Replaced dynamic_cas with Ptr::dynamicCast<>, and & with &&

modules/shape/src/aff_trans.cpp

@@ -186,7 +186,7 @@ void AffineTransformerImpl::estimateTransformation(InputArray _pts1, InputArray
 {
     Mat pts1 = _pts1.getMat();
     Mat pts2 = _pts2.getMat();
-    CV_Assert((pts1.channels()==2) & (pts1.cols>0) & (pts2.channels()==2) & (pts2.cols>0));
+    CV_Assert((pts1.channels()==2) && (pts1.cols>0) && (pts2.channels()==2) && (pts2.cols>0));
     CV_Assert(_matches.size()>1);
 
     if (pts1.type() != CV_32F)
@@ -230,7 +230,7 @@ void AffineTransformerImpl::estimateTransformation(InputArray _pts1, InputArray
 float AffineTransformerImpl::applyTransformation(InputArray inPts, OutputArray outPts)
 {
     Mat pts1 = inPts.getMat();
-    CV_Assert((pts1.channels()==2) & (pts1.cols>0));
+    CV_Assert((pts1.channels()==2) && (pts1.cols>0));
 
     //Apply transformation in the complete set of points
     Mat fAffine;

modules/shape/src/emdL1.cpp

@@ -60,7 +60,7 @@
 float EmdL1::getEMDL1(cv::Mat &sig1, cv::Mat &sig2)
 {
     // Initialization
-    CV_Assert((sig1.rows==sig2.rows) & (sig1.cols==sig2.cols) & (!sig1.empty()) & (!sig2.empty()));
+    CV_Assert((sig1.rows==sig2.rows) && (sig1.cols==sig2.cols) && (!sig1.empty()) && (!sig2.empty()));
     if(!initBaseTrees(sig1.rows, 1))
         return -1;
 

modules/shape/src/haus_dis.cpp

@@ -71,7 +71,7 @@ public:
 
     virtual void setRankProportion(float _rankProportion)
     {
-        CV_Assert((_rankProportion>0) & (_rankProportion<=1));
+        CV_Assert((_rankProportion>0) && (_rankProportion<=1));
         rankProportion=_rankProportion;
     }
     virtual float getRankProportion() const {return rankProportion;}
@@ -135,8 +135,8 @@ float HausdorffDistanceExtractorImpl::computeDistance(InputArray contour1, Input
         set1.convertTo(set1, CV_32F);
     if (set2.type() != CV_32F)
         set2.convertTo(set2, CV_32F);
-    CV_Assert((set1.channels()==2) & (set1.cols>0));
-    CV_Assert((set2.channels()==2) & (set2.cols>0));
+    CV_Assert((set1.channels()==2) && (set1.cols>0));
+    CV_Assert((set2.channels()==2) && (set2.cols>0));
     return std::max( _apply(set1, set2, distanceFlag, rankProportion),
                      _apply(set2, set1, distanceFlag, rankProportion) );
 }

modules/shape/src/sc_dis.cpp

@@ -45,7 +45,7 @@
  * Belongie et al., 2002 by Juan Manuel Perez for GSoC 2013.
  */
 #include "precomp.hpp"
-//#include "opencv2/highgui.hpp"
+#include "opencv2/core.hpp"
 /*
  * ShapeContextDescriptor class
  */
@@ -181,7 +181,7 @@ protected:
               {
                   if (queryInliers.size()>0)
                   {
-                      mask.at<char>(i,j)=char(queryInliers[j] & queryInliers[i]);
+                      mask.at<char>(i,j)=char(queryInliers[j] && queryInliers[i]);
                   }
                   else
                   {
@@ -641,14 +641,14 @@ public:
     virtual void setImages(InputArray _image1, InputArray _image2)
     {
         Mat image1_=_image1.getMat(), image2_=_image2.getMat();
-        CV_Assert((image1_.depth()==0) & (image2_.depth()==0));
+        CV_Assert((image1_.depth()==0) && (image2_.depth()==0));
         image1=image1_;
         image2=image2_;
     }
 
     virtual void getImages(OutputArray _image1, OutputArray _image2) const
     {
-        CV_Assert((!image1.empty()) & (!image2.empty()));
+        CV_Assert((!image1.empty()) && (!image2.empty()));
         _image1.create(image1.size(), image1.type());
         _image2.create(image2.size(), image2.type());
         _image1.getMat()=image1;
@@ -726,11 +726,11 @@ float ShapeContextDistanceExtractorImpl::computeDistance(InputArray contour1, In
     else
         sset1.copyTo(set2);
 
