Merge pull request #650 from taka-no-me:cvdef

modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst

@@ -117,7 +117,7 @@ Finds the camera intrinsic and extrinsic parameters from several views of a cali
 
 .. ocv:function:: double calibrateCamera( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags=0, TermCriteria criteria=TermCriteria( TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON) )
 
-.. ocv:pyfunction:: cv2.calibrateCamera(objectPoints, imagePoints, imageSize[, cameraMatrix[, distCoeffs[, rvecs[, tvecs[, flags[, criteria]]]]]]) -> retval, cameraMatrix, distCoeffs, rvecs, tvecs
+.. ocv:pyfunction:: cv2.calibrateCamera(objectPoints, imagePoints, imageSize, cameraMatrix, distCoeffs[, rvecs[, tvecs[, flags[, criteria]]]]) -> retval, cameraMatrix, distCoeffs, rvecs, tvecs
 
 .. ocv:cfunction:: double cvCalibrateCamera2( const CvMat* object_points, const CvMat* image_points, const CvMat* point_counts, CvSize image_size, CvMat* camera_matrix, CvMat* distortion_coeffs, CvMat* rotation_vectors=NULL, CvMat* translation_vectors=NULL, int flags=0, CvTermCriteria term_crit=cvTermCriteria( CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,DBL_EPSILON) )
 
@@ -433,7 +433,7 @@ Renders the detected chessboard corners.
 
 .. ocv:function:: void drawChessboardCorners( InputOutputArray image, Size patternSize, InputArray corners, bool patternWasFound )
 
-.. ocv:pyfunction:: cv2.drawChessboardCorners(image, patternSize, corners, patternWasFound) -> None
+.. ocv:pyfunction:: cv2.drawChessboardCorners(image, patternSize, corners, patternWasFound) -> image
 
 .. ocv:cfunction:: void cvDrawChessboardCorners( CvArr* image, CvSize pattern_size, CvPoint2D32f* corners, int count, int pattern_was_found )
 .. ocv:pyoldfunction:: cv.DrawChessboardCorners(image, patternSize, corners, patternWasFound)-> None
@@ -923,7 +923,7 @@ Filters off small noise blobs (speckles) in the disparity map
 
 .. ocv:function:: void filterSpeckles( InputOutputArray img, double newVal, int maxSpeckleSize, double maxDiff, InputOutputArray buf=noArray() )
 
-.. ocv:pyfunction:: cv2.filterSpeckles(img, newVal, maxSpeckleSize, maxDiff[, buf]) -> None
+.. ocv:pyfunction:: cv2.filterSpeckles(img, newVal, maxSpeckleSize, maxDiff[, buf]) -> img, buf
 
     :param img: The input 16-bit signed disparity image
 
@@ -1362,7 +1362,7 @@ Calibrates the stereo camera.
 
 .. ocv:function:: double stereoCalibrate( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, Size imageSize, OutputArray R, OutputArray T, OutputArray E, OutputArray F, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6), int flags=CALIB_FIX_INTRINSIC )
 
-.. ocv:pyfunction:: cv2.stereoCalibrate(objectPoints, imagePoints1, imagePoints2, imageSize[, cameraMatrix1[, distCoeffs1[, cameraMatrix2[, distCoeffs2[, R[, T[, E[, F[, criteria[, flags]]]]]]]]]]) -> retval, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, R, T, E, F
+.. ocv:pyfunction:: cv2.stereoCalibrate(objectPoints, imagePoints1, imagePoints2, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, imageSize[, R[, T[, E[, F[, criteria[, flags]]]]]]) -> retval, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, R, T, E, F
 
 .. ocv:cfunction:: double cvStereoCalibrate( const CvMat* object_points, const CvMat* image_points1, const CvMat* image_points2, const CvMat* npoints, CvMat* camera_matrix1, CvMat* dist_coeffs1, CvMat* camera_matrix2, CvMat* dist_coeffs2, CvSize image_size, CvMat* R, CvMat* T, CvMat* E=0, CvMat* F=0, CvTermCriteria term_crit=cvTermCriteria( CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,1e-6), int flags=CV_CALIB_FIX_INTRINSIC )
 

modules/calib3d/include/opencv2/calib3d.hpp

@@ -550,8 +550,8 @@ enum
 CV_EXPORTS_W double calibrateCamera( InputArrayOfArrays objectPoints,
                                      InputArrayOfArrays imagePoints,
                                      Size imageSize,
-                                     CV_OUT InputOutputArray cameraMatrix,
-                                     CV_OUT InputOutputArray distCoeffs,
+                                     InputOutputArray cameraMatrix,
+                                     InputOutputArray distCoeffs,
                                      OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
                                      int flags=0, TermCriteria criteria = TermCriteria(
                                          TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON) );
@@ -571,10 +571,10 @@ CV_EXPORTS_W void calibrationMatrixValues( InputArray cameraMatrix,
 CV_EXPORTS_W double stereoCalibrate( InputArrayOfArrays objectPoints,
                                      InputArrayOfArrays imagePoints1,
                                      InputArrayOfArrays imagePoints2,
-                                     CV_OUT InputOutputArray cameraMatrix1,
-                                     CV_OUT InputOutputArray distCoeffs1,
-                                     CV_OUT InputOutputArray cameraMatrix2,
-                                     CV_OUT InputOutputArray distCoeffs2,
+                                     InputOutputArray cameraMatrix1,
+                                     InputOutputArray distCoeffs1,
+                                     InputOutputArray cameraMatrix2,
+                                     InputOutputArray distCoeffs2,
                                      Size imageSize, OutputArray R,
                                      OutputArray T, OutputArray E, OutputArray F,
                                      TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6),

modules/core/doc/clustering.rst

@@ -9,7 +9,7 @@ Finds centers of clusters and groups input samples around the clusters.
 
 .. ocv:function:: double kmeans( InputArray data, int K, InputOutputArray bestLabels, TermCriteria criteria, int attempts, int flags, OutputArray centers=noArray() )
 
-.. ocv:pyfunction:: cv2.kmeans(data, K, criteria, attempts, flags[, bestLabels[, centers]]) -> retval, bestLabels, centers
+.. ocv:pyfunction:: cv2.kmeans(data, K, bestLabels, criteria, attempts, flags[, centers]) -> retval, bestLabels, centers
 
 .. ocv:cfunction:: int cvKMeans2( const CvArr* samples, int cluster_count, CvArr* labels, CvTermCriteria termcrit, int attempts=1, CvRNG* rng=0, int flags=0, CvArr* _centers=0, double* compactness=0 )
 

modules/core/doc/drawing_functions.rst

@@ -32,7 +32,7 @@ Draws a circle.
 
 .. ocv:function:: void circle(Mat& img, Point center, int radius, const Scalar& color, int thickness=1, int lineType=8, int shift=0)
 
-.. ocv:pyfunction:: cv2.circle(img, center, radius, color[, thickness[, lineType[, shift]]]) -> None
+.. ocv:pyfunction:: cv2.circle(img, center, radius, color[, thickness[, lineType[, shift]]]) -> img
 
 .. ocv:cfunction:: void cvCircle( CvArr* img, CvPoint center, int radius, CvScalar color, int thickness=1, int line_type=8, int shift=0 )
 
@@ -87,8 +87,9 @@ Draws a simple or thick elliptic arc or fills an ellipse sector.
 
