trying to eliminate compile problems

modules/objdetect/doc/cascade_classification.rst

@@ -221,44 +221,6 @@ The function is parallelized with the TBB library.
    * (Python) A face detection example using cascade classifiers can be found at opencv_source_code/samples/python2/facedetect.py
 
 
-CascadeClassifier::setImage
--------------------------------
-Sets an image for detection.
-
-.. ocv:function:: bool CascadeClassifier::setImage( Ptr<FeatureEvaluator>& feval, const Mat& image )
-
-.. ocv:cfunction:: void cvSetImagesForHaarClassifierCascade( CvHaarClassifierCascade* cascade, const CvArr* sum, const CvArr* sqsum, const CvArr* tilted_sum, double scale )
-
-    :param cascade: Haar classifier cascade (OpenCV 1.x API only). See :ocv:func:`CascadeClassifier::detectMultiScale` for more information.
-
-    :param feval: Pointer to the feature evaluator used for computing features.
-
-    :param image: Matrix of the type   ``CV_8UC1``  containing an image where the features are computed.
-
-The function is automatically called by :ocv:func:`CascadeClassifier::detectMultiScale` at every image scale. But if you want to test various locations manually using :ocv:func:`CascadeClassifier::runAt`, you need to call the function before, so that the integral images are computed.
-
-.. note:: in the old API you need to supply integral images (that can be obtained using :ocv:cfunc:`Integral`) instead of the original image.
-
-
-CascadeClassifier::runAt
-----------------------------
-Runs the detector at the specified point.
-
-.. ocv:function:: int CascadeClassifier::runAt( Ptr<FeatureEvaluator>& feval, Point pt, double& weight )
-
-.. ocv:cfunction:: int cvRunHaarClassifierCascade( const CvHaarClassifierCascade* cascade, CvPoint pt, int start_stage=0 )
-
-    :param cascade: Haar classifier cascade (OpenCV 1.x API only). See :ocv:func:`CascadeClassifier::detectMultiScale` for more information.
-
-    :param feval: Feature evaluator used for computing features.
-
-    :param pt: Upper left point of the window where the features are computed. Size of the window is equal to the size of training images.
-
-The function returns 1 if the cascade classifier detects an object in the given location.
-Otherwise, it returns negated index of the stage at which the candidate has been rejected.
-
-Use :ocv:func:`CascadeClassifier::setImage` to set the image for the detector to work with.
-
 groupRectangles
 -------------------
 Groups the object candidate rectangles.

modules/objdetect/include/opencv2/objdetect.hpp

@@ -193,30 +193,31 @@ public:
     virtual Ptr<MaskGenerator> getMaskGenerator() = 0;
 };
 
-class CV_EXPORTS_W CascadeClassifier : public BaseCascadeClassifier
+class CV_EXPORTS_W CascadeClassifier
 {
 public:
     CV_WRAP CascadeClassifier();
     CV_WRAP explicit CascadeClassifier(const String& filename);
-    virtual ~CascadeClassifier();
-    CV_WRAP virtual bool empty() const;
-    CV_WRAP virtual bool load( const String& filename );
-    CV_WRAP virtual void detectMultiScale( InputArray image,
-                                  CV_OUT std::vector<Rect>& objects,
-                                  double scaleFactor = 1.1,
-                                  int minNeighbors = 3, int flags = 0,
-                                  Size minSize = Size(),
-                                  Size maxSize = Size() );
-
-    CV_WRAP virtual void detectMultiScale( InputArray image,
-                                  CV_OUT std::vector<Rect>& objects,
-                                  CV_OUT std::vector<int>& numDetections,
-                                  double scaleFactor=1.1,
-                                  int minNeighbors=3, int flags=0,
-                                  Size minSize=Size(),
-                                  Size maxSize=Size() );
-
-    CV_WRAP virtual void detectMultiScale( InputArray image,
+    ~CascadeClassifier();
+    CV_WRAP bool empty() const;
+    CV_WRAP bool load( const String& filename );
+    CV_WRAP bool read( const FileNode& node );
+    CV_WRAP void detectMultiScale( InputArray image,
+                          CV_OUT std::vector<Rect>& objects,
+                          double scaleFactor = 1.1,
+                          int minNeighbors = 3, int flags = 0,
+                          Size minSize = Size(),
+                          Size maxSize = Size() );
+
+    CV_WRAP void detectMultiScale( InputArray image,
+                          CV_OUT std::vector<Rect>& objects,
+                          CV_OUT std::vector<int>& numDetections,
+                          double scaleFactor=1.1,
+                          int minNeighbors=3, int flags=0,
+                          Size minSize=Size(),
+                          Size maxSize=Size() );
+
+    CV_WRAP void detectMultiScale( InputArray image,
                                   CV_OUT std::vector<Rect>& objects,
                                   CV_OUT std::vector<int>& rejectLevels,
                                   CV_OUT std::vector<double>& levelWeights,
@@ -226,18 +227,18 @@ public:
                                   Size maxSize = Size(),
                                   bool outputRejectLevels = false );
 