-    CV_Assert((set1.channels()==2) & (set1.cols>0));
-    CV_Assert((set2.channels()==2) & (set2.cols>0));
+    CV_Assert((set1.channels()==2) && (set1.cols>0));
+    CV_Assert((set2.channels()==2) && (set2.cols>0));
     if (imageAppearanceWeight!=0)
     {
-        CV_Assert((!image1.empty()) & (!image2.empty()));
+        CV_Assert((!image1.empty()) && (!image2.empty()));
     }
 
     // Initializing Extractor, Descriptor structures and Matcher //
@@ -747,9 +747,9 @@ float ShapeContextDistanceExtractorImpl::computeDistance(InputArray contour1, In
 
     // Initializing some variables //
     std::vector<int> inliers1, inliers2;
-    bool isTPS=false;
-    if ( dynamic_cast<ThinPlateSplineShapeTransformer*>(&*transformer) )
-        isTPS=true;
+
+    Ptr<ThinPlateSplineShapeTransformer> transDown = transformer.dynamicCast<ThinPlateSplineShapeTransformer>();
+
     Mat warpedImage;
     for (int ii=0; ii<iterations; ii++)
     {
@@ -766,8 +766,8 @@ float ShapeContextDistanceExtractorImpl::computeDistance(InputArray contour1, In
         matcher.matchDescriptors(set1SCD, set2SCD, matches, comparer, inliers1, inliers2);
 
         // apply TPS transform //
-        if ( isTPS )
-            dynamic_cast<ThinPlateSplineShapeTransformer*>(&*transformer)->setRegularizationParameter(beta);
+        if ( !transDown.empty() )
+            transDown->setRegularizationParameter(beta);
         transformer->estimateTransformation(set1, set2, matches);
         bEnergy += transformer->applyTransformation(set1, set1);
 
@@ -777,7 +777,7 @@ float ShapeContextDistanceExtractorImpl::computeDistance(InputArray contour1, In
             // Have to accumulate the transformation along all the iterations
             if (ii==0)
             {
-                if ( isTPS )
+                if ( !transDown.empty() )
                 {
                     image2.copyTo(warpedImage);
                 }
@@ -794,7 +794,7 @@ float ShapeContextDistanceExtractorImpl::computeDistance(InputArray contour1, In
     if (imageAppearanceWeight!=0)
     {
         // compute appearance cost
-        if ( isTPS )
+        if ( !transDown.empty() )
         {
             resize(warpedImage, warpedImage, image1.size());
             Mat temp=(warpedImage-image1);

modules/shape/src/tps_trans.cpp

@@ -169,7 +169,7 @@ float ThinPlateSplineShapeTransformerImpl::applyTransformation(InputArray inPts,
 {
     CV_Assert(tpsComputed);
     Mat pts1 = inPts.getMat();
-    CV_Assert((pts1.channels()==2) & (pts1.cols>0));
+    CV_Assert((pts1.channels()==2) && (pts1.cols>0));
 
     //Apply transformation in the complete set of points
     // Ensambling output //
@@ -192,7 +192,7 @@ void ThinPlateSplineShapeTransformerImpl::estimateTransformation(InputArray _pts
 {
     Mat pts1 = _pts1.getMat();
     Mat pts2 = _pts2.getMat();
-    CV_Assert((pts1.channels()==2) & (pts1.cols>0) & (pts2.channels()==2) & (pts2.cols>0));
+    CV_Assert((pts1.channels()==2) && (pts1.cols>0) && (pts2.channels()==2) && (pts2.cols>0));
     CV_Assert(_matches.size()>1);
 
     if (pts1.type() != CV_32F)