 .. ocv:function:: void ellipse(Mat& img, const RotatedRect& box, const Scalar& color, int thickness=1, int lineType=8)
 
-.. ocv:pyfunction:: cv2.ellipse(img, center, axes, angle, startAngle, endAngle, color[, thickness[, lineType[, shift]]]) -> None
-.. ocv:pyfunction:: cv2.ellipse(img, box, color[, thickness[, lineType]]) -> None
+.. ocv:pyfunction:: cv2.ellipse(img, center, axes, angle, startAngle, endAngle, color[, thickness[, lineType[, shift]]]) -> img
+
+.. ocv:pyfunction:: cv2.ellipse(img, box, color[, thickness[, lineType]]) -> img
 
 .. ocv:cfunction:: void cvEllipse( CvArr* img, CvPoint center, CvSize axes, double angle, double start_angle, double end_angle, CvScalar color, int thickness=1, int line_type=8, int shift=0 )
 
@@ -163,7 +164,7 @@ Fills a convex polygon.
 
 .. ocv:function:: void fillConvexPoly(Mat& img, const Point* pts, int npts, const Scalar& color, int lineType=8, int shift=0)
 
-.. ocv:pyfunction:: cv2.fillConvexPoly(img, points, color[, lineType[, shift]]) -> None
+.. ocv:pyfunction:: cv2.fillConvexPoly(img, points, color[, lineType[, shift]]) -> img
 
 .. ocv:cfunction:: void cvFillConvexPoly( CvArr* img, const CvPoint* pts, int npts, CvScalar color, int line_type=8, int shift=0 )
 
@@ -193,7 +194,7 @@ Fills the area bounded by one or more polygons.
 
 .. ocv:function:: void fillPoly(Mat& img, const Point** pts,               const int* npts, int ncontours,              const Scalar& color, int lineType=8,              int shift=0, Point offset=Point() )
 
-.. ocv:pyfunction:: cv2.fillPoly(img, pts, color[, lineType[, shift[, offset]]]) -> None
+.. ocv:pyfunction:: cv2.fillPoly(img, pts, color[, lineType[, shift[, offset]]]) -> img
 
 .. ocv:cfunction:: void cvFillPoly( CvArr* img, CvPoint** pts, const int* npts, int contours, CvScalar color, int line_type=8, int shift=0 )
 
@@ -331,7 +332,7 @@ Draws a line segment connecting two points.
 
 .. ocv:function:: void line(Mat& img, Point pt1, Point pt2, const Scalar& color,          int thickness=1, int lineType=8, int shift=0)
 
-.. ocv:pyfunction:: cv2.line(img, pt1, pt2, color[, thickness[, lineType[, shift]]]) -> None
+.. ocv:pyfunction:: cv2.line(img, pt1, pt2, color[, thickness[, lineType[, shift]]]) -> img
 
 .. ocv:cfunction:: void cvLine( CvArr* img, CvPoint pt1, CvPoint pt2, CvScalar color, int thickness=1, int line_type=8, int shift=0 )
 
@@ -421,7 +422,7 @@ Draws a simple, thick, or filled up-right rectangle.
 
 .. ocv:function:: void rectangle( Mat& img, Rect rec, const Scalar& color, int thickness=1, int lineType=8, int shift=0 )
 
-.. ocv:pyfunction:: cv2.rectangle(img, pt1, pt2, color[, thickness[, lineType[, shift]]]) -> None
+.. ocv:pyfunction:: cv2.rectangle(img, pt1, pt2, color[, thickness[, lineType[, shift]]]) -> img
 
 .. ocv:cfunction:: void cvRectangle( CvArr* img, CvPoint pt1, CvPoint pt2, CvScalar color, int thickness=1, int line_type=8, int shift=0 )
 
@@ -455,7 +456,7 @@ Draws several polygonal curves.
 
 .. ocv:function:: void polylines( InputOutputArray img, InputArrayOfArrays pts, bool isClosed, const Scalar& color, int thickness=1, int lineType=8, int shift=0 )
 
-.. ocv:pyfunction:: cv2.polylines(img, pts, isClosed, color[, thickness[, lineType[, shift]]]) -> None
+.. ocv:pyfunction:: cv2.polylines(img, pts, isClosed, color[, thickness[, lineType[, shift]]]) -> img
 
 .. ocv:cfunction:: void cvPolyLine( CvArr* img, CvPoint** pts, const int* npts, int contours, int is_closed, CvScalar color, int thickness=1, int line_type=8, int shift=0 )
 
@@ -488,7 +489,7 @@ Draws contours outlines or filled contours.
 
 .. ocv:function:: void drawContours( InputOutputArray image, InputArrayOfArrays contours, int contourIdx, const Scalar& color, int thickness=1, int lineType=8, InputArray hierarchy=noArray(), int maxLevel=INT_MAX, Point offset=Point() )
 
-.. ocv:pyfunction:: cv2.drawContours(image, contours, contourIdx, color[, thickness[, lineType[, hierarchy[, maxLevel[, offset]]]]]) -> None
+.. ocv:pyfunction:: cv2.drawContours(image, contours, contourIdx, color[, thickness[, lineType[, hierarchy[, maxLevel[, offset]]]]]) -> image
 
 .. ocv:cfunction:: void cvDrawContours( CvArr * img, CvSeq* contour, CvScalar external_color, CvScalar hole_color, int max_level, int thickness=1, int line_type=8, CvPoint offset=cvPoint(0,0) )
 

modules/core/doc/operations_on_arrays.rst

@@ -592,7 +592,7 @@ Copies the lower or the upper half of a square matrix to another half.
 
 .. ocv:function:: void completeSymm(InputOutputArray mtx, bool lowerToUpper=false)
 
-.. ocv:pyfunction:: cv2.completeSymm(mtx[, lowerToUpper]) -> None
+.. ocv:pyfunction:: cv2.completeSymm(mtx[, lowerToUpper]) -> mtx
 
     :param mtx: input-output floating-point square matrix.
 
@@ -2299,7 +2299,9 @@ Performs Principal Component Analysis of the supplied dataset.
 
 .. ocv:function:: PCA& PCA::operator()(InputArray data, InputArray mean, int flags, double retainedVariance)
 
-.. ocv:pyfunction:: cv2.PCACompute(data[, mean[, eigenvectors[, maxComponents]]]) -> mean, eigenvectors
+.. ocv:pyfunction:: cv2.PCACompute(data, mean[, eigenvectors[, maxComponents]]) -> mean, eigenvectors
+
+.. ocv:pyfunction:: cv2.PCACompute(data, mean, retainedVariance[, eigenvectors]) -> mean, eigenvectors
 
     :param data: input samples stored as the matrix rows or as the matrix columns.
 
@@ -2670,7 +2672,7 @@ Generates a single uniformly-distributed random number or an array of random num
 
 .. ocv:function:: void randu( InputOutputArray dst, InputArray low, InputArray high )
 
-.. ocv:pyfunction:: cv2.randu(dst, low, high) -> None
+.. ocv:pyfunction:: cv2.randu(dst, low, high) -> dst
 
     :param dst: output array of random numbers; the array must be pre-allocated.
 
