Chiebot-Mirror
/
opencv
8
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

a big patch; use special proxy types (Input/OutputArray, Input/OutputArrayOfArrays) for passing in vectors, matrices etc.

Browse Source
pull/13383/head
Vadim Pisarevsky 14 years ago
parent 335370a7c0
commit abeeb40d46
94 changed files with 10407 additions and 9207 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Unified View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 255
      modules/calib3d/include/opencv2/calib3d/calib3d.hpp
  2. 63
      modules/calib3d/src/calibinit.cpp
  3. 647
      modules/calib3d/src/calibration.cpp
  4. 8
      modules/calib3d/src/circlesgrid.cpp
  5. 129
      modules/calib3d/src/fundam.cpp
  6. 34
      modules/calib3d/src/modelest.cpp
  7. 12
      modules/calib3d/src/quadsubpix.cpp
  8. 65
      modules/calib3d/src/solvepnp.cpp
  9. 7
      modules/calib3d/src/stereobm.cpp
  10. 84
      modules/calib3d/src/stereosgbm.cpp
  11. 11
      modules/calib3d/test/test_cameracalibration.cpp
  12. 4
      modules/calib3d/test/test_solvepnp_ransac.cpp
  13. 450
      modules/core/include/opencv2/core/core.hpp
  14. 43
      modules/core/include/opencv2/core/mat.hpp
  15. 18
      modules/core/include/opencv2/core/operations.hpp
  16. 3018
      modules/core/src/arithm.cpp
  17. 8
      modules/core/src/array.cpp
  18. 1251
      modules/core/src/convert.cpp
  19. 452
      modules/core/src/copy.cpp
  20. 215
      modules/core/src/datastructs.cpp
  21. 17
      modules/core/src/drawing.cpp
  22. 84
      modules/core/src/dxt.cpp
  23. 137
      modules/core/src/lapack.cpp
  24. 782
      modules/core/src/mathfuncs.cpp
  25. 1296
      modules/core/src/matmul.cpp
  26. 41
      modules/core/src/matop.cpp
  27. 929
      modules/core/src/matrix.cpp
  28. 258
      modules/core/src/precomp.hpp
  29. 532
      modules/core/src/rand.cpp
  30. 1907
      modules/core/src/stat.cpp
  31. 2
      modules/core/src/system.cpp
  32. 49
      modules/core/test/test_arithm.cpp
  33. 1
      modules/core/test/test_dxt.cpp
  34. 85
      modules/core/test/test_mat.cpp
  35. 2
      modules/features2d/src/bagofwords.cpp
  36. 11
      modules/features2d/test/test_nearestneighbors.cpp
  37. 2
      modules/gpu/test/test_filters.cpp
  38. 2
      modules/gpu/test/test_hog.cpp
  39. 2
      modules/gpu/test/test_operator_async_call.cpp
  40. 2
      modules/gpu/test/test_operator_convert_to.cpp
  41. 2
      modules/gpu/test/test_operator_copy_to.cpp
  42. 2
      modules/gpu/test/test_operator_set_to.cpp
  43. 2
      modules/gpu/test/test_stereo_bm.cpp
  44. 2
      modules/gpu/test/test_stereo_bm_async.cpp
  45. 2
      modules/gpu/test/test_stereo_bp.cpp
  46. 2
      modules/gpu/test/test_stereo_csbp.cpp
  47. 18
      modules/highgui/include/opencv2/highgui/highgui.hpp
  48. 11
      modules/highgui/src/loadsave.cpp
  49. 51
      modules/highgui/src/window.cpp
  50. 288
      modules/imgproc/include/opencv2/imgproc/imgproc.hpp
  51. 711
      modules/imgproc/src/accum.cpp
  52. 10
      modules/imgproc/src/canny.cpp
  53. 63
      modules/imgproc/src/color.cpp
  54. 250
      modules/imgproc/src/contours.cpp
  55. 34
      modules/imgproc/src/corner.cpp
  56. 10
      modules/imgproc/src/cornersubpix.cpp
  57. 61
      modules/imgproc/src/deriv.cpp
  58. 21
      modules/imgproc/src/distransform.cpp
  59. 25
      modules/imgproc/src/emd.cpp
  60. 16
      modules/imgproc/src/featureselect.cpp
  61. 87
      modules/imgproc/src/filter.cpp
  62. 12
      modules/imgproc/src/floodfill.cpp
  63. 13
      modules/imgproc/src/grabcut.cpp
  64. 94
      modules/imgproc/src/histogram.cpp
  65. 49
      modules/imgproc/src/hough.cpp
  66. 68
      modules/imgproc/src/imgwarp.cpp
  67. 9
      modules/imgproc/src/inpaint.cpp
  68. 7
      modules/imgproc/src/moments.cpp
  69. 63
      modules/imgproc/src/morph.cpp
  70. 37
      modules/imgproc/src/pyramids.cpp
  71. 12
      modules/imgproc/src/samplers.cpp
  72. 16
      modules/imgproc/src/segmentation.cpp
  73. 51
      modules/imgproc/src/smooth.cpp
  74. 138
      modules/imgproc/src/sumpixels.cpp
  75. 15
      modules/imgproc/src/templmatch.cpp
  76. 58
      modules/imgproc/src/thresh.cpp
  77. 124
      modules/imgproc/src/undistort.cpp
  78. 10
      modules/imgproc/src/utils.cpp
  79. 4
      modules/imgproc/test/test_imgwarp.cpp
  80. 7
      modules/ml/src/ann_mlp.cpp
  81. 12
      modules/ml/src/knearest.cpp
  82. 6
      modules/ml/test/test_emknearestkmeans.cpp
  83. 2
      modules/objdetect/src/planardetect.cpp
  84. 14
      modules/ts/include/opencv2/ts/ts.hpp
  85. 2
      modules/ts/src/ts_func.cpp
  86. 99
      modules/video/include/opencv2/video/background_segm.hpp
  87. 31
      modules/video/include/opencv2/video/tracking.hpp
  88. 8
      modules/video/src/bgfg_gaussmix.cpp
  89. 1241
      modules/video/src/bgfg_gaussmix2.cpp
  90. 16
      modules/video/src/camshift.cpp
  91. 55
      modules/video/src/lkpyramid.cpp
  92. 34
      modules/video/src/motempl.cpp
  93. 13
      modules/video/src/optflowgf.cpp
  94. 17
      modules/video/test/test_motiontemplates.cpp

255
modules/calib3d/include/opencv2/calib3d/calib3d.hpp
Unescape View File

@ -432,10 +432,7 @@ namespace cv
{ {
//! converts rotation vector to rotation matrix or vice versa using Rodrigues transformation //! converts rotation vector to rotation matrix or vice versa using Rodrigues transformation
CV_EXPORTS_W void Rodrigues(const Mat& src, CV_OUT Mat& dst); CV_EXPORTS_W void Rodrigues(const InputArray& src, OutputArray dst, OutputArray jacobian=OutputArray());
//! converts rotation vector to rotation matrix or vice versa using Rodrigues transformation. Also computes the Jacobian matrix
CV_EXPORTS_AS(RodriguesJ) void Rodrigues(const Mat& src, CV_OUT Mat& dst, CV_OUT Mat& jacobian);
//! type of the robust estimation algorithm //! type of the robust estimation algorithm
enum enum
@ -445,128 +442,93 @@ enum
}; };
//! computes the best-fit perspective transformation mapping srcPoints to dstPoints. //! computes the best-fit perspective transformation mapping srcPoints to dstPoints.
CV_EXPORTS_AS(findHomographyAndOutliers) Mat findHomography( const Mat& srcPoints, CV_EXPORTS_W Mat findHomography( const InputArray& srcPoints,
const Mat& dstPoints, const InputArray& dstPoints,
vector<uchar>& mask, int method=0, int method=0, double ransacReprojThreshold=3,
double ransacReprojThreshold=3 ); OutputArray mask=OutputArray());
//! computes the best-fit perspective transformation mapping srcPoints to dstPoints.
CV_EXPORTS_W Mat findHomography( const Mat& srcPoints,
const Mat& dstPoints,
int method=0, double ransacReprojThreshold=3 );
//! computes the best-fit affine transformation that maps one 3D point set to another (RANSAC algorithm is used)
CV_EXPORTS int estimateAffine3D(const Mat& from, const Mat& to, CV_OUT Mat& dst,
CV_OUT vector<uchar>& outliers,
double param1 = 3.0, double param2 = 0.99);
//! Computes RQ decomposition of 3x3 matrix //! Computes RQ decomposition of 3x3 matrix
CV_EXPORTS void RQDecomp3x3( const Mat& M, Mat& R, Mat& Q ); CV_EXPORTS_W Vec3d RQDecomp3x3( const InputArray& src, OutputArray mtxR, OutputArray mtxQ,
OutputArray Qx=OutputArray(),
//! Computes RQ decomposition of 3x3 matrix. Also, decomposes the output orthogonal matrix into the 3 primitive rotation matrices OutputArray Qy=OutputArray(),
CV_EXPORTS_W Vec3d RQDecomp3x3( const Mat& M, Mat& R, Mat& Q, OutputArray Qz=OutputArray());
CV_OUT Mat& Qx, CV_OUT Mat& Qy, CV_OUT Mat& Qz );
//! Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector //! Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector
CV_EXPORTS void decomposeProjectionMatrix( const Mat& projMatrix, Mat& cameraMatrix, CV_EXPORTS_W void decomposeProjectionMatrix( const InputArray& projMatrix, OutputArray cameraMatrix,
Mat& rotMatrix, Mat& transVect ); OutputArray rotMatrix, OutputArray transVect,
OutputArray rotMatrixX=OutputArray(),
//! Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector. The rotation matrix is further decomposed OutputArray rotMatrixY=OutputArray(),
CV_EXPORTS_W void decomposeProjectionMatrix( const Mat& projMatrix, CV_OUT Mat& cameraMatrix, OutputArray rotMatrixZ=OutputArray(),
CV_OUT Mat& rotMatrix, CV_OUT Mat& transVect, OutputArray eulerAngles=OutputArray() );
CV_OUT Mat& rotMatrixX, CV_OUT Mat& rotMatrixY,
CV_OUT Mat& rotMatrixZ, CV_OUT Vec3d& eulerAngles );
//! computes derivatives of the matrix product w.r.t each of the multiplied matrix coefficients //! computes derivatives of the matrix product w.r.t each of the multiplied matrix coefficients
CV_EXPORTS_W void matMulDeriv( const Mat& A, const Mat& B, CV_OUT Mat& dABdA, CV_OUT Mat& dABdB ); CV_EXPORTS_W void matMulDeriv( const InputArray& A, const InputArray& B,
OutputArray dABdA,
//! composes 2 [R|t] transformations together OutputArray dABdB );
CV_EXPORTS_W void composeRT( const Mat& rvec1, const Mat& tvec1,
const Mat& rvec2, const Mat& tvec2,
CV_OUT Mat& rvec3, CV_OUT Mat& tvec3 );
//! composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments //! composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments
CV_EXPORTS_AS(composeRT_J) void composeRT( const Mat& rvec1, const Mat& tvec1, CV_EXPORTS_W void composeRT( const InputArray& rvec1, const InputArray& tvec1,
const Mat& rvec2, const Mat& tvec2, const InputArray& rvec2, const InputArray& tvec2,
CV_OUT Mat& rvec3, CV_OUT Mat& tvec3, OutputArray rvec3, OutputArray tvec3,
CV_OUT Mat& dr3dr1, CV_OUT Mat& dr3dt1, OutputArray dr3dr1=OutputArray(), OutputArray dr3dt1=OutputArray(),
CV_OUT Mat& dr3dr2, CV_OUT Mat& dr3dt2, OutputArray dr3dr2=OutputArray(), OutputArray dr3dt2=OutputArray(),
CV_OUT Mat& dt3dr1, CV_OUT Mat& dt3dt1, OutputArray dt3dr1=OutputArray(), OutputArray dt3dt1=OutputArray(),
CV_OUT Mat& dt3dr2, CV_OUT Mat& dt3dt2 ); OutputArray dt3dr2=OutputArray(), OutputArray dt3dt2=OutputArray() );
//! projects points from the model coordinate space to the image coordinates. Takes the intrinsic and extrinsic camera parameters into account
CV_EXPORTS_W void projectPoints( const Mat& objectPoints,
const Mat& rvec, const Mat& tvec,
const Mat& cameraMatrix,
const Mat& distCoeffs,
CV_OUT vector<Point2f>& imagePoints );
//! projects points from the model coordinate space to the image coordinates. Also computes derivatives of the image coordinates w.r.t the intrinsic and extrinsic camera parameters //! projects points from the model coordinate space to the image coordinates. Also computes derivatives of the image coordinates w.r.t the intrinsic and extrinsic camera parameters
CV_EXPORTS_AS(projectPointsJ) void projectPoints( const Mat& objectPoints, CV_EXPORTS_W void projectPoints( const InputArray& objectPoints,
const Mat& rvec, const Mat& tvec, const InputArray& rvec, const InputArray& tvec,
const Mat& cameraMatrix, const InputArray& cameraMatrix, const InputArray& distCoeffs,
const Mat& distCoeffs, OutputArray imagePoints,
CV_OUT vector<Point2f>& imagePoints, OutputArray jacobian=OutputArray(),
CV_OUT Mat& dpdrot, CV_OUT Mat& dpdt, CV_OUT Mat& dpdf,
CV_OUT Mat& dpdc, CV_OUT Mat& dpddist,
double aspectRatio=0 ); double aspectRatio=0 );
//! computes the camera pose from a few 3D points and the corresponding projections. The outliers are not handled. //! computes the camera pose from a few 3D points and the corresponding projections. The outliers are not handled.
CV_EXPORTS_W void solvePnP( const Mat& objectPoints, CV_EXPORTS_W void solvePnP( const InputArray& objectPoints, const InputArray& imagePoints,
const Mat& imagePoints, const InputArray& cameraMatrix, const InputArray& distCoeffs,
const Mat& cameraMatrix, OutputArray rvec, OutputArray tvec,
const Mat& distCoeffs,
CV_OUT Mat& rvec, CV_OUT Mat& tvec,
bool useExtrinsicGuess=false ); bool useExtrinsicGuess=false );
//! computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible. //! computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible.
CV_EXPORTS_W void solvePnPRansac( const Mat& objectPoints, CV_EXPORTS_W void solvePnPRansac( const InputArray& objectPoints,
const Mat& imagePoints, const InputArray& imagePoints,
const Mat& cameraMatrix, const InputArray& cameraMatrix,
const Mat& distCoeffs, const InputArray& distCoeffs,
CV_OUT Mat& rvec, OutputArray rvec,
CV_OUT Mat& tvec, OutputArray tvec,
bool useExtrinsicGuess = false, bool useExtrinsicGuess = false,
int iterationsCount = 100, int iterationsCount = 100,
float reprojectionError = 8.0, float reprojectionError = 8.0,
int minInliersCount = 100, int minInliersCount = 100,
CV_OUT vector<int>* inliers = NULL ); OutputArray inliers = OutputArray() );
//! initializes camera matrix from a few 3D points and the corresponding projections. //! initializes camera matrix from a few 3D points and the corresponding projections.
CV_EXPORTS_W Mat initCameraMatrix2D( const vector<vector<Point3f> >& objectPoints, CV_EXPORTS_W Mat initCameraMatrix2D( const InputArrayOfArrays& objectPoints,
const vector<vector<Point2f> >& imagePoints, const InputArrayOfArrays& imagePoints,
Size imageSize, double aspectRatio=1. ); Size imageSize, double aspectRatio=1. );
enum { CALIB_CB_ADAPTIVE_THRESH = 1, CALIB_CB_NORMALIZE_IMAGE = 2, enum { CALIB_CB_ADAPTIVE_THRESH = 1, CALIB_CB_NORMALIZE_IMAGE = 2,
CALIB_CB_FILTER_QUADS = 4, CALIB_CB_FAST_CHECK = 8 }; CALIB_CB_FILTER_QUADS = 4, CALIB_CB_FAST_CHECK = 8 };
//! finds checkerboard pattern of the specified size in the image //! finds checkerboard pattern of the specified size in the image
CV_EXPORTS_W bool findChessboardCorners( const Mat& image, Size patternSize, CV_EXPORTS_W bool findChessboardCorners( const InputArray& image, Size patternSize,
CV_OUT vector<Point2f>& corners, OutputArray corners,
int flags=CALIB_CB_ADAPTIVE_THRESH+ int flags=CALIB_CB_ADAPTIVE_THRESH+
CALIB_CB_NORMALIZE_IMAGE ); CALIB_CB_NORMALIZE_IMAGE );
//! finds subpixel-accurate positions of the chessboard corners //! finds subpixel-accurate positions of the chessboard corners
CV_EXPORTS bool find4QuadCornerSubpix(const Mat& img, std::vector<Point2f>& corners, CV_EXPORTS bool find4QuadCornerSubpix(const InputArray& img, InputOutputArray corners, Size region_size);
Size region_size);
//! draws the checkerboard pattern (found or partly found) in the image //! draws the checkerboard pattern (found or partly found) in the image
CV_EXPORTS_W void drawChessboardCorners( Mat& image, Size patternSize, CV_EXPORTS_W void drawChessboardCorners( InputOutputArray image, Size patternSize,
const Mat& corners, const InputArray& corners, bool patternWasFound );
bool patternWasFound );
CV_EXPORTS void drawChessboardCorners( Mat& image, Size patternSize,
const vector<Point2f>& corners,
bool patternWasFound );
enum { CALIB_CB_SYMMETRIC_GRID = 1, CALIB_CB_ASYMMETRIC_GRID = 2, enum { CALIB_CB_SYMMETRIC_GRID = 1, CALIB_CB_ASYMMETRIC_GRID = 2,
CALIB_CB_CLUSTERING = 4, CALIB_CB_WHITE_CIRCLES = 8 }; CALIB_CB_CLUSTERING = 4, CALIB_CB_WHITE_CIRCLES = 8 };
//! finds circles' grid pattern of the specified size in the image //! finds circles' grid pattern of the specified size in the image
CV_EXPORTS_W bool findCirclesGrid( const Mat& image, Size patternSize, CV_EXPORTS_W bool findCirclesGrid( const InputArray& image, Size patternSize,
CV_OUT vector<Point2f>& centers, OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID );
int flags=CALIB_CB_SYMMETRIC_GRID );
enum enum
{ {
@ -590,16 +552,16 @@ enum
}; };
//! finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern. //! finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern.
CV_EXPORTS_W double calibrateCamera( const vector<vector<Point3f> >& objectPoints, CV_EXPORTS_W double calibrateCamera( const InputArrayOfArrays& objectPoints,
const vector<vector<Point2f> >& imagePoints, const InputArrayOfArrays& imagePoints,
Size imageSize, Size imageSize,
CV_IN_OUT Mat& cameraMatrix, CV_IN_OUT InputOutputArray cameraMatrix,
CV_IN_OUT Mat& distCoeffs, CV_IN_OUT InputOutputArray distCoeffs,
CV_OUT vector<Mat>& rvecs, CV_OUT vector<Mat>& tvecs, OutputArray rvecs, OutputArray tvecs,
int flags=0 ); int flags=0 );
//! computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size. //! computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size.
CV_EXPORTS_W void calibrationMatrixValues( const Mat& cameraMatrix, CV_EXPORTS_W void calibrationMatrixValues( const InputArray& cameraMatrix,
Size imageSize, Size imageSize,
double apertureWidth, double apertureWidth,
double apertureHeight, double apertureHeight,
@ -610,64 +572,58 @@ CV_EXPORTS_W void calibrationMatrixValues( const Mat& cameraMatrix,
CV_OUT double& aspectRatio ); CV_OUT double& aspectRatio );
//! finds intrinsic and extrinsic parameters of a stereo camera //! finds intrinsic and extrinsic parameters of a stereo camera
CV_EXPORTS_W double stereoCalibrate( const vector<vector<Point3f> >& objectPoints, CV_EXPORTS_W double stereoCalibrate( const InputArrayOfArrays& objectPoints,
const vector<vector<Point2f> >& imagePoints1, const InputArrayOfArrays& imagePoints1,
const vector<vector<Point2f> >& imagePoints2, const InputArrayOfArrays& imagePoints2,
CV_IN_OUT Mat& cameraMatrix1, CV_IN_OUT Mat& distCoeffs1, CV_IN_OUT InputOutputArray cameraMatrix1,
CV_IN_OUT Mat& cameraMatrix2, CV_IN_OUT Mat& distCoeffs2, CV_IN_OUT InputOutputArray distCoeffs1,
Size imageSize, CV_OUT Mat& R, CV_OUT Mat& T, CV_IN_OUT InputOutputArray cameraMatrix2,
CV_OUT Mat& E, CV_OUT Mat& F, CV_IN_OUT InputOutputArray distCoeffs2,
Size imageSize, OutputArray R,
OutputArray T, OutputArray E, OutputArray F,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT+ TermCriteria criteria = TermCriteria(TermCriteria::COUNT+
TermCriteria::EPS, 30, 1e-6), TermCriteria::EPS, 30, 1e-6),
int flags=CALIB_FIX_INTRINSIC ); int flags=CALIB_FIX_INTRINSIC );
//! computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters //! computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters
CV_EXPORTS void stereoRectify( const Mat& cameraMatrix1, const Mat& distCoeffs1, CV_EXPORTS void stereoRectify( const InputArray& cameraMatrix1, const InputArray& distCoeffs1,
const Mat& cameraMatrix2, const Mat& distCoeffs2, const InputArray& cameraMatrix2, const InputArray& distCoeffs2,
Size imageSize, const Mat& R, const Mat& T, Size imageSize, const InputArray& R, const InputArray& T,
CV_OUT Mat& R1, CV_OUT Mat& R2, OutputArray R1, OutputArray R2,
CV_OUT Mat& P1, CV_OUT Mat& P2, CV_OUT Mat& Q, OutputArray P1, OutputArray P2,
int flags=CALIB_ZERO_DISPARITY ); OutputArray Q, int flags=CALIB_ZERO_DISPARITY,
double alpha=-1, Size newImageSize=Size(),
//! computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters CV_OUT Rect* validPixROI1=0, CV_OUT Rect* validPixROI2=0 );
CV_EXPORTS_W void stereoRectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,
const Mat& cameraMatrix2, const Mat& distCoeffs2,
Size imageSize, const Mat& R, const Mat& T,
CV_OUT Mat& R1, CV_OUT Mat& R2,
CV_OUT Mat& P1, CV_OUT Mat& P2, CV_OUT Mat& Q,
double alpha, Size newImageSize=Size(),
CV_OUT Rect* validPixROI1=0, CV_OUT Rect* validPixROI2=0,
int flags=CALIB_ZERO_DISPARITY );
//! computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed) //! computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed)
CV_EXPORTS_W bool stereoRectifyUncalibrated( const Mat& points1, const Mat& points2, CV_EXPORTS_W bool stereoRectifyUncalibrated( const InputArray& points1, const InputArray& points2,
const Mat& F, Size imgSize, const InputArray& F, Size imgSize,
CV_OUT Mat& H1, CV_OUT Mat& H2, OutputArray H1, OutputArray H2,
double threshold=5 ); double threshold=5 );
//! computes the rectification transformations for 3-head camera, where all the heads are on the same line. //! computes the rectification transformations for 3-head camera, where all the heads are on the same line.
CV_EXPORTS_W float rectify3Collinear( const Mat& cameraMatrix1, const Mat& distCoeffs1, CV_EXPORTS_W float rectify3Collinear( const InputArray& cameraMatrix1, const InputArray& distCoeffs1,
const Mat& cameraMatrix2, const Mat& distCoeffs2, const InputArray& cameraMatrix2, const InputArray& distCoeffs2,
const Mat& cameraMatrix3, const Mat& distCoeffs3, const InputArray& cameraMatrix3, const InputArray& distCoeffs3,
const vector<vector<Point2f> >& imgpt1, const InputArrayOfArrays& imgpt1, const InputArrayOfArrays& imgpt3,
const vector<vector<Point2f> >& imgpt3, Size imageSize, const InputArray& R12, const InputArray& T12,
Size imageSize, const Mat& R12, const Mat& T12, const InputArray& R13, const InputArray& T13,
const Mat& R13, const Mat& T13, OutputArray R1, OutputArray R2, OutputArray R3,
CV_OUT Mat& R1, CV_OUT Mat& R2, CV_OUT Mat& R3, OutputArray P1, OutputArray P2, OutputArray P3,
CV_OUT Mat& P1, CV_OUT Mat& P2, CV_OUT Mat& P3, CV_OUT Mat& Q, OutputArray Q, double alpha, Size newImgSize,
double alpha, Size newImgSize,
CV_OUT Rect* roi1, CV_OUT Rect* roi2, int flags ); CV_OUT Rect* roi1, CV_OUT Rect* roi2, int flags );
//! returns the optimal new camera matrix //! returns the optimal new camera matrix
CV_EXPORTS_W Mat getOptimalNewCameraMatrix( const Mat& cameraMatrix, const Mat& distCoeffs, CV_EXPORTS_W Mat getOptimalNewCameraMatrix( const InputArray& cameraMatrix, const InputArray& distCoeffs,
Size imageSize, double alpha, Size newImgSize=Size(), Size imageSize, double alpha, Size newImgSize=Size(),
CV_OUT Rect* validPixROI=0); CV_OUT Rect* validPixROI=0);
//! converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1)) //! converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1))
CV_EXPORTS void convertPointsHomogeneous( const Mat& src, CV_OUT vector<Point3f>& dst ); CV_EXPORTS void convertPointsToHomogeneous( const InputArray& src, OutputArray dst );
//! converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z)) //! converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z))
CV_EXPORTS void convertPointsHomogeneous( const Mat& src, CV_OUT vector<Point2f>& dst ); CV_EXPORTS void convertPointsFromHomogeneous( const InputArray& src, OutputArray dst );
//! the algorithm for finding fundamental matrix //! the algorithm for finding fundamental matrix
enum enum
@ -679,19 +635,15 @@ enum
}; };
//! finds fundamental matrix from a set of corresponding 2D points //! finds fundamental matrix from a set of corresponding 2D points
CV_EXPORTS Mat findFundamentalMat( const Mat& points1, const Mat& points2, CV_EXPORTS_W Mat findFundamentalMat( const InputArray& points1, const InputArray& points2,
CV_OUT vector<uchar>& mask, int method=FM_RANSAC,
double param1=3., double param2=0.99 );
//! finds fundamental matrix from a set of corresponding 2D points
CV_EXPORTS_W Mat findFundamentalMat( const Mat& points1, const Mat& points2,
int method=FM_RANSAC, int method=FM_RANSAC,
double param1=3., double param2=0.99 ); double param1=3., double param2=0.99,
OutputArray mask=OutputArray());
//! finds coordinates of epipolar lines corresponding the specified points //! finds coordinates of epipolar lines corresponding the specified points
CV_EXPORTS void computeCorrespondEpilines( const Mat& points1, CV_EXPORTS void computeCorrespondEpilines( const InputArray& points1,
int whichImage, const Mat& F, int whichImage, const InputArray& F,
CV_OUT vector<Vec3f>& lines ); OutputArray lines );
template<> CV_EXPORTS void Ptr<CvStereoBMState>::delete_obj(); template<> CV_EXPORTS void Ptr<CvStereoBMState>::delete_obj();
@ -713,7 +665,8 @@ public:
//! the method that reinitializes the state. The previous content is destroyed //! the method that reinitializes the state. The previous content is destroyed
void init(int preset, int ndisparities=0, int SADWindowSize=21); void init(int preset, int ndisparities=0, int SADWindowSize=21);
//! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair
CV_WRAP_AS(compute) void operator()( const Mat& left, const Mat& right, Mat& disparity, int disptype=CV_16S ); CV_WRAP_AS(compute) void operator()( const InputArray& left, const InputArray& right,
OutputArray disparity, int disptype=CV_16S );
//! pointer to the underlying CvStereoBMState //! pointer to the underlying CvStereoBMState
Ptr<CvStereoBMState> state; Ptr<CvStereoBMState> state;
@ -743,7 +696,8 @@ public:
virtual ~StereoSGBM(); virtual ~StereoSGBM();
//! the stereo correspondence operator that computes disparity map for the specified rectified stereo pair //! the stereo correspondence operator that computes disparity map for the specified rectified stereo pair
CV_WRAP_AS(compute) virtual void operator()(const Mat& left, const Mat& right, Mat& disp); CV_WRAP_AS(compute) virtual void operator()(const InputArray& left, const InputArray& right,
OutputArray disp);
CV_PROP_RW int minDisparity; CV_PROP_RW int minDisparity;
CV_PROP_RW int numberOfDisparities; CV_PROP_RW int numberOfDisparities;
@ -762,7 +716,8 @@ protected:
}; };
//! filters off speckles (small regions of incorrectly computed disparity) //! filters off speckles (small regions of incorrectly computed disparity)
CV_EXPORTS_W void filterSpeckles( Mat& img, double newVal, int maxSpeckleSize, double maxDiff, Mat& buf ); CV_EXPORTS_W void filterSpeckles( InputOutputArray img, double newVal, int maxSpeckleSize, double maxDiff,
InputOutputArray buf=InputOutputArray() );
//! computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by cv::stereoRectify()) //! computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by cv::stereoRectify())
CV_EXPORTS_W Rect getValidDisparityROI( Rect roi1, Rect roi2, CV_EXPORTS_W Rect getValidDisparityROI( Rect roi1, Rect roi2,
@ -770,16 +725,20 @@ CV_EXPORTS_W Rect getValidDisparityROI( Rect roi1, Rect roi2,
int SADWindowSize ); int SADWindowSize );
//! validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm //! validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm
CV_EXPORTS_W void validateDisparity( Mat& disparity, const Mat& cost, CV_EXPORTS_W void validateDisparity( InputOutputArray disparity, const InputArray& cost,
int minDisparity, int numberOfDisparities, int minDisparity, int numberOfDisparities,
int disp12MaxDisp=1 ); int disp12MaxDisp=1 );
//! reprojects disparity image to 3D: (x,y,d)->(X,Y,Z) using the matrix Q returned by cv::stereoRectify //! reprojects disparity image to 3D: (x,y,d)->(X,Y,Z) using the matrix Q returned by cv::stereoRectify
CV_EXPORTS_W void reprojectImageTo3D( const Mat& disparity, CV_EXPORTS_W void reprojectImageTo3D( const InputArray& disparity,
CV_OUT Mat& _3dImage, const Mat& Q, OutputArray _3dImage, const InputArray& Q,
bool handleMissingValues=false, bool handleMissingValues=false,
int ddepth=-1 ); int ddepth=-1 );
CV_EXPORTS_W int estimateAffine3D(const InputArray& _from, const InputArray& _to,
OutputArray _out, OutputArray _outliers,
double param1=3, double param2=0.99);
} }
#endif #endif

63
modules/calib3d/src/calibinit.cpp
Unescape View File

@ -1894,49 +1894,43 @@ cvDrawChessboardCorners( CvArr* _image, CvSize pattern_size,
} }
} }
namespace cv bool cv::findChessboardCorners( const InputArray& _image, Size patternSize,
{ OutputArray corners, int flags )
bool findChessboardCorners( const Mat& image, Size patternSize,
vector<Point2f>& corners, int flags )
{ {
int count = patternSize.area()*2; int count = patternSize.area()*2;
corners.resize(count); vector<Point2f> tmpcorners(count+1);
CvMat _image = image; CvMat c_image = _image.getMat();
bool ok = cvFindChessboardCorners(&_image, patternSize, bool ok = cvFindChessboardCorners(&c_image, patternSize,
(CvPoint2D32f*)&corners[0], &count, flags ) > 0; (CvPoint2D32f*)&tmpcorners[0], &count, flags ) > 0;
if(count >= 0) if( count > 0 )
corners.resize(count); {
tmpcorners.resize(count);
Mat(tmpcorners).copyTo(corners);
}
else
corners.release();
return ok; return ok;
} }
void drawChessboardCorners( Mat& image, Size patternSize, void cv::drawChessboardCorners( InputOutputArray _image, Size patternSize,
const Mat& corners, const InputArray& _corners,
bool patternWasFound ) bool patternWasFound )
{ {
if( corners.cols == 0 || corners.rows == 0 ) Mat corners = _corners.getMat();
if( !corners.empty() )
return; return;
CvMat _image = image; CvMat c_image = _image.getMat();
int nelems = corners.checkVector(2, CV_32F, true); int nelems = corners.checkVector(2, CV_32F, true);
CV_Assert(nelems >= 0); CV_Assert(nelems >= 0);
cvDrawChessboardCorners( &_image, patternSize, (CvPoint2D32f*)corners.data, cvDrawChessboardCorners( &c_image, patternSize, (CvPoint2D32f*)corners.data,
nelems, patternWasFound ); nelems, patternWasFound );
} }
void drawChessboardCorners( Mat& image, Size patternSize, bool cv::findCirclesGrid( const InputArray& _image, Size patternSize,
const vector<Point2f>& corners, OutputArray _centers, int flags )
bool patternWasFound )
{
if( corners.empty() )
return;
CvMat _image = image;
cvDrawChessboardCorners( &_image, patternSize, (CvPoint2D32f*)&corners[0],
(int)corners.size(), patternWasFound );
}
bool findCirclesGrid( const Mat& image, Size patternSize,
vector<Point2f>& centers, int flags )
{ {
Mat image = _image.getMat();
vector<Point2f> centers;
SimpleBlobDetector::Params params; SimpleBlobDetector::Params params;
if(flags & CALIB_CB_WHITE_CIRCLES) if(flags & CALIB_CB_WHITE_CIRCLES)
{ {
@ -1957,6 +1951,7 @@ bool findCirclesGrid( const Mat& image, Size patternSize,
{ {
CirclesGridClusterFinder circlesGridClusterFinder; CirclesGridClusterFinder circlesGridClusterFinder;
circlesGridClusterFinder.findGrid(points, patternSize, centers); circlesGridClusterFinder.findGrid(points, patternSize, centers);
Mat(centers).copyTo(_centers);
return !centers.empty(); return !centers.empty();
} }
@ -2005,10 +2000,10 @@ bool findCirclesGrid( const Mat& image, Size patternSize,
if (i != 0) if (i != 0)
{ {
Mat orgPointsMat; Mat orgPointsMat;
transform(Mat(centers), orgPointsMat, H.inv()); transform(centers, orgPointsMat, H.inv());
convertPointsHomogeneous(orgPointsMat, centers); convertPointsFromHomogeneous(orgPointsMat, centers);
} }
Mat(centers).copyTo(_centers);
return true; return true;
} }
@ -2020,10 +2015,8 @@ bool findCirclesGrid( const Mat& image, Size patternSize,
H = CirclesGridFinder::rectifyGrid(boxFinder.getDetectedGridSize(), centers, points, points); H = CirclesGridFinder::rectifyGrid(boxFinder.getDetectedGridSize(), centers, points, points);
} }
} }
Mat(centers).copyTo(_centers);
return false; return false;
} }
}
/* End of file. */ /* End of file. */

647
modules/calib3d/src/calibration.cpp
Unescape View File

@ -2753,10 +2753,11 @@ CV_IMPL int cvStereoRectifyUncalibrated(
} }
void cv::reprojectImageTo3D( const Mat& disparity, void cv::reprojectImageTo3D( const InputArray& _disparity,
Mat& _3dImage, const Mat& Q, OutputArray __3dImage, const InputArray& _Qmat,
bool handleMissingValues, int dtype ) bool handleMissingValues, int dtype )
{ {
Mat disparity = _disparity.getMat(), Q = _Qmat.getMat();
int stype = disparity.type(); int stype = disparity.type();
CV_Assert( stype == CV_8UC1 || stype == CV_16SC1 || CV_Assert( stype == CV_8UC1 || stype == CV_16SC1 ||
@ -2771,7 +2772,8 @@ void cv::reprojectImageTo3D( const Mat& disparity,
CV_Assert( dtype == CV_16SC3 || dtype == CV_32SC3 || dtype == CV_32FC3 ); CV_Assert( dtype == CV_16SC3 || dtype == CV_32SC3 || dtype == CV_32FC3 );
} }
_3dImage.create(disparity.size(), CV_MAKETYPE(dtype, 3)); __3dImage.create(disparity.size(), CV_MAKETYPE(dtype, 3));
Mat _3dImage = __3dImage.getMat();
const double bigZ = 10000.; const double bigZ = 10000.;
double q[4][4]; double q[4][4];
@ -3092,45 +3094,56 @@ cvDecomposeProjectionMatrix( const CvMat *projMatr, CvMat *calibMatr,
namespace cv namespace cv
{ {
static void collectCalibrationData( const vector<vector<Point3f> >& objectPoints, static void collectCalibrationData( const InputArrayOfArrays& objectPoints,
const vector<vector<Point2f> >& imagePoints, const InputArrayOfArrays& imagePoints1,
const vector<vector<Point2f> >& imagePoints2, const InputArrayOfArrays& imagePoints2,
Mat& objPtMat, Mat& imgPtMat, Mat* imgPtMat2, Mat& objPtMat, Mat& imgPtMat1, Mat* imgPtMat2,
Mat& npoints ) Mat& npoints )
{ {
size_t i, j = 0, ni = 0, nimages = objectPoints.size(), total = 0; int nimages = (int)objectPoints.total();
CV_Assert(nimages > 0 && nimages == imagePoints.size() && int i, j = 0, ni = 0, total = 0;
(!imgPtMat2 || nimages == imagePoints2.size())); CV_Assert(nimages > 0 && nimages == (int)imagePoints1.total() &&
(!imgPtMat2 || nimages == (int)imagePoints2.total()));
for( i = 0; i < nimages; i++ ) for( i = 0; i < nimages; i++ )
{ {
ni = objectPoints[i].size(); ni = objectPoints.getMat(i).checkVector(3, CV_32F);
CV_Assert(ni == imagePoints[i].size() && (!imgPtMat2 || ni == imagePoints2[i].size())); CV_Assert( ni >= 0 );
total += ni; total += ni;
} }
npoints.create(1, (int)nimages, CV_32S); npoints.create(1, (int)nimages, CV_32S);
objPtMat.create(1, (int)total, DataType<Point3f>::type); objPtMat.create(1, (int)total, CV_32FC3);
imgPtMat.create(1, (int)total, DataType<Point2f>::type); imgPtMat1.create(1, (int)total, CV_32FC2);
Point2f* imgPtData2 = 0; Point2f* imgPtData2 = 0;
if( imgPtMat2 ) if( imgPtMat2 )
{ {
imgPtMat2->create(1, (int)total, DataType<Point2f>::type); imgPtMat2->create(1, (int)total, CV_32FC2);
imgPtData2 = imgPtMat2->ptr<Point2f>(); imgPtData2 = imgPtMat2->ptr<Point2f>();
} }
Point3f* objPtData = objPtMat.ptr<Point3f>(); Point3f* objPtData = objPtMat.ptr<Point3f>();
Point2f* imgPtData = imgPtMat.ptr<Point2f>(); Point2f* imgPtData1 = imgPtMat1.ptr<Point2f>();
for( i = 0; i < nimages; i++, j += ni ) for( i = 0; i < nimages; i++, j += ni )
{ {
ni = objectPoints[i].size(); Mat objpt = objectPoints.getMat(i);
((int*)npoints.data)[i] = (int)ni; Mat imgpt1 = imagePoints1.getMat(i);
std::copy(objectPoints[i].begin(), objectPoints[i].end(), objPtData + j); ni = objpt.checkVector(3, CV_32F);
std::copy(imagePoints[i].begin(), imagePoints[i].end(), imgPtData + j); int ni1 = imgpt1.checkVector(2, CV_32F);
if( imgPtMat2 ) CV_Assert( ni > 0 && ni == ni1 );
std::copy(imagePoints2[i].begin(), imagePoints2[i].end(), imgPtData2 + j); npoints.at<int>(i) = ni;
memcpy( objPtData + j, objpt.data, ni*sizeof(objPtData[0]) );
memcpy( imgPtData1 + j, imgpt1.data, ni*sizeof(imgPtData1[0]) );
if( imgPtData2 )
{
Mat imgpt2 = imagePoints2.getMat(i);
int ni2 = imgpt2.checkVector(2, CV_32F);
CV_Assert( ni == ni2 );
memcpy( imgPtData2 + j, imgpt2.data, ni*sizeof(imgPtData2[0]) );
}
} }
} }
@ -3162,126 +3175,153 @@ static Mat prepareDistCoeffs(Mat& distCoeffs0, int rtype)
} }
void cv::Rodrigues(const Mat& src, Mat& dst) void cv::Rodrigues(const InputArray& _src, OutputArray _dst, OutputArray _jacobian)
{ {
Mat src = _src.getMat();
bool v2m = src.cols == 1 || src.rows == 1; bool v2m = src.cols == 1 || src.rows == 1;
dst.create(3, v2m ? 3 : 1, src.depth()); _dst.create(3, v2m ? 3 : 1, src.depth());
CvMat _src = src, _dst = dst; Mat dst = _dst.getMat();
bool ok = cvRodrigues2(&_src, &_dst, 0) > 0; CvMat _csrc = src, _cdst = dst, _cjacobian;
if( _jacobian.needed() )
{
_jacobian.create(v2m ? Size(9, 3) : Size(3, 9), src.depth());
_cjacobian = _jacobian.getMat();
}
bool ok = cvRodrigues2(&_csrc, &_cdst, _jacobian.needed() ? &_cjacobian : 0) > 0;
if( !ok ) if( !ok )
dst = Scalar(0); dst = Scalar(0);
} }
void cv::Rodrigues(const Mat& src, Mat& dst, Mat& jacobian) void cv::matMulDeriv( const InputArray& _Amat, const InputArray& _Bmat,
OutputArray _dABdA, OutputArray _dABdB )
{ {
bool v2m = src.cols == 1 || src.rows == 1; Mat A = _Amat.getMat(), B = _Bmat.getMat();
dst.create(3, v2m ? 3 : 1, src.depth()); _dABdA.create(A.rows*B.cols, A.rows*A.cols, A.type());
jacobian.create(v2m ? Size(9, 3) : Size(3, 9), src.depth()); _dABdB.create(A.rows*B.cols, B.rows*B.cols, A.type());
CvMat _src = src, _dst = dst, _jacobian = jacobian; CvMat matA = A, matB = B, c_dABdA = _dABdA.getMat(), c_dABdB = _dABdB.getMat();
bool ok = cvRodrigues2(&_src, &_dst, &_jacobian) > 0; cvCalcMatMulDeriv(&matA, &matB, &c_dABdA, &c_dABdB);
if( !ok ) }
dst = Scalar(0);
void cv::composeRT( const InputArray& _rvec1, const InputArray& _tvec1,
const InputArray& _rvec2, const InputArray& _tvec2,
OutputArray _rvec3, OutputArray _tvec3,
OutputArray _dr3dr1, OutputArray _dr3dt1,
OutputArray _dr3dr2, OutputArray _dr3dt2,
OutputArray _dt3dr1, OutputArray _dt3dt1,
OutputArray _dt3dr2, OutputArray _dt3dt2 )
{
Mat rvec1 = _rvec1.getMat(), tvec1 = _tvec1.getMat();
Mat rvec2 = _rvec2.getMat(), tvec2 = _tvec2.getMat();
int rtype = rvec1.type();
_rvec3.create(rvec1.size(), rtype);
_tvec3.create(tvec1.size(), rtype);
Mat rvec3 = _rvec3.getMat(), tvec3 = _tvec3.getMat();
CvMat c_rvec1 = rvec1, c_tvec1 = tvec1, c_rvec2 = rvec2,
c_tvec2 = tvec2, c_rvec3 = rvec3, c_tvec3 = tvec3;
CvMat c_dr3dr1, c_dr3dt1, c_dr3dr2, c_dr3dt2, c_dt3dr1, c_dt3dt1, c_dt3dr2, c_dt3dt2;
CvMat *p_dr3dr1=0, *p_dr3dt1=0, *p_dr3dr2=0, *p_dr3dt2=0, *p_dt3dr1=0, *p_dt3dt1=0, *p_dt3dr2=0, *p_dt3dt2=0;
if( _dr3dr1.needed() )
{
_dr3dr1.create(3, 3, rtype);
p_dr3dr1 = &(c_dr3dr1 = _dr3dr1.getMat());
} }
void cv::matMulDeriv( const Mat& A, const Mat& B, Mat& dABdA, Mat& dABdB ) if( _dr3dt1.needed() )
{ {
dABdA.create(A.rows*B.cols, A.rows*A.cols, A.type()); _dr3dt1.create(3, 3, rtype);
dABdB.create(A.rows*B.cols, B.rows*B.cols, A.type()); p_dr3dt1 = &(c_dr3dt1 = _dr3dt1.getMat());
CvMat matA = A, matB = B, _dABdA = dABdA, _dABdB = dABdB;
cvCalcMatMulDeriv(&matA, &matB, &_dABdA, &_dABdB);
} }
void cv::composeRT( const Mat& rvec1, const Mat& tvec1, if( _dr3dr2.needed() )
const Mat& rvec2, const Mat& tvec2,
Mat& rvec3, Mat& tvec3 )
{ {
rvec3.create(rvec1.size(), rvec1.type()); _dr3dr2.create(3, 3, rtype);
tvec3.create(tvec1.size(), tvec1.type()); p_dr3dr2 = &(c_dr3dr2 = _dr3dr2.getMat());
CvMat _rvec1 = rvec1, _tvec1 = tvec1, _rvec2 = rvec2,
_tvec2 = tvec2, _rvec3 = rvec3, _tvec3 = tvec3;
cvComposeRT(&_rvec1, &_tvec1, &_rvec2, &_tvec2, &_rvec3, &_tvec3, 0, 0, 0, 0, 0, 0, 0, 0);
} }
if( _dr3dt2.needed() )
{
_dr3dt2.create(3, 3, rtype);
p_dr3dt2 = &(c_dr3dt2 = _dr3dt2.getMat());
}
void cv::composeRT( const Mat& rvec1, const Mat& tvec1, if( _dt3dr1.needed() )
const Mat& rvec2, const Mat& tvec2,
Mat& rvec3, Mat& tvec3,
Mat& dr3dr1, Mat& dr3dt1,
Mat& dr3dr2, Mat& dr3dt2,
Mat& dt3dr1, Mat& dt3dt1,
Mat& dt3dr2, Mat& dt3dt2 )
{ {
int rtype = rvec1.type(); _dt3dr1.create(3, 3, rtype);
rvec3.create(rvec1.size(), rtype); p_dt3dr1 = &(c_dt3dr1 = _dt3dr1.getMat());
tvec3.create(tvec1.size(), rtype); }
dr3dr1.create(3, 3, rtype); dr3dt1.create(3, 3, rtype);
dr3dr2.create(3, 3, rtype); dr3dt2.create(3, 3, rtype); if( _dt3dt1.needed() )
dt3dr1.create(3, 3, rtype); dt3dt1.create(3, 3, rtype); {
dt3dr2.create(3, 3, rtype); dt3dt2.create(3, 3, rtype); _dt3dt1.create(3, 3, rtype);
p_dt3dt1 = &(c_dt3dt1 = _dt3dt1.getMat());
CvMat _rvec1 = rvec1, _tvec1 = tvec1, _rvec2 = rvec2, }
_tvec2 = tvec2, _rvec3 = rvec3, _tvec3 = tvec3;
CvMat _dr3dr1 = dr3dr1, _dr3dt1 = dr3dt1, _dr3dr2 = dr3dr2, _dr3dt2 = dr3dt2; if( _dt3dr2.needed() )
CvMat _dt3dr1 = dt3dr1, _dt3dt1 = dt3dt1, _dt3dr2 = dt3dr2, _dt3dt2 = dt3dt2; {
cvComposeRT(&_rvec1, &_tvec1, &_rvec2, &_tvec2, &_rvec3, &_tvec3, _dt3dr2.create(3, 3, rtype);
&_dr3dr1, &_dr3dt1, &_dr3dr2, &_dr3dt2, p_dt3dr2 = &(c_dt3dr2 = _dt3dr2.getMat());
&_dt3dr1, &_dt3dt1, &_dt3dr2, &_dt3dt2); }
}
if( _dt3dt2.needed() )
{
void cv::projectPoints( const Mat& opoints, _dt3dt2.create(3, 3, rtype);
const Mat& rvec, const Mat& tvec, p_dt3dt2 = &(c_dt3dt2 = _dt3dt2.getMat());
const Mat& cameraMatrix, }
const Mat& distCoeffs,
vector<Point2f>& ipoints ) cvComposeRT(&c_rvec1, &c_tvec1, &c_rvec2, &c_tvec2, &c_rvec3, &c_tvec3,
{ p_dr3dr1, p_dr3dt1, p_dr3dr2, p_dr3dt2,
CV_Assert(opoints.isContinuous() && opoints.depth() == CV_32F && p_dt3dr1, p_dt3dt1, p_dt3dr2, p_dt3dt2);
((opoints.rows == 1 && opoints.channels() == 3) || }
opoints.cols*opoints.channels() == 3));
ipoints.resize(opoints.cols*opoints.rows*opoints.channels()/3); void cv::projectPoints( const InputArray& _opoints,
CvMat _objectPoints = opoints, _imagePoints = Mat(ipoints); const InputArray& _rvec,
CvMat _rvec = rvec, _tvec = tvec, _cameraMatrix = cameraMatrix, _distCoeffs = distCoeffs; const InputArray& _tvec,
const InputArray& _cameraMatrix,
cvProjectPoints2( &_objectPoints, &_rvec, &_tvec, &_cameraMatrix, const InputArray& _distCoeffs,
distCoeffs.data ? &_distCoeffs : 0, OutputArray _ipoints,
&_imagePoints, 0, 0, 0, 0, 0, 0 ); OutputArray _jacobian,
}
void cv::projectPoints( const Mat& opoints,
const Mat& rvec, const Mat& tvec,
const Mat& cameraMatrix,
const Mat& distCoeffs,
vector<Point2f>& ipoints,
Mat& dpdrot, Mat& dpdt, Mat& dpdf,
Mat& dpdc, Mat& dpddist,
double aspectRatio ) double aspectRatio )
{ {
CV_Assert(opoints.isContinuous() && opoints.depth() == CV_32F && Mat opoints = _opoints.getMat();
((opoints.rows == 1 && opoints.channels() == 3) || int npoints = opoints.checkVector(3), depth = opoints.depth();
opoints.cols*opoints.channels() == 3)); CV_Assert(npoints >= 0 && (depth == CV_32F || depth == CV_64F));
CvMat dpdrot, dpdt, dpdf, dpdc, dpddist;
CvMat *pdpdrot=0, *pdpdt=0, *pdpdf=0, *pdpdc=0, *pdpddist=0;
_ipoints.create(npoints, 1, CV_MAKETYPE(depth, 2), -1, true);
CvMat imagePoints = _ipoints.getMat();
CvMat objectPoints = opoints;
CvMat cameraMatrix = _cameraMatrix.getMat();
CvMat rvec = _rvec.getMat(), tvec = _tvec.getMat();
CvMat distCoeffs = _distCoeffs.getMat();
int ndistCoeffs = distCoeffs.rows + distCoeffs.cols - 1;
int npoints = opoints.cols*opoints.rows*opoints.channels()/3; if( _jacobian.needed() )
ipoints.resize(npoints); {
dpdrot.create(npoints*2, 3, CV_64F); _jacobian.create(npoints*2, 3+3+2+2+ndistCoeffs, CV_64F);
dpdt.create(npoints*2, 3, CV_64F); Mat jacobian = _jacobian.getMat();
dpdf.create(npoints*2, 2, CV_64F); pdpdrot = &(dpdrot = jacobian.colRange(0, 3));
dpdc.create(npoints*2, 2, CV_64F); pdpdt = &(dpdt = jacobian.colRange(3, 6));
dpddist.create(npoints*2, distCoeffs.rows + distCoeffs.cols - 1, CV_64F); pdpdf = &(dpdf = jacobian.colRange(6, 8));
CvMat _objectPoints = opoints, _imagePoints = Mat(ipoints); pdpdc = &(dpdc = jacobian.colRange(8, 10));
CvMat _rvec = rvec, _tvec = tvec, _cameraMatrix = cameraMatrix, _distCoeffs = distCoeffs; pdpddist = &(dpddist = jacobian.colRange(10, 10+ndistCoeffs));
CvMat _dpdrot = dpdrot, _dpdt = dpdt, _dpdf = dpdf, _dpdc = dpdc, _dpddist = dpddist; }
cvProjectPoints2( &_objectPoints, &_rvec, &_tvec, &_cameraMatrix, &_distCoeffs, cvProjectPoints2( &objectPoints, &rvec, &tvec, &cameraMatrix, &distCoeffs,
&_imagePoints, &_dpdrot, &_dpdt, &_dpdf, &_dpdc, &_dpddist, aspectRatio ); &imagePoints, pdpdrot, pdpdt, pdpdf, pdpdc, pdpddist, aspectRatio );
} }
cv::Mat cv::initCameraMatrix2D( const vector<vector<Point3f> >& objectPoints, cv::Mat cv::initCameraMatrix2D( const InputArrayOfArrays& objectPoints,
const vector<vector<Point2f> >& imagePoints, const InputArrayOfArrays& imagePoints,
Size imageSize, double aspectRatio ) Size imageSize, double aspectRatio )
{ {
Mat objPt, imgPt, npoints, cameraMatrix(3, 3, CV_64F); Mat objPt, imgPt, npoints, cameraMatrix(3, 3, CV_64F);
collectCalibrationData( objectPoints, imagePoints, vector<vector<Point2f> >(), collectCalibrationData( objectPoints, imagePoints, InputArrayOfArrays(),
objPt, imgPt, 0, npoints ); objPt, imgPt, 0, npoints );
CvMat _objPt = objPt, _imgPt = imgPt, _npoints = npoints, _cameraMatrix = cameraMatrix; CvMat _objPt = objPt, _imgPt = imgPt, _npoints = npoints, _cameraMatrix = cameraMatrix;
cvInitIntrinsicParams2D( &_objPt, &_imgPt, &_npoints, cvInitIntrinsicParams2D( &_objPt, &_imgPt, &_npoints,
@ -3290,60 +3330,73 @@ cv::Mat cv::initCameraMatrix2D( const vector<vector<Point3f> >& objectPoints,
} }
double cv::calibrateCamera( const vector<vector<Point3f> >& objectPoints, double cv::calibrateCamera( const InputArrayOfArrays& _objectPoints,
const vector<vector<Point2f> >& imagePoints, const InputArrayOfArrays& _imagePoints,
Size imageSize, Mat& cameraMatrix, Mat& distCoeffs, Size imageSize, InputOutputArray _cameraMatrix, InputOutputArray _distCoeffs,
vector<Mat>& rvecs, vector<Mat>& tvecs, int flags ) OutputArray _rvecs, OutputArray _tvecs, int flags )
{ {
int rtype = CV_64F; int rtype = CV_64F;
Mat cameraMatrix = _cameraMatrix.getMat();
cameraMatrix = prepareCameraMatrix(cameraMatrix, rtype); cameraMatrix = prepareCameraMatrix(cameraMatrix, rtype);
Mat distCoeffs = _distCoeffs.getMat();
distCoeffs = prepareDistCoeffs(distCoeffs, rtype); distCoeffs = prepareDistCoeffs(distCoeffs, rtype);
if( !(flags & CALIB_RATIONAL_MODEL) ) if( !(flags & CALIB_RATIONAL_MODEL) )
distCoeffs = distCoeffs.rows == 1 ? distCoeffs.colRange(0, 5) : distCoeffs.rowRange(0, 5); distCoeffs = distCoeffs.rows == 1 ? distCoeffs.colRange(0, 5) : distCoeffs.rowRange(0, 5);
size_t i, nimages = objectPoints.size(); size_t i, nimages = _objectPoints.total();
CV_Assert( nimages > 0 ); CV_Assert( nimages > 0 );
Mat objPt, imgPt, npoints, rvecM((int)nimages, 3, CV_64FC1), tvecM((int)nimages, 3, CV_64FC1); Mat objPt, imgPt, npoints, rvecM((int)nimages, 3, CV_64FC1), tvecM((int)nimages, 3, CV_64FC1);
collectCalibrationData( objectPoints, imagePoints, vector<vector<Point2f> >(), collectCalibrationData( _objectPoints, _imagePoints, InputArrayOfArrays(),
objPt, imgPt, 0, npoints ); objPt, imgPt, 0, npoints );
CvMat _objPt = objPt, _imgPt = imgPt, _npoints = npoints; CvMat c_objPt = objPt, c_imgPt = imgPt, c_npoints = npoints;
CvMat _cameraMatrix = cameraMatrix, _distCoeffs = distCoeffs; CvMat c_cameraMatrix = cameraMatrix, c_distCoeffs = distCoeffs;
CvMat _rvecM = rvecM, _tvecM = tvecM; CvMat c_rvecM = rvecM, c_tvecM = tvecM;
double reprojErr = cvCalibrateCamera2(&_objPt, &_imgPt, &_npoints, imageSize, double reprojErr = cvCalibrateCamera2(&c_objPt, &c_imgPt, &c_npoints, imageSize,
&_cameraMatrix, &_distCoeffs, &_rvecM, &c_cameraMatrix, &c_distCoeffs, &c_rvecM,
&_tvecM, flags ); &c_tvecM, flags );
rvecs.resize(nimages); _rvecs.create(nimages, 1, CV_64FC3);
tvecs.resize(nimages); _tvecs.create(nimages, 1, CV_64FC3);
for( i = 0; i < nimages; i++ ) for( i = 0; i < nimages; i++ )
{ {
rvecM.row((int)i).copyTo(rvecs[i]); _rvecs.create(3, 1, CV_64F, i, true);
tvecM.row((int)i).copyTo(tvecs[i]); _tvecs.create(3, 1, CV_64F, i, true);
Mat rv = _rvecs.getMat(i), tv = _tvecs.getMat(i);
memcpy(rv.data, rvecM.ptr<double>(i), 3*sizeof(double));
memcpy(tv.data, tvecM.ptr<double>(i), 3*sizeof(double));
} }
cameraMatrix.copyTo(_cameraMatrix);
distCoeffs.copyTo(_distCoeffs);
return reprojErr; return reprojErr;
} }
void cv::calibrationMatrixValues( const Mat& cameraMatrix, Size imageSize, void cv::calibrationMatrixValues( const InputArray& _cameraMatrix, Size imageSize,
double apertureWidth, double apertureHeight, double apertureWidth, double apertureHeight,
double& fovx, double& fovy, double& focalLength, double& fovx, double& fovy, double& focalLength,
Point2d& principalPoint, double& aspectRatio ) Point2d& principalPoint, double& aspectRatio )
{ {
CvMat _cameraMatrix = cameraMatrix; CvMat c_cameraMatrix = _cameraMatrix.getMat();
cvCalibrationMatrixValues( &_cameraMatrix, imageSize, apertureWidth, apertureHeight, cvCalibrationMatrixValues( &c_cameraMatrix, imageSize, apertureWidth, apertureHeight,
&fovx, &fovy, &focalLength, (CvPoint2D64f*)&principalPoint, &aspectRatio ); &fovx, &fovy, &focalLength, (CvPoint2D64f*)&principalPoint, &aspectRatio );
} }
double cv::stereoCalibrate( const vector<vector<Point3f> >& objectPoints, double cv::stereoCalibrate( const InputArrayOfArrays& _objectPoints,
const vector<vector<Point2f> >& imagePoints1, const InputArrayOfArrays& _imagePoints1,
const vector<vector<Point2f> >& imagePoints2, const InputArrayOfArrays& _imagePoints2,
Mat& cameraMatrix1, Mat& distCoeffs1, InputOutputArray _cameraMatrix1, InputOutputArray _distCoeffs1,
Mat& cameraMatrix2, Mat& distCoeffs2, InputOutputArray _cameraMatrix2, InputOutputArray _distCoeffs2,
Size imageSize, Mat& R, Mat& T, Size imageSize, OutputArray _Rmat, OutputArray _Tmat,
Mat& E, Mat& F, TermCriteria criteria, OutputArray _Emat, OutputArray _Fmat, TermCriteria criteria,
int flags ) int flags )
{ {
int rtype = CV_64F; int rtype = CV_64F;
Mat cameraMatrix1 = _cameraMatrix1.getMat();
Mat cameraMatrix2 = _cameraMatrix2.getMat();
Mat distCoeffs1 = _distCoeffs1.getMat();
Mat distCoeffs2 = _distCoeffs2.getMat();
cameraMatrix1 = prepareCameraMatrix(cameraMatrix1, rtype); cameraMatrix1 = prepareCameraMatrix(cameraMatrix1, rtype);
cameraMatrix2 = prepareCameraMatrix(cameraMatrix2, rtype); cameraMatrix2 = prepareCameraMatrix(cameraMatrix2, rtype);
distCoeffs1 = prepareDistCoeffs(distCoeffs1, rtype); distCoeffs1 = prepareDistCoeffs(distCoeffs1, rtype);
@ -3355,176 +3408,210 @@ double cv::stereoCalibrate( const vector<vector<Point3f> >& objectPoints,
distCoeffs2 = distCoeffs2.rows == 1 ? distCoeffs2.colRange(0, 5) : distCoeffs2.rowRange(0, 5); distCoeffs2 = distCoeffs2.rows == 1 ? distCoeffs2.colRange(0, 5) : distCoeffs2.rowRange(0, 5);
} }
R.create(3, 3, rtype); _Rmat.create(3, 3, rtype);
T.create(3, 1, rtype); _Tmat.create(3, 1, rtype);
E.create(3, 3, rtype);
F.create(3, 3, rtype);
Mat objPt, imgPt, imgPt2, npoints; Mat objPt, imgPt, imgPt2, npoints;
collectCalibrationData( objectPoints, imagePoints1, imagePoints2, collectCalibrationData( _objectPoints, _imagePoints1, _imagePoints2,
objPt, imgPt, &imgPt2, npoints ); objPt, imgPt, &imgPt2, npoints );
CvMat _objPt = objPt, _imgPt = imgPt, _imgPt2 = imgPt2, _npoints = npoints; CvMat c_objPt = objPt, c_imgPt = imgPt, c_imgPt2 = imgPt2, c_npoints = npoints;
CvMat _cameraMatrix1 = cameraMatrix1, _distCoeffs1 = distCoeffs1; CvMat c_cameraMatrix1 = cameraMatrix1, c_distCoeffs1 = distCoeffs1;
CvMat _cameraMatrix2 = cameraMatrix2, _distCoeffs2 = distCoeffs2; CvMat c_cameraMatrix2 = cameraMatrix2, c_distCoeffs2 = distCoeffs2;
CvMat matR = R, matT = T, matE = E, matF = F; CvMat c_matR = _Rmat.getMat(), c_matT = _Tmat.getMat(), c_matE, c_matF, *p_matE = 0, *p_matF = 0;
return cvStereoCalibrate(&_objPt, &_imgPt, &_imgPt2, &_npoints, &_cameraMatrix1, if( _Emat.needed() )
&_distCoeffs1, &_cameraMatrix2, &_distCoeffs2, imageSize, {
&matR, &matT, &matE, &matF, criteria, flags ); _Emat.create(3, 3, rtype);
p_matE = &(c_matE = _Emat.getMat());
}
if( _Fmat.needed() )
{
_Fmat.create(3, 3, rtype);
p_matF = &(c_matF = _Fmat.getMat());
} }
double err = cvStereoCalibrate(&c_objPt, &c_imgPt, &c_imgPt2, &c_npoints, &c_cameraMatrix1,
&c_distCoeffs1, &c_cameraMatrix2, &c_distCoeffs2, imageSize,
&c_matR, &c_matT, p_matE, p_matF, criteria, flags );
void cv::stereoRectify( const Mat& cameraMatrix1, const Mat& distCoeffs1, cameraMatrix1.copyTo(_cameraMatrix1);
const Mat& cameraMatrix2, const Mat& distCoeffs2, cameraMatrix2.copyTo(_cameraMatrix2);
Size imageSize, const Mat& R, const Mat& T, distCoeffs1.copyTo(_distCoeffs1);
Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q, distCoeffs2.copyTo(_distCoeffs2);
int flags )
{ return err;
int rtype = CV_64F; }
R1.create(3, 3, rtype);
R2.create(3, 3, rtype);
P1.create(3, 4, rtype); void cv::stereoRectify( const InputArray& _cameraMatrix1, const InputArray& _distCoeffs1,
P2.create(3, 4, rtype); const InputArray& _cameraMatrix2, const InputArray& _distCoeffs2,
Q.create(4, 4, rtype); Size imageSize, const InputArray& _Rmat, const InputArray& _Tmat,
CvMat _cameraMatrix1 = cameraMatrix1, _distCoeffs1 = distCoeffs1; OutputArray _Rmat1, OutputArray _Rmat2,
CvMat _cameraMatrix2 = cameraMatrix2, _distCoeffs2 = distCoeffs2; OutputArray _Pmat1, OutputArray _Pmat2,
CvMat matR = R, matT = T, _R1 = R1, _R2 = R2, _P1 = P1, _P2 = P2, matQ = Q; OutputArray _Qmat, int flags,
cvStereoRectify( &_cameraMatrix1, &_cameraMatrix2, &_distCoeffs1, &_distCoeffs2,
imageSize, &matR, &matT, &_R1, &_R2, &_P1, &_P2, &matQ, flags );
}
void cv::stereoRectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,
const Mat& cameraMatrix2, const Mat& distCoeffs2,
Size imageSize, const Mat& R, const Mat& T,
Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,
double alpha, Size newImageSize, double alpha, Size newImageSize,
Rect* validPixROI1, Rect* validPixROI2, Rect* validPixROI1, Rect* validPixROI2 )
int flags )
{ {
CvMat c_cameraMatrix1 = _cameraMatrix1.getMat();
CvMat c_cameraMatrix2 = _cameraMatrix2.getMat();
CvMat c_distCoeffs1 = _distCoeffs1.getMat();
CvMat c_distCoeffs2 = _distCoeffs2.getMat();
CvMat c_R = _Rmat.getMat(), c_T = _Tmat.getMat();
int rtype = CV_64F; int rtype = CV_64F;
R1.create(3, 3, rtype); _Rmat1.create(3, 3, rtype);
R2.create(3, 3, rtype); _Rmat2.create(3, 3, rtype);
P1.create(3, 4, rtype); _Pmat1.create(3, 4, rtype);
P2.create(3, 4, rtype); _Pmat2.create(3, 4, rtype);
Q.create(4, 4, rtype); CvMat c_R1 = _Rmat1.getMat(), c_R2 = _Rmat2.getMat(), c_P1 = _Pmat1.getMat(), c_P2 = _Pmat2.getMat();
CvMat _cameraMatrix1 = cameraMatrix1, _distCoeffs1 = distCoeffs1; CvMat c_Q, *p_Q = 0;
CvMat _cameraMatrix2 = cameraMatrix2, _distCoeffs2 = distCoeffs2;
CvMat matR = R, matT = T, _R1 = R1, _R2 = R2, _P1 = P1, _P2 = P2, matQ = Q; if( _Qmat.needed() )
cvStereoRectify( &_cameraMatrix1, &_cameraMatrix2, &_distCoeffs1, &_distCoeffs2, {
imageSize, &matR, &matT, &_R1, &_R2, &_P1, &_P2, &matQ, flags, _Qmat.create(4, 4, rtype);
alpha, newImageSize, (CvRect*)validPixROI1, (CvRect*)validPixROI2); p_Q = &(c_Q = _Qmat.getMat());
} }
bool cv::stereoRectifyUncalibrated( const Mat& points1, const Mat& points2, cvStereoRectify( &c_cameraMatrix1, &c_cameraMatrix2, &c_distCoeffs1, &c_distCoeffs2,
const Mat& F, Size imgSize, imageSize, &c_R, &c_T, &c_R1, &c_R2, &c_P1, &c_P2, p_Q, flags, alpha,
Mat& H1, Mat& H2, double threshold ) newImageSize, (CvRect*)validPixROI1, (CvRect*)validPixROI2);
}
bool cv::stereoRectifyUncalibrated( const InputArray& _points1, const InputArray& _points2,
const InputArray& _Fmat, Size imgSize,
OutputArray _Hmat1, OutputArray _Hmat2, double threshold )
{ {
int rtype = CV_64F; int rtype = CV_64F;
H1.create(3, 3, rtype); _Hmat1.create(3, 3, rtype);
H2.create(3, 3, rtype); _Hmat2.create(3, 3, rtype);
CvMat _pt1 = points1, _pt2 = points2, matF, *pF=0, _H1 = H1, _H2 = H2; Mat F = _Fmat.getMat();
CvMat c_pt1 = _points1.getMat(), c_pt2 = _points2.getMat();
CvMat c_F, *p_F=0, c_H1 = _Hmat1.getMat(), c_H2 = _Hmat2.getMat();
if( F.size() == Size(3, 3) ) if( F.size() == Size(3, 3) )
pF = &(matF = F); p_F = &(c_F = F);
return cvStereoRectifyUncalibrated(&_pt1, &_pt2, pF, imgSize, &_H1, &_H2, threshold) > 0; return cvStereoRectifyUncalibrated(&c_pt1, &c_pt2, p_F, imgSize, &c_H1, &c_H2, threshold) > 0;
} }
cv::Mat cv::getOptimalNewCameraMatrix( const Mat& cameraMatrix, const Mat& distCoeffs, cv::Mat cv::getOptimalNewCameraMatrix( const InputArray& _cameraMatrix,
const InputArray& _distCoeffs,
Size imgSize, double alpha, Size newImgSize, Size imgSize, double alpha, Size newImgSize,
Rect* validPixROI ) Rect* validPixROI )
{ {
Mat newCameraMatrix(3, 3, cameraMatrix.type()); CvMat c_cameraMatrix = _cameraMatrix.getMat(), c_distCoeffs = _distCoeffs.getMat();
CvMat _cameraMatrix = cameraMatrix,
_distCoeffs = distCoeffs, Mat newCameraMatrix(3, 3, CV_MAT_TYPE(c_cameraMatrix.type));
_newCameraMatrix = newCameraMatrix; CvMat c_newCameraMatrix = newCameraMatrix;
cvGetOptimalNewCameraMatrix(&_cameraMatrix, &_distCoeffs, imgSize,
alpha, &_newCameraMatrix, cvGetOptimalNewCameraMatrix(&c_cameraMatrix, &c_distCoeffs, imgSize,
alpha, &c_newCameraMatrix,
newImgSize, (CvRect*)validPixROI); newImgSize, (CvRect*)validPixROI);
return newCameraMatrix; return newCameraMatrix;
} }
void cv::RQDecomp3x3( const Mat& M, Mat& R, Mat& Q ) cv::Vec3d cv::RQDecomp3x3( const InputArray& _Mmat,
OutputArray _Rmat,
OutputArray _Qmat,
OutputArray _Qx,
OutputArray _Qy,
OutputArray _Qz )
{ {
R.create(3, 3, M.type()); Mat M = _Mmat.getMat();
Q.create(3, 3, M.type()); _Rmat.create(3, 3, M.type());
_Qmat.create(3, 3, M.type());
Vec3d eulerAngles;
CvMat matM = M, matR = R, matQ = Q; CvMat matM = M, matR = _Rmat.getMat(), matQ = _Qmat.getMat(), Qx, Qy, Qz, *pQx=0, *pQy=0, *pQz=0;
cvRQDecomp3x3(&matM, &matR, &matQ, 0, 0, 0, 0); if( _Qx.needed() )
{
_Qx.create(3, 3, M.type());
pQx = &(Qx = _Qx.getMat());
} }
if( _Qy.needed() )
cv::Vec3d cv::RQDecomp3x3( const Mat& M, Mat& R, Mat& Q,
Mat& Qx, Mat& Qy, Mat& Qz )
{ {
R.create(3, 3, M.type()); _Qy.create(3, 3, M.type());
Q.create(3, 3, M.type()); pQy = &(Qy = _Qy.getMat());
Vec3d eulerAngles; }
if( _Qz.needed() )
CvMat matM = M, matR = R, matQ = Q, _Qx = Qx, _Qy = Qy, _Qz = Qz; {
cvRQDecomp3x3(&matM, &matR, &matQ, &_Qx, &_Qy, &_Qz, (CvPoint3D64f*)&eulerAngles[0]); _Qz.create(3, 3, M.type());
pQz = &(Qz = _Qz.getMat());
}
cvRQDecomp3x3(&matM, &matR, &matQ, pQx, pQy, pQz, (CvPoint3D64f*)&eulerAngles[0]);
return eulerAngles; return eulerAngles;
} }
void cv::decomposeProjectionMatrix( const Mat& projMatrix, Mat& cameraMatrix, void cv::decomposeProjectionMatrix( const InputArray& _projMatrix, OutputArray _cameraMatrix,
Mat& rotMatrix, Mat& transVect ) OutputArray _rotMatrix, OutputArray _transVect,
OutputArray _rotMatrixX, OutputArray _rotMatrixY,
OutputArray _rotMatrixZ, OutputArray _eulerAngles )
{ {
Mat projMatrix = _projMatrix.getMat();
int type = projMatrix.type(); int type = projMatrix.type();
cameraMatrix.create(3, 3, type); _cameraMatrix.create(3, 3, type);
rotMatrix.create(3, 3, type); _rotMatrix.create(3, 3, type);
transVect.create(4, 1, type); _transVect.create(4, 1, type);
CvMat _projMatrix = projMatrix, _cameraMatrix = cameraMatrix; CvMat c_projMatrix = projMatrix, c_cameraMatrix = _cameraMatrix.getMat();
CvMat _rotMatrix = rotMatrix, _transVect = transVect; CvMat c_rotMatrix = _rotMatrix.getMat(), c_transVect = _transVect.getMat();
cvDecomposeProjectionMatrix(&_projMatrix, &_cameraMatrix, &_rotMatrix, CvMat c_rotMatrixX, *p_rotMatrixX = 0;
&_transVect, 0, 0, 0, 0); CvMat c_rotMatrixY, *p_rotMatrixY = 0;
} CvMat c_rotMatrixZ, *p_rotMatrixZ = 0;
CvPoint3D64f *p_eulerAngles = 0;
void cv::decomposeProjectionMatrix( const Mat& projMatrix, Mat& cameraMatrix, if( _rotMatrixX.needed() )
Mat& rotMatrix, Mat& transVect,
Mat& rotMatrixX, Mat& rotMatrixY,
Mat& rotMatrixZ, Vec3d& eulerAngles )
{ {
int type = projMatrix.type(); _rotMatrixX.create(3, 3, type);
cameraMatrix.create(3, 3, type); p_rotMatrixX = &(c_rotMatrixX = _rotMatrixX.getMat());
rotMatrix.create(3, 3, type); }
transVect.create(4, 1, type); if( _rotMatrixY.needed() )
rotMatrixX.create(3, 3, type); {
rotMatrixY.create(3, 3, type); _rotMatrixY.create(3, 3, type);
rotMatrixZ.create(3, 3, type); p_rotMatrixY = &(c_rotMatrixY = _rotMatrixY.getMat());
CvMat _projMatrix = projMatrix, _cameraMatrix = cameraMatrix; }
CvMat _rotMatrix = rotMatrix, _transVect = transVect; if( _rotMatrixZ.needed() )
CvMat _rotMatrixX = rotMatrixX, _rotMatrixY = rotMatrixY; {
CvMat _rotMatrixZ = rotMatrixZ; _rotMatrixZ.create(3, 3, type);
cvDecomposeProjectionMatrix(&_projMatrix, &_cameraMatrix, &_rotMatrix, p_rotMatrixZ = &(c_rotMatrixZ = _rotMatrixZ.getMat());
&_transVect, &_rotMatrixX, &_rotMatrixY, }
&_rotMatrixZ, (CvPoint3D64f*)&eulerAngles[0]); if( _eulerAngles.needed() )
{
_eulerAngles.create(3, 1, CV_64F, -1, true);
p_eulerAngles = (CvPoint3D64f*)_eulerAngles.getMat().data;
}
cvDecomposeProjectionMatrix(&c_projMatrix, &c_cameraMatrix, &c_rotMatrix,
&c_transVect, p_rotMatrixX, p_rotMatrixY,
p_rotMatrixZ, p_eulerAngles);
} }
namespace cv namespace cv
{ {
static void adjust3rdMatrix(const vector<vector<Point2f> >& imgpt1_0, static void adjust3rdMatrix(const InputArrayOfArrays& _imgpt1_0,
const vector<vector<Point2f> >& imgpt3_0, const InputArrayOfArrays& _imgpt3_0,
const Mat& cameraMatrix1, const Mat& distCoeffs1, const Mat& cameraMatrix1, const Mat& distCoeffs1,
const Mat& cameraMatrix3, const Mat& distCoeffs3, const Mat& cameraMatrix3, const Mat& distCoeffs3,
const Mat& R1, const Mat& R3, const Mat& P1, Mat& P3 ) const Mat& R1, const Mat& R3, const Mat& P1, Mat& P3 )
{ {
size_t n1 = _imgpt1_0.total(), n3 = _imgpt3_0.total();
vector<Point2f> imgpt1, imgpt3; vector<Point2f> imgpt1, imgpt3;
for( int i = 0; i < (int)std::min(imgpt1_0.size(), imgpt3_0.size()); i++ ) for( int i = 0; i < (int)std::min(n1, n3); i++ )
{
if( !imgpt1_0[i].empty() && !imgpt3_0[i].empty() )
{ {
std::copy(imgpt1_0[i].begin(), imgpt1_0[i].end(), std::back_inserter(imgpt1)); Mat pt1 = _imgpt1_0.getMat(i), pt3 = _imgpt3_0.getMat(i);
std::copy(imgpt3_0[i].begin(), imgpt3_0[i].end(), std::back_inserter(imgpt3)); int ni1 = pt1.checkVector(2, CV_32F), ni3 = pt3.checkVector(2, CV_32F);
} CV_Assert( ni1 > 0 && ni1 == ni3 );
const Point2f* pt1data = pt1.ptr<Point2f>();
const Point2f* pt3data = pt3.ptr<Point2f>();
std::copy(pt1data, pt1data + ni1, std::back_inserter(imgpt1));
std::copy(pt3data, pt3data + ni3, std::back_inserter(imgpt3));
} }
undistortPoints(Mat(imgpt1), imgpt1, cameraMatrix1, distCoeffs1, R1, P1); undistortPoints(imgpt1, imgpt1, cameraMatrix1, distCoeffs1, R1, P1);
undistortPoints(Mat(imgpt3), imgpt3, cameraMatrix3, distCoeffs3, R3, P3); undistortPoints(imgpt3, imgpt3, cameraMatrix3, distCoeffs3, R3, P3);
double y1_ = 0, y2_ = 0, y1y1_ = 0, y1y2_ = 0; double y1_ = 0, y2_ = 0, y1y1_ = 0, y1y2_ = 0;
size_t n = imgpt1.size(); size_t n = imgpt1.size();
@ -3555,20 +3642,31 @@ static void adjust3rdMatrix(const vector<vector<Point2f> >& imgpt1_0,
} }
float cv::rectify3Collinear( const Mat& cameraMatrix1, const Mat& distCoeffs1, float cv::rectify3Collinear( const InputArray& _cameraMatrix1, const InputArray& _distCoeffs1,
const Mat& cameraMatrix2, const Mat& distCoeffs2, const InputArray& _cameraMatrix2, const InputArray& _distCoeffs2,
const Mat& cameraMatrix3, const Mat& distCoeffs3, const InputArray& _cameraMatrix3, const InputArray& _distCoeffs3,
const vector<vector<Point2f> >& imgpt1, const InputArrayOfArrays& _imgpt1,
const vector<vector<Point2f> >& imgpt3, const InputArrayOfArrays& _imgpt3,
Size imageSize, const Mat& R12, const Mat& T12, const Mat& R13, const Mat& T13, Size imageSize, const InputArray& _Rmat12, const InputArray& _Tmat12,
Mat& R1, Mat& R2, Mat& R3, Mat& P1, Mat& P2, Mat& P3, Mat& Q, const InputArray& _Rmat13, const InputArray& _Tmat13,
OutputArray _Rmat1, OutputArray _Rmat2, OutputArray _Rmat3,
OutputArray _Pmat1, OutputArray _Pmat2, OutputArray _Pmat3,
OutputArray _Qmat,
double alpha, Size /*newImgSize*/, double alpha, Size /*newImgSize*/,
Rect* roi1, Rect* roi2, int flags ) Rect* roi1, Rect* roi2, int flags )
{ {
// first, rectify the 1-2 stereo pair // first, rectify the 1-2 stereo pair
stereoRectify( cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, stereoRectify( _cameraMatrix1, _distCoeffs1, _cameraMatrix2, _distCoeffs2,
imageSize, R12, T12, R1, R2, P1, P2, Q, imageSize, _Rmat12, _Tmat12, _Rmat1, _Rmat2, _Pmat1, _Pmat2, _Qmat,
alpha, imageSize, roi1, roi2, flags ); flags, alpha, imageSize, roi1, roi2 );
Mat R12 = _Rmat12.getMat(), R13 = _Rmat13.getMat(), T12 = _Tmat12.getMat(), T13 = _Tmat13.getMat();
_Rmat3.create(3, 3, CV_64F);
_Pmat3.create(3, 4, CV_64F);
Mat P1 = _Pmat1.getMat(), P2 = _Pmat2.getMat();
Mat R3 = _Rmat3.getMat(), P3 = _Pmat3.getMat();
// recompute rectification transforms for cameras 1 & 2. // recompute rectification transforms for cameras 1 & 2.
Mat om, r_r, r_r13; Mat om, r_r, r_r13;
@ -3608,8 +3706,9 @@ float cv::rectify3Collinear( const Mat& cameraMatrix1, const Mat& distCoeffs1,
P3.at<double>(0,3) *= P3.at<double>(0,0); P3.at<double>(0,3) *= P3.at<double>(0,0);
P3.at<double>(1,3) *= P3.at<double>(1,1); P3.at<double>(1,3) *= P3.at<double>(1,1);
if( !imgpt1.empty() && imgpt3.empty() ) if( !_imgpt1.empty() && _imgpt3.empty() )
adjust3rdMatrix(imgpt1, imgpt3, cameraMatrix1, distCoeffs1, cameraMatrix3, distCoeffs3, R1, R3, P1, P3); adjust3rdMatrix(_imgpt1, _imgpt3, _cameraMatrix1.getMat(), _distCoeffs1.getMat(),
_cameraMatrix3.getMat(), _distCoeffs3.getMat(), _Rmat1.getMat(), R3, P1, P3);
return (float)((P3.at<double>(idx,3)/P3.at<double>(idx,idx))/ return (float)((P3.at<double>(idx,3)/P3.at<double>(idx,idx))/
(P2.at<double>(idx,3)/P2.at<double>(idx,idx))); (P2.at<double>(idx,3)/P2.at<double>(idx,idx)));

