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@@ -766,7 +766,7 @@ float CvCascadeBoostTrainData::getVarValue( int vi, int si )
}
struct FeatureIdxOnlyPrecalc
struct FeatureIdxOnlyPrecalc : ParallelLoopBody
{
FeatureIdxOnlyPrecalc( const CvFeatureEvaluator* _featureEvaluator, CvMat* _buf, int _sample_count, bool _is_buf_16u )
{
@@ -776,11 +776,11 @@ struct FeatureIdxOnlyPrecalc
idst = _buf->data.i;
is_buf_16u = _is_buf_16u;
}
void operator()( const BlockedRange& range ) const
void operator()( const Range& range ) const
{
cv::AutoBuffer<float> valCache(sample_count);
float* valCachePtr = (float*)valCache;
for ( int fi = range.begin(); fi < range.end(); fi++)
for ( int fi = range.start; fi < range.end; fi++)
{
for( int si = 0; si < sample_count; si++ )
{
@@ -803,7 +803,7 @@ struct FeatureIdxOnlyPrecalc
bool is_buf_16u;
};
struct FeatureValAndIdxPrecalc
struct FeatureValAndIdxPrecalc : ParallelLoopBody
{
FeatureValAndIdxPrecalc( const CvFeatureEvaluator* _featureEvaluator, CvMat* _buf, Mat* _valCache, int _sample_count, bool _is_buf_16u )
{
@@ -814,9 +814,9 @@ struct FeatureValAndIdxPrecalc
idst = _buf->data.i;
is_buf_16u = _is_buf_16u;
}
void operator()( const BlockedRange& range ) const
void operator()( const Range& range ) const
{
for ( int fi = range.begin(); fi < range.end(); fi++)
for ( int fi = range.start; fi < range.end; fi++)
{
for( int si = 0; si < sample_count; si++ )
{
@@ -840,7 +840,7 @@ struct FeatureValAndIdxPrecalc
bool is_buf_16u;
};
struct FeatureValOnlyPrecalc
struct FeatureValOnlyPrecalc : ParallelLoopBody
{
FeatureValOnlyPrecalc( const CvFeatureEvaluator* _featureEvaluator, Mat* _valCache, int _sample_count )
{
@@ -848,9 +848,9 @@ struct FeatureValOnlyPrecalc
valCache = _valCache;
sample_count = _sample_count;
}
void operator()( const BlockedRange& range ) const
void operator()( const Range& range ) const
{
for ( int fi = range.begin(); fi < range.end(); fi++)
for ( int fi = range.start; fi < range.end; fi++)
for( int si = 0; si < sample_count; si++ )
valCache->at<float>(fi,si) = (*featureEvaluator)( fi, si );
}
@@ -864,12 +864,12 @@ void CvCascadeBoostTrainData::precalculate()
int minNum = MIN( numPrecalcVal, numPrecalcIdx);
double proctime = -TIME( 0 );
parallel_for( BlockedRange(numPrecalcVal, numPrecalcIdx),
FeatureIdxOnlyPrecalc(featureEvaluator, buf, sample_count, is_buf_16u!=0) );
parallel_for( BlockedRange(0, minNum),
FeatureValAndIdxPrecalc(featureEvaluator, buf, &valCache, sample_count, is_buf_16u!=0) );
parallel_for( BlockedRange(minNum, numPrecalcVal),
FeatureValOnlyPrecalc(featureEvaluator, &valCache, sample_count) );
parallel_for_( Range(numPrecalcVal, numPrecalcIdx),
FeatureIdxOnlyPrecalc(featureEvaluator, buf, sample_count, is_buf_16u!=0) );
parallel_for_( Range(0, minNum),
FeatureValAndIdxPrecalc(featureEvaluator, buf, &valCache, sample_count, is_buf_16u!=0) );
parallel_for_( Range(minNum, numPrecalcVal),
FeatureValOnlyPrecalc(featureEvaluator, &valCache, sample_count) );
cout << "Precalculation time: " << (proctime + TIME( 0 )) << endl;
}