@@ -2701,7 +2703,7 @@ Fills the array with normally distributed random numbers.
 
 .. ocv:function:: void randn( InputOutputArray dst, InputArray mean, InputArray stddev )
 
-.. ocv:pyfunction:: cv2.randn(dst, mean, stddev) -> None
+.. ocv:pyfunction:: cv2.randn(dst, mean, stddev) -> dst
 
     :param dst: output array of random numbers; the array must be pre-allocated and have 1 to 4 channels.
 
@@ -2724,7 +2726,7 @@ Shuffles the array elements randomly.
 
 .. ocv:function:: void randShuffle( InputOutputArray dst, double iterFactor=1., RNG* rng=0 )
 
-.. ocv:pyfunction:: cv2.randShuffle(dst[, iterFactor]) -> None
+.. ocv:pyfunction:: cv2.randShuffle(dst[, iterFactor]) -> dst
 
     :param dst: input/output numerical 1D array.
 
@@ -2864,7 +2866,7 @@ Initializes a scaled identity matrix.
 
 .. ocv:function:: void setIdentity( InputOutputArray mtx, const Scalar& s=Scalar(1) )
 
-.. ocv:pyfunction:: cv2.setIdentity(mtx[, s]) -> None
+.. ocv:pyfunction:: cv2.setIdentity(mtx[, s]) -> mtx
 
 .. ocv:cfunction:: void cvSetIdentity(CvArr* mat, CvScalar value=cvRealScalar(1))
 

modules/core/include/opencv2/core.hpp

@@ -46,6 +46,8 @@
 #ifndef __OPENCV_CORE_HPP__
 #define __OPENCV_CORE_HPP__
 
+#include "opencv2/core/cvdef.h"
+
 #include "opencv2/core/types_c.h"
 #include "opencv2/core/version.hpp"
 
@@ -69,11 +71,6 @@
 */
 namespace cv {
 
-#undef abs
-#undef min
-#undef max
-#undef Complex
-
 template<typename _Tp> class CV_EXPORTS Size_;
 template<typename _Tp> class CV_EXPORTS Point_;
 template<typename _Tp> class CV_EXPORTS Rect_;
@@ -2426,10 +2423,10 @@ public:
     Mat mean; //!< mean value subtracted before the projection and added after the back projection
 };
 
-CV_EXPORTS_W void PCACompute(InputArray data, CV_OUT InputOutputArray mean,
+CV_EXPORTS_W void PCACompute(InputArray data, InputOutputArray mean,
                              OutputArray eigenvectors, int maxComponents=0);
 
-CV_EXPORTS_W void PCACompute(InputArray data, CV_OUT InputOutputArray mean,
+CV_EXPORTS_W void PCACompute(InputArray data, InputOutputArray mean,
                              OutputArray eigenvectors, double retainedVariance);
 
 CV_EXPORTS_W void PCAProject(InputArray data, InputArray mean,
@@ -2489,12 +2486,11 @@ public:
 };
 
 //! computes SVD of src
-CV_EXPORTS_W void SVDecomp( InputArray src, CV_OUT OutputArray w,
-    CV_OUT OutputArray u, CV_OUT OutputArray vt, int flags=0 );
+CV_EXPORTS_W void SVDecomp( InputArray src, OutputArray w, OutputArray u, OutputArray vt, int flags=0 );
 
 //! performs back substitution for the previously computed SVD
 CV_EXPORTS_W void SVBackSubst( InputArray w, InputArray u, InputArray vt,
-                               InputArray rhs, CV_OUT OutputArray dst );
+                               InputArray rhs, OutputArray dst );
 
 //! computes Mahalanobis distance between two vectors: sqrt((v1-v2)'*icovar*(v1-v2)), where icovar is the inverse covariation matrix
 CV_EXPORTS_W double Mahalanobis(InputArray v1, InputArray v2, InputArray icovar);
@@ -2525,7 +2521,7 @@ enum
     KMEANS_USE_INITIAL_LABELS=1 // Uses the user-provided labels for K-Means initialization
 };
 //! clusters the input data using k-Means algorithm
-CV_EXPORTS_W double kmeans( InputArray data, int K, CV_OUT InputOutputArray bestLabels,
+CV_EXPORTS_W double kmeans( InputArray data, int K, InputOutputArray bestLabels,
                             TermCriteria criteria, int attempts,
                             int flags, OutputArray centers=noArray() );
 

modules/core/include/opencv2/core/operations.hpp

@@ -51,40 +51,6 @@
 
 #ifdef __cplusplus
 
-/////// exchange-add operation for atomic operations on reference counters ///////
-#if defined __INTEL_COMPILER && !(defined WIN32 || defined _WIN32)
-    // atomic increment on the linux version of the Intel(tm) compiler
-    #define CV_XADD(addr, delta) (int)_InterlockedExchangeAdd(const_cast<void*>(reinterpret_cast<volatile void*>(addr)), delta)
-#elif defined __GNUC__
-  #if defined __clang__ && __clang_major__ >= 3 && !defined __ANDROID__
-    #ifdef __ATOMIC_ACQ_REL
-        #define CV_XADD(addr, delta) __c11_atomic_fetch_add((_Atomic(int)*)(addr), delta, __ATOMIC_ACQ_REL)
-    #else
-        #define CV_XADD(addr, delta) __atomic_fetch_add((_Atomic(int)*)(addr), delta, 4)
-    #endif
-  #else
-    #ifdef __ATOMIC_ACQ_REL
-        // version for gcc >= 4.7
-        #define CV_XADD(addr, delta) __atomic_fetch_add(addr, delta, __ATOMIC_ACQ_REL)
-    #else
-        #define CV_XADD(addr, delta) __sync_fetch_and_add(addr, delta)
-    #endif
-  #endif
-#elif (defined WIN32 || defined _WIN32 || defined WINCE) && (!defined RC_INVOKED)
-    #if !defined(_M_AMD64) && !defined(_M_IA64) && !defined(_M_ARM)
-        extern "C" __declspec(dllimport) long __stdcall InterlockedExchangeAdd(long volatile *Addend, long Value);
-        #define CV_XADD(addr, delta) (int)InterlockedExchangeAdd((long volatile*)addr, delta)
-    #else
-        extern "C" long _InterlockedExchangeAdd (long volatile *Addend, long Value);
-        #pragma intrinsic(_InterlockedExchangeAdd)
-        #define CV_XADD(addr, delta) (int)_InterlockedExchangeAdd((long volatile*)addr, delta)
-    #endif
-#else
-  static inline CV_XADD(int* addr, int delta) { int tmp = *addr; *addr += delta; return tmp; }
-#endif
-
-
-
 #include <limits>
 
 #ifdef _MSC_VER

modules/core/include/opencv2/core/types_c.h

@@ -43,57 +43,6 @@
 #ifndef __OPENCV_CORE_TYPES_H__
 #define __OPENCV_CORE_TYPES_H__
 