8
modules/calib3d/src/circlesgrid.cpp
Unescape View File

@ -280,9 +280,9 @@ void CirclesGridClusterFinder::rectifyPatternPoints(const cv::Size &patternSize,
Mat homography = findHomography(Mat(sortedCorners), Mat(idealPoints), 0); Mat homography = findHomography(Mat(sortedCorners), Mat(idealPoints), 0);
Mat rectifiedPointsMat; Mat rectifiedPointsMat;
transform(Mat(patternPoints), rectifiedPointsMat, homography); transform(patternPoints, rectifiedPointsMat, homography);
rectifiedPatternPoints.clear(); rectifiedPatternPoints.clear();
convertPointsHomogeneous(rectifiedPointsMat, rectifiedPatternPoints); convertPointsFromHomogeneous(rectifiedPointsMat, rectifiedPatternPoints);
} }
void CirclesGridClusterFinder::parsePatternPoints(const cv::Size &patternSize, const std::vector<cv::Point2f> &patternPoints, const std::vector<cv::Point2f> &rectifiedPatternPoints, std::vector<cv::Point2f> &centers) void CirclesGridClusterFinder::parsePatternPoints(const cv::Size &patternSize, const std::vector<cv::Point2f> &patternPoints, const std::vector<cv::Point2f> &rectifiedPatternPoints, std::vector<cv::Point2f> &centers)
@ -727,7 +727,7 @@ Mat CirclesGridFinder::rectifyGrid(Size detectedGridSize, const vector<Point2f>&
Mat dstKeypointsMat; Mat dstKeypointsMat;
transform(Mat(srcKeypoints), dstKeypointsMat, H); transform(Mat(srcKeypoints), dstKeypointsMat, H);
vector<Point2f> dstKeypoints; vector<Point2f> dstKeypoints;
convertPointsHomogeneous(dstKeypointsMat, dstKeypoints); convertPointsFromHomogeneous(dstKeypointsMat, dstKeypoints);
warpedKeypoints.clear(); warpedKeypoints.clear();
for (size_t i = 0; i < dstKeypoints.size(); i++) for (size_t i = 0; i < dstKeypoints.size(); i++)
@ -969,7 +969,7 @@ void CirclesGridFinder::findBasis(const vector<Point2f> &samples, vector<Point2f
Mat centers; Mat centers;
const int clustersCount = 4; const int clustersCount = 4;
kmeans(Mat(samples).reshape(1, 0), clustersCount, bestLabels, termCriteria, parameters.kmeansAttempts, kmeans(Mat(samples).reshape(1, 0), clustersCount, bestLabels, termCriteria, parameters.kmeansAttempts,
KMEANS_RANDOM_CENTERS, &centers); KMEANS_RANDOM_CENTERS, centers);
assert( centers.type() == CV_32FC1 ); assert( centers.type() == CV_32FC1 );
vector<int> basisIndices; vector<int> basisIndices;

129
modules/calib3d/src/fundam.cpp
Unescape View File

@ -1044,114 +1044,95 @@ CV_IMPL void cvConvertPointsHomogeneous( const CvMat* src, CvMat* dst )
} }
} }
namespace cv cv::Mat cv::findHomography( const InputArray& _points1, const InputArray& _points2,
int method, double ransacReprojThreshold, OutputArray _mask )
{ {
Mat points1 = _points1.getMat(), points2 = _points2.getMat();
static Mat _findHomography( const Mat& points1, const Mat& points2, int npoints = points1.checkVector(2);
int method, double ransacReprojThreshold, CV_Assert( npoints >= 0 && points2.checkVector(2) == npoints &&
vector<uchar>* mask ) points1.type() == points2.type());
{
CV_Assert(points1.isContinuous() && points2.isContinuous() &&
points1.type() == points2.type() &&
((points1.rows == 1 && points1.channels() == 2) ||
points1.cols*points1.channels() == 2) &&
((points2.rows == 1 && points2.channels() == 2) ||
points2.cols*points2.channels() == 2));
Mat H(3, 3, CV_64F); Mat H(3, 3, CV_64F);
CvMat _pt1 = Mat(points1), _pt2 = Mat(points2); CvMat _pt1 = points1, _pt2 = points2;
CvMat matH = H, _mask, *pmask = 0; CvMat matH = H, c_mask, *p_mask = 0;
if( mask ) if( _mask.needed() )
{ {
mask->resize(points1.cols*points1.rows*points1.channels()/2); _mask.create(npoints, 1, CV_8U, -1, true);
pmask = &(_mask = cvMat(1, (int)mask->size(), CV_8U, (void*)&(*mask)[0])); p_mask = &(c_mask = _mask.getMat());
} }
bool ok = cvFindHomography( &_pt1, &_pt2, &matH, method, ransacReprojThreshold, pmask ) > 0; bool ok = cvFindHomography( &_pt1, &_pt2, &matH, method, ransacReprojThreshold, p_mask ) > 0;
if( !ok ) if( !ok )
H = Scalar(0); H = Scalar(0);
return H; return H;
} }
static Mat _findFundamentalMat( const Mat& points1, const Mat& points2, cv::Mat cv::findFundamentalMat( const InputArray& _points1, const InputArray& _points2,
int method, double param1, double param2, int method, double param1, double param2,
vector<uchar>* mask ) OutputArray _mask )
{ {
CV_Assert(points1.checkVector(2) >= 0 && points2.checkVector(2) >= 0 && Mat points1 = _points1.getMat(), points2 = _points2.getMat();
(points1.depth() == CV_32F || points1.depth() == CV_32S) && int npoints = points1.checkVector(2);
points1.depth() == points2.depth()); CV_Assert( npoints >= 0 && points2.checkVector(2) == npoints &&
points1.type() == points2.type());
Mat F(3, 3, CV_64F); Mat F(3, 3, CV_64F);
CvMat _pt1 = Mat(points1), _pt2 = Mat(points2); CvMat _pt1 = points1, _pt2 = points2;
CvMat matF = F, _mask, *pmask = 0; CvMat matF = F, c_mask, *p_mask = 0;
if( mask ) if( _mask.needed() )
{ {
mask->resize(points1.cols*points1.rows*points1.channels()/2); _mask.create(npoints, 1, CV_8U, -1, true);
pmask = &(_mask = cvMat(1, (int)mask->size(), CV_8U, (void*)&(*mask)[0])); p_mask = &(c_mask = _mask.getMat());
} }
int n = cvFindFundamentalMat( &_pt1, &_pt2, &matF, method, param1, param2, pmask ); int n = cvFindFundamentalMat( &_pt1, &_pt2, &matF, method, param1, param2, p_mask );
if( n <= 0 ) if( n <= 0 )
F = Scalar(0); F = Scalar(0);
return F; return F;
} }
} void cv::computeCorrespondEpilines( const InputArray& _points, int whichImage,
const InputArray& _Fmat, OutputArray _lines )
cv::Mat cv::findHomography( const Mat& srcPoints, const Mat& dstPoints,
vector<uchar>& mask, int method,
double ransacReprojThreshold )
{ {
return _findHomography(srcPoints, dstPoints, method, ransacReprojThreshold, &mask); Mat points = _points.getMat();
} int npoints = points.checkVector(2);
CV_Assert( npoints >= 0 && (points.depth() == CV_32F || points.depth() == CV_32S));
cv::Mat cv::findHomography( const Mat& srcPoints, const Mat& dstPoints, _lines.create(npoints, 1, CV_32FC3, -1, true);
int method, double ransacReprojThreshold ) CvMat c_points = points, c_lines = _lines.getMat(), c_F = _Fmat.getMat();
{ cvComputeCorrespondEpilines(&c_points, whichImage, &c_F, &c_lines);
return _findHomography(srcPoints, dstPoints, method, ransacReprojThreshold, 0);
} }
void cv::convertPointsFromHomogeneous( const InputArray& _src, OutputArray _dst )
cv::Mat cv::findFundamentalMat( const Mat& points1, const Mat& points2,
vector<uchar>& mask, int method, double param1, double param2 )
{ {
return _findFundamentalMat( points1, points2, method, param1, param2, &mask ); Mat src = _src.getMat();
} int npoints = src.checkVector(3), cn = 3;
if( npoints < 0 )
cv::Mat cv::findFundamentalMat( const Mat& points1, const Mat& points2,
int method, double param1, double param2 )
{ {
return _findFundamentalMat( points1, points2, method, param1, param2, 0 ); npoints = src.checkVector(4);
if( npoints >= 0 )
cn = 4;
} }
CV_Assert( npoints >= 0 && (src.depth() == CV_32F || src.depth() == CV_32S));
void cv::computeCorrespondEpilines( const Mat& points, int whichImage, _dst.create(npoints, 1, CV_MAKETYPE(CV_32F, cn-1));
const Mat& F, vector<Vec3f>& lines ) CvMat c_src = src, c_dst = _dst.getMat();
{ cvConvertPointsHomogeneous(&c_src, &c_dst);
CV_Assert(points.checkVector(2) >= 0 &&
(points.depth() == CV_32F || points.depth() == CV_32S));
lines.resize(points.cols*points.rows*points.channels()/2);
CvMat _points = points, _lines = Mat(lines), matF = F;
cvComputeCorrespondEpilines(&_points, whichImage, &matF, &_lines);
} }
void cv::convertPointsHomogeneous( const Mat& src, vector<Point3f>& dst ) void cv::convertPointsToHomogeneous( const InputArray& _src, OutputArray _dst )
{ {
int srccn = src.checkVector(2) >= 0 ? 2 : src.checkVector(4) >= 0 ? 4 : -1; Mat src = _src.getMat();
CV_Assert( srccn > 0 && (src.depth() == CV_32F || src.depth() == CV_32S)); int npoints = src.checkVector(2), cn = 2;
if( npoints < 0 )
dst.resize(src.cols*src.rows*src.channels()/srccn);
CvMat _src = src, _dst = Mat(dst);
cvConvertPointsHomogeneous(&_src, &_dst);
}
void cv::convertPointsHomogeneous( const Mat& src, vector<Point2f>& dst )
{ {
CV_Assert(src.checkVector(3) >= 0 && npoints = src.checkVector(3);
(src.depth() == CV_32F || src.depth() == CV_32S)); if( npoints >= 0 )
cn = 3;
}
CV_Assert( npoints >= 0 && (src.depth() == CV_32F || src.depth() == CV_32S));
dst.resize(src.cols*src.rows*src.channels()/3); _dst.create(npoints, 1, CV_MAKETYPE(CV_32F, cn+1));
CvMat _src = Mat(src), _dst = Mat(dst); CvMat c_src = src, c_dst = _dst.getMat();
cvConvertPointsHomogeneous(&_src, &_dst); cvConvertPointsHomogeneous(&c_src, &c_dst);
} }
/* End of file. */ /* End of file. */

34
modules/calib3d/src/modelest.cpp
Unescape View File

@ -452,30 +452,30 @@ bool cv::Affine3DEstimator::checkSubset( const CvMat* ms1, int count )
return j == i; return j == i;
} }
int cv::estimateAffine3D(const Mat& from, const Mat& to, Mat& out, vector<uchar>& outliers, double param1, double param2) int cv::estimateAffine3D(const InputArray& _from, const InputArray& _to,
OutputArray _out, OutputArray _outliers,
double param1, double param2)
{ {
int count = from.cols*from.rows*from.channels()/3; Mat from = _from.getMat(), to = _to.getMat();
int count = from.checkVector(3, CV_32F);
CV_Assert( count >= 4 && from.isContinuous() && to.isContinuous() && CV_Assert( count >= 0 && to.checkVector(3, CV_32F) == count );
from.depth() == CV_32F && to.depth() == CV_32F &&
((from.rows == 1 && from.channels() == 3) || from.cols*from.channels() == 3) &&
((to.rows == 1 && to.channels() == 3) || to.cols*to.channels() == 3) &&
count == to.cols*to.rows*to.channels()/3);
out.create(3, 4, CV_64F); _out.create(3, 4, CV_64F);
outliers.resize(count); Mat out = _out.getMat();
fill(outliers.begin(), outliers.end(), (uchar)1);
vector<Point3d> dFrom; _outliers.create(count, 1, CV_8U, -1, true);
vector<Point3d> dTo; Mat outliers = _outliers.getMat();
outliers = Scalar::all(1);
copy(from.ptr<Point3f>(), from.ptr<Point3f>() + count, back_inserter(dFrom)); Mat dFrom, dTo;
copy(to.ptr<Point3f>(), to.ptr<Point3f>() + count, back_inserter(dTo)); from.convertTo(dFrom, CV_64F);
to.convertTo(dTo, CV_64F);
CvMat F3x4 = out; CvMat F3x4 = out;
CvMat mask = cvMat( 1, count, CV_8U, &outliers[0] ); CvMat mask = outliers;
CvMat m1 = cvMat( 1, count, CV_64FC3, &dFrom[0] ); CvMat m1 = dFrom;
CvMat m2 = cvMat( 1, count, CV_64FC3, &dTo[0] ); CvMat m2 = dTo;
const double epsilon = numeric_limits<double>::epsilon(); const double epsilon = numeric_limits<double>::epsilon();
param1 = param1 <= 0 ? 3 : param1; param1 = param1 <= 0 ? 3 : param1;

12
modules/calib3d/src/quadsubpix.cpp
Unescape View File

@ -224,8 +224,14 @@ int segment_hist_max(const Mat& hist, int& low_thresh, int& high_thresh)
} }
} }
bool find4QuadCornerSubpix(const Mat& img, std::vector<Point2f>& corners, Size region_size) }
bool cv::find4QuadCornerSubpix(const InputArray& _img, InputOutputArray _corners, Size region_size)
{ {
Mat img = _img.getMat(), cornersM = _corners.getMat();
int ncorners = cornersM.checkVector(2, CV_32F);
CV_Assert( ncorners >= 0 );
Point2f* corners = cornersM.ptr<Point2f>();
const int nbins = 256; const int nbins = 256;
float ranges[] = {0, 256}; float ranges[] = {0, 256};
const float* _ranges = ranges; const float* _ranges = ranges;
@ -238,7 +244,7 @@ bool find4QuadCornerSubpix(const Mat& img, std::vector<Point2f>& corners, Size r
Mat black_comp, white_comp; Mat black_comp, white_comp;
for(size_t i = 0; i < corners.size(); i++) for(int i = 0; i < ncorners; i++)
{ {
int channels = 0; int channels = 0;
Rect roi(cvRound(corners[i].x - region_size.width), cvRound(corners[i].y - region_size.height), Rect roi(cvRound(corners[i].x - region_size.width), cvRound(corners[i].y - region_size.height),
@ -362,5 +368,3 @@ bool find4QuadCornerSubpix(const Mat& img, std::vector<Point2f>& corners, Size r
return true; return true;
} }
}; // namespace std

65
modules/calib3d/src/solvepnp.cpp
Unescape View File

@ -43,25 +43,22 @@
#include "precomp.hpp" #include "precomp.hpp"
using namespace cv; using namespace cv;
void cv::solvePnP( const Mat& opoints, const Mat& ipoints, void cv::solvePnP( const InputArray& _opoints, const InputArray& _ipoints,
const Mat& cameraMatrix, const Mat& distCoeffs, const InputArray& _cameraMatrix, const InputArray& _distCoeffs,
Mat& rvec, Mat& tvec, bool useExtrinsicGuess ) OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess )
{ {
CV_Assert(opoints.isContinuous() && opoints.depth() == CV_32F && Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
((opoints.rows == 1 && opoints.channels() == 3) || int npoints = opoints.checkVector(3, CV_32F);
opoints.cols*opoints.channels() == 3) && CV_Assert( npoints >= 0 && npoints == ipoints.checkVector(2, CV_32F) );
ipoints.isContinuous() && ipoints.depth() == CV_32F &&
((ipoints.rows == 1 && ipoints.channels() == 2) || _rvec.create(3, 1, CV_64F);
ipoints.cols*ipoints.channels() == 2)); _tvec.create(3, 1, CV_64F);
CvMat c_objectPoints = opoints, c_imagePoints = ipoints;
rvec.create(3, 1, CV_64F); CvMat c_cameraMatrix = _cameraMatrix.getMat(), c_distCoeffs = _distCoeffs.getMat();
tvec.create(3, 1, CV_64F); CvMat c_rvec = _rvec.getMat(), c_tvec = _tvec.getMat();
CvMat _objectPoints = opoints, _imagePoints = ipoints; cvFindExtrinsicCameraParams2(&c_objectPoints, &c_imagePoints, &c_cameraMatrix,
CvMat _cameraMatrix = cameraMatrix, _distCoeffs = distCoeffs; c_distCoeffs.rows*c_distCoeffs.cols ? &c_distCoeffs : 0,
CvMat _rvec = rvec, _tvec = tvec; &c_rvec, &c_tvec, useExtrinsicGuess );
cvFindExtrinsicCameraParams2(&_objectPoints, &_imagePoints, &_cameraMatrix,
distCoeffs.data ? &_distCoeffs : 0,
&_rvec, &_tvec, useExtrinsicGuess );
} }
namespace cv namespace cv
@ -172,7 +169,7 @@ namespace cv
project3dPoints(objectPoints, localRvec, localTvec, rotatedPoints); project3dPoints(objectPoints, localRvec, localTvec, rotatedPoints);
vector<int> localInliers; vector<int> localInliers;
for (size_t i = 0; i < objectPoints.cols; i++) for (int i = 0; i < objectPoints.cols; i++)
{ {
Point2f p(imagePoints.at<Vec2f>(0, i)[0], imagePoints.at<Vec2f>(0, i)[1]); Point2f p(imagePoints.at<Vec2f>(0, i)[0], imagePoints.at<Vec2f>(0, i)[1]);
if ((norm(p - projected_points[i]) < params.reprojectionError) if ((norm(p - projected_points[i]) < params.reprojectionError)
@ -203,7 +200,7 @@ namespace cv
{ {
vector<char> pointsMask(objectPoints.cols, 0); vector<char> pointsMask(objectPoints.cols, 0);
memset(&pointsMask[0], 1, MIN_POINTS_COUNT ); memset(&pointsMask[0], 1, MIN_POINTS_COUNT );
for( size_t i=r.begin(); i!=r.end(); ++i ) for( int i=r.begin(); i!=r.end(); ++i )
{ {
generateVar(pointsMask); generateVar(pointsMask);
pnpTask(pointsMask, objectPoints, imagePoints, parameters, pnpTask(pointsMask, objectPoints, imagePoints, parameters,
@ -230,8 +227,8 @@ namespace cv
const Mat& objectPoints; const Mat& objectPoints;
const Mat& imagePoints; const Mat& imagePoints;
const Parameters& parameters; const Parameters& parameters;
vector<int>& inliers;
Mat &rvec, &tvec; Mat &rvec, &tvec;
vector<int>& inliers;
Mat initRvec, initTvec; Mat initRvec, initTvec;
static RNG generator; static RNG generator;
@ -257,10 +254,14 @@ namespace cv
} }
} }
void cv::solvePnPRansac(const Mat& opoints, const Mat& ipoints, void cv::solvePnPRansac(const InputArray& _opoints, const InputArray& _ipoints,
const Mat& cameraMatrix, const Mat& distCoeffs, Mat& rvec, Mat& tvec, bool useExtrinsicGuess, const InputArray& _cameraMatrix, const InputArray& _distCoeffs,
int iterationsCount, float reprojectionError, int minInliersCount, vector<int>* inliers) OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess,
int iterationsCount, float reprojectionError, int minInliersCount,
OutputArray _inliers)
{ {
Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();
CV_Assert(opoints.isContinuous()); CV_Assert(opoints.isContinuous());
CV_Assert(opoints.depth() == CV_32F); CV_Assert(opoints.depth() == CV_32F);
@ -269,8 +270,10 @@ void cv::solvePnPRansac(const Mat& opoints, const Mat& ipoints,
CV_Assert(ipoints.depth() == CV_32F); CV_Assert(ipoints.depth() == CV_32F);
CV_Assert((ipoints.rows == 1 && ipoints.channels() == 2) || ipoints.cols*ipoints.channels() == 2); CV_Assert((ipoints.rows == 1 && ipoints.channels() == 2) || ipoints.cols*ipoints.channels() == 2);
rvec.create(3, 1, CV_64FC1); _rvec.create(3, 1, CV_64FC1);
tvec.create(3, 1, CV_64FC1); _tvec.create(3, 1, CV_64FC1);
Mat rvec = _rvec.getMat();
Mat tvec = _tvec.getMat();
Mat objectPoints = opoints.reshape(3, 1), imagePoints = ipoints.reshape(2, 1); Mat objectPoints = opoints.reshape(3, 1), imagePoints = ipoints.reshape(2, 1);
@ -294,7 +297,7 @@ void cv::solvePnPRansac(const Mat& opoints, const Mat& ipoints,
localRvec, localTvec, localInliers)); localRvec, localTvec, localInliers));
} }
if (localInliers.size() >= pnpransac::MIN_POINTS_COUNT) if (localInliers.size() >= (size_t)pnpransac::MIN_POINTS_COUNT)
{ {
size_t pointsCount = localInliers.size(); size_t pointsCount = localInliers.size();
Mat inlierObjectPoints(1, pointsCount, CV_32FC3), inlierImagePoints(1, pointsCount, CV_32FC2); Mat inlierObjectPoints(1, pointsCount, CV_32FC3), inlierImagePoints(1, pointsCount, CV_32FC2);
@ -310,14 +313,16 @@ void cv::solvePnPRansac(const Mat& opoints, const Mat& ipoints,
solvePnP(inlierObjectPoints, inlierImagePoints, params.camera.intrinsics, params.camera.distortion, localRvec, localTvec, true); solvePnP(inlierObjectPoints, inlierImagePoints, params.camera.intrinsics, params.camera.distortion, localRvec, localTvec, true);
localRvec.copyTo(rvec); localRvec.copyTo(rvec);
localTvec.copyTo(tvec); localTvec.copyTo(tvec);
if (inliers) if (_inliers.needed())
*inliers = localInliers; Mat(localInliers).copyTo(_inliers);
} }
else else
{ {
tvec.setTo(Scalar(0)); tvec.setTo(Scalar(0));
Mat R = Mat::ones(3, 3, CV_64F); Mat R = Mat::eye(3, 3, CV_64F);
Rodrigues(R, rvec); Rodrigues(R, rvec);
if( _inliers.needed() )
_inliers.release();
} }
return; return;
} }

7
modules/calib3d/src/stereobm.cpp
Unescape View File

@ -920,10 +920,13 @@ void StereoBM::init(int _preset, int _ndisparities, int _SADWindowSize)
state->SADWindowSize = _SADWindowSize; state->SADWindowSize = _SADWindowSize;
} }
void StereoBM::operator()( const Mat& left, const Mat& right, Mat& disparity, int disptype ) void StereoBM::operator()( const InputArray& _left, const InputArray& _right,
OutputArray _disparity, int disptype )
{ {
Mat left = _left.getMat(), right = _right.getMat();
CV_Assert( disptype == CV_16S || disptype == CV_32F ); CV_Assert( disptype == CV_16S || disptype == CV_32F );
disparity.create(left.size(), disptype); _disparity.create(left.size(), disptype);
Mat disparity = _disparity.getMat();
findStereoCorrespondenceBM(left, right, disparity, state); findStereoCorrespondenceBM(left, right, disparity, state);
} }

84
modules/calib3d/src/stereosgbm.cpp
Unescape View File

@ -819,8 +819,49 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
typedef cv::Point_<short> Point2s; typedef cv::Point_<short> Point2s;
void filterSpeckles( Mat& img, double _newval, int maxSpeckleSize, double _maxDiff, Mat& _buf ) void StereoSGBM::operator ()( const InputArray& _left, const InputArray& _right,
OutputArray _disp )
{ {
Mat left = _left.getMat(), right = _right.getMat();
CV_Assert( left.size() == right.size() && left.type() == right.type() &&
left.depth() == DataType<PixType>::depth );
_disp.create( left.size(), CV_16S );
Mat disp = _disp.getMat();
computeDisparitySGBM( left, right, disp, *this, buffer );
medianBlur(disp, disp, 3);
if( speckleWindowSize > 0 )
filterSpeckles(disp, (minDisparity - 1)*DISP_SCALE, speckleWindowSize, DISP_SCALE*speckleRange, buffer);
}
Rect getValidDisparityROI( Rect roi1, Rect roi2,
int minDisparity,
int numberOfDisparities,
int SADWindowSize )
{
int SW2 = SADWindowSize/2;
int minD = minDisparity, maxD = minDisparity + numberOfDisparities - 1;
int xmin = max(roi1.x, roi2.x + maxD) + SW2;
int xmax = min(roi1.x + roi1.width, roi2.x + roi2.width - minD) - SW2;
int ymin = max(roi1.y, roi2.y) + SW2;
int ymax = min(roi1.y + roi1.height, roi2.y + roi2.height) - SW2;
Rect r(xmin, ymin, xmax - xmin, ymax - ymin);
return r.width > 0 && r.height > 0 ? r : Rect();
}
}
void cv::filterSpeckles( InputOutputArray _img, double _newval, int maxSpeckleSize,
double _maxDiff, InputOutputArray __buf )
{
Mat img = _img.getMat();
Mat temp, &_buf = __buf.needed() ? __buf.getMatRef() : temp;
CV_Assert( img.type() == CV_16SC1 ); CV_Assert( img.type() == CV_16SC1 );
int newVal = cvRound(_newval); int newVal = cvRound(_newval);
@ -917,43 +958,10 @@ void filterSpeckles( Mat& img, double _newval, int maxSpeckleSize, double _maxDi
} }
} }
void cv::validateDisparity( InputOutputArray _disp, const InputArray& _cost, int minDisparity,
void StereoSGBM::operator ()( const Mat& left, const Mat& right, Mat& disp ) int numberOfDisparities, int disp12MaxDiff )
{
CV_Assert( left.size() == right.size() && left.type() == right.type() &&
left.depth() == DataType<PixType>::depth );
disp.create( left.size(), CV_16S );
computeDisparitySGBM( left, right, disp, *this, buffer );
medianBlur(disp, disp, 3);
if( speckleWindowSize > 0 )
filterSpeckles(disp, (minDisparity - 1)*DISP_SCALE, speckleWindowSize, DISP_SCALE*speckleRange, buffer);
}
Rect getValidDisparityROI( Rect roi1, Rect roi2,
int minDisparity,
int numberOfDisparities,
int SADWindowSize )
{
int SW2 = SADWindowSize/2;
int minD = minDisparity, maxD = minDisparity + numberOfDisparities - 1;
int xmin = max(roi1.x, roi2.x + maxD) + SW2;
int xmax = min(roi1.x + roi1.width, roi2.x + roi2.width - minD) - SW2;
int ymin = max(roi1.y, roi2.y) + SW2;
int ymax = min(roi1.y + roi1.height, roi2.y + roi2.height) - SW2;
Rect r(xmin, ymin, xmax - xmin, ymax - ymin);
return r.width > 0 && r.height > 0 ? r : Rect();
}
void validateDisparity( Mat& disp, const Mat& cost, int minDisparity, int numberOfDisparities, int disp12MaxDiff )
{ {
Mat disp = _disp.getMat(), cost = _cost.getMat();
int cols = disp.cols, rows = disp.rows; int cols = disp.cols, rows = disp.rows;
int minD = minDisparity, maxD = minDisparity + numberOfDisparities; int minD = minDisparity, maxD = minDisparity + numberOfDisparities;
int x, minX1 = max(maxD, 0), maxX1 = cols + min(minD, 0); int x, minX1 = max(maxD, 0), maxX1 = cols + min(minD, 0);
@ -1031,8 +1039,6 @@ void validateDisparity( Mat& disp, const Mat& cost, int minDisparity, int number
} }
} }
}
CvRect cvGetValidDisparityROI( CvRect roi1, CvRect roi2, int minDisparity, CvRect cvGetValidDisparityROI( CvRect roi1, CvRect roi2, int minDisparity,
int numberOfDisparities, int SADWindowSize ) int numberOfDisparities, int SADWindowSize )
{ {

11
modules/calib3d/test/test_cameracalibration.cpp
Unescape View File

@ -1244,8 +1244,13 @@ void CV_ProjectPointsTest_CPP::project( const Mat& objectPoints, const Mat& rvec
const Mat& cameraMatrix, const Mat& distCoeffs, vector<Point2f>& imagePoints, const Mat& cameraMatrix, const Mat& distCoeffs, vector<Point2f>& imagePoints,
Mat& dpdrot, Mat& dpdt, Mat& dpdf, Mat& dpdc, Mat& dpddist, double aspectRatio) Mat& dpdrot, Mat& dpdt, Mat& dpdf, Mat& dpdc, Mat& dpddist, double aspectRatio)
{ {
projectPoints( objectPoints, rvec, tvec, cameraMatrix, distCoeffs, imagePoints, Mat J;
dpdrot, dpdt, dpdf, dpdc, dpddist, aspectRatio ); projectPoints( objectPoints, rvec, tvec, cameraMatrix, distCoeffs, imagePoints, J, aspectRatio);
J.colRange(0, 3).copyTo(dpdrot);
J.colRange(3, 6).copyTo(dpdt);
J.colRange(6, 8).copyTo(dpdf);
J.colRange(8, 10).copyTo(dpdc);
J.colRange(10, J.cols).copyTo(dpddist);
} }
///////////////////////////////// Stereo Calibration ///////////////////////////////////// ///////////////////////////////// Stereo Calibration /////////////////////////////////////
@ -1696,7 +1701,7 @@ void CV_StereoCalibrationTest_CPP::rectify( const Mat& cameraMatrix1, const Mat&
Rect* validPixROI1, Rect* validPixROI2, int flags ) Rect* validPixROI1, Rect* validPixROI2, int flags )
{ {
stereoRectify( cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, stereoRectify( cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2,
imageSize, R, T, R1, R2, P1, P2, Q, alpha, newImageSize,validPixROI1, validPixROI2, flags ); imageSize, R, T, R1, R2, P1, P2, Q, flags, alpha, newImageSize,validPixROI1, validPixROI2 );
} }
bool CV_StereoCalibrationTest_CPP::rectifyUncalibrated( const Mat& points1, bool CV_StereoCalibrationTest_CPP::rectifyUncalibrated( const Mat& points1,

4
modules/calib3d/test/test_solvepnp_ransac.cpp
Unescape View File

@ -104,8 +104,8 @@ protected:
Mat rvec, tvec; Mat rvec, tvec;
vector<int> inliers; vector<int> inliers;
solvePnPRansac(Mat(points), Mat(points1), intrinsics, dist_coeffs, rvec, tvec, solvePnPRansac(points, points1, intrinsics, dist_coeffs, rvec, tvec,
false, 1000, 2.0, -1, &inliers); false, 1000, 2.0, -1, inliers);
bool isTestSuccess = inliers.size() == 475; bool isTestSuccess = inliers.size() == 475;

450
modules/core/include/opencv2/core/core.hpp
Unescape View File

@ -14,7 +14,7 @@
// For Open Source Computer Vision Library // For Open Source Computer Vision Library
// //
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners. // Third party copyrights are property of their respective owners.
// //
// Redistribution and use in source and binary forms, with or without modification, // Redistribution and use in source and binary forms, with or without modification,
@ -641,6 +641,8 @@ typedef Vec<ushort, 4> Vec4w;
typedef Vec<int, 2> Vec2i; typedef Vec<int, 2> Vec2i;
typedef Vec<int, 3> Vec3i; typedef Vec<int, 3> Vec3i;
typedef Vec<int, 4> Vec4i; typedef Vec<int, 4> Vec4i;
typedef Vec<int, 6> Vec6i;
typedef Vec<int, 8> Vec8i;
typedef Vec<float, 2> Vec2f; typedef Vec<float, 2> Vec2f;
typedef Vec<float, 3> Vec3f; typedef Vec<float, 3> Vec3f;
@ -1252,10 +1254,90 @@ public:
protected: protected:
_Tp* obj; //< the object pointer. _Tp* obj; //< the object pointer.
int* refcount; //< the associated bbbbbbbbbbbbbbbbbb reference counter int* refcount; //< the associated reference counter
}; };
//////////////////////////////// Mat ////////////////////////////////
//////////////////////// Input/Output Array Arguments /////////////////////////////////
/*!
Proxy datatype for passing Mat's and vector<>'s as input parameters
*/
class CV_EXPORTS InputArray
{
public:
enum { KIND_SHIFT=16, NONE=0<<KIND_SHIFT, MAT=1<<KIND_SHIFT,
MATX=2<<KIND_SHIFT, STD_VECTOR=3<<KIND_SHIFT,
STD_VECTOR_VECTOR=4<<KIND_SHIFT,
STD_VECTOR_MAT=5<<KIND_SHIFT, EXPR=6<<KIND_SHIFT };
InputArray();
InputArray(const Mat& m);
InputArray(const MatExpr& expr);
template<typename _Tp> InputArray(const vector<_Tp>& vec);
template<typename _Tp> InputArray(const vector<vector<_Tp> >& vec);
InputArray(const vector<Mat>& vec);
template<typename _Tp, int m, int n> InputArray(const Matx<_Tp, m, n>& matx);
InputArray(const double& val);
Mat getMat(int i=-1) const;
void getMatVector(vector<Mat>& mv) const;
int kind() const;
Size size(int i=-1) const;
size_t total(int i=-1) const;
int type(int i=-1) const;
int depth(int i=-1) const;
int channels(int i=-1) const;
bool empty() const;
int flags;
void* obj;
Size sz;
};
enum
{
DEPTH_MASK_8U = 1 << CV_8U,
DEPTH_MASK_8S = 1 << CV_8S,
DEPTH_MASK_16U = 1 << CV_16U,
DEPTH_MASK_16S = 1 << CV_16S,
DEPTH_MASK_32S = 1 << CV_32S,
DEPTH_MASK_32F = 1 << CV_32F,
DEPTH_MASK_64F = 1 << CV_64F,
DEPTH_MASK_ALL = (DEPTH_MASK_64F<<1)-1,
DEPTH_MASK_ALL_BUT_8S = DEPTH_MASK_ALL & ~DEPTH_MASK_8S,
DEPTH_MASK_FLT = DEPTH_MASK_32F + DEPTH_MASK_64F
};
/*!
Proxy datatype for passing Mat's and vector<>'s as input parameters
*/
class CV_EXPORTS OutputArray : public InputArray
{
public:
OutputArray();
OutputArray(Mat& m);
template<typename _Tp> OutputArray(vector<_Tp>& vec);
template<typename _Tp> OutputArray(vector<vector<_Tp> >& vec);
OutputArray(vector<Mat>& vec);
template<typename _Tp, int m, int n> OutputArray(Matx<_Tp, m, n>& matx);
bool fixedSize() const;
bool fixedType() const;
bool needed() const;
Mat& getMatRef(int i=-1);
void create(Size sz, int type, int i=-1, bool allocateVector=false, int fixedDepthMask=0);
void create(int rows, int cols, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0);
void create(int dims, const int* size, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0);
void release();
void clear();
};
typedef InputArray InputArrayOfArrays;
typedef OutputArray OutputArrayOfArrays;
typedef OutputArray InputOutputArray;
/////////////////////////////////////// Mat ///////////////////////////////////////////
enum { MAGIC_MASK=0xFFFF0000, TYPE_MASK=0x00000FFF, DEPTH_MASK=7 }; enum { MAGIC_MASK=0xFFFF0000, TYPE_MASK=0x00000FFF, DEPTH_MASK=7 };
@ -1563,19 +1645,18 @@ public:
Mat clone() const; Mat clone() const;
//! copies the matrix content to "m". //! copies the matrix content to "m".
// It calls m.create(this->size(), this->type()). // It calls m.create(this->size(), this->type()).
void copyTo( Mat& m ) const; void copyTo( OutputArray m ) const;
template<typename _Tp> void copyTo( vector<_Tp>& v ) const;
//! copies those matrix elements to "m" that are marked with non-zero mask elements. //! copies those matrix elements to "m" that are marked with non-zero mask elements.
void copyTo( Mat& m, const Mat& mask ) const; void copyTo( OutputArray m, const InputArray& mask ) const;
//! converts matrix to another datatype with optional scalng. See cvConvertScale. //! converts matrix to another datatype with optional scalng. See cvConvertScale.
void convertTo( Mat& m, int rtype, double alpha=1, double beta=0 ) const; void convertTo( OutputArray m, int rtype, double alpha=1, double beta=0 ) const;
void assignTo( Mat& m, int type=-1 ) const; void assignTo( Mat& m, int type=-1 ) const;
//! sets every matrix element to s //! sets every matrix element to s
Mat& operator = (const Scalar& s); Mat& operator = (const Scalar& s);
//! sets some of the matrix elements to s, according to the mask //! sets some of the matrix elements to s, according to the mask
Mat& setTo(const Scalar& s, const Mat& mask=Mat()); Mat& setTo(const Scalar& s, const InputArray& mask=InputArray());
//! creates alternative matrix header for the same data, with different //! creates alternative matrix header for the same data, with different
// number of channels and/or different number of rows. see cvReshape. // number of channels and/or different number of rows. see cvReshape.
Mat reshape(int _cn, int _rows=0) const; Mat reshape(int _cn, int _rows=0) const;
@ -1586,13 +1667,13 @@ public:
//! matrix inversion by means of matrix expressions //! matrix inversion by means of matrix expressions
MatExpr inv(int method=DECOMP_LU) const; MatExpr inv(int method=DECOMP_LU) const;
//! per-element matrix multiplication by means of matrix expressions //! per-element matrix multiplication by means of matrix expressions
MatExpr mul(const Mat& m, double scale=1) const; MatExpr mul(const InputArray& m, double scale=1) const;
MatExpr mul(const MatExpr& m, double scale=1) const; MatExpr mul(const MatExpr& m, double scale=1) const;
//! computes cross-product of 2 3D vectors //! computes cross-product of 2 3D vectors
Mat cross(const Mat& m) const; Mat cross(const InputArray& m) const;
//! computes dot-product //! computes dot-product
double dot(const Mat& m) const; double dot(const InputArray& m) const;
//! Matlab-style matrix initialization //! Matlab-style matrix initialization
static MatExpr zeros(int rows, int cols, int type); static MatExpr zeros(int rows, int cols, int type);
@ -1842,7 +1923,7 @@ public:
float uniform(float a, float b); float uniform(float a, float b);
//! returns uniformly distributed double-precision floating-point random number from [a,b) range //! returns uniformly distributed double-precision floating-point random number from [a,b) range
double uniform(double a, double b); double uniform(double a, double b);
void fill( Mat& mat, int distType, const Scalar& a, const Scalar& b ); void fill( InputOutputArray mat, int distType, const InputArray& a, const InputArray& b );
//! returns Gaussian random variate with mean zero. //! returns Gaussian random variate with mean zero.
double gaussian(double sigma); double gaussian(double sigma);
@ -1850,8 +1931,6 @@ public:
}; };
/*! /*!
Termination criteria in iterative algorithms Termination criteria in iterative algorithms
*/ */
@ -1879,6 +1958,7 @@ public:
double epsilon; // the desired accuracy double epsilon; // the desired accuracy
}; };
//! swaps two matrices //! swaps two matrices
CV_EXPORTS void swap(Mat& a, Mat& b); CV_EXPORTS void swap(Mat& a, Mat& b);
@ -1886,79 +1966,75 @@ CV_EXPORTS void swap(Mat& a, Mat& b);
CV_EXPORTS Mat cvarrToMat(const CvArr* arr, bool copyData=false, CV_EXPORTS Mat cvarrToMat(const CvArr* arr, bool copyData=false,
bool allowND=true, int coiMode=0); bool allowND=true, int coiMode=0);
//! extracts Channel of Interest from CvMat or IplImage and makes cv::Mat out of it. //! extracts Channel of Interest from CvMat or IplImage and makes cv::Mat out of it.
CV_EXPORTS void extractImageCOI(const CvArr* arr, CV_OUT Mat& coiimg, int coi=-1); CV_EXPORTS void extractImageCOI(const CvArr* arr, OutputArray coiimg, int coi=-1);
//! inserts single-channel cv::Mat into a multi-channel CvMat or IplImage //! inserts single-channel cv::Mat into a multi-channel CvMat or IplImage
CV_EXPORTS void insertImageCOI(const Mat& coiimg, CvArr* arr, int coi=-1); CV_EXPORTS void insertImageCOI(const InputArray& coiimg, CvArr* arr, int coi=-1);
//! adds one matrix to another (dst = src1 + src2) //! adds one matrix to another (dst = src1 + src2)
CV_EXPORTS_W void add(const Mat& src1, const Mat& src2, CV_OUT Mat& dst, const Mat& mask CV_WRAP_DEFAULT(Mat())); CV_EXPORTS_W void add(const InputArray& src1, const InputArray& src2, OutputArray dst,
const InputArray& mask=InputArray(), int dtype=-1);
//! subtracts one matrix from another (dst = src1 - src2) //! subtracts one matrix from another (dst = src1 - src2)
CV_EXPORTS_W void subtract(const Mat& src1, const Mat& src2, CV_OUT Mat& dst, const Mat& mask CV_WRAP_DEFAULT(Mat())); CV_EXPORTS_W void subtract(const InputArray& src1, const InputArray& src2, OutputArray dst,
//! adds one matrix to another (dst = src1 + src2) const InputArray& mask=InputArray(), int dtype=-1);
CV_EXPORTS void add(const Mat& src1, const Mat& src2, CV_OUT Mat& dst);
//! subtracts one matrix from another (dst = src1 - src2)
CV_EXPORTS void subtract(const Mat& src1, const Mat& src2, CV_OUT Mat& dst);
//! adds scalar to a matrix (dst = src1 + src2)
CV_EXPORTS_W void add(const Mat& src1, const Scalar& src2, CV_OUT Mat& dst, const Mat& mask=Mat());
//! subtracts scalar from a matrix (dst = src1 - src2)
CV_EXPORTS_W void subtract(const Mat& src1, const Scalar& src2, CV_OUT Mat& dst, const Mat& mask=Mat());
//! subtracts matrix from scalar (dst = src1 - src2)
CV_EXPORTS_W void subtract(const Scalar& src1, const Mat& src2, CV_OUT Mat& dst, const Mat& mask=Mat());
//! computes element-wise weighted product of the two arrays (dst = scale*src1*src2) //! computes element-wise weighted product of the two arrays (dst = scale*src1*src2)
CV_EXPORTS_W void multiply(const Mat& src1, const Mat& src2, CV_OUT Mat& dst, double scale=1); CV_EXPORTS_W void multiply(const InputArray& src1, const InputArray& src2,
OutputArray dst, double scale=1, int dtype=-1);
//! computes element-wise weighted quotient of the two arrays (dst = scale*src1/src2) //! computes element-wise weighted quotient of the two arrays (dst = scale*src1/src2)
CV_EXPORTS_W void divide(const Mat& src1, const Mat& src2, CV_OUT Mat& dst, double scale=1); CV_EXPORTS_W void divide(const InputArray& src1, const InputArray& src2, OutputArray dst,
double scale=1, int dtype=-1);
//! computes element-wise weighted reciprocal of an array (dst = scale/src2) //! computes element-wise weighted reciprocal of an array (dst = scale/src2)
CV_EXPORTS_W void divide(double scale, const Mat& src2, CV_OUT Mat& dst); CV_EXPORTS_W void divide(double scale, const InputArray& src2,
OutputArray dst, int dtype=-1);
//! adds scaled array to another one (dst = alpha*src1 + src2) //! adds scaled array to another one (dst = alpha*src1 + src2)
CV_EXPORTS_W void scaleAdd(const Mat& src1, double alpha, const Mat& src2, CV_OUT Mat& dst); CV_EXPORTS_W void scaleAdd(const InputArray& src1, double alpha, const InputArray& src2, OutputArray dst);
//! computes weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma) //! computes weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma)
CV_EXPORTS_W void addWeighted(const Mat& src1, double alpha, const Mat& src2, CV_EXPORTS_W void addWeighted(const InputArray& src1, double alpha, const InputArray& src2,
double beta, double gamma, CV_OUT Mat& dst); double beta, double gamma, OutputArray dst, int dtype=-1);
//! scales array elements, computes absolute values and converts the results to 8-bit unsigned integers: dst(i)=saturate_cast<uchar>abs(src(i)*alpha+beta) //! scales array elements, computes absolute values and converts the results to 8-bit unsigned integers: dst(i)=saturate_cast<uchar>abs(src(i)*alpha+beta)
CV_EXPORTS_W void convertScaleAbs(const Mat& src, CV_OUT Mat& dst, double alpha=1, double beta=0); CV_EXPORTS_W void convertScaleAbs(const InputArray& src, OutputArray dst,
//! transforms 8-bit unsigned integers using lookup table: dst(i)=lut(src(i)) double alpha=1, double beta=0);
CV_EXPORTS_W void LUT(const Mat& src, const Mat& lut, CV_OUT Mat& dst); //! transforms array of numbers using a lookup table: dst(i)=lut(src(i))
CV_EXPORTS_W void LUT(const InputArray& src, const InputArray& lut, OutputArray dst,
int interpolation=0);
//! computes sum of array elements //! computes sum of array elements
CV_EXPORTS_W Scalar sum(const Mat& src); CV_EXPORTS_W Scalar sum(const InputArray& src);
//! computes the number of nonzero array elements //! computes the number of nonzero array elements
CV_EXPORTS_W int countNonZero( const Mat& src ); CV_EXPORTS_W int countNonZero( const InputArray& src );
//! computes mean value of array elements
CV_EXPORTS Scalar mean(const Mat& src);
//! computes mean value of selected array elements //! computes mean value of selected array elements
CV_EXPORTS_W Scalar mean(const Mat& src, const Mat& mask CV_WRAP_DEFAULT(Mat())); CV_EXPORTS_W Scalar mean(const InputArray& src, const InputArray& mask=InputArray());
//! computes mean value and standard deviation of all or selected array elements //! computes mean value and standard deviation of all or selected array elements
CV_EXPORTS_W void meanStdDev(const Mat& src, CV_OUT Scalar& mean, CV_OUT Scalar& stddev, const Mat& mask=Mat()); CV_EXPORTS_W void meanStdDev(const InputArray& src, OutputArray mean, OutputArray stddev,
//! computes norm of array const InputArray& mask=InputArray());
CV_EXPORTS double norm(const Mat& src1, int normType=NORM_L2);
//! computes norm of the difference between two arrays
CV_EXPORTS double norm(const Mat& src1, const Mat& src2, int normType=NORM_L2);
//! computes norm of the selected array part //! computes norm of the selected array part
CV_EXPORTS_W double norm(const Mat& src1, int normType, const Mat& mask CV_WRAP_DEFAULT(Mat())); CV_EXPORTS_W double norm(const InputArray& src1, int normType=NORM_L2, const InputArray& mask=InputArray());
//! computes norm of selected part of the difference between two arrays //! computes norm of selected part of the difference between two arrays
CV_EXPORTS_W double norm(const Mat& src1, const Mat& src2, CV_EXPORTS_W double norm(const InputArray& src1, const InputArray& src2,
int normType, const Mat& mask CV_WRAP_DEFAULT(Mat())); int normType=NORM_L2, const InputArray& mask=InputArray());
//! scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values //! scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values
CV_EXPORTS_W void normalize( const Mat& src, CV_OUT Mat& dst, double alpha=1, double beta=0, CV_EXPORTS_W void normalize( const InputArray& src, OutputArray dst, double alpha=1, double beta=0,
int norm_type=NORM_L2, int rtype=-1, const Mat& mask=Mat()); int norm_type=NORM_L2, int dtype=-1, const InputArray& mask=InputArray());
//! finds global minimum and maximum array elements and returns their values and their locations //! finds global minimum and maximum array elements and returns their values and their locations
CV_EXPORTS_W void minMaxLoc(const Mat& src, CV_OUT double* minVal, CV_EXPORTS_W void minMaxLoc(const InputArray& src, CV_OUT double* minVal,
CV_OUT double* maxVal=0, CV_OUT Point* minLoc=0, CV_OUT double* maxVal=0, CV_OUT Point* minLoc=0,
CV_OUT Point* maxLoc=0, const Mat& mask=Mat()); CV_OUT Point* maxLoc=0, const InputArray& mask=InputArray());
CV_EXPORTS void minMaxIdx(const Mat& src, double* minVal, double* maxVal, CV_EXPORTS void minMaxIdx(const InputArray& src, double* minVal, double* maxVal,
int* minIdx=0, int* maxIdx=0, const Mat& mask=Mat()); int* minIdx=0, int* maxIdx=0, const InputArray& mask=InputArray());
//! transforms 2D matrix to 1D row or column vector by taking sum, minimum, maximum or mean value over all the rows //! transforms 2D matrix to 1D row or column vector by taking sum, minimum, maximum or mean value over all the rows
CV_EXPORTS_W void reduce(const Mat& src, CV_OUT Mat& dst, int dim, int rtype, int dtype=-1); CV_EXPORTS_W void reduce(const InputArray& src, OutputArray dst, int dim, int rtype, int dtype=-1);
//! makes multi-channel array out of several single-channel arrays //! makes multi-channel array out of several single-channel arrays
CV_EXPORTS void merge(const Mat* mv, size_t count, CV_OUT Mat& dst); CV_EXPORTS void merge(const Mat* mv, size_t count, OutputArray dst);
//! makes multi-channel array out of several single-channel arrays //! makes multi-channel array out of several single-channel arrays
CV_EXPORTS_W void merge(const vector<Mat>& mv, Mat& dst); CV_EXPORTS_W void merge(const vector<Mat>& mv, OutputArray dst);
//! copies each plane of a multi-channel array to a dedicated array //! copies each plane of a multi-channel array to a dedicated array
CV_EXPORTS void split(const Mat& src, Mat* mvbegin); CV_EXPORTS void split(const Mat& src, Mat* mvbegin);
@ -1969,133 +2045,131 @@ CV_EXPORTS_W void split(const Mat& m, vector<Mat>& mv);
CV_EXPORTS void mixChannels(const Mat* src, size_t nsrcs, Mat* dst, size_t ndsts, CV_EXPORTS void mixChannels(const Mat* src, size_t nsrcs, Mat* dst, size_t ndsts,
const int* fromTo, size_t npairs); const int* fromTo, size_t npairs);
CV_EXPORTS void mixChannels(const vector<Mat>& src, vector<Mat>& dst, CV_EXPORTS void mixChannels(const vector<Mat>& src, vector<Mat>& dst,
const int* fromTo, int npairs); const int* fromTo, size_t npairs);
//! reverses the order of the rows, columns or both in a matrix //! reverses the order of the rows, columns or both in a matrix
CV_EXPORTS_W void flip(const Mat& src, CV_OUT Mat& dst, int flipCode); CV_EXPORTS_W void flip(const InputArray& src, OutputArray dst, int flipCode);
//! replicates the input matrix the specified number of times in the horizontal and/or vertical direction //! replicates the input matrix the specified number of times in the horizontal and/or vertical direction
CV_EXPORTS_W void repeat(const Mat& src, int ny, int nx, CV_OUT Mat& dst); CV_EXPORTS_W void repeat(const InputArray& src, int ny, int nx, OutputArray dst);
CV_EXPORTS Mat repeat(const Mat& src, int ny, int nx); CV_EXPORTS Mat repeat(const Mat& src, int ny, int nx);
CV_EXPORTS void hconcat(const Mat* src, size_t nsrc, Mat& dst); CV_EXPORTS void hconcat(const Mat* src, size_t nsrc, OutputArray dst);
CV_EXPORTS void hconcat(const Mat& src1, const Mat& src2, Mat& dst); CV_EXPORTS void hconcat(const InputArray& src1, const InputArray& src2, OutputArray dst);
CV_EXPORTS_W void hconcat(const vector<Mat>& src, CV_OUT Mat& dst); CV_EXPORTS_W void hconcat(const InputArray& src, OutputArray dst);
CV_EXPORTS void vconcat(const Mat* src, size_t nsrc, Mat& dst); CV_EXPORTS void vconcat(const Mat* src, size_t nsrc, OutputArray dst);
CV_EXPORTS void vconcat(const Mat& src1, const Mat& src2, Mat& dst); CV_EXPORTS void vconcat(const InputArray& src1, const InputArray& src2, OutputArray dst);
CV_EXPORTS_W void vconcat(const vector<Mat>& src, CV_OUT Mat& dst); CV_EXPORTS_W void vconcat(const InputArray& src, OutputArray dst);
//! computes bitwise conjunction of the two arrays (dst = src1 & src2) //! computes bitwise conjunction of the two arrays (dst = src1 & src2)
CV_EXPORTS_W void bitwise_and(const Mat& src1, const Mat& src2, CV_OUT Mat& dst, const Mat& mask=Mat()); CV_EXPORTS_W void bitwise_and(const InputArray& src1, const InputArray& src2,
OutputArray dst, const InputArray& mask=InputArray());
//! computes bitwise disjunction of the two arrays (dst = src1 | src2) //! computes bitwise disjunction of the two arrays (dst = src1 | src2)
CV_EXPORTS_W void bitwise_or(const Mat& src1, const Mat& src2, CV_OUT Mat& dst, const Mat& mask=Mat()); CV_EXPORTS_W void bitwise_or(const InputArray& src1, const InputArray& src2,
OutputArray dst, const InputArray& mask=InputArray());
//! computes bitwise exclusive-or of the two arrays (dst = src1 ^ src2) //! computes bitwise exclusive-or of the two arrays (dst = src1 ^ src2)
CV_EXPORTS_W void bitwise_xor(const Mat& src1, const Mat& src2, CV_OUT Mat& dst, const Mat& mask=Mat()); CV_EXPORTS_W void bitwise_xor(const InputArray& src1, const InputArray& src2,
//! computes bitwise conjunction of an array and scalar (dst = src1 & src2) OutputArray dst, const InputArray& mask=InputArray());
CV_EXPORTS_W void bitwise_and(const Mat& src1, const Scalar& src2, CV_OUT Mat& dst, const Mat& mask=Mat());
//! computes bitwise disjunction of an array and scalar (dst = src1 | src2)
CV_EXPORTS_W void bitwise_or(const Mat& src1, const Scalar& src2, CV_OUT Mat& dst, const Mat& mask=Mat());
//! computes bitwise exclusive-or of an array and scalar (dst = src1 ^ src2)
CV_EXPORTS_W void bitwise_xor(const Mat& src1, const Scalar& src2, CV_OUT Mat& dst, const Mat& mask=Mat());
//! inverts each bit of array (dst = ~src) //! inverts each bit of array (dst = ~src)
CV_EXPORTS_W void bitwise_not(const Mat& src, CV_OUT Mat& dst); CV_EXPORTS_W void bitwise_not(const InputArray& src, OutputArray dst,
const InputArray& mask=InputArray());
//! computes element-wise absolute difference of two arrays (dst = abs(src1 - src2)) //! computes element-wise absolute difference of two arrays (dst = abs(src1 - src2))
CV_EXPORTS_W void absdiff(const Mat& src1, const Mat& src2, CV_OUT Mat& dst); CV_EXPORTS_W void absdiff(const InputArray& src1, const InputArray& src2, OutputArray dst);
//! computes element-wise absolute difference of array and scalar (dst = abs(src1 - src2))
CV_EXPORTS_W void absdiff(const Mat& src1, const Scalar& src2, CV_OUT Mat& dst);
//! set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb) //! set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb)
CV_EXPORTS_W void inRange(const Mat& src, const Mat& lowerb, CV_EXPORTS_W void inRange(const InputArray& src, const InputArray& lowerb,
const Mat& upperb, CV_OUT Mat& dst); const InputArray& upperb, OutputArray dst);
//! set mask elements for those array elements which are within the fixed bounding box (dst = lowerb <= src && src < upperb)
CV_EXPORTS_W void inRange(const Mat& src, const Scalar& lowerb,
const Scalar& upperb, CV_OUT Mat& dst);
//! compares elements of two arrays (dst = src1 <cmpop> src2) //! compares elements of two arrays (dst = src1 <cmpop> src2)
CV_EXPORTS_W void compare(const Mat& src1, const Mat& src2, CV_OUT Mat& dst, int cmpop); CV_EXPORTS_W void compare(const InputArray& src1, const InputArray& src2, OutputArray dst, int cmpop);
//! compares elements of array with scalar (dst = src1 <cmpop> src2) //! computes per-element minimum of two arrays (dst = min(src1, src2))
CV_EXPORTS_W void compare(const Mat& src1, double s, CV_OUT Mat& dst, int cmpop); CV_EXPORTS_W void min(const InputArray& src1, const InputArray& src2, OutputArray dst);
//! computes per-element maximum of two arrays (dst = max(src1, src2))
CV_EXPORTS_W void max(const InputArray& src1, const InputArray& src2, OutputArray dst);
//! computes per-element minimum of two arrays (dst = min(src1, src2)) //! computes per-element minimum of two arrays (dst = min(src1, src2))
CV_EXPORTS_W void min(const Mat& src1, const Mat& src2, CV_OUT Mat& dst); CV_EXPORTS void min(const Mat& src1, const Mat& src2, Mat& dst);
//! computes per-element minimum of array and scalar (dst = min(src1, src2)) //! computes per-element minimum of array and scalar (dst = min(src1, src2))
CV_EXPORTS_W void min(const Mat& src1, double src2, CV_OUT Mat& dst); CV_EXPORTS void min(const Mat& src1, double src2, Mat& dst);
//! computes per-element maximum of two arrays (dst = max(src1, src2)) //! computes per-element maximum of two arrays (dst = max(src1, src2))
CV_EXPORTS_W void max(const Mat& src1, const Mat& src2, CV_OUT Mat& dst); CV_EXPORTS void max(const Mat& src1, const Mat& src2, Mat& dst);
//! computes per-element maximum of array and scalar (dst = max(src1, src2)) //! computes per-element maximum of array and scalar (dst = max(src1, src2))
CV_EXPORTS_W void max(const Mat& src1, double src2, CV_OUT Mat& dst); CV_EXPORTS void max(const Mat& src1, double src2, Mat& dst);
//! computes square root of each matrix element (dst = src**0.5) //! computes square root of each matrix element (dst = src**0.5)
CV_EXPORTS_W void sqrt(const Mat& src, CV_OUT Mat& dst); CV_EXPORTS_W void sqrt(const InputArray& src, OutputArray dst);
//! raises the input matrix elements to the specified power (b = a**power) //! raises the input matrix elements to the specified power (b = a**power)
CV_EXPORTS_W void pow(const Mat& src, double power, CV_OUT Mat& dst); CV_EXPORTS_W void pow(const InputArray& src, double power, OutputArray dst);
//! computes exponent of each matrix element (dst = e**src) //! computes exponent of each matrix element (dst = e**src)
CV_EXPORTS_W void exp(const Mat& src, CV_OUT Mat& dst); CV_EXPORTS_W void exp(const InputArray& src, OutputArray dst);
//! computes natural logarithm of absolute value of each matrix element: dst = log(abs(src)) //! computes natural logarithm of absolute value of each matrix element: dst = log(abs(src))
CV_EXPORTS_W void log(const Mat& src, CV_OUT Mat& dst); CV_EXPORTS_W void log(const InputArray& src, OutputArray dst);
//! computes cube root of the argument //! computes cube root of the argument
CV_EXPORTS_W float cubeRoot(float val); CV_EXPORTS_W float cubeRoot(float val);
//! computes the angle in degrees (0..360) of the vector (x,y) //! computes the angle in degrees (0..360) of the vector (x,y)
CV_EXPORTS_W float fastAtan2(float y, float x); CV_EXPORTS_W float fastAtan2(float y, float x);
//! converts polar coordinates to Cartesian //! converts polar coordinates to Cartesian
CV_EXPORTS_W void polarToCart(const Mat& magnitude, const Mat& angle, CV_EXPORTS_W void polarToCart(const InputArray& magnitude, const InputArray& angle,
CV_OUT Mat& x, CV_OUT Mat& y, bool angleInDegrees=false); OutputArray x, OutputArray y, bool angleInDegrees=false);
//! converts Cartesian coordinates to polar //! converts Cartesian coordinates to polar
CV_EXPORTS_W void cartToPolar(const Mat& x, const Mat& y, CV_EXPORTS_W void cartToPolar(const InputArray& x, const InputArray& y,
CV_OUT Mat& magnitude, CV_OUT Mat& angle, OutputArray magnitude, OutputArray angle,
bool angleInDegrees=false); bool angleInDegrees=false);
//! computes angle (angle(i)) of each (x(i), y(i)) vector //! computes angle (angle(i)) of each (x(i), y(i)) vector
CV_EXPORTS_W void phase(const Mat& x, const Mat& y, CV_OUT Mat& angle, CV_EXPORTS_W void phase(const InputArray& x, const InputArray& y, OutputArray angle,
bool angleInDegrees=false); bool angleInDegrees=false);
//! computes magnitude (magnitude(i)) of each (x(i), y(i)) vector //! computes magnitude (magnitude(i)) of each (x(i), y(i)) vector
CV_EXPORTS_W void magnitude(const Mat& x, const Mat& y, CV_OUT Mat& magnitude); CV_EXPORTS_W void magnitude(const InputArray& x, const InputArray& y, OutputArray magnitude);
//! checks that each matrix element is within the specified range. //! checks that each matrix element is within the specified range.
CV_EXPORTS_W bool checkRange(const Mat& a, bool quiet=true, CV_OUT Point* pt=0, CV_EXPORTS_W bool checkRange(const InputArray& a, bool quiet=true, CV_OUT Point* pt=0,
double minVal=-DBL_MAX, double maxVal=DBL_MAX); double minVal=-DBL_MAX, double maxVal=DBL_MAX);
//! implements generalized matrix product algorithm GEMM from BLAS //! implements generalized matrix product algorithm GEMM from BLAS
CV_EXPORTS_W void gemm(const Mat& src1, const Mat& src2, double alpha, CV_EXPORTS_W void gemm(const InputArray& src1, const InputArray& src2, double alpha,
const Mat& src3, double gamma, CV_OUT Mat& dst, int flags=0); const InputArray& src3, double gamma, OutputArray dst, int flags=0);
//! multiplies matrix by its transposition from the left or from the right //! multiplies matrix by its transposition from the left or from the right
CV_EXPORTS_W void mulTransposed( const Mat& src, CV_OUT Mat& dst, bool aTa, CV_EXPORTS_W void mulTransposed( const InputArray& src, OutputArray dst, bool aTa,
const Mat& delta=Mat(), const InputArray& delta=InputArray(),
double scale=1, int rtype=-1 ); double scale=1, int dtype=-1 );
//! transposes the matrix //! transposes the matrix
CV_EXPORTS_W void transpose(const Mat& src, CV_OUT Mat& dst); CV_EXPORTS_W void transpose(const InputArray& src, OutputArray dst);
//! performs affine transformation of each element of multi-channel input matrix //! performs affine transformation of each element of multi-channel input matrix
CV_EXPORTS_W void transform(const Mat& src, CV_OUT Mat& dst, const Mat& m ); CV_EXPORTS_W void transform(const InputArray& src, OutputArray dst, const InputArray& m );
//! performs perspective transformation of each element of multi-channel input matrix //! performs perspective transformation of each element of multi-channel input matrix
CV_EXPORTS_W void perspectiveTransform(const Mat& src, CV_OUT Mat& dst, const Mat& m ); CV_EXPORTS_W void perspectiveTransform(const InputArray& src, OutputArray dst, const InputArray& m );
//! extends the symmetrical matrix from the lower half or from the upper half //! extends the symmetrical matrix from the lower half or from the upper half
CV_EXPORTS_W void completeSymm(Mat& mtx, bool lowerToUpper=false); CV_EXPORTS_W void completeSymm(InputOutputArray mtx, bool lowerToUpper=false);
//! initializes scaled identity matrix //! initializes scaled identity matrix
CV_EXPORTS_W void setIdentity(Mat& mtx, const Scalar& s=Scalar(1)); CV_EXPORTS_W void setIdentity(InputOutputArray mtx, const Scalar& s=Scalar(1));
//! computes determinant of a square matrix //! computes determinant of a square matrix
CV_EXPORTS_W double determinant(const Mat& mtx); CV_EXPORTS_W double determinant(const InputArray& mtx);
//! computes trace of a matrix //! computes trace of a matrix
CV_EXPORTS_W Scalar trace(const Mat& mtx); CV_EXPORTS_W Scalar trace(const InputArray& mtx);
//! computes inverse or pseudo-inverse matrix //! computes inverse or pseudo-inverse matrix
CV_EXPORTS_W double invert(const Mat& src, CV_OUT Mat& dst, int flags=DECOMP_LU); CV_EXPORTS_W double invert(const InputArray& src, OutputArray dst, int flags=DECOMP_LU);
//! solves linear system or a least-square problem //! solves linear system or a least-square problem
CV_EXPORTS_W bool solve(const Mat& src1, const Mat& src2, CV_OUT Mat& dst, int flags=DECOMP_LU); CV_EXPORTS_W bool solve(const InputArray& src1, const InputArray& src2,
OutputArray dst, int flags=DECOMP_LU);
//! sorts independently each matrix row or each matrix column //! sorts independently each matrix row or each matrix column
CV_EXPORTS_W void sort(const Mat& src, CV_OUT Mat& dst, int flags); CV_EXPORTS_W void sort(const InputArray& src, OutputArray dst, int flags);
//! sorts independently each matrix row or each matrix column //! sorts independently each matrix row or each matrix column
CV_EXPORTS_W void sortIdx(const Mat& src, CV_OUT Mat& dst, int flags); CV_EXPORTS_W void sortIdx(const InputArray& src, OutputArray dst, int flags);
//! finds real roots of a cubic polynomial //! finds real roots of a cubic polynomial
CV_EXPORTS_W int solveCubic(const Mat& coeffs, CV_OUT Mat& roots); CV_EXPORTS_W int solveCubic(const InputArray& coeffs, OutputArray roots);
//! finds real and complex roots of a polynomial //! finds real and complex roots of a polynomial
CV_EXPORTS_W double solvePoly(const Mat& coeffs, CV_OUT Mat& roots, int maxIters=300); CV_EXPORTS_W double solvePoly(const InputArray& coeffs, OutputArray roots, int maxIters=300);
//! finds eigenvalues of a symmetric matrix //! finds eigenvalues of a symmetric matrix
CV_EXPORTS bool eigen(const Mat& src, CV_OUT Mat& eigenvalues, int lowindex=-1, CV_EXPORTS bool eigen(const InputArray& src, OutputArray eigenvalues, int lowindex=-1,
int highindex=-1); int highindex=-1);
//! finds eigenvalues and eigenvectors of a symmetric matrix //! finds eigenvalues and eigenvectors of a symmetric matrix
CV_EXPORTS bool eigen(const Mat& src, CV_OUT Mat& eigenvalues, CV_OUT Mat& eigenvectors, CV_EXPORTS bool eigen(const InputArray& src, OutputArray eigenvalues,
OutputArray eigenvectors,
int lowindex=-1, int highindex=-1); int lowindex=-1, int highindex=-1);
//! computes covariation matrix of a set of samples //! computes covariation matrix of a set of samples
CV_EXPORTS void calcCovarMatrix( const Mat* samples, int nsamples, Mat& covar, Mat& mean, CV_EXPORTS void calcCovarMatrix( const Mat* samples, int nsamples, Mat& covar, Mat& mean,
int flags, int ctype=CV_64F); int flags, int ctype=CV_64F);
//! computes covariation matrix of a set of samples //! computes covariation matrix of a set of samples
CV_EXPORTS_W void calcCovarMatrix( const Mat& samples, CV_OUT Mat& covar, CV_OUT Mat& mean, CV_EXPORTS_W void calcCovarMatrix( const InputArray& samples, OutputArray covar,
int flags, int ctype=CV_64F); OutputArray mean, int flags, int ctype=CV_64F);
/*! /*!
Principal Component Analysis Principal Component Analysis
@ -2157,17 +2231,17 @@ public:
//! default constructor //! default constructor
PCA(); PCA();
//! the constructor that performs PCA //! the constructor that performs PCA
PCA(const Mat& data, const Mat& mean, int flags, int maxComponents=0); PCA(const InputArray& data, const InputArray& mean, int flags, int maxComponents=0);
//! operator that performs PCA. The previously stored data, if any, is released //! operator that performs PCA. The previously stored data, if any, is released
PCA& operator()(const Mat& data, const Mat& mean, int flags, int maxComponents=0); PCA& operator()(const InputArray& data, const InputArray& mean, int flags, int maxComponents=0);
//! projects vector from the original space to the principal components subspace //! projects vector from the original space to the principal components subspace
Mat project(const Mat& vec) const; Mat project(const InputArray& vec) const;
//! projects vector from the original space to the principal components subspace //! projects vector from the original space to the principal components subspace
void project(const Mat& vec, CV_OUT Mat& result) const; void project(const InputArray& vec, OutputArray result) const;
//! reconstructs the original vector from the projection //! reconstructs the original vector from the projection
Mat backProject(const Mat& vec) const; Mat backProject(const InputArray& vec) const;
//! reconstructs the original vector from the projection //! reconstructs the original vector from the projection
void backProject(const Mat& vec, CV_OUT Mat& result) const; void backProject(const InputArray& vec, OutputArray result) const;
Mat eigenvectors; //!< eigenvectors of the covariation matrix Mat eigenvectors; //!< eigenvectors of the covariation matrix
Mat eigenvalues; //!< eigenvalues of the covariation matrix Mat eigenvalues; //!< eigenvalues of the covariation matrix
@ -2194,17 +2268,19 @@ public:
//! the default constructor //! the default constructor
SVD(); SVD();
//! the constructor that performs SVD //! the constructor that performs SVD
SVD( const Mat& src, int flags=0 ); SVD( const InputArray& src, int flags=0 );
//! the operator that performs SVD. The previously allocated SVD::u, SVD::w are SVD::vt are released. //! the operator that performs SVD. The previously allocated SVD::u, SVD::w are SVD::vt are released.
SVD& operator ()( const Mat& src, int flags=0 ); SVD& operator ()( const InputArray& src, int flags=0 );
//! decomposes matrix and stores the results to user-provided matrices //! decomposes matrix and stores the results to user-provided matrices
static void compute( const Mat& src, CV_OUT Mat& w, CV_OUT Mat& u, CV_OUT Mat& vt, int flags=0 ); static void compute( const InputArray& src, OutputArray w,
OutputArray u, OutputArray vt, int flags=0 );
//! computes singular values of a matrix //! computes singular values of a matrix
static void compute( const Mat& src, CV_OUT Mat& w, int flags=0 ); static void compute( const InputArray& src, OutputArray w, int flags=0 );
//! performs back substitution //! performs back substitution
static void backSubst( const Mat& w, const Mat& u, const Mat& vt, static void backSubst( const InputArray& w, const InputArray& u,
const Mat& rhs, CV_OUT Mat& dst ); const InputArray& vt, const InputArray& rhs,
OutputArray dst );
template<typename _Tp, int m, int n, int nm> static void compute( const Matx<_Tp, m, n>& a, template<typename _Tp, int m, int n, int nm> static void compute( const Matx<_Tp, m, n>& a,
Matx<_Tp, nm, 1>& w, Matx<_Tp, m, nm>& u, Matx<_Tp, n, nm>& vt ); Matx<_Tp, nm, 1>& w, Matx<_Tp, m, nm>& u, Matx<_Tp, n, nm>& vt );
@ -2214,28 +2290,28 @@ public:
const Matx<_Tp, m, nm>& u, const Matx<_Tp, n, nm>& vt, const Matx<_Tp, m, nb>& rhs, Matx<_Tp, n, nb>& dst ); const Matx<_Tp, m, nm>& u, const Matx<_Tp, n, nm>& vt, const Matx<_Tp, m, nb>& rhs, Matx<_Tp, n, nb>& dst );
//! finds dst = arg min_{|dst|=1} |m*dst| //! finds dst = arg min_{|dst|=1} |m*dst|
static void solveZ( const Mat& src, CV_OUT Mat& dst ); static void solveZ( const InputArray& src, OutputArray dst );
//! performs back substitution, so that dst is the solution or pseudo-solution of m*dst = rhs, where m is the decomposed matrix //! performs back substitution, so that dst is the solution or pseudo-solution of m*dst = rhs, where m is the decomposed matrix
void backSubst( const Mat& rhs, CV_OUT Mat& dst ) const; void backSubst( const InputArray& rhs, OutputArray dst ) const;
Mat u, w, vt; Mat u, w, vt;
}; };
//! computes Mahalanobis distance between two vectors: sqrt((v1-v2)'*icovar*(v1-v2)), where icovar is the inverse covariation matrix //! computes Mahalanobis distance between two vectors: sqrt((v1-v2)'*icovar*(v1-v2)), where icovar is the inverse covariation matrix
CV_EXPORTS_W double Mahalanobis(const Mat& v1, const Mat& v2, const Mat& icovar); CV_EXPORTS_W double Mahalanobis(const InputArray& v1, const InputArray& v2, const InputArray& icovar);
//! a synonym for Mahalanobis //! a synonym for Mahalanobis
CV_EXPORTS double Mahalonobis(const Mat& v1, const Mat& v2, const Mat& icovar); CV_EXPORTS double Mahalonobis(const InputArray& v1, const InputArray& v2, const InputArray& icovar);
//! performs forward or inverse 1D or 2D Discrete Fourier Transformation //! performs forward or inverse 1D or 2D Discrete Fourier Transformation
CV_EXPORTS_W void dft(const Mat& src, CV_OUT Mat& dst, int flags=0, int nonzeroRows=0); CV_EXPORTS_W void dft(const InputArray& src, OutputArray dst, int flags=0, int nonzeroRows=0);
//! performs inverse 1D or 2D Discrete Fourier Transformation //! performs inverse 1D or 2D Discrete Fourier Transformation
CV_EXPORTS_W void idft(const Mat& src, CV_OUT Mat& dst, int flags=0, int nonzeroRows=0); CV_EXPORTS_W void idft(const InputArray& src, OutputArray dst, int flags=0, int nonzeroRows=0);
//! performs forward or inverse 1D or 2D Discrete Cosine Transformation //! performs forward or inverse 1D or 2D Discrete Cosine Transformation
CV_EXPORTS_W void dct(const Mat& src, CV_OUT Mat& dst, int flags=0); CV_EXPORTS_W void dct(const InputArray& src, OutputArray dst, int flags=0);
//! performs inverse 1D or 2D Discrete Cosine Transformation //! performs inverse 1D or 2D Discrete Cosine Transformation
CV_EXPORTS_W void idct(const Mat& src, CV_OUT Mat& dst, int flags=0); CV_EXPORTS_W void idct(const InputArray& src, OutputArray dst, int flags=0);
//! computes element-wise product of the two Fourier spectrums. The second spectrum can optionally be conjugated before the multiplication //! computes element-wise product of the two Fourier spectrums. The second spectrum can optionally be conjugated before the multiplication
CV_EXPORTS_W void mulSpectrums(const Mat& a, const Mat& b, CV_OUT Mat& c, CV_EXPORTS_W void mulSpectrums(const InputArray& a, const InputArray& b, OutputArray c,
int flags, bool conjB=false); int flags, bool conjB=false);
//! computes the minimal vector size vecsize1 >= vecsize so that the dft() of the vector of length vecsize1 can be computed efficiently //! computes the minimal vector size vecsize1 >= vecsize so that the dft() of the vector of length vecsize1 can be computed efficiently
CV_EXPORTS_W int getOptimalDFTSize(int vecsize); CV_EXPORTS_W int getOptimalDFTSize(int vecsize);
@ -2250,9 +2326,9 @@ enum
KMEANS_USE_INITIAL_LABELS=1 // Uses the user-provided labels for K-Means initialization KMEANS_USE_INITIAL_LABELS=1 // Uses the user-provided labels for K-Means initialization
}; };
//! clusters the input data using k-Means algorithm //! clusters the input data using k-Means algorithm
CV_EXPORTS_W double kmeans( const Mat& data, int K, CV_OUT Mat& bestLabels, CV_EXPORTS_W double kmeans( const InputArray& data, int K, CV_OUT InputOutputArray bestLabels,
TermCriteria criteria, int attempts, TermCriteria criteria, int attempts,
int flags, CV_OUT Mat* centers=0 ); int flags, OutputArray centers=OutputArray() );
//! returns the thread-local Random number generator //! returns the thread-local Random number generator
CV_EXPORTS RNG& theRNG(); CV_EXPORTS RNG& theRNG();
@ -2261,13 +2337,13 @@ CV_EXPORTS RNG& theRNG();
template<typename _Tp> static inline _Tp randu() { return (_Tp)theRNG(); } template<typename _Tp> static inline _Tp randu() { return (_Tp)theRNG(); }
//! fills array with uniformly-distributed random numbers from the range [low, high) //! fills array with uniformly-distributed random numbers from the range [low, high)
CV_EXPORTS_W void randu(CV_OUT Mat& dst, const Scalar& low, const Scalar& high); CV_EXPORTS_W void randu(CV_IN_OUT OutputArray dst, const InputArray& low, const InputArray& high);
//! fills array with normally-distributed random numbers with the specified mean and the standard deviation //! fills array with normally-distributed random numbers with the specified mean and the standard deviation
CV_EXPORTS_W void randn(CV_OUT Mat& dst, const Scalar& mean, const Scalar& stddev); CV_EXPORTS_W void randn(CV_IN_OUT OutputArray dst, const InputArray& mean, const InputArray& stddev);
//! shuffles the input array elements //! shuffles the input array elements
CV_EXPORTS void randShuffle(Mat& dst, double iterFactor=1., RNG* rng=0); CV_EXPORTS void randShuffle(InputOutputArray dst, double iterFactor=1., RNG* rng=0);
//! draws the line segment (pt1, pt2) in the image //! draws the line segment (pt1, pt2) in the image
CV_EXPORTS_W void line(Mat& img, Point pt1, Point pt2, const Scalar& color, CV_EXPORTS_W void line(Mat& img, Point pt1, Point pt2, const Scalar& color,
@ -2828,6 +2904,7 @@ template<typename _Tp, size_t fixed_size=4096/sizeof(_Tp)+8> class CV_EXPORTS Au
{ {
public: public:
typedef _Tp value_type; typedef _Tp value_type;
enum { buffer_padding = (int)((16 + sizeof(_Tp) - 1)/sizeof(_Tp)) };
//! the default contructor //! the default contructor
AutoBuffer(); AutoBuffer();
@ -2851,7 +2928,7 @@ protected:
//! size of the real buffer //! size of the real buffer
size_t size; size_t size;
//! pre-allocated buffer //! pre-allocated buffer
_Tp buf[fixed_size]; _Tp buf[fixed_size+buffer_padding];
}; };
/////////////////////////// multi-dimensional dense matrix ////////////////////////// /////////////////////////// multi-dimensional dense matrix //////////////////////////
@ -2912,9 +2989,11 @@ public:
//! the default constructor //! the default constructor
NAryMatIterator(); NAryMatIterator();
//! the full constructor taking arbitrary number of n-dim matrices //! the full constructor taking arbitrary number of n-dim matrices
NAryMatIterator(const Mat** arrays, uchar** ptrs, int narrays=-1);
//! the full constructor taking arbitrary number of n-dim matrices
NAryMatIterator(const Mat** arrays, Mat* planes, int narrays=-1); NAryMatIterator(const Mat** arrays, Mat* planes, int narrays=-1);
//! the separate iterator initialization method //! the separate iterator initialization method
void init(const Mat** arrays, Mat* planes, int narrays=-1); void init(const Mat** arrays, Mat* planes, uchar** ptrs, int narrays=-1);
//! proceeds to the next plane of every iterated matrix //! proceeds to the next plane of every iterated matrix
NAryMatIterator& operator ++(); NAryMatIterator& operator ++();
@ -2925,12 +3004,17 @@ public:
const Mat** arrays; const Mat** arrays;
//! the current planes //! the current planes
Mat* planes; Mat* planes;
//! data pointers
uchar** ptrs;
//! the number of arrays //! the number of arrays
int narrays; int narrays;
//! the number of planes in each array //! the number of hyper-planes that the iterator steps through
int nplanes; size_t nplanes;
//! the size of each segment (in elements)
size_t size;
protected: protected:
int iterdepth, idx; int iterdepth;
size_t idx;
}; };
//typedef NAryMatIterator NAryMatNDIterator; //typedef NAryMatIterator NAryMatNDIterator;
@ -3081,7 +3165,7 @@ public:
\param try1d if true and m is a single-column matrix (Nx1), \param try1d if true and m is a single-column matrix (Nx1),
then the sparse matrix will be 1-dimensional. then the sparse matrix will be 1-dimensional.
*/ */
SparseMat(const Mat& m); explicit SparseMat(const Mat& m);
//! converts old-style sparse matrix to the new-style. All the data is copied //! converts old-style sparse matrix to the new-style. All the data is copied
SparseMat(const CvSparseMat* m); SparseMat(const CvSparseMat* m);
//! the destructor //! the destructor
@ -3563,39 +3647,30 @@ public:
//! the default constructor //! the default constructor
CV_WRAP KDTree(); CV_WRAP KDTree();
//! the full constructor that builds the search tree //! the full constructor that builds the search tree
CV_WRAP KDTree(const Mat& _points, bool copyAndReorderPoints=false); CV_WRAP KDTree(const InputArray& points, bool copyAndReorderPoints=false);
//! the full constructor that builds the search tree //! the full constructor that builds the search tree
CV_WRAP KDTree(const Mat& _points, const Mat& _labels, bool copyAndReorderPoints=false); CV_WRAP KDTree(const InputArray& points, const InputArray& _labels,
bool copyAndReorderPoints=false);
//! builds the search tree //! builds the search tree
CV_WRAP void build(const Mat& _points, bool copyAndReorderPoints=false); CV_WRAP void build(const InputArray& points, bool copyAndReorderPoints=false);
//! builds the search tree //! builds the search tree
CV_WRAP void build(const Mat& _points, const Mat& _labels, bool copyAndReorderPoints=false); CV_WRAP void build(const InputArray& points, const InputArray& labels,
bool copyAndReorderPoints=false);
//! finds the K nearest neighbors of "vec" while looking at Emax (at most) leaves //! finds the K nearest neighbors of "vec" while looking at Emax (at most) leaves
int findNearest(const float* vec, CV_WRAP int findNearest(const InputArray& vec, int K, int Emax,
int K, int Emax, int* neighborsIdx, OutputArray neighborsIdx,
Mat* neighbors=0, float* dist=0, int* labels=0) const; OutputArray neighbors=OutputArray(),
//! finds the K nearest neighbors while looking at Emax (at most) leaves OutputArray dist=OutputArray(),
int findNearest(const float* vec, int K, int Emax, OutputArray labels=OutputArray()) const;
vector<int>* neighborsIdx,
Mat* neighbors=0,
vector<float>* dist=0,
vector<int>* labels=0) const;
CV_WRAP int findNearest(const vector<float>& vec, int K, int Emax,
CV_OUT vector<int>* neighborsIdx,
CV_OUT Mat* neighbors=0,
CV_OUT vector<float>* dist=0,
CV_OUT vector<int>* labels=0) const;
//! finds all the points from the initial set that belong to the specified box //! finds all the points from the initial set that belong to the specified box
void findOrthoRange(const float* minBounds, const float* maxBounds, CV_WRAP void findOrthoRange(const InputArray& minBounds,
vector<int>* neighborsIdx, Mat* neighbors=0, const InputArray& maxBounds,
vector<int>* labels=0) const; OutputArray neighborsIdx,
CV_WRAP void findOrthoRange(const vector<float>& minBounds, const vector<float>& maxBounds, OutputArray neighbors=OutputArray(),
CV_OUT vector<int>* neighborsIdx, CV_OUT Mat* neighbors=0, OutputArray labels=OutputArray()) const;
CV_OUT vector<int>* labels=0) const;
//! returns vectors with the specified indices //! returns vectors with the specified indices
void getPoints(const int* idx, size_t nidx, Mat& pts, vector<int>* labels=0) const; CV_WRAP void getPoints(const InputArray& idx, OutputArray pts,
//! returns vectors with the specified indices OutputArray labels=OutputArray()) const;
CV_WRAP void getPoints(const vector<int>& idxs, Mat& pts, CV_OUT vector<int>* labels=0) const;
//! return a vector with the specified index //! return a vector with the specified index
const float* getPoint(int ptidx, int* label=0) const; const float* getPoint(int ptidx, int* label=0) const;
//! returns the search space dimensionality //! returns the search space dimensionality
@ -4042,7 +4117,7 @@ public:
int index; int index;
}; };
#if 0
class CV_EXPORTS AlgorithmImpl; class CV_EXPORTS AlgorithmImpl;
/*! /*!
@ -4088,7 +4163,6 @@ protected:
Ptr<AlgorithmImpl> impl; Ptr<AlgorithmImpl> impl;
}; };
#endif
} }

