Class: OpenCV::CvMat

Inherits:
Object
  • Object
show all
Defined in:
ext/opencv/cvmat.cpp,
ext/opencv/iplimage.cpp

Direct Known Subclasses

IplImage

Constant Summary collapse

DRAWING_OPTION = 
drawing_option
GOOD_FEATURES_TO_TRACK_OPTION = 
good_features_to_track_option
FLOOD_FILL_OPTION = 
flood_fill_option
FIND_CONTOURS_OPTION = 
find_contours_option
OPTICAL_FLOW_HS_OPTION = 
optical_flow_hs_option
OPTICAL_FLOW_BM_OPTION = 
optical_flow_bm_option
FIND_FUNDAMENTAL_MAT_OPTION = 
find_fundamental_matrix_option
ORB_OPTION = 
orb_option
HIST_OPTION = 
hist_option

Class Method Summary collapse

Instance Method Summary collapse

Dynamic Method Handling

This class handles dynamic methods through the method_missing method

#method_missing(*args) ⇒ Object

nodoc



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# File 'ext/opencv/cvmat.cpp', line 338

VALUE
rb_method_missing(int argc, VALUE *argv, VALUE self)
{
  VALUE name, args, method;
  rb_scan_args(argc, argv, "1*", &name, &args);
  method = rb_funcall(name, rb_intern("to_s"), 0);
  if (RARRAY_LEN(args) != 0 || !rb_respond_to(rb_module_opencv(), rb_intern(StringValuePtr(method))))
    return rb_call_super(argc, argv);
  return rb_funcall(rb_module_opencv(), rb_intern(StringValuePtr(method)), 1, self);
}

Class Method Details

.add_weighted(src1, alpha, src2, beta, gamma) ⇒ CvMat

Computes the weighted sum of two arrays. This function calculates the weighted sum of two arrays as follows:

dst(I) = src1(I) * alpha + src2(I) * beta + gamma

Parameters:

  • src1 (CvMat) —

    The first source array.

  • alpha (Number) —

    Weight for the first array elements.

  • src2 (CvMat) —

    The second source array.

  • beta (Number) —

    Weight for the second array elements.

  • gamma (Number) —

    Scalar added to each sum.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 1944

VALUE
rb_add_weighted(VALUE klass, VALUE src1, VALUE alpha, VALUE src2, VALUE beta, VALUE gamma)
{
  CvArr* src1_ptr = CVARR_WITH_CHECK(src1);
  VALUE dst = new_mat_kind_object(cvGetSize(src1_ptr), src1);
  try {
    cvAddWeighted(src1_ptr, NUM2DBL(alpha),
		  CVARR_WITH_CHECK(src2), NUM2DBL(beta),
		  NUM2DBL(gamma), CVARR(dst));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dst;
}

.compute_correspond_epilines(points, which_image, fundamental_matrix) ⇒ Object

For points in one image of stereo pair computes the corresponding epilines in the other image. Finds equation of a line that contains the corresponding point (i.e. projection of the same 3D point) in the other image. Each line is encoded by a vector of 3 elements l=T, so that:

lT*[x, y, 1]T=0,

or

a*x + b*y + c = 0

From the fundamental matrix definition (see cvFindFundamentalMatrix discussion), line l2 for a point p1 in the first image (which_image=1) can be computed as:

l2=F*p1

and the line l1 for a point p2 in the second image (which_image=1) can be computed as:

l1=FT*p2

Line coefficients are defined up to a scale. They are normalized (a2+b2=1) are stored into correspondent_lines.



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# File 'ext/opencv/cvmat.cpp', line 6325

VALUE
rb_compute_correspond_epilines(VALUE klass, VALUE points, VALUE which_image, VALUE fundamental_matrix)
{
  VALUE correspondent_lines;
  CvMat* points_ptr = CVMAT_WITH_CHECK(points);
  int n;
  if (points_ptr->cols <= 3 && points_ptr->rows >= 7)
    n = points_ptr->rows;
  else if (points_ptr->rows <= 3 && points_ptr->cols >= 7)
    n = points_ptr->cols;
  else
    rb_raise(rb_eArgError, "input points should 2xN, Nx2 or 3xN, Nx3 matrix(N >= 7).");
  
  correspondent_lines = cCvMat::new_object(n, 3, CV_MAT_DEPTH(points_ptr->type));
  try {
    cvComputeCorrespondEpilines(points_ptr, NUM2INT(which_image), CVMAT_WITH_CHECK(fundamental_matrix),
				CVMAT(correspondent_lines));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return correspondent_lines;
}

.decode_image(buf, iscolor = 1) ⇒ CvMat

Reads an image from a buffer in memory.

Parameters:

  • buf (CvMat, Array, String) —

    Input array of bytes

  • iscolor (Integer) —

    Flags specifying the color type of a decoded image (the same flags as CvMat#load)

Returns:

  • (CvMat) —

    Loaded matrix



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# File 'ext/opencv/cvmat.cpp', line 316

VALUE
rb_decode_imageM(int argc, VALUE *argv, VALUE self)
{
  int iscolor, need_release;
  CvMat* buff = prepare_decoding(argc, argv, &iscolor, &need_release);
  CvMat* mat_ptr = NULL;
  try {
    mat_ptr = cvDecodeImageM(buff, iscolor);
    if (need_release) {
      cvReleaseMat(&buff);
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return OPENCV_OBJECT(rb_klass, mat_ptr);
}

.decode_image(buf, iscolor = 1) ⇒ CvMat

Reads an image from a buffer in memory.

Parameters:

  • buf (CvMat, Array, String) —

    Input array of bytes

  • iscolor (Integer) —

    Flags specifying the color type of a decoded image (the same flags as CvMat#load)

Returns:

  • (CvMat) —

    Loaded matrix



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# File 'ext/opencv/cvmat.cpp', line 316

VALUE
rb_decode_imageM(int argc, VALUE *argv, VALUE self)
{
  int iscolor, need_release;
  CvMat* buff = prepare_decoding(argc, argv, &iscolor, &need_release);
  CvMat* mat_ptr = NULL;
  try {
    mat_ptr = cvDecodeImageM(buff, iscolor);
    if (need_release) {
      cvReleaseMat(&buff);
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return OPENCV_OBJECT(rb_klass, mat_ptr);
}

.find_fundamental_mat(points1, points2[,options = {}]) ⇒ nil

Calculates fundamental matrix from corresponding points. Size of the output fundamental matrix is 3x3 or 9x3 (7-point method may return up to 3 matrices)

points1 and points2 should be 2xN, Nx2, 3xN or Nx3 1-channel, or 1xN or Nx1 multi-channel matrix. <i>method<i> is method for computing the fundamental matrix

- CV_FM_7POINT for a 7-point algorithm. (N = 7)
- CV_FM_8POINT for an 8-point algorithm. (N >= 8)
- CV_FM_RANSAC for the RANSAC algorithm. (N >= 8)
- CV_FM_LMEDS for the LMedS algorithm. (N >= 8)

option should be Hash include these keys.

:with_status (true or false)
   If set true, return fundamental_matrix and status. [fundamental_matrix, status]
   Otherwise return fundamental matrix only(default).
:maximum_distance
   The parameter is used for RANSAC.  It is the maximum distance from point to epipolar line in pixels, beyond which the point is considered an outlier and is not used for computing the final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the point localization, image resolution and the image noise.
:desirable_level
   The optional output array of N elements, every element of which is set to 0 for outliers and to 1 for the other points. The array is computed only in RANSAC and LMedS methods. For other methods it is set to all 1's.

note: option’s default value is CvMat::FIND_FUNDAMENTAL_MAT_OPTION.

Returns:

  • (nil) 


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# File 'ext/opencv/cvmat.cpp', line 6269

VALUE
rb_find_fundamental_mat(int argc, VALUE *argv, VALUE klass)
{
  VALUE points1, points2, method, option, fundamental_matrix, status;
  int num = 0;
  rb_scan_args(argc, argv, "31", &points1, &points2, &method, &option);
  option = FIND_FUNDAMENTAL_MAT_OPTION(option);
  int fm_method = FIX2INT(method);
  CvMat *points1_ptr = CVMAT_WITH_CHECK(points1);
  if (fm_method == CV_FM_7POINT)
    fundamental_matrix = cCvMat::new_object(9, 3, CV_MAT_DEPTH(points1_ptr->type));
  else
    fundamental_matrix = cCvMat::new_object(3, 3, CV_MAT_DEPTH(points1_ptr->type));

  if (FFM_WITH_STATUS(option)) {
    int status_len = (points1_ptr->rows > points1_ptr->cols) ? points1_ptr->rows : points1_ptr->cols;
    status = cCvMat::new_object(1, status_len, CV_8UC1);
    try {
      num = cvFindFundamentalMat(points1_ptr, CVMAT_WITH_CHECK(points2), CVMAT(fundamental_matrix), fm_method,
				 FFM_MAXIMUM_DISTANCE(option), FFM_DESIRABLE_LEVEL(option), CVMAT(status));
    }
    catch (cv::Exception& e) {
      raise_cverror(e);
    }
    return num == 0 ? Qnil : rb_ary_new3(2, fundamental_matrix, status);
  }
  else {
    try {
      num = cvFindFundamentalMat(points1_ptr, CVMAT_WITH_CHECK(points2), CVMAT(fundamental_matrix), fm_method,
				 FFM_MAXIMUM_DISTANCE(option), FFM_DESIRABLE_LEVEL(option), NULL);
    }
    catch (cv::Exception& e) {
      raise_cverror(e);
    }
    return num == 0 ? Qnil : fundamental_matrix;
  }
}

.find_homography(src_points, dst_points, method = :all, ransac_reproj_threshold = 3, get_mask = false) ⇒ CvMat+

Finds a perspective transformation between two planes.

Parameters:

  • src_points (CvMat) —

    Coordinates of the points in the original plane.

  • dst_points (CvMat) —

    Coordinates of the points in the target plane.

  • method (Symbol) (defaults to: :all) —

    Method used to computed a homography matrix. The following methods are possible:

    • :all - a regular method using all the points

    • :ransac - RANSAC-based robust method

    • :lmeds - Least-Median robust method

  • ransac_reproj_threshold (Number) (defaults to: 3) —

    Maximum allowed reprojection error to treat a point pair as an inlier (used in the RANSAC method only).

  • get_mask (Boolean) (defaults to: false) —

    If true, the optional output mask set by a robust method (:ransac or :lmeds) is returned additionally.

Returns:

  • (CvMat, Array<CvMat>) —

    The perspective transformation H between the source and the destination planes in CvMat. If method is :ransac or :lmeds and get_mask is true, the output mask is also returned in the form of an array [H, output_mask].



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# File 'ext/opencv/cvmat.cpp', line 4256

VALUE
rb_find_homography(int argc, VALUE *argv, VALUE self)
{
  VALUE src_points, dst_points, method, ransac_reproj_threshold, get_status;
  rb_scan_args(argc, argv, "23", &src_points, &dst_points, &method, &ransac_reproj_threshold, &get_status);

  VALUE homography = new_object(cvSize(3, 3), CV_32FC1);
  int _method = CVMETHOD("HOMOGRAPHY_CALC_METHOD", method, 0);
  double _ransac_reproj_threshold = NIL_P(ransac_reproj_threshold) ? 0.0 : NUM2DBL(ransac_reproj_threshold);

  if ((_method != 0) && (!NIL_P(get_status)) && IF_BOOL(get_status, 1, 0, 0)) {
    CvMat *src = CVMAT_WITH_CHECK(src_points);
    int num_points = MAX(src->rows, src->cols);
    VALUE status = new_object(cvSize(num_points, 1), CV_8UC1);
    try {
      cvFindHomography(src, CVMAT_WITH_CHECK(dst_points), CVMAT(homography),
		       _method, _ransac_reproj_threshold, CVMAT(status));
    }
    catch (cv::Exception& e) {
      raise_cverror(e);
    }
    return rb_assoc_new(homography, status);
  }
  else {
    try {
      cvFindHomography(CVMAT(src_points), CVMAT(dst_points), CVMAT(homography),
		       _method, _ransac_reproj_threshold, NULL);
    }
    catch (cv::Exception& e) {
      raise_cverror(e);
    }
    return homography;
  }
}

.get_perspective_transform(src, dst) ⇒ CvMat

Calculates a perspective transform from four pairs of the corresponding points.

Parameters:

  • src (Array<CvPoint>) —

    Coordinates of quadrangle vertices in the source image.

  • dst (Array<CvPoint>) —

    Coordinates of the corresponding quadrangle vertices in the destination image.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 4326

VALUE
rb_get_perspective_transform(VALUE self, VALUE source, VALUE dest)
{
  Check_Type(source, T_ARRAY);
  Check_Type(dest, T_ARRAY);

  int count = RARRAY_LEN(source);

  CvPoint2D32f* source_buff = RB_ALLOC_N(CvPoint2D32f, count);
  CvPoint2D32f* dest_buff = RB_ALLOC_N(CvPoint2D32f, count);

  for (int i = 0; i < count; i++) {
    source_buff[i] = *(CVPOINT2D32F(RARRAY_PTR(source)[i]));
    dest_buff[i] = *(CVPOINT2D32F(RARRAY_PTR(dest)[i]));
  }

  VALUE map_matrix = new_object(cvSize(3, 3), CV_MAKETYPE(CV_32F, 1));

  try {
    cvGetPerspectiveTransform(source_buff, dest_buff, CVMAT(map_matrix));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return map_matrix;
}

.load(filename, iscolor = 1) ⇒ CvMat

Load an image from the specified file

Parameters:

  • filename (String) —

    Name of file to be loaded

  • iscolor (Integer) —

    Flags specifying the color type of a loaded image:

    • > 0 Return a 3-channel color image.

    • = 0 Return a grayscale image.

    • < 0 Return the loaded image as is.

Returns:

  • (CvMat) —

    Loaded image



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# File 'ext/opencv/cvmat.cpp', line 172

VALUE
rb_load_imageM(int argc, VALUE *argv, VALUE self)
{
  VALUE filename, iscolor;
  rb_scan_args(argc, argv, "11", &filename, &iscolor);
  Check_Type(filename, T_STRING);

  int _iscolor;
  if (NIL_P(iscolor)) {
    _iscolor = CV_LOAD_IMAGE_COLOR;
  }
  else {
    Check_Type(iscolor, T_FIXNUM);
    _iscolor = FIX2INT(iscolor);
  }

  CvMat *mat = NULL;
  try {
    mat = cvLoadImageM(StringValueCStr(filename), _iscolor);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  if (mat == NULL) {
    rb_raise(rb_eStandardError, "file does not exist or invalid format image.");
  }
  return OPENCV_OBJECT(rb_klass, mat);
}

.merge(src1 = nil, src2 = nil, src3 = nil, src4 = nil) ⇒ CvMat

Composes a multi-channel array from several single-channel arrays.

Parameters:

  • src-n (CvMat) —

    Source arrays to be merged. All arrays must have the same size and the same depth.

Returns:

  • (CvMat) —

    Merged array

See Also:



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# File 'ext/opencv/cvmat.cpp', line 1582

VALUE
rb_merge(VALUE klass, VALUE args)
{
  int len = RARRAY_LEN(args);
  if (len <= 0 || len > 4) {
    rb_raise(rb_eArgError, "wrong number of argument (%d for 1..4)", len);
  }
  CvMat *src[] = { NULL, NULL, NULL, NULL }, *prev_src = NULL;
  for (int i = 0; i < len; ++i) {
    VALUE object = rb_ary_entry(args, i);
    if (NIL_P(object))
      src[i] = NULL;
    else {
      src[i] = CVMAT_WITH_CHECK(object);
      if (CV_MAT_CN(src[i]->type) != 1)
        rb_raise(rb_eArgError, "image should be single-channel CvMat.");
      if (prev_src == NULL)
        prev_src = src[i];
      else {
        if (!CV_ARE_SIZES_EQ(prev_src, src[i]))
          rb_raise(rb_eArgError, "image size should be same.");
        if (!CV_ARE_DEPTHS_EQ(prev_src, src[i]))
          rb_raise(rb_eArgError, "image depth should be same.");
      }
    }
  }
  // TODO: adapt IplImage
  VALUE dest = Qnil;
  try {
    dest = new_object(cvGetSize(src[0]), CV_MAKETYPE(CV_MAT_DEPTH(src[0]->type), len));
    cvMerge(src[0], src[1], src[2], src[3], CVARR(dest));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

.rotation_matrix2D(center, angle, scale) ⇒ CvMat

Calculates an affine matrix of 2D rotation.