-#if !defined _CRT_SECURE_NO_DEPRECATE && defined _MSC_VER
-#  if _MSC_VER > 1300
-#    define _CRT_SECURE_NO_DEPRECATE /* to avoid multiple Visual Studio 2005 warnings */
-#  endif
-#endif
-
-
-#ifndef SKIP_INCLUDES
-
-#include <assert.h>
-#include <stdlib.h>
-#include <string.h>
-#include <float.h>
-
-#if !defined _MSC_VER && !defined __BORLANDC__
-#  include <stdint.h>
-#endif
-
-#if defined __ICL
-#  define CV_ICC   __ICL
-#elif defined __ICC
-#  define CV_ICC   __ICC
-#elif defined __ECL
-#  define CV_ICC   __ECL
-#elif defined __ECC
-#  define CV_ICC   __ECC
-#elif defined __INTEL_COMPILER
-#  define CV_ICC   __INTEL_COMPILER
-#endif
-
-#if defined CV_ICC && !defined CV_ENABLE_UNROLLED
-#  define CV_ENABLE_UNROLLED 0
-#else
-#  define CV_ENABLE_UNROLLED 1
-#endif
-
-#if (defined _M_X64 && defined _MSC_VER && _MSC_VER >= 1400) || (__GNUC__ >= 4 && defined __x86_64__)
-#  if defined WIN32
-#    include <intrin.h>
-#  endif
-#  if defined __SSE2__ || !defined __GNUC__
-#    include <emmintrin.h>
-#  endif
-#endif
-
-#if defined __BORLANDC__
-#  include <fastmath.h>
-#else
-#  include <math.h>
-#endif
-
 #ifdef HAVE_IPL
 #  ifndef __IPL_H__
 #    if defined WIN32 || defined _WIN32
@@ -106,6 +55,13 @@
 #  define HAVE_IPL
 #endif
 
+#include "opencv2/core/cvdef.h"
+
+#ifndef SKIP_INCLUDES
+#include <assert.h>
+#include <stdlib.h>
+#include <string.h>
+#include <float.h>
 #endif // SKIP_INCLUDES
 
 #if defined WIN32 || defined _WIN32
@@ -116,12 +72,10 @@
 #  define CV_STDCALL
 #endif
 
-#ifndef CV_EXTERN_C
+#ifndef CV_DEFAULT
 #  ifdef __cplusplus
-#    define CV_EXTERN_C extern "C"
 #    define CV_DEFAULT(val) = val
 #  else
-#    define CV_EXTERN_C
 #    define CV_DEFAULT(val)
 #  endif
 #endif
@@ -134,60 +88,10 @@
 #  endif
 #endif
 
-#ifndef CV_INLINE
-#  if defined __cplusplus
-#    define CV_INLINE inline
-#  elif (defined WIN32 || defined _WIN32 || defined WINCE) && !defined __GNUC__
-#    define CV_INLINE __inline
-#  else
-#    define CV_INLINE static
-#  endif
-#endif /* CV_INLINE */
-
-#if (defined WIN32 || defined _WIN32 || defined WINCE) && defined CVAPI_EXPORTS
-#  define CV_EXPORTS __declspec(dllexport)
-#else
-#  define CV_EXPORTS
-#endif
-
 #ifndef CVAPI
 #  define CVAPI(rettype) CV_EXTERN_C CV_EXPORTS rettype CV_CDECL
 #endif
 
-#if defined _MSC_VER || defined __BORLANDC__
-   typedef __int64 int64;
-   typedef unsigned __int64 uint64;
-#  define CV_BIG_INT(n)   n##I64
-#  define CV_BIG_UINT(n)  n##UI64
-#else
-   typedef int64_t int64;
-   typedef uint64_t uint64;
-#  define CV_BIG_INT(n)   n##LL
-#  define CV_BIG_UINT(n)  n##ULL
-#endif
-
-#ifndef HAVE_IPL
-   typedef unsigned char uchar;
-   typedef unsigned short ushort;
-#endif
-
-typedef signed char schar;
-
-/* special informative macros for wrapper generators */
-#define CV_CARRAY(counter)
-#define CV_CUSTOM_CARRAY(args)
-#define CV_EXPORTS_W CV_EXPORTS
-#define CV_EXPORTS_W_SIMPLE CV_EXPORTS
-#define CV_EXPORTS_AS(synonym) CV_EXPORTS
-#define CV_EXPORTS_W_MAP CV_EXPORTS
-#define CV_IN_OUT
-#define CV_OUT
-#define CV_PROP
-#define CV_PROP_RW
-#define CV_WRAP
-#define CV_WRAP_AS(synonym)
-#define CV_WRAP_DEFAULT(value)
-
 /* CvArr* is used to pass arbitrary
  * array-like data structures
  * into functions where the particular
@@ -271,13 +175,6 @@ enum {
 *                             Common macros and inline functions                         *
 \****************************************************************************************/
 
-#ifdef HAVE_TEGRA_OPTIMIZATION
-#  include "tegra_round.hpp"
-#endif
-
-#define CV_PI   3.1415926535897932384626433832795
-#define CV_LOG2 0.69314718055994530941723212145818
-
 #define CV_SWAP(a,b,t) ((t) = (a), (a) = (b), (b) = (t))
 
 #ifndef MIN
@@ -302,88 +199,9 @@ enum {
 #define  CV_CMP(a,b)    (((a) > (b)) - ((a) < (b)))
 #define  CV_SIGN(a)     CV_CMP((a),0)
 
-CV_INLINE  int  cvRound( double value )
-{
-#if (defined _MSC_VER && defined _M_X64) || (defined __GNUC__ && defined __x86_64__ && defined __SSE2__ && !defined __APPLE__)
-    __m128d t = _mm_set_sd( value );
-    return _mm_cvtsd_si32(t);
-#elif defined _MSC_VER && defined _M_IX86
-    int t;
-    __asm
-    {
-        fld value;
-        fistp t;
-    }
-    return t;
-#elif defined HAVE_LRINT || defined CV_ICC || defined __GNUC__
-#  ifdef HAVE_TEGRA_OPTIMIZATION
-    TEGRA_ROUND(value);
-#  else
-    return (int)lrint(value);
-#  endif
-#else
-    // while this is not IEEE754-compliant rounding, it's usually a good enough approximation
-    return (int)(value + (value >= 0 ? 0.5 : -0.5));
-#endif
-}
-
-#if defined __SSE2__ || (defined _M_IX86_FP && 2 == _M_IX86_FP)
-#  include "emmintrin.h"
-#endif
-
-CV_INLINE  int  cvFloor( double value )
-{
-#if defined _MSC_VER && defined _M_X64 || (defined __GNUC__ && defined __SSE2__ && !defined __APPLE__)
-    __m128d t = _mm_set_sd( value );
-    int i = _mm_cvtsd_si32(t);
-    return i - _mm_movemask_pd(_mm_cmplt_sd(t, _mm_cvtsi32_sd(t,i)));
-#elif defined __GNUC__
-    int i = (int)value;
-    return i - (i > value);
-#else
-    int i = cvRound(value);
-    float diff = (float)(value - i);
-    return i - (diff < 0);
-#endif
-}
-
-
-CV_INLINE  int  cvCeil( double value )
-{
-#if defined _MSC_VER && defined _M_X64 || (defined __GNUC__ && defined __SSE2__&& !defined __APPLE__)
-    __m128d t = _mm_set_sd( value );
-    int i = _mm_cvtsd_si32(t);
-    return i + _mm_movemask_pd(_mm_cmplt_sd(_mm_cvtsi32_sd(t,i), t));
-#elif defined __GNUC__
-    int i = (int)value;
-    return i + (i < value);
-#else
-    int i = cvRound(value);
-    float diff = (float)(i - value);
-    return i + (diff < 0);
-#endif
-}
-
 #define cvInvSqrt(value) ((float)(1./sqrt(value)))
 #define cvSqrt(value)  ((float)sqrt(value))
 