43
modules/core/include/opencv2/core/mat.hpp
Unescape View File

@ -608,21 +608,6 @@ template<typename _Tp> inline MatIterator_<_Tp> Mat::end()
return it; return it;
} }
template<typename _Tp> inline void Mat::copyTo(vector<_Tp>& v) const
{
int n = checkVector(DataType<_Tp>::channels);
if( empty() || n == 0 )
{
v.clear();
return;
}
CV_Assert( n > 0 );
v.resize(n);
Mat temp(dims, size.p, DataType<_Tp>::type, &v[0]);
convertTo(temp, DataType<_Tp>::type);
}
template<typename _Tp> inline Mat::operator vector<_Tp>() const template<typename _Tp> inline Mat::operator vector<_Tp>() const
{ {
vector<_Tp> v; vector<_Tp> v;
@ -726,10 +711,12 @@ static inline Mat cvarrToMatND(const CvArr* arr, bool copyData=false, int coiMod
///////////////////////////////////////////// SVD ////////////////////////////////////////////////////// ///////////////////////////////////////////// SVD //////////////////////////////////////////////////////
inline SVD::SVD() {} inline SVD::SVD() {}
inline SVD::SVD( const Mat& m, int flags ) { operator ()(m, flags); } inline SVD::SVD( const InputArray& m, int flags ) { operator ()(m, flags); }
inline void SVD::solveZ( const Mat& m, Mat& dst ) inline void SVD::solveZ( const InputArray& m, OutputArray _dst )
{ {
SVD svd(m); SVD svd(m);
_dst.create(svd.vt.cols, 1, svd.vt.type());
Mat dst = _dst.getMat();
svd.vt.row(svd.vt.rows-1).reshape(1,svd.vt.cols).copyTo(dst); svd.vt.row(svd.vt.rows-1).reshape(1,svd.vt.cols).copyTo(dst);
} }
@ -1075,6 +1062,22 @@ process( const Mat_<T1>& m1, const Mat_<T2>& m2, Mat_<T3>& m3, Op op )
} }
} }
/////////////////////////////// Input/Output Arrays /////////////////////////////////
template<typename _Tp> InputArray::InputArray(const vector<_Tp>& vec)
: flags(STD_VECTOR + DataType<_Tp>::type), obj((void*)&vec) {}
template<typename _Tp> InputArray::InputArray(const vector<vector<_Tp> >& vec)
: flags(STD_VECTOR_VECTOR + DataType<_Tp>::type), obj((void*)&vec) {}
template<typename _Tp, int m, int n> InputArray::InputArray(const Matx<_Tp, m, n>& mtx)
: flags(MATX + DataType<_Tp>::type), obj((void*)&mtx), sz(n, m) {}
template<typename _Tp> OutputArray::OutputArray(vector<_Tp>& vec) : InputArray(vec) {}
template<typename _Tp> OutputArray::OutputArray(vector<vector<_Tp> >& vec) : InputArray(vec) {}
template<typename _Tp, int m, int n> OutputArray::OutputArray(Matx<_Tp, m, n>& mtx) : InputArray(mtx) {}
//////////////////////////////////// Matrix Expressions ///////////////////////////////////////// //////////////////////////////////// Matrix Expressions /////////////////////////////////////////
class CV_EXPORTS MatOp class CV_EXPORTS MatOp
@ -1113,6 +1116,9 @@ public:
virtual void transpose(const MatExpr& expr, MatExpr& res) const; virtual void transpose(const MatExpr& expr, MatExpr& res) const;
virtual void matmul(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const; virtual void matmul(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const;
virtual void invert(const MatExpr& expr, int method, MatExpr& res) const; virtual void invert(const MatExpr& expr, int method, MatExpr& res) const;
virtual Size size(const MatExpr& expr) const;
virtual int type(const MatExpr& expr) const;
}; };
@ -1152,6 +1158,9 @@ public:
MatExpr mul(const MatExpr& e, double scale=1) const; MatExpr mul(const MatExpr& e, double scale=1) const;
MatExpr mul(const Mat& m, double scale=1) const; MatExpr mul(const Mat& m, double scale=1) const;
Size size() const;
int type() const;
const MatOp* op; const MatOp* op;
int flags; int flags;

18
modules/core/include/opencv2/core/operations.hpp
Unescape View File

@ -2298,10 +2298,17 @@ inline Point LineIterator::pos() const
/////////////////////////////// AutoBuffer //////////////////////////////////////// /////////////////////////////// AutoBuffer ////////////////////////////////////////
template<typename _Tp, size_t fixed_size> inline AutoBuffer<_Tp, fixed_size>::AutoBuffer() template<typename _Tp, size_t fixed_size> inline AutoBuffer<_Tp, fixed_size>::AutoBuffer()
: ptr(buf), size(fixed_size) {} {
ptr = alignPtr(buf, 16);
size = fixed_size;
}
template<typename _Tp, size_t fixed_size> inline AutoBuffer<_Tp, fixed_size>::AutoBuffer(size_t _size) template<typename _Tp, size_t fixed_size> inline AutoBuffer<_Tp, fixed_size>::AutoBuffer(size_t _size)
: ptr(buf), size(fixed_size) { allocate(_size); } {
ptr = alignPtr(buf, 16);
size = fixed_size;
allocate(_size);
}
template<typename _Tp, size_t fixed_size> inline AutoBuffer<_Tp, fixed_size>::~AutoBuffer() template<typename _Tp, size_t fixed_size> inline AutoBuffer<_Tp, fixed_size>::~AutoBuffer()
{ deallocate(); } { deallocate(); }
@ -2320,10 +2327,11 @@ template<typename _Tp, size_t fixed_size> inline void AutoBuffer<_Tp, fixed_size
template<typename _Tp, size_t fixed_size> inline void AutoBuffer<_Tp, fixed_size>::deallocate() template<typename _Tp, size_t fixed_size> inline void AutoBuffer<_Tp, fixed_size>::deallocate()
{ {
if( ptr != buf ) _Tp* buf0 = alignPtr(buf, 16);
if( ptr != buf0 )
{ {
cv::deallocate<_Tp>(ptr, size); cv::deallocate<_Tp>(ptr, size);
ptr = buf; ptr = buf0;
size = fixed_size; size = fixed_size;
} }
} }
@ -3550,7 +3558,6 @@ template<typename _Tp> static inline std::ostream& operator << (std::ostream& ou
return out; return out;
} }
#if 0
template<typename _Tp> struct AlgorithmParamType {}; template<typename _Tp> struct AlgorithmParamType {};
template<> struct AlgorithmParamType<int> { enum { type = CV_PARAM_TYPE_INT }; }; template<> struct AlgorithmParamType<int> { enum { type = CV_PARAM_TYPE_INT }; };
template<> struct AlgorithmParamType<double> { enum { type = CV_PARAM_TYPE_REAL }; }; template<> struct AlgorithmParamType<double> { enum { type = CV_PARAM_TYPE_REAL }; };
@ -3594,7 +3601,6 @@ template<typename _Tp> void Algorithm::setParamRange(int propId, const _Tp& minV
{ {
setParamRange_(propId, AlgorithmParamType<_Tp>::type, &minVal, &maxVal); setParamRange_(propId, AlgorithmParamType<_Tp>::type, &minVal, &maxVal);
} }
#endif
} }

3018
modules/core/src/arithm.cpp
View File

File diff suppressed because it is too large Load Diff

8
modules/core/src/array.cpp
Unescape View File

@ -722,10 +722,10 @@ icvGetNodePtr( CvSparseMat* mat, const int* idx, int* _type,
node->hashval = hashval; node->hashval = hashval;
node->next = (CvSparseNode*)mat->hashtable[tabidx]; node->next = (CvSparseNode*)mat->hashtable[tabidx];
mat->hashtable[tabidx] = node; mat->hashtable[tabidx] = node;
CV_MEMCPY_INT( CV_NODE_IDX(mat,node), idx, mat->dims ); memcpy(CV_NODE_IDX(mat,node), idx, mat->dims*sizeof(idx[0]));
ptr = (uchar*)CV_NODE_VAL(mat,node); ptr = (uchar*)CV_NODE_VAL(mat,node);
if( create_node > 0 ) if( create_node > 0 )
CV_ZERO_CHAR( ptr, CV_ELEM_SIZE(mat->type)); memset( ptr, 0, CV_ELEM_SIZE(mat->type));
} }
if( _type ) if( _type )
@ -1512,7 +1512,7 @@ cvScalarToRawData( const CvScalar* scalar, void* data, int type, int extend_to_1
do do
{ {
offset -= pix_size; offset -= pix_size;
CV_MEMCPY_AUTO( (char*)data + offset, data, pix_size ); memcpy((char*)data + offset, data, pix_size);
} }
while( offset > pix_size ); while( offset > pix_size );
} }
@ -2358,7 +2358,7 @@ cvClearND( CvArr* arr, const int* idx )
uchar* ptr; uchar* ptr;
ptr = cvPtrND( arr, idx, &type ); ptr = cvPtrND( arr, idx, &type );
if( ptr ) if( ptr )
CV_ZERO_CHAR( ptr, CV_ELEM_SIZE(type) ); memset( ptr, 0, CV_ELEM_SIZE(type) );
} }
else else
icvDeleteNode( (CvSparseMat*)arr, idx, 0 ); icvDeleteNode( (CvSparseMat*)arr, idx, 0 );

1251
modules/core/src/convert.cpp
View File

File diff suppressed because it is too large Load Diff

452
modules/core/src/copy.cpp
Unescape View File

@ -11,7 +11,7 @@
// For Open Source Computer Vision Library // For Open Source Computer Vision Library
// //
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners. // Third party copyrights are property of their respective owners.
// //
// Redistribution and use in source and binary forms, with or without modification, // Redistribution and use in source and binary forms, with or without modification,
@ -52,18 +52,12 @@ namespace cv
{ {
template<typename T> static void template<typename T> static void
copyMask_(const Mat& srcmat, Mat& dstmat, const Mat& maskmat) copyMask_(const uchar* _src, size_t sstep, const uchar* mask, size_t mstep, uchar* _dst, size_t dstep, Size size)
{ {
const uchar* mask = maskmat.data; for( ; size.height--; mask += mstep, _src += sstep, _dst += dstep )
size_t sstep = srcmat.step;
size_t dstep = dstmat.step;
size_t mstep = maskmat.step;
Size size = getContinuousSize(srcmat, dstmat, maskmat);
for( int y = 0; y < size.height; y++, mask += mstep )
{ {
const T* src = (const T*)(srcmat.data + sstep*y); const T* src = (const T*)_src;
T* dst = (T*)(dstmat.data + dstep*y); T* dst = (T*)_dst;
int x = 0; int x = 0;
for( ; x <= size.width - 4; x += 4 ) for( ; x <= size.width - 4; x += 4 )
{ {
@ -82,389 +76,397 @@ copyMask_(const Mat& srcmat, Mat& dstmat, const Mat& maskmat)
} }
} }
template<typename T> static void static void
setMask_(const void* _scalar, Mat& dstmat, const Mat& maskmat) copyMaskGeneric(const uchar* _src, size_t sstep, const uchar* mask, size_t mstep, uchar* _dst, size_t dstep, Size size, void* _esz)
{ {
T scalar = *(T*)_scalar; size_t k, esz = *(size_t*)_esz;
const uchar* mask = maskmat.data; for( ; size.height--; mask += mstep, _src += sstep, _dst += dstep )
size_t dstep = dstmat.step; {
size_t mstep = maskmat.step; const uchar* src = _src;
Size size = dstmat.size(); uchar* dst = _dst;
int x = 0;
if( dstmat.isContinuous() && maskmat.isContinuous() ) for( ; x < size.width; x++, src += esz, dst += esz )
{ {
size.width *= size.height; if( !mask[x] )
size.height = 1; continue;
for( k = 0; k < esz; k++ )
dst[k] = src[k];
}
}
} }
for( int y = 0; y < size.height; y++, mask += mstep ) template<typename T> static void
setMask_(T value, const uchar* mask, size_t mstep, uchar* _dst, size_t dstep, Size size)
{ {
T* dst = (T*)(dstmat.data + dstep*y); for( ; size.height--; mask += mstep, _dst += dstep )
{
T* dst = (T*)_dst;
int x = 0; int x = 0;
for( ; x <= size.width - 4; x += 4 ) for( ; x <= size.width - 4; x += 4 )
{ {
if( mask[x] ) if( mask[x] )
dst[x] = scalar; dst[x] = value;
if( mask[x+1] ) if( mask[x+1] )
dst[x+1] = scalar; dst[x+1] = value;
if( mask[x+2] ) if( mask[x+2] )
dst[x+2] = scalar; dst[x+2] = value;
if( mask[x+3] ) if( mask[x+3] )
dst[x+3] = scalar; dst[x+3] = value;
} }
for( ; x < size.width; x++ ) for( ; x < size.width; x++ )
if( mask[x] ) if( mask[x] )
dst[x] = scalar; dst[x] = value;
}
} }
static void
setMaskGeneric(const uchar* value, size_t, const uchar* mask, size_t mstep, uchar* _dst, size_t dstep, Size size, void* _esz)
{
size_t k, esz = *(size_t*)_esz;
for( ; size.height--; mask += mstep, _dst += dstep )
{
uchar* dst = _dst;
int x = 0;
for( ; x < size.width; x++, dst += esz )
{
if( !mask[x] )
continue;
for( k = 0; k < esz; k++ )
dst[k] = value[k];
} }
}
}
#define DEF_COPY_SET_MASK(suffix, type) \
static void copyMask##suffix(const uchar* src, size_t sstep, const uchar* mask, size_t mstep, \
uchar* dst, size_t dstep, Size size, void*) \
{ \
copyMask_<type>(src, sstep, mask, mstep, dst, dstep, size); \
} \
static void setMask##suffix( const uchar* src, size_t, const uchar* mask, size_t mstep, \
uchar* dst, size_t dstep, Size size, void*) \
{ \
setMask_<type>(*(const type*)src, mask, mstep, dst, dstep, size); \
}
typedef void (*SetMaskFunc)(const void* scalar, Mat& dst, const Mat& mask); DEF_COPY_SET_MASK(8u, uchar);
DEF_COPY_SET_MASK(16u, ushort);
DEF_COPY_SET_MASK(8uC3, Vec3b);
DEF_COPY_SET_MASK(32s, int);
DEF_COPY_SET_MASK(16uC3, Vec3s);
DEF_COPY_SET_MASK(32sC2, Vec2i);
DEF_COPY_SET_MASK(32sC3, Vec3i);
DEF_COPY_SET_MASK(32sC4, Vec4i);
DEF_COPY_SET_MASK(32sC6, Vec6i);
DEF_COPY_SET_MASK(32sC8, Vec8i);
CopyMaskFunc g_copyMaskFuncTab[] = BinaryFunc copyMaskTab[] =
{ {
0, 0,
copyMask_<uchar>, // 1 copyMask8u,
copyMask_<ushort>, // 2 copyMask16u,
copyMask_<Vec<uchar,3> >, // 3 copyMask8uC3,
copyMask_<int>, // 4 copyMask32s,
0, 0,
copyMask_<Vec<ushort,3> >, // 6 copyMask16uC3,
0, 0,
copyMask_<Vec<int,2> >, // 8 copyMask32sC2,
0, 0, 0, 0, 0, 0,
copyMask_<Vec<int,3> >, // 12 copyMask32sC3,
0, 0, 0, 0, 0, 0,
copyMask_<Vec<int,4> >, // 16 copyMask32sC4,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
copyMask_<Vec<int,6> >, // 24 copyMask32sC6,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
copyMask_<Vec<int,8> > // 32 copyMask32sC8
}; };
static SetMaskFunc setMaskFuncTab[] = BinaryFunc setMaskTab[] =
{ {
0, 0,
setMask_<uchar>, // 1 setMask8u,
setMask_<ushort>, // 2 setMask16u,
setMask_<Vec<uchar,3> >, // 3 setMask8uC3,
setMask_<int>, // 4 setMask32s,
0, 0,
setMask_<Vec<ushort,3> >, // 6 setMask16uC3,
0, 0,
setMask_<Vec<int,2> >, // 8 setMask32sC2,
0, 0, 0, 0, 0, 0,
setMask_<Vec<int,3> >, // 12 setMask32sC3,
0, 0, 0, 0, 0, 0,
setMask_<Vec<int,4> >, // 16 setMask32sC4,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
setMask_<Vec<int,6> >, // 24 setMask32sC6,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
setMask_<Vec<int,8> > // 32 setMask32sC8
}; };
BinaryFunc getCopyMaskFunc(size_t esz)
{
return esz <= 32 && copyMaskTab[esz] ? copyMaskTab[esz] : copyMaskGeneric;
}
/* dst = src */ /* dst = src */
void Mat::copyTo( Mat& dst ) const void Mat::copyTo( OutputArray _dst ) const
{
int dtype = _dst.type();
if( _dst.fixedType() && dtype != type() )
{ {
if( data == dst.data && data != 0 ) convertTo( _dst, dtype );
return; return;
}
if( dims > 2 ) if( empty() )
{
dst.create( dims, size, type() );
if( total() != 0 )
{ {
const Mat* arrays[] = { this, &dst, 0 }; _dst.release();
Mat planes[2];
NAryMatIterator it(arrays, planes);
CV_DbgAssert(it.planes[0].isContinuous() &&
it.planes[1].isContinuous());
size_t planeSize = it.planes[0].elemSize()*it.planes[0].rows*it.planes[0].cols;
for( int i = 0; i < it.nplanes; i++, ++it )
memcpy(it.planes[1].data, it.planes[0].data, planeSize);
}
return; return;
} }
dst.create( rows, cols, type() ); if( dims <= 2 )
Size sz = size(); {
_dst.create( rows, cols, type() );
Mat dst = _dst.getMat();
if( data == dst.data )
return;
if( rows > 0 && cols > 0 ) if( rows > 0 && cols > 0 )
{ {
const uchar* sptr = data; const uchar* sptr = data;
uchar* dptr = dst.data; uchar* dptr = dst.data;
size_t width = sz.width*elemSize(); Size sz = getContinuousSize(*this, dst, (int)elemSize());
if( isContinuous() && dst.isContinuous() ) for( ; sz.height--; sptr += step, dptr += dst.step )
{ memcpy( dptr, sptr, sz.width );
width *= sz.height; }
sz.height = 1; return;
} }
for( ; sz.height--; sptr += step, dptr += dst.step ) _dst.create( dims, size, type() );
memcpy( dptr, sptr, width ); Mat dst = _dst.getMat();
if( data == dst.data )
return;
if( total() != 0 )
{
const Mat* arrays[] = { this, &dst };
uchar* ptrs[2];
NAryMatIterator it(arrays, ptrs, 2);
size_t size = it.size*elemSize();
for( size_t i = 0; i < it.nplanes; i++, ++it )
memcpy(ptrs[1], ptrs[0], size);
} }
} }
void Mat::copyTo( Mat& dst, const Mat& mask ) const void Mat::copyTo( OutputArray _dst, const InputArray& _mask ) const
{ {
Mat mask = _mask.getMat();
if( !mask.data ) if( !mask.data )
{ {
copyTo(dst); copyTo(_dst);
return; return;
} }
if( dims > 2 ) CV_Assert( mask.type() == CV_8U );
{
dst.create( dims, size, type() );
const Mat* arrays[] = { this, &dst, &mask, 0 };
Mat planes[3];
NAryMatIterator it(arrays, planes);
for( int i = 0; i < it.nplanes; i++, ++it ) size_t esz = elemSize();
it.planes[0].copyTo(it.planes[1], it.planes[2]); BinaryFunc copymask = getCopyMaskFunc(esz);
return;
} uchar* data0 = _dst.getMat().data;
_dst.create( dims, size, type() );
Mat dst = _dst.getMat();
uchar* data0 = dst.data;
dst.create( size(), type() );
if( dst.data != data0 ) // do not leave dst uninitialized if( dst.data != data0 ) // do not leave dst uninitialized
dst = Scalar(0); dst = Scalar(0);
getCopyMaskFunc((int)elemSize())(*this, dst, mask);
}
Mat& Mat::operator = (const Scalar& s) if( dims <= 2 )
{ {
if( dims > 2 ) Size sz = getContinuousSize(*this, dst, mask);
{ copymask(data, step, mask.data, mask.step, dst.data, dst.step, sz, &esz);
const Mat* arrays[] = { this, 0 }; return;
Mat planes[1];
NAryMatIterator it(arrays, planes);
for( int i = 0; i < it.nplanes; i++, ++it )
it.planes[0] = s;
return *this;
} }
Size sz = size(); const Mat* arrays[] = { this, &dst, &mask, 0 };
uchar* dst = data; uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
Size sz((int)it.size, 1);
sz.width *= (int)elemSize(); for( size_t i = 0; i < it.nplanes; i++, ++it )
if( isContinuous() ) copymask(ptrs[0], 0, ptrs[2], 0, ptrs[1], 0, sz, &esz);
{
sz.width *= sz.height;
sz.height = 1;
} }
Mat& Mat::operator = (const Scalar& s)
{
const Mat* arrays[] = { this };
uchar* ptr;
NAryMatIterator it(arrays, &ptr, 1);
size_t size = it.size*elemSize();
if( s[0] == 0 && s[1] == 0 && s[2] == 0 && s[3] == 0 ) if( s[0] == 0 && s[1] == 0 && s[2] == 0 && s[3] == 0 )
{ {
for( ; sz.height--; dst += step ) for( size_t i = 0; i < it.nplanes; i++, ++it )
memset( dst, 0, sz.width ); memset( ptr, 0, size );
} }
else else
{ {
int t = type(), esz1 = (int)elemSize1(); if( it.nplanes > 0 )
{
double scalar[12]; double scalar[12];
scalarToRawData(s, scalar, t, 12); scalarToRawData(s, scalar, type(), 12);
int copy_len = 12*esz1; size_t blockSize = 12*elemSize1();
uchar* dst_limit = dst + sz.width;
if( sz.height-- ) for( size_t j = 0; j < size; j += blockSize )
{ {
while( dst + copy_len <= dst_limit ) size_t sz = std::min(blockSize, size - j);
{ memcpy( ptr + j, scalar, sz );
memcpy( dst, scalar, copy_len );
dst += copy_len;
} }
memcpy( dst, scalar, dst_limit - dst );
} }
if( sz.height > 0 ) for( size_t i = 1; i < it.nplanes; i++ )
{ {
dst = dst_limit - sz.width + step; ++it;
for( ; sz.height--; dst += step ) memcpy( ptr, data, size );
memcpy( dst, data, sz.width );
} }
} }
return *this; return *this;
} }
Mat& Mat::setTo(const Scalar& s, const Mat& mask) Mat& Mat::setTo(const Scalar& s, const InputArray& _mask)
{ {
Mat mask = _mask.getMat();
if( !mask.data ) if( !mask.data )
*this = s; *this = s;
else else
{ {
CV_Assert( channels() <= 4 ); CV_Assert( channels() <= 4 && mask.type() == CV_8U );
SetMaskFunc func = setMaskFuncTab[elemSize()]; size_t esz = elemSize();
CV_Assert( func != 0 ); BinaryFunc func = esz <= 32 ? setMaskTab[esz] : setMaskGeneric;
double buf[4]; double buf[4];
scalarToRawData(s, buf, type(), 0); scalarToRawData(s, buf, type(), 0);
if( dims > 2 )
{
const Mat* arrays[] = { this, &mask, 0 }; const Mat* arrays[] = { this, &mask, 0 };
Mat planes[2]; uchar* ptrs[2];
NAryMatIterator it(arrays, planes); NAryMatIterator it(arrays, ptrs);
Size sz((int)it.size, 1);
for( int i = 0; i < it.nplanes; i++, ++it ) for( size_t i = 0; i < it.nplanes; i++, ++it )
func(buf, it.planes[0], it.planes[1]); func((const uchar*)buf, 0, ptrs[1], 0, ptrs[0], 0, sz, &esz);
}
else
func(buf, *this, mask);
} }
return *this; return *this;
} }
template<typename T> static void static void
flipHoriz_( const Mat& srcmat, Mat& dstmat, bool flipv ) flipHoriz( const uchar* src, size_t sstep, uchar* dst, size_t dstep, Size size, size_t esz )
{ {
uchar* dst0 = dstmat.data; int i, j, limit = ((size.width + 1)/2)*esz;
size_t srcstep = srcmat.step; AutoBuffer<int> _tab(size.width*esz);
int dststep = (int)dstmat.step; int* tab = _tab;
Size size = srcmat.size();
if( flipv ) for( i = 0; i < size.width; i++ )
{ for( size_t k = 0; k < esz; k++ )
dst0 += (size.height - 1)*dststep; tab[i*esz + k] = (size.width - i - 1)*esz + k;
dststep = -dststep;
}
for( int y = 0; y < size.height; y++ ) for( ; size.height--; src += sstep, dst += dstep )
{ {
const T* src = (const T*)(srcmat.data + srcstep*y); for( i = 0; i < limit; i++ )
T* dst = (T*)(dst0 + dststep*y);
for( int i = 0; i < (size.width + 1)/2; i++ )
{ {
T t0 = src[i], t1 = src[size.width - i - 1]; j = tab[i];
dst[i] = t1; dst[size.width - i - 1] = t0; uchar t0 = src[i], t1 = src[j];
dst[i] = t1; dst[j] = t0;
} }
} }
} }
typedef void (*FlipHorizFunc)( const Mat& src, Mat& dst, bool flipv );
static void static void
flipVert( const Mat& srcmat, Mat& dstmat ) flipVert( const uchar* src0, size_t sstep, uchar* dst0, size_t dstep, Size size, size_t esz )
{ {
const uchar* src = srcmat.data; const uchar* src1 = src0 + (size.height - 1)*sstep;
uchar* dst = dstmat.data; uchar* dst1 = dst0 + (size.height - 1)*dstep;
size_t srcstep = srcmat.step, dststep = dstmat.step; size.width *= (int)esz;
Size size = srcmat.size();
const uchar* src1 = src + (size.height - 1)*srcstep;
uchar* dst1 = dst + (size.height - 1)*dststep;
size.width *= (int)srcmat.elemSize();
for( int y = 0; y < (size.height + 1)/2; y++, src += srcstep, src1 -= srcstep, for( int y = 0; y < (size.height + 1)/2; y++, src0 += sstep, src1 -= sstep,
dst += dststep, dst1 -= dststep ) dst0 += dstep, dst1 -= dstep )
{ {
int i = 0; int i = 0;
if( ((size_t)(src)|(size_t)(dst)|(size_t)src1|(size_t)dst1) % sizeof(int) == 0 ) if( ((size_t)src0|(size_t)dst0|(size_t)src1|(size_t)dst1) % sizeof(int) == 0 )
{ {
for( ; i <= size.width - 16; i += 16 ) for( ; i <= size.width - 16; i += 16 )
{ {
int t0 = ((int*)(src + i))[0]; int t0 = ((int*)(src0 + i))[0];
int t1 = ((int*)(src1 + i))[0]; int t1 = ((int*)(src1 + i))[0];
((int*)(dst + i))[0] = t1; ((int*)(dst0 + i))[0] = t1;
((int*)(dst1 + i))[0] = t0; ((int*)(dst1 + i))[0] = t0;
t0 = ((int*)(src + i))[1]; t0 = ((int*)(src0 + i))[1];
t1 = ((int*)(src1 + i))[1]; t1 = ((int*)(src1 + i))[1];
((int*)(dst + i))[1] = t1; ((int*)(dst0 + i))[1] = t1;
((int*)(dst1 + i))[1] = t0; ((int*)(dst1 + i))[1] = t0;
t0 = ((int*)(src + i))[2]; t0 = ((int*)(src0 + i))[2];
t1 = ((int*)(src1 + i))[2]; t1 = ((int*)(src1 + i))[2];
((int*)(dst + i))[2] = t1; ((int*)(dst0 + i))[2] = t1;
((int*)(dst1 + i))[2] = t0; ((int*)(dst1 + i))[2] = t0;
t0 = ((int*)(src + i))[3]; t0 = ((int*)(src0 + i))[3];
t1 = ((int*)(src1 + i))[3]; t1 = ((int*)(src1 + i))[3];
((int*)(dst + i))[3] = t1; ((int*)(dst0 + i))[3] = t1;
((int*)(dst1 + i))[3] = t0; ((int*)(dst1 + i))[3] = t0;
} }
for( ; i <= size.width - 4; i += 4 ) for( ; i <= size.width - 4; i += 4 )
{ {
int t0 = ((int*)(src + i))[0]; int t0 = ((int*)(src0 + i))[0];
int t1 = ((int*)(src1 + i))[0]; int t1 = ((int*)(src1 + i))[0];
((int*)(dst + i))[0] = t1; ((int*)(dst0 + i))[0] = t1;
((int*)(dst1 + i))[0] = t0; ((int*)(dst1 + i))[0] = t0;
} }
} }
for( ; i < size.width; i++ ) for( ; i < size.width; i++ )
{ {
uchar t0 = src[i]; uchar t0 = src0[i];
uchar t1 = src1[i]; uchar t1 = src1[i];
dst[i] = t1; dst0[i] = t1;
dst1[i] = t0; dst1[i] = t0;
} }
} }
} }
void flip( const Mat& src, Mat& dst, int flip_mode ) void flip( const InputArray& _src, OutputArray _dst, int flip_mode )
{
static FlipHorizFunc tab[] =
{ {
0, Mat src = _src.getMat();
flipHoriz_<uchar>, // 1
flipHoriz_<ushort>, // 2
flipHoriz_<Vec<uchar,3> >, // 3
flipHoriz_<int>, // 4
0,
flipHoriz_<Vec<ushort,3> >, // 6
0,
flipHoriz_<Vec<int,2> >, // 8
0, 0, 0,
flipHoriz_<Vec<int,3> >, // 12
0, 0, 0,
flipHoriz_<Vec<int,4> >, // 16
0, 0, 0, 0, 0, 0, 0,
flipHoriz_<Vec<int,6> >, // 24
0, 0, 0, 0, 0, 0, 0,
flipHoriz_<Vec<int,8> > // 32
};
CV_Assert( src.dims <= 2 ); CV_Assert( src.dims <= 2 );
dst.create( src.size(), src.type() ); _dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
size_t esz = src.elemSize();
if( flip_mode == 0 ) if( flip_mode <= 0 )
flipVert( src, dst ); flipVert( src.data, src.step, dst.data, dst.step, src.size(), esz );
else
{
int esz = (int)src.elemSize();
CV_Assert( esz <= 32 );
FlipHorizFunc func = tab[esz];
CV_Assert( func != 0 );
if( flip_mode > 0 )
func( src, dst, false );
else if( src.data != dst.data )
func( src, dst, true );
else else
{ flipHoriz( src.data, src.step, dst.data, dst.step, src.size(), esz );
func( dst, dst, false );
flipVert( dst, dst ); if( flip_mode < 0 )
} flipHoriz( dst.data, dst.step, dst.data, dst.step, dst.size(), esz );
}
} }
void repeat(const Mat& src, int ny, int nx, Mat& dst) void repeat(const InputArray& _src, int ny, int nx, OutputArray _dst)
{ {
Mat src = _src.getMat();
CV_Assert( src.dims <= 2 ); CV_Assert( src.dims <= 2 );
dst.create(src.rows*ny, src.cols*nx, src.type()); _dst.create(src.rows*ny, src.cols*nx, src.type());
Mat dst = _dst.getMat();
Size ssize = src.size(), dsize = dst.size(); Size ssize = src.size(), dsize = dst.size();
int esz = (int)src.elemSize(); int esz = (int)src.elemSize();
int x, y; int x, y;
@ -524,7 +526,7 @@ cvCopy( const void* srcarr, void* dstarr, const void* maskarr )
{ {
CvSparseNode* node_copy = (CvSparseNode*)cvSetNew( dst1->heap ); CvSparseNode* node_copy = (CvSparseNode*)cvSetNew( dst1->heap );
int tabidx = node->hashval & (dst1->hashsize - 1); int tabidx = node->hashval & (dst1->hashsize - 1);
CV_MEMCPY_AUTO( node_copy, node, dst1->heap->elem_size ); memcpy( node_copy, node, dst1->heap->elem_size );
node_copy->next = (CvSparseNode*)dst1->hashtable[tabidx]; node_copy->next = (CvSparseNode*)dst1->hashtable[tabidx];
dst1->hashtable[tabidx] = node_copy; dst1->hashtable[tabidx] = node_copy;
} }

215
modules/core/src/datastructs.cpp
Unescape View File

@ -1146,7 +1146,7 @@ cvSeqPush( CvSeq *seq, const void *element )
} }
if( element ) if( element )
CV_MEMCPY_AUTO( ptr, element, elem_size ); memcpy( ptr, element, elem_size );
seq->first->prev->count++; seq->first->prev->count++;
seq->total++; seq->total++;
seq->ptr = ptr + elem_size; seq->ptr = ptr + elem_size;
@ -1171,7 +1171,7 @@ cvSeqPop( CvSeq *seq, void *element )
seq->ptr = ptr = seq->ptr - elem_size; seq->ptr = ptr = seq->ptr - elem_size;
if( element ) if( element )
CV_MEMCPY_AUTO( element, ptr, elem_size ); memcpy( element, ptr, elem_size );
seq->ptr = ptr; seq->ptr = ptr;
seq->total--; seq->total--;
@ -1208,7 +1208,7 @@ cvSeqPushFront( CvSeq *seq, const void *element )
ptr = block->data -= elem_size; ptr = block->data -= elem_size;
if( element ) if( element )
CV_MEMCPY_AUTO( ptr, element, elem_size ); memcpy( ptr, element, elem_size );
block->count++; block->count++;
block->start_index--; block->start_index--;
seq->total++; seq->total++;
@ -1233,7 +1233,7 @@ cvSeqPopFront( CvSeq *seq, void *element )
block = seq->first; block = seq->first;
if( element ) if( element )
CV_MEMCPY_AUTO( element, block->data, elem_size ); memcpy( element, block->data, elem_size );
block->data += elem_size; block->data += elem_size;
block->start_index++; block->start_index++;
seq->total--; seq->total--;
@ -1708,7 +1708,7 @@ cvSeqRemoveSlice( CvSeq* seq, CvSlice slice )
for( i = 0; i < count; i++ ) for( i = 0; i < count; i++ )
{ {
CV_MEMCPY_AUTO( reader_to.ptr, reader_from.ptr, elem_size ); memcpy( reader_to.ptr, reader_from.ptr, elem_size );
CV_NEXT_SEQ_ELEM( elem_size, reader_to ); CV_NEXT_SEQ_ELEM( elem_size, reader_to );
CV_NEXT_SEQ_ELEM( elem_size, reader_from ); CV_NEXT_SEQ_ELEM( elem_size, reader_from );
} }
@ -1726,7 +1726,7 @@ cvSeqRemoveSlice( CvSeq* seq, CvSlice slice )
CV_PREV_SEQ_ELEM( elem_size, reader_to ); CV_PREV_SEQ_ELEM( elem_size, reader_to );
CV_PREV_SEQ_ELEM( elem_size, reader_from ); CV_PREV_SEQ_ELEM( elem_size, reader_from );
CV_MEMCPY_AUTO( reader_to.ptr, reader_from.ptr, elem_size ); memcpy( reader_to.ptr, reader_from.ptr, elem_size );
} }
cvSeqPopMulti( seq, 0, slice.end_index - slice.start_index, 1 ); cvSeqPopMulti( seq, 0, slice.end_index - slice.start_index, 1 );
@ -1796,7 +1796,7 @@ cvSeqInsertSlice( CvSeq* seq, int index, const CvArr* from_arr )
for( i = 0; i < index; i++ ) for( i = 0; i < index; i++ )
{ {
CV_MEMCPY_AUTO( reader_to.ptr, reader_from.ptr, elem_size ); memcpy( reader_to.ptr, reader_from.ptr, elem_size );
CV_NEXT_SEQ_ELEM( elem_size, reader_to ); CV_NEXT_SEQ_ELEM( elem_size, reader_to );
CV_NEXT_SEQ_ELEM( elem_size, reader_from ); CV_NEXT_SEQ_ELEM( elem_size, reader_from );
} }
@ -1814,7 +1814,7 @@ cvSeqInsertSlice( CvSeq* seq, int index, const CvArr* from_arr )
{ {
CV_PREV_SEQ_ELEM( elem_size, reader_to ); CV_PREV_SEQ_ELEM( elem_size, reader_to );
CV_PREV_SEQ_ELEM( elem_size, reader_from ); CV_PREV_SEQ_ELEM( elem_size, reader_from );
CV_MEMCPY_AUTO( reader_to.ptr, reader_from.ptr, elem_size ); memcpy( reader_to.ptr, reader_from.ptr, elem_size );
} }
} }
@ -1823,7 +1823,7 @@ cvSeqInsertSlice( CvSeq* seq, int index, const CvArr* from_arr )
for( i = 0; i < from_total; i++ ) for( i = 0; i < from_total; i++ )
{ {
CV_MEMCPY_AUTO( reader_to.ptr, reader_from.ptr, elem_size ); memcpy( reader_to.ptr, reader_from.ptr, elem_size );
CV_NEXT_SEQ_ELEM( elem_size, reader_to ); CV_NEXT_SEQ_ELEM( elem_size, reader_to );
CV_NEXT_SEQ_ELEM( elem_size, reader_from ); CV_NEXT_SEQ_ELEM( elem_size, reader_from );
} }
@ -2525,7 +2525,7 @@ cvSetAdd( CvSet* set, CvSetElem* element, CvSetElem** inserted_element )
id = free_elem->flags & CV_SET_ELEM_IDX_MASK; id = free_elem->flags & CV_SET_ELEM_IDX_MASK;
if( element ) if( element )
CV_MEMCPY_INT( free_elem, element, (size_t)set->elem_size/sizeof(int) ); memcpy( free_elem, element, set->elem_size );
free_elem->flags = id; free_elem->flags = id;
set->active_count++; set->active_count++;
@ -2616,8 +2616,7 @@ cvGraphAddVtx( CvGraph* graph, const CvGraphVtx* _vertex, CvGraphVtx** _inserted
if( vertex ) if( vertex )
{ {
if( _vertex ) if( _vertex )
CV_MEMCPY_INT( vertex + 1, _vertex + 1, memcpy( vertex + 1, _vertex + 1, graph->elem_size - sizeof(CvGraphVtx) );
(size_t)(graph->elem_size - sizeof(CvGraphVtx))/sizeof(int) );
vertex->first = 0; vertex->first = 0;
index = vertex->flags; index = vertex->flags;
} }
@ -2784,17 +2783,17 @@ cvGraphAddEdgeByPtr( CvGraph* graph,
edge->next[1] = end_vtx->first; edge->next[1] = end_vtx->first;
start_vtx->first = end_vtx->first = edge; start_vtx->first = end_vtx->first = edge;
delta = (graph->edges->elem_size - sizeof(*edge))/sizeof(int); delta = graph->edges->elem_size - sizeof(*edge);
if( _edge ) if( _edge )
{ {
if( delta > 0 ) if( delta > 0 )
CV_MEMCPY_INT( edge + 1, _edge + 1, delta ); memcpy( edge + 1, _edge + 1, delta );
edge->weight = _edge->weight; edge->weight = _edge->weight;
} }
else else
{ {
if( delta > 0 ) if( delta > 0 )
CV_ZERO_INT( edge + 1, delta ); memset( edge + 1, 0, delta );
edge->weight = 1.f; edge->weight = 1.f;
} }
@ -3548,14 +3547,14 @@ KDTree::KDTree()
normType = NORM_L2; normType = NORM_L2;
} }
KDTree::KDTree(const Mat& _points, bool _copyData) KDTree::KDTree(const InputArray& _points, bool _copyData)
{ {
maxDepth = -1; maxDepth = -1;
normType = NORM_L2; normType = NORM_L2;
build(_points, _copyData); build(_points, _copyData);
} }
KDTree::KDTree(const Mat& _points, const Mat& _labels, bool _copyData) KDTree::KDTree(const InputArray& _points, const InputArray& _labels, bool _copyData)
{ {
maxDepth = -1; maxDepth = -1;
normType = NORM_L2; normType = NORM_L2;
@ -3638,14 +3637,15 @@ computeSums( const Mat& points, const size_t* ofs, int a, int b, double* sums )
} }
void KDTree::build(const Mat& _points, bool _copyData) void KDTree::build(const InputArray& _points, bool _copyData)
{ {
build(_points, Mat(), _copyData); build(_points, InputArray(), _copyData);
} }
void KDTree::build(const Mat& _points, const Mat& _labels, bool _copyData) void KDTree::build(const InputArray& __points, const InputArray& __labels, bool _copyData)
{ {
Mat _points = __points.getMat(), _labels = __labels.getMat();
CV_Assert(_points.type() == CV_32F && !_points.empty()); CV_Assert(_points.type() == CV_32F && !_points.empty());
vector<KDTree::Node>().swap(nodes); vector<KDTree::Node>().swap(nodes);
@ -3744,57 +3744,6 @@ void KDTree::build(const Mat& _points, const Mat& _labels, bool _copyData)
} }
int KDTree::findNearest(const float* vec, int K, int emax,
vector<int>* neighborsIdx,
Mat* neighbors,
vector<float>* dist,
vector<int>* labels) const
{
K = std::min(K, points.rows);
CV_Assert(K > 0);
if(neighborsIdx)
neighborsIdx->resize(K);
if(dist)
dist->resize(K);
if(labels)
labels->resize(K);
K = findNearest(vec, K, emax, neighborsIdx ? &(*neighborsIdx)[0] : 0,
neighbors, dist ? &(*dist)[0] : 0, labels ? &(*labels)[0] : 0);
if(neighborsIdx)
neighborsIdx->resize(K);
if(dist)
dist->resize(K);
if(labels)
labels->resize(K);
return K;
}
int KDTree::findNearest(const vector<float>& vec, int K, int emax,
vector<int>* neighborsIdx,
Mat* neighbors,
vector<float>* dist,
vector<int>* labels) const
{
CV_Assert((int)vec.size() == points.cols);
K = std::min(K, points.rows);
CV_Assert(K > 0);
if(neighborsIdx)
neighborsIdx->resize(K);
if(dist)
dist->resize(K);
if(labels)
labels->resize(K);
K = findNearest(&vec[0], K, emax, neighborsIdx ? &(*neighborsIdx)[0] : 0,
neighbors, dist ? &(*dist)[0] : 0, labels ? &(*labels)[0] : 0);
if(neighborsIdx)
neighborsIdx->resize(K);
if(dist)
dist->resize(K);
if(labels)
labels->resize(K);
return K;
}
struct PQueueElem struct PQueueElem
{ {
PQueueElem() : dist(0), idx(0) {} PQueueElem() : dist(0), idx(0) {}
@ -3804,11 +3753,14 @@ struct PQueueElem
}; };
int KDTree::findNearest(const float* vec, int K, int emax, int KDTree::findNearest(const InputArray& _vec, int K, int emax,
int* _neighborsIdx, Mat* _neighbors, OutputArray _neighborsIdx, OutputArray _neighbors,
float* _dist, int* _labels) const OutputArray _dist, OutputArray _labels) const
{ {
Mat vecmat = _vec.getMat();
CV_Assert( vecmat.isContinuous() && vecmat.type() == CV_32F && vecmat.total() == (size_t)points.cols );
const float* vec = vecmat.ptr<float>();
K = std::min(K, points.rows); K = std::min(K, points.rows);
int dims = points.cols; int dims = points.cols;
@ -3929,42 +3881,43 @@ int KDTree::findNearest(const float* vec, int K, int emax,
} }
K = std::min(K, ncount); K = std::min(K, ncount);
if( _neighborsIdx ) if( _neighborsIdx.needed() )
{
for( i = 0; i < K; i++ )
_neighborsIdx[i] = idx[i];
}
if( _dist )
{
for( i = 0; i < K; i++ )
_dist[i] = std::sqrt(dist[i]);
}
if( _labels )
{ {
for( i = 0; i < K; i++ ) _neighborsIdx.create(K, 1, CV_32S, -1, true);
_labels[i] = labels[idx[i]]; Mat nidx = _neighborsIdx.getMat();
Mat(nidx.size(), CV_32S, &idx[0]).copyTo(nidx);
} }
if( _dist.needed() )
sqrt(Mat(K, 1, CV_32F, dist), _dist);
if( _neighbors ) if( _neighbors.needed() || _labels.needed() )
getPoints(idx, K, *_neighbors); getPoints(Mat(K, 1, CV_32S, idx), _neighbors, _labels);
return K; return K;
} }
void KDTree::findOrthoRange(const float* L, const float* R, void KDTree::findOrthoRange(const InputArray& _lowerBound,
vector<int>* neighborsIdx, const InputArray& _upperBound,
Mat* neighbors, vector<int>* _labels) const OutputArray _neighborsIdx,
OutputArray _neighbors,
OutputArray _labels ) const
{ {
int dims = points.cols; int dims = points.cols;
Mat lowerBound = _lowerBound.getMat(), upperBound = _upperBound.getMat();
CV_Assert( L && R ); CV_Assert( lowerBound.size == upperBound.size &&
lowerBound.isContinuous() &&
vector<int> _idx, *idx = neighborsIdx ? neighborsIdx : &_idx; upperBound.isContinuous() &&
lowerBound.type() == upperBound.type() &&
lowerBound.type() == CV_32F &&
lowerBound.total() == (size_t)dims );
const float* L = lowerBound.ptr<float>();
const float* R = upperBound.ptr<float>();
vector<int> idx;
AutoBuffer<int> _stack(MAX_TREE_DEPTH*2 + 1); AutoBuffer<int> _stack(MAX_TREE_DEPTH*2 + 1);
int* stack = _stack; int* stack = _stack;
int top = 0; int top = 0;
idx->clear();
stack[top++] = 0; stack[top++] = 0;
while( --top >= 0 ) while( --top >= 0 )
@ -3981,7 +3934,7 @@ void KDTree::findOrthoRange(const float* L, const float* R,
if( row[j] < L[j] || row[j] >= R[j] ) if( row[j] < L[j] || row[j] >= R[j] )
break; break;
if( j == dims ) if( j == dims )
idx->push_back(i); idx.push_back(i);
continue; continue;
} }
if( L[n.idx] <= n.boundary ) if( L[n.idx] <= n.boundary )
@ -3990,55 +3943,57 @@ void KDTree::findOrthoRange(const float* L, const float* R,
stack[top++] = n.right; stack[top++] = n.right;
} }
if( neighbors ) if( _neighborsIdx.needed() )
getPoints( &(*idx)[0], idx->size(), *neighbors, _labels );
}
void KDTree::findOrthoRange(const vector<float>& L, const vector<float>& R,
vector<int>* neighborsIdx, Mat* neighbors, vector<int>* _labels) const
{ {
size_t dims = points.cols; _neighborsIdx.create(idx.size(), 1, CV_32S, -1, true);
CV_Assert(L.size() == dims && R.size() == dims); Mat nidx = _neighborsIdx.getMat();
findOrthoRange(&L[0], &R[0], neighborsIdx, neighbors, _labels); Mat(nidx.size(), CV_32S, &idx[0]).copyTo(nidx);
}
getPoints( idx, _neighbors, _labels );
} }
void KDTree::getPoints(const int* idx, size_t nidx, Mat& pts, vector<int>* _labels) const void KDTree::getPoints(const InputArray& _idx, OutputArray _pts, OutputArray _labels) const
{ {
int dims = points.cols, n = (int)nidx; Mat idxmat = _idx.getMat(), pts, labelsmat;
pts.create( n, dims, points.type()); CV_Assert( idxmat.isContinuous() && idxmat.type() == CV_32S &&
if(_labels) (idxmat.cols == 1 || idxmat.rows == 1) );
_labels->resize(nidx); const int* idx = idxmat.ptr<int>();
int* dstlabels = 0;
for( int i = 0; i < n; i++ ) int dims = points.cols;
int i, nidx = (int)idxmat.total();
if( nidx == 0 )
{ {
int k = idx[i]; _pts.release();
CV_Assert( (unsigned)k < (unsigned)points.rows ); _labels.release();
const float* src = points.ptr<float>(k); return;
std::copy(src, src + dims, pts.ptr<float>(i));
if(_labels)
(*_labels)[i] = labels[k];
}
} }
if( _pts.needed() )
void KDTree::getPoints(const vector<int>& idx, Mat& pts, vector<int>* _labels) const
{ {
int dims = points.cols; _pts.create( nidx, dims, points.type());
int i, nidx = (int)idx.size(); pts = _pts.getMat();
pts.create( nidx, dims, points.type()); }
if(_labels) if(_labels.needed())
_labels->resize(nidx); {
_labels.create(nidx, 1, CV_32S, -1, true);
labelsmat = _labels.getMat();
CV_Assert( labelsmat.isContinuous() );
dstlabels = labelsmat.ptr<int>();
}
const int* srclabels = !labels.empty() ? &labels[0] : 0;
for( i = 0; i < nidx; i++ ) for( i = 0; i < nidx; i++ )
{ {
int k = idx[i]; int k = idx[i];
CV_Assert( (unsigned)k < (unsigned)points.rows ); CV_Assert( (unsigned)k < (unsigned)points.rows );
const float* src = points.ptr<float>(k); const float* src = points.ptr<float>(k);
if( pts.data )
std::copy(src, src + dims, pts.ptr<float>(i)); std::copy(src, src + dims, pts.ptr<float>(i));
if(_labels) (*_labels)[i] = labels[k]; if( dstlabels )
dstlabels[i] = srclabels ? srclabels[k] : k;
} }
} }
@ -4047,7 +4002,7 @@ const float* KDTree::getPoint(int ptidx, int* label) const
{ {
CV_Assert( (unsigned)ptidx < (unsigned)points.rows); CV_Assert( (unsigned)ptidx < (unsigned)points.rows);
if(label) if(label)
*label = label[ptidx]; *label = labels[ptidx];
return points.ptr<float>(ptidx); return points.ptr<float>(ptidx);
} }

