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Changed parallel_for to parallel_for_ in haar.cpp

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pull/272/head
Zifei Tong 12 years ago
parent 5f41971305
commit 260bdc057c
1 changed files with 35 additions and 16 deletions
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  1. 51
      modules/objdetect/src/haar.cpp

51
modules/objdetect/src/haar.cpp
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@ -1277,14 +1277,15 @@ cvRunHaarClassifierCascade( const CvHaarClassifierCascade* _cascade,
namespace cv
{
struct HaarDetectObjects_ScaleImage_Invoker
class HaarDetectObjects_ScaleImage_Invoker : public ParallelLoopBody
{
public:
HaarDetectObjects_ScaleImage_Invoker( const CvHaarClassifierCascade* _cascade,
int _stripSize, double _factor,
const Mat& _sum1, const Mat& _sqsum1, Mat* _norm1,
Mat* _mask1, Rect _equRect, ConcurrentRectVector& _vec,
Mat* _mask1, Rect _equRect, std::vector<Rect>& _vec,
std::vector<int>& _levels, std::vector<double>& _weights,
bool _outputLevels )
bool _outputLevels, Mutex *_mtx )
{
cascade = _cascade;
stripSize = _stripSize;
@ -1297,13 +1298,14 @@ struct HaarDetectObjects_ScaleImage_Invoker
vec = &_vec;
rejectLevels = _outputLevels ? &_levels : 0;
levelWeights = _outputLevels ? &_weights : 0;
mtx = _mtx;
}
void operator()( const BlockedRange& range ) const
void operator()( const Range& range ) const
{
Size winSize0 = cascade->orig_window_size;
Size winSize(cvRound(winSize0.width*factor), cvRound(winSize0.height*factor));
int y1 = range.begin()*stripSize, y2 = min(range.end()*stripSize, sum1.rows - 1 - winSize0.height);
int y1 = range.start*stripSize, y2 = min(range.end*stripSize, sum1.rows - 1 - winSize0.height);
if (y2 <= y1 || sum1.cols <= 1 + winSize0.width)
return;
@ -1356,8 +1358,10 @@ struct HaarDetectObjects_ScaleImage_Invoker
for( x = 0; x < ssz.width; x += ystep )
if( mask1row[x] != 0 )
{
mtx->lock();
vec->push_back(Rect(cvRound(x*factor), cvRound(y*factor),
winSize.width, winSize.height));
mtx->unlock();
if( --positive == 0 )
break;
}
@ -1378,17 +1382,23 @@ struct HaarDetectObjects_ScaleImage_Invoker
result = -1*cascade->count;
if( cascade->count + result < 4 )
{
mtx->lock();
vec->push_back(Rect(cvRound(x*factor), cvRound(y*factor),
winSize.width, winSize.height));
rejectLevels->push_back(-result);
levelWeights->push_back(gypWeight);
mtx->unlock();
}
}
else
{
if( result > 0 )
{
mtx->lock();
vec->push_back(Rect(cvRound(x*factor), cvRound(y*factor),
winSize.width, winSize.height));
mtx->unlock();
}
}
}
}
@ -1398,18 +1408,20 @@ struct HaarDetectObjects_ScaleImage_Invoker
double factor;
Mat sum1, sqsum1, *norm1, *mask1;
Rect equRect;
ConcurrentRectVector* vec;
std::vector<Rect>* vec;
std::vector<int>* rejectLevels;
std::vector<double>* levelWeights;
Mutex* mtx;
};
struct HaarDetectObjects_ScaleCascade_Invoker
class HaarDetectObjects_ScaleCascade_Invoker : public ParallelLoopBody
{
public:
HaarDetectObjects_ScaleCascade_Invoker( const CvHaarClassifierCascade* _cascade,