-CV_INLINE int cvIsNaN( double value )
-{
-    Cv64suf ieee754;
-    ieee754.f = value;
-    return ((unsigned)(ieee754.u >> 32) & 0x7fffffff) +
-           ((unsigned)ieee754.u != 0) > 0x7ff00000;
-}
-
-
-CV_INLINE int cvIsInf( double value )
-{
-    Cv64suf ieee754;
-    ieee754.f = value;
-    return ((unsigned)(ieee754.u >> 32) & 0x7fffffff) == 0x7ff00000 &&
-           (unsigned)ieee754.u == 0;
-}
-
 
 /*************** Random number generation *******************/
 
@@ -553,82 +371,9 @@ IplConvKernelFP;
 *                                  Matrix type (CvMat)                                   *
 \****************************************************************************************/
 
-#define CV_CN_MAX     512
-#define CV_CN_SHIFT   3
-#define CV_DEPTH_MAX  (1 << CV_CN_SHIFT)
-
-#define CV_8U   0
-#define CV_8S   1
-#define CV_16U  2
-#define CV_16S  3
-#define CV_32S  4
-#define CV_32F  5
-#define CV_64F  6
-#define CV_USRTYPE1 7
-
-#define CV_MAT_DEPTH_MASK       (CV_DEPTH_MAX - 1)
-#define CV_MAT_DEPTH(flags)     ((flags) & CV_MAT_DEPTH_MASK)
-
-#define CV_MAKETYPE(depth,cn) (CV_MAT_DEPTH(depth) + (((cn)-1) << CV_CN_SHIFT))
-#define CV_MAKE_TYPE CV_MAKETYPE
-
-#define CV_8UC1 CV_MAKETYPE(CV_8U,1)
-#define CV_8UC2 CV_MAKETYPE(CV_8U,2)
-#define CV_8UC3 CV_MAKETYPE(CV_8U,3)
-#define CV_8UC4 CV_MAKETYPE(CV_8U,4)
-#define CV_8UC(n) CV_MAKETYPE(CV_8U,(n))
-
-#define CV_8SC1 CV_MAKETYPE(CV_8S,1)
-#define CV_8SC2 CV_MAKETYPE(CV_8S,2)
-#define CV_8SC3 CV_MAKETYPE(CV_8S,3)
-#define CV_8SC4 CV_MAKETYPE(CV_8S,4)
-#define CV_8SC(n) CV_MAKETYPE(CV_8S,(n))
-
-#define CV_16UC1 CV_MAKETYPE(CV_16U,1)
-#define CV_16UC2 CV_MAKETYPE(CV_16U,2)
-#define CV_16UC3 CV_MAKETYPE(CV_16U,3)
-#define CV_16UC4 CV_MAKETYPE(CV_16U,4)
-#define CV_16UC(n) CV_MAKETYPE(CV_16U,(n))
-
-#define CV_16SC1 CV_MAKETYPE(CV_16S,1)
-#define CV_16SC2 CV_MAKETYPE(CV_16S,2)
-#define CV_16SC3 CV_MAKETYPE(CV_16S,3)
-#define CV_16SC4 CV_MAKETYPE(CV_16S,4)
-#define CV_16SC(n) CV_MAKETYPE(CV_16S,(n))
-
-#define CV_32SC1 CV_MAKETYPE(CV_32S,1)
-#define CV_32SC2 CV_MAKETYPE(CV_32S,2)
-#define CV_32SC3 CV_MAKETYPE(CV_32S,3)
-#define CV_32SC4 CV_MAKETYPE(CV_32S,4)
-#define CV_32SC(n) CV_MAKETYPE(CV_32S,(n))
-
-#define CV_32FC1 CV_MAKETYPE(CV_32F,1)
-#define CV_32FC2 CV_MAKETYPE(CV_32F,2)
-#define CV_32FC3 CV_MAKETYPE(CV_32F,3)
-#define CV_32FC4 CV_MAKETYPE(CV_32F,4)
-#define CV_32FC(n) CV_MAKETYPE(CV_32F,(n))
-
-#define CV_64FC1 CV_MAKETYPE(CV_64F,1)
-#define CV_64FC2 CV_MAKETYPE(CV_64F,2)
-#define CV_64FC3 CV_MAKETYPE(CV_64F,3)
-#define CV_64FC4 CV_MAKETYPE(CV_64F,4)
-#define CV_64FC(n) CV_MAKETYPE(CV_64F,(n))
-
 #define CV_AUTO_STEP  0x7fffffff
 #define CV_WHOLE_ARR  cvSlice( 0, 0x3fffffff )
 
-#define CV_MAT_CN_MASK          ((CV_CN_MAX - 1) << CV_CN_SHIFT)
-#define CV_MAT_CN(flags)        ((((flags) & CV_MAT_CN_MASK) >> CV_CN_SHIFT) + 1)
-#define CV_MAT_TYPE_MASK        (CV_DEPTH_MAX*CV_CN_MAX - 1)
-#define CV_MAT_TYPE(flags)      ((flags) & CV_MAT_TYPE_MASK)
-#define CV_MAT_CONT_FLAG_SHIFT  14
-#define CV_MAT_CONT_FLAG        (1 << CV_MAT_CONT_FLAG_SHIFT)
-#define CV_IS_MAT_CONT(flags)   ((flags) & CV_MAT_CONT_FLAG)
-#define CV_IS_CONT_MAT          CV_IS_MAT_CONT
-#define CV_SUBMAT_FLAG_SHIFT    15
-#define CV_SUBMAT_FLAG          (1 << CV_SUBMAT_FLAG_SHIFT)
-#define CV_IS_SUBMAT(flags)     ((flags) & CV_MAT_SUBMAT_FLAG)
-
 #define CV_MAGIC_MASK       0xFFFF0000
 #define CV_MAT_MAGIC_VAL    0x42420000
 #define CV_TYPE_NAME_MAT    "opencv-matrix"
@@ -703,15 +448,6 @@ CvMat;
 #define CV_IS_MAT_CONST(mat)  \
     (((mat)->rows|(mat)->cols) == 1)
 
-/* Size of each channel item,
-   0x124489 = 1000 0100 0100 0010 0010 0001 0001 ~ array of sizeof(arr_type_elem) */
-#define CV_ELEM_SIZE1(type) \
-    ((((sizeof(size_t)<<28)|0x8442211) >> CV_MAT_DEPTH(type)*4) & 15)
-
-/* 0x3a50 = 11 10 10 01 01 00 00 ~ array of log2(sizeof(arr_type_elem)) */
-#define CV_ELEM_SIZE(type) \
-    (CV_MAT_CN(type) << ((((sizeof(size_t)/4+1)*16384|0x3a50) >> CV_MAT_DEPTH(type)*2) & 3))
-
 #define IPL2CV_DEPTH(depth) \
     ((((CV_8U)+(CV_16U<<4)+(CV_32F<<8)+(CV_64F<<16)+(CV_8S<<20)+ \
     (CV_16S<<24)+(CV_32S<<28)) >> ((((depth) & 0xF0) >> 2) + \

modules/imgproc/doc/feature_detection.rst

@@ -162,7 +162,7 @@ Refines the corner locations.
 