17
modules/core/src/drawing.cpp
Unescape View File

@ -235,7 +235,7 @@ LineIterator::LineIterator(const Mat& img, Point pt1, Point pt2,
static void static void
Line( Mat& img, Point pt1, Point pt2, Line( Mat& img, Point pt1, Point pt2,
const void* color, int connectivity = 8 ) const void* _color, int connectivity = 8 )
{ {
if( connectivity == 0 ) if( connectivity == 0 )
connectivity = 8; connectivity = 8;
@ -245,10 +245,21 @@ Line( Mat& img, Point pt1, Point pt2,
LineIterator iterator(img, pt1, pt2, connectivity, true); LineIterator iterator(img, pt1, pt2, connectivity, true);
int i, count = iterator.count; int i, count = iterator.count;
int pix_size = (int)img.elemSize(); int pix_size = (int)img.elemSize();
const uchar* color = (const uchar*)_color;
for( i = 0; i < count; i++, ++iterator ) for( i = 0; i < count; i++, ++iterator )
{ {
CV_MEMCPY_AUTO( *iterator, color, pix_size ); uchar* ptr = *iterator;
if( pix_size == 1 )
ptr[0] = color[0];
else if( pix_size == 3 )
{
ptr[0] = color[0];
ptr[1] = color[1];
ptr[2] = color[2];
}
else
memcpy( *iterator, color, pix_size );
} }
} }
@ -1317,7 +1328,7 @@ Circle( Mat& img, Point center, int radius, const void* color, int fill )
center.y >= radius && center.y < size.height - radius; center.y >= radius && center.y < size.height - radius;
#define ICV_PUT_POINT( ptr, x ) \ #define ICV_PUT_POINT( ptr, x ) \
CV_MEMCPY_CHAR( ptr + (x)*pix_size, color, pix_size ); memcpy( ptr + (x)*pix_size, color, pix_size );
while( dx >= dy ) while( dx >= dy )
{ {

84
modules/core/src/dxt.cpp
Unescape View File

@ -1449,27 +1449,25 @@ static void CCSIDFT_64f( const double* src, double* dst, int n, int nf, int* fac
CCSIDFT( src, dst, n, nf, factors, itab, wave, tab_size, spec, buf, flags, scale); CCSIDFT( src, dst, n, nf, factors, itab, wave, tab_size, spec, buf, flags, scale);
} }
}
void dft( const Mat& src0, Mat& dst, int flags, int nonzero_rows )
{
static DFTFunc dft_tbl[6];
static int inittab = 0;
if( !inittab ) void cv::dft( const InputArray& _src0, OutputArray _dst, int flags, int nonzero_rows )
{ {
dft_tbl[0] = (DFTFunc)DFT_32f; static DFTFunc dft_tbl[6] =
dft_tbl[1] = (DFTFunc)RealDFT_32f; {
dft_tbl[2] = (DFTFunc)CCSIDFT_32f; (DFTFunc)DFT_32f,
dft_tbl[3] = (DFTFunc)DFT_64f; (DFTFunc)RealDFT_32f,
dft_tbl[4] = (DFTFunc)RealDFT_64f; (DFTFunc)CCSIDFT_32f,
dft_tbl[5] = (DFTFunc)CCSIDFT_64f; (DFTFunc)DFT_64f,
inittab = 1; (DFTFunc)RealDFT_64f,
} (DFTFunc)CCSIDFT_64f
};
AutoBuffer<uchar> buf; AutoBuffer<uchar> buf;
void *spec = 0; void *spec = 0;
Mat src = src0; Mat src0 = _src0.getMat(), src = src0;
int prev_len = 0, stage = 0; int prev_len = 0, stage = 0;
bool inv = (flags & DFT_INVERSE) != 0; bool inv = (flags & DFT_INVERSE) != 0;
int nf = 0, real_transform = src.channels() == 1 || (inv && (flags & DFT_REAL_OUTPUT)!=0); int nf = 0, real_transform = src.channels() == 1 || (inv && (flags & DFT_REAL_OUTPUT)!=0);
@ -1485,11 +1483,13 @@ void dft( const Mat& src0, Mat& dst, int flags, int nonzero_rows )
CV_Assert( type == CV_32FC1 || type == CV_32FC2 || type == CV_64FC1 || type == CV_64FC2 ); CV_Assert( type == CV_32FC1 || type == CV_32FC2 || type == CV_64FC1 || type == CV_64FC2 );
if( !inv && src.channels() == 1 && (flags & DFT_COMPLEX_OUTPUT) ) if( !inv && src.channels() == 1 && (flags & DFT_COMPLEX_OUTPUT) )
dst.create( src.size(), CV_MAKETYPE(depth, 2) ); _dst.create( src.size(), CV_MAKETYPE(depth, 2) );
else if( inv && src.channels() == 2 && (flags & DFT_REAL_OUTPUT) ) else if( inv && src.channels() == 2 && (flags & DFT_REAL_OUTPUT) )
dst.create( src.size(), depth ); _dst.create( src.size(), depth );
else else
dst.create( src.size(), type ); _dst.create( src.size(), type );
Mat dst = _dst.getMat();
if( !real_transform ) if( !real_transform )
elem_size = complex_elem_size; elem_size = complex_elem_size;
@ -1840,14 +1840,15 @@ void dft( const Mat& src0, Mat& dst, int flags, int nonzero_rows )
} }
void idft( const Mat& src, Mat& dst, int flags, int nonzero_rows ) void cv::idft( const InputArray& src, OutputArray dst, int flags, int nonzero_rows )
{ {
dft( src, dst, flags | DFT_INVERSE, nonzero_rows ); dft( src, dst, flags | DFT_INVERSE, nonzero_rows );
} }
void mulSpectrums( const Mat& srcA, const Mat& srcB, void cv::mulSpectrums( const InputArray& _srcA, const InputArray& _srcB,
Mat& dst, int flags, bool conjB ) OutputArray _dst, int flags, bool conjB )
{ {
Mat srcA = _srcA.getMat(), srcB = _srcB.getMat();
int depth = srcA.depth(), cn = srcA.channels(), type = srcA.type(); int depth = srcA.depth(), cn = srcA.channels(), type = srcA.type();
int rows = srcA.rows, cols = srcA.cols; int rows = srcA.rows, cols = srcA.cols;
int j, k; int j, k;
@ -1855,7 +1856,8 @@ void mulSpectrums( const Mat& srcA, const Mat& srcB,
CV_Assert( type == srcB.type() && srcA.size() == srcB.size() ); CV_Assert( type == srcB.type() && srcA.size() == srcB.size() );
CV_Assert( type == CV_32FC1 || type == CV_32FC2 || type == CV_64FC1 || type == CV_64FC2 ); CV_Assert( type == CV_32FC1 || type == CV_32FC2 || type == CV_64FC1 || type == CV_64FC2 );
dst.create( srcA.rows, srcA.cols, type ); _dst.create( srcA.rows, srcA.cols, type );
Mat dst = _dst.getMat();
bool is_1d = (flags & DFT_ROWS) || (rows == 1 || (cols == 1 && bool is_1d = (flags & DFT_ROWS) || (rows == 1 || (cols == 1 &&
srcA.isContinuous() && srcB.isContinuous() && dst.isContinuous())); srcA.isContinuous() && srcB.isContinuous() && dst.isContinuous()));
@ -2008,6 +2010,9 @@ void mulSpectrums( const Mat& srcA, const Mat& srcB,
Discrete Cosine Transform Discrete Cosine Transform
\****************************************************************************************/ \****************************************************************************************/
namespace cv
{
/* DCT is calculated using DFT, as described here: /* DCT is calculated using DFT, as described here:
http://www.ece.utexas.edu/~bevans/courses/ee381k/lectures/09_DCT/lecture9/: http://www.ece.utexas.edu/~bevans/courses/ee381k/lectures/09_DCT/lecture9/:
*/ */
@ -2211,22 +2216,20 @@ static void IDCT_64f(const double* src, int src_step, double* dft_src, double* d
n, nf, factors, itab, dft_wave, dct_wave, spec, buf); n, nf, factors, itab, dft_wave, dct_wave, spec, buf);
} }
void dct( const Mat& src0, Mat& dst, int flags ) }
{
static DCTFunc dct_tbl[4];
static int inittab = 0;
if( !inittab ) void cv::dct( const InputArray& _src0, OutputArray _dst, int flags )
{ {
dct_tbl[0] = (DCTFunc)DCT_32f; static DCTFunc dct_tbl[4] =
dct_tbl[1] = (DCTFunc)IDCT_32f; {
dct_tbl[2] = (DCTFunc)DCT_64f; (DCTFunc)DCT_32f,
dct_tbl[3] = (DCTFunc)IDCT_64f; (DCTFunc)IDCT_32f,
inittab = 1; (DCTFunc)DCT_64f,
} (DCTFunc)IDCT_64f
};
bool inv = (flags & DCT_INVERSE) != 0; bool inv = (flags & DCT_INVERSE) != 0;
Mat src = src0; Mat src0 = _src0.getMat(), src = src0;
int type = src.type(), depth = src.depth(); int type = src.type(), depth = src.depth();
void /* *spec_dft = 0, */ *spec = 0; void /* *spec_dft = 0, */ *spec = 0;
@ -2242,7 +2245,8 @@ void dct( const Mat& src0, Mat& dst, int flags )
AutoBuffer<uchar> buf; AutoBuffer<uchar> buf;
CV_Assert( type == CV_32FC1 || type == CV_64FC1 ); CV_Assert( type == CV_32FC1 || type == CV_64FC1 );
dst.create( src.rows, src.cols, type ); _dst.create( src.rows, src.cols, type );
Mat dst = _dst.getMat();
DCTFunc dct_func = dct_tbl[inv + (depth == CV_64F)*2]; DCTFunc dct_func = dct_tbl[inv + (depth == CV_64F)*2];
@ -2369,11 +2373,14 @@ void dct( const Mat& src0, Mat& dst, int flags )
} }
void idct( const Mat& src, Mat& dst, int flags ) void cv::idct( const InputArray& src, OutputArray dst, int flags )
{ {
dct( src, dst, flags | DCT_INVERSE ); dct( src, dst, flags | DCT_INVERSE );
} }
namespace cv
{
static const int optimalDFTSizeTab[] = { static const int optimalDFTSizeTab[] = {
1, 2, 3, 4, 5, 6, 8, 9, 10, 12, 15, 16, 18, 20, 24, 25, 27, 30, 32, 36, 40, 45, 48, 1, 2, 3, 4, 5, 6, 8, 9, 10, 12, 15, 16, 18, 20, 24, 25, 27, 30, 32, 36, 40, 45, 48,
50, 54, 60, 64, 72, 75, 80, 81, 90, 96, 100, 108, 120, 125, 128, 135, 144, 150, 160, 50, 54, 60, 64, 72, 75, 80, 81, 90, 96, 100, 108, 120, 125, 128, 135, 144, 150, 160,
@ -2555,8 +2562,9 @@ static const int optimalDFTSizeTab[] = {
2097152000, 2099520000, 2109375000, 2123366400, 2125764000 2097152000, 2099520000, 2109375000, 2123366400, 2125764000
}; };
int }
getOptimalDFTSize( int size0 )
int cv::getOptimalDFTSize( int size0 )
{ {
int a = 0, b = sizeof(optimalDFTSizeTab)/sizeof(optimalDFTSizeTab[0]) - 1; int a = 0, b = sizeof(optimalDFTSizeTab)/sizeof(optimalDFTSizeTab[0]) - 1;
if( (unsigned)size0 >= (unsigned)optimalDFTSizeTab[b] ) if( (unsigned)size0 >= (unsigned)optimalDFTSizeTab[b] )
@ -2574,8 +2582,6 @@ getOptimalDFTSize( int size0 )
return optimalDFTSizeTab[b]; return optimalDFTSizeTab[b];
} }
}
CV_IMPL void CV_IMPL void
cvDFT( const CvArr* srcarr, CvArr* dstarr, int flags, int nonzero_rows ) cvDFT( const CvArr* srcarr, CvArr* dstarr, int flags, int nonzero_rows )
{ {

137
modules/core/src/lapack.cpp
Unescape View File

@ -213,6 +213,8 @@ bool Cholesky(double* A, int m, double* b, int n)
return CholImpl(A, m, b, n); return CholImpl(A, m, b, n);
} }
}
/****************************************************************************************\ /****************************************************************************************\
* Determinant of the matrix * * Determinant of the matrix *
\****************************************************************************************/ \****************************************************************************************/
@ -222,8 +224,9 @@ bool Cholesky(double* A, int m, double* b, int n)
m(0,1)*((double)m(1,0)*m(2,2) - (double)m(1,2)*m(2,0)) + \ m(0,1)*((double)m(1,0)*m(2,2) - (double)m(1,2)*m(2,0)) + \
m(0,2)*((double)m(1,0)*m(2,1) - (double)m(1,1)*m(2,0))) m(0,2)*((double)m(1,0)*m(2,1) - (double)m(1,1)*m(2,0)))
double determinant( const Mat& mat ) double cv::determinant( const InputArray& _mat )
{ {
Mat mat = _mat.getMat();
double result = 0; double result = 0;
int type = mat.type(), rows = mat.rows; int type = mat.type(), rows = mat.rows;
size_t step = mat.step; size_t step = mat.step;
@ -325,12 +328,15 @@ double determinant( const Mat& mat )
#define Df( y, x ) ((float*)(dstdata + y*dststep))[x] #define Df( y, x ) ((float*)(dstdata + y*dststep))[x]
#define Dd( y, x ) ((double*)(dstdata + y*dststep))[x] #define Dd( y, x ) ((double*)(dstdata + y*dststep))[x]
double invert( const Mat& src, Mat& dst, int method ) double cv::invert( const InputArray& _src, OutputArray _dst, int method )
{ {
double result = 0; double result = 0;
Mat src = _src.getMat();
int type = src.type(); int type = src.type();
CV_Assert( method == DECOMP_LU || method == DECOMP_CHOLESKY || method == DECOMP_SVD ); CV_Assert( method == DECOMP_LU || method == DECOMP_CHOLESKY || method == DECOMP_SVD );
_dst.create( src.cols, src.rows, type );
Mat dst = _dst.getMat();
if( method == DECOMP_SVD ) if( method == DECOMP_SVD )
{ {
@ -346,7 +352,6 @@ double invert( const Mat& src, Mat& dst, int method )
} }
CV_Assert( src.rows == src.cols && (type == CV_32F || type == CV_64F)); CV_Assert( src.rows == src.cols && (type == CV_32F || type == CV_64F));
dst.create( src.rows, src.cols, type );
if( src.rows <= 3 ) if( src.rows <= 3 )
{ {
@ -572,9 +577,10 @@ double invert( const Mat& src, Mat& dst, int method )
* Solving a linear system * * Solving a linear system *
\****************************************************************************************/ \****************************************************************************************/
bool solve( const Mat& src, const Mat& _src2, Mat& dst, int method ) bool cv::solve( const InputArray& _src, const InputArray& _src2arg, OutputArray _dst, int method )
{ {
bool result = true; bool result = true;
Mat src = _src.getMat(), _src2 = _src2arg.getMat();
int type = src.type(); int type = src.type();
bool is_normal = (method & DECOMP_NORMAL) != 0; bool is_normal = (method & DECOMP_NORMAL) != 0;
@ -588,7 +594,8 @@ bool solve( const Mat& src, const Mat& _src2, Mat& dst, int method )
if( (method == DECOMP_LU || method == DECOMP_CHOLESKY) && if( (method == DECOMP_LU || method == DECOMP_CHOLESKY) &&
src.rows <= 3 && src.rows == src.cols && _src2.cols == 1 ) src.rows <= 3 && src.rows == src.cols && _src2.cols == 1 )
{ {
dst.create( src.cols, _src2.cols, src.type() ); _dst.create( src.cols, _src2.cols, src.type() );
Mat dst = _dst.getMat();
#define bf(y) ((float*)(bdata + y*src2step))[0] #define bf(y) ((float*)(bdata + y*src2step))[0]
#define bd(y) ((double*)(bdata + y*src2step))[0] #define bd(y) ((double*)(bdata + y*src2step))[0]
@ -729,7 +736,8 @@ bool solve( const Mat& src, const Mat& _src2, Mat& dst, int method )
char N[] = {'N', '\0'}, L[] = {'L', '\0'}; char N[] = {'N', '\0'}, L[] = {'L', '\0'};
Mat src2 = _src2; Mat src2 = _src2;
dst.create( src.cols, src2.cols, src.type() ); _dst.create( src.cols, src2.cols, src.type() );
Mat dst = _dst.getMat();
if( m <= n ) if( m <= n )
is_normal = false; is_normal = false;
@ -905,6 +913,9 @@ bool solve( const Mat& src, const Mat& _src2, Mat& dst, int method )
/////////////////// finding eigenvalues and eigenvectors of a symmetric matrix /////////////// /////////////////// finding eigenvalues and eigenvectors of a symmetric matrix ///////////////
namespace cv
{
template<typename Real> static inline Real hypot(Real a, Real b) template<typename Real> static inline Real hypot(Real a, Real b)
{ {
a = std::abs(a); a = std::abs(a);
@ -1077,9 +1088,10 @@ template<typename Real> bool jacobi(const Mat& _S0, Mat& _e, Mat& matE, bool com
} }
static bool eigen( const Mat& src, Mat& evals, Mat& evects, bool computeEvects, static bool eigen( const InputArray& _src, OutputArray _evals, OutputArray _evects, bool computeEvects,
int lowindex, int highindex ) int lowindex, int highindex )
{ {
Mat src = _src.getMat();
int type = src.type(); int type = src.type();
integer n = src.rows; integer n = src.rows;
@ -1094,9 +1106,14 @@ static bool eigen( const Mat& src, Mat& evals, Mat& evects, bool computeEvects,
CV_Assert( src.rows == src.cols ); CV_Assert( src.rows == src.cols );
CV_Assert (type == CV_32F || type == CV_64F); CV_Assert (type == CV_32F || type == CV_64F);
// allow for 1xn eigenvalue matrix too _evals.create(n, 1, type, -1, true);
if( !(evals.rows == 1 && evals.cols == n && evals.type() == type) ) Mat evals = _evals.getMat(), evects;
evals.create(n, 1, type);
if( computeEvects )
{
_evects.create(n, n, type);
evects = _evects.getMat();
}
if( n <= 20 ) if( n <= 20 )
{ {
@ -1122,10 +1139,7 @@ static bool eigen( const Mat& src, Mat& evals, Mat& evects, bool computeEvects,
lda = (int)(src.step/elem_size); lda = (int)(src.step/elem_size);
if( computeEvects ) if( computeEvects )
{
evects.create(n, n, type);
ldv = (int)(evects.step/elem_size); ldv = (int)(evects.step/elem_size);
}
bool copy_evals = !evals.isContinuous(); bool copy_evals = !evals.isContinuous();
@ -1211,19 +1225,21 @@ static bool eigen( const Mat& src, Mat& evals, Mat& evects, bool computeEvects,
return result; return result;
} }
bool eigen( const Mat& src, Mat& evals, int lowindex, int highindex ) }
bool cv::eigen( const InputArray& src, OutputArray evals, int lowindex, int highindex )
{ {
Mat evects; return eigen(src, evals, OutputArray(), false, lowindex, highindex);
return eigen(src, evals, evects, false, lowindex, highindex);
} }
bool eigen( const Mat& src, Mat& evals, Mat& evects, int lowindex, bool cv::eigen( const InputArray& src, OutputArray evals, OutputArray evects,
int highindex ) int lowindex, int highindex )
{ {
return eigen(src, evals, evects, true, lowindex, highindex); return eigen(src, evals, evects, true, lowindex, highindex);
} }
namespace cv
{
/* y[0:m,0:n] += diag(a[0:1,0:m]) * x[0:m,0:n] */ /* y[0:m,0:n] += diag(a[0:1,0:m]) * x[0:m,0:n] */
template<typename T1, typename T2, typename T3> static void template<typename T1, typename T2, typename T3> static void
@ -1316,29 +1332,33 @@ SVBkSb( int m, int n, const T* w, int incw,
} }
static void _SVDcompute( const Mat& a, Mat& w, Mat* u, Mat* vt, int flags ) static void _SVDcompute( const InputArray& _aarr, OutputArray _w,
OutputArray _u, OutputArray _vt, int flags )
{ {
Mat a = _aarr.getMat(), u, vt;
integer m = a.rows, n = a.cols, mn = std::max(m, n), nm = std::min(m, n); integer m = a.rows, n = a.cols, mn = std::max(m, n), nm = std::min(m, n);
int type = a.type(), elem_size = (int)a.elemSize(); int type = a.type(), elem_size = (int)a.elemSize();
bool compute_uv = u && vt; bool compute_uv = _u.needed() || _vt.needed();
if( flags & SVD::NO_UV ) if( flags & SVD::NO_UV )
{ {
if(u) u->release(); _u.release();
if(vt) vt->release(); _vt.release();
u = vt = 0;
compute_uv = false; compute_uv = false;
} }
if( compute_uv ) if( compute_uv )
{ {
u->create( (int)m, (int)((flags & SVD::FULL_UV) ? m : nm), type ); _u.create( (int)m, (int)((flags & SVD::FULL_UV) ? m : nm), type );
vt->create( (int)((flags & SVD::FULL_UV) ? n : nm), n, type ); _vt.create( (int)((flags & SVD::FULL_UV) ? n : nm), n, type );
u = _u.getMat();
vt = _vt.getMat();
} }
w.create(nm, 1, type); _w.create(nm, 1, type, -1, true);
Mat _a = a; Mat _a = a, w = _w.getMat();
CV_Assert( w.isContinuous() );
int a_ofs = 0, work_ofs=0, iwork_ofs=0, buf_size = 0; int a_ofs = 0, work_ofs=0, iwork_ofs=0, buf_size = 0;
bool temp_a = false; bool temp_a = false;
double u1=0, v1=0, work1=0; double u1=0, v1=0, work1=0;
@ -1353,7 +1373,7 @@ static void _SVDcompute( const Mat& a, Mat& w, Mat* u, Mat* vt, int flags )
{ {
if( mode[0] == 'N' || mode[0] == 'A' ) if( mode[0] == 'N' || mode[0] == 'A' )
temp_a = true; temp_a = true;
else if( compute_uv && (a.size() == vt->size() || a.size() == u->size()) && mode[0] == 'S' ) else if( compute_uv && (a.size() == vt.size() || a.size() == u.size()) && mode[0] == 'S' )
mode[0] = 'O'; mode[0] = 'O';
} }
@ -1396,59 +1416,67 @@ static void _SVDcompute( const Mat& a, Mat& w, Mat* u, Mat* vt, int flags )
if( !(flags & SVD::MODIFY_A) && !temp_a ) if( !(flags & SVD::MODIFY_A) && !temp_a )
{ {
if( compute_uv && a.size() == vt->size() ) if( compute_uv && a.size() == vt.size() )
{ {
a.copyTo(*vt); a.copyTo(vt);
_a = *vt; _a = vt;
} }
else if( compute_uv && a.size() == u->size() ) else if( compute_uv && a.size() == u.size() )
{ {
a.copyTo(*u); a.copyTo(u);
_a = *u; _a = u;
} }
} }
if( compute_uv ) if( compute_uv )
{ {
ldv = (int)(vt->step ? vt->step/elem_size : vt->cols); ldv = (int)(vt.step ? vt.step/elem_size : vt.cols);
ldu = (int)(u->step ? u->step/elem_size : u->cols); ldu = (int)(u.step ? u.step/elem_size : u.cols);
} }
lda = (int)(_a.step ? _a.step/elem_size : _a.cols); lda = (int)(_a.step ? _a.step/elem_size : _a.cols);
if( type == CV_32F ) if( type == CV_32F )
{ {
sgesdd_(mode, &n, &m, (float*)_a.data, &lda, (float*)w.data, sgesdd_(mode, &n, &m, _a.ptr<float>(), &lda, w.ptr<float>(),
vt ? (float*)vt->data : (float*)&v1, &ldv, u ? (float*)u->data : (float*)&u1, &ldu, vt.data ? vt.ptr<float>() : (float*)&v1, &ldv,
(float*)(buffer + work_ofs), &lwork, (integer*)(buffer + iwork_ofs), &info ); u.data ? u.ptr<float>() : (float*)&u1, &ldu,
(float*)(buffer + work_ofs), &lwork,
(integer*)(buffer + iwork_ofs), &info );
} }
else else
{ {
dgesdd_(mode, &n, &m, (double*)_a.data, &lda, (double*)w.data, dgesdd_(mode, &n, &m, _a.ptr<double>(), &lda, w.ptr<double>(),
vt ? (double*)vt->data : &v1, &ldv, u ? (double*)u->data : &u1, &ldu, vt.data ? vt.ptr<double>() : &v1, &ldv,
(double*)(buffer + work_ofs), &lwork, (integer*)(buffer + iwork_ofs), &info ); u.data ? u.ptr<double>() : &u1, &ldu,
(double*)(buffer + work_ofs), &lwork,
(integer*)(buffer + iwork_ofs), &info );
} }
CV_Assert(info >= 0); CV_Assert(info >= 0);
if(info != 0) if(info != 0)
{ {
*u = Scalar(0.); if( u.data )
*vt = Scalar(0.); u = Scalar(0.);
if( vt.data )
vt = Scalar(0.);
w = Scalar(0.); w = Scalar(0.);
} }
} }
void SVD::compute( const Mat& a, Mat& w, Mat& u, Mat& vt, int flags ) void SVD::compute( const InputArray& a, OutputArray w, OutputArray u, OutputArray vt, int flags )
{ {
_SVDcompute(a, w, &u, &vt, flags); _SVDcompute(a, w, u, vt, flags);
} }
void SVD::compute( const Mat& a, Mat& w, int flags ) void SVD::compute( const InputArray& a, OutputArray w, int flags )
{ {
_SVDcompute(a, w, 0, 0, flags); _SVDcompute(a, w, OutputArray(), OutputArray(), flags);
} }
void SVD::backSubst( const Mat& w, const Mat& u, const Mat& vt, const Mat& rhs, Mat& dst ) void SVD::backSubst( const InputArray& _w, const InputArray& _u, const InputArray& _vt,
const InputArray& _rhs, OutputArray _dst )
{ {
Mat w = _w.getMat(), u = _u.getMat(), vt = _vt.getMat(), rhs = _rhs.getMat();
int type = w.type(), esz = (int)w.elemSize(); int type = w.type(), esz = (int)w.elemSize();
int m = u.rows, n = vt.cols, nb = rhs.data ? rhs.cols : m; int m = u.rows, n = vt.cols, nb = rhs.data ? rhs.cols : m;
AutoBuffer<double> buffer(nb); AutoBuffer<double> buffer(nb);
@ -1456,7 +1484,8 @@ void SVD::backSubst( const Mat& w, const Mat& u, const Mat& vt, const Mat& rhs,
CV_Assert( rhs.data == 0 || (rhs.type() == type && rhs.rows == m) ); CV_Assert( rhs.data == 0 || (rhs.type() == type && rhs.rows == m) );
dst.create( n, nb, type ); _dst.create( n, nb, type );
Mat dst = _dst.getMat();
if( type == CV_32F ) if( type == CV_32F )
SVBkSb(m, n, (float*)w.data, 1, (float*)u.data, (int)(u.step/esz), false, SVBkSb(m, n, (float*)w.data, 1, (float*)u.data, (int)(u.step/esz), false,
(float*)vt.data, (int)(vt.step/esz), true, (float*)rhs.data, (int)(rhs.step/esz), (float*)vt.data, (int)(vt.step/esz), true, (float*)rhs.data, (int)(rhs.step/esz),
@ -1470,14 +1499,14 @@ void SVD::backSubst( const Mat& w, const Mat& u, const Mat& vt, const Mat& rhs,
} }
SVD& SVD::operator ()(const Mat& a, int flags) SVD& SVD::operator ()(const InputArray& a, int flags)
{ {
_SVDcompute(a, w, &u, &vt, flags); _SVDcompute(a, w, u, vt, flags);
return *this; return *this;
} }
void SVD::backSubst( const Mat& rhs, Mat& dst ) const void SVD::backSubst( const InputArray& rhs, OutputArray dst ) const
{ {
backSubst( w, u, vt, rhs, dst ); backSubst( w, u, vt, rhs, dst );
} }

782
modules/core/src/mathfuncs.cpp
View File

File diff suppressed because it is too large Load Diff

1296
modules/core/src/matmul.cpp
View File

File diff suppressed because it is too large Load Diff

41
modules/core/src/matop.cpp
Unescape View File

@ -208,9 +208,11 @@ static inline bool isIdentity(const MatExpr& e) { return e.op == &g_MatOp_Identi
static inline bool isAddEx(const MatExpr& e) { return e.op == &g_MatOp_AddEx; } static inline bool isAddEx(const MatExpr& e) { return e.op == &g_MatOp_AddEx; }
static inline bool isScaled(const MatExpr& e) { return isAddEx(e) && (!e.b.data || e.beta == 0) && e.s == Scalar(); } static inline bool isScaled(const MatExpr& e) { return isAddEx(e) && (!e.b.data || e.beta == 0) && e.s == Scalar(); }
static inline bool isBin(const MatExpr& e, char c) { return e.op == &g_MatOp_Bin && e.flags == c; } static inline bool isBin(const MatExpr& e, char c) { return e.op == &g_MatOp_Bin && e.flags == c; }
static inline bool isCmp(const MatExpr& e) { return e.op == &g_MatOp_Cmp; }
static inline bool isReciprocal(const MatExpr& e) { return isBin(e,'/') && (!e.b.data || e.beta == 0); } static inline bool isReciprocal(const MatExpr& e) { return isBin(e,'/') && (!e.b.data || e.beta == 0); }
static inline bool isT(const MatExpr& e) { return e.op == &g_MatOp_T; } static inline bool isT(const MatExpr& e) { return e.op == &g_MatOp_T; }
static inline bool isInv(const MatExpr& e) { return e.op == &g_MatOp_Invert; } static inline bool isInv(const MatExpr& e) { return e.op == &g_MatOp_Invert; }
static inline bool isSolve(const MatExpr& e) { return e.op == &g_MatOp_Solve; }
static inline bool isGEMM(const MatExpr& e) { return e.op == &g_MatOp_GEMM; } static inline bool isGEMM(const MatExpr& e) { return e.op == &g_MatOp_GEMM; }
static inline bool isMatProd(const MatExpr& e) { return e.op == &g_MatOp_GEMM && (!e.c.data || e.beta == 0); } static inline bool isMatProd(const MatExpr& e) { return e.op == &g_MatOp_GEMM && (!e.c.data || e.beta == 0); }
static inline bool isInitializer(const MatExpr& e) { return e.op == &g_MatOp_Initializer; } static inline bool isInitializer(const MatExpr& e) { return e.op == &g_MatOp_Initializer; }
@ -572,6 +574,17 @@ void MatOp::invert(const MatExpr& expr, int method, MatExpr& res) const
MatOp_Invert::makeExpr(res, method, m); MatOp_Invert::makeExpr(res, method, m);
} }
Size MatOp::size(const MatExpr& expr) const
{
return !expr.a.empty() ? expr.a.size() : expr.b.empty() ? expr.b.size() : expr.c.size();
}
int MatOp::type(const MatExpr& expr) const
{
return !expr.a.empty() ? expr.a.type() : expr.b.empty() ? expr.b.type() : expr.c.type();
}
////////////////////////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////////////////////////
MatExpr::MatExpr(const Mat& m) : op(&g_MatOp_Identity), flags(0), a(m), b(Mat()), c(Mat()), alpha(1), beta(0), s(Scalar()) MatExpr::MatExpr(const Mat& m) : op(&g_MatOp_Identity), flags(0), a(m), b(Mat()), c(Mat()), alpha(1), beta(0), s(Scalar())
@ -1142,6 +1155,30 @@ MatExpr abs(const MatExpr& e)
} }
Size MatExpr::size() const
{
if( isT(*this) || isInv(*this) )
return Size(a.rows, a.cols);
if( isGEMM(*this) )
return Size(b.cols, a.rows);
if( isSolve(*this) )
return Size(b.cols, a.cols);
if( isInitializer(*this) )
return a.size();
return op ? op->size(*this) : Size();
}
int MatExpr::type() const
{
if( isInitializer(*this) )
return a.type();
if( isCmp(*this) )
return CV_8U;
return op ? op->type(*this) : -1;
}
///////////////////////////////////////////////////////////////////////////////////////////////////// /////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_Identity::assign(const MatExpr& e, Mat& m, int type) const void MatOp_Identity::assign(const MatExpr& e, Mat& m, int type) const
@ -1552,10 +1589,10 @@ MatExpr Mat::inv(int method) const
} }
MatExpr Mat::mul(const Mat& m, double scale) const MatExpr Mat::mul(const InputArray& m, double scale) const
{ {
MatExpr e; MatExpr e;
MatOp_Bin::makeExpr(e, '*', *this, m, scale); MatOp_Bin::makeExpr(e, '*', *this, m.getMat(), scale);
return e; return e;
} }

929
modules/core/src/matrix.cpp
View File

File diff suppressed because it is too large Load Diff

258
modules/core/src/precomp.hpp
Unescape View File

@ -65,74 +65,6 @@
#include <stdlib.h> #include <stdlib.h>
#include <string.h> #include <string.h>
#define CV_MEMCPY_CHAR( dst, src, len ) \
{ \
size_t _icv_memcpy_i_, _icv_memcpy_len_ = (len); \
char* _icv_memcpy_dst_ = (char*)(dst); \
const char* _icv_memcpy_src_ = (const char*)(src); \
\
for( _icv_memcpy_i_ = 0; _icv_memcpy_i_ < _icv_memcpy_len_; _icv_memcpy_i_++ ) \
_icv_memcpy_dst_[_icv_memcpy_i_] = _icv_memcpy_src_[_icv_memcpy_i_]; \
}
#define CV_MEMCPY_INT( dst, src, len ) \
{ \
size_t _icv_memcpy_i_, _icv_memcpy_len_ = (len); \
int* _icv_memcpy_dst_ = (int*)(dst); \
const int* _icv_memcpy_src_ = (const int*)(src); \
assert( ((size_t)_icv_memcpy_src_&(sizeof(int)-1)) == 0 && \
((size_t)_icv_memcpy_dst_&(sizeof(int)-1)) == 0 ); \
\
for(_icv_memcpy_i_=0;_icv_memcpy_i_<_icv_memcpy_len_;_icv_memcpy_i_++) \
_icv_memcpy_dst_[_icv_memcpy_i_] = _icv_memcpy_src_[_icv_memcpy_i_];\
}
#define CV_MEMCPY_AUTO( dst, src, len ) \
{ \
size_t _icv_memcpy_i_, _icv_memcpy_len_ = (len); \
char* _icv_memcpy_dst_ = (char*)(dst); \
const char* _icv_memcpy_src_ = (const char*)(src); \
if( (_icv_memcpy_len_ & (sizeof(int)-1)) == 0 ) \
{ \
assert( ((size_t)_icv_memcpy_src_&(sizeof(int)-1)) == 0 && \
((size_t)_icv_memcpy_dst_&(sizeof(int)-1)) == 0 ); \
for( _icv_memcpy_i_ = 0; _icv_memcpy_i_ < _icv_memcpy_len_; \
_icv_memcpy_i_+=sizeof(int) ) \
{ \
*(int*)(_icv_memcpy_dst_+_icv_memcpy_i_) = \
*(const int*)(_icv_memcpy_src_+_icv_memcpy_i_); \
} \
} \
else \
{ \
for(_icv_memcpy_i_ = 0; _icv_memcpy_i_ < _icv_memcpy_len_; _icv_memcpy_i_++)\
_icv_memcpy_dst_[_icv_memcpy_i_] = _icv_memcpy_src_[_icv_memcpy_i_]; \
} \
}
#define CV_ZERO_CHAR( dst, len ) \
{ \
size_t _icv_memcpy_i_, _icv_memcpy_len_ = (len); \
char* _icv_memcpy_dst_ = (char*)(dst); \
\
for( _icv_memcpy_i_ = 0; _icv_memcpy_i_ < _icv_memcpy_len_; _icv_memcpy_i_++ ) \
_icv_memcpy_dst_[_icv_memcpy_i_] = '\0'; \
}
#define CV_ZERO_INT( dst, len ) \
{ \
size_t _icv_memcpy_i_, _icv_memcpy_len_ = (len); \
int* _icv_memcpy_dst_ = (int*)(dst); \
assert( ((size_t)_icv_memcpy_dst_&(sizeof(int)-1)) == 0 ); \
\
for(_icv_memcpy_i_=0;_icv_memcpy_i_<_icv_memcpy_len_;_icv_memcpy_i_++) \
_icv_memcpy_dst_[_icv_memcpy_i_] = 0; \
}
namespace cv namespace cv
{ {
@ -150,24 +82,12 @@ extern const uchar g_Saturate8u[];
#define CV_MIN_8U(a,b) ((a) - CV_FAST_CAST_8U((a) - (b))) #define CV_MIN_8U(a,b) ((a) - CV_FAST_CAST_8U((a) - (b)))
#define CV_MAX_8U(a,b) ((a) + CV_FAST_CAST_8U((b) - (a))) #define CV_MAX_8U(a,b) ((a) + CV_FAST_CAST_8U((b) - (a)))
typedef void (*CopyMaskFunc)(const Mat& src, Mat& dst, const Mat& mask);
extern CopyMaskFunc g_copyMaskFuncTab[];
static inline CopyMaskFunc getCopyMaskFunc(int esz)
{
CV_Assert( (unsigned)esz <= 32U );
CopyMaskFunc func = g_copyMaskFuncTab[esz];
CV_Assert( func != 0 );
return func;
}
#if defined WIN32 || defined _WIN32 #if defined WIN32 || defined _WIN32
void deleteThreadAllocData(); void deleteThreadAllocData();
void deleteThreadRNGData(); void deleteThreadRNGData();
#endif #endif
template<typename T1, typename T2=T1, typename T3=T1> struct OpAdd template<typename T1, typename T2=T1, typename T3=T1> struct OpAdd
{ {
typedef T1 type1; typedef T1 type1;
@ -192,22 +112,6 @@ template<typename T1, typename T2=T1, typename T3=T1> struct OpRSub
T3 operator ()(T1 a, T2 b) const { return saturate_cast<T3>(b - a); } T3 operator ()(T1 a, T2 b) const { return saturate_cast<T3>(b - a); }
}; };
template<typename T1, typename T2=T1, typename T3=T1> struct OpMul
{
typedef T1 type1;
typedef T2 type2;
typedef T3 rtype;
T3 operator ()(T1 a, T2 b) const { return saturate_cast<T3>(a * b); }
};
template<typename T1, typename T2=T1, typename T3=T1> struct OpDiv
{
typedef T1 type1;
typedef T2 type2;
typedef T3 rtype;
T3 operator ()(T1 a, T2 b) const { return saturate_cast<T3>(a / b); }
};
template<typename T> struct OpMin template<typename T> struct OpMin
{ {
typedef T type1; typedef T type1;
@ -261,154 +165,34 @@ inline Size getContinuousSize( const Mat& m1, const Mat& m2,
struct NoVec struct NoVec
{ {
int operator()(const void*, const void*, void*, int) const { return 0; } size_t operator()(const void*, const void*, void*, size_t) const { return 0; }
}; };
extern volatile bool USE_SSE2;
template<class Op, class VecOp> static void typedef void (*BinaryFunc)(const uchar* src1, size_t step1,
binaryOpC1_( const Mat& srcmat1, const Mat& srcmat2, Mat& dstmat ) const uchar* src2, size_t step2,
{ uchar* dst, size_t step, Size sz,
Op op; VecOp vecOp; void*);
typedef typename Op::type1 T1;
typedef typename Op::type2 T2;
typedef typename Op::rtype DT;
const T1* src1 = (const T1*)srcmat1.data;
const T2* src2 = (const T2*)srcmat2.data;
DT* dst = (DT*)dstmat.data;
size_t step1 = srcmat1.step/sizeof(src1[0]);
size_t step2 = srcmat2.step/sizeof(src2[0]);
size_t step = dstmat.step/sizeof(dst[0]);
Size size = getContinuousSize( srcmat1, srcmat2, dstmat, dstmat.channels() );
if( size.width == 1 )
{
for( ; size.height--; src1 += step1, src2 += step2, dst += step )
dst[0] = op( src1[0], src2[0] );
return;
}
for( ; size.height--; src1 += step1, src2 += step2, dst += step )
{
int x;
x = vecOp(src1, src2, dst, size.width);
for( ; x <= size.width - 4; x += 4 )
{
DT f0, f1;
f0 = op( src1[x], src2[x] );
f1 = op( src1[x+1], src2[x+1] );
dst[x] = f0;
dst[x+1] = f1;
f0 = op(src1[x+2], src2[x+2]);
f1 = op(src1[x+3], src2[x+3]);
dst[x+2] = f0;
dst[x+3] = f1;
}
for( ; x < size.width; x++ )
dst[x] = op( src1[x], src2[x] );
}
}
typedef void (*BinaryFunc)(const Mat& src1, const Mat& src2, Mat& dst);
template<class Op> static void BinaryFunc getConvertFunc(int sdepth, int ddepth);
binarySOpCn_( const Mat& srcmat, Mat& dstmat, const Scalar& _scalar ) BinaryFunc getConvertScaleFunc(int sdepth, int ddepth);
{ BinaryFunc getCopyMaskFunc(size_t esz);
Op op;
typedef typename Op::type1 T;
typedef typename Op::type2 WT;
typedef typename Op::rtype DT;
const T* src0 = (const T*)srcmat.data;
DT* dst0 = (DT*)dstmat.data;
size_t step1 = srcmat.step/sizeof(src0[0]);
size_t step = dstmat.step/sizeof(dst0[0]);
int cn = dstmat.channels();
Size size = getContinuousSize( srcmat, dstmat, cn );
WT scalar[12];
scalarToRawData(_scalar, scalar, CV_MAKETYPE(DataType<WT>::depth,cn), 12);
for( ; size.height--; src0 += step1, dst0 += step )
{
int i, len = size.width;
const T* src = src0;
T* dst = dst0;
for( ; (len -= 12) >= 0; dst += 12, src += 12 )
{
DT t0 = op(src[0], scalar[0]);
DT t1 = op(src[1], scalar[1]);
dst[0] = t0; dst[1] = t1;
t0 = op(src[2], scalar[2]); enum { BLOCK_SIZE = 1024 };
t1 = op(src[3], scalar[3]);
dst[2] = t0; dst[3] = t1;
t0 = op(src[4], scalar[4]); #ifdef HAVE_IPP
t1 = op(src[5], scalar[5]); static inline IppiSize ippiSize(int width, int height) { IppiSize sz={width, height}; return sz; }
dst[4] = t0; dst[5] = t1; static inline IppiSize ippiSize(Size _sz) { reIppiSize sz={_sz.width, _sz.height}; return sz; }
#endif
t0 = op(src[6], scalar[6]);
t1 = op(src[7], scalar[7]);
dst[6] = t0; dst[7] = t1;
t0 = op(src[8], scalar[8]);
t1 = op(src[9], scalar[9]);
dst[8] = t0; dst[9] = t1;
t0 = op(src[10], scalar[10]);
t1 = op(src[11], scalar[11]);
dst[10] = t0; dst[11] = t1;
}
for( (len) += 12, i = 0; i < (len); i++ )
dst[i] = op((WT)src[i], scalar[i]);
}
}
template<class Op> static void
binarySOpC1_( const Mat& srcmat, Mat& dstmat, double _scalar )
{
Op op;
typedef typename Op::type1 T;
typedef typename Op::type2 WT;
typedef typename Op::rtype DT;
WT scalar = saturate_cast<WT>(_scalar);
const T* src = (const T*)srcmat.data;
DT* dst = (DT*)dstmat.data;
size_t step1 = srcmat.step/sizeof(src[0]);
size_t step = dstmat.step/sizeof(dst[0]);
Size size = srcmat.size();
size.width *= srcmat.channels();
if( srcmat.isContinuous() && dstmat.isContinuous() )
{
size.width *= size.height;
size.height = 1;
}
for( ; size.height--; src += step1, dst += step )
{
int x;
for( x = 0; x <= size.width - 4; x += 4 )
{
DT f0 = op( src[x], scalar );
DT f1 = op( src[x+1], scalar );
dst[x] = f0;
dst[x+1] = f1;
f0 = op( src[x+2], scalar );
f1 = op( src[x+3], scalar );
dst[x+2] = f0;
dst[x+3] = f1;
}
for( ; x < size.width; x++ )
dst[x] = op( src[x], scalar );
}
}
typedef void (*BinarySFuncCn)(const Mat& src1, Mat& dst, const Scalar& scalar); #if defined HAVE_IPP && (IPP_VERSION_MAJOR >= 7)
typedef void (*BinarySFuncC1)(const Mat& src1, Mat& dst, double scalar); #define ARITHM_USE_IPP 1
#define IF_IPP(then_call, else_call) then_call
#else
#define ARITHM_USE_IPP 0
#define IF_IPP(then_call, else_call) else_call
#endif
} }

532
modules/core/src/rand.cpp
View File

File diff suppressed because one or more lines are too long

1907
modules/core/src/stat.cpp
View File

File diff suppressed because it is too large Load Diff

2
modules/core/src/system.cpp
Unescape View File

@ -170,12 +170,14 @@ struct IPPInitializer
IPPInitializer ippInitializer; IPPInitializer ippInitializer;
#else #else
volatile bool useOptimizedFlag = false; volatile bool useOptimizedFlag = false;
volatile bool USE_SSE2 = false;
#endif #endif
void setUseOptimized( bool flag ) void setUseOptimized( bool flag )
{ {
useOptimizedFlag = flag; useOptimizedFlag = flag;
currentFeatures = flag ? &featuresEnabled : &featuresDisabled; currentFeatures = flag ? &featuresEnabled : &featuresDisabled;
USE_SSE2 = currentFeatures->have[CV_CPU_SSE2];
} }
bool useOptimized(void) bool useOptimized(void)

49
modules/core/test/test_arithm.cpp
Unescape View File

@ -35,7 +35,7 @@ struct BaseElemWiseOp
virtual int getRandomType(RNG& rng) virtual int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_ALL_BUT_8S, 1, return cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1,
ninputs > 1 ? ARITHM_MAX_CHANNELS : 4); ninputs > 1 ? ARITHM_MAX_CHANNELS : 4);
} }
@ -172,6 +172,10 @@ struct ScaleAddOp : public BaseAddOp
{ {
scaleAdd(src[0], alpha, src[1], dst); scaleAdd(src[0], alpha, src[1], dst);
} }
double getMaxErr(int depth)
{
return depth <= CV_32S ? 2 : depth < CV_64F ? 1e-4 : 1e-12;
}
}; };
@ -414,7 +418,7 @@ struct CmpOp : public BaseElemWiseOp
} }
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_ALL_BUT_8S, 1, 1); return cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1, 1);
} }
double getMaxErr(int) double getMaxErr(int)
@ -431,6 +435,8 @@ struct CmpSOp : public BaseElemWiseOp
{ {
BaseElemWiseOp::generateScalars(depth, rng); BaseElemWiseOp::generateScalars(depth, rng);
cmpop = rng.uniform(0, 6); cmpop = rng.uniform(0, 6);
if( depth < CV_32F )
gamma[0] = cvRound(gamma[0]);
} }
void op(const vector<Mat>& src, Mat& dst, const Mat&) void op(const vector<Mat>& src, Mat& dst, const Mat&)
{ {
@ -442,7 +448,7 @@ struct CmpSOp : public BaseElemWiseOp
} }
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_ALL_BUT_8S, 1, 1); return cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1, 1);
} }
double getMaxErr(int) double getMaxErr(int)
{ {
@ -465,7 +471,7 @@ struct CopyOp : public BaseElemWiseOp
} }
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_ALL, 1, ARITHM_MAX_CHANNELS); return cvtest::randomType(rng, DEPTH_MASK_ALL, 1, ARITHM_MAX_CHANNELS);
} }
double getMaxErr(int) double getMaxErr(int)
{ {
@ -488,7 +494,7 @@ struct SetOp : public BaseElemWiseOp
} }
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_ALL, 1, ARITHM_MAX_CHANNELS); return cvtest::randomType(rng, DEPTH_MASK_ALL, 1, ARITHM_MAX_CHANNELS);
} }
double getMaxErr(int) double getMaxErr(int)
{ {
@ -504,14 +510,14 @@ inRangeS_(const _Tp* src, const _WTp* a, const _WTp* b, uchar* dst, size_t total
for( i = 0; i < total; i++ ) for( i = 0; i < total; i++ )
{ {
_Tp val = src[i*cn]; _Tp val = src[i*cn];
dst[i] = a[0] <= val && val < b[0] ? 255 : 0; dst[i] = a[0] <= val && val <= b[0] ? 255 : 0;
} }
for( c = 1; c < cn; c++ ) for( c = 1; c < cn; c++ )
{ {
for( i = 0; i < total; i++ ) for( i = 0; i < total; i++ )
{ {
_Tp val = src[i*cn + c]; _Tp val = src[i*cn + c];
dst[i] = a[c] <= val && val < b[c] ? dst[i] : 0; dst[i] = a[c] <= val && val <= b[c] ? dst[i] : 0;
} }
} }
} }
@ -523,14 +529,14 @@ template<typename _Tp> static void inRange_(const _Tp* src, const _Tp* a, const
for( i = 0; i < total; i++ ) for( i = 0; i < total; i++ )
{ {
_Tp val = src[i*cn]; _Tp val = src[i*cn];
dst[i] = a[i*cn] <= val && val < b[i*cn] ? 255 : 0; dst[i] = a[i*cn] <= val && val <= b[i*cn] ? 255 : 0;
} }
for( c = 1; c < cn; c++ ) for( c = 1; c < cn; c++ )
{ {
for( i = 0; i < total; i++ ) for( i = 0; i < total; i++ )
{ {
_Tp val = src[i*cn + c]; _Tp val = src[i*cn + c];
dst[i] = a[i*cn + c] <= val && val < b[i*cn + c] ? dst[i] : 0; dst[i] = a[i*cn + c] <= val && val <= b[i*cn + c] ? dst[i] : 0;
} }
} }
} }
@ -703,13 +709,13 @@ struct ConvertScaleOp : public BaseElemWiseOp
} }
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
int srctype = cvtest::randomType(rng, cvtest::TYPE_MASK_ALL, 1, ARITHM_MAX_CHANNELS); int srctype = cvtest::randomType(rng, DEPTH_MASK_ALL, 1, ARITHM_MAX_CHANNELS);
ddepth = cvtest::randomType(rng, cvtest::TYPE_MASK_ALL, 1, 1); ddepth = cvtest::randomType(rng, DEPTH_MASK_ALL, 1, 1);
return srctype; return srctype;
} }
double getMaxErr(int) double getMaxErr(int)
{ {
return ddepth <= CV_32S ? 2 : ddepth < CV_64F ? 1e-4 : 1e-12; return ddepth <= CV_32S ? 2 : ddepth < CV_64F ? 1e-3 : 1e-12;
} }
void generateScalars(int depth, RNG& rng) void generateScalars(int depth, RNG& rng)
{ {
@ -940,7 +946,7 @@ struct ExpOp : public BaseElemWiseOp
ExpOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; ExpOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_FLT, 1, ARITHM_MAX_CHANNELS); return cvtest::randomType(rng, DEPTH_MASK_FLT, 1, ARITHM_MAX_CHANNELS);
} }
void getValueRange(int depth, double& minval, double& maxval) void getValueRange(int depth, double& minval, double& maxval)
{ {
@ -967,7 +973,7 @@ struct LogOp : public BaseElemWiseOp
LogOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; LogOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_FLT, 1, ARITHM_MAX_CHANNELS); return cvtest::randomType(rng, DEPTH_MASK_FLT, 1, ARITHM_MAX_CHANNELS);
} }
void getValueRange(int depth, double& minval, double& maxval) void getValueRange(int depth, double& minval, double& maxval)
{ {
@ -1052,7 +1058,7 @@ struct CartToPolarToCartOp : public BaseElemWiseOp
} }
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_FLT, 1, 1); return cvtest::randomType(rng, DEPTH_MASK_FLT, 1, 1);
} }
void op(const vector<Mat>& src, Mat& dst, const Mat&) void op(const vector<Mat>& src, Mat& dst, const Mat&)
{ {
@ -1128,7 +1134,7 @@ struct SumOp : public BaseElemWiseOp
} }
double getMaxErr(int) double getMaxErr(int)
{ {
return 1e-6; return 1e-5;
} }
}; };
@ -1139,7 +1145,7 @@ struct CountNonZeroOp : public BaseElemWiseOp
{} {}
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_ALL, 1, 1); return cvtest::randomType(rng, DEPTH_MASK_ALL, 1, 1);
} }
void op(const vector<Mat>& src, Mat& dst, const Mat& mask) void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
{ {
@ -1208,7 +1214,7 @@ struct NormOp : public BaseElemWiseOp
}; };
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_ALL_BUT_8S, 1, 4); return cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1, 4);
} }
void op(const vector<Mat>& src, Mat& dst, const Mat& mask) void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
{ {
@ -1242,7 +1248,7 @@ struct MinMaxLocOp : public BaseElemWiseOp
}; };
int getRandomType(RNG& rng) int getRandomType(RNG& rng)
{ {
return cvtest::randomType(rng, cvtest::TYPE_MASK_ALL_BUT_8S, 1, 1); return cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1, 1);
} }
void saveOutput(const vector<int>& minidx, const vector<int>& maxidx, void saveOutput(const vector<int>& minidx, const vector<int>& maxidx,
double minval, double maxval, Mat& dst) double minval, double maxval, Mat& dst)
@ -1341,6 +1347,8 @@ INSTANTIATE_TEST_CASE_P(Core_SubRS, ElemWiseTest, ::testing::Values(ElemWiseOpPt
INSTANTIATE_TEST_CASE_P(Core_ScaleAdd, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::ScaleAddOp))); INSTANTIATE_TEST_CASE_P(Core_ScaleAdd, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::ScaleAddOp)));
INSTANTIATE_TEST_CASE_P(Core_AddWeighted, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AddWeightedOp))); INSTANTIATE_TEST_CASE_P(Core_AddWeighted, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AddWeightedOp)));
INSTANTIATE_TEST_CASE_P(Core_AbsDiff, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AbsDiffOp))); INSTANTIATE_TEST_CASE_P(Core_AbsDiff, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AbsDiffOp)));
INSTANTIATE_TEST_CASE_P(Core_AbsDiffS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AbsDiffSOp))); INSTANTIATE_TEST_CASE_P(Core_AbsDiffS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AbsDiffSOp)));
INSTANTIATE_TEST_CASE_P(Core_And, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogicOp('&')))); INSTANTIATE_TEST_CASE_P(Core_And, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogicOp('&'))));
@ -1380,3 +1388,6 @@ INSTANTIATE_TEST_CASE_P(Core_Sum, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(
INSTANTIATE_TEST_CASE_P(Core_Norm, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::NormOp))); INSTANTIATE_TEST_CASE_P(Core_Norm, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::NormOp)));
INSTANTIATE_TEST_CASE_P(Core_MinMaxLoc, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MinMaxLocOp))); INSTANTIATE_TEST_CASE_P(Core_MinMaxLoc, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MinMaxLocOp)));
INSTANTIATE_TEST_CASE_P(Core_CartToPolarToCart, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::CartToPolarToCartOp))); INSTANTIATE_TEST_CASE_P(Core_CartToPolarToCart, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::CartToPolarToCartOp)));

1
modules/core/test/test_dxt.cpp
Unescape View File

@ -827,3 +827,4 @@ TEST(Core_DCT, accuracy) { CxCore_DCTTest test; test.safe_run(); }
TEST(Core_DFT, accuracy) { CxCore_DFTTest test; test.safe_run(); } TEST(Core_DFT, accuracy) { CxCore_DFTTest test; test.safe_run(); }
TEST(Core_MulSpectrums, accuracy) { CxCore_MulSpectrumsTest test; test.safe_run(); } TEST(Core_MulSpectrums, accuracy) { CxCore_MulSpectrumsTest test; test.safe_run(); }

85
modules/core/test/test_mat.cpp
Unescape View File

@ -277,8 +277,6 @@ public:
protected: protected:
void run(int) void run(int)
{ {
int code = cvtest::TS::OK;
double diffPrjEps, diffBackPrjEps, double diffPrjEps, diffBackPrjEps,
prjEps, backPrjEps, prjEps, backPrjEps,
evalEps, evecEps; evalEps, evecEps;
@ -327,26 +325,44 @@ protected:
if( err > eigenEps ) if( err > eigenEps )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy of eigen(); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "bad accuracy of eigen(); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
} }
// check pca eigenvalues // check pca eigenvalues
evalEps = 1e-6, evecEps = 1; evalEps = 1e-6, evecEps = 1e-3;
err = norm( rPCA.eigenvalues, subEval ); err = norm( rPCA.eigenvalues, subEval );
if( err > evalEps ) if( err > evalEps )
{ {
ts->printf( cvtest::TS::LOG, "pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
// check pca eigenvectors // check pca eigenvectors
err = norm( rPCA.eigenvectors, subEvec, CV_RELATIVE_L2 ); for(int i = 0; i < subEvec.rows; i++)
{
Mat r0 = rPCA.eigenvectors.row(i);
Mat r1 = subEvec.row(i);
err = norm( r0, r1, CV_L2 );
if( err > evecEps ) if( err > evecEps )
{ {
r1 *= -1;
double err2 = norm(r0, r1, CV_L2);
if( err2 > evecEps )
{
Mat tmp;
absdiff(rPCA.eigenvectors, subEvec, tmp);
double mval = 0; Point mloc;
minMaxLoc(tmp, 0, &mval, 0, &mloc);
ts->printf( cvtest::TS::LOG, "pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->printf( cvtest::TS::LOG, "max diff is %g at (i=%d, j=%d) (%g vs %g)\n",
goto exit_func; mval, mloc.y, mloc.x, rPCA.eigenvectors.at<float>(mloc.y, mloc.x),
subEvec.at<float>(mloc.y, mloc.x));
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
return;
}
}
} }
prjEps = 1.265, backPrjEps = 1.265; prjEps = 1.265, backPrjEps = 1.265;
@ -359,8 +375,8 @@ protected:
if( err > prjEps ) if( err > prjEps )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_ROW); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
// check pca backProject // check pca backProject
Mat backPrj = rPrjTestPoints.row(i) * subEvec + avg; Mat backPrj = rPrjTestPoints.row(i) * subEvec + avg;
@ -368,27 +384,28 @@ protected:
if( err > backPrjEps ) if( err > backPrjEps )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_ROW); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
} }
// 2. check C++ PCA & COL // 2. check C++ PCA & COL
cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, maxComponents ); cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, maxComponents );
diffPrjEps = 1, diffBackPrjEps = 1; diffPrjEps = 1, diffBackPrjEps = 1;
err = norm(cPCA.project(rTestPoints.t()), rPrjTestPoints.t(), CV_RELATIVE_L2 ); Mat ocvPrjTestPoints = cPCA.project(rTestPoints.t());
err = norm(cv::abs(ocvPrjTestPoints), cv::abs(rPrjTestPoints.t()), CV_RELATIVE_L2 );
if( err > diffPrjEps ) if( err > diffPrjEps )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_COL); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_COL); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
err = norm(cPCA.backProject(rPrjTestPoints.t()), rBackPrjTestPoints.t(), CV_RELATIVE_L2 ); err = norm(cPCA.backProject(ocvPrjTestPoints), rBackPrjTestPoints.t(), CV_RELATIVE_L2 );
if( err > diffBackPrjEps ) if( err > diffBackPrjEps )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
#ifdef CHECK_C #ifdef CHECK_C
@ -411,15 +428,15 @@ protected:
if( err > diffPrjEps ) if( err > diffPrjEps )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
err = norm(backPrjTestPoints, rBackPrjTestPoints, CV_RELATIVE_L2); err = norm(backPrjTestPoints, rBackPrjTestPoints, CV_RELATIVE_L2);
if( err > diffBackPrjEps ) if( err > diffBackPrjEps )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
// 3. check C PCA & COL // 3. check C PCA & COL
@ -435,27 +452,21 @@ protected:
cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints ); cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints ); cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
err = norm(prjTestPoints, rPrjTestPoints.t(), CV_RELATIVE_L2 ); err = norm(cv::abs(prjTestPoints), cv::abs(rPrjTestPoints.t()), CV_RELATIVE_L2 );
if( err > diffPrjEps ) if( err > diffPrjEps )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
err = norm(backPrjTestPoints, rBackPrjTestPoints.t(), CV_RELATIVE_L2); err = norm(backPrjTestPoints, rBackPrjTestPoints.t(), CV_RELATIVE_L2);
if( err > diffBackPrjEps ) if( err > diffBackPrjEps )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err ); ts->printf( cvtest::TS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );
code = cvtest::TS::FAIL_BAD_ACCURACY; ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
goto exit_func; return;
} }
#endif #endif
exit_func:
RNG& _rng = ts->get_rng();
_rng = rng;
ts->set_failed_test_info( code );
} }
}; };
@ -790,7 +801,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
break; break;
} }
minMaxLoc(Md, &val1, &val2, idx1, idx2); minMaxIdx(Md, &val1, &val2, idx1, idx2);
s1 = idx2string(idx1, dims), s2 = idx2string(idx2, dims); s1 = idx2string(idx1, dims), s2 = idx2string(idx2, dims);
if( (min_val < 0 && (val1 != min_val || s1 != min_sidx)) || if( (min_val < 0 && (val1 != min_val || s1 != min_sidx)) ||
(max_val > 0 && (val2 != max_val || s2 != max_sidx)) ) (max_val > 0 && (val2 != max_val || s2 != max_sidx)) )
@ -809,3 +820,5 @@ void Core_ArrayOpTest::run( int /* start_from */)
TEST(Core_PCA, accuracy) { Core_PCATest test; test.safe_run(); } TEST(Core_PCA, accuracy) { Core_PCATest test; test.safe_run(); }
TEST(Core_Reduce, accuracy) { Core_ReduceTest test; test.safe_run(); } TEST(Core_Reduce, accuracy) { Core_ReduceTest test; test.safe_run(); }
TEST(Core_Array, basic_operations) { Core_ArrayOpTest test; test.safe_run(); } TEST(Core_Array, basic_operations) { Core_ArrayOpTest test; test.safe_run(); }

2
modules/features2d/src/bagofwords.cpp
Unescape View File

@ -113,7 +113,7 @@ BOWKMeansTrainer::~BOWKMeansTrainer()
Mat BOWKMeansTrainer::cluster( const Mat& descriptors ) const Mat BOWKMeansTrainer::cluster( const Mat& descriptors ) const
{ {
Mat labels, vocabulary; Mat labels, vocabulary;
kmeans( descriptors, clusterCount, labels, termcrit, attempts, flags, &vocabulary ); kmeans( descriptors, clusterCount, labels, termcrit, attempts, flags, vocabulary );
return vocabulary; return vocabulary;
} }

11
modules/features2d/test/test_nearestneighbors.cpp
Unescape View File

@ -281,7 +281,6 @@ void CV_KDTreeTest_CPP::createModel( const Mat& data )
int CV_KDTreeTest_CPP::checkGetPoins( const Mat& data ) int CV_KDTreeTest_CPP::checkGetPoins( const Mat& data )
{ {
Mat res1( data.size(), data.type() ), Mat res1( data.size(), data.type() ),
res2( data.size(), data.type() ),
res3( data.size(), data.type() ); res3( data.size(), data.type() );
Mat idxs( 1, data.rows, CV_32SC1 ); Mat idxs( 1, data.rows, CV_32SC1 );
for( int pi = 0; pi < data.rows; pi++ ) for( int pi = 0; pi < data.rows; pi++ )
@ -292,14 +291,11 @@ int CV_KDTreeTest_CPP::checkGetPoins( const Mat& data )
for( int di = 0; di < data.cols; di++ ) for( int di = 0; di < data.cols; di++ )
res1.at<float>(pi, di) = point[di]; res1.at<float>(pi, di) = point[di];
} }
// 2nd way
tr->getPoints( idxs.ptr<int>(0), data.rows, res2 );
// 3d way // 3d way
tr->getPoints( idxs, res3 ); tr->getPoints( idxs, res3 );
if( norm( res1, data, NORM_L1) != 0 || if( norm( res1, data, NORM_L1) != 0 ||
norm( res2, data, NORM_L1) != 0 ||
norm( res3, data, NORM_L1) != 0) norm( res3, data, NORM_L1) != 0)
return cvtest::TS::FAIL_BAD_ACCURACY; return cvtest::TS::FAIL_BAD_ACCURACY;
return cvtest::TS::OK; return cvtest::TS::OK;
@ -309,7 +305,7 @@ int CV_KDTreeTest_CPP::checkFindBoxed()
{ {
vector<float> min( dims, minValue), max(dims, maxValue); vector<float> min( dims, minValue), max(dims, maxValue);
vector<int> indices; vector<int> indices;
tr->findOrthoRange( &min[0], &max[0], &indices ); tr->findOrthoRange( min, max, indices );
// TODO check indices // TODO check indices
if( (int)indices.size() != featuresCount) if( (int)indices.size() != featuresCount)
return cvtest::TS::FAIL_BAD_ACCURACY; return cvtest::TS::FAIL_BAD_ACCURACY;
@ -326,11 +322,12 @@ int CV_KDTreeTest_CPP::findNeighbors( Mat& points, Mat& neighbors )
for( int pi = 0; pi < points.rows; pi++ ) for( int pi = 0; pi < points.rows; pi++ )
{ {
// 1st way // 1st way
tr->findNearest( points.ptr<float>(pi), neighbors.cols, emax, neighbors.ptr<int>(pi) ); Mat nrow = neighbors.row(pi);
tr->findNearest( points.row(pi), neighbors.cols, emax, nrow );
// 2nd way // 2nd way
vector<int> neighborsIdx2( neighbors2.cols, 0 ); vector<int> neighborsIdx2( neighbors2.cols, 0 );
tr->findNearest( points.ptr<float>(pi), neighbors2.cols, emax, &neighborsIdx2 ); tr->findNearest( points.row(pi), neighbors2.cols, emax, neighborsIdx2 );
vector<int>::const_iterator it2 = neighborsIdx2.begin(); vector<int>::const_iterator it2 = neighborsIdx2.begin();
for( j = 0; it2 != neighborsIdx2.end(); ++it2, j++ ) for( j = 0; it2 != neighborsIdx2.end(); ++it2, j++ )
neighbors2.at<int>(pi,j) = *it2; neighbors2.at<int>(pi,j) = *it2;

2
modules/gpu/test/test_filters.cpp
Unescape View File

@ -344,7 +344,7 @@ protected:
ts->printf(cvtest::TS::LOG, "Tesing %s\n", names[i]); ts->printf(cvtest::TS::LOG, "Tesing %s\n", names[i]);
cv::Mat cpuRes; cv::Mat cpuRes;
cv::morphologyEx(img, cpuRes, ops[i], kernel); cv::morphologyEx(img, cpuRes, ops[i], (Mat)kernel);
GpuMat gpuRes; GpuMat gpuRes;
cv::gpu::morphologyEx(GpuMat(img), gpuRes, ops[i], kernel); cv::gpu::morphologyEx(GpuMat(img), gpuRes, ops[i], kernel);