Parameters:

  • center (CvPoint2D32f) —

    Center of the rotation in the source image.

  • angle (Number) —

    Rotation angle in degrees. Positive values mean counter-clockwise rotation (the coordinate origin is assumed to be the top-left corner).

  • scale (Number) —

    Isotropic scale factor.

Returns:

  • (CvMat) —

    The output affine transformation, 2x3 floating-point matrix.



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# File 'ext/opencv/cvmat.cpp', line 4303

VALUE
rb_rotation_matrix2D(VALUE self, VALUE center, VALUE angle, VALUE scale)
{
  VALUE map_matrix = new_object(cvSize(3, 2), CV_MAKETYPE(CV_32F, 1));
  try {
    cv2DRotationMatrix(VALUE_TO_CVPOINT2D32F(center), NUM2DBL(angle), NUM2DBL(scale), CVMAT(map_matrix));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return map_matrix;
}

.solve(src1, src2, inversion_method = :lu) ⇒ Number

Solves one or more linear systems or least-squares problems.

Parameters:

  • src1 (CvMat) —

    Input matrix on the left-hand side of the system.

  • src2 (CvMat) —

    Input matrix on the right-hand side of the system.

  • inversion_method (Symbol) —

    Inversion method.

    • :lu - Gaussian elimincation with optimal pivot element chose.

    • :svd - Singular value decomposition(SVD) method.

    • :svd_sym - SVD method for a symmetric positively-defined matrix.

Returns:

  • (Number) —

    Output solution.



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# File 'ext/opencv/cvmat.cpp', line 2849

VALUE
rb_solve(int argc, VALUE *argv, VALUE self)
{
  VALUE src1, src2, symbol;
  rb_scan_args(argc, argv, "21", &src1, &src2, &symbol);
  VALUE dest = Qnil;
  CvArr* src2_ptr = CVARR_WITH_CHECK(src2);
  try {
    dest = new_mat_kind_object(cvGetSize(src2_ptr), src2);
    cvSolve(CVARR_WITH_CHECK(src1), src2_ptr, CVARR(dest), CVMETHOD("INVERSION_METHOD", symbol, CV_LU));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

Instance Method Details

#[](idx0) ⇒ CvScalar #[](idx0, idx1) ⇒ CvScalar #[](idx0, idx1, idx2) ⇒ CvScalar #[](idx0, idx1, idx2, ...) ⇒ CvScalar Also known as: at

Returns a specific array element.

Parameters:

  • idx-n (Integer) —

    Zero-based component of the element index

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1008

VALUE
rb_aref(VALUE self, VALUE args)
{
  int index[CV_MAX_DIM];
  for (int i = 0; i < RARRAY_LEN(args); ++i)
    index[i] = NUM2INT(rb_ary_entry(args, i));
  
  CvScalar scalar = cvScalarAll(0);
  try {
    switch (RARRAY_LEN(args)) {
    case 1:
      scalar = cvGet1D(CVARR(self), index[0]);
      break;
    case 2:
      scalar = cvGet2D(CVARR(self), index[0], index[1]);
      break;
    default:
      scalar = cvGetND(CVARR(self), index);
      break;      
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return cCvScalar::new_object(scalar);
}

#[]=(idx0, value) ⇒ CvMat #[]=(idx0, idx1, value) ⇒ CvMat #[]=(idx0, idx1, idx2, value) ⇒ CvMat #[]=(idx0, idx1, idx2, ..., value) ⇒ CvMat

Changes the particular array element

Parameters:

  • idx-n (Integer) —

    Zero-based component of the element index

  • value (CvScalar) —

    The assigned value

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1099

VALUE
rb_aset(VALUE self, VALUE args)
{
  CvScalar scalar = VALUE_TO_CVSCALAR(rb_ary_pop(args));
  int index[CV_MAX_DIM];
  for (int i = 0; i < RARRAY_LEN(args); ++i)
    index[i] = NUM2INT(rb_ary_entry(args, i));

  try {
    switch (RARRAY_LEN(args)) {
    case 1:
      cvSet1D(CVARR(self), index[0], scalar);
      break;
    case 2:
      cvSet2D(CVARR(self), index[0], index[1], scalar);
      break;
    default:
      cvSetND(CVARR(self), index, scalar);
      break;
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#abs_diff(val) ⇒ CvMat

Computes the per-element absolute difference between two arrays or between an array and a scalar.

Parameters:

  • val (CvMat, CvScalar) —

    Array or scalar to compute absolute difference

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2270

VALUE
rb_abs_diff(VALUE self, VALUE val)
{
  CvArr* self_ptr = CVARR(self);
  VALUE dest = new_mat_kind_object(cvGetSize(self_ptr), self);
  try {
    if (rb_obj_is_kind_of(val, rb_klass))
      cvAbsDiff(self_ptr, CVARR(val), CVARR(dest));
    else
      cvAbsDiffS(self_ptr, CVARR(dest), VALUE_TO_CVSCALAR(val));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#adaptive_threshold(max_value, options) ⇒ CvMat

Applies an adaptive threshold to an array.

Examples:

mat = CvMat.new(3, 3, CV_8U, 1)
mat.set_data([1, 2, 3, 4, 5, 6, 7, 8, 9])
mat #=> [1, 2, 3,
         4, 5, 6,
         7, 8, 9]
result = mat.adaptive_threshold(7, threshold_type: CV_THRESH_BINARY,
                                adaptive_method: CV_ADAPTIVE_THRESH_MEAN_C,
                                block_size: 3, param1: 1)
result #=> [0, 0, 0,
            7, 7, 7,
            7, 7, 7]

Returns Destination image of the same size and the same type as self.

Parameters:

  • max_value (Number) —

    Non-zero value assigned to the pixels for which the condition is satisfied.

  • options (Hash) —

    Threshold option

Options Hash (options):

  • :threshold_type (Integer, Symbol) — default: CV_THRESH_BINARY —

    Thresholding type; must be one of CV_THRESH_BINARY or :binary, CV_THRESH_BINARY_INV or :binary_inv.

  • :adaptive_method (Integer, Symbol) — default: CV_ADAPTIVE_THRESH_MEAN_C —

    Adaptive thresholding algorithm to use: CV_ADAPTIVE_THRESH_MEAN_C or :mean_c, CV_ADAPTIVE_THRESH_GAUSSIAN_C or :gaussian_c.

  • :block_size (Integer) — default: 3 —

    The size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on.

  • :param1 (Number) — default: 5 —

    The method-dependent parameter. For the methods CV_ADAPTIVE_THRESH_MEAN_C and CV_ADAPTIVE_THRESH_GAUSSIAN_C it is a constant subtracted from the mean or weighted mean, though it may be negative

Returns:

  • (CvMat) —

    Destination image of the same size and the same type as self.



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# File 'ext/opencv/cvmat.cpp', line 4981

VALUE
rb_adaptive_threshold(int argc, VALUE *argv, VALUE self)
{
  VALUE dest, max_value, adaptive_method, threshold_type, block_size, constant;
  rb_scan_args(argc, argv, "5", &max_value, &adaptive_method, &threshold_type, &block_size, &constant);

  CvMat* self_ptr = CVMAT(self);
  // Create our destination pixels
  dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_MAT_DEPTH(self_ptr->type), 1);

  try {
    const cv::Mat selfMat(CVMAT(self)); // WBH convert openCv1-style cvMat to openCv2-style cv::Mat
    cv::Mat destMat(CVMAT(dest));

		cv::adaptiveThreshold(selfMat, destMat, max_value, adaptive_method, threshold_type, block_size, constant);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return dest;
}

#add(val, mask = nil) ⇒ CvMat Also known as: +

Computes the per-element sum of two arrays or an array and a scalar.

Parameters:

  • val (CvMat, CvScalar) —

    Array or scalar to add

  • mask (CvMat) —

    Optional operation mask, 8-bit single channel array, that specifies elements of the destination array to be changed.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 1762

VALUE
rb_add(int argc, VALUE *argv, VALUE self)
{
  VALUE val, mask, dest;
  rb_scan_args(argc, argv, "11", &val, &mask);
  dest = copy(self);
  try {
    if (rb_obj_is_kind_of(val, rb_klass))
      cvAdd(CVARR(self), CVARR(val), CVARR(dest), MASK(mask));
    else
      cvAddS(CVARR(self), VALUE_TO_CVSCALAR(val), CVARR(dest), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#and(val, mask = nil) ⇒ CvMat Also known as: &

Calculates the per-element bit-wise conjunction of two arrays or an array and a scalar.

Parameters:

  • val (CvMat, CvScalar) —

    Array or scalar to calculate bit-wise conjunction

  • mask (CvMat) —

    Optional operation mask, 8-bit single channel array, that specifies elements of the destination array to be changed.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 1971

VALUE
rb_and(int argc, VALUE *argv, VALUE self)
{
  VALUE val, mask, dest;
  rb_scan_args(argc, argv, "11", &val, &mask);
  dest = copy(self);
  try {
    if (rb_obj_is_kind_of(val, rb_klass))
      cvAnd(CVARR(self), CVARR(val), CVARR(dest), MASK(mask));
    else
      cvAndS(CVARR(self), VALUE_TO_CVSCALAR(val), CVARR(dest), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#and_into(other, dest) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 1989

VALUE
rb_and_into(VALUE self, VALUE other, VALUE dest)
{
  try {
    cvAnd(CVARR(self), CVARR(other), CVARR(dest));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#apply_color_map(colormap) ⇒ Object

Applies a GNU Octave/MATLAB equivalent colormap on a given image.

Parameters:

colormap - The colormap to apply.



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# File 'ext/opencv/cvmat.cpp', line 5870

VALUE
rb_apply_color_map(VALUE self, VALUE colormap)
{
  VALUE dst;
  try {
    cv::Mat dst_mat;
    cv::Mat self_mat(CVMAT(self));

    cv::applyColorMap(self_mat, dst_mat, NUM2INT(colormap));
    CvMat tmp = dst_mat;
    dst = new_object(tmp.rows, tmp.cols, tmp.type);
    cvCopy(&tmp, CVMAT(dst));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return dst;
}

#avg(mask = nil) ⇒ CvScalar

Calculates an average (mean) of array elements.

Parameters:

  • mask (CvMat) —

    Optional operation mask.

Returns:

  • (CvScalar) —

    The average of array elements.



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# File 'ext/opencv/cvmat.cpp', line 2429

VALUE
rb_avg(int argc, VALUE *argv, VALUE self)
{
  VALUE mask;
  rb_scan_args(argc, argv, "01", &mask);
  CvScalar avg;
  try {
    avg = cvAvg(CVARR(self), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return cCvScalar::new_object(avg);
}

#avg_sdv(mask = nil) ⇒ Array<CvScalar>

Calculates a mean and standard deviation of array elements.

Parameters:

  • mask (CvMat) —

    Optional operation mask.

Returns:

  • (Array<CvScalar>) —

    [mean, stddev], where mean is the computed mean value and stddev is the computed standard deviation.



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# File 'ext/opencv/cvmat.cpp', line 2465

VALUE
rb_avg_sdv(int argc, VALUE *argv, VALUE self)
{
  VALUE mask, mean, std_dev;
  rb_scan_args(argc, argv, "01", &mask);
  mean = cCvScalar::new_object();
  std_dev = cCvScalar::new_object();
  try {
    cvAvgSdv(CVARR(self), CVSCALAR(mean), CVSCALAR(std_dev), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_ary_new3(2, mean, std_dev);
}

#avg_value(mask) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 2444

VALUE
rb_avg_value(VALUE self, VALUE mask)
{
  CvScalar avg;
  try {
    avg = cvAvg(CVARR(self), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_float_new(avg.val[0]);
}

#calc_hist(<i>[hist_options]) ⇒ Object

# Return

hist_options should be Hash include these keys.

:bins
   Number of bins to create per-channel. Defaults to -1, which will use the depth of the image as the bin count.
:mask
   Optional Optional mask. If the matrix is not empty, it must be an 8-bit array of the same size as arrays[i] .
   The non-zero mask elements mark the array elements counted in the histogram.



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# File 'ext/opencv/cvmat.cpp', line 5799

VALUE
rb_calc_hist(int argc, VALUE *argv, VALUE self)
{
  VALUE hist_options;
  rb_scan_args(argc, argv, "01", &hist_options);

  const cv::Mat src(CVMAT(self));

  hist_options = HIST_OPTION(hist_options);

  VALUE minVal = DO_HIST_MIN(hist_options);
  const float rangeMin = minVal != Qnil ? NUM2DBL(minVal) : 0;

  VALUE maxVal = DO_HIST_MAX(hist_options);
  const float rangeMax = maxVal != Qnil ? NUM2DBL(maxVal) : std::pow(2.0, (float)src.elemSize1() * 8.0);

  const float channelRanges[] = { rangeMin, rangeMax };
  const float* ranges[] = { channelRanges, channelRanges, channelRanges, channelRanges };

  int binCount = DO_HIST_BINS(hist_options);
  if (binCount < 0) {
    binCount = int(channelRanges[1]);
  }

  const int histSize[] = { binCount, binCount, binCount, binCount };
  const int channels[] = { 0, 1, 2, 3 };

  cv::Mat maskMat;
  VALUE maskVal = DO_HIST_MASK(hist_options);
  if (maskVal != Qnil) {
     if (!(rb_obj_is_kind_of(maskVal, cCvMat::rb_class())) || cvGetElemType(CVARR(maskVal)) != CV_8UC1)
       rb_raise(rb_eTypeError, "mask should be mask image.");
     maskMat = CVMAT(maskVal);
  }

  // Commented by WBH until we have time to re-implement MatND (removed by rebase, dunno if it needs to be changed)
  /*
  try {
    cv::MatND histMat;

    cv::calcHist(
      &src, 1,
      channels,
      maskMat,
      histMat, src.channels(),
      histSize, ranges,
      true,
      false
    );

    const CvMatND histmatnd(histMat);
    return cCvMatND::new_object(&histmatnd);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  */

  return Qnil;
}

#cam_shift(window, criteria) ⇒ Array

Implements CAMSHIFT object tracking algrorithm. First, it finds an object center using cvMeanShift and, after that, calculates the object size and orientation. The function returns number of iterations made within cvMeanShift.

Returns:

  • (Array) 


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# File 'ext/opencv/cvmat.cpp', line 5998

VALUE
rb_cam_shift(VALUE self, VALUE window, VALUE criteria)
{
  VALUE comp = cCvConnectedComp::new_object();
  VALUE box = cCvBox2D::new_object();
  try {
    cvCamShift(CVARR(self), VALUE_TO_CVRECT(window), VALUE_TO_CVTERMCRITERIA(criteria),
	       CVCONNECTEDCOMP(comp), CVBOX2D(box));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_ary_new3(2, comp, box);
}

#canny(thresh1, thresh2, aperture_size = 3) ⇒ CvMat

Finds edges in an image using the [Canny86] algorithm.

Canny86: J. Canny. A Computational Approach to Edge Detection, IEEE Trans. on Pattern Analysis and Machine Intelligence, 8(6), pp. 679-698 (1986).