 .. ocv:function:: void cornerSubPix( InputArray image, InputOutputArray corners, Size winSize, Size zeroZone, TermCriteria criteria )
 
-.. ocv:pyfunction:: cv2.cornerSubPix(image, corners, winSize, zeroZone, criteria) -> None
+.. ocv:pyfunction:: cv2.cornerSubPix(image, corners, winSize, zeroZone, criteria) -> corners
 
 .. ocv:cfunction:: void cvFindCornerSubPix( const CvArr* image, CvPoint2D32f* corners, int count, CvSize win, CvSize zero_zone, CvTermCriteria criteria )
 

modules/imgproc/doc/miscellaneous_transformations.rst

@@ -488,7 +488,7 @@ Fills a connected component with the given color.
 
 .. ocv:function:: int floodFill( InputOutputArray image, InputOutputArray mask, Point seedPoint, Scalar newVal, Rect* rect=0, Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), int flags=4 )
 
-.. ocv:pyfunction:: cv2.floodFill(image, mask, seedPoint, newVal[, loDiff[, upDiff[, flags]]]) -> retval, rect
+.. ocv:pyfunction:: cv2.floodFill(image, mask, seedPoint, newVal[, loDiff[, upDiff[, flags]]]) -> retval, image, mask, rect
 
 .. ocv:cfunction:: void cvFloodFill( CvArr* image, CvPoint seed_point, CvScalar new_val, CvScalar lo_diff=cvScalarAll(0), CvScalar up_diff=cvScalarAll(0), CvConnectedComp* comp=NULL, int flags=4, CvArr* mask=NULL )
 .. ocv:pyoldfunction:: cv.FloodFill(image, seed_point, new_val, lo_diff=(0, 0, 0, 0), up_diff=(0, 0, 0, 0), flags=4, mask=None)-> comp
@@ -731,7 +731,7 @@ Performs a marker-based image segmentation using the watershed algorithm.
 
 .. ocv:cfunction:: void cvWatershed( const CvArr* image, CvArr* markers )
 
-.. ocv:pyfunction:: cv2.watershed(image, markers) -> None
+.. ocv:pyfunction:: cv2.watershed(image, markers) -> markers
 
     :param image: Input 8-bit 3-channel image.
 
@@ -753,7 +753,7 @@ Runs the GrabCut algorithm.
 
 .. ocv:function:: void grabCut( InputArray img, InputOutputArray mask, Rect rect, InputOutputArray bgdModel, InputOutputArray fgdModel, int iterCount, int mode=GC_EVAL )
 
-.. ocv:pyfunction:: cv2.grabCut(img, mask, rect, bgdModel, fgdModel, iterCount[, mode]) -> None
+.. ocv:pyfunction:: cv2.grabCut(img, mask, rect, bgdModel, fgdModel, iterCount[, mode]) -> mask, bgdModel, fgdModel
 
     :param img: Input 8-bit 3-channel image.
 

modules/imgproc/doc/motion_analysis_and_object_tracking.rst

@@ -9,7 +9,7 @@ Adds an image to the accumulator.
 
 .. ocv:function:: void accumulate( InputArray src, InputOutputArray dst, InputArray mask=noArray() )
 
-.. ocv:pyfunction:: cv2.accumulate(src, dst[, mask]) -> None
+.. ocv:pyfunction:: cv2.accumulate(src, dst[, mask]) -> dst
 
 .. ocv:cfunction:: void cvAcc( const CvArr* image, CvArr* sum, const CvArr* mask=NULL )
 
@@ -45,7 +45,7 @@ Adds the square of a source image to the accumulator.
 
 .. ocv:function:: void accumulateSquare( InputArray src, InputOutputArray dst,  InputArray mask=noArray() )
 
-.. ocv:pyfunction:: cv2.accumulateSquare(src, dst[, mask]) -> None
+.. ocv:pyfunction:: cv2.accumulateSquare(src, dst[, mask]) -> dst
 
 .. ocv:cfunction:: void cvSquareAcc( const CvArr* image, CvArr* sqsum, const CvArr* mask=NULL )
 
@@ -79,7 +79,7 @@ Adds the per-element product of two input images to the accumulator.
 
 .. ocv:function:: void accumulateProduct( InputArray src1, InputArray src2, InputOutputArray dst, InputArray mask=noArray() )
 
-.. ocv:pyfunction:: cv2.accumulateProduct(src1, src2, dst[, mask]) -> None
+.. ocv:pyfunction:: cv2.accumulateProduct(src1, src2, dst[, mask]) -> dst
 
 .. ocv:cfunction:: void cvMultiplyAcc( const CvArr* image1, const CvArr* image2, CvArr* acc, const CvArr* mask=NULL )
 
@@ -115,7 +115,7 @@ Updates a running average.
 
 .. ocv:function:: void accumulateWeighted( InputArray src, InputOutputArray dst, double alpha, InputArray mask=noArray() )
 
-.. ocv:pyfunction:: cv2.accumulateWeighted(src, dst, alpha[, mask]) -> None
+.. ocv:pyfunction:: cv2.accumulateWeighted(src, dst, alpha[, mask]) -> dst
 
 .. ocv:cfunction:: void cvRunningAvg( const CvArr* image, CvArr* acc, double alpha, const CvArr* mask=NULL )
 .. ocv:pyoldfunction:: cv.RunningAvg(image, acc, alpha, mask=None)-> None

modules/imgproc/doc/structural_analysis_and_shape_descriptors.rst

@@ -159,7 +159,7 @@ Finds contours in a binary image.
 
 .. ocv:function:: void findContours( InputOutputArray image, OutputArrayOfArrays contours, int mode, int method, Point offset=Point())
 
-.. ocv:pyfunction:: cv2.findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> contours, hierarchy
+.. ocv:pyfunction:: cv2.findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> image, contours, hierarchy
 
 .. ocv:cfunction:: int cvFindContours( CvArr* image, CvMemStorage* storage, CvSeq** first_contour, int header_size=sizeof(CvContour), int mode=CV_RETR_LIST, int method=CV_CHAIN_APPROX_SIMPLE, CvPoint offset=cvPoint(0,0) )
 

modules/imgproc/include/opencv2/imgproc.hpp

@@ -1103,7 +1103,7 @@ CV_EXPORTS_W Moments moments( InputArray array, bool binaryImage=false );
 
 //! computes 7 Hu invariants from the moments
 CV_EXPORTS void HuMoments( const Moments& moments, double hu[7] );
-CV_EXPORTS_W void HuMoments( const Moments& m, CV_OUT OutputArray hu );
+CV_EXPORTS_W void HuMoments( const Moments& m, OutputArray hu );
 
 //! type of the template matching operation
 enum { TM_SQDIFF=0, TM_SQDIFF_NORMED=1, TM_CCORR=2, TM_CCORR_NORMED=3, TM_CCOEFF=4, TM_CCOEFF_NORMED=5 };

modules/legacy/src/_vm.h

@@ -68,8 +68,6 @@ CvStatus  icvMakeScanlinesLengths( int*        scanlines,
 
 /*=============================== PreWarp section ======================================*/
 