2
modules/gpu/test/test_hog.cpp
Unescape View File

@ -249,7 +249,7 @@ struct CV_GpuHogGetDescriptorsTestRunner: cv::gpu::HOGDescriptor
cv::cvtColor(img_rgb, img, CV_BGR2BGRA); cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
computeBlockHistograms(cv::gpu::GpuMat(img)); computeBlockHistograms(cv::gpu::GpuMat(img));
// Everything is fine with interpolation for left top subimage // Everything is fine with interpolation for left top subimage
CHECK(cv::norm(block_hists, descriptors.rowRange(0, 1)) == 0.f, cvtest::TS::FAIL_INVALID_OUTPUT); CHECK(cv::norm((cv::Mat)block_hists, (cv::Mat)descriptors.rowRange(0, 1)) == 0.f, cvtest::TS::FAIL_INVALID_OUTPUT);
img_rgb = cv::imread(std::string(ts->get_data_path()) + "hog/positive2.png"); img_rgb = cv::imread(std::string(ts->get_data_path()) + "hog/positive2.png");
CHECK(!img_rgb.empty(), cvtest::TS::FAIL_MISSING_TEST_DATA); CHECK(!img_rgb.empty(), cvtest::TS::FAIL_MISSING_TEST_DATA);

2
modules/gpu/test/test_operator_async_call.cpp
Unescape View File

@ -74,7 +74,7 @@ struct CV_AsyncGpuMatTest : public cvtest::BaseTest
Mat cpu_gold0(100, 100, CV_8UC1, Scalar::all(255)); Mat cpu_gold0(100, 100, CV_8UC1, Scalar::all(255));
Mat cpu_gold1(100, 100, CV_8UC1, Scalar::all(128)); Mat cpu_gold1(100, 100, CV_8UC1, Scalar::all(128));
if (norm(cpudst0, cpu_gold0, NORM_INF) > 0 || norm(cpudst1, cpu_gold1, NORM_INF) > 0) if (norm((Mat)cpudst0, cpu_gold0, NORM_INF) > 0 || norm((Mat)cpudst1, cpu_gold1, NORM_INF) > 0)
ts->set_failed_test_info(cvtest::TS::FAIL_GENERIC); ts->set_failed_test_info(cvtest::TS::FAIL_GENERIC);
else else
ts->set_failed_test_info(cvtest::TS::OK); ts->set_failed_test_info(cvtest::TS::OK);

2
modules/gpu/test/test_operator_convert_to.cpp
Unescape View File

@ -92,7 +92,7 @@ void CV_GpuMatOpConvertToTest::run(int /* start_from */)
cpumatsrc.convertTo(cpumatdst, dst_type, 0.5, 3.0); cpumatsrc.convertTo(cpumatdst, dst_type, 0.5, 3.0);
gpumatsrc.convertTo(gpumatdst, dst_type, 0.5, 3.0); gpumatsrc.convertTo(gpumatdst, dst_type, 0.5, 3.0);
double r = norm(cpumatdst, gpumatdst, NORM_INF); double r = norm(cpumatdst, (Mat)gpumatdst, NORM_INF);
if (r > 1) if (r > 1)
{ {
ts->printf(cvtest::TS::LOG, ts->printf(cvtest::TS::LOG,

2
modules/gpu/test/test_operator_copy_to.cpp
Unescape View File

@ -106,7 +106,7 @@ bool CV_GpuMatOpCopyToTest::compare_matrix(cv::Mat & cpumat, gpu::GpuMat & gpuma
cv::waitKey(0); cv::waitKey(0);
#endif #endif
double ret = norm(cmat, gmat); double ret = norm(cmat, (Mat)gmat);
if (ret < 1.0) if (ret < 1.0)
return true; return true;

2
modules/gpu/test/test_operator_set_to.cpp
Unescape View File

@ -78,7 +78,7 @@ bool CV_GpuMatOpSetToTest::testSetTo(cv::Mat& cpumat, gpu::GpuMat& gpumat, const
cpumat.setTo(s, cpumask); cpumat.setTo(s, cpumask);
gpumat.setTo(s, gpumask); gpumat.setTo(s, gpumask);
double ret = norm(cpumat, gpumat, NORM_INF); double ret = norm(cpumat, (Mat)gpumat, NORM_INF);
if (ret < std::numeric_limits<double>::epsilon()) if (ret < std::numeric_limits<double>::epsilon())
return true; return true;

2
modules/gpu/test/test_stereo_bm.cpp
Unescape View File

@ -106,7 +106,7 @@ struct CV_GpuStereoBMTest : public cvtest::BaseTest
bm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), disp); bm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), disp);
disp.convertTo(disp, img_reference.type()); disp.convertTo(disp, img_reference.type());
double norm = cv::norm(disp, img_reference, cv::NORM_INF); double norm = cv::norm((Mat)disp, img_reference, cv::NORM_INF);
//cv::imwrite(std::string(ts->get_data_path()) + "stereobm/aloe-disp.png", disp); //cv::imwrite(std::string(ts->get_data_path()) + "stereobm/aloe-disp.png", disp);

2
modules/gpu/test/test_stereo_bm_async.cpp
Unescape View File

@ -70,7 +70,7 @@ struct CV_AsyncStereoBMTest : public cvtest::BaseTest
stream.waitForCompletion(); stream.waitForCompletion();
disp.convertTo(disp, img_reference.type()); disp.convertTo(disp, img_reference.type());
double norm = cv::norm(disp, img_reference, cv::NORM_INF); double norm = cv::norm((Mat)disp, img_reference, cv::NORM_INF);
if (norm >= 100) if (norm >= 100)
{ {

2
modules/gpu/test/test_stereo_bp.cpp
Unescape View File

@ -67,7 +67,7 @@ struct CV_GpuStereoBPTest : public cvtest::BaseTest
disp.convertTo(disp, img_template.type()); disp.convertTo(disp, img_template.type());
double norm = cv::norm(disp, img_template, cv::NORM_INF); double norm = cv::norm((cv::Mat)disp, img_template, cv::NORM_INF);
if (norm >= 0.5) if (norm >= 0.5)
{ {
ts->printf(cvtest::TS::LOG, "\nStereoBP norm = %f\n", norm); ts->printf(cvtest::TS::LOG, "\nStereoBP norm = %f\n", norm);

2
modules/gpu/test/test_stereo_csbp.cpp
Unescape View File

@ -67,7 +67,7 @@ struct CV_GpuStereoCSBPTest : public cvtest::BaseTest
disp.convertTo(disp, img_template.type()); disp.convertTo(disp, img_template.type());
double norm = cv::norm(disp, img_template, cv::NORM_INF); double norm = cv::norm((cv::Mat)disp, img_template, cv::NORM_INF);
if (norm >= 0.5) if (norm >= 0.5)
{ {
ts->printf(cvtest::TS::LOG, "\nConstantSpaceStereoBP norm = %f\n", norm); ts->printf(cvtest::TS::LOG, "\nConstantSpaceStereoBP norm = %f\n", norm);

18
modules/highgui/include/opencv2/highgui/highgui.hpp
Unescape View File

@ -66,7 +66,9 @@ CV_EXPORTS_W double getWindowProperty(const string& winname, int prop_id);//YV
//Only for Qt //Only for Qt
//------------------------ //------------------------
CV_EXPORTS CvFont fontQt(const string& nameFont, int pointSize CV_DEFAULT(-1), Scalar color CV_DEFAULT(Scalar::all(0)), int weight CV_DEFAULT(CV_FONT_NORMAL), int style CV_DEFAULT(CV_STYLE_NORMAL), int spacing CV_DEFAULT(0)); CV_EXPORTS CvFont fontQt(const string& nameFont, int pointSize CV_DEFAULT(-1),
Scalar color CV_DEFAULT(Scalar::all(0)), int weight CV_DEFAULT(CV_FONT_NORMAL),
int style CV_DEFAULT(CV_STYLE_NORMAL), int spacing CV_DEFAULT(0));
CV_EXPORTS void addText( const Mat& img, const string& text, Point org, CvFont font); CV_EXPORTS void addText( const Mat& img, const string& text, Point org, CvFont font);
CV_EXPORTS void displayOverlay(const string& winname, const string& text, int delayms); CV_EXPORTS void displayOverlay(const string& winname, const string& text, int delayms);
@ -81,10 +83,12 @@ CV_EXPORTS int startLoop(int (*pt2Func)(int argc, char *argv[]), int argc, char
CV_EXPORTS void stopLoop(); CV_EXPORTS void stopLoop();
typedef void (CV_CDECL *ButtonCallback)(int state, void* userdata); typedef void (CV_CDECL *ButtonCallback)(int state, void* userdata);
CV_EXPORTS int createButton( const string& bar_name, ButtonCallback on_change , void* userdata CV_DEFAULT(NULL), int type CV_DEFAULT(CV_PUSH_BUTTON), bool initial_button_state CV_DEFAULT(0)); CV_EXPORTS int createButton( const string& bar_name, ButtonCallback on_change,
void* userdata CV_DEFAULT(NULL), int type CV_DEFAULT(CV_PUSH_BUTTON),
bool initial_button_state CV_DEFAULT(0));
//------------------------- //-------------------------
CV_EXPORTS_W void imshow( const string& winname, const Mat& mat ); CV_EXPORTS_W void imshow( const string& winname, const InputArray& mat );
typedef void (CV_CDECL *TrackbarCallback)(int pos, void* userdata); typedef void (CV_CDECL *TrackbarCallback)(int pos, void* userdata);
@ -102,11 +106,11 @@ typedef void (*MouseCallback )(int event, int x, int y, int flags, void* param);
CV_EXPORTS void setMouseCallback( const string& windowName, MouseCallback onMouse, void* param=0); CV_EXPORTS void setMouseCallback( const string& windowName, MouseCallback onMouse, void* param=0);
CV_EXPORTS_W Mat imread( const string& filename, int flags=1 ); CV_EXPORTS_W Mat imread( const string& filename, int flags=1 );
CV_EXPORTS_W bool imwrite( const string& filename, const Mat& img, CV_EXPORTS_W bool imwrite( const string& filename, const InputArray& img,
const vector<int>& params=vector<int>()); const vector<int>& params=vector<int>());
CV_EXPORTS_W Mat imdecode( const Mat& buf, int flags ); CV_EXPORTS_W Mat imdecode( const InputArray& buf, int flags );
CV_EXPORTS_W bool imencode( const string& ext, const Mat& img, CV_EXPORTS_W bool imencode( const string& ext, const InputArray& img,
CV_OUT vector<uchar>& buf, vector<uchar>& buf,
const vector<int>& params=vector<int>()); const vector<int>& params=vector<int>());
CV_EXPORTS_W int waitKey(int delay=0); CV_EXPORTS_W int waitKey(int delay=0);

11
modules/highgui/src/loadsave.cpp
Unescape View File

@ -295,9 +295,10 @@ static bool imwrite_( const string& filename, const Mat& image,
return code; return code;
} }
bool imwrite( const string& filename, const Mat& img, bool imwrite( const string& filename, const InputArray& _img,
const vector<int>& params ) const vector<int>& params )
{ {
Mat img = _img.getMat();
return imwrite_(filename, img, params, false); return imwrite_(filename, img, params, false);
} }
@ -388,17 +389,17 @@ imdecode_( const Mat& buf, int flags, int hdrtype, Mat* mat=0 )
} }
Mat imdecode( const Mat& buf, int flags ) Mat imdecode( const InputArray& _buf, int flags )
{ {
Mat img; Mat buf = _buf.getMat(), img;
imdecode_( buf, flags, LOAD_MAT, &img ); imdecode_( buf, flags, LOAD_MAT, &img );
return img; return img;
} }
bool imencode( const string& ext, const Mat& image, bool imencode( const string& ext, const InputArray& _image,
vector<uchar>& buf, const vector<int>& params ) vector<uchar>& buf, const vector<int>& params )
{ {
Mat temp; Mat temp, image = _image.getMat();
const Mat* pimage = &image; const Mat* pimage = &image;
int channels = image.channels(); int channels = image.channels();

51
modules/highgui/src/window.cpp
Unescape View File

@ -126,41 +126,38 @@ CV_IMPL double cvGetWindowProperty(const char* name, int prop_id)
} }
} }
namespace cv void cv::namedWindow( const string& winname, int flags )
{
void namedWindow( const string& winname, int flags )
{ {
cvNamedWindow( winname.c_str(), flags ); cvNamedWindow( winname.c_str(), flags );
} }
void destroyWindow( const string& winname ) void cv::destroyWindow( const string& winname )
{ {
cvDestroyWindow( winname.c_str() ); cvDestroyWindow( winname.c_str() );
} }
void setWindowProperty(const string& winname, int prop_id, double prop_value) void cv::setWindowProperty(const string& winname, int prop_id, double prop_value)
{ {
cvSetWindowProperty( winname.c_str(),prop_id,prop_value); cvSetWindowProperty( winname.c_str(),prop_id,prop_value);
} }
double getWindowProperty(const string& winname, int prop_id) double cv::getWindowProperty(const string& winname, int prop_id)
{ {
return cvGetWindowProperty(winname.c_str(),prop_id); return cvGetWindowProperty(winname.c_str(),prop_id);
} }
void imshow( const string& winname, const Mat& img ) void cv::imshow( const string& winname, const InputArray& img )
{ {
CvMat _img = img; CvMat c_img = img.getMat();
cvShowImage( winname.c_str(), &_img ); cvShowImage( winname.c_str(), &c_img );
} }
int waitKey(int delay) int cv::waitKey(int delay)
{ {
return cvWaitKey(delay); return cvWaitKey(delay);
} }
int createTrackbar(const string& trackbarName, const string& winName, int cv::createTrackbar(const string& trackbarName, const string& winName,
int* value, int count, TrackbarCallback callback, int* value, int count, TrackbarCallback callback,
void* userdata) void* userdata)
{ {
@ -168,83 +165,81 @@ int createTrackbar(const string& trackbarName, const string& winName,
value, count, callback, userdata); value, count, callback, userdata);
} }
void setTrackbarPos( const string& trackbarName, const string& winName, int value ) void cv::setTrackbarPos( const string& trackbarName, const string& winName, int value )
{ {
cvSetTrackbarPos(trackbarName.c_str(), winName.c_str(), value ); cvSetTrackbarPos(trackbarName.c_str(), winName.c_str(), value );
} }
int getTrackbarPos( const string& trackbarName, const string& winName ) int cv::getTrackbarPos( const string& trackbarName, const string& winName )
{ {
return cvGetTrackbarPos(trackbarName.c_str(), winName.c_str()); return cvGetTrackbarPos(trackbarName.c_str(), winName.c_str());
} }
void setMouseCallback( const string& windowName, MouseCallback onMouse, void* param) void cv::setMouseCallback( const string& windowName, MouseCallback onMouse, void* param)
{ {
cvSetMouseCallback(windowName.c_str(), onMouse, param); cvSetMouseCallback(windowName.c_str(), onMouse, param);
} }
int startWindowThread() int cv::startWindowThread()
{ {
return cvStartWindowThread(); return cvStartWindowThread();
} }
#if defined (HAVE_QT) #if defined (HAVE_QT)
CvFont fontQt(const string& nameFont, int pointSize, Scalar color, int weight, int style, int spacing) CvFont cv::fontQt(const string& nameFont, int pointSize, Scalar color, int weight, int style, int spacing)
{ {
return cvFontQt(nameFont.c_str(), pointSize,color,weight, style); return cvFontQt(nameFont.c_str(), pointSize,color,weight, style);
} }
void addText( const Mat& img, const string& text, Point org, CvFont font) void cv::addText( const Mat& img, const string& text, Point org, CvFont font)
{ {
CvMat _img = img; CvMat _img = img;
cvAddText( &_img, text.c_str(), org,&font); cvAddText( &_img, text.c_str(), org,&font);
} }
void displayStatusBar(const string& name, const string& text, int delayms) void cv::displayStatusBar(const string& name, const string& text, int delayms)
{ {
cvDisplayStatusBar(name.c_str(),text.c_str(), delayms); cvDisplayStatusBar(name.c_str(),text.c_str(), delayms);
} }
void createOpenGLCallback(const string& name, OpenGLCallback callback, void* param) void cv::createOpenGLCallback(const string& name, OpenGLCallback callback, void* param)
{ {
cvCreateOpenGLCallback(name.c_str(),callback, param); cvCreateOpenGLCallback(name.c_str(),callback, param);
} }
void displayOverlay(const string& name, const string& text, int delayms) void cv::displayOverlay(const string& name, const string& text, int delayms)
{ {
cvDisplayOverlay(name.c_str(),text.c_str(), delayms); cvDisplayOverlay(name.c_str(),text.c_str(), delayms);
} }
int startLoop(int (*pt2Func)(int argc, char *argv[]), int argc, char* argv[]) int cv::startLoop(int (*pt2Func)(int argc, char *argv[]), int argc, char* argv[])
{ {
return cvStartLoop(pt2Func, argc, argv); return cvStartLoop(pt2Func, argc, argv);
} }
void stopLoop() void cv::stopLoop()
{ {
cvStopLoop(); cvStopLoop();
} }
void saveWindowParameters(const string& windowName) void cv::saveWindowParameters(const string& windowName)
{ {
cvSaveWindowParameters(windowName.c_str()); cvSaveWindowParameters(windowName.c_str());
} }
void loadWindowParameters(const string& windowName) void cv::loadWindowParameters(const string& windowName)
{ {
cvLoadWindowParameters(windowName.c_str()); cvLoadWindowParameters(windowName.c_str());
} }
int createButton(const string& button_name, ButtonCallback on_change, void* userdata, int button_type , bool initial_button_state ) int cv::createButton(const string& button_name, ButtonCallback on_change, void* userdata, int button_type , bool initial_button_state )
{ {
return cvCreateButton(button_name.c_str(), on_change, userdata, button_type , initial_button_state ); return cvCreateButton(button_name.c_str(), on_change, userdata, button_type , initial_button_state );
} }
#endif #endif
}
#if defined WIN32 || defined _WIN32 // see window_w32.cpp #if defined WIN32 || defined _WIN32 // see window_w32.cpp
#elif defined (HAVE_GTK) // see window_gtk.cpp #elif defined (HAVE_GTK) // see window_gtk.cpp
#elif defined (HAVE_COCOA) // see window_carbon.cpp #elif defined (HAVE_COCOA) // see window_carbon.cpp

288
modules/imgproc/include/opencv2/imgproc/imgproc.hpp
Unescape View File

@ -287,28 +287,28 @@ enum { KERNEL_GENERAL=0, KERNEL_SYMMETRICAL=1, KERNEL_ASYMMETRICAL=2,
KERNEL_SMOOTH=4, KERNEL_INTEGER=8 }; KERNEL_SMOOTH=4, KERNEL_INTEGER=8 };
//! returns type (one of KERNEL_*) of 1D or 2D kernel specified by its coefficients. //! returns type (one of KERNEL_*) of 1D or 2D kernel specified by its coefficients.
CV_EXPORTS int getKernelType(const Mat& kernel, Point anchor); CV_EXPORTS int getKernelType(const InputArray& kernel, Point anchor);
//! returns the primitive row filter with the specified kernel //! returns the primitive row filter with the specified kernel
CV_EXPORTS Ptr<BaseRowFilter> getLinearRowFilter(int srcType, int bufType, CV_EXPORTS Ptr<BaseRowFilter> getLinearRowFilter(int srcType, int bufType,
const Mat& kernel, int anchor, const InputArray& kernel, int anchor,
int symmetryType); int symmetryType);
//! returns the primitive column filter with the specified kernel //! returns the primitive column filter with the specified kernel
CV_EXPORTS Ptr<BaseColumnFilter> getLinearColumnFilter(int bufType, int dstType, CV_EXPORTS Ptr<BaseColumnFilter> getLinearColumnFilter(int bufType, int dstType,
const Mat& kernel, int anchor, const InputArray& kernel, int anchor,
int symmetryType, double delta=0, int symmetryType, double delta=0,
int bits=0); int bits=0);
//! returns 2D filter with the specified kernel //! returns 2D filter with the specified kernel
CV_EXPORTS Ptr<BaseFilter> getLinearFilter(int srcType, int dstType, CV_EXPORTS Ptr<BaseFilter> getLinearFilter(int srcType, int dstType,
const Mat& kernel, const InputArray& kernel,
Point anchor=Point(-1,-1), Point anchor=Point(-1,-1),
double delta=0, int bits=0); double delta=0, int bits=0);
//! returns the separable linear filter engine //! returns the separable linear filter engine
CV_EXPORTS Ptr<FilterEngine> createSeparableLinearFilter(int srcType, int dstType, CV_EXPORTS Ptr<FilterEngine> createSeparableLinearFilter(int srcType, int dstType,
const Mat& rowKernel, const Mat& columnKernel, const InputArray& rowKernel, const InputArray& columnKernel,
Point _anchor=Point(-1,-1), double delta=0, Point _anchor=Point(-1,-1), double delta=0,
int _rowBorderType=BORDER_DEFAULT, int _rowBorderType=BORDER_DEFAULT,
int _columnBorderType=-1, int _columnBorderType=-1,
@ -316,7 +316,7 @@ CV_EXPORTS Ptr<FilterEngine> createSeparableLinearFilter(int srcType, int dstTyp
//! returns the non-separable linear filter engine //! returns the non-separable linear filter engine
CV_EXPORTS Ptr<FilterEngine> createLinearFilter(int srcType, int dstType, CV_EXPORTS Ptr<FilterEngine> createLinearFilter(int srcType, int dstType,
const Mat& kernel, Point _anchor=Point(-1,-1), const InputArray& kernel, Point _anchor=Point(-1,-1),
double delta=0, int _rowBorderType=BORDER_DEFAULT, double delta=0, int _rowBorderType=BORDER_DEFAULT,
int _columnBorderType=-1, const Scalar& _borderValue=Scalar()); int _columnBorderType=-1, const Scalar& _borderValue=Scalar());
@ -328,7 +328,7 @@ CV_EXPORTS Ptr<FilterEngine> createGaussianFilter( int type, Size ksize,
double sigma1, double sigma2=0, double sigma1, double sigma2=0,
int borderType=BORDER_DEFAULT); int borderType=BORDER_DEFAULT);
//! initializes kernels of the generalized Sobel operator //! initializes kernels of the generalized Sobel operator
CV_EXPORTS_W void getDerivKernels( CV_OUT Mat& kx, CV_OUT Mat& ky, CV_EXPORTS_W void getDerivKernels( OutputArray kx, OutputArray ky,
int dx, int dy, int ksize, int dx, int dy, int ksize,
bool normalize=false, int ktype=CV_32F ); bool normalize=false, int ktype=CV_32F );
//! returns filter engine for the generalized Sobel operator //! returns filter engine for the generalized Sobel operator
@ -358,14 +358,14 @@ CV_EXPORTS Ptr<BaseRowFilter> getMorphologyRowFilter(int op, int type, int ksize
//! returns vertical 1D morphological filter //! returns vertical 1D morphological filter
CV_EXPORTS Ptr<BaseColumnFilter> getMorphologyColumnFilter(int op, int type, int ksize, int anchor=-1); CV_EXPORTS Ptr<BaseColumnFilter> getMorphologyColumnFilter(int op, int type, int ksize, int anchor=-1);
//! returns 2D morphological filter //! returns 2D morphological filter
CV_EXPORTS Ptr<BaseFilter> getMorphologyFilter(int op, int type, const Mat& kernel, CV_EXPORTS Ptr<BaseFilter> getMorphologyFilter(int op, int type, const InputArray& kernel,
Point anchor=Point(-1,-1)); Point anchor=Point(-1,-1));
//! returns "magic" border value for erosion and dilation. It is automatically transformed to Scalar::all(-DBL_MAX) for dilation. //! returns "magic" border value for erosion and dilation. It is automatically transformed to Scalar::all(-DBL_MAX) for dilation.
static inline Scalar morphologyDefaultBorderValue() { return Scalar::all(DBL_MAX); } static inline Scalar morphologyDefaultBorderValue() { return Scalar::all(DBL_MAX); }
//! returns morphological filter engine. Only MORPH_ERODE and MORPH_DILATE are supported. //! returns morphological filter engine. Only MORPH_ERODE and MORPH_DILATE are supported.
CV_EXPORTS Ptr<FilterEngine> createMorphologyFilter(int op, int type, const Mat& kernel, CV_EXPORTS Ptr<FilterEngine> createMorphologyFilter(int op, int type, const InputArray& kernel,
Point anchor=Point(-1,-1), int _rowBorderType=BORDER_CONSTANT, Point anchor=Point(-1,-1), int _rowBorderType=BORDER_CONSTANT,
int _columnBorderType=-1, int _columnBorderType=-1,
const Scalar& _borderValue=morphologyDefaultBorderValue()); const Scalar& _borderValue=morphologyDefaultBorderValue());
@ -378,123 +378,124 @@ CV_EXPORTS_W Mat getStructuringElement(int shape, Size ksize, Point anchor=Point
template<> CV_EXPORTS void Ptr<IplConvKernel>::delete_obj(); template<> CV_EXPORTS void Ptr<IplConvKernel>::delete_obj();
//! copies 2D array to a larger destination array with extrapolation of the outer part of src using the specified border mode //! copies 2D array to a larger destination array with extrapolation of the outer part of src using the specified border mode
CV_EXPORTS_W void copyMakeBorder( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS_W void copyMakeBorder( const InputArray& src, OutputArray dst,
int top, int bottom, int left, int right, int top, int bottom, int left, int right,
int borderType, const Scalar& value=Scalar() ); int borderType, const Scalar& value=Scalar() );
//! smooths the image using median filter. //! smooths the image using median filter.
CV_EXPORTS_W void medianBlur( const Mat& src, CV_OUT Mat& dst, int ksize ); CV_EXPORTS_W void medianBlur( const InputArray& src, OutputArray dst, int ksize );
//! smooths the image using Gaussian filter. //! smooths the image using Gaussian filter.
CV_EXPORTS_AS(gaussianBlur) void GaussianBlur( const Mat& src, CV_OUT Mat& dst, Size ksize, CV_EXPORTS_AS(gaussianBlur) void GaussianBlur( const InputArray& src,
OutputArray dst, Size ksize,
double sigma1, double sigma2=0, double sigma1, double sigma2=0,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! smooths the image using bilateral filter //! smooths the image using bilateral filter
CV_EXPORTS_W void bilateralFilter( const Mat& src, CV_OUT Mat& dst, int d, CV_EXPORTS_W void bilateralFilter( const InputArray& src, OutputArray dst, int d,
double sigmaColor, double sigmaSpace, double sigmaColor, double sigmaSpace,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! smooths the image using the box filter. Each pixel is processed in O(1) time //! smooths the image using the box filter. Each pixel is processed in O(1) time
CV_EXPORTS_W void boxFilter( const Mat& src, CV_OUT Mat& dst, int ddepth, CV_EXPORTS_W void boxFilter( const InputArray& src, OutputArray dst, int ddepth,
Size ksize, Point anchor=Point(-1,-1), Size ksize, Point anchor=Point(-1,-1),
bool normalize=true, bool normalize=true,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! a synonym for normalized box filter //! a synonym for normalized box filter
CV_EXPORTS_W void blur( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS_W void blur( const InputArray& src, OutputArray dst,
Size ksize, Point anchor=Point(-1,-1), Size ksize, Point anchor=Point(-1,-1),
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! applies non-separable 2D linear filter to the image //! applies non-separable 2D linear filter to the image
CV_EXPORTS_W void filter2D( const Mat& src, CV_OUT Mat& dst, int ddepth, CV_EXPORTS_W void filter2D( const InputArray& src, OutputArray dst, int ddepth,
const Mat& kernel, Point anchor=Point(-1,-1), const InputArray& kernel, Point anchor=Point(-1,-1),
double delta=0, int borderType=BORDER_DEFAULT ); double delta=0, int borderType=BORDER_DEFAULT );
//! applies separable 2D linear filter to the image //! applies separable 2D linear filter to the image
CV_EXPORTS_W void sepFilter2D( const Mat& src, CV_OUT Mat& dst, int ddepth, CV_EXPORTS_W void sepFilter2D( const InputArray& src, OutputArray dst, int ddepth,
const Mat& kernelX, const Mat& kernelY, const InputArray& kernelX, const InputArray& kernelY,
Point anchor=Point(-1,-1), Point anchor=Point(-1,-1),
double delta=0, int borderType=BORDER_DEFAULT ); double delta=0, int borderType=BORDER_DEFAULT );
//! applies generalized Sobel operator to the image //! applies generalized Sobel operator to the image
CV_EXPORTS_AS(sobel) void Sobel( const Mat& src, CV_OUT Mat& dst, int ddepth, CV_EXPORTS_AS(sobel) void Sobel( const InputArray& src, OutputArray dst, int ddepth,
int dx, int dy, int ksize=3, int dx, int dy, int ksize=3,
double scale=1, double delta=0, double scale=1, double delta=0,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! applies the vertical or horizontal Scharr operator to the image //! applies the vertical or horizontal Scharr operator to the image
CV_EXPORTS_AS(scharr) void Scharr( const Mat& src, CV_OUT Mat& dst, int ddepth, CV_EXPORTS_AS(scharr) void Scharr( const InputArray& src, OutputArray dst, int ddepth,
int dx, int dy, double scale=1, double delta=0, int dx, int dy, double scale=1, double delta=0,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! applies Laplacian operator to the image //! applies Laplacian operator to the image
CV_EXPORTS_AS(laplacian) void Laplacian( const Mat& src, CV_OUT Mat& dst, int ddepth, CV_EXPORTS_AS(laplacian) void Laplacian( const InputArray& src, OutputArray dst, int ddepth,
int ksize=1, double scale=1, double delta=0, int ksize=1, double scale=1, double delta=0,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! applies Canny edge detector and produces the edge map. //! applies Canny edge detector and produces the edge map.
CV_EXPORTS_AS(canny) void Canny( const Mat& image, CV_OUT Mat& edges, CV_EXPORTS_AS(canny) void Canny( const InputArray& image, OutputArray edges,
double threshold1, double threshold2, double threshold1, double threshold2,
int apertureSize=3, bool L2gradient=false ); int apertureSize=3, bool L2gradient=false );
//! computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria //! computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria
CV_EXPORTS_W void cornerMinEigenVal( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS_W void cornerMinEigenVal( const InputArray& src, OutputArray dst,
int blockSize, int ksize=3, int blockSize, int ksize=3,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! computes Harris cornerness criteria at each image pixel //! computes Harris cornerness criteria at each image pixel
CV_EXPORTS_W void cornerHarris( const Mat& src, CV_OUT Mat& dst, int blockSize, CV_EXPORTS_W void cornerHarris( const InputArray& src, OutputArray dst, int blockSize,
int ksize, double k, int ksize, double k,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! computes both eigenvalues and the eigenvectors of 2x2 derivative covariation matrix at each pixel. The output is stored as 6-channel matrix. //! computes both eigenvalues and the eigenvectors of 2x2 derivative covariation matrix at each pixel. The output is stored as 6-channel matrix.
CV_EXPORTS_W void cornerEigenValsAndVecs( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS_W void cornerEigenValsAndVecs( const InputArray& src, OutputArray dst,
int blockSize, int ksize, int blockSize, int ksize,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! computes another complex cornerness criteria at each pixel //! computes another complex cornerness criteria at each pixel
CV_EXPORTS_W void preCornerDetect( const Mat& src, CV_OUT Mat& dst, int ksize, CV_EXPORTS_W void preCornerDetect( const InputArray& src, OutputArray dst, int ksize,
int borderType=BORDER_DEFAULT ); int borderType=BORDER_DEFAULT );
//! adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria //! adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria
CV_EXPORTS void cornerSubPix( const Mat& image, vector<Point2f>& corners, CV_EXPORTS void cornerSubPix( const InputArray& image, InputOutputArray corners,
Size winSize, Size zeroZone, Size winSize, Size zeroZone,
TermCriteria criteria ); TermCriteria criteria );
//! finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima //! finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima
CV_EXPORTS_W void goodFeaturesToTrack( const Mat& image, CV_OUT vector<Point2f>& corners, CV_EXPORTS_W void goodFeaturesToTrack( const InputArray& image, OutputArray corners,
int maxCorners, double qualityLevel, double minDistance, int maxCorners, double qualityLevel, double minDistance,
const Mat& mask=Mat(), int blockSize=3, const InputArray& mask=InputArray(), int blockSize=3,
bool useHarrisDetector=false, double k=0.04 ); bool useHarrisDetector=false, double k=0.04 );
//! finds lines in the black-n-white image using the standard or pyramid Hough transform //! finds lines in the black-n-white image using the standard or pyramid Hough transform
CV_EXPORTS_AS(houghLines) void HoughLines( const Mat& image, CV_OUT vector<Vec2f>& lines, CV_EXPORTS_AS(houghLines) void HoughLines( const InputArray& image, OutputArray lines,
double rho, double theta, int threshold, double rho, double theta, int threshold,
double srn=0, double stn=0 ); double srn=0, double stn=0 );
//! finds line segments in the black-n-white image using probabalistic Hough transform //! finds line segments in the black-n-white image using probabalistic Hough transform
CV_EXPORTS_AS(houghLinesP) void HoughLinesP( Mat& image, CV_OUT vector<Vec4i>& lines, CV_EXPORTS_AS(houghLinesP) void HoughLinesP( const InputArray& image, OutputArray lines,
double rho, double theta, int threshold, double rho, double theta, int threshold,
double minLineLength=0, double maxLineGap=0 ); double minLineLength=0, double maxLineGap=0 );
//! finds circles in the grayscale image using 2+1 gradient Hough transform //! finds circles in the grayscale image using 2+1 gradient Hough transform
CV_EXPORTS_AS(houghCircles) void HoughCircles( const Mat& image, CV_OUT vector<Vec3f>& circles, CV_EXPORTS_AS(houghCircles) void HoughCircles( const InputArray& image, OutputArray circles,
int method, double dp, double minDist, int method, double dp, double minDist,
double param1=100, double param2=100, double param1=100, double param2=100,
int minRadius=0, int maxRadius=0 ); int minRadius=0, int maxRadius=0 );
//! erodes the image (applies the local minimum operator) //! erodes the image (applies the local minimum operator)
CV_EXPORTS_W void erode( const Mat& src, CV_OUT Mat& dst, const Mat& kernel, CV_EXPORTS_W void erode( const InputArray& src, OutputArray dst, const InputArray& kernel,
Point anchor=Point(-1,-1), int iterations=1, Point anchor=Point(-1,-1), int iterations=1,
int borderType=BORDER_CONSTANT, int borderType=BORDER_CONSTANT,
const Scalar& borderValue=morphologyDefaultBorderValue() ); const Scalar& borderValue=morphologyDefaultBorderValue() );
//! dilates the image (applies the local maximum operator) //! dilates the image (applies the local maximum operator)
CV_EXPORTS_W void dilate( const Mat& src, CV_OUT Mat& dst, const Mat& kernel, CV_EXPORTS_W void dilate( const InputArray& src, OutputArray dst, const InputArray& kernel,
Point anchor=Point(-1,-1), int iterations=1, Point anchor=Point(-1,-1), int iterations=1,
int borderType=BORDER_CONSTANT, int borderType=BORDER_CONSTANT,
const Scalar& borderValue=morphologyDefaultBorderValue() ); const Scalar& borderValue=morphologyDefaultBorderValue() );
//! applies an advanced morphological operation to the image //! applies an advanced morphological operation to the image
CV_EXPORTS_W void morphologyEx( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS_W void morphologyEx( const InputArray& src, OutputArray dst,
int op, const Mat& kernel, int op, const InputArray& kernel,
Point anchor=Point(-1,-1), int iterations=1, Point anchor=Point(-1,-1), int iterations=1,
int borderType=BORDER_CONSTANT, int borderType=BORDER_CONSTANT,
const Scalar& borderValue=morphologyDefaultBorderValue() ); const Scalar& borderValue=morphologyDefaultBorderValue() );
@ -512,36 +513,40 @@ enum
}; };
//! resizes the image //! resizes the image
CV_EXPORTS_W void resize( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS_W void resize( const InputArray& src, OutputArray dst,
Size dsize, double fx=0, double fy=0, Size dsize, double fx=0, double fy=0,
int interpolation=INTER_LINEAR ); int interpolation=INTER_LINEAR );
//! warps the image using affine transformation //! warps the image using affine transformation
CV_EXPORTS_W void warpAffine( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS_W void warpAffine( const InputArray& src, OutputArray dst,
const Mat& M, Size dsize, const InputArray& M, Size dsize,
int flags=INTER_LINEAR, int flags=INTER_LINEAR,
int borderMode=BORDER_CONSTANT, int borderMode=BORDER_CONSTANT,
const Scalar& borderValue=Scalar()); const Scalar& borderValue=Scalar());
//! warps the image using perspective transformation //! warps the image using perspective transformation
CV_EXPORTS_W void warpPerspective( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS_W void warpPerspective( const InputArray& src, OutputArray dst,
const Mat& M, Size dsize, const InputArray& M, Size dsize,
int flags=INTER_LINEAR, int flags=INTER_LINEAR,
int borderMode=BORDER_CONSTANT, int borderMode=BORDER_CONSTANT,
const Scalar& borderValue=Scalar()); const Scalar& borderValue=Scalar());
enum { INTER_BITS=5, INTER_BITS2=INTER_BITS*2, enum
{
INTER_BITS=5, INTER_BITS2=INTER_BITS*2,
INTER_TAB_SIZE=(1<<INTER_BITS), INTER_TAB_SIZE=(1<<INTER_BITS),
INTER_TAB_SIZE2=INTER_TAB_SIZE*INTER_TAB_SIZE }; INTER_TAB_SIZE2=INTER_TAB_SIZE*INTER_TAB_SIZE
};
//! warps the image using the precomputed maps. The maps are stored in either floating-point or integer fixed-point format //! warps the image using the precomputed maps. The maps are stored in either floating-point or integer fixed-point format
CV_EXPORTS_W void remap( const Mat& src, CV_OUT Mat& dst, const Mat& map1, const Mat& map2, CV_EXPORTS_W void remap( const InputArray& src, OutputArray dst,
const InputArray& map1, const InputArray& map2,
int interpolation, int borderMode=BORDER_CONSTANT, int interpolation, int borderMode=BORDER_CONSTANT,
const Scalar& borderValue=Scalar()); const Scalar& borderValue=Scalar());
//! converts maps for remap from floating-point to fixed-point format or backwards //! converts maps for remap from floating-point to fixed-point format or backwards
CV_EXPORTS_W void convertMaps( const Mat& map1, const Mat& map2, CV_EXPORTS_W void convertMaps( const InputArray& map1, const InputArray& map2,
CV_OUT Mat& dstmap1, CV_OUT Mat& dstmap2, OutputArray dstmap1, OutputArray dstmap2,
int dstmap1type, bool nninterpolation=false ); int dstmap1type, bool nninterpolation=false );
//! returns 2x3 affine transformation matrix for the planar rotation. //! returns 2x3 affine transformation matrix for the planar rotation.
@ -551,29 +556,34 @@ CV_EXPORTS Mat getPerspectiveTransform( const Point2f src[], const Point2f dst[]
//! returns 2x3 affine transformation for the corresponding 3 point pairs. //! returns 2x3 affine transformation for the corresponding 3 point pairs.
CV_EXPORTS Mat getAffineTransform( const Point2f src[], const Point2f dst[] ); CV_EXPORTS Mat getAffineTransform( const Point2f src[], const Point2f dst[] );
//! computes 2x3 affine transformation matrix that is inverse to the specified 2x3 affine transformation. //! computes 2x3 affine transformation matrix that is inverse to the specified 2x3 affine transformation.
CV_EXPORTS_W void invertAffineTransform( const Mat& M, CV_OUT Mat& iM ); CV_EXPORTS_W void invertAffineTransform( const InputArray& M, OutputArray iM );
//! extracts rectangle from the image at sub-pixel location //! extracts rectangle from the image at sub-pixel location
CV_EXPORTS_W void getRectSubPix( const Mat& image, Size patchSize, CV_EXPORTS_W void getRectSubPix( const InputArray& image, Size patchSize,
Point2f center, CV_OUT Mat& patch, int patchType=-1 ); Point2f center, OutputArray patch, int patchType=-1 );
//! computes the integral image //! computes the integral image
CV_EXPORTS_W void integral( const Mat& src, CV_OUT Mat& sum, int sdepth=-1 ); CV_EXPORTS_W void integral( const InputArray& src, OutputArray sum, int sdepth=-1 );
//! computes the integral image and integral for the squared image //! computes the integral image and integral for the squared image
CV_EXPORTS_AS(integral2) void integral( const Mat& src, CV_OUT Mat& sum, CV_OUT Mat& sqsum, int sdepth=-1 ); CV_EXPORTS_AS(integral2) void integral( const InputArray& src, OutputArray sum,
OutputArray sqsum, int sdepth=-1 );
//! computes the integral image, integral for the squared image and the tilted integral image //! computes the integral image, integral for the squared image and the tilted integral image
CV_EXPORTS_AS(integral3) void integral( const Mat& src, CV_OUT Mat& sum, CV_OUT Mat& sqsum, CV_OUT Mat& tilted, int sdepth=-1 ); CV_EXPORTS_AS(integral3) void integral( const InputArray& src, OutputArray sum,
OutputArray sqsum, OutputArray tilted,
int sdepth=-1 );
//! adds image to the accumulator (dst += src). Unlike cv::add, dst and src can have different types. //! adds image to the accumulator (dst += src). Unlike cv::add, dst and src can have different types.
CV_EXPORTS_W void accumulate( const Mat& src, CV_IN_OUT Mat& dst, const Mat& mask=Mat() ); CV_EXPORTS_W void accumulate( const InputArray& src, CV_IN_OUT InputOutputArray dst,
const InputArray& mask=InputArray() );
//! adds squared src image to the accumulator (dst += src*src). //! adds squared src image to the accumulator (dst += src*src).
CV_EXPORTS_W void accumulateSquare( const Mat& src, CV_IN_OUT Mat& dst, const Mat& mask=Mat() ); CV_EXPORTS_W void accumulateSquare( const InputArray& src, CV_IN_OUT InputOutputArray dst,
const InputArray& mask=InputArray() );
//! adds product of the 2 images to the accumulator (dst += src1*src2). //! adds product of the 2 images to the accumulator (dst += src1*src2).
CV_EXPORTS_W void accumulateProduct( const Mat& src1, const Mat& src2, CV_EXPORTS_W void accumulateProduct( const InputArray& src1, const InputArray& src2,
CV_IN_OUT Mat& dst, const Mat& mask=Mat() ); CV_IN_OUT InputOutputArray dst, const InputArray& mask=InputArray() );
//! updates the running average (dst = dst*(1-alpha) + src*alpha) //! updates the running average (dst = dst*(1-alpha) + src*alpha)
CV_EXPORTS_W void accumulateWeighted( const Mat& src, CV_IN_OUT Mat& dst, CV_EXPORTS_W void accumulateWeighted( const InputArray& src, CV_IN_OUT InputOutputArray dst,
double alpha, const Mat& mask=Mat() ); double alpha, const InputArray& mask=InputArray() );
//! type of the threshold operation //! type of the threshold operation
enum { THRESH_BINARY=CV_THRESH_BINARY, THRESH_BINARY_INV=CV_THRESH_BINARY_INV, enum { THRESH_BINARY=CV_THRESH_BINARY, THRESH_BINARY_INV=CV_THRESH_BINARY_INV,
@ -582,30 +592,37 @@ enum { THRESH_BINARY=CV_THRESH_BINARY, THRESH_BINARY_INV=CV_THRESH_BINARY_INV,
THRESH_OTSU=CV_THRESH_OTSU }; THRESH_OTSU=CV_THRESH_OTSU };
//! applies fixed threshold to the image //! applies fixed threshold to the image
CV_EXPORTS_W double threshold( const Mat& src, CV_OUT Mat& dst, double thresh, double maxval, int type ); CV_EXPORTS_W double threshold( const InputArray& src, OutputArray dst,
double thresh, double maxval, int type );
//! adaptive threshold algorithm //! adaptive threshold algorithm
enum { ADAPTIVE_THRESH_MEAN_C=0, ADAPTIVE_THRESH_GAUSSIAN_C=1 }; enum { ADAPTIVE_THRESH_MEAN_C=0, ADAPTIVE_THRESH_GAUSSIAN_C=1 };
//! applies variable (adaptive) threshold to the image //! applies variable (adaptive) threshold to the image
CV_EXPORTS_W void adaptiveThreshold( const Mat& src, CV_OUT Mat& dst, double maxValue, CV_EXPORTS_W void adaptiveThreshold( const InputArray& src, OutputArray dst,
int adaptiveMethod, int thresholdType, double maxValue, int adaptiveMethod,
int blockSize, double C ); int thresholdType, int blockSize, double C );
//! smooths and downsamples the image //! smooths and downsamples the image
CV_EXPORTS_W void pyrDown( const Mat& src, CV_OUT Mat& dst, const Size& dstsize=Size()); CV_EXPORTS_W void pyrDown( const InputArray& src, OutputArray dst,
const Size& dstsize=Size());
//! upsamples and smoothes the image //! upsamples and smoothes the image
CV_EXPORTS_W void pyrUp( const Mat& src, CV_OUT Mat& dst, const Size& dstsize=Size()); CV_EXPORTS_W void pyrUp( const InputArray& src, OutputArray dst,
const Size& dstsize=Size());
//! builds the gaussian pyramid using pyrDown() as a basic operation //! builds the gaussian pyramid using pyrDown() as a basic operation
CV_EXPORTS void buildPyramid( const Mat& src, CV_OUT vector<Mat>& dst, int maxlevel ); CV_EXPORTS void buildPyramid( const InputArray& src, OutputArrayOfArrays dst, int maxlevel );
//! corrects lens distortion for the given camera matrix and distortion coefficients //! corrects lens distortion for the given camera matrix and distortion coefficients
CV_EXPORTS_W void undistort( const Mat& src, CV_OUT Mat& dst, const Mat& cameraMatrix, CV_EXPORTS_W void undistort( const InputArray& src, OutputArray dst,
const Mat& distCoeffs, const Mat& newCameraMatrix=Mat() ); const InputArray& cameraMatrix,
const InputArray& distCoeffs,
const InputArray& newCameraMatrix=InputArray() );
//! initializes maps for cv::remap() to correct lens distortion and optionally rectify the image //! initializes maps for cv::remap() to correct lens distortion and optionally rectify the image
CV_EXPORTS_W void initUndistortRectifyMap( const Mat& cameraMatrix, const Mat& distCoeffs, CV_EXPORTS_W void initUndistortRectifyMap( const InputArray& cameraMatrix, const InputArray& distCoeffs,
const Mat& R, const Mat& newCameraMatrix, const InputArray& R, const InputArray& newCameraMatrix,
Size size, int m1type, CV_OUT Mat& map1, CV_OUT Mat& map2 ); Size size, int m1type, OutputArray map1, OutputArray map2 );
enum enum
{ {
@ -614,42 +631,39 @@ enum
}; };
//! initializes maps for cv::remap() for wide-angle //! initializes maps for cv::remap() for wide-angle
CV_EXPORTS_W float initWideAngleProjMap( const Mat& cameraMatrix, const Mat& distCoeffs, CV_EXPORTS_W float initWideAngleProjMap( const InputArray& cameraMatrix, const InputArray& distCoeffs,
Size imageSize, int destImageWidth, Size imageSize, int destImageWidth,
int m1type, CV_OUT Mat& map1, CV_OUT Mat& map2, int m1type, OutputArray map1, OutputArray map2,
int projType=PROJ_SPHERICAL_EQRECT, double alpha=0); int projType=PROJ_SPHERICAL_EQRECT, double alpha=0);
//! returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true) //! returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true)
CV_EXPORTS_W Mat getDefaultNewCameraMatrix( const Mat& cameraMatrix, Size imgsize=Size(), CV_EXPORTS_W Mat getDefaultNewCameraMatrix( const InputArray& cameraMatrix, Size imgsize=Size(),
bool centerPrincipalPoint=false ); bool centerPrincipalPoint=false );
//! returns points' coordinates after lens distortion correction //! returns points' coordinates after lens distortion correction
CV_EXPORTS void undistortPoints( const Mat& src, CV_OUT vector<Point2f>& dst, CV_EXPORTS void undistortPoints( const InputArray& src, OutputArray dst,
const Mat& cameraMatrix, const Mat& distCoeffs, const InputArray& cameraMatrix, const InputArray& distCoeffs,
const Mat& R=Mat(), const Mat& P=Mat()); const InputArray& R=InputArray(), const InputArray& P=InputArray());
//! returns points' coordinates after lens distortion correction
CV_EXPORTS_W void undistortPoints( const Mat& src, CV_OUT Mat& dst,
const Mat& cameraMatrix, const Mat& distCoeffs,
const Mat& R=Mat(), const Mat& P=Mat());
template<> CV_EXPORTS void Ptr<CvHistogram>::delete_obj(); template<> CV_EXPORTS void Ptr<CvHistogram>::delete_obj();
//! computes the joint dense histogram for a set of images. //! computes the joint dense histogram for a set of images.
CV_EXPORTS void calcHist( const Mat* images, int nimages, CV_EXPORTS void calcHist( const Mat* images, int nimages,
const int* channels, const Mat& mask, const int* channels, const InputArray& mask,
Mat& hist, int dims, const int* histSize, OutputArray hist, int dims, const int* histSize,
const float** ranges, bool uniform=true, bool accumulate=false ); const float** ranges, bool uniform=true, bool accumulate=false );
//! computes the joint sparse histogram for a set of images. //! computes the joint sparse histogram for a set of images.
CV_EXPORTS void calcHist( const Mat* images, int nimages, CV_EXPORTS void calcHist( const Mat* images, int nimages,
const int* channels, const Mat& mask, const int* channels, const InputArray& mask,
SparseMat& hist, int dims, SparseMat& hist, int dims,
const int* histSize, const float** ranges, const int* histSize, const float** ranges,
bool uniform=true, bool accumulate=false ); bool uniform=true, bool accumulate=false );
//! computes back projection for the set of images //! computes back projection for the set of images
CV_EXPORTS void calcBackProject( const Mat* images, int nimages, CV_EXPORTS void calcBackProject( const Mat* images, int nimages,
const int* channels, const Mat& hist, const int* channels, const InputArray& hist,
Mat& backProject, const float** ranges, OutputArray backProject, const float** ranges,
double scale=1, bool uniform=true ); double scale=1, bool uniform=true );
//! computes back projection for the set of images //! computes back projection for the set of images
@ -659,25 +673,26 @@ CV_EXPORTS void calcBackProject( const Mat* images, int nimages,
double scale=1, bool uniform=true ); double scale=1, bool uniform=true );
//! compares two histograms stored in dense arrays //! compares two histograms stored in dense arrays
CV_EXPORTS_W double compareHist( const Mat& H1, const Mat& H2, int method ); CV_EXPORTS_W double compareHist( const InputArray& H1, const InputArray& H2, int method );
//! compares two histograms stored in sparse arrays //! compares two histograms stored in sparse arrays
CV_EXPORTS double compareHist( const SparseMat& H1, const SparseMat& H2, int method ); CV_EXPORTS double compareHist( const SparseMat& H1, const SparseMat& H2, int method );
//! normalizes the grayscale image brightness and contrast by normalizing its histogram //! normalizes the grayscale image brightness and contrast by normalizing its histogram
CV_EXPORTS_W void equalizeHist( const Mat& src, CV_OUT Mat& dst ); CV_EXPORTS_W void equalizeHist( const InputArray& src, OutputArray dst );
CV_EXPORTS float EMD( const Mat& signature1, const Mat& signature2, CV_EXPORTS float EMD( const InputArray& signature1, const InputArray& signature2,
int distType, const Mat& cost=Mat(), int distType, const InputArray& cost=InputArray(),
float* lowerBound=0, Mat* flow=0 ); float* lowerBound=0, OutputArray flow=OutputArray() );
//! segments the image using watershed algorithm //! segments the image using watershed algorithm
CV_EXPORTS_W void watershed( const Mat& image, Mat& markers ); CV_EXPORTS_W void watershed( const InputArray& image, InputOutputArray markers );
//! filters image using meanshift algorithm //! filters image using meanshift algorithm
CV_EXPORTS_W void pyrMeanShiftFiltering( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS_W void pyrMeanShiftFiltering( const InputArray& src, OutputArray dst,
double sp, double sr, int maxLevel=1, double sp, double sr, int maxLevel=1,
TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS,5,1) ); TermCriteria termcrit=TermCriteria(
TermCriteria::MAX_ITER+TermCriteria::EPS,5,1) );
//! class of the pixel in GrabCut algorithm //! class of the pixel in GrabCut algorithm
enum enum
@ -697,8 +712,8 @@ enum
}; };
//! segments the image using GrabCut algorithm //! segments the image using GrabCut algorithm
CV_EXPORTS_W void grabCut( const Mat& img, Mat& mask, Rect rect, CV_EXPORTS_W void grabCut( const InputArray& img, InputOutputArray mask, Rect rect,
Mat& bgdModel, Mat& fgdModel, InputOutputArray bgdModel, InputOutputArray fgdModel,
int iterCount, int mode = GC_EVAL ); int iterCount, int mode = GC_EVAL );
//! the inpainting algorithm //! the inpainting algorithm
@ -709,35 +724,33 @@ enum
}; };
//! restores the damaged image areas using one of the available intpainting algorithms //! restores the damaged image areas using one of the available intpainting algorithms
CV_EXPORTS_W void inpaint( const Mat& src, const Mat& inpaintMask, CV_EXPORTS_W void inpaint( const InputArray& src, const InputArray& inpaintMask,
CV_OUT Mat& dst, double inpaintRange, int flags ); OutputArray dst, double inpaintRange, int flags );
//! builds the discrete Voronoi diagram //! builds the discrete Voronoi diagram
CV_EXPORTS_AS(distanceTransformWithLabels) CV_EXPORTS_W void distanceTransform( const InputArray& src, OutputArray dst,
void distanceTransform( const Mat& src, CV_OUT Mat& dst, Mat& labels, OutputArray labels, int distanceType, int maskSize );
int distanceType, int maskSize );
//! computes the distance transform map //! computes the distance transform map
CV_EXPORTS_W void distanceTransform( const Mat& src, CV_OUT Mat& dst, CV_EXPORTS void distanceTransform( const InputArray& src, OutputArray dst,
int distanceType, int maskSize ); int distanceType, int maskSize );
enum { FLOODFILL_FIXED_RANGE = 1 << 16, enum { FLOODFILL_FIXED_RANGE = 1 << 16, FLOODFILL_MASK_ONLY = 1 << 17 };
FLOODFILL_MASK_ONLY = 1 << 17 };
//! fills the semi-uniform image region starting from the specified seed point //! fills the semi-uniform image region starting from the specified seed point
CV_EXPORTS_W int floodFill( Mat& image, CV_EXPORTS int floodFill( InputOutputArray image,
Point seedPoint, Scalar newVal, CV_OUT Rect* rect=0, Point seedPoint, Scalar newVal, CV_OUT Rect* rect=0,
Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), Scalar loDiff=Scalar(), Scalar upDiff=Scalar(),
int flags=4 ); int flags=4 );
//! fills the semi-uniform image region and/or the mask starting from the specified seed point //! fills the semi-uniform image region and/or the mask starting from the specified seed point
CV_EXPORTS_AS(floodFillMask) int floodFill( Mat& image, Mat& mask, CV_EXPORTS_W int floodFill( InputOutputArray image, InputOutputArray mask,
Point seedPoint, Scalar newVal, CV_OUT Rect* rect=0, Point seedPoint, Scalar newVal, CV_OUT Rect* rect=0,
Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), Scalar loDiff=Scalar(), Scalar upDiff=Scalar(),
int flags=4 ); int flags=4 );
//! converts image from one color space to another //! converts image from one color space to another
CV_EXPORTS_W void cvtColor( const Mat& src, CV_OUT Mat& dst, int code, int dstCn=0 ); CV_EXPORTS_W void cvtColor( const InputArray& src, OutputArray dst, int code, int dstCn=0 );
//! raster image moments //! raster image moments
class CV_EXPORTS_W_MAP Moments class CV_EXPORTS_W_MAP Moments
@ -762,7 +775,7 @@ public:
}; };
//! computes moments of the rasterized shape or a vector of points //! computes moments of the rasterized shape or a vector of points
CV_EXPORTS_W Moments moments( const Mat& array, bool binaryImage=false ); CV_EXPORTS_W Moments moments( const InputArray& array, bool binaryImage=false );
//! computes 7 Hu invariants from the moments //! computes 7 Hu invariants from the moments
CV_EXPORTS void HuMoments( const Moments& moments, double hu[7] ); CV_EXPORTS void HuMoments( const Moments& moments, double hu[7] );
@ -771,7 +784,8 @@ CV_EXPORTS void HuMoments( const Moments& moments, double hu[7] );
enum { TM_SQDIFF=0, TM_SQDIFF_NORMED=1, TM_CCORR=2, TM_CCORR_NORMED=3, TM_CCOEFF=4, TM_CCOEFF_NORMED=5 }; enum { TM_SQDIFF=0, TM_SQDIFF_NORMED=1, TM_CCORR=2, TM_CCORR_NORMED=3, TM_CCOEFF=4, TM_CCOEFF_NORMED=5 };
//! computes the proximity map for the raster template and the image where the template is searched for //! computes the proximity map for the raster template and the image where the template is searched for
CV_EXPORTS_W void matchTemplate( const Mat& image, const Mat& templ, CV_OUT Mat& result, int method ); CV_EXPORTS_W void matchTemplate( const InputArray& image, const InputArray& templ,
OutputArray result, int method );
//! mode of the contour retrieval algorithm //! mode of the contour retrieval algorithm
enum enum
@ -792,74 +806,58 @@ enum
}; };
//! retrieves contours and the hierarchical information from black-n-white image. //! retrieves contours and the hierarchical information from black-n-white image.
CV_EXPORTS void findContours( Mat& image, CV_OUT vector<vector<Point> >& contours, CV_EXPORTS void findContours( InputOutputArray image, OutputArrayOfArrays contours,
vector<Vec4i>& hierarchy, int mode, OutputArray hierarchy, int mode,
int method, Point offset=Point()); int method, Point offset=Point());
//! retrieves contours from black-n-white image. //! retrieves contours from black-n-white image.
CV_EXPORTS void findContours( Mat& image, CV_OUT vector<vector<Point> >& contours, CV_EXPORTS void findContours( InputOutputArray image, OutputArrayOfArrays contours,
int mode, int method, Point offset=Point()); int mode, int method, Point offset=Point());
//! draws contours in the image //! draws contours in the image
CV_EXPORTS void drawContours( Mat& image, const vector<vector<Point> >& contours, CV_EXPORTS void drawContours( InputOutputArray image, const InputArrayOfArrays& contours,
int contourIdx, const Scalar& color, int contourIdx, const Scalar& color,
int thickness=1, int lineType=8, int thickness=1, int lineType=8,
const vector<Vec4i>& hierarchy=vector<Vec4i>(), const InputArray& hierarchy=InputArray(),
int maxLevel=INT_MAX, Point offset=Point() ); int maxLevel=INT_MAX, Point offset=Point() );
//! approximates contour or a curve using Douglas-Peucker algorithm //! approximates contour or a curve using Douglas-Peucker algorithm
CV_EXPORTS void approxPolyDP( const Mat& curve, CV_EXPORTS void approxPolyDP( const InputArray& curve,
CV_OUT vector<Point>& approxCurve, OutputArray approxCurve,
double epsilon, bool closed );
//! approximates contour or a curve using Douglas-Peucker algorithm
CV_EXPORTS void approxPolyDP( const Mat& curve,
CV_OUT vector<Point2f>& approxCurve,
double epsilon, bool closed ); double epsilon, bool closed );
//! computes the contour perimeter (closed=true) or a curve length //! computes the contour perimeter (closed=true) or a curve length
CV_EXPORTS_W double arcLength( const Mat& curve, bool closed ); CV_EXPORTS_W double arcLength( const InputArray& curve, bool closed );
//! computes the bounding rectangle for a contour //! computes the bounding rectangle for a contour
CV_EXPORTS_W Rect boundingRect( const Mat& points ); CV_EXPORTS_W Rect boundingRect( const InputArray& points );
//! computes the contour area //! computes the contour area
CV_EXPORTS_W double contourArea( const Mat& contour, bool oriented=false ); CV_EXPORTS_W double contourArea( const InputArray& contour, bool oriented=false );
//! computes the minimal rotated rectangle for a set of points //! computes the minimal rotated rectangle for a set of points
CV_EXPORTS_W RotatedRect minAreaRect( const Mat& points ); CV_EXPORTS_W RotatedRect minAreaRect( const InputArray& points );
//! computes the minimal enclosing circle for a set of points //! computes the minimal enclosing circle for a set of points
CV_EXPORTS_W void minEnclosingCircle( const Mat& points, CV_EXPORTS_W void minEnclosingCircle( const InputArray& points,
Point2f& center, float& radius ); Point2f& center, float& radius );
//! matches two contours using one of the available algorithms //! matches two contours using one of the available algorithms
CV_EXPORTS_W double matchShapes( const Mat& contour1, CV_EXPORTS_W double matchShapes( const InputArray& contour1, const InputArray& contour2,
const Mat& contour2,
int method, double parameter ); int method, double parameter );
//! computes convex hull for a set of 2D points. //! computes convex hull for a set of 2D points.
CV_EXPORTS void convexHull( const Mat& points, CV_OUT vector<int>& hull, bool clockwise=false ); CV_EXPORTS void convexHull( const InputArray& points, OutputArray hull,
//! computes convex hull for a set of 2D points. bool clockwise=false, bool returnPoints=true );
CV_EXPORTS void convexHull( const Mat& points, CV_OUT vector<Point>& hull, bool clockwise=false );
//! computes convex hull for a set of 2D points.
CV_EXPORTS void convexHull( const Mat& points, CV_OUT vector<Point2f>& hull, bool clockwise=false );
//! returns true iff the contour is convex. Does not support contours with self-intersection //! returns true iff the contour is convex. Does not support contours with self-intersection
CV_EXPORTS_W bool isContourConvex( const Mat& contour ); CV_EXPORTS_W bool isContourConvex( const InputArray& contour );
//! fits ellipse to the set of 2D points //! fits ellipse to the set of 2D points
CV_EXPORTS_W RotatedRect fitEllipse( const Mat& points ); CV_EXPORTS_W RotatedRect fitEllipse( const InputArray& points );
//! fits line to the set of 2D points using M-estimator algorithm //! fits line to the set of 2D points using M-estimator algorithm
CV_EXPORTS void fitLine( const Mat& points, CV_OUT Vec4f& line, int distType, CV_EXPORTS void fitLine( const InputArray& points, OutputArray line, int distType,
double param, double reps, double aeps );
//! fits line to the set of 3D points using M-estimator algorithm
CV_EXPORTS void fitLine( const Mat& points, CV_OUT Vec6f& line, int distType,
double param, double reps, double aeps ); double param, double reps, double aeps );
//! checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary //! checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary
CV_EXPORTS_W double pointPolygonTest( const Mat& contour, CV_EXPORTS_W double pointPolygonTest( const InputArray& contour, Point2f pt, bool measureDist );
Point2f pt, bool measureDist );
//! estimates the best-fit affine transformation that maps one 2D point set to another or one image to another.
CV_EXPORTS_W Mat estimateRigidTransform( const Mat& A, const Mat& B,
bool fullAffine );
} }
// 2009-01-12, Xavier Delacour <xavier.delacour@gmail.com> // 2009-01-12, Xavier Delacour <xavier.delacour@gmail.com>
struct lsh_hash { struct lsh_hash {