Size _winsize, const Range& _xrange, double _ystep,
size_t _sumstep, const int** _p, const int** _pq,
ConcurrentRectVector& _vec )
std::vector<Rect>& _vec, Mutex* _mtx )
{
cascade = _cascade;
winsize = _winsize;
@ -1418,11 +1430,12 @@ struct HaarDetectObjects_ScaleCascade_Invoker
sumstep = _sumstep;
p = _p; pq = _pq;
vec = &_vec;
mtx = _mtx;
}
void operator()( const BlockedRange& range ) const
void operator()( const Range& range ) const
{
int iy, startY = range.begin(), endY = range.end();
int iy, startY = range.start, endY = range.end;
const int *p0 = p[0], *p1 = p[1], *p2 = p[2], *p3 = p[3];
const int *pq0 = pq[0], *pq1 = pq[1], *pq2 = pq[2], *pq3 = pq[3];
bool doCannyPruning = p0 != 0;
@ -1449,7 +1462,11 @@ struct HaarDetectObjects_ScaleCascade_Invoker
int result = cvRunHaarClassifierCascade( cascade, cvPoint(x, y), 0 );
if( result > 0 )
{
mtx->lock();
vec->push_back(Rect(x, y, winsize.width, winsize.height));
mtx->unlock();
}
ixstep = result != 0 ? 1 : 2;
}
}
@ -1462,7 +1479,8 @@ struct HaarDetectObjects_ScaleCascade_Invoker
Range xrange;
const int** p;
const int** pq;
ConcurrentRectVector* vec;
std::vector<Rect>* vec;
Mutex* mtx;
};
@ -1482,7 +1500,7 @@ cvHaarDetectObjectsForROC( const CvArr* _img,
CvSeq* result_seq = 0;
cv::Ptr<CvMemStorage> temp_storage;
cv::ConcurrentRectVector allCandidates;
std::vector<cv::Rect> allCandidates;
std::vector<cv::Rect> rectList;
std::vector<int> rweights;
double factor;
@ -1490,6 +1508,7 @@ cvHaarDetectObjectsForROC( const CvArr* _img,
bool doCannyPruning = (flags & CV_HAAR_DO_CANNY_PRUNING) != 0;
bool findBiggestObject = (flags & CV_HAAR_FIND_BIGGEST_OBJECT) != 0;
bool roughSearch = (flags & CV_HAAR_DO_ROUGH_SEARCH) != 0;
cv::Mutex mtx;
if( !CV_IS_HAAR_CLASSIFIER(cascade) )
CV_Error( !cascade ? CV_StsNullPtr : CV_StsBadArg, "Invalid classifier cascade" );
@ -1599,11 +1618,11 @@ cvHaarDetectObjectsForROC( const CvArr* _img,
cvSetImagesForHaarClassifierCascade( cascade, &sum1, &sqsum1, _tilted, 1. );
cv::Mat _norm1(&norm1), _mask1(&mask1);
cv::parallel_for(cv::BlockedRange(0, stripCount),
cv::parallel_for_(cv::Range(0, stripCount),
cv::HaarDetectObjects_ScaleImage_Invoker(cascade,
(((sz1.height + stripCount - 1)/stripCount + ystep-1)/ystep)*ystep,
factor, cv::Mat(&sum1), cv::Mat(&sqsum1), &_norm1, &_mask1,
cv::Rect(equRect), allCandidates, rejectLevels, levelWeights, outputRejectLevels));
cv::Rect(equRect), allCandidates, rejectLevels, levelWeights, outputRejectLevels, &mtx));
}
}
else
@ -1695,10 +1714,10 @@ cvHaarDetectObjectsForROC( const CvArr* _img,
endX = cvRound((scanROI.x + scanROI.width - winSize.width) / ystep);
}
cv::parallel_for(cv::BlockedRange(startY, endY),
cv::parallel_for_(cv::Range(startY, endY),
cv::HaarDetectObjects_ScaleCascade_Invoker(cascade, winSize, cv::Range(startX, endX),
ystep, sum->step, (const int**)p,
(const int**)pq, allCandidates ));
(const int**)pq, allCandidates, &mtx ));
if( findBiggestObject && !allCandidates.empty() && scanROI.area() == 0 )
{

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