Parameters:

  • thresh1 (Number) —

    First threshold for the hysteresis procedure.

  • thresh2 (Number) —

    Second threshold for the hysteresis procedure.

  • aperture_size (Integer) —

    Aperture size for the sobel operator.

Returns:

  • (CvMat) —

    Output edge map



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# File 'ext/opencv/cvmat.cpp', line 3814

VALUE
rb_canny(int argc, VALUE *argv, VALUE self)
{
  VALUE dest, thresh1, thresh2, aperture_size, l2_gradient;
  int args_given = rb_scan_args(argc, argv, "22", &thresh1, &thresh2, &aperture_size, &l2_gradient);
  switch(args_given) {
  	case 2: aperture_size = 3; // intentional fallthrough, params applied cumulatively
  	case 1: l2_gradient = false;
  }

  CvMat* self_ptr = CVMAT(self);
  // Create our destination pixels
  dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_MAT_DEPTH(self_ptr->type), 1);

  try {
    const cv::Mat selfMat(CVMAT(self)); // WBH convert openCv1-style cvMat to openCv2-style cv::Mat
    cv::Mat destMat(CVMAT(dest));

		cv::Canny(selfMat, destMat, NUM2INT(thresh1), NUM2INT(thresh2), NUM2INT(aperture_size), l2_gradient);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return dest;
}

#channel ⇒ Integer

Returns number of channels of the matrix

Returns:

  • (Integer) —

    Number of channels of the matrix



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# File 'ext/opencv/cvmat.cpp', line 473

VALUE
rb_channel(VALUE self)
{
  return INT2FIX(CV_MAT_CN(CVMAT(self)->type));
}

#circle(center, radius, options = nil) ⇒ CvMat

Returns an image that is drawn a circle

Parameters:

  • center (CvPoint) —

    Center of the circle.

  • radius (Integer) —

    Radius of the circle.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3204

VALUE
rb_circle(int argc, VALUE *argv, VALUE self)
{
  return rb_circle_bang(argc, argv, rb_rcv_clone(self));
}

#circle!(center, radius, options = nil) ⇒ CvMat

Draws a circle

Parameters:

  • center (CvPoint) —

    Center of the circle.

  • radius (Integer) —

    Radius of the circle.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 3227

VALUE
rb_circle_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE center, radius, drawing_option;
  rb_scan_args(argc, argv, "21", &center, &radius, &drawing_option);
  drawing_option = DRAWING_OPTION(drawing_option);
  try {
    cvCircle(CVARR(self), VALUE_TO_CVPOINT(center), NUM2INT(radius),
	     DO_COLOR(drawing_option),
	     DO_THICKNESS(drawing_option),
	     DO_LINE_TYPE(drawing_option),
	     DO_SHIFT(drawing_option));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#cmp(val, dest, operand) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 2091

VALUE
rb_cmp(VALUE self, VALUE val, VALUE dest, VALUE operand)
{
  return rb_cmp_internal(self, val, dest, NUM2INT(operand));
}

#convert_scale(params) ⇒ CvMat

Converts one array to another with optional linear transformation.

Parameters:

  • params (Hash) —

    Transform parameters

Options Hash (params):

  • :depth (Integer) — default: same as self —

    Depth of the destination array

  • :scale (Number) — default: 1.0 —

    Scale factor

  • :shift (Number) — default: 0.0 —

    Value added to the scaled source array elements

Returns:

  • (CvMat) —

    Converted array



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# File 'ext/opencv/cvmat.cpp', line 1701

VALUE
rb_convert_scale(VALUE self, VALUE hash)
{
  Check_Type(hash, T_HASH);
  CvMat* self_ptr = CVMAT(self);
  VALUE depth = LOOKUP_HASH(hash, "depth");
  VALUE scale = LOOKUP_HASH(hash, "scale");
  VALUE shift = LOOKUP_HASH(hash, "shift");

  VALUE dest = Qnil;
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self,
			       CVMETHOD("DEPTH", depth, CV_MAT_DEPTH(self_ptr->type)),
			       CV_MAT_CN(self_ptr->type));
    cvConvertScale(self_ptr, CVARR(dest), IF_DBL(scale, 1.0), IF_DBL(shift, 0.0));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#convert_scale_abs(params) ⇒ CvMat

Scales, computes absolute values, and converts the result to 8-bit.

Parameters:

  • params (Hash) —

    Transform parameters

Options Hash (params):

  • :scale (Number) — default: 1.0 —

    Scale factor

  • :shift (Number) — default: 0.0 —

    Value added to the scaled source array elements

Returns:

  • (CvMat) —

    Converted array



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# File 'ext/opencv/cvmat.cpp', line 1733

VALUE
rb_convert_scale_abs(VALUE self, VALUE hash)
{
  Check_Type(hash, T_HASH);
  CvMat* self_ptr = CVMAT(self);
  VALUE scale = LOOKUP_HASH(hash, "scale");
  VALUE shift = LOOKUP_HASH(hash, "shift");
  VALUE dest = Qnil;
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_8U, CV_MAT_CN(CVMAT(self)->type));
    cvConvertScaleAbs(self_ptr, CVARR(dest), IF_DBL(scale, 1.0), IF_DBL(shift, 0.0));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#copy(dst = nil, mask = nil) ⇒ CvMat

Copies one array to another.

The function copies selected elements from an input array to an output array:

dst(I) = src(I) if mask(I) != 0

Parameters:

  • dst (CvMat) —

    The destination array.

  • mask (CvMat) —

    Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed.

Returns:

  • (CvMat) —

    Copy of the array



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# File 'ext/opencv/cvmat.cpp', line 522

VALUE
rb_copy(int argc, VALUE *argv, VALUE self)
{
  VALUE _dst, _mask;
  rb_scan_args(argc, argv, "02", &_dst, &_mask);

  CvMat* mask = MASK(_mask);
  CvArr *src = CVARR(self);
  if (NIL_P(_dst)) {
    CvSize size = cvGetSize(src);
    _dst = new_mat_kind_object(size, self);
  }

  try {
    cvCopy(src, CVARR_WITH_CHECK(_dst), mask);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return _dst;
}

#copy_make_border(border_type, size, offset[,value = CvScalar.new(0)]) ⇒ Object

Copies image and makes border around it. border_type:

  • IPL_BORDER_CONSTANT, :constant

    border is filled with the fixed value, passed as last parameter of the function.

  • IPL_BORDER_REPLICATE, :replicate

    the pixels from the top and bottom rows, the left-most and right-most columns are replicated to fill the border

size: The destination image size offset: Coordinates of the top-left corner (or bottom-left in the case of images with bottom-left origin) of the destination image rectangle. value: Value of the border pixels if bordertype is IPL_BORDER_CONSTANT or :constant.



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# File 'ext/opencv/cvmat.cpp', line 4799

VALUE
rb_copy_make_border(int argc, VALUE *argv, VALUE self)
{
  VALUE border_type, size, offset, value, dest;
  rb_scan_args(argc, argv, "31", &border_type, &size, &offset, &value);
  dest = new_mat_kind_object(VALUE_TO_CVSIZE(size), self);

  int type = 0;
  if (SYMBOL_P(border_type)) {
    ID type_id = rb_to_id(border_type);
    if (type_id == rb_intern("constant"))
      type = IPL_BORDER_CONSTANT;
    else if (type_id == rb_intern("replicate"))
      type = IPL_BORDER_REPLICATE;
    else
      rb_raise(rb_eArgError, "Invalid border_type (should be :constant or :replicate)");
  }
  else
    type = NUM2INT(border_type);

  try {
    cvCopyMakeBorder(CVARR(self), CVARR(dest), VALUE_TO_CVPOINT(offset), type,
		     NIL_P(value) ? cvScalar(0) : VALUE_TO_CVSCALAR(value));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#corner_eigenvv(block_size, aperture_size = 3) ⇒ CvMat

Calculates eigenvalues and eigenvectors of image blocks for corner detection.

Parameters:

  • block_size (Integer) —

    Neighborhood size.

  • aperture_size (Integer) —

    Aperture parameter for the sobel operator.

Returns:

  • (CvMat) —

    Result array.



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# File 'ext/opencv/cvmat.cpp', line 3876

VALUE
rb_corner_eigenvv(int argc, VALUE *argv, VALUE self)
{
  VALUE block_size, aperture_size, dest;
  if (rb_scan_args(argc, argv, "11", &block_size, &aperture_size) < 2)
    aperture_size = INT2FIX(3);
  CvMat* self_ptr = CVMAT(self);
  dest = new_object(cvSize(self_ptr->cols * 6, self_ptr->rows), CV_MAKETYPE(CV_32F, 1));
  try {
    cvCornerEigenValsAndVecs(self_ptr, CVARR(dest), NUM2INT(block_size), NUM2INT(aperture_size));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#corner_harris(block_size, aperture_size = 3, k = 0.04) ⇒ CvMat

Harris edge detector.

Parameters:

  • block_size (Integer) —

    Neighborhood size.

  • aperture_size (Integer) —

    Aperture parameter for the sobel operator.

  • k (Number) —

    Harris detector free parameter.

Returns:

  • (CvMat) —

    The Harris detector responses.



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# File 'ext/opencv/cvmat.cpp', line 3929

VALUE
rb_corner_harris(int argc, VALUE *argv, VALUE self)
{
  VALUE block_size, aperture_size, k, dest;
  rb_scan_args(argc, argv, "12", &block_size, &aperture_size, &k);
  CvArr* self_ptr = CVARR(self);
  dest = new_object(cvGetSize(self_ptr), CV_MAKETYPE(CV_32F, 1));
  try {
    cvCornerHarris(self_ptr, CVARR(dest), NUM2INT(block_size), IF_INT(aperture_size, 3), IF_DBL(k, 0.04));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#corner_min_eigen_val(block_size, aperture_size = 3) ⇒ CvMat

Calculates the minimal eigenvalue of gradient matrices for corner detection.

Parameters:

  • block_size (Integer) —

    Neighborhood size.

  • aperture_size (Integer) —

    Aperture parameter for the sobel operator.

Returns:

  • (CvMat) —

    Result array.



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# File 'ext/opencv/cvmat.cpp', line 3902

VALUE
rb_corner_min_eigen_val(int argc, VALUE *argv, VALUE self)
{
  VALUE block_size, aperture_size, dest;
  if (rb_scan_args(argc, argv, "11", &block_size, &aperture_size) < 2)
    aperture_size = INT2FIX(3);
  CvArr* self_ptr = CVARR(self);
  dest = new_object(cvGetSize(self_ptr), CV_MAKETYPE(CV_32F, 1));
  try {
    cvCornerMinEigenVal(self_ptr, CVARR(dest), NUM2INT(block_size), NUM2INT(aperture_size));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#count_non_zero ⇒ Integer

Counts non-zero array elements.

Returns:

  • (Integer) —

    The number of non-zero elements.



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# File 'ext/opencv/cvmat.cpp', line 2389

VALUE
rb_count_non_zero(VALUE self)
{
  int n = 0;
  try {
    n = cvCountNonZero(CVARR(self));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return INT2NUM(n);
}

#create_mask ⇒ CvMat

Creates a mask (1-channel 8bit unsinged image whose elements are 0) from the matrix. The size of the mask is the same as source matrix.

Returns:

  • (CvMat) —

    Created mask



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# File 'ext/opencv/cvmat.cpp', line 420

VALUE
rb_create_mask(VALUE self)
{
  VALUE mask = cCvMat::new_object(cvGetSize(CVARR(self)), CV_8UC1);
  try {
    cvZero(CVARR(self));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return mask;
}

#cross_product(mat) ⇒ CvMat

Calculates the cross product of two 3D vectors.

Parameters:

  • mat (CvMat) —

    A vector to calculate the cross product.

Returns:

  • (CvMat) —

    The cross product of two vectors.



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# File 'ext/opencv/cvmat.cpp', line 2634

VALUE
rb_cross_product(VALUE self, VALUE mat)
{
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvCrossProduct(self_ptr, CVARR_WITH_CHECK(mat), CVARR(dest));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#data ⇒ Object

Deprecated.

This method will be removed.



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# File 'ext/opencv/cvmat.cpp', line 483

VALUE
rb_data(VALUE self)
{
  IplImage *image = IPLIMAGE(self);
  return rb_str_new((char *)image->imageData, image->imageSize);
}

#set_data(data) ⇒ CvMat

Assigns user data to the array header

Parameters:

  • data (Array<Integer>) —

    User data

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1133

VALUE
rb_set_data(VALUE self, VALUE data)
{
  CvMat *self_ptr = CVMAT(self);
  int depth = CV_MAT_DEPTH(self_ptr->type);

  if (TYPE(data) == T_STRING) {
    if (!CV_IS_MAT_CONT(self_ptr->type))
      rb_raise(rb_eArgError, "CvMat must be continuous");
      
    const int dataLength = RSTRING_LEN(data);
    if (dataLength != self_ptr->width * self_ptr->height * CV_ELEM_SIZE(self_ptr->type))
      rb_raise(rb_eArgError, "Invalid data string length");
    
    memcpy(self_ptr->data.ptr, RSTRING_PTR(data), dataLength);
    
  } else {
    data = rb_funcall(data, rb_intern("flatten"), 0);
    
    const int DATA_LEN = RARRAY_LEN(data);
   
    void* array = NULL;
  
    switch (depth) {
    case CV_8U:
      array = rb_cvAlloc(sizeof(uchar) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((uchar*)array)[i] = (uchar)(NUM2INT(rb_ary_entry(data, i)));
      break;
    case CV_8S:
      array = rb_cvAlloc(sizeof(char) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((char*)array)[i] = (char)(NUM2INT(rb_ary_entry(data, i)));
      break;
    case CV_16U:
      array = rb_cvAlloc(sizeof(ushort) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((ushort*)array)[i] = (ushort)(NUM2INT(rb_ary_entry(data, i)));
      break;
    case CV_16S:
      array = rb_cvAlloc(sizeof(short) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((short*)array)[i] = (short)(NUM2INT(rb_ary_entry(data, i)));
      break;
    case CV_32S:
      array = rb_cvAlloc(sizeof(int) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((int*)array)[i] = NUM2INT(rb_ary_entry(data, i));
      break;
    case CV_32F:
      array = rb_cvAlloc(sizeof(float) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((float*)array)[i] = (float)NUM2DBL(rb_ary_entry(data, i));
      break;
    case CV_64F:
      array = rb_cvAlloc(sizeof(double) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((double*)array)[i] = NUM2DBL(rb_ary_entry(data, i));
      break;
    default:
      rb_raise(rb_eArgError, "Invalid CvMat depth");
      break;
    }

    try {
      cvSetData(self_ptr, array, self_ptr->step);    
    }
    catch (cv::Exception& e) {
      raise_cverror(e);
    }
  }

  return self;
}

#dct(flags = CV_DXT_FORWARD) ⇒ CvMat

Performs forward or inverse Discrete Cosine Transform(DCT) of 1D or 2D floating-point array.

Parameters:

  • flags (Integer) (defaults to: CV_DXT_FORWARD) —

    transformation flags, representing a combination of the following values:

    • CV_DXT_FORWARD - Performs a 1D or 2D transform.

    • CV_DXT_INVERSE - Performs an inverse 1D or 2D transform instead of the default forward transform.

    • CV_DXT_ROWS - Performs a forward or inverse transform of every individual row of the input matrix. This flag enables you to transform multiple vectors simultaneously and can be used to decrease the overhead (which is sometimes several times larger than the processing itself) to perform 3D and higher-dimensional transforms and so forth.

