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Merge pull request #272 from 5kg:fix_haar

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Andrey Kamaev 2013-01-09 16:53:11 +04:00 committed by OpenCV Buildbot
commit 399c20a928
1 changed files with 35 additions and 16 deletions
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51
modules/objdetect/src/haar.cpp
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@ -1277,14 +1277,15 @@ cvRunHaarClassifierCascade( const CvHaarClassifierCascade* _cascade,
namespace cv namespace cv
{ {
struct HaarDetectObjects_ScaleImage_Invoker class HaarDetectObjects_ScaleImage_Invoker : public ParallelLoopBody
{ {
public:
HaarDetectObjects_ScaleImage_Invoker( const CvHaarClassifierCascade* _cascade, HaarDetectObjects_ScaleImage_Invoker( const CvHaarClassifierCascade* _cascade,
int _stripSize, double _factor, int _stripSize, double _factor,
const Mat& _sum1, const Mat& _sqsum1, Mat* _norm1, 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, std::vector<int>& _levels, std::vector<double>& _weights,
bool _outputLevels ) bool _outputLevels, Mutex *_mtx )
{ {
cascade = _cascade; cascade = _cascade;
stripSize = _stripSize; stripSize = _stripSize;
@ -1297,13 +1298,14 @@ struct HaarDetectObjects_ScaleImage_Invoker
vec = &_vec; vec = &_vec;
rejectLevels = _outputLevels ? &_levels : 0; rejectLevels = _outputLevels ? &_levels : 0;
levelWeights = _outputLevels ? &_weights : 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 winSize0 = cascade->orig_window_size;
Size winSize(cvRound(winSize0.width*factor), cvRound(winSize0.height*factor)); 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) if (y2 <= y1 || sum1.cols <= 1 + winSize0.width)
return; return;
@ -1356,8 +1358,10 @@ struct HaarDetectObjects_ScaleImage_Invoker
for( x = 0; x < ssz.width; x += ystep ) for( x = 0; x < ssz.width; x += ystep )
if( mask1row[x] != 0 ) if( mask1row[x] != 0 )
{ {
mtx->lock();
vec->push_back(Rect(cvRound(x*factor), cvRound(y*factor), vec->push_back(Rect(cvRound(x*factor), cvRound(y*factor),
winSize.width, winSize.height)); winSize.width, winSize.height));
mtx->unlock();
if( --positive == 0 ) if( --positive == 0 )
break; break;
} }
@ -1378,17 +1382,23 @@ struct HaarDetectObjects_ScaleImage_Invoker
result = -1*cascade->count; result = -1*cascade->count;
if( cascade->count + result < 4 ) if( cascade->count + result < 4 )
{ {
mtx->lock();
vec->push_back(Rect(cvRound(x*factor), cvRound(y*factor), vec->push_back(Rect(cvRound(x*factor), cvRound(y*factor),
winSize.width, winSize.height)); winSize.width, winSize.height));
rejectLevels->push_back(-result); rejectLevels->push_back(-result);
levelWeights->push_back(gypWeight); levelWeights->push_back(gypWeight);
mtx->unlock();
} }
} }
else else
{ {
if( result > 0 ) if( result > 0 )
{
mtx->lock();
vec->push_back(Rect(cvRound(x*factor), cvRound(y*factor), vec->push_back(Rect(cvRound(x*factor), cvRound(y*factor),
winSize.width, winSize.height)); winSize.width, winSize.height));
mtx->unlock();
}
} }
} }
} }
@ -1398,18 +1408,20 @@ struct HaarDetectObjects_ScaleImage_Invoker
double factor; double factor;
Mat sum1, sqsum1, *norm1, *mask1; Mat sum1, sqsum1, *norm1, *mask1;
Rect equRect; Rect equRect;
ConcurrentRectVector* vec; std::vector<Rect>* vec;
std::vector<int>* rejectLevels; std::vector<int>* rejectLevels;
std::vector<double>* levelWeights; std::vector<double>* levelWeights;
Mutex* mtx;
}; };
struct HaarDetectObjects_ScaleCascade_Invoker class HaarDetectObjects_ScaleCascade_Invoker : public ParallelLoopBody
{ {
public:
HaarDetectObjects_ScaleCascade_Invoker( const CvHaarClassifierCascade* _cascade, HaarDetectObjects_ScaleCascade_Invoker( const CvHaarClassifierCascade* _cascade,