-CV_INLINE int icvGetColor(uchar* valueRGB);
-
 CvStatus  icvFindRunsInOneImage(
                                 int     numLines,       /* number of scanlines		*/
                                 uchar*  prewarp,        /* prewarp image 			*/

modules/legacy/src/lcm.cpp

@@ -199,7 +199,7 @@ int _cvNodeMultyplicity(CvVoronoiSite2D* pSite,
 //      pLCM : in, information about graph
 //    Returns: pointer to graph node
 //F*/
-CV_IMPL
+CV_INLINE
 CvLCMNode* _cvCreateLCMNode(CvLCM* pLCM);
 
 /*F///////////////////////////////////////////////////////////////////////////////////////
@@ -211,7 +211,7 @@ CvLCMNode* _cvCreateLCMNode(CvLCM* pLCM);
 //      pLCM : in, information about graph
 //    Returns: pointer to graph edge
 //F*/
-CV_IMPL
+CV_INLINE
 CvLCMEdge* _cvCreateLCMEdge(CvLCM* pLCM);
 
 /*F///////////////////////////////////////////////////////////////////////////////////////
@@ -228,7 +228,7 @@ CvLCMEdge* _cvCreateLCMEdge(CvLCM* pLCM);
 //             =1, if node  is terminal for edge
 //    Returns:
 //F*/
-CV_IMPL
+CV_INLINE
 void _cvAttachLCMEdgeToLCMNode(CvLCMNode* LCMNode,
                                CvLCMEdge* LCMEdge,
                                CvLCMEdge* &LCMEdge_prev,
@@ -263,7 +263,7 @@ void _cvProjectionPointToSegment(CvPoint2D32f* PointO,
 //      pLCMCCNData : out
 //    Returns:
 //F*/
-CV_IMPL
+CV_INLINE
 void _cvPrepareData(CvLCMComplexNodeData* pLCMCCNData,
                     CvLCMData* pLCMData);
 

modules/python/src2/gen2.py

@@ -354,6 +354,7 @@ class ArgInfo(object):
             elif m == "/IO":
                 self.inputarg = True
                 self.outputarg = True
+                self.returnarg = True
             elif m.startswith("/A"):
                 self.isarray = True
                 self.arraylen = m[2:].strip()
@@ -427,7 +428,7 @@ class FuncVariant(object):
                 continue
             if a.returnarg:
                 outlist.append((a.name, argno))
-            if (not a.inputarg or a.returnarg) and a.isbig():
+            if (not a.inputarg) and a.isbig():
                 outarr_list.append((a.name, argno))
                 continue
             if not a.inputarg:

modules/python/src2/hdr_parser.py

@@ -400,7 +400,7 @@ class CppHeaderParser(object):
         # note that we do not strip "static" prefix, which does matter;
         # it means class methods, not instance methods
         decl_str = self.batch_replace(decl_str, [("virtual", ""), ("static inline", ""), ("inline", ""),\
-            ("CV_EXPORTS_W", ""), ("CV_EXPORTS", ""), ("CV_CDECL", ""), ("CV_WRAP ", " "), ("static CV_INLINE", ""), ("CV_INLINE", "")]).strip()
+            ("CV_EXPORTS_W", ""), ("CV_EXPORTS", ""), ("CV_CDECL", ""), ("CV_WRAP ", " "), ("CV_INLINE", "")]).strip()
 
         static_method = False
         context = top[0]

modules/softcascade/doc/softcascade_detector.rst

@@ -43,7 +43,7 @@ Implementation of soft (stageless) cascaded detector. ::
         virtual bool load(const FileNode& fileNode);
         virtual void read(const FileNode& fileNode);
         virtual void detect(InputArray image, InputArray rois, std::vector<Detection>& objects) const;
-        virtual void detect(InputArray image, InputArray rois, CV_OUT OutputArray rects, CV_OUT OutputArray confs) const;
+        virtual void detect(InputArray image, InputArray rois, OutputArray rects, OutputArray confs) const;
 
     }
 
@@ -119,7 +119,7 @@ Public interface for of soft (stageless) cascaded detector. ::
     public:
         virtual ~ChannelFeatureBuilder();
 
-        virtual void operator()(InputArray src, CV_OUT OutputArray channels) const = 0;
+        virtual void operator()(InputArray src, OutputArray channels) const = 0;
 
         static cv::Ptr<ChannelFeatureBuilder> create();
     };
@@ -131,7 +131,7 @@ Destructor for ChannelFeatureBuilder.
 
 .. ocv:function:: softcascade::ChannelFeatureBuilder::~ChannelFeatureBuilder()
 
-.. ocv:pyfunction:: cv2.softcascade_ChannelFeatureBuilder_create() -> retval
+.. ocv:pyfunction:: cv2.softcascade_ChannelFeatureBuilder_create(featureType) -> retval
 
 
 softcascade::ChannelFeatureBuilder::operator()

modules/softcascade/include/opencv2/softcascade.hpp

@@ -127,7 +127,7 @@ public:
     virtual ~ChannelFeatureBuilder();
 
     // apply channels to source frame
-    CV_WRAP_AS(compute) virtual void operator()(InputArray src, CV_OUT OutputArray channels, cv::Size channelsSize = cv::Size()) const = 0;
+    CV_WRAP_AS(compute) virtual void operator()(InputArray src, OutputArray channels, cv::Size channelsSize = cv::Size()) const = 0;
 
     CV_WRAP virtual int totalChannels() const = 0;
     virtual cv::AlgorithmInfo* info() const = 0;
@@ -170,7 +170,7 @@ public:
 
     // Param rects is an output array of bounding rectangles for detected objects.
     // Param confs is an output array of confidence for detected objects. i-th bounding rectangle corresponds i-th confidence.
-    CV_WRAP virtual void detect(InputArray image, InputArray rois, CV_OUT OutputArray rects, CV_OUT OutputArray confs) const;
+    CV_WRAP virtual void detect(InputArray image, InputArray rois, OutputArray rects, OutputArray confs) const;
 
 private:
     void detectNoRoi(const Mat& image, std::vector<Detection>& objects) const;

modules/softcascade/src/integral_channel_builder.cpp

@@ -55,7 +55,7 @@ public:
 
     virtual int totalChannels() const {return N_CHANNELS; }
 
-    virtual void operator()(cv::InputArray _frame, CV_OUT cv::OutputArray _integrals, cv::Size channelsSize) const
+    virtual void operator()(cv::InputArray _frame, cv::OutputArray _integrals, cv::Size channelsSize) const
     {
         CV_Assert(_frame.type() == CV_8UC3);
 

modules/video/doc/motion_analysis_and_object_tracking.rst

@@ -10,7 +10,7 @@ Calculates an optical flow for a sparse feature set using the iterative Lucas-Ka
 
 .. ocv:function:: void calcOpticalFlowPyrLK( InputArray prevImg, InputArray nextImg, InputArray prevPts, InputOutputArray nextPts, OutputArray status, OutputArray err, Size winSize=Size(21,21), int maxLevel=3, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01), int flags=0, double minEigThreshold=1e-4 )
 