Returns:

  • (CvMat) —

    Output array



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# File 'ext/opencv/cvmat.cpp', line 3050

VALUE
rb_dct(int argc, VALUE *argv, VALUE self)
{
  VALUE flag_value;
  rb_scan_args(argc, argv, "01", &flag_value);

  int flags = NIL_P(flag_value) ? CV_DXT_FORWARD : NUM2INT(flag_value);
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvDCT(self_ptr, CVARR(dest), flags);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#depth ⇒ Symbol

Returns depth type of the matrix

Returns:

  • (Symbol) —

    Depth type in the form of symbol :cv<bit depth><s|u|f>, where s=signed, u=unsigned, f=float.



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# File 'ext/opencv/cvmat.cpp', line 461

VALUE
rb_depth(VALUE self)
{
  return rb_hash_lookup(rb_funcall(rb_const_get(rb_module_opencv(), rb_intern("DEPTH")), rb_intern("invert"), 0),
			INT2FIX(CV_MAT_DEPTH(CVMAT(self)->type)));
}

#det ⇒ Number Also known as: determinant

Returns the determinant of a square floating-point matrix.

Returns:

  • (Number) —

    The determinant of the matrix.



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# File 'ext/opencv/cvmat.cpp', line 2793

VALUE
rb_det(VALUE self)
{
  double det = 0.0;
  try {
    det = cvDet(CVARR(self));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_float_new(det);
}

#dft(flags = CV_DXT_FORWARD, nonzero_rows = 0) ⇒ CvMat

Performs a forward or inverse Discrete Fourier transform of a 1D or 2D floating-point array.

Parameters:

  • flags (Integer) (defaults to: CV_DXT_FORWARD) —

    transformation flags, representing a combination of the following values:

    • CV_DXT_FORWARD - Performs a 1D or 2D transform.

    • CV_DXT_INVERSE - Performs an inverse 1D or 2D transform instead of the default forward transform.

    • CV_DXT_SCALE - Scales the result: divide it by the number of array elements. Normally, it is combined with CV_DXT_INVERSE.

    • CV_DXT_INV_SCALE - CV_DXT_INVERSE + CV_DXT_SCALE

  • nonzero_rows (Integer) (defaults to: 0) —

    when the parameter is not zero, the function assumes that only the first nonzero_rows rows of the input array (CV_DXT_INVERSE is not set) or only the first nonzero_rows of the output array (CV_DXT_INVERSE is set) contain non-zeros.

Returns:

  • (CvMat) —

    Output array



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# File 'ext/opencv/cvmat.cpp', line 3016

VALUE
rb_dft(int argc, VALUE *argv, VALUE self)
{
  VALUE flag_value, nonzero_row_value;
  rb_scan_args(argc, argv, "02", &flag_value, &nonzero_row_value);

  int flags = NIL_P(flag_value) ? CV_DXT_FORWARD : NUM2INT(flag_value);
  int nonzero_rows = NIL_P(nonzero_row_value) ? 0 : NUM2INT(nonzero_row_value);
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvDFT(self_ptr, CVARR(dest), flags, nonzero_rows);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#diag(val = 0) ⇒ CvMat Also known as: diagonal

Returns a specified diagonal of the matrix

Parameters:

  • val (Integer) —

    Index of the array diagonal. Zero value corresponds to the main diagonal, -1 corresponds to the diagonal above the main, 1 corresponds to the diagonal below the main, and so forth.

Returns:

  • (CvMat) —

    Specified diagonal



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# File 'ext/opencv/cvmat.cpp', line 912

VALUE
rb_diag(int argc, VALUE *argv, VALUE self)
{
  VALUE val;
  if (rb_scan_args(argc, argv, "01", &val) < 1)
    val = INT2FIX(0);
  CvMat* diag = NULL;
  try {
    diag = cvGetDiag(CVARR(self), RB_CVALLOC(CvMat), NUM2INT(val));
  }
  catch (cv::Exception& e) {
    cvReleaseMat(&diag);
    raise_cverror(e);
  }
  return DEPEND_OBJECT(rb_klass, diag, self);
}

#dilate([element = nil][,iteration = 1]) ⇒ Object

Create dilates image by using arbitrary structuring element. element is structuring element used for erosion. element should be IplConvKernel. If it is nil, a 3x3 rectangular structuring element is used. iterations is number of times erosion is applied.



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# File 'ext/opencv/cvmat.cpp', line 4494

VALUE
rb_dilate(int argc, VALUE *argv, VALUE self)
{
  return rb_dilate_bang(argc, argv, rb_rcv_clone(self));
}

#dilate!([element = nil][,iteration = 1]) ⇒ self

Dilate image by using arbitrary structuring element. see also #dilate.

Returns:

  • (self) 


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# File 'ext/opencv/cvmat.cpp', line 4507

VALUE
rb_dilate_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE element, iteration;
  rb_scan_args(argc, argv, "02", &element, &iteration);
  IplConvKernel* kernel = NIL_P(element) ? NULL : IPLCONVKERNEL_WITH_CHECK(element);
  try {
    cvDilate(CVARR(self), CVARR(self), kernel, IF_INT(iteration, 1));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#dilate_into(dest, element, iteration) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 4522

VALUE
rb_dilate_into(VALUE self, VALUE dest, VALUE element, VALUE iteration)
{
  IplConvKernel* kernel = NIL_P(element) ? NULL : IPLCONVKERNEL_WITH_CHECK(element);
  try {
    cvDilate(CVARR(self), CVARR(dest), kernel, NUM2INT(iteration));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#dim_size(index) ⇒ Integer

Returns array size along the specified dimension.

Parameters:

  • index (Intger) —

    Zero-based dimension index (for matrices 0 means number of rows, 1 means number of columns; for images 0 means height, 1 means width)

Returns:

  • (Integer) —

    Array size



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# File 'ext/opencv/cvmat.cpp', line 982

VALUE
rb_dim_size(VALUE self, VALUE index)
{
  int dimsize = 0;
  try {
    dimsize = cvGetDimSize(CVARR(self), NUM2INT(index));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return INT2NUM(dimsize);
}

#dims ⇒ Array<Integer>

Returns array dimensions sizes

Returns:

  • (Array<Integer>) —

    Array dimensions sizes. For 2d arrays the number of rows (height) goes first, number of columns (width) next.



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# File 'ext/opencv/cvmat.cpp', line 955

VALUE
rb_dims(VALUE self)
{
  int size[CV_MAX_DIM];
  int dims = 0;
  try {
    dims = cvGetDims(CVARR(self), size);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  VALUE ary = rb_ary_new2(dims);
  for (int i = 0; i < dims; ++i) {
    rb_ary_store(ary, i, INT2NUM(size[i]));
  }
  return ary;
}

#distance_transform(<i>labels, distance_type, mask_size</i>)) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 5009

VALUE
rb_distance_transform(VALUE self, VALUE labels, VALUE distance_type, VALUE mask_size)
{
  if (!(rb_obj_is_kind_of(self, cCvMat::rb_class())) || cvGetElemType(CVARR(self)) != CV_8UC1)
    rb_raise(rb_eTypeError, "self should be 8-bit single-channel CvMat.");

  if (labels != Qnil) {
    if (!(rb_obj_is_kind_of(labels, cCvMat::rb_class())) || cvGetElemType(CVARR(labels)) != CV_32S)
      rb_raise(rb_eTypeError, "labels should be 32-bit signed single-channel CvMat.");
  }

  CvMat* self_ptr = CVMAT(self);
  VALUE dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_32F, 1);

  try {
    const cv::Mat selfMat(CVMAT(self));
    cv::Mat destMat(CVMAT(dest));

    if (labels != Qnil) {
      cv::Mat labelsMat(CVMAT(labels));
      cv::distanceTransform(selfMat, destMat, labelsMat, NUM2INT(distance_type), NUM2INT(mask_size));
    } else {
      cv::distanceTransform(selfMat, destMat, NUM2INT(distance_type), NUM2INT(mask_size));
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return dest;
}

#div(val, scale = 1.0) ⇒ CvMat Also known as: /

Performs per-element division of two arrays or a scalar by an array.

Parameters:

  • val (CvMat, CvScalar) —

    Array or scalar to divide

  • scale (Number) —

    Scale factor

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 1904

VALUE
rb_div(int argc, VALUE *argv, VALUE self)
{
  VALUE val, scale;
  if (rb_scan_args(argc, argv, "11", &val, &scale) < 2)
    scale = rb_float_new(1.0);
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    if (rb_obj_is_kind_of(val, rb_klass))
      cvDiv(self_ptr, CVARR(val), CVARR(dest), NUM2DBL(scale));
    else {
      CvScalar scl = VALUE_TO_CVSCALAR(val);
      VALUE mat = new_mat_kind_object(cvGetSize(self_ptr), self);
      CvArr* mat_ptr = CVARR(mat);
      cvSet(mat_ptr, scl);
      cvDiv(self_ptr, mat_ptr, CVARR(dest), NUM2DBL(scale));
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#dot_product(mat) ⇒ Number

WBH started this but didn’t end up needing it, so didn’t complete debugging (used bounding_rect instead) Note that WBH of 11/2014 tried to revisit this method and was beset with 3 hours of frustration based around the fact that the ROI can only be set via a constructor, but constructing a new object means allocating and returning memory associated with that new object. GL with debugging that, future self.

VALUE rb_set_roi(int argc, VALUE *argv, VALUE self) {

VALUE dest, newMat, delta, ksize, rect, scale;
rb_scan_args(argc, argv, "1", &rect);

CvMat* self_ptr = CVMAT(self);
dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_MAT_DEPTH(self_ptr->type), 1);

cv::Rect cppCvRect; cppCvRect.x = CVRECT(rect)->x; cppCvRect.y = CVRECT(rect)->y;

try {
  cv::Mat selfMat(CVMAT(self)); // WBH convert openCv1-style cvMat to openCv2-style cv::Mat
  cv::Mat destMat(CVMAT(dest));
  destMat(selfMat(cppCvRect));
}
catch (cv::Exception& e) {
  raise_cverror(e);
}
return newMat;

}

Calculates the dot product of two arrays in Euclidean metrics.

Parameters:

  • mat (CvMat) —

    An array to calculate the dot product.

Returns:

  • (Number) —

    The dot product of two arrays.



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# File 'ext/opencv/cvmat.cpp', line 2613

VALUE
rb_dot_product(VALUE self, VALUE mat)
{
  double result = 0.0;
  try {
    result = cvDotProduct(CVARR(self), CVARR_WITH_CHECK(mat));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_float_new(result);
}

#draw_chessboard_corners(pattern_size, corners, pattern_was_found) ⇒ nil

Returns an image which is rendered the detected chessboard corners.

pattern_size (CvSize) - Number of inner corners per a chessboard row and column. corners (Array<CvPoint2D32f>) - Array of detected corners, the output of CvMat#find_chessboard_corners. pattern_was_found (Boolean)- Parameter indicating whether the complete board was found or not.

Returns:

  • (nil) 


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# File 'ext/opencv/cvmat.cpp', line 5357

VALUE
rb_draw_chessboard_corners(VALUE self, VALUE pattern_size, VALUE corners, VALUE pattern_was_found)
{
  return rb_draw_chessboard_corners_bang(copy(self), pattern_size, corners, pattern_was_found);
}

#draw_chessboard_corners!(pattern_size, corners, pattern_was_found) ⇒ self

Renders the detected chessboard corners.

pattern_size (CvSize) - Number of inner corners per a chessboard row and column. corners (Array<CvPoint2D32f>) - Array of detected corners, the output of CvMat#find_chessboard_corners. pattern_was_found (Boolean)- Parameter indicating whether the complete board was found or not.

Returns:

  • (self) 


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# File 'ext/opencv/cvmat.cpp', line 5373

VALUE
rb_draw_chessboard_corners_bang(VALUE self, VALUE pattern_size, VALUE corners, VALUE pattern_was_found)
{
  Check_Type(corners, T_ARRAY);
  int count = RARRAY_LEN(corners);
  CvPoint2D32f* corners_buff = RB_ALLOC_N(CvPoint2D32f, count);
  VALUE* corners_ptr = RARRAY_PTR(corners);
  for (int i = 0; i < count; i++) {
    corners_buff[i] = *(CVPOINT2D32F(corners_ptr[i]));
  }

  try {
    int found = (pattern_was_found == Qtrue);
    cvDrawChessboardCorners(CVARR(self), VALUE_TO_CVSIZE(pattern_size), corners_buff, count, found);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return self;
}

#draw_contours(contour, external_color, hole_color, max_level, options) ⇒ Object

Draws contour outlines or interiors in an image.

  • contour (CvContour) - Pointer to the first contour

  • external_color (CvScalar) - Color of the external contours

  • hole_color (CvScalar) - Color of internal contours (holes)

  • max_level (Integer) - Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours following it on the same level are drawn. If 2, all contours following and all contours one level below the contours are drawn, and so forth. If the value is negative, the function does not draw the contours following after contour but draws the child contours of contour up to the |max_level| - 1 level.

  • options (Hash) - Drawing options.

    • :thickness (Integer) - Thickness of lines the contours are drawn with. If it is negative, the contour interiors are drawn (default: 1).

    • :line_type (Integer or Symbol) - Type of the contour segments, see CvMat#line description (default: 8).



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# File 'ext/opencv/cvmat.cpp', line 5316

VALUE
rb_draw_contours(int argc, VALUE *argv, VALUE self)
{
  return rb_draw_contours_bang(argc, argv, copy(self));
}

#draw_contours!(contour, external_color, hole_color, max_level, options) ⇒ Object

Draws contour outlines or interiors in an image.

see CvMat#draw_contours



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# File 'ext/opencv/cvmat.cpp', line 5330

VALUE
rb_draw_contours_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE contour, external_color, hole_color, max_level, options;
  rb_scan_args(argc, argv, "41", &contour, &external_color, &hole_color, &max_level, &options);
  options = DRAWING_OPTION(options);
  try {
    cvDrawContours(CVARR(self), CVSEQ_WITH_CHECK(contour), VALUE_TO_CVSCALAR(external_color),
		   VALUE_TO_CVSCALAR(hole_color), NUM2INT(max_level),
		   DO_THICKNESS(options), DO_LINE_TYPE(options));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#each_col {|col| ... } ⇒ CvMat Also known as: each_column

TODO:

To return an enumerator if no block is given

Calls block once for each column in the matrix, passing that column as a parameter.

Yields:

  • (col) —

    Each column in the matrix

Returns:



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# File 'ext/opencv/cvmat.cpp', line 884

VALUE
rb_each_col(VALUE self)
{
  int cols = CVMAT(self)->cols;
  CvMat *col = NULL;
  for (int i = 0; i < cols; ++i) {
    try {
      col = cvGetCol(CVARR(self), RB_CVALLOC(CvMat), i);
    }
    catch (cv::Exception& e) {
      if (col != NULL)
	cvReleaseMat(&col);
      raise_cverror(e);
    }
    rb_yield(DEPEND_OBJECT(rb_klass, col, self));
  }
  return self;
}

#each_row {|row| ... } ⇒ CvMat

TODO:

To return an enumerator if no block is given

Calls block once for each row in the matrix, passing that row as a parameter.

Yields:

  • (row) —

    Each row in the matrix

Returns:



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# File 'ext/opencv/cvmat.cpp', line 857

VALUE
rb_each_row(VALUE self)
{
  int rows = CVMAT(self)->rows;
  CvMat* row = NULL;
  for (int i = 0; i < rows; ++i) {
    try {
      row = cvGetRow(CVARR(self), RB_CVALLOC(CvMat), i);
    }
    catch (cv::Exception& e) {
      if (row != NULL)
	cvReleaseMat(&row);
      raise_cverror(e);
    }
    rb_yield(DEPEND_OBJECT(rb_klass, row, self));
  }
  return self;
}

#eigenvv ⇒ Array<CvMat>

Computes eigenvalues and eigenvectors of symmetric matrix. self should be symmetric square matrix. self is modified during the processing.

