build: unreachable code after CV_Error()

modules/datasets/src/or_pascal.cpp

@@ -143,7 +143,6 @@ Ptr<Object> OR_pascalImp::parseAnnotation(const string &path, const string &id)
         case XML_ERROR_FILE_NOT_FOUND:
             error_message = "XML file not found! " + error_message;
             CV_Error(Error::StsParseError, error_message);
-            return annotation;
         default:
             CV_Error(Error::StsParseError, error_message);
             break;

modules/face/src/lbph_faces.cpp

@@ -307,10 +307,8 @@ static Mat histc(InputArray _src, int minVal, int maxVal, bool normed)
         case CV_32FC1:
             return histc_(src, minVal, maxVal, normed);
             break;
-        default:
-            CV_Error(Error::StsUnmatchedFormats, "This type is not implemented yet."); break;
     }
-    return Mat();
+    CV_Error(Error::StsUnmatchedFormats, "This type is not implemented yet.");
 }
 
 

modules/line_descriptor/src/binary_descriptor.cpp

@@ -337,13 +337,8 @@ int BinaryDescriptor::descriptorSize() const
 /* power function with error management */
 static inline int get2Pow( int i )
 {
-  if( i >= 0 && i <= 7 )
+  CV_DbgAssert(i >= 0 && i <= 7);
   return 1 << i;
-  else
-  {
-    CV_Error( Error::StsBadArg, "Invalid power argument" );
-    return -1;
-  }
 }
 
 /* compute Gaussian pyramids */

modules/tracking/src/tracker.cpp

@@ -73,7 +73,6 @@ bool Tracker::init( InputArray image, const Rect2d& boundingBox )
   if( model == 0 )
   {
     CV_Error( -1, "The model is not initialized" );
-    return false;
   }
 
   if( initTracker )

modules/tracking/src/trackerBoostingModel.cpp

@@ -89,7 +89,6 @@ void TrackerBoostingModel::responseToConfidenceMap( const std::vector<Mat>& resp
   if( currentSample.empty() )
   {
     CV_Error( -1, "The samples in Model estimation are empty" );
-    return;
   }
 
   for ( size_t i = 0; i < currentSample.size(); i++ )

modules/tracking/src/trackerFeature.cpp

@@ -90,7 +90,6 @@ Ptr<TrackerFeature> TrackerFeature::create( const String& trackerFeatureType )
   }
 
   CV_Error( -1, "Tracker feature type not supported" );
-  return Ptr<TrackerFeature>();
 }
 
 String TrackerFeature::getClassName() const

modules/tracking/src/trackerMILModel.cpp

@@ -67,7 +67,6 @@ void TrackerMILModel::responseToConfidenceMap( const std::vector<Mat>& responses
   if( currentSample.empty() )
   {
     CV_Error( -1, "The samples in Model estimation are empty" );
-    return;
   }
 
   for ( size_t i = 0; i < responses.size(); i++ )

modules/tracking/src/trackerModel.cpp

@@ -112,7 +112,6 @@ bool TrackerModel::runStateEstimator()
   if( stateEstimator == 0 )
   {
     CV_Error( -1, "Tracker state estimator is not setted" );
-    return false;
   }
   Ptr<TrackerTargetState> targetState = stateEstimator->estimate( confidenceMaps );
   if( targetState == 0 )

modules/tracking/src/trackerSamplerAlgorithm.cpp

@@ -83,7 +83,6 @@ Ptr<TrackerSamplerAlgorithm> TrackerSamplerAlgorithm::create( const String& trac
   }
 
   CV_Error( -1, "Tracker sampler algorithm type not supported" );
-  return Ptr<TrackerSamplerAlgorithm>();
 }
 
 String TrackerSamplerAlgorithm::getClassName() const

modules/tracking/src/trackerStateEstimator.cpp

@@ -85,7 +85,6 @@ Ptr<TrackerStateEstimator> TrackerStateEstimator::create( const String& trackeSt
   }
 
   CV_Error( -1, "Tracker state estimator type not supported" );
-  return Ptr<TrackerStateEstimator>();
 }
 
 String TrackerStateEstimator::getClassName() const

modules/xfeatures2d/samples/bagofwords_classification.cpp

@@ -1794,12 +1794,9 @@ bool VocData::getClassifierGroundTruthImage(const string& obj_class, const strin
     {
         //image found, so return corresponding ground truth
         return m_classifier_gt_all_present[std::distance(m_classifier_gt_all_ids.begin(),it)] != 0;
-    } else {
+    }
     string err_msg = "could not find classifier ground truth for image '" + id + "' and class '" + obj_class + "'";
     CV_Error(Error::StsError,err_msg.c_str());
-    }
-
-    return true;
 }
 
 //-------------------------------------------------------------------

modules/xfeatures2d/src/pct_signatures/distance.hpp

@@ -204,10 +204,8 @@ namespace cv
                     return distanceL5(points1, idx1, points2, idx2);
                 case PCTSignatures::L_INFINITY:
                     return distanceLInfinity(points1, idx1, points2, idx2);
-                default:
-                    CV_Error(Error::StsBadArg, "Distance function not implemented!");
-                    return -1;
                 }
+                CV_Error(Error::StsBadArg, "Distance function not implemented!");
             }
         }
     }

modules/xfeatures2d/src/pct_signatures/similarity.hpp

@@ -117,10 +117,8 @@ namespace cv
                     return gaussianSimilarity(distancefunction, similarityParameter, points1, idx1, points2, idx2);
                 case PCTSignatures::HEURISTIC:
                     return heuristicSimilarity(distancefunction, similarityParameter, points1, idx1, points2, idx2);
-                default:
-                    CV_Error(Error::StsNotImplemented, "Similarity function not implemented!");
-                    return -1;
                 }
+                CV_Error(Error::StsNotImplemented, "Similarity function not implemented!");
             }
         }
     }

modules/xfeatures2d/src/surf.cuda.cpp

@@ -51,7 +51,7 @@ using namespace cv::cuda;
 
 cv::cuda::SURF_CUDA::SURF_CUDA() { throw_no_cuda(); }
 cv::cuda::SURF_CUDA::SURF_CUDA(double, int, int, bool, float, bool) { throw_no_cuda(); }
-int cv::cuda::SURF_CUDA::descriptorSize() const { throw_no_cuda(); return 0;}
+int cv::cuda::SURF_CUDA::descriptorSize() const { throw_no_cuda(); }
 void cv::cuda::SURF_CUDA::uploadKeypoints(const std::vector<KeyPoint>&, GpuMat&) { throw_no_cuda(); }
 void cv::cuda::SURF_CUDA::downloadKeypoints(const GpuMat&, std::vector<KeyPoint>&) { throw_no_cuda(); }
 void cv::cuda::SURF_CUDA::downloadDescriptors(const GpuMat&, std::vector<float>&) { throw_no_cuda(); }

modules/ximgproc/src/disparity_filters.cpp

@@ -480,7 +480,6 @@ Ptr<StereoMatcher> createRightMatcher(Ptr<StereoMatcher> matcher_left)
     else
     {
         CV_Error(Error::StsBadArg, "createRightMatcher supports only StereoBM and StereoSGBM");
-        return Ptr<StereoMatcher>();
     }
 }