-    CV_WRAP virtual bool isOldFormatCascade() const;
-    CV_WRAP virtual Size getOriginalWindowSize() const;
-    CV_WRAP virtual int getFeatureType() const;
-    virtual void* getOldCascade();
+    CV_WRAP bool isOldFormatCascade() const;
+    CV_WRAP Size getOriginalWindowSize() const;
+    CV_WRAP int getFeatureType() const;
+    void* getOldCascade();
 
-    virtual void setMaskGenerator(const Ptr<MaskGenerator>& maskGenerator);
-    virtual Ptr<MaskGenerator> getMaskGenerator();
+    void setMaskGenerator(const Ptr<BaseCascadeClassifier::MaskGenerator>& maskGenerator);
+    Ptr<BaseCascadeClassifier::MaskGenerator> getMaskGenerator();
 protected:
     Ptr<BaseCascadeClassifier> cc;
 };
 
-CV_EXPORTS Ptr<CascadeClassifier::MaskGenerator> createFaceDetectionMaskGenerator();
+CV_EXPORTS Ptr<BaseCascadeClassifier::MaskGenerator> createFaceDetectionMaskGenerator();
 
 //////////////// HOG (Histogram-of-Oriented-Gradients) Descriptor and Object Detector //////////////
 

modules/objdetect/src/cascadedetect.cpp

@@ -918,12 +918,12 @@ Ptr<CascadeClassifierImpl::MaskGenerator> CascadeClassifierImpl::getMaskGenerato
     return maskGenerator;
 }
 
-Ptr<CascadeClassifier::MaskGenerator> createFaceDetectionMaskGenerator()
+Ptr<BaseCascadeClassifier::MaskGenerator> createFaceDetectionMaskGenerator()
 {
 #ifdef HAVE_TEGRA_OPTIMIZATION
     return tegra::getCascadeClassifierMaskGenerator(*this);
 #else
-    return Ptr<CascadeClassifierImpl::MaskGenerator>();
+    return Ptr<BaseCascadeClassifier::MaskGenerator>();
 #endif
 }
 
@@ -1390,6 +1390,17 @@ bool CascadeClassifier::load( const String& filename )
     return !empty();
 }
 
+bool CascadeClassifier::read(const FileNode &root)
+{
+    Ptr<CascadeClassifierImpl> ccimpl;
+    bool ok = ccimpl->read_(root);
+    if( ok )
+        cc = ccimpl.staticCast<BaseCascadeClassifier>();
+    else
+        cc.release();
+    return ok;
+}
+
 void CascadeClassifier::detectMultiScale( InputArray image,
                       CV_OUT std::vector<Rect>& objects,
                       double scaleFactor,
@@ -1452,7 +1463,7 @@ void* CascadeClassifier::getOldCascade()
     return cc->getOldCascade();
 }
 
-void CascadeClassifier::setMaskGenerator(const Ptr<MaskGenerator>& maskGenerator)
+void CascadeClassifier::setMaskGenerator(const Ptr<BaseCascadeClassifier::MaskGenerator>& maskGenerator)
 {
     CV_Assert(!empty());
     cc->setMaskGenerator(maskGenerator);

modules/objdetect/src/cascadedetect.hpp

@@ -86,7 +86,7 @@ protected:
     class Data
     {
     public:
-        struct CV_EXPORTS DTreeNode
+        struct DTreeNode
         {
             int featureIdx;
             float threshold; // for ordered features only
@@ -94,12 +94,12 @@ protected:
             int right;
         };
 
-        struct CV_EXPORTS DTree
+        struct DTree
         {
             int nodeCount;
         };
 
-        struct CV_EXPORTS Stage
+        struct Stage
         {
             int first;
             int ntrees;