Returns:

  • (Array<CvMat>) —

    Array of [eigenvalues, eigenvectors]



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# File 'ext/opencv/cvmat.cpp', line 2926

VALUE
rb_eigenvv(int argc, VALUE *argv, VALUE self)
{
  VALUE epsilon, lowindex, highindex;
  rb_scan_args(argc, argv, "03", &epsilon, &lowindex, &highindex);
  double eps = (NIL_P(epsilon)) ? 0.0 : NUM2DBL(epsilon);
  int lowidx = (NIL_P(lowindex)) ? -1 : NUM2INT(lowindex);
  int highidx = (NIL_P(highindex)) ? -1 : NUM2INT(highindex);
  VALUE eigen_vectors = Qnil, eigen_values = Qnil;
  CvArr* self_ptr = CVARR(self);
  try {
    CvSize size = cvGetSize(self_ptr);
    int type = cvGetElemType(self_ptr);
    eigen_vectors = new_object(size, type);
    eigen_values = new_object(size.height, 1, type);
    // NOTE: eps, lowidx, highidx are ignored in the current OpenCV implementation.
    cvEigenVV(self_ptr, CVARR(eigen_vectors), CVARR(eigen_values), eps, lowidx, highidx);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_ary_new3(2, eigen_vectors, eigen_values);
}

#ellipse(center, axes, angle, start_angle, end_angle, options = nil) ⇒ CvMat

Returns an image that is drawn a simple or thick elliptic arc or fills an ellipse sector.

Parameters:

  • center (CvPoint) —

    Center of the ellipse.

  • axes (CvSize) —

    Length of the ellipse axes.

  • angle (Number) —

    Ellipse rotation angle in degrees.

  • start_angle (Number) —

    Starting angle of the elliptic arc in degrees.

  • end_angle (Number) —

    Ending angle of the elliptic arc in degrees.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3266

VALUE
rb_ellipse(int argc, VALUE *argv, VALUE self)
{
  return rb_ellipse_bang(argc, argv, rb_rcv_clone(self));
}

#ellipse!(center, axes, angle, start_angle, end_angle, options = nil) ⇒ CvMat

Draws a simple or thick elliptic arc or fills an ellipse sector.

Parameters:

  • center (CvPoint) —

    Center of the ellipse.

  • axes (CvSize) —

    Length of the ellipse axes.

  • angle (Number) —

    Ellipse rotation angle in degrees.

  • start_angle (Number) —

    Starting angle of the elliptic arc in degrees.

  • end_angle (Number) —

    Ending angle of the elliptic arc in degrees.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 3292

VALUE
rb_ellipse_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE center, axis, angle, start_angle, end_angle, drawing_option;
  rb_scan_args(argc, argv, "51", &center, &axis, &angle, &start_angle, &end_angle, &drawing_option);
  drawing_option = DRAWING_OPTION(drawing_option);
  try {
    cvEllipse(CVARR(self), VALUE_TO_CVPOINT(center),
	      VALUE_TO_CVSIZE(axis),
	      NUM2DBL(angle), NUM2DBL(start_angle), NUM2DBL(end_angle),
	      DO_COLOR(drawing_option),
	      DO_THICKNESS(drawing_option),
	      DO_LINE_TYPE(drawing_option),
	      DO_SHIFT(drawing_option));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#ellipse_box(box, options = nil) ⇒ CvMat

Returns an image that is drawn a simple or thick elliptic arc or fills an ellipse sector.

Parameters:

  • box (CvBox2D) —

    Alternative ellipse representation via CvBox2D. This means that the function draws an ellipse inscribed in the rotated rectangle.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3330

VALUE
rb_ellipse_box(int argc, VALUE *argv, VALUE self)
{
  return rb_ellipse_box_bang(argc, argv, rb_rcv_clone(self));
}

#ellipse_box!(box, options = nil) ⇒ CvMat

Draws a simple or thick elliptic arc or fills an ellipse sector.

Parameters:

  • box (CvBox2D) —

    Alternative ellipse representation via CvBox2D. This means that the function draws an ellipse inscribed in the rotated rectangle.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 3353

VALUE
rb_ellipse_box_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE box, drawing_option;
  rb_scan_args(argc, argv, "11", &box, &drawing_option);
  drawing_option = DRAWING_OPTION(drawing_option);
  try {
    cvEllipseBox(CVARR(self), VALUE_TO_CVBOX2D(box),
		 DO_COLOR(drawing_option),
		 DO_THICKNESS(drawing_option),
		 DO_LINE_TYPE(drawing_option),
		 DO_SHIFT(drawing_option));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#encode_image(ext, params = nil) ⇒ Array<Integer> Also known as: encode

Encodes an image into a memory buffer.

Examples:

jpg = CvMat.load('image.jpg')
bytes1 = jpg.encode_image('.jpg') # Encodes a JPEG image which quality is 95
bytes2 = jpg.encode_image('.jpg', CV_IMWRITE_JPEG_QUALITY => 10) # Encodes a JPEG image which quality is 10

png = CvMat.load('image.png')
bytes3 = mat.encode_image('.png', CV_IMWRITE_PNG_COMPRESSION => 1)  # Encodes a PNG image which compression level is 1

Parameters:

  • ext (String) —

    File extension that defines the output format (‘.jpg’, ‘.png’, …)

  • params (Hash) (defaults to: nil) —

    • Format-specific parameters.

Options Hash (params):

  • CV_IMWRITE_JPEG_QUALITY (Integer) — default: 95 —

    For JPEG, it can be a quality ( CV_IMWRITE_JPEG_QUALITY ) from 0 to 100 (the higher is the better).

  • CV_IMWRITE_PNG_COMPRESSION (Integer) — default: 3 —

    For PNG, it can be the compression level ( CV_IMWRITE_PNG_COMPRESSION ) from 0 to 9. A higher value means a smaller size and longer compression time.

  • CV_IMWRITE_PXM_BINARY (Integer) — default: 1 —

    For PPM, PGM, or PBM, it can be a binary format flag ( CV_IMWRITE_PXM_BINARY ), 0 or 1.

Returns:

  • (Array<Integer>) —

    Encoded image as array of bytes.



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# File 'ext/opencv/cvmat.cpp', line 224

VALUE
rb_encode_imageM(int argc, VALUE *argv, VALUE self)
{
  VALUE _ext, _params;
  rb_scan_args(argc, argv, "11", &_ext, &_params);
  Check_Type(_ext, T_STRING);
  const char* ext = RSTRING_PTR(_ext);
  CvMat* buff = NULL;
  int* params = NULL;

  if (!NIL_P(_params)) {
    params = hash_to_format_specific_param(_params);
  }

  try {
    buff = cvEncodeImage(ext, CVARR(self), params);
  }
  catch (cv::Exception& e) {
    if (params != NULL) {
      free(params);
      params = NULL;
    }
    raise_cverror(e);
  }
  if (params != NULL) {
    free(params);
    params = NULL;
  }

  const int size = buff->rows * buff->cols;
  VALUE array = rb_ary_new2(size);
  for (int i = 0; i < size; i++) {
    rb_ary_store(array, i, CHR2FIX(CV_MAT_ELEM(*buff, char, 0, i)));
  }

  try {
    cvReleaseMat(&buff);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return array;
}

#eq(val) ⇒ CvMat

Performs the per-element comparison “equal” of two arrays or an array and scalar value.

Parameters:

  • val (CvMat, CvScalar, Number) —

    Array, scalar or number to compare

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2136

VALUE
rb_eq(VALUE self, VALUE val)
{
  VALUE dest = new_mat_kind_object(cvGetSize(CVARR(self)), self, CV_8U, 1);
  return rb_cmp_internal(self, val, dest, CV_CMP_EQ);
}

#equalize_hist ⇒ Object

Equalize histgram of grayscale of image.

equalizes histogram of the input image using the following algorithm:

  1. calculate histogram H for src.

  2. normalize histogram, so that the sum of histogram bins is 255.

  3. compute integral of the histogram: H’(i) = sum0≤j≤iH(j)

  4. transform the image using H’ as a look-up table: dst(x,y)=H’(src(x,y))

The algorithm normalizes brightness and increases contrast of the image.

support single-channel 8bit image (grayscale) only.



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# File 'ext/opencv/cvmat.cpp', line 5770

VALUE
rb_equalize_hist(VALUE self)
{
  VALUE dest = Qnil;
  try {
    CvArr* self_ptr = CVARR(self);
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvEqualizeHist(self_ptr, CVARR(dest));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#erode([element = nil, iteration = 1]) ⇒ Object

Create erodes image by using arbitrary structuring element. element is structuring element used for erosion. element should be IplConvKernel. If it is nil, a 3x3 rectangular structuring element is used. iterations is number of times erosion is applied.



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# File 'ext/opencv/cvmat.cpp', line 4457

VALUE
rb_erode(int argc, VALUE *argv, VALUE self)
{
  return rb_erode_bang(argc, argv, rb_rcv_clone(self));
}

#erode!([element = nil][,iteration = 1]) ⇒ self

Erodes image by using arbitrary structuring element. see also #erode.

Returns:

  • (self) 


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# File 'ext/opencv/cvmat.cpp', line 4470

VALUE
rb_erode_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE element, iteration;
  rb_scan_args(argc, argv, "02", &element, &iteration);
  IplConvKernel* kernel = NIL_P(element) ? NULL : IPLCONVKERNEL_WITH_CHECK(element);
  try {
    cvErode(CVARR(self), CVARR(self), kernel, IF_INT(iteration, 1));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#rb_extract_orb(params[,mask]) ⇒ Array

Extracts ORB Features from an image

params (hash) - Various algorithm parameters, allowing the following keys:

:scale_factor   - Scale factor used to transform scale level n into scale level n-1. Defaults to 1.2
:n_levels       - Number of pyramid levels to consider when generating keypoints. Defaults to 3
:edge_threshold - Defaults to 31
:first_level    - The pyramid level of the image this function is being called on - level 0 is the largest level
                  of the pyramid, so any value > 0 will generate pyramid levels larger than the original image.
                  Defaults to 0
:keypoints      - If given, should be an array of tuples of [ x, y, size ] describing keypoints to generate
                  descriptors for. Defaults to nil
:keypoints_only - If true, descriptors will not be generated. Returned value will only be array(hash) containing
                  keypoints (given keypoints will be ignored). Defaults to false.
:num_keypoints  - If given, maximum number of desired keypoints to find. Defaults to 500

mask (CvMat) - The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels.

Returns array of keypoints (array of hashes) and descriptors (cvmat). Keypoints array contains entries with the following keys: ‘point’ => CvPoint, ‘size’ => float, ‘angle’ => float, ‘response’ => float, ‘octave’ => float

Returns:

  • (Array) 


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# File 'ext/opencv/cvmat.cpp', line 6421

VALUE
rb_extract_orb(int argc, VALUE *argv, VALUE self)
{
  // Commented by WBH until we can research the replacement for cv::ORB::CommonParams (which no longer exists)
  /*
  VALUE mask, orb_option;
  rb_scan_args(argc, argv, "02", &mask, &orb_option);

  orb_option = ORB_OPTION(orb_option);

  const cv::Mat selfMat(CVMAT(self));
  const CvSize size = cvGetSize(CVARR(self));

  cv::Mat descriptorsMat;

  if (mask == Qnil) {
    mask = new_object(cvSize(size.width, size.height), CV_MAKETYPE(CV_8U, 1));
    cvSet(CVARR(mask), cvScalarAll(255));
  }
  const cv::Mat maskMat(CVMAT(mask));

  std::vector<cv::KeyPoint> keypoints;
  VALUE inputKeypoints = DO_ORB_KEYPOINTS(orb_option);
  const bool descriptorsOnly = inputKeypoints != Qnil;
  if (descriptorsOnly) {
    const int inputKeypointsLength = RARRAY_LEN(inputKeypoints);
    for (int i = 0; i < inputKeypointsLength; ++i) {
      VALUE inputKeypoint = rb_ary_entry(inputKeypoints, i);
      keypoints.push_back(cv::KeyPoint(
        (float)NUM2DBL(rb_ary_entry(inputKeypoint, 0)),
        (float)NUM2DBL(rb_ary_entry(inputKeypoint, 1)),
        (float)NUM2DBL(rb_ary_entry(inputKeypoint, 2))
      ));
    }
  }

  try {
    cv::ORB::CommonParams params(DO_ORB_SCALE_FACTOR(orb_option),
                                 DO_ORB_N_LEVELS(orb_option),
                                 DO_ORB_EDGE_THRESHOLD(orb_option),
                                 DO_ORB_FIRST_LEVEL(orb_option));
    cv::ORB featuresFinder(DO_ORB_NUM_KEYPOINTS(orb_option), params);

    if (DO_ORB_KEYPOINTS_ONLY(orb_option)) {
      featuresFinder(selfMat, maskMat, keypoints);
    } else {
      featuresFinder(selfMat, maskMat, keypoints, descriptorsMat, descriptorsOnly);
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  VALUE keypointsList = rb_ary_new2(keypoints.size());
  for (size_t i = 0; i < keypoints.size(); ++i) {
    const cv::KeyPoint& keypoint = keypoints[i];

    VALUE keypointData = rb_hash_new();

    rb_hash_aset(keypointData, rb_str_new2("point"), cCvPoint::new_object(cvPoint(keypoint.pt.x, keypoint.pt.y)));
    rb_hash_aset(keypointData, rb_str_new2("size"), rb_float_new(keypoint.size));
    rb_hash_aset(keypointData, rb_str_new2("angle"), rb_float_new(keypoint.angle));
    rb_hash_aset(keypointData, rb_str_new2("response"), rb_float_new(keypoint.response));
    rb_hash_aset(keypointData, rb_str_new2("octave"), rb_float_new(keypoint.octave));

    rb_ary_store(keypointsList, i, keypointData);
  }

  VALUE result = Qnil;
  if (DO_ORB_KEYPOINTS_ONLY(orb_option)) {
    result = keypointsList;
  } else {
    CvMat descriptorsCvMat = descriptorsMat;
    VALUE descriptors = new_mat_kind_object(cvGetSize(&descriptorsCvMat), self, CV_8U, 1);
    cvCopy(&descriptorsCvMat, CVMAT(descriptors));

    if (descriptorsOnly) {
      result = descriptors;
    } else {
      result = rb_ary_new2(2);
      rb_ary_store(result, 0, keypointsList);
      rb_ary_store(result, 1, descriptors);
    }
  }

  return result;
  */
}

#extract_surf(params, mask = nil) ⇒ Array<CvSeq<CvSURFPoint>, Array<float>>

Extracts Speeded Up Robust Features from an image

Parameters:

  • params (CvSURFParams) —

    Various algorithm parameters put to the structure CvSURFParams.

  • mask (CvMat) (defaults to: nil) —

    The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels.

Returns:

  • (Array<CvSeq<CvSURFPoint>, Array<float>>) —

    Output vector of keypoints and descriptors.



