Update for IPP for OpenCV 2017u2 integration;

Updated integrations for:
cv::split
cv::merge
cv::insertChannel
cv::extractChannel
cv::Mat::convertTo - now with scaled conversions support
cv::LUT - disabled due to performance issues
Mat::copyTo
Mat::setTo
cv::flip
cv::copyMakeBorder - currently disabled
cv::polarToCart
cv::pow - ipp pow function was removed due to performance issues
cv::hal::magnitude32f/64f - disabled for <= SSE42, poor performance
cv::countNonZero
cv::minMaxIdx
cv::norm
cv::canny - new integration. Disabled for threaded;
cv::cornerHarris
cv::boxFilter
cv::bilateralFilter
cv::integral

modules/objdetect/src/cascadedetect.cpp

@@ -484,6 +484,8 @@ bool FeatureEvaluator::updateScaleData( Size imgsz, const std::vector<float>& _s
 
 bool FeatureEvaluator::setImage( InputArray _image, const std::vector<float>& _scales )
 {
+    CV_INSTRUMENT_REGION()
+
     Size imgsz = _image.size();
     bool recalcOptFeatures = updateScaleData(imgsz, _scales);
 
@@ -628,6 +630,8 @@ Ptr<FeatureEvaluator> HaarEvaluator::clone() const
 
 void HaarEvaluator::computeChannels(int scaleIdx, InputArray img)
 {
+    CV_INSTRUMENT_REGION()
+
     const ScaleData& s = scaleData->at(scaleIdx);
     sqofs = hasTiltedFeatures ? sbufSize.area() * 2 : sbufSize.area();
 
@@ -670,6 +674,8 @@ void HaarEvaluator::computeChannels(int scaleIdx, InputArray img)
 
 void HaarEvaluator::computeOptFeatures()
 {
+    CV_INSTRUMENT_REGION()
+
     if (hasTiltedFeatures)
         tofs = sbufSize.area();
 
@@ -916,6 +922,8 @@ void CascadeClassifierImpl::read(const FileNode& node)
 
 int CascadeClassifierImpl::runAt( Ptr<FeatureEvaluator>& evaluator, Point pt, int scaleIdx, double& weight )
 {
+    CV_INSTRUMENT_REGION()
+
     assert( !oldCascade &&
            (data.featureType == FeatureEvaluator::HAAR ||
             data.featureType == FeatureEvaluator::LBP ||
@@ -984,6 +992,8 @@ public:
 
     void operator()(const Range& range) const
     {
+        CV_INSTRUMENT_REGION()
+
         Ptr<FeatureEvaluator> evaluator = classifier->featureEvaluator->clone();
         double gypWeight = 0.;
         Size origWinSize = classifier->data.origWinSize;

modules/objdetect/src/cascadedetect.hpp

@@ -489,6 +489,8 @@ template<class FEval>
 inline int predictOrdered( CascadeClassifierImpl& cascade,
                            Ptr<FeatureEvaluator> &_featureEvaluator, double& sum )
 {
+    CV_INSTRUMENT_REGION()
+
     int nstages = (int)cascade.data.stages.size();
     int nodeOfs = 0, leafOfs = 0;
     FEval& featureEvaluator = (FEval&)*_featureEvaluator;
@@ -529,6 +531,8 @@ template<class FEval>
 inline int predictCategorical( CascadeClassifierImpl& cascade,
                                Ptr<FeatureEvaluator> &_featureEvaluator, double& sum )
 {
+    CV_INSTRUMENT_REGION()
+
     int nstages = (int)cascade.data.stages.size();
     int nodeOfs = 0, leafOfs = 0;
     FEval& featureEvaluator = (FEval&)*_featureEvaluator;
@@ -571,6 +575,8 @@ template<class FEval>
 inline int predictOrderedStump( CascadeClassifierImpl& cascade,
                                 Ptr<FeatureEvaluator> &_featureEvaluator, double& sum )
 {
+    CV_INSTRUMENT_REGION()
+
     CV_Assert(!cascade.data.stumps.empty());
     FEval& featureEvaluator = (FEval&)*_featureEvaluator;
     const CascadeClassifierImpl::Data::Stump* cascadeStumps = &cascade.data.stumps[0];
@@ -608,6 +614,8 @@ template<class FEval>
 inline int predictCategoricalStump( CascadeClassifierImpl& cascade,
                                     Ptr<FeatureEvaluator> &_featureEvaluator, double& sum )
 {
+    CV_INSTRUMENT_REGION()
+
     CV_Assert(!cascade.data.stumps.empty());
     int nstages = (int)cascade.data.stages.size();
     FEval& featureEvaluator = (FEval&)*_featureEvaluator;

modules/objdetect/src/haar.cpp

@@ -340,8 +340,8 @@ icvCreateHidHaarClassifierCascade( CvHaarClassifierCascade* cascade )
             out->isStumpBased &= node_count == 1;
         }
     }
-/*
-#ifdef HAVE_IPP
+
+#if defined HAVE_IPP && !IPP_DISABLE_HAAR
     int can_use_ipp = CV_IPP_CHECK_COND && (!out->has_tilted_features && !out->is_tree && out->isStumpBased);
 
     if( can_use_ipp )
@@ -396,7 +396,7 @@ icvCreateHidHaarClassifierCascade( CvHaarClassifierCascade* cascade )
         }
     }
 #endif
-*/
+
     cascade->hid_cascade = out;
     assert( (char*)haar_node_ptr - (char*)out <= datasize );