X-Git-Url: http://git.maemo.org/git/?p=opencv;a=blobdiff_plain;f=interfaces%2Fswig%2Fpython%2Fcvshadow.h;fp=interfaces%2Fswig%2Fpython%2Fcvshadow.h;h=77a3c00525f51698b6a45dd4b2b4735cd90b131a;hp=fb8bd91347ccddee5e6d255646bacb71b8b2b2a6;hb=e4c14cdbdf2fe805e79cd96ded236f57e7b89060;hpb=454138ff8a20f6edb9b65a910101403d8b520643

diff --git a/interfaces/swig/python/cvshadow.h b/interfaces/swig/python/cvshadow.h
index fb8bd91..77a3c00 100644
--- a/interfaces/swig/python/cvshadow.h
+++ b/interfaces/swig/python/cvshadow.h
@@ -9,14 +9,6 @@
 // modify cvCvtSeqToArray to take CvArr as input instead of raw data
 CvArr * cvCvtSeqToArray_Shadow( const CvSeq* seq, CvArr * elements, CvSlice slice=CV_WHOLE_SEQ);
 
-// formally overload ArcLength and cvContourPerimeter
-double cvArcLength_Shadow( const CvSeq * seq, CvSlice slice=CV_WHOLE_SEQ, int is_closed=-1);
-double cvArcLength_Shadow( const CvArr * arr, CvSlice slice=CV_WHOLE_SEQ, int is_closed=-1);
-
-// cvContourPerimeter is a macro, but this still works
-static double cvContourPerimeter_Shadow(CvSeq * seq){ return cvContourPerimeter( seq ); }
-static double cvContourPerimeter_Shadow(CvArr * arr){ return cvContourPerimeter( arr ); }
-
 // Return a typed sequence instead of generic CvSeq
 CvTypedSeq<CvRect> * cvHaarDetectObjects_Shadow( const CvArr* image, CvHaarClassifierCascade* cascade,
         CvMemStorage* storage, double scale_factor=1.1, int min_neighbors=3, int flags=0,
@@ -27,11 +19,11 @@ CvTypedSeq<CvPoint> * cvApproxPoly_Shadow( const void* src_seq, int header_size,
                                     int method, double parameter, int parameter2=0);
 
 // Always return a new Mat of indices
-CvMat * cvConvexHull2_Shadow( const CvArr * points, int orientation=CV_CLOCKWISE, 
+CvMat * cvConvexHull2_Shadow( const CvArr * points, int orientation=CV_CLOCKWISE,
 		                  int return_points=0);
 
 std::vector<CvPoint> cvSnakeImage_Shadow( const CvMat * image, std::vector<CvPoint>  points,
-		std::vector<float> alpha, std::vector<float> beta, std::vector<float> gamma, 
+		std::vector<float> alpha, std::vector<float> beta, std::vector<float> gamma,
 		CvSize win, CvTermCriteria criteria, int calc_gradient=1 );
 
 #endif