OpenCV - cascade_classifier.patch

cascade_classifier.patch

Peter Minin, 2013-06-04 04:42 pm

                                        Size minSize=Size(),
                                        Size maxSize=Size() );
         CV_WRAP virtual void detectMultiScale( const Mat& image,
                                        CV_OUT vector<Rect>& objects,
                                        vector<int>& weights,
                                        double scaleFactor=1.1,
                                        int minNeighbors=3, int flags=0,
                                        Size minSize=Size(),
                                        Size maxSize=Size() );
         CV_WRAP virtual void detectMultiScale( const Mat& image,
                                        CV_OUT vector<Rect>& objects,
                                        vector<int>& rejectLevels,
-...
                                        int minNeighbors=3, int flags=0,
                                        Size minSize=Size(),
                                        Size maxSize=Size(),
                                        bool outputRejectLevels=false );
                                        bool outputRejectLevels=false,
                                        bool outputWeights=false );
         bool isOldFormatCascade() const;

     };
     struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
     struct getNeighbors { int operator ()(const CvAvgComp& e) const { return e.neighbors; } };
     bool CascadeClassifier::detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
-...
                                               vector<double>& levelWeights,
                                               double scaleFactor, int minNeighbors,
                                               int flags, Size minObjectSize, Size maxObjectSize,
                                               bool outputRejectLevels )
                                               bool outputRejectLevels, bool outputWeights )
+    {
         const double GROUP_EPS = 0.2;
         CV_Assert( scaleFactor > 1 && image.depth() == CV_8U );
         CV_Assert( !(outputRejectLevels && outputWeights) );
         if( empty() )
             return;
-...
             Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
             objects.resize(vecAvgComp.size());
             std::transform(vecAvgComp.begin(), vecAvgComp.end(), objects.begin(), getRect());
             if (outputWeights) {
                 rejectLevels.resize(vecAvgComp.size());
                 std::transform(vecAvgComp.begin(), vecAvgComp.end(), rejectLevels.begin(),
                         getNeighbors());
+            }
             return;
+        }
-...
+        {
             groupRectangles( objects, rejectLevels, levelWeights, minNeighbors, GROUP_EPS );
+        }
         else if( outputWeights )
+        {
             groupRectangles( objects, rejectLevels, minNeighbors, GROUP_EPS );
+        }
         else
+        {
             groupRectangles( objects, minNeighbors, GROUP_EPS );
-...
             minNeighbors, flags, minObjectSize, maxObjectSize, false );
+    }
     void CascadeClassifier::detectMultiScale( const Mat& image, CV_OUT vector<Rect>& objects,
                                               vector<int>& weights, double scaleFactor,
                                               int minNeighbors, int flags, Size minObjectSize,
                                               Size maxObjectSize )
+    {
         vector<double> fakeLevelWeights;
         detectMultiScale( image, objects, weights, fakeLevelWeights, scaleFactor,
                 minNeighbors, flags, minObjectSize, maxObjectSize, false, true );
+    }
     bool CascadeClassifier::Data::read(const FileNode &root)
+    {
         static const float THRESHOLD_EPS = 1e-5f;

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