711
modules/imgproc/src/accum.cpp
Unescape View File

@ -45,555 +45,406 @@
namespace cv namespace cv
{ {
inline float sqr(uchar a) { return CV_8TO32F_SQR(a); } template<typename T, typename AT> void
inline float sqr(float a) { return a*a; } acc_( const T* src, AT* dst, const uchar* mask, int len, int cn )
{
inline double sqr(double a) { return a*a; } int i = 0;
inline Vec3f sqr(const Vec3b& a) if( !mask )
{ {
return Vec3f(CV_8TO32F_SQR(a[0]), CV_8TO32F_SQR(a[1]), CV_8TO32F_SQR(a[2])); len *= cn;
} for( ; i <= len - 4; i += 4 )
inline Vec3f sqr(const Vec3f& a)
{ {
return Vec3f(a[0]*a[0], a[1]*a[1], a[2]*a[2]); AT t0, t1;
t0 = src[i] + dst[i];
t1 = src[i+1] + dst[i+1];
dst[i] = t0; dst[i+1] = t1;
t0 = src[i+2] + dst[i+2];
t1 = src[i+3] + dst[i+3];
dst[i+2] = t0; dst[i+3] = t1;
} }
inline Vec3d sqr(const Vec3d& a)
{ for( ; i < len; i++ )
return Vec3d(a[0]*a[0], a[1]*a[1], a[2]*a[2]); dst[i] += src[i];
} }
inline float multiply(uchar a, uchar b) { return CV_8TO32F(a)*CV_8TO32F(b); } else if( cn == 1 )
inline float multiply(float a, float b) { return a*b; }
inline double multiply(double a, double b) { return a*b; }
inline Vec3f multiply(const Vec3b& a, const Vec3b& b)
{ {
return Vec3f( for( ; i < len; i++ )
CV_8TO32F(a[0])*CV_8TO32F(b[0]),
CV_8TO32F(a[1])*CV_8TO32F(b[1]),
CV_8TO32F(a[2])*CV_8TO32F(b[2]));
}
inline Vec3f multiply(const Vec3f& a, const Vec3f& b)
{ {
return Vec3f(a[0]*b[0], a[1]*b[1], a[2]*b[2]); if( mask[i] )
dst[i] += src[i];
} }
inline Vec3d multiply(const Vec3d& a, const Vec3d& b)
{
return Vec3d(a[0]*b[0], a[1]*b[1], a[2]*b[2]);
} }
else if( cn == 3 )
inline float addw(uchar a, float alpha, float b, float beta)
{ {
return b*beta + CV_8TO32F(a)*alpha; for( ; i < len; i++, src += 3, dst += 3 )
}
inline float addw(float a, float alpha, float b, float beta)
{ {
return b*beta + a*alpha; if( mask[i] )
}
inline double addw(uchar a, double alpha, double b, double beta)
{ {
return b*beta + CV_8TO32F(a)*alpha; AT t0 = src[0] + dst[0];
AT t1 = src[1] + dst[1];
AT t2 = src[2] + dst[2];
dst[0] = t0; dst[1] = t1; dst[2] = t2;
} }
inline double addw(float a, double alpha, double b, double beta)
{
return b*beta + a*alpha;
} }
inline double addw(double a, double alpha, double b, double beta)
{
return b*beta + a*alpha;
} }
else
inline Vec3f addw(const Vec3b& a, float alpha, const Vec3f& b, float beta)
{
return Vec3f(b[0]*beta + CV_8TO32F(a[0])*alpha,
b[1]*beta + CV_8TO32F(a[1])*alpha,
b[2]*beta + CV_8TO32F(a[2])*alpha);
}
inline Vec3f addw(const Vec3f& a, float alpha, const Vec3f& b, float beta)
{ {
return Vec3f(b[0]*beta + a[0]*alpha, b[1]*beta + a[1]*alpha, b[2]*beta + a[2]*alpha); for( ; i < len; i++, src += cn, dst += cn )
} if( mask[i] )
inline Vec3d addw(const Vec3b& a, double alpha, const Vec3d& b, double beta)
{ {
return Vec3d(b[0]*beta + CV_8TO32F(a[0])*alpha, for( int k = 0; k < cn; k++ )
b[1]*beta + CV_8TO32F(a[1])*alpha, dst[k] += src[k];
b[2]*beta + CV_8TO32F(a[2])*alpha);
} }
inline Vec3d addw(const Vec3f& a, double alpha, const Vec3d& b, double beta)
{
return Vec3d(b[0]*beta + a[0]*alpha, b[1]*beta + a[1]*alpha, b[2]*beta + a[2]*alpha);
} }
inline Vec3d addw(const Vec3d& a, double alpha, const Vec3d& b, double beta)
{
return Vec3d(b[0]*beta + a[0]*alpha, b[1]*beta + a[1]*alpha, b[2]*beta + a[2]*alpha);
} }
template<typename T, typename AT> void template<typename T, typename AT> void
acc_( const Mat& _src, Mat& _dst ) accSqr_( const T* src, AT* dst, const uchar* mask, int len, int cn )
{ {
Size size = _src.size(); int i = 0;
size.width *= _src.channels();
if( _src.isContinuous() && _dst.isContinuous() ) if( !mask )
{ {
size.width *= size.height; len *= cn;
size.height = 1; for( ; i <= len - 4; i += 4 )
}
int i, j;
for( i = 0; i < size.height; i++ )
{ {
const T* src = (const T*)(_src.data + _src.step*i); AT t0, t1;
AT* dst = (AT*)(_dst.data + _dst.step*i); t0 = (AT)src[i]*src[i] + dst[i];
t1 = (AT)src[i+1]*src[i+1] + dst[i+1];
dst[i] = t0; dst[i+1] = t1;
for( j = 0; j <= size.width - 4; j += 4 ) t0 = (AT)src[i+2]*src[i+2] + dst[i+2];
{ t1 = (AT)src[i+3]*src[i+3] + dst[i+3];
AT t0 = dst[j] + src[j], t1 = dst[j+1] + src[j+1]; dst[i+2] = t0; dst[i+3] = t1;
dst[j] = t0; dst[j+1] = t1;
t0 = dst[j+2] + src[j+2]; t1 = dst[j+3] + src[j+3];
dst[j+2] = t0; dst[j+3] = t1;
} }
for( ; j < size.width; j++ ) for( ; i < len; i++ )
dst[j] += src[j]; dst[i] += (AT)src[i]*src[i];
}
} }
else if( cn == 1 )
template<typename T, typename AT> void
accSqr_( const Mat& _src, Mat& _dst )
{ {
Size size = _src.size(); for( ; i < len; i++ )
size.width *= _src.channels();
if( _src.isContinuous() && _dst.isContinuous() )
{ {
size.width *= size.height; if( mask[i] )
size.height = 1; dst[i] += (AT)src[i]*src[i];
} }
}
int i, j; else if( cn == 3 )
for( i = 0; i < size.height; i++ ) {
for( ; i < len; i++, src += 3, dst += 3 )
{ {
const T* src = (const T*)(_src.data + _src.step*i); if( mask[i] )
AT* dst = (AT*)(_dst.data + _dst.step*i); {
AT t0 = (AT)src[0]*src[0] + dst[0];
AT t1 = (AT)src[1]*src[1] + dst[1];
AT t2 = (AT)src[2]*src[2] + dst[2];
for( j = 0; j <= size.width - 4; j += 4 ) dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
}
else
{
for( ; i < len; i++, src += cn, dst += cn )
if( mask[i] )
{ {
AT t0 = dst[j] + sqr(src[j]), t1 = dst[j+1] + sqr(src[j+1]); for( int k = 0; k < cn; k++ )
dst[j] = t0; dst[j+1] = t1; dst[k] += (AT)src[k]*src[k];
t0 = dst[j+2] + sqr(src[j+2]); t1 = dst[j+3] + sqr(src[j+3]);
dst[j+2] = t0; dst[j+3] = t1;
} }
for( ; j < size.width; j++ )
dst[j] += sqr(src[j]);
} }
} }
template<typename T, typename AT> void template<typename T, typename AT> void
accProd_( const Mat& _src1, const Mat& _src2, Mat& _dst ) accProd_( const T* src1, const T* src2, AT* dst, const uchar* mask, int len, int cn )
{
Size size = _src1.size();
size.width *= _src1.channels();
if( _src1.isContinuous() && _src2.isContinuous() && _dst.isContinuous() )
{ {
size.width *= size.height; int i = 0;
size.height = 1;
}
int i, j; if( !mask )
for( i = 0; i < size.height; i++ )
{ {
const T* src1 = (const T*)(_src1.data + _src1.step*i); len *= cn;
const T* src2 = (const T*)(_src2.data + _src2.step*i); for( ; i <= len - 4; i += 4 )
AT* dst = (AT*)(_dst.data + _dst.step*i);
for( j = 0; j <= size.width - 4; j += 4 )
{ {
AT t0, t1; AT t0, t1;
t0 = dst[j] + multiply(src1[j], src2[j]); t0 = (AT)src1[i]*src2[i] + dst[i];
t1 = dst[j+1] + multiply(src1[j+1], src2[j+1]); t1 = (AT)src1[i+1]*src2[i+1] + dst[i+1];
dst[j] = t0; dst[j+1] = t1; dst[i] = t0; dst[i+1] = t1;
t0 = dst[j+2] + multiply(src1[j+2], src2[j+2]);
t1 = dst[j+3] + multiply(src1[j+3], src2[j+3]);
dst[j+2] = t0; dst[j+3] = t1;
}
for( ; j < size.width; j++ ) t0 = (AT)src1[i+2]*src2[i+2] + dst[i+2];
dst[j] += multiply(src1[j], src2[j]); t1 = (AT)src1[i+3]*src2[i+3] + dst[i+3];
dst[i+2] = t0; dst[i+3] = t1;
} }
}
template<typename T, typename AT> void for( ; i < len; i++ )
accW_( const Mat& _src, Mat& _dst, double _alpha ) dst[i] += (AT)src1[i]*src2[i];
}
else if( cn == 1 )
{ {
AT alpha = (AT)_alpha, beta = (AT)(1 - _alpha); for( ; i < len; i++ )
Size size = _src.size();
size.width *= _src.channels();
if( _src.isContinuous() && _dst.isContinuous() )
{ {
size.width *= size.height; if( mask[i] )
size.height = 1; dst[i] += (AT)src1[i]*src2[i];
} }
}
int i, j; else if( cn == 3 )
for( i = 0; i < size.height; i++ ) {
for( ; i < len; i++, src1 += 3, src2 += 3, dst += 3 )
{ {
const T* src = (const T*)(_src.data + _src.step*i); if( mask[i] )
AT* dst = (AT*)(_dst.data + _dst.step*i); {
AT t0 = (AT)src1[0]*src2[0] + dst[0];
AT t1 = (AT)src1[1]*src2[1] + dst[1];
AT t2 = (AT)src1[2]*src2[2] + dst[2];
for( j = 0; j <= size.width - 4; j += 4 ) dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
}
else
{ {
AT t0, t1; for( ; i < len; i++, src1 += cn, src2 += cn, dst += cn )
t0 = addw(src[j], alpha, dst[j], beta); if( mask[i] )
t1 = addw(src[j+1], alpha, dst[j+1], beta); {
dst[j] = t0; dst[j+1] = t1; for( int k = 0; k < cn; k++ )
t0 = addw(src[j+2], alpha, dst[j+2], beta); dst[k] += (AT)src1[k]*src2[k];
t1 = addw(src[j+3], alpha, dst[j+3], beta);
dst[j+2] = t0; dst[j+3] = t1;
} }
for( ; j < size.width; j++ )
dst[j] = addw(src[j], alpha, dst[j], beta);
} }
} }
template<typename T, typename AT> void template<typename T, typename AT> void
accMask_( const Mat& _src, Mat& _dst, const Mat& _mask ) accW_( const T* src, AT* dst, const uchar* mask, int len, int cn, double alpha )
{ {
Size size = _src.size(); AT a = (AT)alpha, b = 1 - a;
int i = 0;
if( _src.isContinuous() && _dst.isContinuous() && _mask.isContinuous() ) if( !mask )
{ {
size.width *= size.height; len *= cn;
size.height = 1; for( ; i <= len - 4; i += 4 )
}
int i, j;
for( i = 0; i < size.height; i++ )
{ {
const T* src = (const T*)(_src.data + _src.step*i); AT t0, t1;
AT* dst = (AT*)(_dst.data + _dst.step*i); t0 = src[i]*a + dst[i]*b;
const uchar* mask = _mask.data + _mask.step*i; t1 = src[i+1]*a + dst[i+1]*b;
dst[i] = t0; dst[i+1] = t1;
for( j = 0; j < size.width; j++ ) t0 = src[i+2]*a + dst[i+2]*b;
if( mask[j] ) t1 = src[i+3]*a + dst[i+3]*b;
dst[j] += src[j]; dst[i+2] = t0; dst[i+3] = t1;
}
} }
for( ; i < len; i++ )
template<typename T, typename AT> void dst[i] = src[i]*a + dst[i]*b;
accSqrMask_( const Mat& _src, Mat& _dst, const Mat& _mask ) }
else if( cn == 1 )
{ {
Size size = _src.size(); for( ; i < len; i++ )
if( _src.isContinuous() && _dst.isContinuous() && _mask.isContinuous() )
{ {
size.width *= size.height; if( mask[i] )
size.height = 1; dst[i] = src[i]*a + dst[i]*b;
} }
}
int i, j; else if( cn == 3 )
for( i = 0; i < size.height; i++ ) {
for( ; i < len; i++, src += 3, dst += 3 )
{ {
const T* src = (const T*)(_src.data + _src.step*i); if( mask[i] )
AT* dst = (AT*)(_dst.data + _dst.step*i); {
const uchar* mask = _mask.data + _mask.step*i; AT t0 = src[0]*a + dst[0]*b;
AT t1 = src[1]*a + dst[1]*b;
AT t2 = src[2]*a + dst[2]*b;
for( j = 0; j < size.width; j++ ) dst[0] = t0; dst[1] = t1; dst[2] = t2;
if( mask[j] )
dst[j] += sqr(src[j]);
} }
} }
}
else
template<typename T, typename AT> void
accProdMask_( const Mat& _src1, const Mat& _src2, Mat& _dst, const Mat& _mask )
{ {
Size size = _src1.size(); for( ; i < len; i++, src += cn, dst += cn )
if( mask[i] )
if( _src1.isContinuous() && _src2.isContinuous() &&
_dst.isContinuous() && _mask.isContinuous() )
{ {
size.width *= size.height; for( int k = 0; k < cn; k++ )
size.height = 1; dst[k] += src[k]*a + dst[k]*b;
} }
int i, j;
for( i = 0; i < size.height; i++ )
{
const T* src1 = (const T*)(_src1.data + _src1.step*i);
const T* src2 = (const T*)(_src2.data + _src2.step*i);
AT* dst = (AT*)(_dst.data + _dst.step*i);
const uchar* mask = _mask.data + _mask.step*i;
for( j = 0; j < size.width; j++ )
if( mask[j] )
dst[j] += multiply(src1[j], src2[j]);
} }
} }
template<typename T, typename AT> void #define DEF_ACC_FUNCS(suffix, type, acctype) \
accWMask_( const Mat& _src, Mat& _dst, double _alpha, const Mat& _mask ) static void acc_##suffix(const type* src, acctype* dst, \
{ const uchar* mask, int len, int cn) \
typedef typename DataType<AT>::channel_type AT1; { acc_(src, dst, mask, len, cn); } \
AT1 alpha = (AT1)_alpha, beta = (AT1)(1 - _alpha); \
Size size = _src.size(); static void accSqr_##suffix(const type* src, acctype* dst, \
const uchar* mask, int len, int cn) \
{ accSqr_(src, dst, mask, len, cn); } \
\
static void accProd_##suffix(const type* src1, const type* src2, \
acctype* dst, const uchar* mask, int len, int cn) \
{ accProd_(src1, src2, dst, mask, len, cn); } \
\
static void accW_##suffix(const type* src, acctype* dst, \
const uchar* mask, int len, int cn, double alpha) \
{ accW_(src, dst, mask, len, cn, alpha); }
if( _src.isContinuous() && _dst.isContinuous() && _mask.isContinuous() )
{
size.width *= size.height;
size.height = 1;
}
int i, j; DEF_ACC_FUNCS(8u32f, uchar, float)
for( i = 0; i < size.height; i++ ) DEF_ACC_FUNCS(8u64f, uchar, double)
{ DEF_ACC_FUNCS(16u32f, ushort, float)
const T* src = (const T*)(_src.data + _src.step*i); DEF_ACC_FUNCS(16u64f, ushort, double)
AT* dst = (AT*)(_dst.data + _dst.step*i); DEF_ACC_FUNCS(32f, float, float)
const uchar* mask = _mask.data + _mask.step*i; DEF_ACC_FUNCS(32f64f, float, double)
DEF_ACC_FUNCS(64f, double, double)
for( j = 0; j < size.width; j++ )
if( mask[j] )
dst[j] = addw(src[j], alpha, dst[j], beta);
}
}
typedef void (*AccFunc)(const uchar*, uchar*, const uchar*, int, int);
typedef void (*AccProdFunc)(const uchar*, const uchar*, uchar*, const uchar*, int, int);
typedef void (*AccWFunc)(const uchar*, uchar*, const uchar*, int, int, double);
typedef void (*AccFunc)(const Mat&, Mat&); static AccFunc accTab[] =
typedef void (*AccMaskFunc)(const Mat&, Mat&, const Mat&); {
typedef void (*AccProdFunc)(const Mat&, const Mat&, Mat&); (AccFunc)acc_8u32f, (AccFunc)acc_8u64f,
typedef void (*AccProdMaskFunc)(const Mat&, const Mat&, Mat&, const Mat&); (AccFunc)acc_16u32f, (AccFunc)acc_16u64f,
typedef void (*AccWFunc)(const Mat&, Mat&, double); (AccFunc)acc_32f, (AccFunc)acc_32f64f,
typedef void (*AccWMaskFunc)(const Mat&, Mat&, double, const Mat&); (AccFunc)acc_64f
};
void accumulate( const Mat& src, Mat& dst, const Mat& mask ) static AccFunc accSqrTab[] =
{ {
CV_Assert( dst.size() == src.size() && dst.channels() == src.channels() ); (AccFunc)accSqr_8u32f, (AccFunc)accSqr_8u64f,
(AccFunc)accSqr_16u32f, (AccFunc)accSqr_16u64f,
(AccFunc)accSqr_32f, (AccFunc)accSqr_32f64f,
(AccFunc)accSqr_64f
};
if( !mask.data ) static AccProdFunc accProdTab[] =
{ {
AccFunc func = 0; (AccProdFunc)accProd_8u32f, (AccProdFunc)accProd_8u64f,
if( src.depth() == CV_8U && dst.depth() == CV_32F ) (AccProdFunc)accProd_16u32f, (AccProdFunc)accProd_16u64f,
func = acc_<uchar, float>; (AccProdFunc)accProd_32f, (AccProdFunc)accProd_32f64f,
else if( src.depth() == CV_8U && dst.depth() == CV_64F ) (AccProdFunc)accProd_64f
func = acc_<uchar, double>; };
else if( src.depth() == CV_32F && dst.depth() == CV_32F )
func = acc_<float, float>;
else if( src.depth() == CV_32F && dst.depth() == CV_64F )
func = acc_<float, double>;
else if( src.depth() == CV_64F && dst.depth() == CV_64F )
func = acc_<double, double>;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src, dst ); static AccWFunc accWTab[] =
}
else
{ {
CV_Assert( mask.size() == src.size() && mask.type() == CV_8UC1 ); (AccWFunc)accW_8u32f, (AccWFunc)accW_8u64f,
(AccWFunc)accW_16u32f, (AccWFunc)accW_16u64f,
AccMaskFunc func = 0; (AccWFunc)accW_32f, (AccWFunc)accW_32f64f,
if( src.type() == CV_8UC1 && dst.type() == CV_32FC1 ) (AccWFunc)accW_64f
func = accMask_<uchar, float>; };
else if( src.type() == CV_8UC3 && dst.type() == CV_32FC3 )
func = accMask_<Vec3b, Vec3f>;
else if( src.type() == CV_8UC1 && dst.type() == CV_64FC1 )
func = accMask_<uchar, double>;
else if( src.type() == CV_8UC3 && dst.type() == CV_64FC3 )
func = accMask_<Vec3b, Vec3d>;
else if( src.type() == CV_32FC1 && dst.type() == CV_32FC1 )
func = accMask_<float, float>;
else if( src.type() == CV_32FC3 && dst.type() == CV_32FC3 )
func = accMask_<Vec3f, Vec3f>;
else if( src.type() == CV_32FC1 && dst.type() == CV_64FC1 )
func = accMask_<float, double>;
else if( src.type() == CV_32FC3 && dst.type() == CV_64FC3 )
func = accMask_<Vec3f, Vec3d>;
else if( src.type() == CV_64FC1 && dst.type() == CV_64FC1 )
func = accMask_<double, double>;
else if( src.type() == CV_64FC3 && dst.type() == CV_64FC3 )
func = accMask_<Vec3d, Vec3d>;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src, dst, mask ); inline int getAccTabIdx(int sdepth, int ddepth)
} {
return sdepth == CV_8U && ddepth == CV_32F ? 0 :
sdepth == CV_8U && ddepth == CV_64F ? 1 :
sdepth == CV_16U && ddepth == CV_32F ? 2 :
sdepth == CV_16U && ddepth == CV_64F ? 3 :
sdepth == CV_32F && ddepth == CV_32F ? 4 :
sdepth == CV_32F && ddepth == CV_64F ? 5 :
sdepth == CV_64F && ddepth == CV_64F ? 6 : -1;
} }
}
void accumulateSquare( const Mat& src, Mat& dst, const Mat& mask ) void cv::accumulate( const InputArray& _src, InputOutputArray _dst, const InputArray& _mask )
{ {
CV_Assert( dst.size() == src.size() && dst.channels() == src.channels() ); Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src.depth(), ddepth = dst.depth(), cn = src.channels();
if( !mask.data ) CV_Assert( dst.size == src.size && dst.channels() == cn );
{
AccFunc func = 0;
if( src.depth() == CV_8U && dst.depth() == CV_32F )
func = accSqr_<uchar, float>;
else if( src.depth() == CV_8U && dst.depth() == CV_64F )
func = accSqr_<uchar, double>;
else if( src.depth() == CV_32F && dst.depth() == CV_32F )
func = accSqr_<float, float>;
else if( src.depth() == CV_32F && dst.depth() == CV_64F )
func = accSqr_<float, double>;
else if( src.depth() == CV_64F && dst.depth() == CV_64F )
func = accSqr_<double, double>;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src, dst ); if( !mask.empty() )
} CV_Assert( mask.size == src.size && mask.type() == CV_8U );
else
{
CV_Assert( mask.size() == src.size() && mask.type() == CV_8UC1 );
AccMaskFunc func = 0;
if( src.type() == CV_8UC1 && dst.type() == CV_32FC1 )
func = accSqrMask_<uchar, float>;
else if( src.type() == CV_8UC3 && dst.type() == CV_32FC3 )
func = accSqrMask_<Vec3b, Vec3f>;
else if( src.type() == CV_8UC1 && dst.type() == CV_64FC1 )
func = accSqrMask_<uchar, double>;
else if( src.type() == CV_8UC3 && dst.type() == CV_64FC3 )
func = accSqrMask_<Vec3b, Vec3d>;
else if( src.type() == CV_32FC1 && dst.type() == CV_32FC1 )
func = accSqrMask_<float, float>;
else if( src.type() == CV_32FC3 && dst.type() == CV_32FC3 )
func = accSqrMask_<Vec3f, Vec3f>;
else if( src.type() == CV_32FC1 && dst.type() == CV_64FC1 )
func = accSqrMask_<float, double>;
else if( src.type() == CV_32FC3 && dst.type() == CV_64FC3 )
func = accSqrMask_<Vec3f, Vec3d>;
else if( src.type() == CV_64FC1 && dst.type() == CV_64FC1 )
func = accSqrMask_<double, double>;
else if( src.type() == CV_64FC3 && dst.type() == CV_64FC3 )
func = accSqrMask_<Vec3d, Vec3d>;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src, dst, mask ); int fidx = getAccTabIdx(sdepth, ddepth);
} AccFunc func = fidx >= 0 ? accTab[fidx] : 0;
CV_Assert( func != 0 );
const Mat* arrays[] = {&src, &dst, &mask, 0};
uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, cn);
} }
void accumulateProduct( const Mat& src1, const Mat& src2, Mat& dst, const Mat& mask ) void cv::accumulateSquare( const InputArray& _src, InputOutputArray _dst, const InputArray& _mask )
{ {
CV_Assert( dst.size() == src1.size() && dst.channels() == src1.channels() && Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
src1.size() == src2.size() && src1.type() == src2.type() ); int sdepth = src.depth(), ddepth = dst.depth(), cn = src.channels();
if( !mask.data ) CV_Assert( dst.size == src.size && dst.channels() == cn );
{
AccProdFunc func = 0;
if( src1.depth() == CV_8U && dst.depth() == CV_32F )
func = accProd_<uchar, float>;
else if( src1.depth() == CV_8U && dst.depth() == CV_64F )
func = accProd_<uchar, double>;
else if( src1.depth() == CV_32F && dst.depth() == CV_32F )
func = accProd_<float, float>;
else if( src1.depth() == CV_32F && dst.depth() == CV_64F )
func = accProd_<float, double>;
else if( src1.depth() == CV_64F && dst.depth() == CV_64F )
func = accProd_<double, double>;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src1, src2, dst ); if( !mask.empty() )
CV_Assert( mask.size == src.size && mask.type() == CV_8U );
int fidx = getAccTabIdx(sdepth, ddepth);
AccFunc func = fidx >= 0 ? accSqrTab[fidx] : 0;
CV_Assert( func != 0 );
const Mat* arrays[] = {&src, &dst, &mask, 0};
uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, cn);
} }
else
void cv::accumulateProduct( const InputArray& _src1, const InputArray& _src2,
InputOutputArray _dst, const InputArray& _mask )
{ {
CV_Assert( mask.size() == src1.size() && mask.type() == CV_8UC1 ); Mat src1 = _src1.getMat(), src2 = _src2.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src1.depth(), ddepth = dst.depth(), cn = src1.channels();
AccProdMaskFunc func = 0;
if( src1.type() == CV_8UC1 && dst.type() == CV_32FC1 )
func = accProdMask_<uchar, float>;
else if( src1.type() == CV_8UC3 && dst.type() == CV_32FC3 )
func = accProdMask_<Vec3b, Vec3f>;
else if( src1.type() == CV_8UC1 && dst.type() == CV_64FC1 )
func = accProdMask_<uchar, double>;
else if( src1.type() == CV_8UC3 && dst.type() == CV_64FC3 )
func = accProdMask_<Vec3b, Vec3d>;
else if( src1.type() == CV_32FC1 && dst.type() == CV_32FC1 )
func = accProdMask_<float, float>;
else if( src1.type() == CV_32FC3 && dst.type() == CV_32FC3 )
func = accProdMask_<Vec3f, Vec3f>;
else if( src1.type() == CV_32FC1 && dst.type() == CV_64FC1 )
func = accProdMask_<float, double>;
else if( src1.type() == CV_32FC3 && dst.type() == CV_64FC3 )
func = accProdMask_<Vec3f, Vec3d>;
else if( src1.type() == CV_64FC1 && dst.type() == CV_64FC1 )
func = accProdMask_<double, double>;
else if( src1.type() == CV_64FC3 && dst.type() == CV_64FC3 )
func = accProdMask_<Vec3d, Vec3d>;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src1, src2, dst, mask ); CV_Assert( src2.size && src1.size && src2.type() == src1.type() );
} CV_Assert( dst.size == src1.size && dst.channels() == cn );
}
if( !mask.empty() )
CV_Assert( mask.size == src1.size && mask.type() == CV_8U );
void accumulateWeighted( const Mat& src, Mat& dst, double alpha, const Mat& mask ) int fidx = getAccTabIdx(sdepth, ddepth);
{ AccProdFunc func = fidx >= 0 ? accProdTab[fidx] : 0;
CV_Assert( dst.size() == src.size() && dst.channels() == src.channels() ); CV_Assert( func != 0 );
if( !mask.data ) const Mat* arrays[] = {&src1, &src2, &dst, &mask, 0};
{ uchar* ptrs[4];
AccWFunc func = 0; NAryMatIterator it(arrays, ptrs);
if( src.depth() == CV_8U && dst.depth() == CV_32F ) int len = (int)it.size;
func = accW_<uchar, float>;
else if( src.depth() == CV_8U && dst.depth() == CV_64F )
func = accW_<uchar, double>;
else if( src.depth() == CV_32F && dst.depth() == CV_32F )
func = accW_<float, float>;
else if( src.depth() == CV_32F && dst.depth() == CV_64F )
func = accW_<float, double>;
else if( src.depth() == CV_64F && dst.depth() == CV_64F )
func = accW_<double, double>;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src, dst, alpha ); for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], ptrs[3], len, cn);
} }
else
void cv::accumulateWeighted( const InputArray& _src, CV_IN_OUT InputOutputArray _dst,
double alpha, const InputArray& _mask )
{ {
CV_Assert( mask.size() == src.size() && mask.type() == CV_8UC1 ); Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src.depth(), ddepth = dst.depth(), cn = src.channels();
AccWMaskFunc func = 0;
if( src.type() == CV_8UC1 && dst.type() == CV_32FC1 )
func = accWMask_<uchar, float>;
else if( src.type() == CV_8UC3 && dst.type() == CV_32FC3 )
func = accWMask_<Vec3b, Vec3f>;
else if( src.type() == CV_8UC1 && dst.type() == CV_64FC1 )
func = accWMask_<uchar, double>;
else if( src.type() == CV_8UC3 && dst.type() == CV_64FC3 )
func = accWMask_<Vec3b, Vec3d>;
else if( src.type() == CV_32FC1 && dst.type() == CV_32FC1 )
func = accWMask_<float, float>;
else if( src.type() == CV_32FC3 && dst.type() == CV_32FC3 )
func = accWMask_<Vec3f, Vec3f>;
else if( src.type() == CV_32FC1 && dst.type() == CV_64FC1 )
func = accWMask_<float, double>;
else if( src.type() == CV_32FC3 && dst.type() == CV_64FC3 )
func = accWMask_<Vec3f, Vec3d>;
else if( src.type() == CV_64FC1 && dst.type() == CV_64FC1 )
func = accWMask_<double, double>;
else if( src.type() == CV_64FC3 && dst.type() == CV_64FC3 )
func = accWMask_<Vec3d, Vec3d>;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src, dst, alpha, mask ); CV_Assert( dst.size == src.size && dst.channels() == cn );
}
} if( !mask.empty() )
CV_Assert( mask.size == src.size && mask.type() == CV_8U );
int fidx = getAccTabIdx(sdepth, ddepth);
AccWFunc func = fidx >= 0 ? accWTab[fidx] : 0;
CV_Assert( func != 0 );
const Mat* arrays[] = {&src, &dst, &mask, 0};
uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, cn, alpha);
} }

10
modules/imgproc/src/canny.cpp
Unescape View File

@ -335,14 +335,14 @@ CV_IMPL void cvCanny( const void* srcarr, void* dstarr,
} }
} }
void cv::Canny( const Mat& image, Mat& edges, void cv::Canny( const InputArray& image, OutputArray _edges,
double threshold1, double threshold2, double threshold1, double threshold2,
int apertureSize, bool L2gradient ) int apertureSize, bool L2gradient )
{ {
Mat src = image; Mat src = image.getMat();
edges.create(src.size(), CV_8U); _edges.create(src.size(), CV_8U);
CvMat _src = src, _dst = edges; CvMat c_src = src, c_dst = _edges.getMat();
cvCanny( &_src, &_dst, threshold1, threshold2, cvCanny( &c_src, &c_dst, threshold1, threshold2,
apertureSize + (L2gradient ? CV_CANNY_L2_GRADIENT : 0)); apertureSize + (L2gradient ? CV_CANNY_L2_GRADIENT : 0));
} }

63
modules/imgproc/src/color.cpp
Unescape View File

@ -2618,13 +2618,15 @@ static void Bayer2RGB_VNG_8u( const Mat& srcmat, Mat& dstmat, int code )
} }
} }
}
////////////////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////////////////
// The main function // // The main function //
////////////////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////////////////
void cvtColor( const Mat& src, Mat& dst, int code, int dcn ) void cv::cvtColor( const InputArray& _src, OutputArray _dst, int code, int dcn )
{ {
Mat src = _src.getMat(), dst;
Size sz = src.size(); Size sz = src.size();
int scn = src.channels(), depth = src.depth(), bidx; int scn = src.channels(), depth = src.depth(), bidx;
@ -2638,7 +2640,9 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
dcn = code == CV_BGR2BGRA || code == CV_RGB2BGRA || code == CV_BGRA2RGBA ? 4 : 3; dcn = code == CV_BGR2BGRA || code == CV_RGB2BGRA || code == CV_BGRA2RGBA ? 4 : 3;
bidx = code == CV_BGR2BGRA || code == CV_BGRA2BGR ? 0 : 2; bidx = code == CV_BGR2BGRA || code == CV_BGRA2BGR ? 0 : 2;
dst.create( sz, CV_MAKETYPE(depth, dcn)); _dst.create( sz, CV_MAKETYPE(depth, dcn));
dst = _dst.getMat();
if( depth == CV_8U ) if( depth == CV_8U )
CvtColorLoop(src, dst, RGB2RGB<uchar>(scn, dcn, bidx)); CvtColorLoop(src, dst, RGB2RGB<uchar>(scn, dcn, bidx));
else if( depth == CV_16U ) else if( depth == CV_16U )
@ -2650,7 +2654,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
case CV_BGR2BGR565: case CV_BGR2BGR555: case CV_RGB2BGR565: case CV_RGB2BGR555: case CV_BGR2BGR565: case CV_BGR2BGR555: case CV_RGB2BGR565: case CV_RGB2BGR555:
case CV_BGRA2BGR565: case CV_BGRA2BGR555: case CV_RGBA2BGR565: case CV_RGBA2BGR555: case CV_BGRA2BGR565: case CV_BGRA2BGR555: case CV_RGBA2BGR565: case CV_RGBA2BGR555:
CV_Assert( (scn == 3 || scn == 4) && depth == CV_8U ); CV_Assert( (scn == 3 || scn == 4) && depth == CV_8U );
dst.create(sz, CV_8UC2); _dst.create(sz, CV_8UC2);
dst = _dst.getMat();
CvtColorLoop(src, dst, RGB2RGB5x5(scn, CvtColorLoop(src, dst, RGB2RGB5x5(scn,
code == CV_BGR2BGR565 || code == CV_BGR2BGR555 || code == CV_BGR2BGR565 || code == CV_BGR2BGR555 ||
@ -2664,7 +2669,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
case CV_BGR5652BGRA: case CV_BGR5552BGRA: case CV_BGR5652RGBA: case CV_BGR5552RGBA: case CV_BGR5652BGRA: case CV_BGR5552BGRA: case CV_BGR5652RGBA: case CV_BGR5552RGBA:
if(dcn <= 0) dcn = 3; if(dcn <= 0) dcn = 3;
CV_Assert( (dcn == 3 || dcn == 4) && scn == 2 && depth == CV_8U ); CV_Assert( (dcn == 3 || dcn == 4) && scn == 2 && depth == CV_8U );
dst.create(sz, CV_MAKETYPE(depth, dcn)); _dst.create(sz, CV_MAKETYPE(depth, dcn));
dst = _dst.getMat();
CvtColorLoop(src, dst, RGB5x52RGB(dcn, CvtColorLoop(src, dst, RGB5x52RGB(dcn,
code == CV_BGR5652BGR || code == CV_BGR5552BGR || code == CV_BGR5652BGR || code == CV_BGR5552BGR ||
@ -2676,7 +2682,9 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
case CV_BGR2GRAY: case CV_BGRA2GRAY: case CV_RGB2GRAY: case CV_RGBA2GRAY: case CV_BGR2GRAY: case CV_BGRA2GRAY: case CV_RGB2GRAY: case CV_RGBA2GRAY:
CV_Assert( scn == 3 || scn == 4 ); CV_Assert( scn == 3 || scn == 4 );
dst.create(sz, CV_MAKETYPE(depth, 1)); _dst.create(sz, CV_MAKETYPE(depth, 1));
dst = _dst.getMat();
bidx = code == CV_BGR2GRAY || code == CV_BGRA2GRAY ? 0 : 2; bidx = code == CV_BGR2GRAY || code == CV_BGRA2GRAY ? 0 : 2;
if( depth == CV_8U ) if( depth == CV_8U )
@ -2689,14 +2697,17 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
case CV_BGR5652GRAY: case CV_BGR5552GRAY: case CV_BGR5652GRAY: case CV_BGR5552GRAY:
CV_Assert( scn == 2 && depth == CV_8U ); CV_Assert( scn == 2 && depth == CV_8U );
dst.create(sz, CV_8UC1); _dst.create(sz, CV_8UC1);
dst = _dst.getMat();
CvtColorLoop(src, dst, RGB5x52Gray(code == CV_BGR5652GRAY ? 6 : 5)); CvtColorLoop(src, dst, RGB5x52Gray(code == CV_BGR5652GRAY ? 6 : 5));
break; break;
case CV_GRAY2BGR: case CV_GRAY2BGRA: case CV_GRAY2BGR: case CV_GRAY2BGRA:
if( dcn <= 0 ) dcn = 3; if( dcn <= 0 ) dcn = 3;
CV_Assert( scn == 1 && (dcn == 3 || dcn == 4)); CV_Assert( scn == 1 && (dcn == 3 || dcn == 4));
dst.create(sz, CV_MAKETYPE(depth, dcn)); _dst.create(sz, CV_MAKETYPE(depth, dcn));
dst = _dst.getMat();
if( depth == CV_8U ) if( depth == CV_8U )
CvtColorLoop(src, dst, Gray2RGB<uchar>(dcn)); CvtColorLoop(src, dst, Gray2RGB<uchar>(dcn));
@ -2708,7 +2719,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
case CV_GRAY2BGR565: case CV_GRAY2BGR555: case CV_GRAY2BGR565: case CV_GRAY2BGR555:
CV_Assert( scn == 1 && depth == CV_8U ); CV_Assert( scn == 1 && depth == CV_8U );
dst.create(sz, CV_8UC2); _dst.create(sz, CV_8UC2);
dst = _dst.getMat();
CvtColorLoop(src, dst, Gray2RGB5x5(code == CV_GRAY2BGR565 ? 6 : 5)); CvtColorLoop(src, dst, Gray2RGB5x5(code == CV_GRAY2BGR565 ? 6 : 5));
break; break;
@ -2723,7 +2735,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
const float* coeffs_f = code == CV_BGR2YCrCb || code == CV_RGB2YCrCb ? 0 : yuv_f; const float* coeffs_f = code == CV_BGR2YCrCb || code == CV_RGB2YCrCb ? 0 : yuv_f;
const int* coeffs_i = code == CV_BGR2YCrCb || code == CV_RGB2YCrCb ? 0 : yuv_i; const int* coeffs_i = code == CV_BGR2YCrCb || code == CV_RGB2YCrCb ? 0 : yuv_i;
dst.create(sz, CV_MAKETYPE(depth, 3)); _dst.create(sz, CV_MAKETYPE(depth, 3));
dst = _dst.getMat();
if( depth == CV_8U ) if( depth == CV_8U )
CvtColorLoop(src, dst, RGB2YCrCb_i<uchar>(scn, bidx, coeffs_i)); CvtColorLoop(src, dst, RGB2YCrCb_i<uchar>(scn, bidx, coeffs_i));
@ -2745,7 +2758,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
const float* coeffs_f = code == CV_YCrCb2BGR || code == CV_YCrCb2RGB ? 0 : yuv_f; const float* coeffs_f = code == CV_YCrCb2BGR || code == CV_YCrCb2RGB ? 0 : yuv_f;
const int* coeffs_i = code == CV_YCrCb2BGR || code == CV_YCrCb2RGB ? 0 : yuv_i; const int* coeffs_i = code == CV_YCrCb2BGR || code == CV_YCrCb2RGB ? 0 : yuv_i;
dst.create(sz, CV_MAKETYPE(depth, dcn)); _dst.create(sz, CV_MAKETYPE(depth, dcn));
dst = _dst.getMat();
if( depth == CV_8U ) if( depth == CV_8U )
CvtColorLoop(src, dst, YCrCb2RGB_i<uchar>(dcn, bidx, coeffs_i)); CvtColorLoop(src, dst, YCrCb2RGB_i<uchar>(dcn, bidx, coeffs_i));
@ -2760,7 +2774,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
CV_Assert( scn == 3 || scn == 4 ); CV_Assert( scn == 3 || scn == 4 );
bidx = code == CV_BGR2XYZ ? 0 : 2; bidx = code == CV_BGR2XYZ ? 0 : 2;
dst.create(sz, CV_MAKETYPE(depth, 3)); _dst.create(sz, CV_MAKETYPE(depth, 3));
dst = _dst.getMat();
if( depth == CV_8U ) if( depth == CV_8U )
CvtColorLoop(src, dst, RGB2XYZ_i<uchar>(scn, bidx, 0)); CvtColorLoop(src, dst, RGB2XYZ_i<uchar>(scn, bidx, 0));
@ -2775,7 +2790,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
CV_Assert( scn == 3 && (dcn == 3 || dcn == 4) ); CV_Assert( scn == 3 && (dcn == 3 || dcn == 4) );
bidx = code == CV_XYZ2BGR ? 0 : 2; bidx = code == CV_XYZ2BGR ? 0 : 2;
dst.create(sz, CV_MAKETYPE(depth, dcn)); _dst.create(sz, CV_MAKETYPE(depth, dcn));
dst = _dst.getMat();
if( depth == CV_8U ) if( depth == CV_8U )
CvtColorLoop(src, dst, XYZ2RGB_i<uchar>(dcn, bidx, 0)); CvtColorLoop(src, dst, XYZ2RGB_i<uchar>(dcn, bidx, 0));
@ -2794,7 +2810,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
int hrange = depth == CV_32F ? 360 : code == CV_BGR2HSV || code == CV_RGB2HSV || int hrange = depth == CV_32F ? 360 : code == CV_BGR2HSV || code == CV_RGB2HSV ||
code == CV_BGR2HLS || code == CV_RGB2HLS ? 180 : 255; code == CV_BGR2HLS || code == CV_RGB2HLS ? 180 : 255;
dst.create(sz, CV_MAKETYPE(depth, 3)); _dst.create(sz, CV_MAKETYPE(depth, 3));
dst = _dst.getMat();
if( code == CV_BGR2HSV || code == CV_RGB2HSV || if( code == CV_BGR2HSV || code == CV_RGB2HSV ||
code == CV_BGR2HSV_FULL || code == CV_RGB2HSV_FULL ) code == CV_BGR2HSV_FULL || code == CV_RGB2HSV_FULL )
@ -2824,7 +2841,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
int hrange = depth == CV_32F ? 360 : code == CV_HSV2BGR || code == CV_HSV2RGB || int hrange = depth == CV_32F ? 360 : code == CV_HSV2BGR || code == CV_HSV2RGB ||
code == CV_HLS2BGR || code == CV_HLS2RGB ? 180 : 255; code == CV_HLS2BGR || code == CV_HLS2RGB ? 180 : 255;
dst.create(sz, CV_MAKETYPE(depth, dcn)); _dst.create(sz, CV_MAKETYPE(depth, dcn));
dst = _dst.getMat();
if( code == CV_HSV2BGR || code == CV_HSV2RGB || if( code == CV_HSV2BGR || code == CV_HSV2RGB ||
code == CV_HSV2BGR_FULL || code == CV_HSV2RGB_FULL ) code == CV_HSV2BGR_FULL || code == CV_HSV2RGB_FULL )
@ -2853,7 +2871,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
bool srgb = code == CV_BGR2Lab || code == CV_RGB2Lab || bool srgb = code == CV_BGR2Lab || code == CV_RGB2Lab ||
code == CV_BGR2Luv || code == CV_RGB2Luv; code == CV_BGR2Luv || code == CV_RGB2Luv;
dst.create(sz, CV_MAKETYPE(depth, 3)); _dst.create(sz, CV_MAKETYPE(depth, 3));
dst = _dst.getMat();
if( code == CV_BGR2Lab || code == CV_RGB2Lab || if( code == CV_BGR2Lab || code == CV_RGB2Lab ||
code == CV_LBGR2Lab || code == CV_LRGB2Lab ) code == CV_LBGR2Lab || code == CV_LRGB2Lab )
@ -2883,7 +2902,8 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
bool srgb = code == CV_Lab2BGR || code == CV_Lab2RGB || bool srgb = code == CV_Lab2BGR || code == CV_Lab2RGB ||
code == CV_Luv2BGR || code == CV_Luv2RGB; code == CV_Luv2BGR || code == CV_Luv2RGB;
dst.create(sz, CV_MAKETYPE(depth, dcn)); _dst.create(sz, CV_MAKETYPE(depth, dcn));
dst = _dst.getMat();
if( code == CV_Lab2BGR || code == CV_Lab2RGB || if( code == CV_Lab2BGR || code == CV_Lab2RGB ||
code == CV_Lab2LBGR || code == CV_Lab2LRGB ) code == CV_Lab2LBGR || code == CV_Lab2LRGB )
@ -2906,7 +2926,10 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
case CV_BayerBG2GRAY: case CV_BayerGB2GRAY: case CV_BayerRG2GRAY: case CV_BayerGR2GRAY: case CV_BayerBG2GRAY: case CV_BayerGB2GRAY: case CV_BayerRG2GRAY: case CV_BayerGR2GRAY:
if(dcn <= 0) dcn = 1; if(dcn <= 0) dcn = 1;
CV_Assert( scn == 1 && dcn == 1 && depth == CV_8U ); CV_Assert( scn == 1 && dcn == 1 && depth == CV_8U );
dst.create(sz, depth);
_dst.create(sz, depth);
dst = _dst.getMat();
Bayer2Gray_8u(src, dst, code); Bayer2Gray_8u(src, dst, code);
break; break;
@ -2914,7 +2937,9 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
case CV_BayerBG2BGR_VNG: case CV_BayerGB2BGR_VNG: case CV_BayerRG2BGR_VNG: case CV_BayerGR2BGR_VNG: case CV_BayerBG2BGR_VNG: case CV_BayerGB2BGR_VNG: case CV_BayerRG2BGR_VNG: case CV_BayerGR2BGR_VNG:
if(dcn <= 0) dcn = 3; if(dcn <= 0) dcn = 3;
CV_Assert( scn == 1 && dcn == 3 && depth == CV_8U ); CV_Assert( scn == 1 && dcn == 3 && depth == CV_8U );
dst.create(sz, CV_MAKETYPE(depth, dcn));
_dst.create(sz, CV_MAKETYPE(depth, dcn));
dst = _dst.getMat();
if( code == CV_BayerBG2BGR || code == CV_BayerGB2BGR || if( code == CV_BayerBG2BGR || code == CV_BayerGB2BGR ||
code == CV_BayerRG2BGR || code == CV_BayerGR2BGR ) code == CV_BayerRG2BGR || code == CV_BayerGR2BGR )
@ -2927,8 +2952,6 @@ void cvtColor( const Mat& src, Mat& dst, int code, int dcn )
} }
} }
}
CV_IMPL void CV_IMPL void
cvCvtColor( const CvArr* srcarr, CvArr* dstarr, int code ) cvCvtColor( const CvArr* srcarr, CvArr* dstarr, int code )
{ {

250
modules/imgproc/src/contours.cpp
Unescape View File

@ -1469,37 +1469,40 @@ cvFindContours( void* img, CvMemStorage* storage,
return count; return count;
} }
namespace cv void cv::findContours( const InputOutputArray _image, OutputArrayOfArrays _contours,
{ OutputArray _hierarchy, int mode, int method, Point offset )
static void
_findContours( Mat& image, vector<vector<Point> >& contours,
vector<Vec4i>* hierarchy, int mode, int method, Point offset )
{ {
Mat image = _image.getMat();
MemStorage storage(cvCreateMemStorage()); MemStorage storage(cvCreateMemStorage());
CvMat _image = image; CvMat _cimage = image;
CvSeq* _contours = 0; CvSeq* _ccontours = 0;
if( hierarchy ) if( _hierarchy.needed() )
hierarchy->clear(); _hierarchy.clear();
cvFindContours(&_image, storage, &_contours, sizeof(CvContour), mode, method, offset); cvFindContours(&_cimage, storage, &_ccontours, sizeof(CvContour), mode, method, offset);
if( !_contours ) if( !_ccontours )
{ {
contours.clear(); _contours.clear();
return; return;
} }
Seq<CvSeq*> all_contours(cvTreeToNodeSeq( _contours, sizeof(CvSeq), storage )); Seq<CvSeq*> all_contours(cvTreeToNodeSeq( _ccontours, sizeof(CvSeq), storage ));
size_t i, total = all_contours.size(); size_t i, total = all_contours.size();
contours.resize(total); _contours.create(total, 1, 0, -1, true);
SeqIterator<CvSeq*> it = all_contours.begin(); SeqIterator<CvSeq*> it = all_contours.begin();
for( i = 0; i < total; i++, ++it ) for( i = 0; i < total; i++, ++it )
{ {
CvSeq* c = *it; CvSeq* c = *it;
((CvContour*)c)->color = (int)i; ((CvContour*)c)->color = (int)i;
Seq<Point>(c).copyTo(contours[i]); _contours.create(c->total, 1, CV_32SC2, i, true);
Mat ci = _contours.getMat(i);
CV_Assert( ci.isContinuous() );
cvCvtSeqToArray(c, ci.data);
} }
if( hierarchy ) if( _hierarchy.needed() )
{ {
hierarchy->resize(total); _hierarchy.create(1, total, CV_32SC4, -1, true);
Vec4i* hierarchy = _hierarchy.getMat().ptr<Vec4i>();
it = all_contours.begin(); it = all_contours.begin();
for( i = 0; i < total; i++, ++it ) for( i = 0; i < total; i++, ++it )
{ {
@ -1508,62 +1511,57 @@ _findContours( Mat& image, vector<vector<Point> >& contours,
int h_prev = c->h_prev ? ((CvContour*)c->h_prev)->color : -1; int h_prev = c->h_prev ? ((CvContour*)c->h_prev)->color : -1;
int v_next = c->v_next ? ((CvContour*)c->v_next)->color : -1; int v_next = c->v_next ? ((CvContour*)c->v_next)->color : -1;
int v_prev = c->v_prev ? ((CvContour*)c->v_prev)->color : -1; int v_prev = c->v_prev ? ((CvContour*)c->v_prev)->color : -1;
(*hierarchy)[i] = Vec4i(h_next, h_prev, v_next, v_prev); hierarchy[i] = Vec4i(h_next, h_prev, v_next, v_prev);
}
} }
} }
} }
void cv::findContours( Mat& image, vector<vector<Point> >& contours, void cv::findContours( InputOutputArray _image, OutputArrayOfArrays _contours,
vector<Vec4i>& hierarchy, int mode, int method, Point offset )
{
_findContours(image, contours, &hierarchy, mode, method, offset);
}
void cv::findContours( Mat& image, vector<vector<Point> >& contours,
int mode, int method, Point offset) int mode, int method, Point offset)
{ {
_findContours(image, contours, 0, mode, method, offset); findContours(_image, _contours, OutputArrayOfArrays(), mode, method, offset);
} }
namespace cv namespace cv
{ {
static void addChildContour(const vector<vector<Point> >& contours, static void addChildContour(const InputArrayOfArrays& contours,
const vector<Vec4i>& hierarchy, size_t ncontours,
const Vec4i* hierarchy,
int i, vector<CvSeq>& seq, int i, vector<CvSeq>& seq,
vector<CvSeqBlock>& block) vector<CvSeqBlock>& block)
{ {
size_t count = contours.size();
for( ; i >= 0; i = hierarchy[i][0] ) for( ; i >= 0; i = hierarchy[i][0] )
{ {
const vector<Point>& ci = contours[i]; Mat ci = contours.getMat(i);
cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point), cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
!ci.empty() ? (void*)&ci[0] : 0, (int)ci.size(), !ci.empty() ? (void*)ci.data : 0, (int)ci.total(),
&seq[i], &block[i] ); &seq[i], &block[i] );
int h_next = hierarchy[i][0], h_prev = hierarchy[i][1], int h_next = hierarchy[i][0], h_prev = hierarchy[i][1],
v_next = hierarchy[i][2], v_prev = hierarchy[i][3]; v_next = hierarchy[i][2], v_prev = hierarchy[i][3];
seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0; seq[i].h_next = (size_t)h_next < ncontours ? &seq[h_next] : 0;
seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0; seq[i].h_prev = (size_t)h_prev < ncontours ? &seq[h_prev] : 0;
seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0; seq[i].v_next = (size_t)v_next < ncontours ? &seq[v_next] : 0;
seq[i].v_prev = (size_t)v_prev < count ? &seq[v_prev] : 0; seq[i].v_prev = (size_t)v_prev < ncontours ? &seq[v_prev] : 0;
if( v_next >= 0 ) if( v_next >= 0 )
addChildContour(contours, hierarchy, v_next, seq, block); addChildContour(contours, ncontours, hierarchy, v_next, seq, block);
} }
} }
} }
void cv::drawContours( Mat& image, const vector<vector<Point> >& contours, void cv::drawContours( InputOutputArray _image, const InputArrayOfArrays& _contours,
int contourIdx, const Scalar& color, int thickness, int contourIdx, const Scalar& color, int thickness,
int lineType, const vector<Vec4i>& hierarchy, int lineType, const InputArray& _hierarchy,
int maxLevel, Point offset ) int maxLevel, Point offset )
{ {
CvMat _image = image; Mat image = _image.getMat(), hierarchy = _hierarchy.getMat();
CvMat _cimage = image;
size_t i = 0, first = 0, last = contours.size(); size_t ncontours = _contours.total();
size_t i = 0, first = 0, last = ncontours;
vector<CvSeq> seq; vector<CvSeq> seq;
vector<CvSeqBlock> block; vector<CvSeqBlock> block;
@ -1585,9 +1583,13 @@ void cv::drawContours( Mat& image, const vector<vector<Point> >& contours,
for( i = first; i < last; i++ ) for( i = first; i < last; i++ )
{ {
const vector<Point>& ci = contours[i]; Mat ci = _contours.getMat(i);
if( ci.empty() )
continue;
int npoints = ci.checkVector(2, CV_32S);
CV_Assert( npoints > 0 );
cvMakeSeqHeaderForArray( CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point), cvMakeSeqHeaderForArray( CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
!ci.empty() ? (void*)&ci[0] : 0, (int)ci.size(), &seq[i], &block[i] ); ci.data, npoints, &seq[i], &block[i] );
} }
if( hierarchy.empty() || maxLevel == 0 ) if( hierarchy.empty() || maxLevel == 0 )
@ -1599,13 +1601,15 @@ void cv::drawContours( Mat& image, const vector<vector<Point> >& contours,
else else
{ {
size_t count = last - first; size_t count = last - first;
CV_Assert(hierarchy.size() == contours.size()); CV_Assert(hierarchy.total() == ncontours && hierarchy.type() == CV_32SC4 );
if( count == contours.size() ) const Vec4i* h = hierarchy.ptr<Vec4i>();
if( count == ncontours )
{ {
for( i = first; i < last; i++ ) for( i = first; i < last; i++ )
{ {
int h_next = hierarchy[i][0], h_prev = hierarchy[i][1], int h_next = h[i][0], h_prev = h[i][1],
v_next = hierarchy[i][2], v_prev = hierarchy[i][3]; v_next = h[i][2], v_prev = h[i][3];
seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0; seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0;
seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0; seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0;
seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0; seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0;
@ -1614,85 +1618,88 @@ void cv::drawContours( Mat& image, const vector<vector<Point> >& contours,
} }
else else
{ {
int child = hierarchy[first][2]; int child = h[first][2];
if( child >= 0 ) if( child >= 0 )
{ {
addChildContour(contours, hierarchy, child, seq, block); addChildContour(_contours, ncontours, h, child, seq, block);
seq[first].v_next = &seq[child]; seq[first].v_next = &seq[child];
} }
} }
} }
cvDrawContours( &_image, &seq[first], color, color, contourIdx >= 0 ? cvDrawContours( &_cimage, &seq[first], color, color, contourIdx >= 0 ?
-maxLevel : maxLevel, thickness, lineType, offset ); -maxLevel : maxLevel, thickness, lineType, offset );
} }
void cv::approxPolyDP( const Mat& curve, vector<Point>& approxCurve, void cv::approxPolyDP( const InputArray& _curve, OutputArray _approxCurve,
double epsilon, bool closed ) double epsilon, bool closed )
{ {
CV_Assert(curve.checkVector(2, CV_32S) >= 0); Mat curve = _curve.getMat();
CvMat _curve = curve; int npoints = curve.checkVector(2), depth = curve.depth();
CV_Assert( npoints >= 0 && (depth == CV_32S || depth == CV_32F));
CvMat _ccurve = curve;
MemStorage storage(cvCreateMemStorage()); MemStorage storage(cvCreateMemStorage());
Seq<Point> seq(cvApproxPoly(&_curve, sizeof(CvContour), storage, CV_POLY_APPROX_DP, epsilon, closed)); CvSeq* result = cvApproxPoly(&_ccurve, sizeof(CvContour), storage, CV_POLY_APPROX_DP, epsilon, closed);
seq.copyTo(approxCurve); if( result->total > 0 )
}
void cv::approxPolyDP( const Mat& curve, vector<Point2f>& approxCurve,
double epsilon, bool closed )
{ {
CV_Assert(curve.checkVector(2, CV_32F) >= 0); _approxCurve.create(result->total, 1, CV_MAKETYPE(curve.depth(), 2), -1, true);
CvMat _curve = curve; cvCvtSeqToArray(result, _approxCurve.getMat().data );
MemStorage storage(cvCreateMemStorage());
Seq<Point2f> seq(cvApproxPoly(&_curve, sizeof(CvContour), storage, CV_POLY_APPROX_DP, epsilon, closed));
seq.copyTo(approxCurve);
} }
}
double cv::arcLength( const Mat& curve, bool closed ) double cv::arcLength( const InputArray& _curve, bool closed )
{ {
Mat curve = _curve.getMat();
CV_Assert(curve.checkVector(2) >= 0 && (curve.depth() == CV_32F || curve.depth() == CV_32S)); CV_Assert(curve.checkVector(2) >= 0 && (curve.depth() == CV_32F || curve.depth() == CV_32S));
CvMat _curve = curve; CvMat _ccurve = curve;
return cvArcLength(&_curve, CV_WHOLE_SEQ, closed); return cvArcLength(&_ccurve, CV_WHOLE_SEQ, closed);
} }
cv::Rect cv::boundingRect( const Mat& points ) cv::Rect cv::boundingRect( const InputArray& _points )
{ {
Mat points = _points.getMat();
CV_Assert(points.checkVector(2) >= 0 && (points.depth() == CV_32F || points.depth() == CV_32S)); CV_Assert(points.checkVector(2) >= 0 && (points.depth() == CV_32F || points.depth() == CV_32S));
CvMat _points = points; CvMat _cpoints = points;
return cvBoundingRect(&_points, 0); return cvBoundingRect(&_cpoints, 0);
} }
double cv::contourArea( const Mat& contour, bool oriented ) double cv::contourArea( const InputArray& _contour, bool oriented )
{ {
Mat contour = _contour.getMat();
CV_Assert(contour.checkVector(2) >= 0 && (contour.depth() == CV_32F || contour.depth() == CV_32S)); CV_Assert(contour.checkVector(2) >= 0 && (contour.depth() == CV_32F || contour.depth() == CV_32S));
CvMat _contour = contour; CvMat _ccontour = contour;
return cvContourArea(&_contour, CV_WHOLE_SEQ, oriented); return cvContourArea(&_ccontour, CV_WHOLE_SEQ, oriented);
} }
cv::RotatedRect cv::minAreaRect( const Mat& points ) cv::RotatedRect cv::minAreaRect( const InputArray& _points )
{ {
Mat points = _points.getMat();
CV_Assert(points.checkVector(2) >= 0 && (points.depth() == CV_32F || points.depth() == CV_32S)); CV_Assert(points.checkVector(2) >= 0 && (points.depth() == CV_32F || points.depth() == CV_32S));
CvMat _points = points; CvMat _cpoints = points;
return cvMinAreaRect2(&_points, 0); return cvMinAreaRect2(&_cpoints, 0);
} }
void cv::minEnclosingCircle( const Mat& points, void cv::minEnclosingCircle( const InputArray& _points,
Point2f& center, float& radius ) Point2f& center, float& radius )
{ {
Mat points = _points.getMat();
CV_Assert(points.checkVector(2) >= 0 && (points.depth() == CV_32F || points.depth() == CV_32S)); CV_Assert(points.checkVector(2) >= 0 && (points.depth() == CV_32F || points.depth() == CV_32S));
CvMat _points = points; CvMat _cpoints = points;
cvMinEnclosingCircle( &_points, (CvPoint2D32f*)&center, &radius ); cvMinEnclosingCircle( &_cpoints, (CvPoint2D32f*)&center, &radius );
} }
double cv::matchShapes( const Mat& contour1, double cv::matchShapes( const InputArray& _contour1,
const Mat& contour2, const InputArray& _contour2,
int method, double parameter ) int method, double parameter )
{ {
Mat contour1 = _contour1.getMat(), contour2 = _contour2.getMat();
CV_Assert(contour1.checkVector(2) >= 0 && contour2.checkVector(2) >= 0 && CV_Assert(contour1.checkVector(2) >= 0 && contour2.checkVector(2) >= 0 &&
(contour1.depth() == CV_32F || contour1.depth() == CV_32S) && (contour1.depth() == CV_32F || contour1.depth() == CV_32S) &&
contour1.depth() == contour2.depth()); contour1.depth() == contour2.depth());
@ -1702,79 +1709,68 @@ double cv::matchShapes( const Mat& contour1,
} }
void cv::convexHull( const Mat& points, vector<int>& hull, bool clockwise ) void cv::convexHull( const InputArray& _points, OutputArray _hull, bool clockwise, bool returnPoints )
{ {
int nelems = points.checkVector(2); Mat points = _points.getMat();
CV_Assert(nelems >= 0 && (points.depth() == CV_32F || points.depth() == CV_32S)); int nelems = points.checkVector(2), depth = points.depth();
hull.resize(nelems); CV_Assert(nelems >= 0 && (depth == CV_32F || depth == CV_32S));
CvMat _points = Mat(points), _hull=Mat(hull);
cvConvexHull2(&_points, &_hull, clockwise ? CV_CLOCKWISE : CV_COUNTER_CLOCKWISE, 0);
hull.resize(_hull.cols + _hull.rows - 1);
}
void cv::convexHull( const Mat& points, if( nelems == 0 )
vector<Point>& hull, bool clockwise )
{ {
int nelems = points.checkVector(2, CV_32S); _hull.release();
CV_Assert(nelems >= 0); return;
hull.resize(nelems);
CvMat _points = Mat(points), _hull=Mat(hull);
cvConvexHull2(&_points, &_hull, clockwise ? CV_CLOCKWISE : CV_COUNTER_CLOCKWISE, 1);
hull.resize(_hull.cols + _hull.rows - 1);
} }
returnPoints = !_hull.fixedType() ? returnPoints : _hull.type() != CV_32S;
void cv::convexHull( const Mat& points, Mat hull(nelems, 1, returnPoints ? CV_MAKETYPE(depth, 2) : CV_32S);
vector<Point2f>& hull, bool clockwise ) CvMat _cpoints = points, _chull = hull;
{ cvConvexHull2(&_cpoints, &_chull, clockwise ? CV_CLOCKWISE : CV_COUNTER_CLOCKWISE, returnPoints);
int nelems = points.checkVector(2, CV_32F); _hull.create(_chull.rows, 1, hull.type(), -1, true);
CV_Assert(nelems >= 0); Mat dhull = _hull.getMat(), shull(dhull.size(), dhull.type(), hull.data);
hull.resize(nelems); shull.copyTo(dhull);
CvMat _points = Mat(points), _hull=Mat(hull);
cvConvexHull2(&_points, &_hull, clockwise ? CV_CLOCKWISE : CV_COUNTER_CLOCKWISE, 1);
hull.resize(_hull.cols + _hull.rows - 1);
} }
bool cv::isContourConvex( const Mat& contour ) bool cv::isContourConvex( const InputArray& _contour )
{ {
Mat contour = _contour.getMat();
CV_Assert(contour.checkVector(2) >= 0 && CV_Assert(contour.checkVector(2) >= 0 &&
(contour.depth() == CV_32F || contour.depth() == CV_32S)); (contour.depth() == CV_32F || contour.depth() == CV_32S));
CvMat c = Mat(contour); CvMat c = Mat(contour);
return cvCheckContourConvexity(&c) > 0; return cvCheckContourConvexity(&c) > 0;
} }
cv::RotatedRect cv::fitEllipse( const Mat& points ) cv::RotatedRect cv::fitEllipse( const InputArray& _points )
{ {
Mat points = _points.getMat();
CV_Assert(points.checkVector(2) >= 0 && CV_Assert(points.checkVector(2) >= 0 &&
(points.depth() == CV_32F || points.depth() == CV_32S)); (points.depth() == CV_32F || points.depth() == CV_32S));
CvMat _points = points; CvMat _cpoints = points;
return cvFitEllipse2(&_points); return cvFitEllipse2(&_cpoints);
} }
void cv::fitLine( const Mat& points, Vec4f& line, int distType, void cv::fitLine( const InputArray& _points, OutputArray _line, int distType,
double param, double reps, double aeps ) double param, double reps, double aeps )
{ {
CV_Assert(points.checkVector(2) >= 0 && Mat points = _points.getMat();
(points.depth() == CV_32F || points.depth() == CV_32S)); bool is3d = points.checkVector(3) >= 0, is2d = is3d ? false : points.checkVector(2) >= 0;
CvMat _points = points;
cvFitLine(&_points, distType, param, reps, aeps, &line[0]);
}
CV_Assert((is2d || is3d) && (points.depth() == CV_32F || points.depth() == CV_32S));
CvMat _cpoints = points;
float line[6];
cvFitLine(&_cpoints, distType, param, reps, aeps, &line[0]);
void cv::fitLine( const Mat& points, Vec6f& line, int distType, _line.create(is2d ? 4 : 6, 1, CV_32F, -1, true);
double param, double reps, double aeps ) Mat l = _line.getMat();
{ CV_Assert( l.isContinuous() );
CV_Assert(points.checkVector(3) >= 0 && memcpy( l.data, line, (is2d ? 4 : 6)*sizeof(line[0]) );
(points.depth() == CV_32F || points.depth() == CV_32S));
CvMat _points = points;
cvFitLine(&_points, distType, param, reps, aeps, &line[0]);
} }
double cv::pointPolygonTest( const Mat& contour,
double cv::pointPolygonTest( const InputArray& _contour,
Point2f pt, bool measureDist ) Point2f pt, bool measureDist )
{ {
Mat contour = _contour.getMat();
CV_Assert(contour.checkVector(2) >= 0 && CV_Assert(contour.checkVector(2) >= 0 &&
(contour.depth() == CV_32F || contour.depth() == CV_32S)); (contour.depth() == CV_32F || contour.depth() == CV_32S));
CvMat c = Mat(contour); CvMat c = Mat(contour);

34
modules/imgproc/src/corner.cpp
Unescape View File

@ -297,35 +297,46 @@ cornerEigenValsVecs( const Mat& src, Mat& eigenv, int block_size,
calcEigenValsVecs( cov, eigenv ); calcEigenValsVecs( cov, eigenv );
} }
}
void cornerMinEigenVal( const Mat& src, Mat& dst, int blockSize, int ksize, int borderType ) void cv::cornerMinEigenVal( const InputArray& _src, OutputArray _dst, int blockSize, int ksize, int borderType )
{ {
dst.create( src.size(), CV_32F ); Mat src = _src.getMat();
_dst.create( src.size(), CV_32F );
Mat dst = _dst.getMat();
cornerEigenValsVecs( src, dst, blockSize, ksize, MINEIGENVAL, 0, borderType ); cornerEigenValsVecs( src, dst, blockSize, ksize, MINEIGENVAL, 0, borderType );
} }
void cornerHarris( const Mat& src, Mat& dst, int blockSize, int ksize, double k, int borderType ) void cv::cornerHarris( const InputArray& _src, OutputArray _dst, int blockSize, int ksize, double k, int borderType )
{ {
dst.create( src.size(), CV_32F ); Mat src = _src.getMat();
_dst.create( src.size(), CV_32F );
Mat dst = _dst.getMat();
cornerEigenValsVecs( src, dst, blockSize, ksize, HARRIS, k, borderType ); cornerEigenValsVecs( src, dst, blockSize, ksize, HARRIS, k, borderType );
} }
void cornerEigenValsAndVecs( const Mat& src, Mat& dst, int blockSize, int ksize, int borderType ) void cv::cornerEigenValsAndVecs( const InputArray& _src, OutputArray _dst, int blockSize, int ksize, int borderType )
{ {
if( dst.rows != src.rows || dst.cols*dst.channels() != src.cols*6 || dst.depth() != CV_32F ) Mat src = _src.getMat();
dst.create( src.size(), CV_32FC(6) ); Size dsz = _dst.size();
int dtype = _dst.type();
if( dsz.height != src.rows || dsz.width*CV_MAT_CN(dtype) != src.cols*6 || CV_MAT_DEPTH(dtype) != CV_32F )
_dst.create( src.size(), CV_32FC(6) );
Mat dst = _dst.getMat();
cornerEigenValsVecs( src, dst, blockSize, ksize, EIGENVALSVECS, 0, borderType ); cornerEigenValsVecs( src, dst, blockSize, ksize, EIGENVALSVECS, 0, borderType );
} }
void preCornerDetect( const Mat& src, Mat& dst, int ksize, int borderType ) void cv::preCornerDetect( const InputArray& _src, OutputArray _dst, int ksize, int borderType )
{ {
Mat Dx, Dy, D2x, D2y, Dxy; Mat Dx, Dy, D2x, D2y, Dxy, src = _src.getMat();
CV_Assert( src.type() == CV_8UC1 || src.type() == CV_32FC1 ); CV_Assert( src.type() == CV_8UC1 || src.type() == CV_32FC1 );
dst.create( src.size(), CV_32F ); _dst.create( src.size(), CV_32F );
Mat dst = _dst.getMat();
Sobel( src, Dx, CV_32F, 1, 0, ksize, 1, 0, borderType ); Sobel( src, Dx, CV_32F, 1, 0, ksize, 1, 0, borderType );
Sobel( src, Dy, CV_32F, 0, 1, ksize, 1, 0, borderType ); Sobel( src, Dy, CV_32F, 0, 1, ksize, 1, 0, borderType );
@ -358,9 +369,6 @@ void preCornerDetect( const Mat& src, Mat& dst, int ksize, int borderType )
} }
} }
}
CV_IMPL void CV_IMPL void
cvCornerMinEigenVal( const CvArr* srcarr, CvArr* dstarr, cvCornerMinEigenVal( const CvArr* srcarr, CvArr* dstarr,
int block_size, int aperture_size ) int block_size, int aperture_size )

10
modules/imgproc/src/cornersubpix.cpp
Unescape View File

@ -254,12 +254,16 @@ cvFindCornerSubPix( const void* srcarr, CvPoint2D32f* corners,
} }
} }
void cv::cornerSubPix( const Mat& image, vector<Point2f>& corners, void cv::cornerSubPix( const InputArray& _image, InputOutputArray _corners,
Size winSize, Size zeroZone, Size winSize, Size zeroZone,
TermCriteria criteria ) TermCriteria criteria )
{ {
CvMat _image = image; Mat corners = _corners.getMat();
cvFindCornerSubPix(&_image, (CvPoint2D32f*)&corners[0], (int)corners.size(), int ncorners = corners.checkVector(2);
CV_Assert( ncorners >= 0 && corners.depth() == CV_32F );
CvMat c_image = _image.getMat();
cvFindCornerSubPix( &c_image, (CvPoint2D32f*)corners.data, ncorners,
winSize, zeroZone, criteria ); winSize, zeroZone, criteria );
} }

61
modules/imgproc/src/deriv.cpp
Unescape View File

@ -111,16 +111,16 @@ void icvSepConvSmall3_32f( float* src, int src_step, float* dst, int dst_step,
namespace cv namespace cv
{ {
static void getScharrKernels( Mat& kx, Mat& ky, int dx, int dy, bool normalize, int ktype ) static void getScharrKernels( OutputArray _kx, OutputArray _ky,
int dx, int dy, bool normalize, int ktype )
{ {
const int ksize = 3; const int ksize = 3;
CV_Assert( ktype == CV_32F || ktype == CV_64F ); CV_Assert( ktype == CV_32F || ktype == CV_64F );
_kx.create(ksize, 1, ktype, -1, true);
if( kx.cols != ksize || kx.rows != 1 || kx.type() != ktype ) _ky.create(ksize, 1, ktype, -1, true);
kx.create( ksize, 1, ktype ); Mat kx = _kx.getMat();
if( ky.cols != ksize || ky.rows != 1 || ky.type() != ktype ) Mat ky = _ky.getMat();
ky.create( ksize, 1, ktype );
CV_Assert( dx >= 0 && dy >= 0 && dx+dy == 1 ); CV_Assert( dx >= 0 && dy >= 0 && dx+dy == 1 );
@ -142,7 +142,8 @@ static void getScharrKernels( Mat& kx, Mat& ky, int dx, int dy, bool normalize,
} }
static void getSobelKernels( Mat& kx, Mat& ky, int dx, int dy, int _ksize, bool normalize, int ktype ) static void getSobelKernels( OutputArray _kx, OutputArray _ky,
int dx, int dy, int _ksize, bool normalize, int ktype )
{ {
int i, j, ksizeX = _ksize, ksizeY = _ksize; int i, j, ksizeX = _ksize, ksizeY = _ksize;
if( ksizeX == 1 && dx > 0 ) if( ksizeX == 1 && dx > 0 )
@ -152,10 +153,10 @@ static void getSobelKernels( Mat& kx, Mat& ky, int dx, int dy, int _ksize, bool
CV_Assert( ktype == CV_32F || ktype == CV_64F ); CV_Assert( ktype == CV_32F || ktype == CV_64F );
if( kx.cols != ksizeX || kx.rows != 1 || kx.type() != ktype ) _kx.create(ksizeX, 1, ktype, -1, true);
kx.create( ksizeX, 1, ktype ); _ky.create(ksizeY, 1, ktype, -1, true);
if( ky.cols != ksizeY || ky.rows != 1 || ky.type() != ktype ) Mat kx = _kx.getMat();
ky.create( ksizeY, 1, ktype ); Mat ky = _ky.getMat();
if( _ksize % 2 == 0 || _ksize > 31 ) if( _ksize % 2 == 0 || _ksize > 31 )
CV_Error( CV_StsOutOfRange, "The kernel size must be odd and not larger than 31" ); CV_Error( CV_StsOutOfRange, "The kernel size must be odd and not larger than 31" );
@ -218,8 +219,9 @@ static void getSobelKernels( Mat& kx, Mat& ky, int dx, int dy, int _ksize, bool
} }
} }
}
void getDerivKernels( Mat& kx, Mat& ky, int dx, int dy, void cv::getDerivKernels( OutputArray kx, OutputArray ky, int dx, int dy,
int ksize, bool normalize, int ktype ) int ksize, bool normalize, int ktype )
{ {
if( ksize <= 0 ) if( ksize <= 0 )
@ -229,7 +231,7 @@ void getDerivKernels( Mat& kx, Mat& ky, int dx, int dy,
} }
Ptr<FilterEngine> createDerivFilter(int srcType, int dstType, cv::Ptr<cv::FilterEngine> cv::createDerivFilter(int srcType, int dstType,
int dx, int dy, int ksize, int borderType ) int dx, int dy, int ksize, int borderType )
{ {
Mat kx, ky; Mat kx, ky;
@ -238,9 +240,11 @@ Ptr<FilterEngine> createDerivFilter(int srcType, int dstType,
kx, ky, Point(-1,-1), 0, borderType ); kx, ky, Point(-1,-1), 0, borderType );
} }
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7) #if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
namespace cv
{
static bool IPPDerivScharr(const Mat& src, Mat& dst, int ddepth, int dx, int dy, double scale) static bool IPPDerivScharr(const Mat& src, Mat& dst, int ddepth, int dx, int dy, double scale)
{ {
int bufSize = 0; int bufSize = 0;
@ -346,8 +350,6 @@ static bool IPPDeriv(const Mat& src, Mat& dst, int ddepth, int dx, int dy, int k
if( ddepth < 0 ) if( ddepth < 0 )
ddepth = src.depth(); ddepth = src.depth();
dst.create( src.size(), CV_MAKETYPE(ddepth, src.channels()) );
if(src.type() == CV_8U && dst.type() == CV_16S && scale == 1) if(src.type() == CV_8U && dst.type() == CV_16S && scale == 1)
{ {
if((dx == 1) && (dy == 0)) if((dx == 1) && (dy == 0))
@ -462,19 +464,23 @@ static bool IPPDeriv(const Mat& src, Mat& dst, int ddepth, int dx, int dy, int k
return IPPDerivScharr(src, dst, ddepth, dx, dy, scale); return IPPDerivScharr(src, dst, ddepth, dx, dy, scale);
return false; return false;
}
} }
#endif #endif
void cv::Sobel( const InputArray& _src, OutputArray _dst, int ddepth, int dx, int dy,
void Sobel( const Mat& src, Mat& dst, int ddepth, int dx, int dy,
int ksize, double scale, double delta, int borderType ) int ksize, double scale, double delta, int borderType )
{ {
Mat src = _src.getMat();
_dst.create( src.size(), CV_MAKETYPE(ddepth, src.channels()) );
Mat dst = _dst.getMat();
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7) #if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
if(dx < 3 && dy < 3 && src.channels() == 1 && borderType == 1) if(dx < 3 && dy < 3 && src.channels() == 1 && borderType == 1)
{ {
if(IPPDeriv(src, dst, ddepth, dx, dy, ksize,scale) == true) if(IPPDeriv(src, dst, ddepth, dx, dy, ksize,scale))
return; return;
} }
#endif #endif
@ -495,13 +501,17 @@ void Sobel( const Mat& src, Mat& dst, int ddepth, int dx, int dy,
} }
void Scharr( const Mat& src, Mat& dst, int ddepth, int dx, int dy, void cv::Scharr( const InputArray& _src, OutputArray _dst, int ddepth, int dx, int dy,
double scale, double delta, int borderType ) double scale, double delta, int borderType )
{ {
Mat src = _src.getMat();
_dst.create( src.size(), CV_MAKETYPE(ddepth, src.channels()) );
Mat dst = _dst.getMat();
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7) #if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
if(dx < 2 && dy < 2 && src.channels() == 1 && borderType == 1) if(dx < 2 && dy < 2 && src.channels() == 1 && borderType == 1)
{ {
if(IPPDerivScharr(src, dst, ddepth, dx, dy, scale) == true) if(IPPDerivScharr(src, dst, ddepth, dx, dy, scale))
return; return;
} }
#endif #endif
@ -522,9 +532,13 @@ void Scharr( const Mat& src, Mat& dst, int ddepth, int dx, int dy,
} }
void Laplacian( const Mat& src, Mat& dst, int ddepth, int ksize, void cv::Laplacian( const InputArray& _src, OutputArray _dst, int ddepth, int ksize,
double scale, double delta, int borderType ) double scale, double delta, int borderType )
{ {
Mat src = _src.getMat();
_dst.create( src.size(), CV_MAKETYPE(ddepth, src.channels()) );
Mat dst = _dst.getMat();
if( ksize == 1 || ksize == 3 ) if( ksize == 1 || ksize == 3 )
{ {
float K[2][9] = float K[2][9] =
@ -548,7 +562,6 @@ void Laplacian( const Mat& src, Mat& dst, int ddepth, int ksize,
if( ddepth < 0 ) if( ddepth < 0 )
ddepth = src.depth(); ddepth = src.depth();
int dtype = CV_MAKETYPE(ddepth, src.channels()); int dtype = CV_MAKETYPE(ddepth, src.channels());
dst.create( src.size(), dtype );
int dy0 = std::min(std::max((int)(STRIPE_SIZE/(getElemSize(src.type())*src.cols)), 1), src.rows); int dy0 = std::min(std::max((int)(STRIPE_SIZE/(getElemSize(src.type())*src.cols)), 1), src.rows);
Ptr<FilterEngine> fx = createSeparableLinearFilter(src.type(), Ptr<FilterEngine> fx = createSeparableLinearFilter(src.type(),
@ -578,8 +591,6 @@ void Laplacian( const Mat& src, Mat& dst, int ddepth, int ksize,
} }
} }
}
///////////////////////////////////////////////////////////////////////////////////////// /////////////////////////////////////////////////////////////////////////////////////////
CV_IMPL void CV_IMPL void