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# File 'ext/opencv/cvmat.cpp', line 6359

VALUE
rb_extract_surf(int argc, VALUE *argv, VALUE self)
{
  VALUE _params, _mask;
  rb_scan_args(argc, argv, "11", &_params, &_mask);

  // Prepare arguments
  CvSURFParams params = *CVSURFPARAMS_WITH_CHECK(_params);
  CvMat* mask = MASK(_mask);
  VALUE storage = cCvMemStorage::new_object();
  CvSeq* keypoints = NULL;
  CvSeq* descriptors = NULL;

  // Compute SURF keypoints and descriptors
  try {
    cvExtractSURF(CVARR(self), mask, &keypoints, &descriptors, CVMEMSTORAGE(storage),
		  params, 0);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  VALUE _keypoints = cCvSeq::new_sequence(cCvSeq::rb_class(), keypoints, cCvSURFPoint::rb_class(), storage);
  
  // Create descriptor array
  const int DIM_SIZE = (params.extended) ? 128 : 64;
  const int NUM_KEYPOINTS = keypoints->total;
  VALUE _descriptors = rb_ary_new2(NUM_KEYPOINTS);
  for (int m = 0; m < NUM_KEYPOINTS; ++m) {
    VALUE elem = rb_ary_new2(DIM_SIZE);
    float *descriptor = (float*)cvGetSeqElem(descriptors, m);
    for (int n = 0; n < DIM_SIZE; ++n) {
      rb_ary_store(elem, n, rb_float_new(descriptor[n]));
    }
    rb_ary_store(_descriptors, m, elem);
  }
  
  return rb_assoc_new(_keypoints, _descriptors);
}

#fill_convex_poly(points, options = nil) ⇒ CvMat

Returns an image that is filled a convex polygon.

Parameters:

  • points (Array<CvPoint>) —

    Polygon vertices.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3464

VALUE
rb_fill_convex_poly(int argc, VALUE *argv, VALUE self)
{
  return rb_fill_convex_poly_bang(argc, argv, rb_rcv_clone(self));
}

#fill_convex_poly!(points, options = nil) ⇒ CvMat

Fills a convex polygon.

Parameters:

  • points (Array<CvPoint>) —

    Polygon vertices.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 3486

VALUE
rb_fill_convex_poly_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE points, drawing_option;
  int i, num_points;
  CvPoint *p;

  rb_scan_args(argc, argv, "11", &points, &drawing_option);
  Check_Type(points, T_ARRAY);
  drawing_option = DRAWING_OPTION(drawing_option);
  num_points = RARRAY_LEN(points);
  p = RB_ALLOC_N(CvPoint, num_points);
  for (i = 0; i < num_points; ++i)
    p[i] = VALUE_TO_CVPOINT(rb_ary_entry(points, i));

  try {
    cvFillConvexPoly(CVARR(self), p, num_points,
		     DO_COLOR(drawing_option),
		     DO_LINE_TYPE(drawing_option),
		     DO_SHIFT(drawing_option));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#fill_poly(points, options = nil) ⇒ CvMat

Returns an image that is filled the area bounded by one or more polygons.

Parameters:

  • points (Array<CvPoint>) —

    Array of polygons where each polygon is represented as an array of points.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3388

VALUE
rb_fill_poly(int argc, VALUE *argv, VALUE self)
{
  return rb_fill_poly_bang(argc, argv, self);
}

#fill_poly!(points, options = nil) ⇒ CvMat

Fills the area bounded by one or more polygons.

Parameters:

  • points (Array<CvPoint>) —

    Array of polygons where each polygon is represented as an array of points.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 3410

VALUE
rb_fill_poly_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE polygons, drawing_option;
  VALUE points;
  int i, j;
  int num_polygons;
  int *num_points;
  CvPoint **p;

  rb_scan_args(argc, argv, "11", &polygons, &drawing_option);
  Check_Type(polygons, T_ARRAY);
  drawing_option = DRAWING_OPTION(drawing_option);
  num_polygons = RARRAY_LEN(polygons);
  num_points = RB_ALLOC_N(int, num_polygons);

  p = RB_ALLOC_N(CvPoint*, num_polygons);
  for (j = 0; j < num_polygons; ++j) {
    points = rb_ary_entry(polygons, j);
    Check_Type(points, T_ARRAY);
    num_points[j] = RARRAY_LEN(points);
    p[j] = RB_ALLOC_N(CvPoint, num_points[j]);
    for (i = 0; i < num_points[j]; ++i) {
      p[j][i] = VALUE_TO_CVPOINT(rb_ary_entry(points, i));
    }
  }
  try {
    cvFillPoly(CVARR(self), p, num_points, num_polygons,
	       DO_COLOR(drawing_option),
	       DO_LINE_TYPE(drawing_option),
	       DO_SHIFT(drawing_option));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#filter2d(kernel[,anchor]) ⇒ Object

Convolves image with the kernel. Convolution kernel, single-channel floating point matrix (or same depth of self’s). If you want to apply different kernels to different channels, split the image using CvMat#split into separate color planes and process them individually.



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# File 'ext/opencv/cvmat.cpp', line 4767

VALUE
rb_filter2d(int argc, VALUE *argv, VALUE self)
{
  VALUE _kernel, _anchor;
  rb_scan_args(argc, argv, "11", &_kernel, &_anchor);
  CvMat* kernel = CVMAT_WITH_CHECK(_kernel);
  CvArr* self_ptr = CVARR(self);
  VALUE _dest = Qnil;
  try {
    _dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvFilter2D(self_ptr, CVARR(_dest), kernel, NIL_P(_anchor) ? cvPoint(-1,-1) : VALUE_TO_CVPOINT(_anchor));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return _dest;
}

#find_chessboard_corners(pattern_size, flag = CV_CALIB_CB_ADAPTIVE_THRESH) ⇒ Array<Array<CvPoint2D32f>, Boolean>

Finds the positions of internal corners of the chessboard.

Examples:

mat = CvMat.load('chessboard.jpg', 1)
gray = mat.BGR2GRAY
pattern_size = CvSize.new(4, 4)
corners, found = gray.find_chessboard_corners(pattern_size, CV_CALIB_CB_ADAPTIVE_THRESH)

if found
  corners = gray.find_corner_sub_pix(corners, CvSize.new(3, 3), CvSize.new(-1, -1), CvTermCriteria.new(20, 0.03))
end

result = mat.draw_chessboard_corners(pattern_size, corners, found)
w = GUI::Window.new('Result')
w.show result
GUI::wait_key

Parameters:

  • pattern_size (CvSize) —

    Number of inner corners per a chessboard row and column.

  • flags (Integer) —

    Various operation flags that can be zero or a combination of the following values.

    • CV_CALIB_CB_ADAPTIVE_THRESH

      • Use adaptive thresholding to convert the image to black and white, rather than a fixed threshold level (computed from the average image brightness).

    • CV_CALIB_CB_NORMALIZE_IMAGE

      • Normalize the image gamma with CvMat#equalize_hist() before applying fixed or adaptive thresholding.

    • CV_CALIB_CB_FILTER_QUADS

      • Use additional criteria (like contour area, perimeter, square-like shape) to filter out false quads extracted at the contour retrieval stage.

    • CALIB_CB_FAST_CHECK

      • Run a fast check on the image that looks for chessboard corners, and shortcut the call if none is found. This can drastically speed up the call in the degenerate condition when no chessboard is observed.

Returns:

  • (Array<Array<CvPoint2D32f>, Boolean>) —

    An array which includes the positions of internal corners of the chessboard, and a parameter indicating whether the complete board was found or not.



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# File 'ext/opencv/cvmat.cpp', line 3981

VALUE
rb_find_chessboard_corners(int argc, VALUE *argv, VALUE self)
{
  VALUE pattern_size_val, flag_val;
  rb_scan_args(argc, argv, "11", &pattern_size_val, &flag_val);

  int flag = NIL_P(flag_val) ? CV_CALIB_CB_ADAPTIVE_THRESH : NUM2INT(flag_val);
  CvSize pattern_size = VALUE_TO_CVSIZE(pattern_size_val);
  CvPoint2D32f* corners = RB_ALLOC_N(CvPoint2D32f, pattern_size.width * pattern_size.height);
  int num_found_corners = 0;
  int pattern_was_found = 0;
  try {
    pattern_was_found = cvFindChessboardCorners(CVARR(self), pattern_size, corners, &num_found_corners, flag);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  VALUE found_corners = rb_ary_new2(num_found_corners);
  for (int i = 0; i < num_found_corners; i++) {
    rb_ary_store(found_corners, i, cCvPoint2D32f::new_object(corners[i]));
  }

  VALUE found = (pattern_was_found > 0) ? Qtrue : Qfalse;
  return rb_assoc_new(found_corners, found);
}

#find_contours(find_contours_options) ⇒ CvContour, CvChain

Finds contours in binary image.

Parameters:

  • find_contours_options (Hash) —

    Options

Options Hash (find_contours_options):

  • :mode (Symbol) — default: :list —

    Retrieval mode.

    • :external - retrive only the extreme outer contours

    • :list - retrieve all the contours and puts them in the list.

    • :ccomp - retrieve all the contours and organizes them into two-level hierarchy: top level are external boundaries of the components, second level are bounda boundaries of the holes

    • :tree - retrieve all the contours and reconstructs the full hierarchy of nested contours Connectivity determines which neighbors of a pixel are considered.

  • :method (Symbol) — default: :approx_simple —

    Approximation method.

    • :code - output contours in the Freeman chain code. All other methods output polygons (sequences of vertices).

    • :approx_none - translate all the points from the chain code into points;

    • :approx_simple - compress horizontal, vertical, and diagonal segments, that is, the function leaves only their ending points;

    • :approx_tc89_l1, :approx_tc89_kcos - apply one of the flavors of Teh-Chin chain approximation algorithm.

  • :offset (CvPoint) — default: CvPoint.new(0, 0) —

    Offset, by which every contour point is shifted.

Returns:

  • (CvContour, CvChain) —

    Detected contours. If :method is :code, returns as CvChain, otherwise CvContour.



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# File 'ext/opencv/cvmat.cpp', line 5252

VALUE
rb_find_contours(int argc, VALUE *argv, VALUE self)
{
  return rb_find_contours_bang(argc, argv, copy(self));
}

#find_contours!(find_contours_options) ⇒ CvContour, CvChain

Finds contours in binary image.

Returns:

  • (CvContour, CvChain) —

    Detected contours. If :method is :code, returns as CvChain, otherwise CvContour.



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# File 'ext/opencv/cvmat.cpp', line 5266

VALUE
rb_find_contours_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE find_contours_option, klass, element_klass, storage;
  rb_scan_args(argc, argv, "01", &find_contours_option);
  CvSeq *contour = NULL;
  find_contours_option = FIND_CONTOURS_OPTION(find_contours_option);
  int mode = FC_MODE(find_contours_option);
  int method = FC_METHOD(find_contours_option);
  int header_size;
  if (method == CV_CHAIN_CODE) {
    klass = cCvChain::rb_class();
    element_klass = T_FIXNUM;
    header_size = sizeof(CvChain);
  }
  else {
    klass = cCvContour::rb_class();
    element_klass = cCvPoint::rb_class();
    header_size = sizeof(CvContour);
  }
  storage = cCvMemStorage::new_object();

  int count = 0;
  try {
    count = cvFindContours(CVARR(self), CVMEMSTORAGE(storage), &contour, header_size,
			   mode, method, FC_OFFSET(find_contours_option));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  if (count == 0)
    return Qnil;
  else
    return cCvSeq::new_sequence(klass, contour, element_klass, storage);
}

#find_corner_sub_pix(corners, win_size, zero_zone, criteria) ⇒ Array<CvPoint2D32f>

Refines the corner locations.

Parameters:

  • corners (Array<CvPoint>) —

    Initial coordinates of the input corners.

  • win_size (CvSize) —

    Half of the side length of the search window.

  • zero_zone (CvSize) —

    Half of the size of the dead region in the middle of the search zone over which the summation in the formula below is not done.

  • criteria (CvTermCriteria) —

    Criteria for termination of the iterative process of corner refinement.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 4020

VALUE
rb_find_corner_sub_pix(VALUE self, VALUE corners, VALUE win_size, VALUE zero_zone, VALUE criteria)
{
  Check_Type(corners, T_ARRAY);
  int count = RARRAY_LEN(corners);
  CvPoint2D32f* corners_buff = RB_ALLOC_N(CvPoint2D32f, count);
  VALUE* corners_ptr = RARRAY_PTR(corners);

  for (int i = 0; i < count; i++) {
    corners_buff[i] = *(CVPOINT2D32F(corners_ptr[i]));
  }

  try {
    cvFindCornerSubPix(CVARR(self), corners_buff, count, VALUE_TO_CVSIZE(win_size),
		       VALUE_TO_CVSIZE(zero_zone), VALUE_TO_CVTERMCRITERIA(criteria));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  VALUE refined_corners = rb_ary_new2(count);
  for (int i = 0; i < count; i++) {
    rb_ary_store(refined_corners, i, cCvPoint2D32f::new_object(corners_buff[i]));
  }

  return refined_corners;
}

#fit_ellipse ⇒ CvBox2D

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1313

VALUE
rb_fit_ellipse(VALUE self)
{
  VALUE box = cCvBox2D::new_object();
  try {
    const cv::Mat selfMat(CVMAT(self));
    *CVBOX2D(box) = cv::fitEllipse(selfMat);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return box;
}

#fit_line ⇒ Object

self should be 2-channel or 3-channel mat (where channels are [x,y] or [x,y,z])



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# File 'ext/opencv/cvmat.cpp', line 1294

VALUE
rb_fit_line(VALUE self, VALUE dest, VALUE distType, VALUE param, VALUE reps, VALUE aeps)
{
  try {
    const cv::Mat selfMat(CVMAT(self));
    cv::Mat destMat(CVMAT(dest));
    cv::fitLine(selfMat, destMat, NUM2INT(distType), NUM2DBL(param), NUM2DBL(reps), NUM2DBL(aeps));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#flip(flip_mode) ⇒ CvMat

Returns a fliped 2D array around vertical, horizontal, or both axes.

Parameters:

  • flip_mode (Symbol) —

    Flag to specify how to flip the array.

    • :x - Flipping around the x-axis.

    • :y - Flipping around the y-axis.

    • :xy - Flipping around both axes.

Returns:

  • (CvMat) —

    Flipped array



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# File 'ext/opencv/cvmat.cpp', line 1495

VALUE
rb_flip(int argc, VALUE *argv, VALUE self)
{
  return rb_flip_bang(argc, argv, copy(self));
}

#flip!(flip_mode) ⇒ CvMat

Flips a 2D array around vertical, horizontal, or both axes.

Parameters:

  • flip_mode (Symbol) —

    Flag to specify how to flip the array.

    • :x - Flipping around the x-axis.

    • :y - Flipping around the y-axis.

    • :xy - Flipping around both axes.

Returns:

  • (CvMat) —

    Flipped array



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# File 'ext/opencv/cvmat.cpp', line 1509

VALUE
rb_flip_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE format;
  int mode = 1;
  if (rb_scan_args(argc, argv, "01", &format) > 0) {
    Check_Type(format, T_SYMBOL);
    ID flip_mode = rb_to_id(format);
    if (flip_mode == rb_intern("x")) {
      mode = 1;
    }
    else if (flip_mode == rb_intern("y")) {
      mode = 0;
    }
    else if (flip_mode == rb_intern("xy")) {
      mode = -1;
    }
  }
  try {
    cvFlip(CVARR(self), NULL, mode);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#flood_fill(seed_point, new_val, lo_diff = CvScalar.new(0), up_diff = CvScalar.new(0), flood_fill_option = nil) ⇒ Array<CvMat, CvConnectedComp>

Fills a connected component with the given color.

Parameters:

  • seed_point (CvPoint) —

    Starting point.

  • new_val (CvScalar) —

    New value of the repainted domain pixels.

  • lo_diff (CvScalar) (defaults to: CvScalar.new(0)) —

    Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value.

  • up_diff (CvScalar) (defaults to: CvScalar.new(0)) —

    Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value.

  • flood_fill_option (Hash) (defaults to: nil)

Options Hash (flood_fill_option):

  • :connectivity (Integer) — default: 4 —

    Connectivity determines which neighbors of a pixel are considered (4 or 8).

  • :fixed_range (Boolean) — default: false —

    If set the difference between the current pixel and seed pixel is considered, otherwise difference between neighbor pixels is considered (the range is floating).

