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Instrumentation for OpenCV API regions and IPP functions;

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This commit is contained in:
Pavel Vlasov
2016-08-18 09:53:00 +03:00
parent 680ca88ce0
commit 30a6cee2fe
133 changed files with 1691 additions and 456 deletions
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modules/objdetect/src/cascadedetect.cpp
+24
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@@ -59,6 +59,8 @@ template<typename _Tp> void copyVectorToUMat(const std::vector<_Tp>& v, UMat& um
void groupRectangles(std::vector<Rect>& rectList, int groupThreshold, double eps,
std::vector<int>* weights, std::vector<double>* levelWeights)
{
CV_INSTRUMENT_REGION()
if( groupThreshold <= 0 || rectList.empty() )
{
if( weights )
@@ -359,23 +361,31 @@ static void groupRectangles_meanshift(std::vector<Rect>& rectList, double detect
void groupRectangles(std::vector<Rect>& rectList, int groupThreshold, double eps)
{
CV_INSTRUMENT_REGION()
groupRectangles(rectList, groupThreshold, eps, 0, 0);
}
void groupRectangles(std::vector<Rect>& rectList, std::vector<int>& weights, int groupThreshold, double eps)
{
CV_INSTRUMENT_REGION()
groupRectangles(rectList, groupThreshold, eps, &weights, 0);
}
//used for cascade detection algorithm for ROC-curve calculating
void groupRectangles(std::vector<Rect>& rectList, std::vector<int>& rejectLevels,
std::vector<double>& levelWeights, int groupThreshold, double eps)
{
CV_INSTRUMENT_REGION()
groupRectangles(rectList, groupThreshold, eps, &rejectLevels, &levelWeights);
}
//can be used for HOG detection algorithm only
void groupRectangles_meanshift(std::vector<Rect>& rectList, std::vector<double>& foundWeights,
std::vector<double>& foundScales, double detectThreshold, Size winDetSize)
{
CV_INSTRUMENT_REGION()
groupRectangles_meanshift(rectList, detectThreshold, &foundWeights, foundScales, winDetSize);
}
@@ -1217,6 +1227,8 @@ void CascadeClassifierImpl::detectMultiScaleNoGrouping( InputArray _image, std::
double scaleFactor, Size minObjectSize, Size maxObjectSize,
bool outputRejectLevels )
{
CV_INSTRUMENT_REGION()
Size imgsz = _image.size();
Mat grayImage;
@@ -1320,6 +1332,8 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
int flags, Size minObjectSize, Size maxObjectSize,
bool outputRejectLevels )
{
CV_INSTRUMENT_REGION()
CV_Assert( scaleFactor > 1 && _image.depth() == CV_8U );
if( empty() )
@@ -1352,6 +1366,8 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
double scaleFactor, int minNeighbors,
int flags, Size minObjectSize, Size maxObjectSize)
{
CV_INSTRUMENT_REGION()
std::vector<int> fakeLevels;
std::vector<double> fakeWeights;
detectMultiScale( _image, objects, fakeLevels, fakeWeights, scaleFactor,
@@ -1363,6 +1379,8 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
int minNeighbors, int flags, Size minObjectSize,
Size maxObjectSize )
{
CV_INSTRUMENT_REGION()
Mat image = _image.getMat();
CV_Assert( scaleFactor > 1 && image.depth() == CV_8U );
@@ -1636,6 +1654,8 @@ void CascadeClassifier::detectMultiScale( InputArray image,
Size minSize,
Size maxSize )
{
CV_INSTRUMENT_REGION()
CV_Assert(!empty());
cc->detectMultiScale(image, objects, scaleFactor, minNeighbors, flags, minSize, maxSize);
clipObjects(image.size(), objects, 0, 0);
@@ -1648,6 +1668,8 @@ void CascadeClassifier::detectMultiScale( InputArray image,
int minNeighbors, int flags,
Size minSize, Size maxSize )
{
CV_INSTRUMENT_REGION()
CV_Assert(!empty());
cc->detectMultiScale(image, objects, numDetections,
scaleFactor, minNeighbors, flags, minSize, maxSize);
@@ -1663,6 +1685,8 @@ void CascadeClassifier::detectMultiScale( InputArray image,
Size minSize, Size maxSize,
bool outputRejectLevels )
{
CV_INSTRUMENT_REGION()
CV_Assert(!empty());
cc->detectMultiScale(image, objects, rejectLevels, levelWeights,
scaleFactor, minNeighbors, flags,