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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
View File
@@ -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,
modules/objdetect/src/detection_based_tracker.cpp
+2
View File
@@ -618,6 +618,8 @@ cv::DetectionBasedTracker::~DetectionBasedTracker()
void DetectionBasedTracker::process(const Mat& imageGray)
{
CV_INSTRUMENT_REGION()
CV_Assert(imageGray.type()==CV_8UC1);
if ( separateDetectionWork && !separateDetectionWork->isWorking() ) {
modules/objdetect/src/haar.cpp
+11 -3
View File
@@ -1275,6 +1275,8 @@ CV_IMPL int
cvRunHaarClassifierCascade( const CvHaarClassifierCascade* _cascade,
CvPoint pt, int start_stage )
{
CV_INSTRUMENT_REGION()
double stage_sum;
return cvRunHaarClassifierCascadeSum(_cascade, pt, stage_sum, start_stage);
}
@@ -1308,6 +1310,8 @@ public:
void operator()( const Range& range ) const
{
CV_INSTRUMENT_REGION()
Size winSize0 = cascade->orig_window_size;
Size winSize(cvRound(winSize0.width*factor), cvRound(winSize0.height*factor));
int y1 = range.start*stripSize, y2 = std::min(range.end*stripSize, sum1.rows - 1 - winSize0.height);
@@ -1322,10 +1326,10 @@ public:
if(CV_IPP_CHECK_COND && cascade->hid_cascade->ipp_stages )
{
IppiRect iequRect = {equRect.x, equRect.y, equRect.width, equRect.height};
ippiRectStdDev_32f_C1R(sum1.ptr<float>(y1), (int)sum1.step,
CV_INSTRUMENT_FUN_IPP(ippiRectStdDev_32f_C1R, sum1.ptr<float>(y1), (int)sum1.step,
sqsum1.ptr<double>(y1), (int)sqsum1.step,
norm1->ptr<float>(y1), (int)norm1->step,
ippiSize(ssz.width, ssz.height), iequRect );
ippiSize(ssz.width, ssz.height), iequRect);
int positive = (ssz.width/ystep)*((ssz.height + ystep-1)/ystep);
@@ -1344,7 +1348,7 @@ public:
for( int j = 0; j < cascade->count; j++ )
{
if( ippiApplyHaarClassifier_32f_C1R(
if (CV_INSTRUMENT_FUN_IPP(ippiApplyHaarClassifier_32f_C1R,
sum1.ptr<float>(y1), (int)sum1.step,
norm1->ptr<float>(y1), (int)norm1->step,
mask1->ptr<uchar>(y1), (int)mask1->step,
@@ -1441,6 +1445,8 @@ public:
void operator()( const Range& range ) const
{
CV_INSTRUMENT_REGION()
int iy, startY = range.start, endY = range.end;
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];
@@ -1500,6 +1506,8 @@ cvHaarDetectObjectsForROC( const CvArr* _img,
double scaleFactor, int minNeighbors, int flags,
CvSize minSize, CvSize maxSize, bool outputRejectLevels )
{
CV_INSTRUMENT_REGION()
const double GROUP_EPS = 0.2;
CvMat stub, *img = (CvMat*)_img;
cv::Ptr<CvMat> temp, sum, tilted, sqsum, normImg, sumcanny, imgSmall;
modules/objdetect/src/hog.cpp
+20
View File
@@ -236,6 +236,8 @@ inline float32x4_t vsetq_f32(float f0, float f1, float f2, float f3)
void HOGDescriptor::computeGradient(const Mat& img, Mat& grad, Mat& qangle,
Size paddingTL, Size paddingBR) const
{
CV_INSTRUMENT_REGION()
CV_Assert( img.type() == CV_8U || img.type() == CV_8UC3 );
Size gradsize(img.cols + paddingTL.width + paddingBR.width,
@@ -1582,6 +1584,8 @@ static bool ocl_compute(InputArray _img, Size win_stride, std::vector<float>& _d
void HOGDescriptor::compute(InputArray _img, std::vector<float>& descriptors,
Size winStride, Size padding, const std::vector<Point>& locations) const
{
CV_INSTRUMENT_REGION()
if( winStride == Size() )
winStride = cellSize;
Size cacheStride(gcd(winStride.width, blockStride.width),
@@ -1647,6 +1651,8 @@ void HOGDescriptor::detect(const Mat& img,
std::vector<Point>& hits, std::vector<double>& weights, double hitThreshold,
Size winStride, Size padding, const std::vector<Point>& locations) const
{
CV_INSTRUMENT_REGION()
hits.clear();
weights.clear();
if( svmDetector.empty() )
@@ -1758,6 +1764,8 @@ void HOGDescriptor::detect(const Mat& img,
void HOGDescriptor::detect(const Mat& img, std::vector<Point>& hits, double hitThreshold,
Size winStride, Size padding, const std::vector<Point>& locations) const
{
CV_INSTRUMENT_REGION()
std::vector<double> weightsV;
detect(img, hits, weightsV, hitThreshold, winStride, padding, locations);
}
@@ -2040,6 +2048,8 @@ void HOGDescriptor::detectMultiScale(
double hitThreshold, Size winStride, Size padding,
double scale0, double finalThreshold, bool useMeanshiftGrouping) const
{
CV_INSTRUMENT_REGION()
double scale = 1.;
int levels = 0;
@@ -2093,6 +2103,8 @@ void HOGDescriptor::detectMultiScale(InputArray img, std::vector<Rect>& foundLoc
double hitThreshold, Size winStride, Size padding,
double scale0, double finalThreshold, bool useMeanshiftGrouping) const
{
CV_INSTRUMENT_REGION()
std::vector<double> foundWeights;
detectMultiScale(img, foundLocations, foundWeights, hitThreshold, winStride,
padding, scale0, finalThreshold, useMeanshiftGrouping);
@@ -3489,6 +3501,8 @@ public:
void operator()( const Range& range ) const
{
CV_INSTRUMENT_REGION()
int i, i1 = range.start, i2 = range.end;
Size maxSz(cvCeil(img.cols/(*locations)[0].scale), cvCeil(img.rows/(*locations)[0].scale));
@@ -3531,6 +3545,8 @@ void HOGDescriptor::detectROI(const cv::Mat& img, const std::vector<cv::Point> &
CV_OUT std::vector<cv::Point>& foundLocations, CV_OUT std::vector<double>& confidences,
double hitThreshold, cv::Size winStride, cv::Size padding) const
{
CV_INSTRUMENT_REGION()
foundLocations.clear();
confidences.clear();
@@ -3641,6 +3657,8 @@ void HOGDescriptor::detectMultiScaleROI(const cv::Mat& img,
CV_OUT std::vector<cv::Rect>& foundLocations, std::vector<DetectionROI>& locations,
double hitThreshold, int groupThreshold) const
{
CV_INSTRUMENT_REGION()
std::vector<Rect> allCandidates;
Mutex mtx;
@@ -3747,6 +3765,8 @@ void HOGDescriptor::readALTModel(String modelfile)
void HOGDescriptor::groupRectangles(std::vector<cv::Rect>& rectList, std::vector<double>& weights, int groupThreshold, double eps) const
{
CV_INSTRUMENT_REGION()
if( groupThreshold <= 0 || rectList.empty() )
{
return;