  • :mask_only (Boolean) — default: false —

    If set, the function does not fill the image(new_val is ignored), but the fills mask.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 5146

VALUE
rb_flood_fill(int argc, VALUE *argv, VALUE self)
{
  return rb_flood_fill_bang(argc, argv, copy(self));
}

#flood_fill!(seed_point, new_val, lo_diff = CvScalar.new(0), up_diff = CvScalar.new(0), flood_fill_option = nil) ⇒ Object

Fills a connected component with the given color.



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# File 'ext/opencv/cvmat.cpp', line 5160

VALUE
rb_flood_fill_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE seed_point, new_val, lo_diff, up_diff, flood_fill_option;
  rb_scan_args(argc, argv, "23", &seed_point, &new_val, &lo_diff, &up_diff, &flood_fill_option);
  flood_fill_option = FLOOD_FILL_OPTION(flood_fill_option);
  int flags = FF_CONNECTIVITY(flood_fill_option);
  if (FF_FIXED_RANGE(flood_fill_option)) {
    flags |= CV_FLOODFILL_FIXED_RANGE;
  }
  if (FF_MASK_ONLY(flood_fill_option)) {
    flags |= CV_FLOODFILL_MASK_ONLY;
  }
  cv::Rect rect;
  VALUE mask = FF_MASK(flood_fill_option);
  try {
    if (mask == Qnil) {
      CvSize size = cvGetSize(CVARR(self));
      mask = new_object(cvSize(size.width + 2, size.height + 2), CV_MAKETYPE(CV_8U, 1));
      cvSetZero(CVARR(mask));
    }

    cv::Mat selfMat(CVMAT(self));
    cv::Mat maskMat(CVMAT(mask));

    cv::floodFill(
      selfMat,
      maskMat,
      cv::Point(VALUE_TO_CVPOINT(seed_point)),
      cv::Scalar(VALUE_TO_CVSCALAR(new_val)),
      &rect,
      cv::Scalar(NIL_P(lo_diff) ? cvScalar(0) : VALUE_TO_CVSCALAR(lo_diff)),
      cv::Scalar(NIL_P(up_diff) ? cvScalar(0) : VALUE_TO_CVSCALAR(up_diff)),
      flags);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_ary_new3(3, self, cCvRect::new_object(cvRect(rect.x, rect.y, rect.width, rect.height)), mask);
}

#flood_fill_mask(seed_point, mask, lo_diff, up_diff, connectivity, fixed_range) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 5201

VALUE
rb_flood_fill_mask(VALUE self, VALUE seed_point, VALUE mask, VALUE lo_diff, VALUE up_diff, VALUE connectivity, VALUE fixed_range)
{
  int flags = NUM2INT(connectivity);
  if (RTEST(fixed_range)) {
    flags |= CV_FLOODFILL_FIXED_RANGE;
  }
  flags |= CV_FLOODFILL_MASK_ONLY;
  cv::Rect rect;
  try {
    cv::Mat selfMat(CVMAT(self));
    cv::Mat maskMat(CVMAT(mask));

    cv::floodFill(
      selfMat,
      maskMat,
      cv::Point(VALUE_TO_CVPOINT(seed_point)),
      cv::Scalar(cvScalar(0)),
      &rect,
      cv::Scalar(NIL_P(lo_diff) ? cvScalar(0) : VALUE_TO_CVSCALAR(lo_diff)),
      cv::Scalar(NIL_P(up_diff) ? cvScalar(0) : VALUE_TO_CVSCALAR(up_diff)),
      flags);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return cCvRect::new_object(cvRect(rect.x, rect.y, rect.width, rect.height));
}

#ge(val) ⇒ CvMat

Performs the per-element comparison “greater than or equal” of two arrays or an array and scalar value.

Parameters:

  • val (CvMat, CvScalar, Number) —

    Array, scalar or number to compare

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2168

VALUE
rb_ge(VALUE self, VALUE val)
{
  VALUE dest = new_mat_kind_object(cvGetSize(CVARR(self)), self, CV_8U, 1);
  return rb_cmp_internal(self, val, dest, CV_CMP_GE);
}

#get_cols(<i>n</i>)) ⇒ Return column #get_cols(<i>n1, n2, ...</i>)) ⇒ Return Array of columns

Return column(or columns) of matrix. argument should be Fixnum or CvSlice compatible object.

Overloads:

  • #get_cols(<i>n</i>)) ⇒ Return column

    Returns:

    • (Return column)
  • #get_cols(<i>n1, n2, ...</i>)) ⇒ Return Array of columns

    Returns:



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# File 'ext/opencv/cvmat.cpp', line 821

VALUE
rb_get_cols(VALUE self, VALUE args)
{
  int len = RARRAY_LEN(args);
  if (len < 1)
    rb_raise(rb_eArgError, "wrong number of argument.(more than 1)");
  VALUE ary = rb_ary_new2(len);
  for (int i = 0; i < len; ++i) {
    VALUE value = rb_ary_entry(args, i);
    CvMat* col = NULL;
    try {
      if (FIXNUM_P(value))
	col = cvGetCol(CVARR(self), RB_CVALLOC(CvMat), FIX2INT(value));
      else {
	CvSlice slice = VALUE_TO_CVSLICE(value);
	col = cvGetCols(CVARR(self), RB_CVALLOC(CvMat), slice.start_index, slice.end_index);
      }
    }
    catch (cv::Exception& e) {
      if (col != NULL)
	cvReleaseMat(&col);
      raise_cverror(e);
    }
    rb_ary_store(ary, i, DEPEND_OBJECT(rb_klass, col, self));
  }
  return RARRAY_LEN(ary) > 1 ? ary : rb_ary_entry(ary, 0);
}

#get_rows(<i>n</i>)) ⇒ Return row #get_rows(<i>n1, n2, ...</i>)) ⇒ Return Array of row

Return row(or rows) of matrix. argument should be Fixnum or CvSlice compatible object.

Overloads:

  • #get_rows(<i>n</i>)) ⇒ Return row

    Returns:

    • (Return row)
  • #get_rows(<i>n1, n2, ...</i>)) ⇒ Return Array of row

    Returns:

    • (Return Array of row) 


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# File 'ext/opencv/cvmat.cpp', line 783

VALUE
rb_get_rows(VALUE self, VALUE args)
{
  int len = RARRAY_LEN(args);
  if (len < 1)
    rb_raise(rb_eArgError, "wrong number of argument.(more than 1)");
  VALUE ary = rb_ary_new2(len);
  for (int i = 0; i < len; ++i) {
    VALUE value = rb_ary_entry(args, i);

    CvMat* row = NULL;
    try {
      if (FIXNUM_P(value))
	row = cvGetRow(CVARR(self), RB_CVALLOC(CvMat), FIX2INT(value));
      else {
	CvSlice slice = VALUE_TO_CVSLICE(value);
	row = cvGetRows(CVARR(self), RB_CVALLOC(CvMat), slice.start_index, slice.end_index);
      }
    }
    catch (cv::Exception& e) {
      if (row != NULL)
	cvReleaseMat(&row);
      raise_cverror(e);
    }
    rb_ary_store(ary, i, DEPEND_OBJECT(rb_klass, row, self));
  }
  return RARRAY_LEN(ary) > 1 ? ary : rb_ary_entry(ary, 0);
}

#good_features_to_track(quality_level, min_distance, good_features_to_track_option = {}) ⇒ Array<CvPoint2D32f>

Determines strong corners on an image.

Parameters:

  • quality_level (Number) —

    Parameter characterizing the minimal accepted quality of image corners. The parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue or the Harris function response.

  • min_distance (Number) —

    Minimum possible Euclidean distance between the returned corners.

  • good_features_to_track_option (Hash) (defaults to: {}) —

    Options.

Options Hash (good_features_to_track_option):

  • :mask (CvMat) — default: nil —

    Optional region of interest. If the image is not empty (it needs to have the type CV_8UC1 and the same size as image), it specifies the region in which the corners are detected.

  • :block_size (Integer) — default: 3 —

    Size of an average block for computing a derivative covariation matrix over each pixel neighborhood.

  • :use_harris (Boolean) — default: false —

    Parameter indicating whether to use a Harris detector.

  • :k (Number) — default: 0.04 —

    Free parameter of the Harris detector.

Returns:

  • (Array<CvPoint2D32f>) —

    Output vector of detected corners.



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# File 'ext/opencv/cvmat.cpp', line 4068

VALUE
rb_good_features_to_track(int argc, VALUE *argv, VALUE self)
{
  VALUE quality_level, min_distance, good_features_to_track_option;
  rb_scan_args(argc, argv, "21", &quality_level, &min_distance, &good_features_to_track_option);
  good_features_to_track_option = GOOD_FEATURES_TO_TRACK_OPTION(good_features_to_track_option);
  int np = GF_MAX(good_features_to_track_option);
  if (np <= 0)
    rb_raise(rb_eArgError, "option :max should be positive value.");

  CvMat *self_ptr = CVMAT(self);
  CvPoint2D32f *p32 = (CvPoint2D32f*)rb_cvAlloc(sizeof(CvPoint2D32f) * np);
  int type = CV_MAKETYPE(CV_32F, 1);
  CvMat* eigen = rb_cvCreateMat(self_ptr->rows, self_ptr->cols, type);
  CvMat* tmp = rb_cvCreateMat(self_ptr->rows, self_ptr->cols, type);
  try {
    cvGoodFeaturesToTrack(self_ptr, &eigen, &tmp, p32, &np, NUM2DBL(quality_level), NUM2DBL(min_distance),
			  GF_MASK(good_features_to_track_option),
			  GF_BLOCK_SIZE(good_features_to_track_option),
			  GF_USE_HARRIS(good_features_to_track_option),
			  GF_K(good_features_to_track_option));
  }
  catch (cv::Exception& e) {
    if (eigen != NULL)
      cvReleaseMat(&eigen);
    if (tmp != NULL)
      cvReleaseMat(&tmp);
    if (p32 != NULL)
      cvFree(&p32);
    raise_cverror(e);
  }
  VALUE corners = rb_ary_new2(np);
  for (int i = 0; i < np; ++i)
    rb_ary_store(corners, i, cCvPoint2D32f::new_object(p32[i]));
  cvFree(&p32);
  cvReleaseMat(&eigen);
  cvReleaseMat(&tmp);
  return corners;
}

#grab_cut ⇒ Object

Does grab cut segmentation.



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# File 'ext/opencv/cvmat.cpp', line 5489

VALUE
rb_grab_cut(VALUE self, VALUE mask, VALUE rect, VALUE bgdModel, VALUE fgdModel, VALUE iterCount, VALUE mode)
{
  if (!(rb_obj_is_kind_of(self, cCvMat::rb_class())) || cvGetElemType(CVARR(self)) != CV_8UC3)
    rb_raise(rb_eTypeError, "image (self) should be 8-bit 3-channel image.");

  if (!(rb_obj_is_kind_of(mask, cCvMat::rb_class())) || cvGetElemType(CVARR(mask)) != CV_8UC1)
    rb_raise(rb_eTypeError, "argument 1 (mask) should be mask image.");

  const int INVALID_TYPE = -1;
  int valid_mode = CVMETHOD("GRAB_CUT_MODE", mode, INVALID_TYPE);

  try {
    const cv::Mat selfMat(CVMAT(self));
    cv::Mat maskMat(CVMAT(mask));
    cv::Mat bgMat(CVMAT(bgdModel));
    cv::Mat fgMat(CVMAT(fgdModel));

    cv::grabCut(selfMat, maskMat, VALUE_TO_CVRECT(rect), bgMat, fgMat, NUM2INT(iterCount), valid_mode);
  } catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return mask;
}

#grab_cut2 ⇒ Array, ...

Does grab cut segmentation.

Returns ].

Returns:

  • (Array, cvmat(bgdCenters:cv32fc1), cvmat(fgdCenters:cv32fc1)) —

    ]



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# File 'ext/opencv/cvmat.cpp', line 5520

VALUE
rb_grab_cut2(VALUE self, VALUE mask, VALUE rect, VALUE bgdModel, VALUE fgdModel, VALUE iterCount, VALUE mode,
             VALUE bgdLabels, VALUE fgdLabels, VALUE bgdCenters, VALUE fgdCenters)
{
  if (!(rb_obj_is_kind_of(self, cCvMat::rb_class())) || cvGetElemType(CVARR(self)) != CV_8UC3)
    rb_raise(rb_eTypeError, "image (self) should be 8-bit 3-channel image.");

  if (!(rb_obj_is_kind_of(mask, cCvMat::rb_class())) || cvGetElemType(CVARR(mask)) != CV_8UC1)
    rb_raise(rb_eTypeError, "argument 1 (mask) should be mask image.");

  const int INVALID_TYPE = -1;
  int valid_mode = CVMETHOD("GRAB_CUT_MODE", mode, INVALID_TYPE);

  try {
    const cv::Mat selfMat(CVMAT(self));
    cv::Mat maskMat(CVMAT(mask));
    cv::Mat bgMat(CVMAT(bgdModel));
    cv::Mat fgMat(CVMAT(fgdModel));
    
    int labelsMode = cv::GC_LABELS_INIT_KMEANS;

    if (bgdLabels == Qnil) {
      bgdLabels = new_object(cvSize(1, 1), CV_MAKETYPE(CV_32F, 2));
      cvSetZero(CVARR(bgdLabels));
    } else {
      labelsMode = cv::GC_LABELS_USE_INITIAL;
    }
    cv::Mat bgdLabelsMat(CVMAT(bgdLabels));

    if (fgdLabels == Qnil) {
      fgdLabels = new_object(cvSize(1, 1), CV_MAKETYPE(CV_32F, 2));
      cvSetZero(CVARR(fgdLabels));
    } else {
      labelsMode = cv::GC_LABELS_USE_INITIAL;
    }
    cv::Mat fgdLabelsMat(CVMAT(fgdLabels));

    int centersMode = cv::GC_CENTERS_MODE_INIT_RANDOM;

    if (bgdCenters == Qnil) {
      // K=5 (# of clusters) for 3-dimensions (RGB)
      bgdCenters = new_object(cvSize(3, 5), CV_MAKETYPE(CV_32F, 2));
      cvSetZero(CVARR(bgdCenters));
    } else {
      centersMode = cv::GC_CENTERS_MODE_USE_INITIAL;
    }
    cv::Mat bgdCentersMat(CVMAT(bgdCenters));

    if (fgdCenters == Qnil) {
      // K=5 (# of clusters) for 3-dimensions (RGB)
      fgdCenters = new_object(cvSize(3, 5), CV_MAKETYPE(CV_32F, 2));
      cvSetZero(CVARR(fgdCenters));
    } else {
      centersMode = cv::GC_CENTERS_MODE_USE_INITIAL;
    }
    cv::Mat fgdCentersMat(CVMAT(fgdCenters));

    cv::grabCut2(selfMat, maskMat, VALUE_TO_CVRECT(rect), bgMat, fgMat, bgdLabelsMat, fgdLabelsMat, bgdCentersMat, fgdCentersMat, NUM2INT(iterCount), valid_mode, labelsMode, centersMode);

    CvMat bgdLabelsTmp = bgdLabelsMat;
    bgdLabels = new_object(bgdLabelsTmp.rows, bgdLabelsTmp.cols, bgdLabelsTmp.type);
    cvCopy(&bgdLabelsTmp, CVMAT(bgdLabels));
    
    CvMat fgdLabelsTmp = fgdLabelsMat;
    fgdLabels = new_object(fgdLabelsTmp.rows, fgdLabelsTmp.cols, fgdLabelsTmp.type);
    cvCopy(&fgdLabelsTmp, CVMAT(fgdLabels));
    
    CvMat bgdCentersTmp = bgdCentersMat;
    bgdCenters = new_object(bgdCentersTmp.rows, bgdCentersTmp.cols, bgdCentersTmp.type);
    cvCopy(&bgdCentersTmp, CVMAT(bgdCenters));
    
    CvMat fgdCentersTmp = fgdCentersMat;
    fgdCenters = new_object(fgdCentersTmp.rows, fgdCentersTmp.cols, fgdCentersTmp.type);
    cvCopy(&fgdCentersTmp, CVMAT(fgdCenters));
  } catch (cv::Exception& e) {
    raise_cverror(e);
  }
    
  return rb_ary_new3(5, mask, bgdLabels, fgdLabels, bgdCenters, fgdCenters);
}

#gt(val) ⇒ CvMat

Performs the per-element comparison “greater than” of two arrays or an array and scalar value.

