generic-library/opencv
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The bug was fixed

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This commit is contained in:
Alexey Kazakov 2011-04-19 12:31:35 +00:00
parent e9a5bbc003
commit 537a36115f
2 changed files with 35 additions and 7 deletions
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16
modules/objdetect/include/opencv2/objdetect/objdetect.hpp
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@ -347,9 +347,16 @@ public:
double scaleFactor=1.1, double scaleFactor=1.1,
int minNeighbors=3, int flags=0, int minNeighbors=3, int flags=0,
Size minSize=Size(), Size minSize=Size(),
Size maxSize=Size() );
CV_WRAP virtual void detectMultiScale( const Mat& image,
CV_OUT vector<Rect>& objects,
vector<int>& rejectLevels,
double scaleFactor=1.1,
int minNeighbors=3, int flags=0,
Size minSize=Size(),
Size maxSize=Size(), Size maxSize=Size(),
bool outputRejectLevels = false, bool outputRejectLevels = false );
vector<int>& rejectLevels = vector<int>(0));
bool isOldFormatCascade() const; bool isOldFormatCascade() const;
@ -358,9 +365,12 @@ public:
bool setImage( const Mat& ); bool setImage( const Mat& );
protected: protected:
//virtual bool detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
// int stripSize, int yStep, double factor, vector<Rect>& candidates );
virtual bool detectSingleScale( const Mat& image, int stripCount, Size processingRectSize, virtual bool detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
int stripSize, int yStep, double factor, vector<Rect>& candidates, int stripSize, int yStep, double factor, vector<Rect>& candidates,
bool outputRejectLevels = false, vector<int>& rejectLevels = vector<int>(0) ); vector<int>& rejectLevels, bool outputRejectLevels = false);
protected: protected:
enum { BOOST = 0 }; enum { BOOST = 0 };

26
modules/objdetect/src/cascadedetect.cpp
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@ -926,7 +926,7 @@ struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } }
bool CascadeClassifier::detectSingleScale( const Mat& image, int stripCount, Size processingRectSize, bool CascadeClassifier::detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
int stripSize, int yStep, double factor, vector<Rect>& candidates, int stripSize, int yStep, double factor, vector<Rect>& candidates,
bool outputRejectLevels, vector<int>& levels ) vector<int>& levels, bool outputRejectLevels )
{ {
if( !featureEvaluator->setImage( image, data.origWinSize ) ) if( !featureEvaluator->setImage( image, data.origWinSize ) )
return false; return false;
@ -949,6 +949,14 @@ bool CascadeClassifier::detectSingleScale( const Mat& image, int stripCount, Siz
return true; return true;
} }
//bool CascadeClassifier::detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
// int stripSize, int yStep, double factor, vector<Rect>& candidates )
//{
// vector<int> fakeLevels;
// return detectSingleScale( image, stripCount, processingRectSize,
// stripSize, yStep, factor, candidates, fakeLevels, false );
//}
bool CascadeClassifier::isOldFormatCascade() const bool CascadeClassifier::isOldFormatCascade() const
{ {
return !oldCascade.empty(); return !oldCascade.empty();
@ -969,10 +977,11 @@ bool CascadeClassifier::setImage(const Mat& image)
return featureEvaluator->setImage(image, data.origWinSize); return featureEvaluator->setImage(image, data.origWinSize);
} }
void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& objects, void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& objects,
vector<int>& rejectLevels,
double scaleFactor, int minNeighbors, double scaleFactor, int minNeighbors,
int flags, Size minObjectSize, Size maxObjectSize, int flags, Size minObjectSize, Size maxObjectSize,
bool outputRejectLevels, vector<int>& rejectLevels ) bool outputRejectLevels )
{ {
const double GROUP_EPS = 0.2; const double GROUP_EPS = 0.2;
@ -1042,7 +1051,7 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
#endif #endif
if( !detectSingleScale( scaledImage, stripCount, processingRectSize, stripSize, yStep, factor, candidates, if( !detectSingleScale( scaledImage, stripCount, processingRectSize, stripSize, yStep, factor, candidates,
outputRejectLevels, rejectLevels ) ) rejectLevels, outputRejectLevels ) )
break; break;
} }
@ -1051,6 +1060,15 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
groupRectangles( objects, rejectLevels, minNeighbors, GROUP_EPS ); groupRectangles( objects, rejectLevels, minNeighbors, GROUP_EPS );
}
void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& objects,
double scaleFactor, int minNeighbors,
int flags, Size minObjectSize, Size maxObjectSize)
{
vector<int> fakeLevels;
detectMultiScale( image, objects, fakeLevels, scaleFactor,
minNeighbors, flags, minObjectSize, maxObjectSize, false );
} }
bool CascadeClassifier::Data::read(const FileNode &root) bool CascadeClassifier::Data::read(const FileNode &root)