21
modules/imgproc/src/distransform.cpp
Unescape View File

@ -850,21 +850,24 @@ cvDistTransform( const void* srcarr, void* dstarr,
} }
} }
void cv::distanceTransform( const Mat& src, Mat& dst, Mat& labels, void cv::distanceTransform( const InputArray& _src, OutputArray _dst, OutputArray _labels,
int distanceType, int maskSize ) int distanceType, int maskSize )
{ {
dst.create(src.size(), CV_32F); Mat src = _src.getMat();
labels.create(src.size(), CV_32S); _dst.create(src.size(), CV_32F);
CvMat _src = src, _dst = dst, _labels = labels; _labels.create(src.size(), CV_32S);
cvDistTransform(&_src, &_dst, distanceType, maskSize, 0, &_labels); CvMat c_src = src, c_dst = _dst.getMat(), c_labels = _labels.getMat();
cvDistTransform(&c_src, &c_dst, distanceType, maskSize, 0, &c_labels);
} }
void cv::distanceTransform( const Mat& src, Mat& dst, void cv::distanceTransform( const InputArray& _src, OutputArray _dst,
int distanceType, int maskSize ) int distanceType, int maskSize )
{ {
dst.create(src.size(), CV_32F); Mat src = _src.getMat();
CvMat _src = src, _dst = dst; _dst.create(src.size(), CV_32F);
cvDistTransform(&_src, &_dst, distanceType, maskSize, 0, 0); Mat dst = _dst.getMat();
CvMat c_src = src, c_dst = _dst.getMat();
cvDistTransform(&c_src, &c_dst, distanceType, maskSize, 0, 0);
} }
/* End of file. */ /* End of file. */

25
modules/imgproc/src/emd.cpp
Unescape View File

@ -1138,22 +1138,25 @@ icvDistC( const float *x, const float *y, void *user_param )
} }
namespace cv float cv::EMD( const InputArray& _signature1, const InputArray& _signature2,
int distType, const InputArray& _cost,
float* lowerBound, OutputArray _flow )
{ {
Mat signature1 = _signature1.getMat(), signature2 = _signature2.getMat();
Mat cost = _cost.getMat(), flow;
float EMD( const Mat& signature1, const Mat& signature2, CvMat _csignature1 = signature1;
int distType, const Mat& cost, float* lowerBound, Mat* flow ) CvMat _csignature2 = signature2;
CvMat _ccost = cost, _cflow;
if( _flow.needed() )
{ {
CvMat _signature1 = signature1; _flow.create((int)signature1.total(), (int)signature2.total(), CV_32F);
CvMat _signature2 = signature2; flow = _flow.getMat();
CvMat _cost = cost, _flow; _cflow = flow;
if( flow )
_flow = *flow;
return cvCalcEMD2( &_signature1, &_signature2, distType, 0, cost.empty() ? 0 : &_cost,
flow ? &_flow : 0, lowerBound, 0 );
} }
return cvCalcEMD2( &_csignature1, &_csignature2, distType, 0, cost.empty() ? 0 : &_ccost,
_flow.needed() ? &_cflow : 0, lowerBound, 0 );
} }
/* End of file. */ /* End of file. */

16
modules/imgproc/src/featureselect.cpp
Unescape View File

@ -50,13 +50,16 @@ template<typename T> struct greaterThanPtr
bool operator()(const T* a, const T* b) const { return *a > *b; } bool operator()(const T* a, const T* b) const { return *a > *b; }
}; };
void goodFeaturesToTrack( const Mat& image, vector<Point2f>& corners, }
void cv::goodFeaturesToTrack( const InputArray& _image, OutputArray _corners,
int maxCorners, double qualityLevel, double minDistance, int maxCorners, double qualityLevel, double minDistance,
const Mat& mask, int blockSize, const InputArray& _mask, int blockSize,
bool useHarrisDetector, double harrisK ) bool useHarrisDetector, double harrisK )
{ {
CV_Assert( qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0 ); Mat image = _image.getMat(), mask = _mask.getMat();
CV_Assert( qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0 );
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size()) ); CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size()) );
Mat eig, tmp; Mat eig, tmp;
@ -90,7 +93,7 @@ void goodFeaturesToTrack( const Mat& image, vector<Point2f>& corners,
} }
sort( tmpCorners, greaterThanPtr<float>() ); sort( tmpCorners, greaterThanPtr<float>() );
corners.clear(); vector<Point2f> corners;
size_t i, j, total = tmpCorners.size(), ncorners = 0; size_t i, j, total = tmpCorners.size(), ncorners = 0;
if(minDistance >= 1) if(minDistance >= 1)
@ -182,6 +185,9 @@ void goodFeaturesToTrack( const Mat& image, vector<Point2f>& corners,
break; break;
} }
} }
Mat(corners).convertTo(_corners, _corners.fixedType() ? _corners.type() : CV_32F);
/* /*
for( i = 0; i < total; i++ ) for( i = 0; i < total; i++ )
{ {
@ -210,8 +216,6 @@ void goodFeaturesToTrack( const Mat& image, vector<Point2f>& corners,
*/ */
} }
}
CV_IMPL void CV_IMPL void
cvGoodFeaturesToTrack( const void* _image, void*, void*, cvGoodFeaturesToTrack( const void* _image, void*, void*,
CvPoint2D32f* _corners, int *_corner_count, CvPoint2D32f* _corners, int *_corner_count,

87
modules/imgproc/src/filter.cpp
Unescape View File

@ -46,20 +46,6 @@
Base Image Filter Base Image Filter
\****************************************************************************************/ \****************************************************************************************/
namespace cv
{
BaseRowFilter::BaseRowFilter() { ksize = anchor = -1; }
BaseRowFilter::~BaseRowFilter() {}
BaseColumnFilter::BaseColumnFilter() { ksize = anchor = -1; }
BaseColumnFilter::~BaseColumnFilter() {}
void BaseColumnFilter::reset() {}
BaseFilter::BaseFilter() { ksize = Size(-1,-1); anchor = Point(-1,-1); }
BaseFilter::~BaseFilter() {}
void BaseFilter::reset() {}
/* /*
Various border types, image boundaries are denoted with '|' Various border types, image boundaries are denoted with '|'
@ -69,7 +55,7 @@ void BaseFilter::reset() {}
* BORDER_WRAP: cdefgh|abcdefgh|abcdefg * BORDER_WRAP: cdefgh|abcdefgh|abcdefg
* BORDER_CONSTANT: iiiiii|abcdefgh|iiiiiii with some specified 'i' * BORDER_CONSTANT: iiiiii|abcdefgh|iiiiiii with some specified 'i'
*/ */
int borderInterpolate( int p, int len, int borderType ) int cv::borderInterpolate( int p, int len, int borderType )
{ {
if( (unsigned)p < (unsigned)len ) if( (unsigned)p < (unsigned)len )
; ;
@ -104,6 +90,20 @@ int borderInterpolate( int p, int len, int borderType )
} }
namespace cv
{
BaseRowFilter::BaseRowFilter() { ksize = anchor = -1; }
BaseRowFilter::~BaseRowFilter() {}
BaseColumnFilter::BaseColumnFilter() { ksize = anchor = -1; }
BaseColumnFilter::~BaseColumnFilter() {}
void BaseColumnFilter::reset() {}
BaseFilter::BaseFilter() { ksize = Size(-1,-1); anchor = Point(-1,-1); }
BaseFilter::~BaseFilter() {}
void BaseFilter::reset() {}
FilterEngine::FilterEngine() FilterEngine::FilterEngine()
{ {
srcType = dstType = bufType = -1; srcType = dstType = bufType = -1;
@ -454,13 +454,15 @@ void FilterEngine::apply(const Mat& src, Mat& dst,
dst.data + dstOfs.y*dst.step + dstOfs.x*dst.elemSize(), (int)dst.step ); dst.data + dstOfs.y*dst.step + dstOfs.x*dst.elemSize(), (int)dst.step );
} }
}
/****************************************************************************************\ /****************************************************************************************\
* Separable linear filter * * Separable linear filter *
\****************************************************************************************/ \****************************************************************************************/
int getKernelType(const Mat& _kernel, Point anchor) int cv::getKernelType(const InputArray& __kernel, Point anchor)
{ {
Mat _kernel = __kernel.getMat();
CV_Assert( _kernel.channels() == 1 ); CV_Assert( _kernel.channels() == 1 );
int i, sz = _kernel.rows*_kernel.cols; int i, sz = _kernel.rows*_kernel.cols;
@ -495,6 +497,9 @@ int getKernelType(const Mat& _kernel, Point anchor)
} }
namespace cv
{
struct RowNoVec struct RowNoVec
{ {
RowNoVec() {} RowNoVec() {}
@ -2527,10 +2532,13 @@ template<typename ST, typename DT> struct FixedPtCastEx
int SHIFT, DELTA; int SHIFT, DELTA;
}; };
Ptr<BaseRowFilter> getLinearRowFilter( int srcType, int bufType, }
const Mat& kernel, int anchor,
cv::Ptr<cv::BaseRowFilter> cv::getLinearRowFilter( int srcType, int bufType,
const InputArray& _kernel, int anchor,
int symmetryType ) int symmetryType )
{ {
Mat kernel = _kernel.getMat();
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(bufType); int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(bufType);
int cn = CV_MAT_CN(srcType); int cn = CV_MAT_CN(srcType);
CV_Assert( cn == CV_MAT_CN(bufType) && CV_Assert( cn == CV_MAT_CN(bufType) &&
@ -2577,11 +2585,12 @@ Ptr<BaseRowFilter> getLinearRowFilter( int srcType, int bufType,
} }
Ptr<BaseColumnFilter> getLinearColumnFilter( int bufType, int dstType, cv::Ptr<cv::BaseColumnFilter> cv::getLinearColumnFilter( int bufType, int dstType,
const Mat& kernel, int anchor, const InputArray& _kernel, int anchor,
int symmetryType, double delta, int symmetryType, double delta,
int bits ) int bits )
{ {
Mat kernel = _kernel.getMat();
int sdepth = CV_MAT_DEPTH(bufType), ddepth = CV_MAT_DEPTH(dstType); int sdepth = CV_MAT_DEPTH(bufType), ddepth = CV_MAT_DEPTH(dstType);
int cn = CV_MAT_CN(dstType); int cn = CV_MAT_CN(dstType);
CV_Assert( cn == CV_MAT_CN(bufType) && CV_Assert( cn == CV_MAT_CN(bufType) &&
@ -2672,13 +2681,14 @@ Ptr<BaseColumnFilter> getLinearColumnFilter( int bufType, int dstType,
} }
Ptr<FilterEngine> createSeparableLinearFilter( cv::Ptr<cv::FilterEngine> cv::createSeparableLinearFilter(
int _srcType, int _dstType, int _srcType, int _dstType,
const Mat& _rowKernel, const Mat& _columnKernel, const InputArray& __rowKernel, const InputArray& __columnKernel,
Point _anchor, double _delta, Point _anchor, double _delta,
int _rowBorderType, int _columnBorderType, int _rowBorderType, int _columnBorderType,
const Scalar& _borderValue ) const Scalar& _borderValue )
{ {
Mat _rowKernel = __rowKernel.getMat(), _columnKernel = __columnKernel.getMat();
_srcType = CV_MAT_TYPE(_srcType); _srcType = CV_MAT_TYPE(_srcType);
_dstType = CV_MAT_TYPE(_dstType); _dstType = CV_MAT_TYPE(_dstType);
int sdepth = CV_MAT_DEPTH(_srcType), ddepth = CV_MAT_DEPTH(_dstType); int sdepth = CV_MAT_DEPTH(_srcType), ddepth = CV_MAT_DEPTH(_dstType);
@ -2742,6 +2752,9 @@ Ptr<FilterEngine> createSeparableLinearFilter(
* Non-separable linear filter * * Non-separable linear filter *
\****************************************************************************************/ \****************************************************************************************/
namespace cv
{
void preprocess2DKernel( const Mat& kernel, vector<Point>& coords, vector<uchar>& coeffs ) void preprocess2DKernel( const Mat& kernel, vector<Point>& coords, vector<uchar>& coeffs )
{ {
int i, j, k, nz = countNonZero(kernel), ktype = kernel.type(); int i, j, k, nz = countNonZero(kernel), ktype = kernel.type();
@ -2868,11 +2881,13 @@ template<typename ST, class CastOp, class VecOp> struct Filter2D : public BaseFi
VecOp vecOp; VecOp vecOp;
}; };
}
Ptr<BaseFilter> getLinearFilter(int srcType, int dstType, cv::Ptr<cv::BaseFilter> cv::getLinearFilter(int srcType, int dstType,
const Mat& _kernel, Point anchor, const InputArray& __kernel, Point anchor,
double delta, int bits) double delta, int bits)
{ {
Mat _kernel = __kernel.getMat();
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(dstType); int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(dstType);
int cn = CV_MAT_CN(srcType), kdepth = _kernel.depth(); int cn = CV_MAT_CN(srcType), kdepth = _kernel.depth();
CV_Assert( cn == CV_MAT_CN(dstType) && ddepth >= sdepth ); CV_Assert( cn == CV_MAT_CN(dstType) && ddepth >= sdepth );
@ -2946,11 +2961,13 @@ Ptr<BaseFilter> getLinearFilter(int srcType, int dstType,
} }
Ptr<FilterEngine> createLinearFilter( int _srcType, int _dstType, const Mat& _kernel, cv::Ptr<cv::FilterEngine> cv::createLinearFilter( int _srcType, int _dstType,
const InputArray& __kernel,
Point _anchor, double _delta, Point _anchor, double _delta,
int _rowBorderType, int _columnBorderType, int _rowBorderType, int _columnBorderType,
const Scalar& _borderValue ) const Scalar& _borderValue )
{ {
Mat _kernel = __kernel.getMat();
_srcType = CV_MAT_TYPE(_srcType); _srcType = CV_MAT_TYPE(_srcType);
_dstType = CV_MAT_TYPE(_dstType); _dstType = CV_MAT_TYPE(_dstType);
int cn = CV_MAT_CN(_srcType); int cn = CV_MAT_CN(_srcType);
@ -2977,10 +2994,12 @@ Ptr<FilterEngine> createLinearFilter( int _srcType, int _dstType, const Mat& _ke
} }
void filter2D( const Mat& src, Mat& dst, int ddepth, void cv::filter2D( const InputArray& _src, OutputArray _dst, int ddepth,
const Mat& kernel, Point anchor, const InputArray& _kernel, Point anchor,
double delta, int borderType ) double delta, int borderType )
{ {
Mat src = _src.getMat(), kernel = _kernel.getMat();
if( ddepth < 0 ) if( ddepth < 0 )
ddepth = src.depth(); ddepth = src.depth();
@ -2991,7 +3010,8 @@ void filter2D( const Mat& src, Mat& dst, int ddepth,
int dft_filter_size = 50; int dft_filter_size = 50;
#endif #endif
dst.create( src.size(), CV_MAKETYPE(ddepth, src.channels()) ); _dst.create( src.size(), CV_MAKETYPE(ddepth, src.channels()) );
Mat dst = _dst.getMat();
anchor = normalizeAnchor(anchor, kernel.size()); anchor = normalizeAnchor(anchor, kernel.size());
if( kernel.cols*kernel.rows >= dft_filter_size ) if( kernel.cols*kernel.rows >= dft_filter_size )
@ -3015,22 +3035,23 @@ void filter2D( const Mat& src, Mat& dst, int ddepth,
} }
void sepFilter2D( const Mat& src, Mat& dst, int ddepth, void cv::sepFilter2D( const InputArray& _src, OutputArray _dst, int ddepth,
const Mat& kernelX, const Mat& kernelY, Point anchor, const InputArray& _kernelX, const InputArray& _kernelY, Point anchor,
double delta, int borderType ) double delta, int borderType )
{ {
Mat src = _src.getMat(), kernelX = _kernelX.getMat(), kernelY = _kernelY.getMat();
if( ddepth < 0 ) if( ddepth < 0 )
ddepth = src.depth(); ddepth = src.depth();
dst.create( src.size(), CV_MAKETYPE(ddepth, src.channels()) ); _dst.create( src.size(), CV_MAKETYPE(ddepth, src.channels()) );
Mat dst = _dst.getMat();
Ptr<FilterEngine> f = createSeparableLinearFilter(src.type(), Ptr<FilterEngine> f = createSeparableLinearFilter(src.type(),
dst.type(), kernelX, kernelY, anchor, delta, borderType & ~BORDER_ISOLATED ); dst.type(), kernelX, kernelY, anchor, delta, borderType & ~BORDER_ISOLATED );
f->apply(src, dst, Rect(0,0,-1,-1), Point(), (borderType & BORDER_ISOLATED) != 0 ); f->apply(src, dst, Rect(0,0,-1,-1), Point(), (borderType & BORDER_ISOLATED) != 0 );
} }
}
CV_IMPL void CV_IMPL void
cvFilter2D( const CvArr* srcarr, CvArr* dstarr, const CvMat* _kernel, CvPoint anchor ) cvFilter2D( const CvArr* srcarr, CvArr* dstarr, const CvMat* _kernel, CvPoint anchor )

12
modules/imgproc/src/floodfill.cpp
Unescape View File

@ -1114,25 +1114,25 @@ cvFloodFill( CvArr* arr, CvPoint seed_point,
} }
int cv::floodFill( Mat& image, Point seedPoint, int cv::floodFill( InputOutputArray _image, Point seedPoint,
Scalar newVal, Rect* rect, Scalar newVal, Rect* rect,
Scalar loDiff, Scalar upDiff, int flags ) Scalar loDiff, Scalar upDiff, int flags )
{ {
CvConnectedComp ccomp; CvConnectedComp ccomp;
CvMat _image = image; CvMat c_image = _image.getMat();
cvFloodFill(&_image, seedPoint, newVal, loDiff, upDiff, &ccomp, flags, 0); cvFloodFill(&c_image, seedPoint, newVal, loDiff, upDiff, &ccomp, flags, 0);
if( rect ) if( rect )
*rect = ccomp.rect; *rect = ccomp.rect;
return cvRound(ccomp.area); return cvRound(ccomp.area);
} }
int cv::floodFill( Mat& image, Mat& mask, int cv::floodFill( InputOutputArray _image, InputOutputArray _mask,
Point seedPoint, Scalar newVal, Rect* rect, Point seedPoint, Scalar newVal, Rect* rect,
Scalar loDiff, Scalar upDiff, int flags ) Scalar loDiff, Scalar upDiff, int flags )
{ {
CvConnectedComp ccomp; CvConnectedComp ccomp;
CvMat _image = image, _mask = mask; CvMat c_image = _image.getMat(), c_mask = _mask.getMat();
cvFloodFill(&_image, seedPoint, newVal, loDiff, upDiff, &ccomp, flags, &_mask); cvFloodFill(&c_image, seedPoint, newVal, loDiff, upDiff, &ccomp, flags, &c_mask);
if( rect ) if( rect )
*rect = ccomp.rect; *rect = ccomp.rect;
return cvRound(ccomp.area); return cvRound(ccomp.area);

13
modules/imgproc/src/grabcut.cpp
Unescape View File

@ -375,10 +375,10 @@ void initGMMs( const Mat& img, const Mat& mask, GMM& bgdGMM, GMM& fgdGMM )
CV_Assert( !bgdSamples.empty() && !fgdSamples.empty() ); CV_Assert( !bgdSamples.empty() && !fgdSamples.empty() );
Mat _bgdSamples( (int)bgdSamples.size(), 3, CV_32FC1, &bgdSamples[0][0] ); Mat _bgdSamples( (int)bgdSamples.size(), 3, CV_32FC1, &bgdSamples[0][0] );
kmeans( _bgdSamples, GMM::componentsCount, bgdLabels, kmeans( _bgdSamples, GMM::componentsCount, bgdLabels,
TermCriteria( CV_TERMCRIT_ITER, kMeansItCount, 0.0), 0, kMeansType, 0 ); TermCriteria( CV_TERMCRIT_ITER, kMeansItCount, 0.0), 0, kMeansType );
Mat _fgdSamples( (int)fgdSamples.size(), 3, CV_32FC1, &fgdSamples[0][0] ); Mat _fgdSamples( (int)fgdSamples.size(), 3, CV_32FC1, &fgdSamples[0][0] );
kmeans( _fgdSamples, GMM::componentsCount, fgdLabels, kmeans( _fgdSamples, GMM::componentsCount, fgdLabels,
TermCriteria( CV_TERMCRIT_ITER, kMeansItCount, 0.0), 0, kMeansType, 0 ); TermCriteria( CV_TERMCRIT_ITER, kMeansItCount, 0.0), 0, kMeansType );
bgdGMM.initLearning(); bgdGMM.initLearning();
for( int i = 0; i < (int)bgdSamples.size(); i++ ) for( int i = 0; i < (int)bgdSamples.size(); i++ )
@ -521,10 +521,15 @@ void estimateSegmentation( GCGraph<double>& graph, Mat& mask )
} }
} }
void cv::grabCut( const Mat& img, Mat& mask, Rect rect, void cv::grabCut( const InputArray& _img, InputOutputArray _mask, Rect rect,
Mat& bgdModel, Mat& fgdModel, InputOutputArray _bgdModel, InputOutputArray _fgdModel,
int iterCount, int mode ) int iterCount, int mode )
{ {
Mat img = _img.getMat();
Mat& mask = _mask.getMatRef();
Mat& bgdModel = _bgdModel.getMatRef();
Mat& fgdModel = _fgdModel.getMatRef();
if( img.empty() ) if( img.empty() )
CV_Error( CV_StsBadArg, "image is empty" ); CV_Error( CV_StsBadArg, "image is empty" );
if( img.type() != CV_8UC3 ) if( img.type() != CV_8UC3 )

94
modules/imgproc/src/histogram.cpp
Unescape View File

@ -43,6 +43,10 @@
namespace cv namespace cv
{ {
template<> void Ptr<CvHistogram>::delete_obj()
{ cvReleaseHist(&obj); }
////////////////// Helper functions ////////////////////// ////////////////// Helper functions //////////////////////
static const size_t OUT_OF_RANGE = (size_t)1 << (sizeof(size_t)*8 - 2); static const size_t OUT_OF_RANGE = (size_t)1 << (sizeof(size_t)*8 - 2);
@ -586,18 +590,22 @@ calcHist_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
} }
} }
}
void calcHist( const Mat* images, int nimages, const int* channels, void cv::calcHist( const Mat* images, int nimages, const int* channels,
const Mat& mask, Mat& hist, int dims, const int* histSize, const InputArray& _mask, OutputArray _hist, int dims, const int* histSize,
const float** ranges, bool uniform, bool accumulate ) const float** ranges, bool uniform, bool accumulate )
{ {
Mat mask = _mask.getMat();
CV_Assert(dims > 0 && histSize); CV_Assert(dims > 0 && histSize);
hist.create(dims, histSize, CV_32F);
Mat ihist = hist; uchar* histdata = _hist.getMat().data;
_hist.create(dims, histSize, CV_32F);
Mat hist = _hist.getMat(), ihist = hist;
ihist.flags = (ihist.flags & ~CV_MAT_TYPE_MASK)|CV_32S; ihist.flags = (ihist.flags & ~CV_MAT_TYPE_MASK)|CV_32S;
if( !accumulate ) if( !accumulate || histdata != hist.data )
hist = Scalar(0.); hist = Scalar(0.);
else else
hist.convertTo(ihist, CV_32S); hist.convertTo(ihist, CV_32S);
@ -626,6 +634,8 @@ void calcHist( const Mat* images, int nimages, const int* channels,
ihist.convertTo(hist, CV_32F); ihist.convertTo(hist, CV_32F);
} }
namespace cv
{
template<typename T> static void template<typename T> static void
calcSparseHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas, calcSparseHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
@ -803,11 +813,13 @@ static void calcHist( const Mat* images, int nimages, const int* channels,
} }
} }
}
void calcHist( const Mat* images, int nimages, const int* channels, void cv::calcHist( const Mat* images, int nimages, const int* channels,
const Mat& mask, SparseMat& hist, int dims, const int* histSize, const InputArray& _mask, SparseMat& hist, int dims, const int* histSize,
const float** ranges, bool uniform, bool accumulate ) const float** ranges, bool uniform, bool accumulate )
{ {
Mat mask = _mask.getMat();
calcHist( images, nimages, channels, mask, hist, dims, histSize, calcHist( images, nimages, channels, mask, hist, dims, histSize,
ranges, uniform, accumulate, false ); ranges, uniform, accumulate, false );
} }
@ -815,6 +827,8 @@ void calcHist( const Mat* images, int nimages, const int* channels,
/////////////////////////////////////// B A C K P R O J E C T //////////////////////////////////// /////////////////////////////////////// B A C K P R O J E C T ////////////////////////////////////
namespace cv
{
template<typename T, typename BT> static void template<typename T, typename BT> static void
calcBackProj_( vector<uchar*>& _ptrs, const vector<int>& _deltas, calcBackProj_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
@ -1103,11 +1117,13 @@ calcBackProj_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
} }
} }
}
void calcBackProject( const Mat* images, int nimages, const int* channels, void cv::calcBackProject( const Mat* images, int nimages, const int* channels,
const Mat& hist, Mat& backProject, const InputArray& _hist, OutputArray _backProject,
const float** ranges, double scale, bool uniform ) const float** ranges, double scale, bool uniform )
{ {
Mat hist = _hist.getMat();
vector<uchar*> ptrs; vector<uchar*> ptrs;
vector<int> deltas; vector<int> deltas;
vector<double> uniranges; vector<double> uniranges;
@ -1115,7 +1131,8 @@ void calcBackProject( const Mat* images, int nimages, const int* channels,
int dims = hist.dims == 2 && hist.size[1] == 1 ? 1 : hist.dims; int dims = hist.dims == 2 && hist.size[1] == 1 ? 1 : hist.dims;
CV_Assert( dims > 0 && hist.data ); CV_Assert( dims > 0 && hist.data );
backProject.create( images[0].size(), images[0].depth() ); _backProject.create( images[0].size(), images[0].depth() );
Mat backProject = _backProject.getMat();
histPrepareImages( images, nimages, channels, backProject, dims, hist.size, ranges, histPrepareImages( images, nimages, channels, backProject, dims, hist.size, ranges,
uniform, ptrs, deltas, imsize, uniranges ); uniform, ptrs, deltas, imsize, uniranges );
const double* _uniranges = uniform ? &uniranges[0] : 0; const double* _uniranges = uniform ? &uniranges[0] : 0;
@ -1132,6 +1149,9 @@ void calcBackProject( const Mat* images, int nimages, const int* channels,
} }
namespace cv
{
template<typename T, typename BT> static void template<typename T, typename BT> static void
calcSparseBackProj_( vector<uchar*>& _ptrs, const vector<int>& _deltas, calcSparseBackProj_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, const SparseMat& hist, int dims, const float** _ranges, Size imsize, const SparseMat& hist, int dims, const float** _ranges,
@ -1260,8 +1280,9 @@ calcSparseBackProj_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
} }
} }
}
void calcBackProject( const Mat* images, int nimages, const int* channels, void cv::calcBackProject( const Mat* images, int nimages, const int* channels,
const SparseMat& hist, Mat& backProject, const SparseMat& hist, Mat& backProject,
const float** ranges, double scale, bool uniform ) const float** ranges, double scale, bool uniform )
{ {
@ -1295,13 +1316,14 @@ void calcBackProject( const Mat* images, int nimages, const int* channels,
////////////////// C O M P A R E H I S T O G R A M S //////////////////////// ////////////////// C O M P A R E H I S T O G R A M S ////////////////////////
double compareHist( const Mat& H1, const Mat& H2, int method ) double cv::compareHist( const InputArray& _H1, const InputArray& _H2, int method )
{ {
Mat H1 = _H1.getMat(), H2 = _H2.getMat();
const Mat* arrays[] = {&H1, &H2, 0}; const Mat* arrays[] = {&H1, &H2, 0};
Mat planes[2]; Mat planes[2];
NAryMatIterator it(arrays, planes); NAryMatIterator it(arrays, planes);
double result = 0; double result = 0;
int i, len; int j, len = (int)it.size;
CV_Assert( H1.type() == H2.type() && H1.type() == CV_32F ); CV_Assert( H1.type() == H2.type() && H1.type() == CV_32F );
@ -1309,7 +1331,7 @@ double compareHist( const Mat& H1, const Mat& H2, int method )
CV_Assert( it.planes[0].isContinuous() && it.planes[1].isContinuous() ); CV_Assert( it.planes[0].isContinuous() && it.planes[1].isContinuous() );
for( i = 0; i < it.nplanes; i++, ++it ) for( size_t i = 0; i < it.nplanes; i++, ++it )
{ {
const float* h1 = (const float*)it.planes[0].data; const float* h1 = (const float*)it.planes[0].data;
const float* h2 = (const float*)it.planes[1].data; const float* h2 = (const float*)it.planes[1].data;
@ -1317,20 +1339,20 @@ double compareHist( const Mat& H1, const Mat& H2, int method )
if( method == CV_COMP_CHISQR ) if( method == CV_COMP_CHISQR )
{ {
for( i = 0; i < len; i++ ) for( j = 0; j < len; j++ )
{ {
double a = h1[i] - h2[i]; double a = h1[j] - h2[j];
double b = h1[i] + h2[i]; double b = h1[j] + h2[j];
if( fabs(b) > FLT_EPSILON ) if( fabs(b) > FLT_EPSILON )
result += a*a/b; result += a*a/b;
} }
} }
else if( method == CV_COMP_CORREL ) else if( method == CV_COMP_CORREL )
{ {
for( i = 0; i < len; i++ ) for( j = 0; j < len; j++ )
{ {
double a = h1[i]; double a = h1[j];
double b = h2[i]; double b = h2[j];
s12 += a*b; s12 += a*b;
s1 += a; s1 += a;
@ -1341,15 +1363,15 @@ double compareHist( const Mat& H1, const Mat& H2, int method )
} }
else if( method == CV_COMP_INTERSECT ) else if( method == CV_COMP_INTERSECT )
{ {
for( i = 0; i < len; i++ ) for( j = 0; j < len; j++ )
result += std::min(h1[i], h2[i]); result += std::min(h1[j], h2[j]);
} }
else if( method == CV_COMP_BHATTACHARYYA ) else if( method == CV_COMP_BHATTACHARYYA )
{ {
for( i = 0; i < len; i++ ) for( j = 0; j < len; j++ )
{ {
double a = h1[i]; double a = h1[j];
double b = h2[i]; double b = h2[j];
result += std::sqrt(a*b); result += std::sqrt(a*b);
s1 += a; s1 += a;
s2 += b; s2 += b;
@ -1361,9 +1383,7 @@ double compareHist( const Mat& H1, const Mat& H2, int method )
if( method == CV_COMP_CORREL ) if( method == CV_COMP_CORREL )
{ {
size_t total = 1; size_t total = H1.total();
for( i = 0; i < H1.dims; i++ )
total *= H1.size[i];
double scale = 1./total; double scale = 1./total;
double num = s12 - s1*s2*scale; double num = s12 - s1*s2*scale;
double denom2 = (s11 - s1*s1*scale)*(s22 - s2*s2*scale); double denom2 = (s11 - s1*s1*scale)*(s22 - s2*s2*scale);
@ -1380,7 +1400,7 @@ double compareHist( const Mat& H1, const Mat& H2, int method )
} }
double compareHist( const SparseMat& H1, const SparseMat& H2, int method ) double cv::compareHist( const SparseMat& H1, const SparseMat& H2, int method )
{ {
double result = 0; double result = 0;
int i, dims = H1.dims(); int i, dims = H1.dims();
@ -1491,12 +1511,6 @@ double compareHist( const SparseMat& H1, const SparseMat& H2, int method )
} }
template<> void Ptr<CvHistogram>::delete_obj()
{ cvReleaseHist(&obj); }
}
const int CV_HIST_DEFAULT_TYPE = CV_32F; const int CV_HIST_DEFAULT_TYPE = CV_32F;
/* Creates new histogram */ /* Creates new histogram */
@ -2395,11 +2409,13 @@ CV_IMPL void cvEqualizeHist( const CvArr* srcarr, CvArr* dstarr )
} }
void cv::equalizeHist( const Mat& src, Mat& dst ) void cv::equalizeHist( const InputArray& _src, OutputArray _dst )
{ {
dst.create( src.size(), src.type() ); Mat src = _src.getMat();
CvMat _src = src, _dst = dst; _dst.create( src.size(), src.type() );
cvEqualizeHist( &_src, &_dst ); Mat dst = _dst.getMat();
CvMat _csrc = src, _cdst = dst;
cvEqualizeHist( &_csrc, &_cdst );
} }
/* Implementation of RTTI and Generic Functions for CvHistogram */ /* Implementation of RTTI and Generic Functions for CvHistogram */

49
modules/imgproc/src/hough.cpp
Unescape View File

@ -1090,44 +1090,53 @@ namespace cv
const int STORAGE_SIZE = 1 << 12; const int STORAGE_SIZE = 1 << 12;
void HoughLines( const Mat& image, vector<Vec2f>& lines, static void seqToMat(const CvSeq* seq, OutputArray& _arr)
{
if( seq )
{
_arr.create(1, seq->total, seq->flags, -1, true);
Mat arr = _arr.getMat();
cvCvtSeqToArray(seq, arr.data);
}
else
_arr.release();
}
}
void cv::HoughLines( const InputArray& _image, OutputArray _lines,
double rho, double theta, int threshold, double rho, double theta, int threshold,
double srn, double stn ) double srn, double stn )
{ {
CvMemStorage* storage = cvCreateMemStorage(STORAGE_SIZE); Ptr<CvMemStorage> storage = cvCreateMemStorage(STORAGE_SIZE);
CvMat _image = image; CvMat c_image = _image.getMat();
CvSeq* seq = cvHoughLines2( &_image, storage, srn == 0 && stn == 0 ? CvSeq* seq = cvHoughLines2( &c_image, storage, srn == 0 && stn == 0 ?
CV_HOUGH_STANDARD : CV_HOUGH_MULTI_SCALE, CV_HOUGH_STANDARD : CV_HOUGH_MULTI_SCALE,
rho, theta, threshold, srn, stn ); rho, theta, threshold, srn, stn );
Seq<Vec2f>(seq).copyTo(lines); seqToMat(seq, _lines);
cvReleaseMemStorage(&storage);
} }
void HoughLinesP( Mat& image, vector<Vec4i>& lines, void cv::HoughLinesP( const InputArray& _image, OutputArray _lines,
double rho, double theta, int threshold, double rho, double theta, int threshold,
double minLineLength, double maxGap ) double minLineLength, double maxGap )
{ {
CvMemStorage* storage = cvCreateMemStorage(STORAGE_SIZE); Ptr<CvMemStorage> storage = cvCreateMemStorage(STORAGE_SIZE);
CvMat _image = image; CvMat c_image = _image.getMat();
CvSeq* seq = cvHoughLines2( &_image, storage, CV_HOUGH_PROBABILISTIC, CvSeq* seq = cvHoughLines2( &c_image, storage, CV_HOUGH_PROBABILISTIC,
rho, theta, threshold, minLineLength, maxGap ); rho, theta, threshold, minLineLength, maxGap );
Seq<Vec4i>(seq).copyTo(lines); seqToMat(seq, _lines);
cvReleaseMemStorage(&storage);
} }
void HoughCircles( const Mat& image, vector<Vec3f>& circles, void cv::HoughCircles( const InputArray& _image, OutputArray _circles,
int method, double dp, double min_dist, int method, double dp, double min_dist,
double param1, double param2, double param1, double param2,
int minRadius, int maxRadius ) int minRadius, int maxRadius )
{ {
CvMemStorage* storage = cvCreateMemStorage(STORAGE_SIZE); Ptr<CvMemStorage> storage = cvCreateMemStorage(STORAGE_SIZE);
CvMat _image = image; CvMat c_image = _image.getMat();
CvSeq* seq = cvHoughCircles( &_image, storage, method, CvSeq* seq = cvHoughCircles( &c_image, storage, method,
dp, min_dist, param1, param2, minRadius, maxRadius ); dp, min_dist, param1, param2, minRadius, maxRadius );
Seq<Vec3f>(seq).copyTo(circles); seqToMat(seq, _circles);
cvReleaseMemStorage(&storage);
}
} }
/* End of file. */ /* End of file. */

68
modules/imgproc/src/imgwarp.cpp
Unescape View File

@ -1313,9 +1313,11 @@ typedef void (*ResizeAreaFastFunc)( const Mat& src, Mat& dst,
typedef void (*ResizeAreaFunc)( const Mat& src, Mat& dst, typedef void (*ResizeAreaFunc)( const Mat& src, Mat& dst,
const DecimateAlpha* xofs, int xofs_count ); const DecimateAlpha* xofs, int xofs_count );
}
////////////////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////////////////
void resize( const Mat& src, Mat& dst, Size dsize, void cv::resize( const InputArray& _src, OutputArray _dst, Size dsize,
double inv_scale_x, double inv_scale_y, int interpolation ) double inv_scale_x, double inv_scale_y, int interpolation )
{ {
static ResizeFunc linear_tab[] = static ResizeFunc linear_tab[] =
@ -1420,6 +1422,7 @@ void resize( const Mat& src, Mat& dst, Size dsize,
0, resizeArea_<float, float>, resizeArea_<double, double>, 0 0, resizeArea_<float, float>, resizeArea_<double, double>, 0
}; };
Mat src = _src.getMat();
Size ssize = src.size(); Size ssize = src.size();
CV_Assert( ssize.area() > 0 ); CV_Assert( ssize.area() > 0 );
@ -1434,7 +1437,8 @@ void resize( const Mat& src, Mat& dst, Size dsize,
inv_scale_x = (double)dsize.width/src.cols; inv_scale_x = (double)dsize.width/src.cols;
inv_scale_y = (double)dsize.height/src.rows; inv_scale_y = (double)dsize.height/src.rows;
} }
dst.create(dsize, src.type()); _dst.create(dsize, src.type());
Mat dst = _dst.getMat();
int depth = src.depth(), cn = src.channels(); int depth = src.depth(), cn = src.channels();
double scale_x = 1./inv_scale_x, scale_y = 1./inv_scale_y; double scale_x = 1./inv_scale_x, scale_y = 1./inv_scale_y;
@ -1653,6 +1657,9 @@ void resize( const Mat& src, Mat& dst, Size dsize,
* General warping (affine, perspective, remap) * * General warping (affine, perspective, remap) *
\****************************************************************************************/ \****************************************************************************************/
namespace cv
{
template<typename T> template<typename T>
static void remapNearest( const Mat& _src, Mat& _dst, const Mat& _xy, static void remapNearest( const Mat& _src, Mat& _dst, const Mat& _xy,
int borderType, const Scalar& _borderValue ) int borderType, const Scalar& _borderValue )
@ -2392,7 +2399,10 @@ typedef void (*RemapFunc)(const Mat& _src, Mat& _dst, const Mat& _xy,
const Mat& _fxy, const void* _wtab, const Mat& _fxy, const void* _wtab,
int borderType, const Scalar& _borderValue); int borderType, const Scalar& _borderValue);
void remap( const Mat& src, Mat& dst, const Mat& map1, const Mat& map2, }
void cv::remap( const InputArray& _src, OutputArray _dst,
const InputArray& _map1, const InputArray& _map2,
int interpolation, int borderType, const Scalar& borderValue ) int interpolation, int borderType, const Scalar& borderValue )
{ {
static RemapNNFunc nn_tab[] = static RemapNNFunc nn_tab[] =
@ -2425,8 +2435,12 @@ void remap( const Mat& src, Mat& dst, const Mat& map1, const Mat& map2,
remapLanczos4<Cast<float, float>, float, 1>, 0, 0 remapLanczos4<Cast<float, float>, float, 1>, 0, 0
}; };
Mat src = _src.getMat(), map1 = _map1.getMat(), map2 = _map2.getMat();
CV_Assert( (!map2.data || map2.size() == map1.size())); CV_Assert( (!map2.data || map2.size() == map1.size()));
dst.create( map1.size(), src.type() );
_dst.create( map1.size(), src.type() );
Mat dst = _dst.getMat();
CV_Assert(dst.data != src.data); CV_Assert(dst.data != src.data);
int depth = src.depth(), map_depth = map1.depth(); int depth = src.depth(), map_depth = map1.depth();
@ -2650,9 +2664,11 @@ void remap( const Mat& src, Mat& dst, const Mat& map1, const Mat& map2,
} }
void convertMaps( const Mat& map1, const Mat& map2, Mat& dstmap1, Mat& dstmap2, void cv::convertMaps( const InputArray& _map1, const InputArray& _map2,
OutputArray _dstmap1, OutputArray _dstmap2,
int dstm1type, bool nninterpolate ) int dstm1type, bool nninterpolate )
{ {
Mat map1 = _map1.getMat(), map2 = _map2.getMat(), dstmap1, dstmap2;
Size size = map1.size(); Size size = map1.size();
const Mat *m1 = &map1, *m2 = &map2; const Mat *m1 = &map1, *m2 = &map2;
int m1type = m1->type(), m2type = m2->type(); int m1type = m1->type(), m2type = m2->type();
@ -2671,11 +2687,16 @@ void convertMaps( const Mat& map1, const Mat& map2, Mat& dstmap1, Mat& dstmap2,
if( dstm1type <= 0 ) if( dstm1type <= 0 )
dstm1type = m1type == CV_16SC2 ? CV_32FC2 : CV_16SC2; dstm1type = m1type == CV_16SC2 ? CV_32FC2 : CV_16SC2;
CV_Assert( dstm1type == CV_16SC2 || dstm1type == CV_32FC1 || dstm1type == CV_32FC2 ); CV_Assert( dstm1type == CV_16SC2 || dstm1type == CV_32FC1 || dstm1type == CV_32FC2 );
dstmap1.create( size, dstm1type ); _dstmap1.create( size, dstm1type );
dstmap1 = _dstmap1.getMat();
if( !nninterpolate && dstm1type != CV_32FC2 ) if( !nninterpolate && dstm1type != CV_32FC2 )
dstmap2.create( size, dstm1type == CV_16SC2 ? CV_16UC1 : CV_32FC1 ); {
_dstmap2.create( size, dstm1type == CV_16SC2 ? CV_16UC1 : CV_32FC1 );
dstmap2 = _dstmap2.getMat();
}
else else
dstmap2.release(); _dstmap2.release();
if( m1type == dstm1type || (nninterpolate && if( m1type == dstm1type || (nninterpolate &&
((m1type == CV_16SC2 && dstm1type == CV_32FC2) || ((m1type == CV_16SC2 && dstm1type == CV_32FC2) ||
@ -2782,10 +2803,13 @@ void convertMaps( const Mat& map1, const Mat& map2, Mat& dstmap1, Mat& dstmap2,
} }
void warpAffine( const Mat& src, Mat& dst, const Mat& M0, Size dsize, void cv::warpAffine( const InputArray& _src, OutputArray _dst,
const InputArray& _M0, Size dsize,
int flags, int borderType, const Scalar& borderValue ) int flags, int borderType, const Scalar& borderValue )
{ {
dst.create( dsize, src.type() ); Mat src = _src.getMat(), M0 = _M0.getMat();
_dst.create( dsize, src.type() );
Mat dst = _dst.getMat();
CV_Assert( dst.data != src.data && src.cols > 0 && src.rows > 0 ); CV_Assert( dst.data != src.data && src.cols > 0 && src.rows > 0 );
const int BLOCK_SZ = 64; const int BLOCK_SZ = 64;
@ -2917,10 +2941,13 @@ void warpAffine( const Mat& src, Mat& dst, const Mat& M0, Size dsize,
} }
void warpPerspective( const Mat& src, Mat& dst, const Mat& M0, Size dsize, void cv::warpPerspective( const InputArray& _src, OutputArray _dst, const InputArray& _M0,
int flags, int borderType, const Scalar& borderValue ) Size dsize, int flags, int borderType, const Scalar& borderValue )
{ {
dst.create( dsize, src.type() ); Mat src = _src.getMat(), M0 = _M0.getMat();
_dst.create( dsize, src.type() );
Mat dst = _dst.getMat();
CV_Assert( dst.data != src.data && src.cols > 0 && src.rows > 0 ); CV_Assert( dst.data != src.data && src.cols > 0 && src.rows > 0 );
const int BLOCK_SZ = 32; const int BLOCK_SZ = 32;
@ -2999,7 +3026,7 @@ void warpPerspective( const Mat& src, Mat& dst, const Mat& M0, Size dsize,
} }
Mat getRotationMatrix2D( Point2f center, double angle, double scale ) cv::Mat cv::getRotationMatrix2D( Point2f center, double angle, double scale )
{ {
angle *= CV_PI/180; angle *= CV_PI/180;
double alpha = cos(angle)*scale; double alpha = cos(angle)*scale;
@ -3042,7 +3069,7 @@ Mat getRotationMatrix2D( Point2f center, double angle, double scale )
* where: * where:
* cij - matrix coefficients, c22 = 1 * cij - matrix coefficients, c22 = 1
*/ */
Mat getPerspectiveTransform( const Point2f src[], const Point2f dst[] ) cv::Mat cv::getPerspectiveTransform( const Point2f src[], const Point2f dst[] )
{ {
Mat M(3, 3, CV_64F), X(8, 1, CV_64F, M.data); Mat M(3, 3, CV_64F), X(8, 1, CV_64F, M.data);
double a[8][8], b[8]; double a[8][8], b[8];
@ -3087,7 +3114,7 @@ Mat getPerspectiveTransform( const Point2f src[], const Point2f dst[] )
* where: * where:
* cij - matrix coefficients * cij - matrix coefficients
*/ */
Mat getAffineTransform( const Point2f src[], const Point2f dst[] ) cv::Mat cv::getAffineTransform( const Point2f src[], const Point2f dst[] )
{ {
Mat M(2, 3, CV_64F), X(6, 1, CV_64F, M.data); Mat M(2, 3, CV_64F), X(6, 1, CV_64F, M.data);
double a[6*6], b[6]; double a[6*6], b[6];
@ -3110,10 +3137,13 @@ Mat getAffineTransform( const Point2f src[], const Point2f dst[] )
return M; return M;
} }
void invertAffineTransform(const Mat& matM, Mat& _iM) void cv::invertAffineTransform(const InputArray& _matM, OutputArray __iM)
{ {
Mat matM = _matM.getMat();
CV_Assert(matM.rows == 2 && matM.cols == 3); CV_Assert(matM.rows == 2 && matM.cols == 3);
_iM.create(2, 3, matM.type()); __iM.create(2, 3, matM.type());
Mat _iM = __iM.getMat();
if( matM.type() == CV_32F ) if( matM.type() == CV_32F )
{ {
const float* M = (const float*)matM.data; const float* M = (const float*)matM.data;
@ -3148,8 +3178,6 @@ void invertAffineTransform(const Mat& matM, Mat& _iM)
CV_Error( CV_StsUnsupportedFormat, "" ); CV_Error( CV_StsUnsupportedFormat, "" );
} }
}
CV_IMPL void CV_IMPL void
cvResize( const CvArr* srcarr, CvArr* dstarr, int method ) cvResize( const CvArr* srcarr, CvArr* dstarr, int method )
{ {

9
modules/imgproc/src/inpaint.cpp
Unescape View File

@ -807,10 +807,11 @@ cvInpaint( const CvArr* _input_img, const CvArr* _inpaint_mask, CvArr* _output_i
} }
} }
void cv::inpaint( const Mat& src, const Mat& mask, Mat& dst, void cv::inpaint( const InputArray& _src, const InputArray& _mask, OutputArray _dst,
double inpaintRange, int flags ) double inpaintRange, int flags )
{ {
dst.create( src.size(), src.type() ); Mat src = _src.getMat();
CvMat _src = src, _mask = mask, _dst = dst; _dst.create( src.size(), src.type() );
cvInpaint( &_src, &_mask, &_dst, inpaintRange, flags ); CvMat c_src = src, c_mask = _mask.getMat(), c_dst = _dst.getMat();
cvInpaint( &c_src, &c_mask, &c_dst, inpaintRange, flags );
} }

7
modules/imgproc/src/moments.cpp
Unescape View File

@ -601,13 +601,14 @@ Moments::operator CvMoments() const
return m; return m;
} }
} }
cv::Moments cv::moments( const Mat& array, bool binaryImage ) cv::Moments cv::moments( const InputArray& _array, bool binaryImage )
{ {
CvMoments om; CvMoments om;
CvMat _array = array; CvMat c_array = _array.getMat();
cvMoments(&_array, &om, binaryImage); cvMoments(&c_array, &om, binaryImage);
return om; return om;
} }

63
modules/imgproc/src/morph.cpp
Unescape View File

@ -822,9 +822,11 @@ template<class Op, class VecOp> struct MorphFilter : BaseFilter
VecOp vecOp; VecOp vecOp;
}; };
}
/////////////////////////////////// External Interface ///////////////////////////////////// /////////////////////////////////// External Interface /////////////////////////////////////
Ptr<BaseRowFilter> getMorphologyRowFilter(int op, int type, int ksize, int anchor) cv::Ptr<cv::BaseRowFilter> cv::getMorphologyRowFilter(int op, int type, int ksize, int anchor)
{ {
int depth = CV_MAT_DEPTH(type); int depth = CV_MAT_DEPTH(type);
if( anchor < 0 ) if( anchor < 0 )
@ -865,7 +867,7 @@ Ptr<BaseRowFilter> getMorphologyRowFilter(int op, int type, int ksize, int ancho
return Ptr<BaseRowFilter>(0); return Ptr<BaseRowFilter>(0);
} }
Ptr<BaseColumnFilter> getMorphologyColumnFilter(int op, int type, int ksize, int anchor) cv::Ptr<cv::BaseColumnFilter> cv::getMorphologyColumnFilter(int op, int type, int ksize, int anchor)
{ {
int depth = CV_MAT_DEPTH(type); int depth = CV_MAT_DEPTH(type);
if( anchor < 0 ) if( anchor < 0 )
@ -907,8 +909,9 @@ Ptr<BaseColumnFilter> getMorphologyColumnFilter(int op, int type, int ksize, int
} }
Ptr<BaseFilter> getMorphologyFilter(int op, int type, const Mat& kernel, Point anchor) cv::Ptr<cv::BaseFilter> cv::getMorphologyFilter(int op, int type, const InputArray& _kernel, Point anchor)
{ {
Mat kernel = _kernel.getMat();
int depth = CV_MAT_DEPTH(type); int depth = CV_MAT_DEPTH(type);
anchor = normalizeAnchor(anchor, kernel.size()); anchor = normalizeAnchor(anchor, kernel.size());
CV_Assert( op == MORPH_ERODE || op == MORPH_DILATE ); CV_Assert( op == MORPH_ERODE || op == MORPH_DILATE );
@ -940,10 +943,11 @@ Ptr<BaseFilter> getMorphologyFilter(int op, int type, const Mat& kernel, Point a
} }
Ptr<FilterEngine> createMorphologyFilter( int op, int type, const Mat& kernel, cv::Ptr<cv::FilterEngine> cv::createMorphologyFilter( int op, int type, const InputArray& _kernel,
Point anchor, int _rowBorderType, int _columnBorderType, Point anchor, int _rowBorderType, int _columnBorderType,
const Scalar& _borderValue ) const Scalar& _borderValue )
{ {
Mat kernel = _kernel.getMat();
anchor = normalizeAnchor(anchor, kernel.size()); anchor = normalizeAnchor(anchor, kernel.size());
Ptr<BaseRowFilter> rowFilter; Ptr<BaseRowFilter> rowFilter;
@ -978,7 +982,7 @@ Ptr<FilterEngine> createMorphologyFilter( int op, int type, const Mat& kernel,
} }
Mat getStructuringElement(int shape, Size ksize, Point anchor) cv::Mat cv::getStructuringElement(int shape, Size ksize, Point anchor)
{ {
int i, j; int i, j;
int r = 0, c = 0; int r = 0, c = 0;
@ -1031,31 +1035,36 @@ Mat getStructuringElement(int shape, Size ksize, Point anchor)
return elem; return elem;
} }
static void morphOp( int op, const Mat& src, Mat& dst, const Mat& _kernel, namespace cv
{
static void morphOp( int op, const InputArray& _src, OutputArray& _dst,
const InputArray& _kernel,
Point anchor, int iterations, Point anchor, int iterations,
int borderType, const Scalar& borderValue ) int borderType, const Scalar& borderValue )
{ {
Mat kernel; Mat src = _src.getMat(), kernel = _kernel.getMat();
Size ksize = _kernel.data ? _kernel.size() : Size(3,3); Size ksize = kernel.data ? kernel.size() : Size(3,3);
anchor = normalizeAnchor(anchor, ksize); anchor = normalizeAnchor(anchor, ksize);
CV_Assert( anchor.inside(Rect(0, 0, ksize.width, ksize.height)) ); CV_Assert( anchor.inside(Rect(0, 0, ksize.width, ksize.height)) );
if( iterations == 0 || _kernel.rows*_kernel.cols == 1 ) _dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
if( iterations == 0 || kernel.rows*kernel.cols == 1 )
{ {
src.copyTo(dst); src.copyTo(dst);
return; return;
} }
dst.create( src.size(), src.type() ); if( !kernel.data )
if( !_kernel.data )
{ {
kernel = getStructuringElement(MORPH_RECT, Size(1+iterations*2,1+iterations*2)); kernel = getStructuringElement(MORPH_RECT, Size(1+iterations*2,1+iterations*2));
anchor = Point(iterations, iterations); anchor = Point(iterations, iterations);
iterations = 1; iterations = 1;
} }
else if( iterations > 1 && countNonZero(_kernel) == _kernel.rows*_kernel.cols ) else if( iterations > 1 && countNonZero(kernel) == kernel.rows*kernel.cols )
{ {
anchor = Point(anchor.x*iterations, anchor.y*iterations); anchor = Point(anchor.x*iterations, anchor.y*iterations);
kernel = getStructuringElement(MORPH_RECT, kernel = getStructuringElement(MORPH_RECT,
@ -1064,8 +1073,6 @@ static void morphOp( int op, const Mat& src, Mat& dst, const Mat& _kernel,
anchor); anchor);
iterations = 1; iterations = 1;
} }
else
kernel = _kernel;
Ptr<FilterEngine> f = createMorphologyFilter(op, src.type(), Ptr<FilterEngine> f = createMorphologyFilter(op, src.type(),
kernel, anchor, borderType, borderType, borderValue ); kernel, anchor, borderType, borderType, borderValue );
@ -1075,8 +1082,12 @@ static void morphOp( int op, const Mat& src, Mat& dst, const Mat& _kernel,
f->apply( dst, dst ); f->apply( dst, dst );
} }
template<> void Ptr<IplConvKernel>::delete_obj()
{ cvReleaseStructuringElement(&obj); }
void erode( const Mat& src, Mat& dst, const Mat& kernel, }
void cv::erode( const InputArray& src, OutputArray dst, const InputArray& kernel,
Point anchor, int iterations, Point anchor, int iterations,
int borderType, const Scalar& borderValue ) int borderType, const Scalar& borderValue )
{ {
@ -1084,7 +1095,7 @@ void erode( const Mat& src, Mat& dst, const Mat& kernel,
} }
void dilate( const Mat& src, Mat& dst, const Mat& kernel, void cv::dilate( const InputArray& src, OutputArray dst, const InputArray& kernel,
Point anchor, int iterations, Point anchor, int iterations,
int borderType, const Scalar& borderValue ) int borderType, const Scalar& borderValue )
{ {
@ -1092,11 +1103,14 @@ void dilate( const Mat& src, Mat& dst, const Mat& kernel,
} }
void morphologyEx( const Mat& src, Mat& dst, int op, const Mat& kernel, void cv::morphologyEx( const InputArray& _src, OutputArray _dst, int op,
Point anchor, int iterations, int borderType, const InputArray& kernel, Point anchor, int iterations,
const Scalar& borderValue ) int borderType, const Scalar& borderValue )
{ {
Mat temp; Mat src = _src.getMat(), temp;
_dst.create(src.size(), src.type());
Mat dst = _dst.getMat();
switch( op ) switch( op )
{ {
case MORPH_ERODE: case MORPH_ERODE:
@ -1137,13 +1151,6 @@ void morphologyEx( const Mat& src, Mat& dst, int op, const Mat& kernel,
} }
} }
template<> void Ptr<IplConvKernel>::delete_obj()
{ cvReleaseStructuringElement(&obj); }
}
CV_IMPL IplConvKernel * CV_IMPL IplConvKernel *
cvCreateStructuringElementEx( int cols, int rows, cvCreateStructuringElementEx( int cols, int rows,
int anchorX, int anchorY, int anchorX, int anchorY,

37
modules/imgproc/src/pyramids.cpp
Unescape View File

@ -399,11 +399,15 @@ pyrUp_( const Mat& _src, Mat& _dst )
typedef void (*PyrFunc)(const Mat&, Mat&); typedef void (*PyrFunc)(const Mat&, Mat&);
void pyrDown( const Mat& _src, Mat& _dst, const Size& _dsz ) }
void cv::pyrDown( const InputArray& _src, OutputArray _dst, const Size& _dsz )
{ {
Size dsz = _dsz == Size() ? Size((_src.cols + 1)/2, (_src.rows + 1)/2) : _dsz; Mat src = _src.getMat();
_dst.create( dsz, _src.type() ); Size dsz = _dsz == Size() ? Size((src.cols + 1)/2, (src.rows + 1)/2) : _dsz;
int depth = _src.depth(); _dst.create( dsz, src.type() );
Mat dst = _dst.getMat();
int depth = src.depth();
PyrFunc func = 0; PyrFunc func = 0;
if( depth == CV_8U ) if( depth == CV_8U )
func = pyrDown_<FixPtCast<uchar, 8>, PyrDownVec_32s8u>; func = pyrDown_<FixPtCast<uchar, 8>, PyrDownVec_32s8u>;
@ -416,14 +420,16 @@ void pyrDown( const Mat& _src, Mat& _dst, const Size& _dsz )
else else
CV_Error( CV_StsUnsupportedFormat, "" ); CV_Error( CV_StsUnsupportedFormat, "" );
func( _src, _dst ); func( src, dst );
} }
void pyrUp( const Mat& _src, Mat& _dst, const Size& _dsz ) void cv::pyrUp( const InputArray& _src, OutputArray _dst, const Size& _dsz )
{ {
Size dsz = _dsz == Size() ? Size(_src.cols*2, _src.rows*2) : _dsz; Mat src = _src.getMat();
_dst.create( dsz, _src.type() ); Size dsz = _dsz == Size() ? Size(src.cols*2, src.rows*2) : _dsz;
int depth = _src.depth(); _dst.create( dsz, src.type() );
Mat dst = _dst.getMat();
int depth = src.depth();
PyrFunc func = 0; PyrFunc func = 0;
if( depth == CV_8U ) if( depth == CV_8U )
func = pyrUp_<FixPtCast<uchar, 6>, NoVec<int, uchar> >; func = pyrUp_<FixPtCast<uchar, 6>, NoVec<int, uchar> >;
@ -436,17 +442,16 @@ void pyrUp( const Mat& _src, Mat& _dst, const Size& _dsz )
else else
CV_Error( CV_StsUnsupportedFormat, "" ); CV_Error( CV_StsUnsupportedFormat, "" );
func( _src, _dst ); func( src, dst );
} }
void buildPyramid( const Mat& _src, vector<Mat>& _dst, int maxlevel ) void cv::buildPyramid( const InputArray& _src, OutputArrayOfArrays _dst, int maxlevel )
{ {
_dst.resize( maxlevel + 1 ); Mat src = _src.getMat();
_dst[0] = _src; _dst.create( maxlevel + 1, 1, 0 );
_dst.getMatRef(0) = src;
for( int i = 1; i <= maxlevel; i++ ) for( int i = 1; i <= maxlevel; i++ )
pyrDown( _dst[i-1], _dst[i] ); pyrDown( _dst.getMatRef(i-1), _dst.getMatRef(i) );
}
} }
CV_IMPL void cvPyrDown( const void* srcarr, void* dstarr, int _filter ) CV_IMPL void cvPyrDown( const void* srcarr, void* dstarr, int _filter )

12
modules/imgproc/src/samplers.cpp
Unescape View File

@ -868,13 +868,15 @@ cvGetQuadrangleSubPix( const void* srcarr, void* dstarr, const CvMat* mat )
} }
void cv::getRectSubPix( const Mat& image, Size patchSize, Point2f center, void cv::getRectSubPix( const InputArray& _image, Size patchSize, Point2f center,
Mat& patch, int patchType ) OutputArray _patch, int patchType )
{ {
patch.create(patchSize, patchType < 0 ? image.type() : Mat image = _image.getMat();
_patch.create(patchSize, patchType < 0 ? image.type() :
CV_MAKETYPE(CV_MAT_DEPTH(patchType),image.channels())); CV_MAKETYPE(CV_MAT_DEPTH(patchType),image.channels()));
CvMat _image = image, _patch = patch; Mat patch = _patch.getMat();
cvGetRectSubPix(&_image, &_patch, center); CvMat _cimage = image, _cpatch = patch;
cvGetRectSubPix(&_cimage, &_cpatch, center);
} }
/* End of file. */ /* End of file. */

16
modules/imgproc/src/segmentation.cpp
Unescape View File

@ -303,10 +303,10 @@ cvWatershed( const CvArr* srcarr, CvArr* dstarr )
} }
void cv::watershed( const Mat& src, Mat& markers ) void cv::watershed( const InputArray& src, InputOutputArray markers )
{ {
CvMat _src = src, _markers = markers; CvMat c_src = src.getMat(), c_markers = markers.getMat();
cvWatershed( &_src, &_markers ); cvWatershed( &c_src, &c_markers );
} }
@ -523,14 +523,16 @@ cvPyrMeanShiftFiltering( const CvArr* srcarr, CvArr* dstarr,
} }
} }
void cv::pyrMeanShiftFiltering( const Mat& src, Mat& dst, void cv::pyrMeanShiftFiltering( const InputArray& _src, OutputArray _dst,
double sp, double sr, int maxLevel, double sp, double sr, int maxLevel,
TermCriteria termcrit ) TermCriteria termcrit )
{ {
Mat src = _src.getMat();
if( src.empty() ) if( src.empty() )
return; return;
dst.create( src.size(), src.type() ); _dst.create( src.size(), src.type() );
CvMat _src = src, _dst = dst; CvMat c_src = src, c_dst = _dst.getMat();
cvPyrMeanShiftFiltering( &_src, &_dst, sp, sr, maxLevel, termcrit ); cvPyrMeanShiftFiltering( &c_src, &c_dst, sp, sr, maxLevel, termcrit );
} }

51
modules/imgproc/src/smooth.cpp
Unescape View File

@ -197,7 +197,9 @@ template<typename ST, typename T> struct ColumnSum : public BaseColumnFilter
}; };
Ptr<BaseRowFilter> getRowSumFilter(int srcType, int sumType, int ksize, int anchor) }
cv::Ptr<cv::BaseRowFilter> cv::getRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{ {
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(sumType); int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(sumType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(srcType) ); CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(srcType) );
@ -232,7 +234,7 @@ Ptr<BaseRowFilter> getRowSumFilter(int srcType, int sumType, int ksize, int anch
} }
Ptr<BaseColumnFilter> getColumnSumFilter(int sumType, int dstType, int ksize, cv::Ptr<cv::BaseColumnFilter> cv::getColumnSumFilter(int sumType, int dstType, int ksize,
int anchor, double scale) int anchor, double scale)
{ {
int sdepth = CV_MAT_DEPTH(sumType), ddepth = CV_MAT_DEPTH(dstType); int sdepth = CV_MAT_DEPTH(sumType), ddepth = CV_MAT_DEPTH(dstType);
@ -272,7 +274,7 @@ Ptr<BaseColumnFilter> getColumnSumFilter(int sumType, int dstType, int ksize,
} }
Ptr<FilterEngine> createBoxFilter( int srcType, int dstType, Size ksize, cv::Ptr<cv::FilterEngine> cv::createBoxFilter( int srcType, int dstType, Size ksize,
Point anchor, bool normalize, int borderType ) Point anchor, bool normalize, int borderType )
{ {
int sdepth = CV_MAT_DEPTH(srcType); int sdepth = CV_MAT_DEPTH(srcType);
@ -292,14 +294,16 @@ Ptr<FilterEngine> createBoxFilter( int srcType, int dstType, Size ksize,
} }
void boxFilter( const Mat& src, Mat& dst, int ddepth, void cv::boxFilter( const InputArray& _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor, Size ksize, Point anchor,
bool normalize, int borderType ) bool normalize, int borderType )
{ {
Mat src = _src.getMat();
int sdepth = src.depth(), cn = src.channels(); int sdepth = src.depth(), cn = src.channels();
if( ddepth < 0 ) if( ddepth < 0 )
ddepth = sdepth; ddepth = sdepth;
dst.create( src.size(), CV_MAKETYPE(ddepth, cn) ); _dst.create( src.size(), CV_MAKETYPE(ddepth, cn) );
Mat dst = _dst.getMat();
if( borderType != BORDER_CONSTANT && normalize ) if( borderType != BORDER_CONSTANT && normalize )
{ {
if( src.rows == 1 ) if( src.rows == 1 )
@ -312,7 +316,7 @@ void boxFilter( const Mat& src, Mat& dst, int ddepth,
f->apply( src, dst ); f->apply( src, dst );
} }
void blur( const Mat& src, CV_OUT Mat& dst, void cv::blur( const InputArray& src, OutputArray dst,
Size ksize, Point anchor, int borderType ) Size ksize, Point anchor, int borderType )
{ {
boxFilter( src, dst, -1, ksize, anchor, true, borderType ); boxFilter( src, dst, -1, ksize, anchor, true, borderType );
@ -322,7 +326,7 @@ void blur( const Mat& src, CV_OUT Mat& dst,
Gaussian Blur Gaussian Blur
\****************************************************************************************/ \****************************************************************************************/
Mat getGaussianKernel( int n, double sigma, int ktype ) cv::Mat cv::getGaussianKernel( int n, double sigma, int ktype )
{ {
const int SMALL_GAUSSIAN_SIZE = 7; const int SMALL_GAUSSIAN_SIZE = 7;
static const float small_gaussian_tab[][SMALL_GAUSSIAN_SIZE] = static const float small_gaussian_tab[][SMALL_GAUSSIAN_SIZE] =
@ -375,7 +379,7 @@ Mat getGaussianKernel( int n, double sigma, int ktype )
} }
Ptr<FilterEngine> createGaussianFilter( int type, Size ksize, cv::Ptr<cv::FilterEngine> cv::createGaussianFilter( int type, Size ksize,
double sigma1, double sigma2, double sigma1, double sigma2,
int borderType ) int borderType )
{ {
@ -406,17 +410,20 @@ Ptr<FilterEngine> createGaussianFilter( int type, Size ksize,
} }
void GaussianBlur( const Mat& src, Mat& dst, Size ksize, void cv::GaussianBlur( const InputArray& _src, OutputArray _dst, Size ksize,
double sigma1, double sigma2, double sigma1, double sigma2,
int borderType ) int borderType )
{ {
Mat src = _src.getMat();
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
if( ksize.width == 1 && ksize.height == 1 ) if( ksize.width == 1 && ksize.height == 1 )
{ {
src.copyTo(dst); src.copyTo(dst);
return; return;
} }
dst.create( src.size(), src.type() );
if( borderType != BORDER_CONSTANT ) if( borderType != BORDER_CONSTANT )
{ {
if( src.rows == 1 ) if( src.rows == 1 )
@ -433,6 +440,9 @@ void GaussianBlur( const Mat& src, Mat& dst, Size ksize,
Median Filter Median Filter
\****************************************************************************************/ \****************************************************************************************/
namespace cv
{
#if _MSC_VER >= 1200 #if _MSC_VER >= 1200
#pragma warning( disable: 4244 ) #pragma warning( disable: 4244 )
#endif #endif
@ -1207,9 +1217,14 @@ medianBlur_SortNet( const Mat& _src, Mat& _dst, int m )
} }
} }
}
void medianBlur( const Mat& src0, Mat& dst, int ksize ) void cv::medianBlur( const InputArray& _src0, OutputArray _dst, int ksize )
{ {
Mat src0 = _src0.getMat();
_dst.create( src0.size(), src0.type() );
Mat dst = _dst.getMat();
if( ksize <= 1 ) if( ksize <= 1 )
{ {
src0.copyTo(dst); src0.copyTo(dst);
@ -1226,7 +1241,6 @@ void medianBlur( const Mat& src0, Mat& dst, int ksize )
#endif #endif
); );
dst.create( src0.size(), src0.type() );
Mat src; Mat src;
if( useSortNet ) if( useSortNet )
{ {
@ -1266,6 +1280,9 @@ void medianBlur( const Mat& src0, Mat& dst, int ksize )
Bilateral Filtering Bilateral Filtering
\****************************************************************************************/ \****************************************************************************************/
namespace cv
{
static void static void
bilateralFilter_8u( const Mat& src, Mat& dst, int d, bilateralFilter_8u( const Mat& src, Mat& dst, int d,
double sigma_color, double sigma_space, double sigma_color, double sigma_space,
@ -1497,12 +1514,16 @@ bilateralFilter_32f( const Mat& src, Mat& dst, int d,
} }
} }
}
void bilateralFilter( const Mat& src, Mat& dst, int d, void cv::bilateralFilter( const InputArray& _src, OutputArray _dst, int d,
double sigmaColor, double sigmaSpace, double sigmaColor, double sigmaSpace,
int borderType ) int borderType )
{ {
dst.create( src.size(), src.type() ); Mat src = _src.getMat();
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
if( src.depth() == CV_8U ) if( src.depth() == CV_8U )
bilateralFilter_8u( src, dst, d, sigmaColor, sigmaSpace, borderType ); bilateralFilter_8u( src, dst, d, sigmaColor, sigmaSpace, borderType );
else if( src.depth() == CV_32F ) else if( src.depth() == CV_32F )
@ -1512,8 +1533,6 @@ void bilateralFilter( const Mat& src, Mat& dst, int d,
"Bilateral filtering is only implemented for 8u and 32f images" ); "Bilateral filtering is only implemented for 8u and 32f images" );
} }
}
////////////////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////////////////
CV_IMPL void CV_IMPL void

