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Add a variant of detectMultiScale with an argument 'weights' that

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receives the number of neighbors joined into each detected object
This commit is contained in:
Peter Minin
2013-06-06 19:00:55 +04:00
parent 99340b5613
commit ab6be9b7b7
3 changed files with 36 additions and 2 deletions
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24
modules/objdetect/src/cascadedetect.cpp
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@@ -1023,6 +1023,7 @@ public:
};
struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
struct getNeighbors { int operator ()(const CvAvgComp& e) const { return e.neighbors; } };
bool CascadeClassifier::detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
@@ -1092,11 +1093,12 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
vector<double>& levelWeights,
double scaleFactor, int minNeighbors,
int flags, Size minObjectSize, Size maxObjectSize,
bool outputRejectLevels )
bool outputRejectLevels, bool outputWeights )
{
const double GROUP_EPS = 0.2;
CV_Assert( scaleFactor > 1 && image.depth() == CV_8U );
CV_Assert( !( outputRejectLevels && outputWeights ) );
if( empty() )
return;
@@ -1111,6 +1113,12 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
objects.resize(vecAvgComp.size());
std::transform(vecAvgComp.begin(), vecAvgComp.end(), objects.begin(), getRect());
if( outputWeights )
{
rejectLevels.resize(vecAvgComp.size());
std::transform(vecAvgComp.begin(), vecAvgComp.end(), rejectLevels.begin(),
getNeighbors());
}
return;
}
@@ -1183,6 +1191,10 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
{
groupRectangles( objects, rejectLevels, levelWeights, minNeighbors, GROUP_EPS );
}
else if( outputWeights )
{
groupRectangles( objects, rejectLevels, minNeighbors, GROUP_EPS );
}
else
{
groupRectangles( objects, minNeighbors, GROUP_EPS );
@@ -1199,6 +1211,16 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
minNeighbors, flags, minObjectSize, maxObjectSize, false );
}
void CascadeClassifier::detectMultiScale( const Mat& image, CV_OUT vector<Rect>& objects,
vector<int>& weights, double scaleFactor,
int minNeighbors, int flags, Size minObjectSize,
Size maxObjectSize )
{
vector<double> fakeLevelWeights;
detectMultiScale( image, objects, weights, fakeLevelWeights, scaleFactor,
minNeighbors, flags, minObjectSize, maxObjectSize, false, true );
}
bool CascadeClassifier::Data::read(const FileNode &root)
{
static const float THRESHOLD_EPS = 1e-5f;