Size _winsize, const Range& _xrange, double _ystep, Size _winsize, const Range& _xrange, double _ystep,
size_t _sumstep, const int** _p, const int** _pq, size_t _sumstep, const int** _p, const int** _pq,
ConcurrentRectVector& _vec ) std::vector<Rect>& _vec, Mutex* _mtx )
{ {
cascade = _cascade; cascade = _cascade;
winsize = _winsize; winsize = _winsize;
@ -1418,11 +1430,12 @@ struct HaarDetectObjects_ScaleCascade_Invoker
sumstep = _sumstep; sumstep = _sumstep;
p = _p; pq = _pq; p = _p; pq = _pq;
vec = &_vec; 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 *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]; const int *pq0 = pq[0], *pq1 = pq[1], *pq2 = pq[2], *pq3 = pq[3];
bool doCannyPruning = p0 != 0; bool doCannyPruning = p0 != 0;
@ -1449,7 +1462,11 @@ struct HaarDetectObjects_ScaleCascade_Invoker
int result = cvRunHaarClassifierCascade( cascade, cvPoint(x, y), 0 ); int result = cvRunHaarClassifierCascade( cascade, cvPoint(x, y), 0 );
if( result > 0 ) if( result > 0 )
{
mtx->lock();
vec->push_back(Rect(x, y, winsize.width, winsize.height)); vec->push_back(Rect(x, y, winsize.width, winsize.height));
mtx->unlock();
}
ixstep = result != 0 ? 1 : 2; ixstep = result != 0 ? 1 : 2;
} }
} }
@ -1462,7 +1479,8 @@ struct HaarDetectObjects_ScaleCascade_Invoker
Range xrange; Range xrange;
const int** p; const int** p;
const int** pq; const int** pq;
ConcurrentRectVector* vec; std::vector<Rect>* vec;
Mutex* mtx;
}; };
@ -1482,7 +1500,7 @@ cvHaarDetectObjectsForROC( const CvArr* _img,
CvSeq* result_seq = 0; CvSeq* result_seq = 0;
cv::Ptr<CvMemStorage> temp_storage; cv::Ptr<CvMemStorage> temp_storage;
cv::ConcurrentRectVector allCandidates; std::vector<cv::Rect> allCandidates;
std::vector<cv::Rect> rectList; std::vector<cv::Rect> rectList;
std::vector<int> rweights; std::vector<int> rweights;
double factor; double factor;
@ -1490,6 +1508,7 @@ cvHaarDetectObjectsForROC( const CvArr* _img,
bool doCannyPruning = (flags & CV_HAAR_DO_CANNY_PRUNING) != 0; bool doCannyPruning = (flags & CV_HAAR_DO_CANNY_PRUNING) != 0;
bool findBiggestObject = (flags & CV_HAAR_FIND_BIGGEST_OBJECT) != 0; bool findBiggestObject = (flags & CV_HAAR_FIND_BIGGEST_OBJECT) != 0;
bool roughSearch = (flags & CV_HAAR_DO_ROUGH_SEARCH) != 0; bool roughSearch = (flags & CV_HAAR_DO_ROUGH_SEARCH) != 0;
cv::Mutex mtx;
if( !CV_IS_HAAR_CLASSIFIER(cascade) ) if( !CV_IS_HAAR_CLASSIFIER(cascade) )
CV_Error( !cascade ? CV_StsNullPtr : CV_StsBadArg, "Invalid 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. ); cvSetImagesForHaarClassifierCascade( cascade, &sum1, &sqsum1, _tilted, 1. );
cv::Mat _norm1(&norm1), _mask1(&mask1); 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, cv::HaarDetectObjects_ScaleImage_Invoker(cascade,
(((sz1.height + stripCount - 1)/stripCount + ystep-1)/ystep)*ystep, (((sz1.height + stripCount - 1)/stripCount + ystep-1)/ystep)*ystep,
factor, cv::Mat(&sum1), cv::Mat(&sqsum1), &_norm1, &_mask1, 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 else
@ -1695,10 +1714,10 @@ cvHaarDetectObjectsForROC( const CvArr* _img,
endX = cvRound((scanROI.x + scanROI.width - winSize.width) / ystep); 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), cv::HaarDetectObjects_ScaleCascade_Invoker(cascade, winSize, cv::Range(startX, endX),
ystep, sum->step, (const int**)p, ystep, sum->step, (const int**)p,
(const int**)pq, allCandidates )); (const int**)pq, allCandidates, &mtx ));
if( findBiggestObject && !allCandidates.empty() && scanROI.area() == 0 ) if( findBiggestObject && !allCandidates.empty() && scanROI.area() == 0 )
{ {