-.. ocv:pyfunction:: cv2.calcOpticalFlowPyrLK(prevImg, nextImg, prevPts[, nextPts[, status[, err[, winSize[, maxLevel[, criteria[, flags[, minEigThreshold]]]]]]]]) -> nextPts, status, err
+.. ocv:pyfunction:: cv2.calcOpticalFlowPyrLK(prevImg, nextImg, prevPts, nextPts[, status[, err[, winSize[, maxLevel[, criteria[, flags[, minEigThreshold]]]]]]]) -> nextPts, status, err
 
 .. ocv:cfunction:: void cvCalcOpticalFlowPyrLK( const CvArr* prev, const CvArr* curr, CvArr* prev_pyr, CvArr* curr_pyr, const CvPoint2D32f* prev_features, CvPoint2D32f* curr_features, int count, CvSize win_size, int level, char* status, float* track_error, CvTermCriteria criteria, int flags )
 .. ocv:pyoldfunction:: cv.CalcOpticalFlowPyrLK(prev, curr, prevPyr, currPyr, prevFeatures, winSize, level, criteria, flags, guesses=None) -> (currFeatures, status, track_error)
@@ -77,7 +77,7 @@ Computes a dense optical flow using the Gunnar Farneback's algorithm.
 
 .. ocv:cfunction:: void cvCalcOpticalFlowFarneback( const CvArr* prev, const CvArr* next, CvArr* flow, double pyr_scale, int levels, int winsize, int iterations, int poly_n, double poly_sigma, int flags )
 
-.. ocv:pyfunction:: cv2.calcOpticalFlowFarneback(prev, next, pyr_scale, levels, winsize, iterations, poly_n, poly_sigma, flags[, flow]) -> flow
+.. ocv:pyfunction:: cv2.calcOpticalFlowFarneback(prev, next, flow, pyr_scale, levels, winsize, iterations, poly_n, poly_sigma, flags) -> flow
 
     :param prev: first 8-bit single-channel input image.
 
@@ -204,7 +204,7 @@ Updates the motion history image by a moving silhouette.
 
 .. ocv:function:: void updateMotionHistory( InputArray silhouette, InputOutputArray mhi, double timestamp, double duration )
 
-.. ocv:pyfunction:: cv2.updateMotionHistory(silhouette, mhi, timestamp, duration) -> None
+.. ocv:pyfunction:: cv2.updateMotionHistory(silhouette, mhi, timestamp, duration) -> mhi
 
 .. ocv:cfunction:: void cvUpdateMotionHistory( const CvArr* silhouette, CvArr* mhi, double timestamp, double duration )
 .. ocv:pyoldfunction:: cv.UpdateMotionHistory(silhouette, mhi, timestamp, duration)-> None

modules/video/include/opencv2/video/tracking.hpp

@@ -325,7 +325,7 @@ CV_EXPORTS_W int buildOpticalFlowPyramid(InputArray img, OutputArrayOfArrays pyr
 
 //! computes sparse optical flow using multi-scale Lucas-Kanade algorithm
 CV_EXPORTS_W void calcOpticalFlowPyrLK( InputArray prevImg, InputArray nextImg,
-                           InputArray prevPts, CV_OUT InputOutputArray nextPts,
+                           InputArray prevPts, InputOutputArray nextPts,
                            OutputArray status, OutputArray err,
                            Size winSize=Size(21,21), int maxLevel=3,
                            TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01),
@@ -333,7 +333,7 @@ CV_EXPORTS_W void calcOpticalFlowPyrLK( InputArray prevImg, InputArray nextImg,
 
 //! computes dense optical flow using Farneback algorithm
 CV_EXPORTS_W void calcOpticalFlowFarneback( InputArray prev, InputArray next,
-                           CV_OUT InputOutputArray flow, double pyr_scale, int levels, int winsize,
+                           InputOutputArray flow, double pyr_scale, int levels, int winsize,
                            int iterations, int poly_n, double poly_sigma, int flags );
 
 //! estimates the best-fit Euqcidean, similarity, affine or perspective transformation

modules/video/src/bgfg_gaussmix2.cpp

@@ -187,7 +187,7 @@ struct GMM
 // shadow detection performed per pixel
 // should work for rgb data, could be usefull for gray scale and depth data as well
 // See: Prati,Mikic,Trivedi,Cucchiarra,"Detecting Moving Shadows...",IEEE PAMI,2003.
-static CV_INLINE bool
+CV_INLINE bool
 detectShadowGMM(const float* data, int nchannels, int nmodes,
                 const GMM* gmm, const float* mean,
                 float Tb, float TB, float tau)

samples/ocl/performance.cpp

@@ -1031,7 +1031,7 @@ class CascadeClassifier_GPU : public OclCascadeClassifier
 {
 public:
     void detectMultiScale(oclMat &image,
-                          CV_OUT std::vector<cv::Rect>& faces,
+                          std::vector<cv::Rect>& faces,
                           double scaleFactor = 1.1,
                           int minNeighbors = 3, int flags = 0,
                           Size minSize = Size(),

samples/python2/calibrate.py

@@ -65,7 +65,7 @@ if __name__ == '__main__':
 
         print 'ok'
 
-    rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h))
+    rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h), None, None)
     print "RMS:", rms
     print "camera matrix:\n", camera_matrix
     print "distortion coefficients: ", dist_coefs.ravel()

samples/python2/contours.py

@@ -46,7 +46,7 @@ if __name__ == '__main__':
     img = make_image()
     h, w = img.shape[:2]
 
-    contours0, hierarchy = cv2.findContours( img.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+    _, contours0, hierarchy = cv2.findContours( img.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
     contours = [cv2.approxPolyDP(cnt, 3, True) for cnt in contours0]
 
     def update(levels):

samples/python2/digits_video.py

@@ -35,7 +35,7 @@ def main():
 
         bin = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, 31, 10)
         bin = cv2.medianBlur(bin, 3)
-        contours, heirs = cv2.findContours( bin.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
+        _, contours, heirs = cv2.findContours( bin.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
         try:
             heirs = heirs[0]
         except:

samples/python2/kmeans.py

@@ -32,7 +32,7 @@ if __name__ == '__main__':
         points, _ = make_gaussians(cluster_n, img_size)
 
         term_crit = (cv2.TERM_CRITERIA_EPS, 30, 0.1)
-        ret, labels, centers = cv2.kmeans(points, cluster_n, term_crit, 10, 0)
+        ret, labels, centers = cv2.kmeans(points, cluster_n, None, term_crit, 10, 0)
 
         img = np.zeros((img_size, img_size, 3), np.uint8)
         for (x, y), label in zip(np.int32(points), labels.ravel()):

samples/python2/opt_flow.py

@@ -63,7 +63,7 @@ if __name__ == '__main__':
     while True:
         ret, img = cam.read()
         gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, 0.5, 3, 15, 3, 5, 1.2, 0)
+        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
         prevgray = gray
 
         cv2.imshow('flow', draw_flow(gray, flow))

samples/python2/squares.py

@@ -24,7 +24,7 @@ def find_squares(img):
                 bin = cv2.dilate(bin, None)
             else:
                 retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY)
-            contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
+            bin, contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
             for cnt in contours:
                 cnt_len = cv2.arcLength(cnt, True)
                 cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True)