138
modules/imgproc/src/sumpixels.cpp
Unescape View File

@ -45,28 +45,17 @@
namespace cv namespace cv
{ {
template<typename QT> inline QT sqr(uchar a) { return a*a; }
template<typename QT> inline QT sqr(float a) { return a*a; }
template<typename QT> inline QT sqr(double a) { return a*a; }
template<> inline double sqr(uchar a) { return CV_8TO32F_SQR(a); }
template<typename T, typename ST, typename QT> template<typename T, typename ST, typename QT>
void integral_( const Mat& _src, Mat& _sum, Mat& _sqsum, Mat& _tilted ) void integral_( const T* src, size_t srcstep, ST* sum, size_t sumstep,
QT* sqsum, size_t sqsumstep, ST* tilted, size_t tiltedstep,
Size size, int cn )
{ {
int cn = _src.channels();
Size size = _src.size();
int x, y, k; int x, y, k;
const T* src = (const T*)_src.data; srcstep /= sizeof(T);
ST* sum = (ST*)_sum.data; sumstep /= sizeof(ST);
ST* tilted = (ST*)_tilted.data; tiltedstep /= sizeof(ST);
QT* sqsum = (QT*)_sqsum.data; sqsumstep /= sizeof(QT);
int srcstep = (int)(_src.step/sizeof(T));
int sumstep = (int)(_sum.step/sizeof(ST));
int tiltedstep = (int)(_tilted.step/sizeof(ST));
int sqsumstep = (int)(_sqsum.step/sizeof(QT));
size.width *= cn; size.width *= cn;
@ -113,7 +102,7 @@ void integral_( const Mat& _src, Mat& _sum, Mat& _sqsum, Mat& _tilted )
{ {
T it = src[x]; T it = src[x];
s += it; s += it;
sq += sqr<QT>(it); sq += (QT)it*it;
ST t = sum[x - sumstep] + s; ST t = sum[x - sumstep] + s;
QT tq = sqsum[x - sqsumstep] + sq; QT tq = sqsum[x - sqsumstep] + sq;
sum[x] = t; sum[x] = t;
@ -128,44 +117,54 @@ void integral_( const Mat& _src, Mat& _sum, Mat& _sqsum, Mat& _tilted )
ST* buf = _buf; ST* buf = _buf;
ST s; ST s;
QT sq; QT sq;
for( k = 0; k < cn; k++, src++, sum++, tilted++, sqsum++, buf++ ) for( k = 0; k < cn; k++, src++, sum++, tilted++, buf++ )
{ {
sum[-cn] = tilted[-cn] = 0; sum[-cn] = tilted[-cn] = 0;
sqsum[-cn] = 0;
for( x = 0, s = 0, sq = 0; x < size.width; x += cn ) for( x = 0, s = 0, sq = 0; x < size.width; x += cn )
{ {
T it = src[x]; T it = src[x];
buf[x] = tilted[x] = it; buf[x] = tilted[x] = it;
s += it; s += it;
sq += sqr<QT>(it); sq += (QT)it*it;
sum[x] = s; sum[x] = s;
if( sqsum )
sqsum[x] = sq; sqsum[x] = sq;
} }
if( size.width == cn ) if( size.width == cn )
buf[cn] = 0; buf[cn] = 0;
if( sqsum )
{
sqsum[-cn] = 0;
sqsum++;
}
} }
for( y = 1; y < size.height; y++ ) for( y = 1; y < size.height; y++ )
{ {
src += srcstep - cn; src += srcstep - cn;
sum += sumstep - cn; sum += sumstep - cn;
sqsum += sqsumstep - cn;
tilted += tiltedstep - cn; tilted += tiltedstep - cn;
buf += -cn; buf += -cn;
for( k = 0; k < cn; k++, src++, sum++, sqsum++, tilted++, buf++ ) if( sqsum )
sqsum += sqsumstep - cn;
for( k = 0; k < cn; k++, src++, sum++, tilted++, buf++ )
{ {
T it = src[0]; T it = src[0];
ST t0 = s = it; ST t0 = s = it;
QT tq0 = sq = sqr<QT>(it); QT tq0 = sq = (QT)it*it;
sum[-cn] = 0; sum[-cn] = 0;
if( sqsum )
sqsum[-cn] = 0; sqsum[-cn] = 0;
tilted[-cn] = tilted[-tiltedstep]; tilted[-cn] = tilted[-tiltedstep];
sum[0] = sum[-sumstep] + t0; sum[0] = sum[-sumstep] + t0;
if( sqsum )
sqsum[0] = sqsum[-sqsumstep] + tq0; sqsum[0] = sqsum[-sqsumstep] + tq0;
tilted[0] = tilted[-tiltedstep] + t0 + buf[cn]; tilted[0] = tilted[-tiltedstep] + t0 + buf[cn];
@ -174,10 +173,11 @@ void integral_( const Mat& _src, Mat& _sum, Mat& _sqsum, Mat& _tilted )
ST t1 = buf[x]; ST t1 = buf[x];
buf[x - cn] = t1 + t0; buf[x - cn] = t1 + t0;
t0 = it = src[x]; t0 = it = src[x];
tq0 = sqr<QT>(it); tq0 = (QT)it*it;
s += t0; s += t0;
sq += tq0; sq += tq0;
sum[x] = sum[x - sumstep] + s; sum[x] = sum[x - sumstep] + s;
if( sqsum )
sqsum[x] = sqsum[x - sqsumstep] + sq; sqsum[x] = sqsum[x - sqsumstep] + sq;
t1 += buf[x + cn] + t0 + tilted[x - tiltedstep - cn]; t1 += buf[x + cn] + t0 + tilted[x - tiltedstep - cn];
tilted[x] = t1; tilted[x] = t1;
@ -188,79 +188,96 @@ void integral_( const Mat& _src, Mat& _sum, Mat& _sqsum, Mat& _tilted )
ST t1 = buf[x]; ST t1 = buf[x];
buf[x - cn] = t1 + t0; buf[x - cn] = t1 + t0;
t0 = it = src[x]; t0 = it = src[x];
tq0 = sqr<QT>(it); tq0 = (QT)it*it;
s += t0; s += t0;
sq += tq0; sq += tq0;
sum[x] = sum[x - sumstep] + s; sum[x] = sum[x - sumstep] + s;
if( sqsum )
sqsum[x] = sqsum[x - sqsumstep] + sq; sqsum[x] = sqsum[x - sqsumstep] + sq;
tilted[x] = t0 + t1 + tilted[x - tiltedstep - cn]; tilted[x] = t0 + t1 + tilted[x - tiltedstep - cn];
buf[x] = t0; buf[x] = t0;
} }
if( sqsum )
sqsum++;
} }
} }
} }
} }
typedef void (*IntegralFunc)(const Mat& _src, Mat& _sum, Mat& _sqsum, Mat& _tilted );
static void #define DEF_INTEGRAL_FUNC(suffix, T, ST, QT) \
integral( const Mat& src, Mat& sum, Mat* _sqsum, Mat* _tilted, int sdepth ) void integral_##suffix( T* src, size_t srcstep, ST* sum, size_t sumstep, QT* sqsum, size_t sqsumstep, \
ST* tilted, size_t tiltedstep, Size size, int cn ) \
{ integral_(src, srcstep, sum, sumstep, sqsum, sqsumstep, tilted, tiltedstep, size, cn); }
DEF_INTEGRAL_FUNC(8u32s, uchar, int, double)
DEF_INTEGRAL_FUNC(8u32f, uchar, float, double)
DEF_INTEGRAL_FUNC(8u64f, uchar, double, double)
DEF_INTEGRAL_FUNC(32f, float, float, float)
DEF_INTEGRAL_FUNC(32f64f, float, double, double)
DEF_INTEGRAL_FUNC(64f, double, double, double)
typedef void (*IntegralFunc)(const uchar* src, size_t srcstep, uchar* sum, size_t sumstep,
uchar* sqsum, size_t sqsumstep, uchar* tilted, size_t tstep,
Size size, int cn );
}
void cv::integral( const InputArray& _src, OutputArray _sum, OutputArray _sqsum, OutputArray _tilted, int sdepth )
{ {
Mat src = _src.getMat(), sum, sqsum, tilted;
int depth = src.depth(), cn = src.channels(); int depth = src.depth(), cn = src.channels();
Size isize(src.cols + 1, src.rows+1); Size isize(src.cols + 1, src.rows+1);
Mat sqsum, tilted;
if( sdepth <= 0 ) if( sdepth <= 0 )
sdepth = depth == CV_8U ? CV_32S : CV_64F; sdepth = depth == CV_8U ? CV_32S : CV_64F;
sdepth = CV_MAT_DEPTH(sdepth); sdepth = CV_MAT_DEPTH(sdepth);
sum.create( isize, CV_MAKETYPE(sdepth, cn) ); _sum.create( isize, CV_MAKETYPE(sdepth, cn) );
sum = _sum.getMat();
if( _tilted )
_tilted->create( isize, CV_MAKETYPE(sdepth, cn) );
else
_tilted = &tilted;
if( !_sqsum ) if( _tilted.needed() )
_sqsum = &sqsum; {
_tilted.create( isize, CV_MAKETYPE(sdepth, cn) );
tilted = _tilted.getMat();
}
if( _sqsum != &sqsum || _tilted->data ) if( _sqsum.needed() )
_sqsum->create( isize, CV_MAKETYPE(CV_64F, cn) ); {
_sqsum.create( isize, CV_MAKETYPE(CV_64F, cn) );
sqsum = _sqsum.getMat();
}
IntegralFunc func = 0; IntegralFunc func = 0;
if( depth == CV_8U && sdepth == CV_32S ) if( depth == CV_8U && sdepth == CV_32S )
func = integral_<uchar, int, double>; func = (IntegralFunc)integral_8u32s;
else if( depth == CV_8U && sdepth == CV_32F ) else if( depth == CV_8U && sdepth == CV_32F )
func = integral_<uchar, float, double>; func = (IntegralFunc)integral_8u32f;
else if( depth == CV_8U && sdepth == CV_64F ) else if( depth == CV_8U && sdepth == CV_64F )
func = integral_<uchar, double, double>; func = (IntegralFunc)integral_8u64f;
else if( depth == CV_32F && sdepth == CV_32F ) else if( depth == CV_32F && sdepth == CV_32F )
func = integral_<float, float, double>; func = (IntegralFunc)integral_32f;
else if( depth == CV_32F && sdepth == CV_64F ) else if( depth == CV_32F && sdepth == CV_64F )
func = integral_<float, double, double>; func = (IntegralFunc)integral_32f64f;
else if( depth == CV_64F && sdepth == CV_64F ) else if( depth == CV_64F && sdepth == CV_64F )
func = integral_<double, double, double>; func = (IntegralFunc)integral_64f;
else else
CV_Error( CV_StsUnsupportedFormat, "" ); CV_Error( CV_StsUnsupportedFormat, "" );
func( src, sum, *_sqsum, *_tilted ); func( src.data, src.step, sum.data, sum.step, sqsum.data, sqsum.step,
tilted.data, tilted.step, src.size(), cn );
} }
void integral( const Mat& src, Mat& sum, int sdepth ) void cv::integral( const InputArray& src, OutputArray sum, int sdepth )
{ {
integral( src, sum, 0, 0, sdepth ); integral( src, sum, OutputArray(), OutputArray(), sdepth );
} }
void integral( const Mat& src, Mat& sum, Mat& sqsum, int sdepth ) void cv::integral( const InputArray& src, OutputArray sum, OutputArray sqsum, int sdepth )
{ {
integral( src, sum, &sqsum, 0, sdepth ); integral( src, sum, sqsum, OutputArray(), sdepth );
}
void integral( const Mat& src, Mat& sum, Mat& sqsum, Mat& tilted, int sdepth )
{
integral( src, sum, &sqsum, &tilted, sdepth );
}
} }
@ -283,7 +300,8 @@ cvIntegral( const CvArr* image, CvArr* sumImage,
tilted0 = tilted = cv::cvarrToMat(tiltedSumImage); tilted0 = tilted = cv::cvarrToMat(tiltedSumImage);
ptilted = &tilted; ptilted = &tilted;
} }
cv::integral( src, sum, psqsum, ptilted, sum.depth() ); cv::integral( src, sum, psqsum ? cv::OutputArray(*psqsum) : cv::OutputArray(),
ptilted ? cv::OutputArray(*ptilted) : cv::OutputArray(), sum.depth() );
CV_Assert( sum.data == sum0.data && sqsum.data == sqsum0.data && tilted.data == tilted0.data ); CV_Assert( sum.data == sum0.data && sqsum.data == sqsum0.data && tilted.data == tilted0.data );
} }

15
modules/imgproc/src/templmatch.cpp
Unescape View File

@ -233,10 +233,11 @@ cv::crossCorr( const Mat& img, const Mat& templ, Mat& corr,
icvCrossCorr( &_img, &_templ, &_corr, anchor, delta, borderType ); icvCrossCorr( &_img, &_templ, &_corr, anchor, delta, borderType );
}*/ }*/
}
/*****************************************************************************************/ /*****************************************************************************************/
void matchTemplate( const Mat& _img, const Mat& _templ, Mat& result, int method ) void cv::matchTemplate( const InputArray& _img, const InputArray& _templ, OutputArray _result, int method )
{ {
CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED ); CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED );
@ -246,17 +247,19 @@ void matchTemplate( const Mat& _img, const Mat& _templ, Mat& result, int method
method == CV_TM_SQDIFF_NORMED || method == CV_TM_SQDIFF_NORMED ||
method == CV_TM_CCOEFF_NORMED; method == CV_TM_CCOEFF_NORMED;
Mat img = _img, templ = _templ; Mat img = _img.getMat(), templ = _templ.getMat();
if( img.rows < templ.rows || img.cols < templ.cols ) if( img.rows < templ.rows || img.cols < templ.cols )
std::swap(img, templ); std::swap(img, templ);
CV_Assert( (img.depth() == CV_8U || img.depth() == CV_32F) && CV_Assert( (img.depth() == CV_8U || img.depth() == CV_32F) &&
img.type() == templ.type() ); img.type() == templ.type() );
Size corrSize(img.cols - templ.cols + 1, img.rows - templ.rows + 1);
_result.create(corrSize, CV_32F);
Mat result = _result.getMat();
int cn = img.channels(); int cn = img.channels();
crossCorr( img, templ, result, crossCorr( img, templ, result, result.size(), result.type(), Point(0,0), 0, 0);
Size(img.cols - templ.cols + 1, img.rows - templ.rows + 1),
CV_32F, Point(0,0), 0, 0);
if( method == CV_TM_CCORR ) if( method == CV_TM_CCORR )
return; return;
@ -368,8 +371,6 @@ void matchTemplate( const Mat& _img, const Mat& _templ, Mat& result, int method
} }
} }
}
CV_IMPL void CV_IMPL void
cvMatchTemplate( const CvArr* _img, const CvArr* _templ, CvArr* _result, int method ) cvMatchTemplate( const CvArr* _img, const CvArr* _templ, CvArr* _result, int method )

58
modules/imgproc/src/thresh.cpp
Unescape View File

@ -475,20 +475,24 @@ getThreshVal_Otsu_8u( const Mat& _src )
return max_val; return max_val;
} }
}
double threshold( const Mat& _src, Mat& _dst, double thresh, double maxval, int type ) double cv::threshold( const InputArray& _src, OutputArray _dst, double thresh, double maxval, int type )
{ {
Mat src = _src.getMat();
bool use_otsu = (type & THRESH_OTSU) != 0; bool use_otsu = (type & THRESH_OTSU) != 0;
type &= THRESH_MASK; type &= THRESH_MASK;
if( use_otsu ) if( use_otsu )
{ {
CV_Assert( _src.type() == CV_8UC1 ); CV_Assert( src.type() == CV_8UC1 );
thresh = getThreshVal_Otsu_8u(_src); thresh = getThreshVal_Otsu_8u(src);
} }
_dst.create( _src.size(), _src.type() ); _dst.create( src.size(), src.type() );
if( _src.depth() == CV_8U ) Mat dst = _dst.getMat();
if( src.depth() == CV_8U )
{ {
int ithresh = cvFloor(thresh); int ithresh = cvFloor(thresh);
thresh = ithresh; thresh = ithresh;
@ -506,16 +510,16 @@ double threshold( const Mat& _src, Mat& _dst, double thresh, double maxval, int
int v = type == THRESH_BINARY ? (ithresh >= 255 ? 0 : imaxval) : int v = type == THRESH_BINARY ? (ithresh >= 255 ? 0 : imaxval) :
type == THRESH_BINARY_INV ? (ithresh >= 255 ? imaxval : 0) : type == THRESH_BINARY_INV ? (ithresh >= 255 ? imaxval : 0) :
type == THRESH_TRUNC ? imaxval : 0; type == THRESH_TRUNC ? imaxval : 0;
_dst = Scalar::all(v); dst = Scalar::all(v);
} }
else else
_src.copyTo(_dst); src.copyTo(dst);
} }
else else
thresh_8u( _src, _dst, (uchar)ithresh, (uchar)imaxval, type ); thresh_8u( src, dst, (uchar)ithresh, (uchar)imaxval, type );
} }
else if( _src.depth() == CV_32F ) else if( src.depth() == CV_32F )
thresh_32f( _src, _dst, (float)thresh, (float)maxval, type ); thresh_32f( src, dst, (float)thresh, (float)maxval, type );
else else
CV_Error( CV_StsUnsupportedFormat, "" ); CV_Error( CV_StsUnsupportedFormat, "" );
@ -523,31 +527,33 @@ double threshold( const Mat& _src, Mat& _dst, double thresh, double maxval, int
} }
void adaptiveThreshold( const Mat& _src, Mat& _dst, double maxValue, void cv::adaptiveThreshold( const InputArray& _src, OutputArray _dst, double maxValue,
int method, int type, int blockSize, double delta ) int method, int type, int blockSize, double delta )
{ {
CV_Assert( _src.type() == CV_8UC1 ); Mat src = _src.getMat();
CV_Assert( src.type() == CV_8UC1 );
CV_Assert( blockSize % 2 == 1 && blockSize > 1 ); CV_Assert( blockSize % 2 == 1 && blockSize > 1 );
Size size = _src.size(); Size size = src.size();
_dst.create( size, _src.type() ); _dst.create( size, src.type() );
Mat dst = _dst.getMat();
if( maxValue < 0 ) if( maxValue < 0 )
{ {
_dst = Scalar(0); dst = Scalar(0);
return; return;
} }
Mat _mean; Mat mean;
if( _src.data != _dst.data ) if( src.data != dst.data )
_mean = _dst; mean = dst;
if( method == ADAPTIVE_THRESH_MEAN_C ) if( method == ADAPTIVE_THRESH_MEAN_C )
boxFilter( _src, _mean, _src.type(), Size(blockSize, blockSize), boxFilter( src, mean, src.type(), Size(blockSize, blockSize),
Point(-1,-1), true, BORDER_REPLICATE ); Point(-1,-1), true, BORDER_REPLICATE );
else if( method == ADAPTIVE_THRESH_GAUSSIAN_C ) else if( method == ADAPTIVE_THRESH_GAUSSIAN_C )
GaussianBlur( _src, _mean, Size(blockSize, blockSize), 0, 0, BORDER_REPLICATE ); GaussianBlur( src, mean, Size(blockSize, blockSize), 0, 0, BORDER_REPLICATE );
else else
CV_Error( CV_StsBadFlag, "Unknown/unsupported adaptive threshold method" ); CV_Error( CV_StsBadFlag, "Unknown/unsupported adaptive threshold method" );
@ -565,7 +571,7 @@ void adaptiveThreshold( const Mat& _src, Mat& _dst, double maxValue,
else else
CV_Error( CV_StsBadFlag, "Unknown/unsupported threshold type" ); CV_Error( CV_StsBadFlag, "Unknown/unsupported threshold type" );
if( _src.isContinuous() && _mean.isContinuous() && _dst.isContinuous() ) if( src.isContinuous() && mean.isContinuous() && dst.isContinuous() )
{ {
size.width *= size.height; size.width *= size.height;
size.height = 1; size.height = 1;
@ -573,15 +579,13 @@ void adaptiveThreshold( const Mat& _src, Mat& _dst, double maxValue,
for( i = 0; i < size.height; i++ ) for( i = 0; i < size.height; i++ )
{ {
const uchar* src = _src.data + _src.step*i; const uchar* sdata = src.data + src.step*i;
const uchar* mean = _mean.data + _mean.step*i; const uchar* mdata = mean.data + mean.step*i;
uchar* dst = _dst.data + _dst.step*i; uchar* ddata = dst.data + dst.step*i;
for( j = 0; j < size.width; j++ ) for( j = 0; j < size.width; j++ )
dst[j] = tab[src[j] - mean[j] + 255]; ddata[j] = tab[sdata[j] - mdata[j] + 255];
}
} }
} }
CV_IMPL double CV_IMPL double

124
modules/imgproc/src/undistort.cpp
Unescape View File

@ -42,12 +42,10 @@
#include "precomp.hpp" #include "precomp.hpp"
namespace cv cv::Mat cv::getDefaultNewCameraMatrix( const InputArray& _cameraMatrix, Size imgsize,
{
Mat getDefaultNewCameraMatrix( const Mat& cameraMatrix, Size imgsize,
bool centerPrincipalPoint ) bool centerPrincipalPoint )
{ {
Mat cameraMatrix = _cameraMatrix.getMat();
if( !centerPrincipalPoint && cameraMatrix.type() == CV_64F ) if( !centerPrincipalPoint && cameraMatrix.type() == CV_64F )
return cameraMatrix; return cameraMatrix;
@ -61,35 +59,42 @@ Mat getDefaultNewCameraMatrix( const Mat& cameraMatrix, Size imgsize,
return newCameraMatrix; return newCameraMatrix;
} }
void initUndistortRectifyMap( const Mat& _cameraMatrix, const Mat& _distCoeffs, void cv::initUndistortRectifyMap( const InputArray& _cameraMatrix, const InputArray& _distCoeffs,
const Mat& matR, const Mat& _newCameraMatrix, const InputArray& _matR, const InputArray& _newCameraMatrix,
Size size, int m1type, Mat& map1, Mat& map2 ) Size size, int m1type, OutputArray _map1, OutputArray _map2 )
{ {
Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();
Mat matR = _matR.getMat(), newCameraMatrix = _newCameraMatrix.getMat();
if( m1type <= 0 ) if( m1type <= 0 )
m1type = CV_16SC2; m1type = CV_16SC2;
CV_Assert( m1type == CV_16SC2 || m1type == CV_32FC1 || m1type == CV_32FC2 ); CV_Assert( m1type == CV_16SC2 || m1type == CV_32FC1 || m1type == CV_32FC2 );
map1.create( size, m1type ); _map1.create( size, m1type );
Mat map1 = _map1.getMat(), map2;
if( m1type != CV_32FC2 ) if( m1type != CV_32FC2 )
map2.create( size, m1type == CV_16SC2 ? CV_16UC1 : CV_32FC1 ); {
_map2.create( size, m1type == CV_16SC2 ? CV_16UC1 : CV_32FC1 );
map2 = _map2.getMat();
}
else else
map2.release(); _map2.release();
Mat_<double> R = Mat_<double>::eye(3, 3), distCoeffs; Mat_<double> R = Mat_<double>::eye(3, 3);
Mat_<double> A = Mat_<double>(_cameraMatrix), Ar; Mat_<double> A = Mat_<double>(cameraMatrix), Ar;
if( _newCameraMatrix.data ) if( newCameraMatrix.data )
Ar = Mat_<double>(_newCameraMatrix); Ar = Mat_<double>(newCameraMatrix);
else else
Ar = getDefaultNewCameraMatrix( A, size, true ); Ar = getDefaultNewCameraMatrix( A, size, true );
if( matR.data ) if( matR.data )
R = Mat_<double>(matR); R = Mat_<double>(matR);
if( _distCoeffs.data ) if( distCoeffs.data )
distCoeffs = Mat_<double>(_distCoeffs); distCoeffs = Mat_<double>(distCoeffs);
else else
{ {
distCoeffs.create(8, 1); distCoeffs.create(8, 1, CV_64F);
distCoeffs = 0.; distCoeffs = 0.;
} }
@ -156,28 +161,33 @@ void initUndistortRectifyMap( const Mat& _cameraMatrix, const Mat& _distCoeffs,
} }
void undistort( const Mat& src, Mat& dst, const Mat& _cameraMatrix, void cv::undistort( const InputArray& _src, OutputArray _dst, const InputArray& _cameraMatrix,
const Mat& _distCoeffs, const Mat& _newCameraMatrix ) const InputArray& _distCoeffs, const InputArray& _newCameraMatrix )
{ {
dst.create( src.size(), src.type() ); Mat src = _src.getMat(), cameraMatrix = _cameraMatrix.getMat();
Mat distCoeffs = _distCoeffs.getMat(), newCameraMatrix = _newCameraMatrix.getMat();
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
CV_Assert( dst.data != src.data ); CV_Assert( dst.data != src.data );
int stripe_size0 = std::min(std::max(1, (1 << 12) / std::max(src.cols, 1)), src.rows); int stripe_size0 = std::min(std::max(1, (1 << 12) / std::max(src.cols, 1)), src.rows);
Mat map1(stripe_size0, src.cols, CV_16SC2), map2(stripe_size0, src.cols, CV_16UC1); Mat map1(stripe_size0, src.cols, CV_16SC2), map2(stripe_size0, src.cols, CV_16UC1);
Mat_<double> A, distCoeffs, Ar, I = Mat_<double>::eye(3,3); Mat_<double> A, Ar, I = Mat_<double>::eye(3,3);
_cameraMatrix.convertTo(A, CV_64F); cameraMatrix.convertTo(A, CV_64F);
if( _distCoeffs.data ) if( distCoeffs.data )
distCoeffs = Mat_<double>(_distCoeffs); distCoeffs = Mat_<double>(distCoeffs);
else else
{ {
distCoeffs.create(5, 1); distCoeffs.create(5, 1, CV_64F);
distCoeffs = 0.; distCoeffs = 0.;
} }
if( _newCameraMatrix.data ) if( newCameraMatrix.data )
_newCameraMatrix.convertTo(Ar, CV_64F); newCameraMatrix.convertTo(Ar, CV_64F);
else else
A.copyTo(Ar); A.copyTo(Ar);
@ -196,8 +206,6 @@ void undistort( const Mat& src, Mat& dst, const Mat& _cameraMatrix,
} }
} }
}
CV_IMPL void CV_IMPL void
cvUndistort2( const CvArr* srcarr, CvArr* dstarr, const CvMat* Aarr, const CvMat* dist_coeffs, const CvMat* newAarr ) cvUndistort2( const CvArr* srcarr, CvArr* dstarr, const CvMat* Aarr, const CvMat* dist_coeffs, const CvMat* newAarr )
@ -373,48 +381,34 @@ void cvUndistortPoints( const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatr
} }
namespace cv void cv::undistortPoints( const InputArray& _src, OutputArray _dst,
const InputArray& _cameraMatrix,
const InputArray& _distCoeffs,
const InputArray& _Rmat,
const InputArray& _Pmat )
{ {
Mat src = _src.getMat(), cameraMatrix = _cameraMatrix.getMat();
Mat distCoeffs = _distCoeffs.getMat(), R = _Rmat.getMat(), P = _Pmat.getMat();
void undistortPoints( const Mat& src, Mat& dst,
const Mat& cameraMatrix, const Mat& distCoeffs,
const Mat& R, const Mat& P )
{
CV_Assert( src.isContinuous() && (src.depth() == CV_32F || src.depth() == CV_64F) && CV_Assert( src.isContinuous() && (src.depth() == CV_32F || src.depth() == CV_64F) &&
((src.rows == 1 && src.channels() == 2) || src.cols*src.channels() == 2)); ((src.rows == 1 && src.channels() == 2) || src.cols*src.channels() == 2));
dst.create(src.size(), src.type()); _dst.create(src.size(), src.type(), -1, true);
CvMat _src = src, _dst = dst, _cameraMatrix = cameraMatrix; Mat dst = _dst.getMat();
CvMat matR, matP, _distCoeffs, *pR=0, *pP=0, *pD=0;
if( R.data )
pR = &(matR = R);
if( P.data )
pP = &(matP = P);
if( distCoeffs.data )
pD = &(_distCoeffs = distCoeffs);
cvUndistortPoints(&_src, &_dst, &_cameraMatrix, pD, pR, pP);
}
void undistortPoints( const Mat& src, std::vector<Point2f>& dst,
const Mat& cameraMatrix, const Mat& distCoeffs,
const Mat& R, const Mat& P )
{
size_t sz = src.cols*src.rows*src.channels()/2;
CV_Assert( src.isContinuous() && src.depth() == CV_32F &&
((src.rows == 1 && src.channels() == 2) || src.cols*src.channels() == 2));
dst.resize(sz); CvMat _csrc = src, _cdst = dst, _ccameraMatrix = cameraMatrix;
CvMat _src = src, _dst = Mat(dst), _cameraMatrix = cameraMatrix; CvMat matR, matP, _cdistCoeffs, *pR=0, *pP=0, *pD=0;
CvMat matR, matP, _distCoeffs, *pR=0, *pP=0, *pD=0;
if( R.data ) if( R.data )
pR = &(matR = R); pR = &(matR = R);
if( P.data ) if( P.data )
pP = &(matP = P); pP = &(matP = P);
if( distCoeffs.data ) if( distCoeffs.data )
pD = &(_distCoeffs = distCoeffs); pD = &(_cdistCoeffs = distCoeffs);
cvUndistortPoints(&_src, &_dst, &_cameraMatrix, pD, pR, pP); cvUndistortPoints(&_csrc, &_cdst, &_ccameraMatrix, pD, pR, pP);
} }
namespace cv
{
static Point2f mapPointSpherical(const Point2f& p, float alpha, Vec4d* J, int projType) static Point2f mapPointSpherical(const Point2f& p, float alpha, Vec4d* J, int projType)
{ {
@ -492,11 +486,13 @@ static Point2f invMapPointSpherical(Point2f _p, float alpha, int projType)
return i < maxiter ? Point2f((float)q[0], (float)q[1]) : Point2f(-FLT_MAX, -FLT_MAX); return i < maxiter ? Point2f((float)q[0], (float)q[1]) : Point2f(-FLT_MAX, -FLT_MAX);
} }
}
float initWideAngleProjMap( const Mat& cameraMatrix0, const Mat& distCoeffs0, float cv::initWideAngleProjMap( const InputArray& _cameraMatrix0, const InputArray& _distCoeffs0,
Size imageSize, int destImageWidth, int m1type, Size imageSize, int destImageWidth, int m1type,
Mat& map1, Mat& map2, int projType, double _alpha ) OutputArray _map1, OutputArray _map2, int projType, double _alpha )
{ {
Mat cameraMatrix0 = _cameraMatrix0.getMat(), distCoeffs0 = _distCoeffs0.getMat();
double k[8] = {0,0,0,0,0,0,0,0}, M[9]={0,0,0,0,0,0,0,0,0}; double k[8] = {0,0,0,0,0,0,0,0}, M[9]={0,0,0,0,0,0,0,0,0};
Mat distCoeffs(distCoeffs0.rows, distCoeffs0.cols, CV_MAKETYPE(CV_64F,distCoeffs0.channels()), k); Mat distCoeffs(distCoeffs0.rows, distCoeffs0.cols, CV_MAKETYPE(CV_64F,distCoeffs0.channels()), k);
Mat cameraMatrix(3,3,CV_64F,M); Mat cameraMatrix(3,3,CV_64F,M);
@ -562,15 +558,15 @@ float initWideAngleProjMap( const Mat& cameraMatrix0, const Mat& distCoeffs0,
if(m1type == CV_32FC2) if(m1type == CV_32FC2)
{ {
_map1.create(mapxy.size(), mapxy.type());
Mat map1 = _map1.getMat();
mapxy.copyTo(map1); mapxy.copyTo(map1);
map2.release(); _map2.release();
} }
else else
convertMaps(mapxy, Mat(), map1, map2, m1type, false); convertMaps(mapxy, Mat(), _map1, _map2, m1type, false);
return scale; return scale;
} }
}
/* End of file */ /* End of file */

10
modules/imgproc/src/utils.cpp
Unescape View File

@ -195,13 +195,17 @@ static void copyMakeConstBorder_8u( const uchar* src, size_t srcstep, Size srcro
memcpy(dst + (i + srcroi.height)*dststep, constBuf, dstroi.width); memcpy(dst + (i + srcroi.height)*dststep, constBuf, dstroi.width);
} }
}
void copyMakeBorder( const Mat& src, Mat& dst, int top, int bottom, void cv::copyMakeBorder( const InputArray& _src, OutputArray _dst, int top, int bottom,
int left, int right, int borderType, const Scalar& value ) int left, int right, int borderType, const Scalar& value )
{ {
Mat src = _src.getMat();
CV_Assert( top >= 0 && bottom >= 0 && left >= 0 && right >= 0 ); CV_Assert( top >= 0 && bottom >= 0 && left >= 0 && right >= 0 );
dst.create( src.rows + top + bottom, src.cols + left + right, src.type() ); _dst.create( src.rows + top + bottom, src.cols + left + right, src.type() );
Mat dst = _dst.getMat();
if( borderType != BORDER_CONSTANT ) if( borderType != BORDER_CONSTANT )
copyMakeBorder_8u( src.data, src.step, src.size(), copyMakeBorder_8u( src.data, src.step, src.size(),
dst.data, dst.step, dst.size(), dst.data, dst.step, dst.size(),
@ -216,8 +220,6 @@ void copyMakeBorder( const Mat& src, Mat& dst, int top, int bottom,
} }
} }
}
CV_IMPL void CV_IMPL void
cvCopyMakeBorder( const CvArr* srcarr, CvArr* dstarr, CvPoint offset, cvCopyMakeBorder( const CvArr* srcarr, CvArr* dstarr, CvPoint offset,

4
modules/imgproc/test/test_imgwarp.cpp
Unescape View File

@ -524,7 +524,7 @@ int CV_WarpAffineTest::prepare_test_case( int test_case_idx )
angle = cvtest::randReal(rng)*360; angle = cvtest::randReal(rng)*360;
scale = ((double)dst.rows/src.rows + (double)dst.cols/src.cols)*0.5; scale = ((double)dst.rows/src.rows + (double)dst.cols/src.cols)*0.5;
getRotationMatrix2D(center, angle, scale).convertTo(mat, mat.depth()); getRotationMatrix2D(center, angle, scale).convertTo(mat, mat.depth());
rng.fill( tmp, CV_RAND_NORMAL, cvScalarAll(1.), cvScalarAll(0.01) ); rng.fill( tmp, CV_RAND_NORMAL, Scalar::all(1.), Scalar::all(0.01) );
cv::max(tmp, 0.9, tmp); cv::max(tmp, 0.9, tmp);
cv::min(tmp, 1.1, tmp); cv::min(tmp, 1.1, tmp);
cv::multiply(tmp, mat, mat, 1.); cv::multiply(tmp, mat, mat, 1.);
@ -639,7 +639,7 @@ int CV_WarpPerspectiveTest::prepare_test_case( int test_case_idx )
float buf[16]; float buf[16];
Mat tmp( 1, 16, CV_32FC1, buf ); Mat tmp( 1, 16, CV_32FC1, buf );
rng.fill( tmp, CV_RAND_NORMAL, cvScalarAll(0.), cvScalarAll(0.1) ); rng.fill( tmp, CV_RAND_NORMAL, Scalar::all(0.), Scalar::all(0.1) );
for( i = 0; i < 4; i++ ) for( i = 0; i < 4; i++ )
{ {

7
modules/ml/src/ann_mlp.cpp
Unescape View File

@ -1228,7 +1228,7 @@ int CvANN_MLP::train_rprop( CvVectors x0, CvVectors u, const double* sw )
__BEGIN__; __BEGIN__;
int i, ivcount, ovcount, l_count, total = 0, max_iter, buf_sz, dcount0, dcount=0; int i, ivcount, ovcount, l_count, total = 0, max_iter, buf_sz, dcount0;
double *buf_ptr; double *buf_ptr;
double prev_E = DBL_MAX*0.5, epsilon; double prev_E = DBL_MAX*0.5, epsilon;
double dw_plus, dw_minus, dw_min, dw_max; double dw_plus, dw_minus, dw_min, dw_max;
@ -1294,10 +1294,7 @@ int CvANN_MLP::train_rprop( CvVectors x0, CvVectors u, const double* sw )
*/ */
for( iter = 0; iter < max_iter; iter++ ) for( iter = 0; iter < max_iter; iter++ )
{ {
int n1, n2, si, j, k; int n1, n2, j, k;
double* w;
CvMat _w, _dEdw, hdr1, hdr2, ghdr1, ghdr2, _df;
CvMat *x1, *x2, *grad1, *grad2, *temp;
double E = 0; double E = 0;
// first, iterate through all the samples and compute dEdw // first, iterate through all the samples and compute dEdw

12
modules/ml/src/knearest.cpp
Unescape View File

@ -355,8 +355,6 @@ float CvKNearest::find_nearest( const CvMat* _samples, int k, CvMat* _results,
float result = 0.f; float result = 0.f;
const int max_blk_count = 128, max_buf_sz = 1 << 12; const int max_blk_count = 128, max_buf_sz = 1 << 12;
int i, count, count_scale, blk_count0, blk_count = 0, buf_sz, k1;
if( !samples ) if( !samples )
CV_Error( CV_StsError, "The search tree must be constructed first using train method" ); CV_Error( CV_StsError, "The search tree must be constructed first using train method" );
@ -395,15 +393,15 @@ float CvKNearest::find_nearest( const CvMat* _samples, int k, CvMat* _results,
"The distances from the neighbors (if present) must be floating-point matrix of <num_samples> x <k> size" ); "The distances from the neighbors (if present) must be floating-point matrix of <num_samples> x <k> size" );
} }
count = _samples->rows; int count = _samples->rows;
count_scale = k*2; int count_scale = k*2;
blk_count0 = MIN( count, max_blk_count ); int blk_count0 = MIN( count, max_blk_count );
buf_sz = MIN( blk_count0 * count_scale, max_buf_sz ); int buf_sz = MIN( blk_count0 * count_scale, max_buf_sz );
blk_count0 = MAX( buf_sz/count_scale, 1 ); blk_count0 = MAX( buf_sz/count_scale, 1 );
blk_count0 += blk_count0 % 2; blk_count0 += blk_count0 % 2;
blk_count0 = MIN( blk_count0, count ); blk_count0 = MIN( blk_count0, count );
buf_sz = blk_count0 * count_scale + k; buf_sz = blk_count0 * count_scale + k;
k1 = get_sample_count(); int k1 = get_sample_count();
k1 = MIN( k1, k ); k1 = MIN( k1, k );
cv::parallel_for(cv::BlockedRange(0, count), P1(this, buf_sz, k, _samples, _neighbors, k1, cv::parallel_for(cv::BlockedRange(0, count), P1(this, buf_sz, k, _samples, _neighbors, k1,

6
modules/ml/test/test_emknearestkmeans.cpp
Unescape View File

@ -203,7 +203,7 @@ void CV_KMeansTest::run( int /*start_from*/ )
int code = cvtest::TS::OK; int code = cvtest::TS::OK;
Mat bestLabels; Mat bestLabels;
// 1. flag==KMEANS_PP_CENTERS // 1. flag==KMEANS_PP_CENTERS
kmeans( data, 3, bestLabels, TermCriteria( TermCriteria::COUNT, iters, 0.0), 0, KMEANS_PP_CENTERS, 0 ); kmeans( data, 3, bestLabels, TermCriteria( TermCriteria::COUNT, iters, 0.0), 0, KMEANS_PP_CENTERS, OutputArray() );
if( calcErr( bestLabels, labels, sizes, false ) > 0.01f ) if( calcErr( bestLabels, labels, sizes, false ) > 0.01f )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy if flag==KMEANS_PP_CENTERS" ); ts->printf( cvtest::TS::LOG, "bad accuracy if flag==KMEANS_PP_CENTERS" );
@ -211,7 +211,7 @@ void CV_KMeansTest::run( int /*start_from*/ )
} }
// 2. flag==KMEANS_RANDOM_CENTERS // 2. flag==KMEANS_RANDOM_CENTERS
kmeans( data, 3, bestLabels, TermCriteria( TermCriteria::COUNT, iters, 0.0), 0, KMEANS_RANDOM_CENTERS, 0 ); kmeans( data, 3, bestLabels, TermCriteria( TermCriteria::COUNT, iters, 0.0), 0, KMEANS_RANDOM_CENTERS, OutputArray() );
if( calcErr( bestLabels, labels, sizes, false ) > 0.01f ) if( calcErr( bestLabels, labels, sizes, false ) > 0.01f )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy if flag==KMEANS_PP_CENTERS" ); ts->printf( cvtest::TS::LOG, "bad accuracy if flag==KMEANS_PP_CENTERS" );
@ -223,7 +223,7 @@ void CV_KMeansTest::run( int /*start_from*/ )
RNG rng; RNG rng;
for( int i = 0; i < 0.5f * pointsCount; i++ ) for( int i = 0; i < 0.5f * pointsCount; i++ )
bestLabels.at<int>( rng.next() % pointsCount, 0 ) = rng.next() % 3; bestLabels.at<int>( rng.next() % pointsCount, 0 ) = rng.next() % 3;
kmeans( data, 3, bestLabels, TermCriteria( TermCriteria::COUNT, iters, 0.0), 0, KMEANS_USE_INITIAL_LABELS, 0 ); kmeans( data, 3, bestLabels, TermCriteria( TermCriteria::COUNT, iters, 0.0), 0, KMEANS_USE_INITIAL_LABELS, OutputArray() );
if( calcErr( bestLabels, labels, sizes, false ) > 0.01f ) if( calcErr( bestLabels, labels, sizes, false ) > 0.01f )
{ {
ts->printf( cvtest::TS::LOG, "bad accuracy if flag==KMEANS_PP_CENTERS" ); ts->printf( cvtest::TS::LOG, "bad accuracy if flag==KMEANS_PP_CENTERS" );

2
modules/objdetect/src/planardetect.cpp
Unescape View File

@ -184,7 +184,7 @@ bool PlanarObjectDetector::operator()(const vector<Mat>& pyr, const vector<KeyPo
return false; return false;
vector<uchar> mask; vector<uchar> mask;
matH = findHomography(Mat(fromPt), Mat(toPt), mask, RANSAC, 10); matH = findHomography(fromPt, toPt, RANSAC, 10, mask);
if( matH.data ) if( matH.data )
{ {
const Mat_<double>& H = matH; const Mat_<double>& H = matH;

14
modules/ts/include/opencv2/ts/ts.hpp
Unescape View File

@ -24,20 +24,6 @@ using cv::Rect;
class CV_EXPORTS TS; class CV_EXPORTS TS;
enum
{
TYPE_MASK_8U = 1 << CV_8U,
TYPE_MASK_8S = 1 << CV_8S,
TYPE_MASK_16U = 1 << CV_16U,
TYPE_MASK_16S = 1 << CV_16S,
TYPE_MASK_32S = 1 << CV_32S,
TYPE_MASK_32F = 1 << CV_32F,
TYPE_MASK_64F = 1 << CV_64F,
TYPE_MASK_ALL = (TYPE_MASK_64F<<1)-1,
TYPE_MASK_ALL_BUT_8S = TYPE_MASK_ALL & ~TYPE_MASK_8S,
TYPE_MASK_FLT = TYPE_MASK_32F + TYPE_MASK_64F
};
CV_EXPORTS int64 readSeed(const char* str); CV_EXPORTS int64 readSeed(const char* str);
CV_EXPORTS void randUni( RNG& rng, Mat& a, const Scalar& param1, const Scalar& param2 ); CV_EXPORTS void randUni( RNG& rng, Mat& a, const Scalar& param1, const Scalar& param2 );

2
modules/ts/src/ts_func.cpp
Unescape View File

@ -71,7 +71,7 @@ int randomType(RNG& rng, int typeMask, int minChannels, int maxChannels)
{ {
int channels = rng.uniform(minChannels, maxChannels+1); int channels = rng.uniform(minChannels, maxChannels+1);
int depth = 0; int depth = 0;
CV_Assert((typeMask & TYPE_MASK_ALL) != 0); CV_Assert((typeMask & DEPTH_MASK_ALL) != 0);
for(;;) for(;;)
{ {
depth = rng.uniform(CV_8U, CV_64F+1); depth = rng.uniform(CV_8U, CV_64F+1);

99
modules/video/include/opencv2/video/background_segm.hpp
Unescape View File

@ -358,7 +358,7 @@ public:
//! the virtual destructor //! the virtual destructor
virtual ~BackgroundSubtractor(); virtual ~BackgroundSubtractor();
//! the update operator that takes the next video frame and returns the current foreground mask as 8-bit binary image. //! the update operator that takes the next video frame and returns the current foreground mask as 8-bit binary image.
CV_WRAP_AS(apply) virtual void operator()(const Mat& image, CV_OUT Mat& fgmask, CV_WRAP_AS(apply) virtual void operator()(const InputArray& image, OutputArray fgmask,
double learningRate=0); double learningRate=0);
}; };
@ -383,7 +383,7 @@ public:
//! the destructor //! the destructor
virtual ~BackgroundSubtractorMOG(); virtual ~BackgroundSubtractorMOG();
//! the update operator //! the update operator
virtual void operator()(const Mat& image, Mat& fgmask, double learningRate=0); virtual void operator()(const InputArray& image, OutputArray fgmask, double learningRate=0);
//! re-initiaization method //! re-initiaization method
virtual void initialize(Size frameSize, int frameType); virtual void initialize(Size frameSize, int frameType);
@ -400,52 +400,73 @@ public:
}; };
class CV_EXPORTS_W BackgroundSubtractorMOG2 : public BackgroundSubtractor class BackgroundSubtractorMOG2 : public BackgroundSubtractor
{ {
public: public:
//! the default constructor //! the default constructor
CV_WRAP BackgroundSubtractorMOG2(); BackgroundSubtractorMOG2();
//! the full constructor that takes the length of the history, the number of gaussian mixtures, the background ratio parameter and the noise strength //! the full constructor that takes the length of the history, the number of gaussian mixtures, the background ratio parameter and the noise strength
CV_WRAP BackgroundSubtractorMOG2(double alphaT, BackgroundSubtractorMOG2(int history, float varThreshold, bool bShadowDetection=1);
double sigma=15,
int nmixtures=5,
bool postFiltering=false,
double minArea=15,
bool detectShadows=true,
bool removeForeground=false,
double Tb=16,
double Tg=9,
double TB=0.9,
double CT=0.05,
int shadowOutputValue=127,
double tau=0.5);
//! the destructor //! the destructor
virtual ~BackgroundSubtractorMOG2(); virtual ~BackgroundSubtractorMOG2();
//! the update operator //! the update operator
virtual void operator()(const Mat& image, Mat& fgmask, double learningRate=0); virtual void operator()(const InputArray& image, OutputArray fgmask, double learningRate=-1);
//! re-initiaization method //! re-initiaization method
virtual void initialize(Size frameSize, virtual void initialize(Size frameSize, int frameType);
double alphaT,
double sigma=15, Size frameSize;
int nmixtures=5, int frameType;
bool postFiltering=false, Mat bgmodel;
double minArea=15, Mat bgmodelUsedModes;//keep track of number of modes per pixel
bool detectShadows=true, int nframes;
bool removeForeground=false, int history;
int nmixtures;
double Tb=16, //! here it is the maximum allowed number of mixture comonents.
double Tg=9, //! Actual number is determined dynamically per pixel
double TB=0.9, float varThreshold;
double CT=0.05, // threshold on the squared Mahalan. dist. to decide if it is well described
//by the background model or not. Related to Cthr from the paper.
int nShadowDetection=127, //This does not influence the update of the background. A typical value could be 4 sigma
double tau=0.5); //and that is varThreshold=4*4=16; Corresponds to Tb in the paper.
void* model; /////////////////////////
//less important parameters - things you might change but be carefull
////////////////////////
float backgroundRatio;
//corresponds to fTB=1-cf from the paper
//TB - threshold when the component becomes significant enough to be included into
//the background model. It is the TB=1-cf from the paper. So I use cf=0.1 => TB=0.
//For alpha=0.001 it means that the mode should exist for approximately 105 frames before
//it is considered foreground
//float noiseSigma;
float varThresholdGen;
//correspondts to Tg - threshold on the squared Mahalan. dist. to decide
//when a sample is close to the existing components. If it is not close
//to any a new component will be generated. I use 3 sigma => Tg=3*3=9.
//Smaller Tg leads to more generated components and higher Tg might make
//lead to small number of components but they can grow too large
float fVarInit;
float fVarMin;
float fVarMax;
//initial variance for the newly generated components.
//It will will influence the speed of adaptation. A good guess should be made.
//A simple way is to estimate the typical standard deviation from the images.
//I used here 10 as a reasonable value
// min and max can be used to further control the variance
float fCT;//CT - complexity reduction prior
//this is related to the number of samples needed to accept that a component
//actually exists. We use CT=0.05 of all the samples. By setting CT=0 you get
//the standard Stauffer&Grimson algorithm (maybe not exact but very similar)
//shadow detection parameters
bool bShadowDetection;//default 1 - do shadow detection
unsigned char nShadowDetection;//do shadow detection - insert this value as the detection result - 127 default value
float fTau;
// Tau - shadow threshold. The shadow is detected if the pixel is darker
//version of the background. Tau is a threshold on how much darker the shadow can be.
//Tau= 0.5 means that if pixel is more than 2 times darker then it is not shadow
//See: Prati,Mikic,Trivedi,Cucchiarra,"Detecting Moving Shadows...",IEEE PAMI,2003.
}; };
} }

31
modules/video/include/opencv2/video/tracking.hpp
Unescape View File

@ -244,30 +244,30 @@ namespace cv
{ {
//! updates motion history image using the current silhouette //! updates motion history image using the current silhouette
CV_EXPORTS_W void updateMotionHistory( const Mat& silhouette, Mat& mhi, CV_EXPORTS_W void updateMotionHistory( const InputArray& silhouette, InputOutputArray mhi,
double timestamp, double duration ); double timestamp, double duration );
//! computes the motion gradient orientation image from the motion history image //! computes the motion gradient orientation image from the motion history image
CV_EXPORTS_W void calcMotionGradient( const Mat& mhi, CV_OUT Mat& mask, CV_EXPORTS_W void calcMotionGradient( const InputArray& mhi, OutputArray mask,
CV_OUT Mat& orientation, OutputArray orientation,
double delta1, double delta2, double delta1, double delta2,
int apertureSize=3 ); int apertureSize=3 );
//! computes the global orientation of the selected motion history image part //! computes the global orientation of the selected motion history image part
CV_EXPORTS_W double calcGlobalOrientation( const Mat& orientation, const Mat& mask, CV_EXPORTS_W double calcGlobalOrientation( const InputArray& orientation, const InputArray& mask,
const Mat& mhi, double timestamp, const InputArray& mhi, double timestamp,
double duration ); double duration );
CV_EXPORTS_W void segmentMotion(const Mat& mhi, Mat& segmask, CV_EXPORTS_W void segmentMotion(const InputArray& mhi, OutputArray segmask,
vector<Rect>& boundingRects, vector<Rect>& boundingRects,
double timestamp, double segThresh); double timestamp, double segThresh);
//! updates the object tracking window using CAMSHIFT algorithm //! updates the object tracking window using CAMSHIFT algorithm
CV_EXPORTS_W RotatedRect CamShift( const Mat& probImage, CV_IN_OUT Rect& window, CV_EXPORTS_W RotatedRect CamShift( const InputArray& probImage, CV_IN_OUT Rect& window,
TermCriteria criteria ); TermCriteria criteria );
//! updates the object tracking window using meanshift algorithm //! updates the object tracking window using meanshift algorithm
CV_EXPORTS_W int meanShift( const Mat& probImage, CV_IN_OUT Rect& window, CV_EXPORTS_W int meanShift( const InputArray& probImage, CV_IN_OUT Rect& window,
TermCriteria criteria ); TermCriteria criteria );
/*! /*!
@ -315,9 +315,9 @@ public:
enum { OPTFLOW_USE_INITIAL_FLOW=4, OPTFLOW_FARNEBACK_GAUSSIAN=256 }; enum { OPTFLOW_USE_INITIAL_FLOW=4, OPTFLOW_FARNEBACK_GAUSSIAN=256 };
//! computes sparse optical flow using multi-scale Lucas-Kanade algorithm //! computes sparse optical flow using multi-scale Lucas-Kanade algorithm
CV_EXPORTS_W void calcOpticalFlowPyrLK( const Mat& prevImg, const Mat& nextImg, CV_EXPORTS_W void calcOpticalFlowPyrLK( const InputArray& prevImg, const InputArray& nextImg,
const vector<Point2f>& prevPts, CV_OUT vector<Point2f>& nextPts, const InputArray& prevPts, CV_OUT InputOutputArray nextPts,
CV_OUT vector<uchar>& status, CV_OUT vector<float>& err, OutputArray status, OutputArray err,
Size winSize=Size(15,15), int maxLevel=3, Size winSize=Size(15,15), int maxLevel=3,
TermCriteria criteria=TermCriteria( TermCriteria criteria=TermCriteria(
TermCriteria::COUNT+TermCriteria::EPS, TermCriteria::COUNT+TermCriteria::EPS,
@ -326,10 +326,15 @@ CV_EXPORTS_W void calcOpticalFlowPyrLK( const Mat& prevImg, const Mat& nextImg,
int flags=0 ); int flags=0 );
//! computes dense optical flow using Farneback algorithm //! computes dense optical flow using Farneback algorithm
CV_EXPORTS_W void calcOpticalFlowFarneback( const Mat& prev, const Mat& next, CV_EXPORTS_W void calcOpticalFlowFarneback( const InputArray& prev, const InputArray& next,
CV_OUT Mat& flow, double pyr_scale, int levels, int winsize, CV_OUT InputOutputArray flow, double pyr_scale, int levels, int winsize,
int iterations, int poly_n, double poly_sigma, int flags ); int iterations, int poly_n, double poly_sigma, int flags );
//! estimates the best-fit Euqcidean, similarity, affine or perspective transformation
// that maps one 2D point set to another or one image to another.
CV_EXPORTS_W Mat estimateRigidTransform( const InputArray& src, const InputArray& dst,
bool fullAffine);
} }
#endif #endif

8
modules/video/src/bgfg_gaussmix.cpp
Unescape View File

@ -59,7 +59,7 @@ namespace cv
{ {
BackgroundSubtractor::~BackgroundSubtractor() {} BackgroundSubtractor::~BackgroundSubtractor() {}
void BackgroundSubtractor::operator()(const Mat&, Mat&, double) void BackgroundSubtractor::operator()(const InputArray&, OutputArray, double)
{ {
} }
@ -381,15 +381,17 @@ static void process8uC3( BackgroundSubtractorMOG& obj, const Mat& image, Mat& fg
} }
} }
void BackgroundSubtractorMOG::operator()(const Mat& image, Mat& fgmask, double learningRate) void BackgroundSubtractorMOG::operator()(const InputArray& _image, OutputArray _fgmask, double learningRate)
{ {
Mat image = _image.getMat();
bool needToInitialize = nframes == 0 || learningRate >= 1 || image.size() != frameSize || image.type() != frameType; bool needToInitialize = nframes == 0 || learningRate >= 1 || image.size() != frameSize || image.type() != frameType;
if( needToInitialize ) if( needToInitialize )
initialize(image.size(), image.type()); initialize(image.size(), image.type());
CV_Assert( image.depth() == CV_8U ); CV_Assert( image.depth() == CV_8U );
fgmask.create( image.size(), CV_8U ); _fgmask.create( image.size(), CV_8U );
Mat fgmask = _fgmask.getMat();
++nframes; ++nframes;
learningRate = learningRate >= 0 && nframes > 1 ? learningRate : 1./min( nframes, history ); learningRate = learningRate >= 0 && nframes > 1 ? learningRate : 1./min( nframes, history );

1241
modules/video/src/bgfg_gaussmix2.cpp
View File

File diff suppressed because it is too large Load Diff

16
modules/video/src/camshift.cpp
Unescape View File

@ -289,29 +289,25 @@ cvCamShift( const void* imgProb, CvRect windowIn,
return itersUsed; return itersUsed;
} }
namespace cv
{
RotatedRect CamShift( const Mat& probImage, Rect& window, cv::RotatedRect cv::CamShift( const InputArray& _probImage, Rect& window,
TermCriteria criteria ) TermCriteria criteria )
{ {
CvConnectedComp comp; CvConnectedComp comp;
CvBox2D box; CvBox2D box;
CvMat _probImage = probImage; CvMat c_probImage = _probImage.getMat();
cvCamShift(&_probImage, window, (CvTermCriteria)criteria, &comp, &box); cvCamShift(&c_probImage, window, (CvTermCriteria)criteria, &comp, &box);
window = comp.rect; window = comp.rect;
return RotatedRect(Point2f(box.center), Size2f(box.size), box.angle); return RotatedRect(Point2f(box.center), Size2f(box.size), box.angle);
} }
int meanShift( const Mat& probImage, Rect& window, TermCriteria criteria ) int cv::meanShift( const InputArray& _probImage, Rect& window, TermCriteria criteria )
{ {
CvConnectedComp comp; CvConnectedComp comp;
CvMat _probImage = probImage; CvMat c_probImage = _probImage.getMat();
int iters = cvMeanShift(&_probImage, window, (CvTermCriteria)criteria, &comp ); int iters = cvMeanShift(&c_probImage, window, (CvTermCriteria)criteria, &comp );
window = comp.rect; window = comp.rect;
return iters; return iters;
} }
}
/* End of file. */ /* End of file. */

55
modules/video/src/lkpyramid.cpp
Unescape View File

@ -42,18 +42,15 @@
#include <float.h> #include <float.h>
#include <stdio.h> #include <stdio.h>
namespace cv void cv::calcOpticalFlowPyrLK( const InputArray& _prevImg, const InputArray& _nextImg,
{ const InputArray& _prevPts, InputOutputArray _nextPts,
OutputArray _status, OutputArray _err,
void calcOpticalFlowPyrLK( const Mat& prevImg, const Mat& nextImg,
const vector<Point2f>& prevPts,
vector<Point2f>& nextPts,
vector<uchar>& status, vector<float>& err,
Size winSize, int maxLevel, Size winSize, int maxLevel,
TermCriteria criteria, TermCriteria criteria,
double derivLambda, double derivLambda,
int flags ) int flags )
{ {
Mat prevImg = _prevImg.getMat(), nextImg = _nextImg.getMat(), prevPtsMat = _prevPts.getMat();
derivLambda = std::min(std::max(derivLambda, 0.), 1.); derivLambda = std::min(std::max(derivLambda, 0.), 1.);
double lambda1 = 1. - derivLambda, lambda2 = derivLambda; double lambda1 = 1. - derivLambda, lambda2 = derivLambda;
const int derivKernelSize = 3; const int derivKernelSize = 3;
@ -66,15 +63,33 @@ void calcOpticalFlowPyrLK( const Mat& prevImg, const Mat& nextImg,
CV_Assert( prevImg.size() == nextImg.size() && CV_Assert( prevImg.size() == nextImg.size() &&
prevImg.type() == nextImg.type() ); prevImg.type() == nextImg.type() );
size_t npoints = prevPts.size(); size_t npoints = prevPtsMat.total();
nextPts.resize(npoints);
status.resize(npoints);
for( size_t i = 0; i < npoints; i++ )
status[i] = true;
err.resize(npoints);
if( npoints == 0 ) if( npoints == 0 )
{
_nextPts.release();
_status.release();
_err.release();
return; return;
}
CV_Assert( prevPtsMat.isContinuous() );
const Point2f* prevPts = (const Point2f*)prevPtsMat.data;
_nextPts.create((int)npoints, 1, prevPtsMat.type(), -1, true);
Mat nextPtsMat = _nextPts.getMat();
CV_Assert( nextPtsMat.isContinuous() );
Point2f* nextPts = (Point2f*)nextPtsMat.data;
_status.create((int)npoints, 1, CV_8U, -1, true);
Mat statusMat = _status.getMat();
CV_Assert( statusMat.isContinuous() );
uchar* status = statusMat.data;
for( size_t i = 0; i < npoints; i++ )
status[i] = true;
_err.create((int)npoints, 1, CV_32F, -1, true);
Mat errMat = _err.getMat();
CV_Assert( errMat.isContinuous() );
float* err = (float*)errMat.data;
vector<Mat> prevPyr, nextPyr; vector<Mat> prevPyr, nextPyr;
@ -334,8 +349,6 @@ void calcOpticalFlowPyrLK( const Mat& prevImg, const Mat& nextImg,
} }
} }
}
static void static void
intersect( CvPoint2D32f pt, CvSize win_size, CvSize imgSize, intersect( CvPoint2D32f pt, CvSize win_size, CvSize imgSize,
CvPoint* min_pt, CvPoint* max_pt ) CvPoint* min_pt, CvPoint* max_pt )
@ -1852,18 +1865,14 @@ cvEstimateRigidTransform( const CvArr* matA, const CvArr* matB, CvMat* matM, int
return 1; return 1;
} }
namespace cv cv::Mat cv::estimateRigidTransform( const InputArray& A,
{ const InputArray& B,
Mat estimateRigidTransform( const Mat& A,
const Mat& B,
bool fullAffine ) bool fullAffine )
{ {
Mat M(2, 3, CV_64F); Mat M(2, 3, CV_64F);
CvMat matA = A, matB = B, matM = M; CvMat matA = A.getMat(), matB = B.getMat(), matM = M;
cvEstimateRigidTransform(&matA, &matB, &matM, fullAffine); cvEstimateRigidTransform(&matA, &matB, &matM, fullAffine);
return M; return M;
} }
}
/* End of file. */ /* End of file. */

34
modules/video/src/motempl.cpp
Unescape View File

@ -442,38 +442,40 @@ cvSegmentMotion( const CvArr* mhiimg, CvArr* segmask, CvMemStorage* storage,
} }
void cv::updateMotionHistory( const Mat& silhouette, Mat& mhi, void cv::updateMotionHistory( const InputArray& _silhouette, InputOutputArray _mhi,
double timestamp, double duration ) double timestamp, double duration )
{ {
CvMat _silhouette = silhouette, _mhi = mhi; CvMat c_silhouette = _silhouette.getMat(), c_mhi = _mhi.getMat();
cvUpdateMotionHistory( &_silhouette, &_mhi, timestamp, duration ); cvUpdateMotionHistory( &c_silhouette, &c_mhi, timestamp, duration );
} }
void cv::calcMotionGradient( const Mat& mhi, Mat& mask, void cv::calcMotionGradient( const InputArray& _mhi, OutputArray _mask,
Mat& orientation, OutputArray _orientation,
double delta1, double delta2, double delta1, double delta2,
int aperture_size ) int aperture_size )
{ {
mask.create(mhi.size(), CV_8U); Mat mhi = _mhi.getMat();
orientation.create(mhi.size(), CV_32F); _mask.create(mhi.size(), CV_8U);
CvMat _mhi = mhi, _mask = mask, _orientation = orientation; _orientation.create(mhi.size(), CV_32F);
cvCalcMotionGradient(&_mhi, &_mask, &_orientation, delta1, delta2, aperture_size); CvMat c_mhi = mhi, c_mask = _mask.getMat(), c_orientation = _orientation.getMat();
cvCalcMotionGradient(&c_mhi, &c_mask, &c_orientation, delta1, delta2, aperture_size);
} }
double cv::calcGlobalOrientation( const Mat& orientation, const Mat& mask, double cv::calcGlobalOrientation( const InputArray& _orientation, const InputArray& _mask,
const Mat& mhi, double timestamp, const InputArray& _mhi, double timestamp,
double duration ) double duration )
{ {
CvMat _orientation = orientation, _mask = mask, _mhi = mhi; CvMat c_orientation = _orientation.getMat(), c_mask = _mask.getMat(), c_mhi = _mhi.getMat();
return cvCalcGlobalOrientation(&_orientation, &_mask, &_mhi, timestamp, duration); return cvCalcGlobalOrientation(&c_orientation, &c_mask, &c_mhi, timestamp, duration);
} }
void cv::segmentMotion(const Mat& mhi, Mat& segmask, void cv::segmentMotion(const InputArray& _mhi, OutputArray _segmask,
vector<Rect>& boundingRects, vector<Rect>& boundingRects,
double timestamp, double segThresh) double timestamp, double segThresh)
{ {
segmask.create(mhi.size(), CV_32F); Mat mhi = _mhi.getMat();
CvMat c_mhi = mhi, c_segmask = segmask; _segmask.create(mhi.size(), CV_32F);
CvMat c_mhi = mhi, c_segmask = _segmask.getMat();
Ptr<CvMemStorage> storage = cvCreateMemStorage(); Ptr<CvMemStorage> storage = cvCreateMemStorage();
Seq<CvConnectedComp> comps = cvSegmentMotion(&c_mhi, &c_segmask, storage, timestamp, segThresh); Seq<CvConnectedComp> comps = cvSegmentMotion(&c_mhi, &c_segmask, storage, timestamp, segThresh);
Seq<CvConnectedComp>::const_iterator it(comps); Seq<CvConnectedComp>::const_iterator it(comps);

13
modules/video/src/optflowgf.cpp
Unescape View File

@ -561,22 +561,24 @@ FarnebackUpdateFlow_GaussianBlur( const Mat& _R0, const Mat& _R1,
} }
} }
}
void calcOpticalFlowFarneback( const Mat& prev0, const Mat& next0, void cv::calcOpticalFlowFarneback( const InputArray& _prev0, const InputArray& _next0,
Mat& flow0, double pyr_scale, int levels, int winsize, OutputArray _flow0, double pyr_scale, int levels, int winsize,
int iterations, int poly_n, double poly_sigma, int flags ) int iterations, int poly_n, double poly_sigma, int flags )
{ {
Mat prev0 = _prev0.getMat(), next0 = _next0.getMat();
const int min_size = 32; const int min_size = 32;
const Mat* img[2] = { &prev0, &next0 }; const Mat* img[2] = { &prev0, &next0 };
Mat fimg;
int i, k; int i, k;
double scale; double scale;
Mat prevFlow, flow; Mat prevFlow, flow, fimg;
CV_Assert( prev0.size() == next0.size() && prev0.channels() == next0.channels() && CV_Assert( prev0.size() == next0.size() && prev0.channels() == next0.channels() &&
prev0.channels() == 1 && pyr_scale < 1 ); prev0.channels() == 1 && pyr_scale < 1 );
flow0.create( prev0.size(), CV_32FC2 ); _flow0.create( prev0.size(), CV_32FC2 );
Mat flow0 = _flow0.getMat();
for( k = 0, scale = 1; k < levels; k++ ) for( k = 0, scale = 1; k < levels; k++ )
{ {
@ -643,7 +645,6 @@ void calcOpticalFlowFarneback( const Mat& prev0, const Mat& next0,
} }
} }
}
CV_IMPL void cvCalcOpticalFlowFarneback( CV_IMPL void cvCalcOpticalFlowFarneback(
const CvArr* _prev, const CvArr* _next, const CvArr* _prev, const CvArr* _next,

17
modules/video/test/test_motiontemplates.cpp
Unescape View File

@ -169,12 +169,15 @@ double CV_UpdateMHITest::get_success_error_level( int /*test_case_idx*/, int /*i
void CV_UpdateMHITest::run_func() void CV_UpdateMHITest::run_func()
{ {
cvUpdateMotionHistory( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], timestamp, duration ); CvMat m = test_mat[INPUT_OUTPUT][0];
cv::updateMotionHistory( test_mat[INPUT][0], test_mat[INPUT_OUTPUT][0], timestamp, duration);
m = test_mat[INPUT_OUTPUT][0];
} }
void CV_UpdateMHITest::prepare_to_validation( int /*test_case_idx*/ ) void CV_UpdateMHITest::prepare_to_validation( int /*test_case_idx*/ )
{ {
CvMat m0 = test_mat[REF_INPUT_OUTPUT][0];
test_updateMHI( test_mat[INPUT][0], test_mat[REF_INPUT_OUTPUT][0], timestamp, duration ); test_updateMHI( test_mat[INPUT][0], test_mat[REF_INPUT_OUTPUT][0], timestamp, duration );
} }
@ -290,8 +293,10 @@ double CV_MHIGradientTest::get_success_error_level( int /*test_case_idx*/, int /
void CV_MHIGradientTest::run_func() void CV_MHIGradientTest::run_func()
{ {
cvCalcMotionGradient( test_array[INPUT][0], test_array[OUTPUT][0], cv::calcMotionGradient(test_mat[INPUT][0], test_mat[OUTPUT][0],
test_array[OUTPUT][1], delta1, delta2, aperture_size ); test_mat[OUTPUT][1], delta1, delta2, aperture_size );
//cvCalcMotionGradient( test_array[INPUT][0], test_array[OUTPUT][0],
// test_array[OUTPUT][1], delta1, delta2, aperture_size );
} }
@ -453,8 +458,10 @@ double CV_MHIGlobalOrientTest::get_success_error_level( int /*test_case_idx*/, i
void CV_MHIGlobalOrientTest::run_func() void CV_MHIGlobalOrientTest::run_func()
{ {
angle = cvCalcGlobalOrientation( test_array[INPUT][2], test_array[INPUT][1], //angle = cvCalcGlobalOrientation( test_array[INPUT][2], test_array[INPUT][1],
test_array[INPUT][0], timestamp, duration ); // test_array[INPUT][0], timestamp, duration );
angle = cv::calcGlobalOrientation(test_mat[INPUT][2], test_mat[INPUT][1],
test_mat[INPUT][0], timestamp, duration );
} }

Write Preview
Loading…
Cancel
Save