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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin
2018-09-15 00:52:21 +03:00
committed by Alexander Alekhin
parent a024593fa6 14b438317e
commit 808ba552c5
235 changed files with 18422 additions and 3526 deletions
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modules/objdetect/src/cascadedetect.cpp
+17 -17
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@@ -60,7 +60,7 @@ 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()
CV_INSTRUMENT_REGION();
if( groupThreshold <= 0 || rectList.empty() )
{
@@ -361,14 +361,14 @@ static void groupRectangles_meanshift(std::vector<Rect>& rectList, double detect
void groupRectangles(std::vector<Rect>& rectList, int groupThreshold, double eps)
{
CV_INSTRUMENT_REGION()
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()
CV_INSTRUMENT_REGION();
groupRectangles(rectList, groupThreshold, eps, &weights, 0);
}
@@ -376,7 +376,7 @@ void groupRectangles(std::vector<Rect>& rectList, std::vector<int>& weights, int
void groupRectangles(std::vector<Rect>& rectList, std::vector<int>& rejectLevels,
std::vector<double>& levelWeights, int groupThreshold, double eps)
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
groupRectangles(rectList, groupThreshold, eps, &rejectLevels, &levelWeights);
}
@@ -384,7 +384,7 @@ void groupRectangles(std::vector<Rect>& rectList, std::vector<int>& rejectLevels
void groupRectangles_meanshift(std::vector<Rect>& rectList, std::vector<double>& foundWeights,
std::vector<double>& foundScales, double detectThreshold, Size winDetSize)
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
groupRectangles_meanshift(rectList, detectThreshold, foundWeights, foundScales, winDetSize);
}
@@ -483,7 +483,7 @@ bool FeatureEvaluator::updateScaleData( Size imgsz, const std::vector<float>& _s
bool FeatureEvaluator::setImage( InputArray _image, const std::vector<float>& _scales )
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
Size imgsz = _image.size();
bool recalcOptFeatures = updateScaleData(imgsz, _scales);
@@ -632,7 +632,7 @@ Ptr<FeatureEvaluator> HaarEvaluator::clone() const
void HaarEvaluator::computeChannels(int scaleIdx, InputArray img)
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
const ScaleData& s = scaleData->at(scaleIdx);
sqofs = hasTiltedFeatures ? sbufSize.area() * 2 : sbufSize.area();
@@ -676,7 +676,7 @@ void HaarEvaluator::computeChannels(int scaleIdx, InputArray img)
void HaarEvaluator::computeOptFeatures()
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
if (hasTiltedFeatures)
tofs = sbufSize.area();
@@ -929,7 +929,7 @@ void CascadeClassifierImpl::read(const FileNode& node)
int CascadeClassifierImpl::runAt( Ptr<FeatureEvaluator>& evaluator, Point pt, int scaleIdx, double& weight )
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
assert( !oldCascade &&
(data.featureType == FeatureEvaluator::HAAR ||
@@ -995,7 +995,7 @@ public:
void operator()(const Range& range) const CV_OVERRIDE
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
Ptr<FeatureEvaluator> evaluator = classifier->featureEvaluator->clone();
double gypWeight = 0.;
@@ -1240,7 +1240,7 @@ void CascadeClassifierImpl::detectMultiScaleNoGrouping( InputArray _image, std::
double scaleFactor, Size minObjectSize, Size maxObjectSize,
bool outputRejectLevels )
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
Size imgsz = _image.size();
Size originalWindowSize = getOriginalWindowSize();
@@ -1367,7 +1367,7 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
int flags, Size minObjectSize, Size maxObjectSize,
bool outputRejectLevels )
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
CV_Assert( scaleFactor > 1 && _image.depth() == CV_8U );
@@ -1401,7 +1401,7 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
double scaleFactor, int minNeighbors,
int flags, Size minObjectSize, Size maxObjectSize)
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
std::vector<int> fakeLevels;
std::vector<double> fakeWeights;
@@ -1414,7 +1414,7 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
int minNeighbors, int flags, Size minObjectSize,
Size maxObjectSize )
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
Mat image = _image.getMat();
CV_Assert( scaleFactor > 1 && image.depth() == CV_8U );
@@ -1688,7 +1688,7 @@ void CascadeClassifier::detectMultiScale( InputArray image,
Size minSize,
Size maxSize )
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
CV_Assert(!empty());
cc->detectMultiScale(image, objects, scaleFactor, minNeighbors, flags, minSize, maxSize);
@@ -1702,7 +1702,7 @@ void CascadeClassifier::detectMultiScale( InputArray image,
int minNeighbors, int flags,
Size minSize, Size maxSize )
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
CV_Assert(!empty());
cc->detectMultiScale(image, objects, numDetections,
@@ -1719,7 +1719,7 @@ void CascadeClassifier::detectMultiScale( InputArray image,
Size minSize, Size maxSize,
bool outputRejectLevels )
{
CV_INSTRUMENT_REGION()
CV_INSTRUMENT_REGION();
CV_Assert(!empty());
cc->detectMultiScale(image, objects, rejectLevels, levelWeights,