Parameters:

  • val (CvMat, CvScalar, Number) —

    Array, scalar or number to compare

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2152

VALUE
rb_gt(VALUE self, VALUE val)
{
  VALUE dest = new_mat_kind_object(cvGetSize(CVARR(self)), self, CV_8U, 1);
  return rb_cmp_internal(self, val, dest, CV_CMP_GT);
}

#rows ⇒ Integer Also known as: rows

Returns number of rows of the matrix.

Returns:

  • (Integer) —

    Number of rows of the matrix



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# File 'ext/opencv/cvmat.cpp', line 449

VALUE
rb_height(VALUE self)
{
  return INT2NUM(CVMAT(self)->height);
}

#hough_circles(method, dp, min_dist, param1, param2, min_radius = 0, max_radius = 0) ⇒ CvSeq<CvCircle32f>

Finds circles in a grayscale image using the Hough transform.

Parameters:

  • method (Integer) —

    Detection method to use. Currently, the only implemented method is CV_HOUGH_GRADIENT.

  • dp (Number) —

    Inverse ratio of the accumulator resolution to the image resolution. For example, if dp=1, the accumulator has the same resolution as the input image. If dp=2, the accumulator has half as big width and height.

  • min_dist (Number) —

    Minimum distance between the centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed.

  • param1 (Number) —

    First method-specific parameter. In case of CV_HOUGH_GRADIENT, it is the higher threshold of the two passed to the #canny detector (the lower one is twice smaller).

  • param2 (Number) —

    Second method-specific parameter. In case of CV_HOUGH_GRADIENT, it is the accumulator threshold for the circle centers at the detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 5704

VALUE
rb_hough_circles(int argc, VALUE *argv, VALUE self)
{
  const int INVALID_TYPE = -1;
  VALUE method, dp, min_dist, param1, param2, min_radius, max_radius, storage;
  rb_scan_args(argc, argv, "52", &method, &dp, &min_dist, &param1, &param2, 
	       &min_radius, &max_radius);
  storage = cCvMemStorage::new_object();
  int method_flag = CVMETHOD("HOUGH_TRANSFORM_METHOD", method, INVALID_TYPE);
  if (method_flag == INVALID_TYPE)
    rb_raise(rb_eArgError, "Invalid method: %d", method_flag);
  CvSeq *seq = NULL;
  try {
    seq = cvHoughCircles(CVARR(self), CVMEMSTORAGE(storage),
			 method_flag, NUM2DBL(dp), NUM2DBL(min_dist),
			 NUM2DBL(param1), NUM2DBL(param2),
			 IF_INT(min_radius, 0), IF_INT(max_radius, 0));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return cCvSeq::new_sequence(cCvSeq::rb_class(), seq, cCvCircle32f::rb_class(), storage);
}

#hough_lines(method, rho, theta, threshold, param1, param2) ⇒ CvSeq<CvLine, CvTwoPoints>

Finds lines in binary image using a Hough transform.

Parameters:

  • method (Integer) —

    The Hough transform variant, one of the following:

    • CV_HOUGH_STANDARD - classical or standard Hough transform.

    • CV_HOUGH_PROBABILISTIC - probabilistic Hough transform (more efficient in case if picture contains a few long linear segments).

    • CV_HOUGH_MULTI_SCALE - multi-scale variant of the classical Hough transform. The lines are encoded the same way as CV_HOUGH_STANDARD.

  • rho (Number) —

    Distance resolution in pixel-related units.

  • theta (Number) —

    Angle resolution measured in radians.

  • threshold (Number) —

    Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold.

  • param1 (Number) —

    The first method-dependent parameter:

    • For the classical Hough transform it is not used (0).

    • For the probabilistic Hough transform it is the minimum line length.

    • For the multi-scale Hough transform it is the divisor for the distance resolution. (The coarse distance resolution will be rho and the accurate resolution will be (rho / param1)).

  • param2 (Number) —

    The second method-dependent parameter:

    • For the classical Hough transform it is not used (0).

    • For the probabilistic Hough transform it is the maximum gap between line segments lying on the same line to treat them as a single line segment (i.e. to join them).

    • For the multi-scale Hough transform it is the divisor for the angle resolution. (The coarse angle resolution will be theta and the accurate resolution will be (theta / param2).)

Returns:

  • (CvSeq<CvLine, CvTwoPoints>) —

    Output lines. If method is CV_HOUGH_STANDARD or CV_HOUGH_MULTI_SCALE, the class of elements is CvLine, otherwise CvTwoPoints.



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# File 'ext/opencv/cvmat.cpp', line 5650

VALUE
rb_hough_lines(int argc, VALUE *argv, VALUE self)
{
  const int INVALID_TYPE = -1;
  VALUE method, rho, theta, threshold, p1, p2;
  rb_scan_args(argc, argv, "42", &method, &rho, &theta, &threshold, &p1, &p2);
  int method_flag = CVMETHOD("HOUGH_TRANSFORM_METHOD", method, INVALID_TYPE);
  if (method_flag == INVALID_TYPE)
    rb_raise(rb_eArgError, "Invalid method: %d", method_flag);
  VALUE storage = cCvMemStorage::new_object();
  CvSeq *seq = NULL;
  try {
    seq = cvHoughLines2(CVARR(copy(self)), CVMEMSTORAGE(storage),
			method_flag, NUM2DBL(rho), NUM2DBL(theta), NUM2INT(threshold),
			IF_DBL(p1, 0), IF_DBL(p2, 0));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  switch (method_flag) {
  case CV_HOUGH_STANDARD:
  case CV_HOUGH_MULTI_SCALE:
    return cCvSeq::new_sequence(cCvSeq::rb_class(), seq, cCvLine::rb_class(), storage);
    break;
  case CV_HOUGH_PROBABILISTIC:
    return cCvSeq::new_sequence(cCvSeq::rb_class(), seq, cCvTwoPoints::rb_class(), storage);
    break;
  default:
    break;
  }

  return Qnil;
}

#identity(value) ⇒ CvMat

Returns a scaled identity matrix.

arr(i, j) = value if i = j, 0 otherwise

Parameters:

  • value (CvScalar) —

    Value to assign to diagonal elements.

Returns:

  • (CvMat) —

    Scaled identity matrix.



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# File 'ext/opencv/cvmat.cpp', line 1365

VALUE
rb_set_identity(int argc, VALUE *argv, VALUE self)
{
  return rb_set_identity_bang(argc, argv, copy(self));
}

#identity!(value) ⇒ CvMat

Initializes a scaled identity matrix.

arr(i, j) = value if i = j, 0 otherwise

Parameters:

  • value (CvScalar) —

    Value to assign to diagonal elements.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1379

VALUE
rb_set_identity_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE val;
  CvScalar value;
  if (rb_scan_args(argc, argv, "01",  &val) < 1)
    value = cvRealScalar(1);
  else
    value = VALUE_TO_CVSCALAR(val);

  try {
    cvSetIdentity(CVARR(self), value);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#in_range(min, max) ⇒ CvMat

Checks if array elements lie between the elements of two other arrays.

Parameters:

  • min (CvMat, CvScalar) —

    Inclusive lower boundary array or a scalar.

  • max (CvMat, CvScalar) —

    Inclusive upper boundary array or a scalar.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2233

VALUE
rb_in_range(VALUE self, VALUE min, VALUE max)
{
  CvArr* self_ptr = CVARR(self);
  CvSize size = cvGetSize(self_ptr);
  VALUE dest = new_object(size, CV_8UC1);
  try {
    if (rb_obj_is_kind_of(min, rb_klass) && rb_obj_is_kind_of(max, rb_klass))
      cvInRange(self_ptr, CVARR(min), CVARR(max), CVARR(dest));
    else if (rb_obj_is_kind_of(min, rb_klass)) {
      VALUE tmp = new_object(size, cvGetElemType(self_ptr));
      cvSet(CVARR(tmp), VALUE_TO_CVSCALAR(max));
      cvInRange(self_ptr, CVARR(min), CVARR(tmp), CVARR(dest));
    }
    else if (rb_obj_is_kind_of(max, rb_klass)) {
      VALUE tmp = new_object(size, cvGetElemType(self_ptr));
      cvSet(CVARR(tmp), VALUE_TO_CVSCALAR(min));
      cvInRange(self_ptr, CVARR(tmp), CVARR(max), CVARR(dest));
    }
    else
      cvInRangeS(self_ptr, VALUE_TO_CVSCALAR(min), VALUE_TO_CVSCALAR(max), CVARR(dest));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#inpaint(inpaint_method, mask, radius) ⇒ Object

Inpaints the selected region in the image The radius of circlular neighborhood of each point inpainted that is considered by the algorithm.



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# File 'ext/opencv/cvmat.cpp', line 5735

VALUE
rb_inpaint(VALUE self, VALUE inpaint_method, VALUE mask, VALUE radius)
{
  const int INVALID_TYPE = -1;
  VALUE dest = Qnil;
  int method = CVMETHOD("INPAINT_METHOD", inpaint_method, INVALID_TYPE);
  if (method == INVALID_TYPE)
    rb_raise(rb_eArgError, "Invalid method");
  try {
    CvArr* self_ptr = CVARR(self);
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvInpaint(self_ptr, MASK(mask), CVARR(dest), NUM2DBL(radius), method);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#inside?(point) ⇒ Boolean #inside?(rect) ⇒ Boolean

Tests whether a coordinate or rectangle is inside of the matrix

Overloads:

  • #inside?(point) ⇒ Boolean

    Parameters:

    • obj (#x, #y) —

      Tested coordinate

  • #inside?(rect) ⇒ Boolean

    Parameters:

Returns:

  • (Boolean) —

    If the point or rectangle is inside of the matrix, return true. If not, return false.



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# File 'ext/opencv/cvmat.cpp', line 376

VALUE
rb_inside_q(VALUE self, VALUE object)
{
  if (cCvPoint::rb_compatible_q(cCvPoint::rb_class(), object)) {
    CvMat *mat = CVMAT(self);
    int x = NUM2INT(rb_funcall(object, rb_intern("x"), 0));
    int y = NUM2INT(rb_funcall(object, rb_intern("y"), 0));
    if (cCvRect::rb_compatible_q(cCvRect::rb_class(), object)) {
      int width = NUM2INT(rb_funcall(object, rb_intern("width"), 0));
      int height = NUM2INT(rb_funcall(object, rb_intern("height"), 0));
      return (x >= 0) && (y >= 0) && (x < mat->width) && ((x + width) < mat->width)
	&& (y < mat->height) && ((y + height) < mat->height) ? Qtrue : Qfalse;
    }
    else {
      return (x >= 0) && (y >= 0) && (x < mat->width) && (y < mat->height) ? Qtrue : Qfalse;
    }
  }
  rb_raise(rb_eArgError, "argument 1 should have method \"x\", \"y\"");
  return Qnil;
}

#integral(need_sqsum = false, need_tilted_sum = false) ⇒ Array?

Calculates integral images. If need_sqsum = true, calculate the integral image for squared pixel values. If need_tilted_sum = true, calculate the integral for the image rotated by 45 degrees.

sum(X,Y)=sumx<X,y<Yimage(x,y)
sqsum(X,Y)=sumx<X,y<Yimage(x,y)2
tilted_sum(X,Y)=sumy<Y,abs(x-X)<yimage(x,y)

Using these integral images, one may calculate sum, mean, standard deviation over arbitrary up-right or rotated rectangular region of the image in a constant time.

Returns:

  • (Array, nil) 


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# File 'ext/opencv/cvmat.cpp', line 4843

VALUE
rb_integral(int argc, VALUE *argv, VALUE self)
{
  VALUE need_sqsum = Qfalse, need_tiled_sum = Qfalse;
  rb_scan_args(argc, argv, "02", &need_sqsum, &need_tiled_sum);

  VALUE sum = Qnil;
  VALUE sqsum = Qnil;
  VALUE tiled_sum = Qnil;
  CvArr* self_ptr = CVARR(self);
  try {
    CvSize self_size = cvGetSize(self_ptr);
    CvSize size = cvSize(self_size.width + 1, self_size.height + 1);
    int type_cv64fcn = CV_MAKETYPE(CV_64F, CV_MAT_CN(cvGetElemType(self_ptr)));
    sum = cCvMat::new_object(size, type_cv64fcn);
    sqsum = (need_sqsum == Qtrue ? cCvMat::new_object(size, type_cv64fcn) : Qnil);
    tiled_sum = (need_tiled_sum == Qtrue ? cCvMat::new_object(size, type_cv64fcn) : Qnil);
    cvIntegral(self_ptr, CVARR(sum), (need_sqsum == Qtrue) ? CVARR(sqsum) : NULL,
	       (need_tiled_sum == Qtrue) ? CVARR(tiled_sum) : NULL);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  
  if ((need_sqsum != Qtrue) && (need_tiled_sum != Qtrue))
    return sum;
  else {
    VALUE dest = rb_ary_new3(1, sum);
    if (need_sqsum == Qtrue)
      rb_ary_push(dest, sqsum);
    if (need_tiled_sum == Qtrue)
      rb_ary_push(dest, tiled_sum);
    return dest;
  }
}

#invert(inversion_method = :lu) ⇒ Number

Finds inverse or pseudo-inverse of matrix.

Parameters:

  • inversion_method (Symbol) —

    Inversion method.

    • :lu - Gaussian elimincation with optimal pivot element chose.

    • :svd - Singular value decomposition(SVD) method.

    • :svd_sym - SVD method for a symmetric positively-defined matrix.

Returns:

  • (Number) —

    Inverse or pseudo-inverse of matrix.



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# File 'ext/opencv/cvmat.cpp', line 2817

VALUE
rb_invert(int argc, VALUE *argv, VALUE self)
{
  VALUE symbol;
  rb_scan_args(argc, argv, "01", &symbol);
  int method = CVMETHOD("INVERSION_METHOD", symbol, CV_LU);
  VALUE dest = Qnil;
  CvArr* self_ptr = CVARR(self);
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvInvert(self_ptr, CVARR(dest), method);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#kmeans(k, termcrit) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 5470

VALUE
rb_kmeans(VALUE self, VALUE k, VALUE termcrit)
{
  VALUE labels = new_object(CVMAT(self)->height, 1, CV_32SC1);
  try {
    cvKMeans2(CVARR(self), NUM2INT(k), CVARR(labels), *CVTERMCRITERIA(termcrit));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return labels;
}

#laplace(aperture_size = 3) ⇒ Object

Calculates the Laplacian of an image.

Parameters:

  • aperture_size (Integer) —

    Aperture size used to compute the second-derivative filters. The size must be positive and odd.

Returns:

  • Output image.



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# File 'ext/opencv/cvmat.cpp', line 3734

VALUE
rb_laplace(int argc, VALUE *argv, VALUE self)
{
  VALUE aperture_size, dest;
  if (rb_scan_args(argc, argv, "01", &aperture_size) < 1)
    aperture_size = INT2FIX(3);
  CvMat* self_ptr = CVMAT(self);
  switch(CV_MAT_DEPTH(self_ptr->type)) {
  case CV_8U:
    dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_8U, 1);
    break;
  case CV_32F:
    dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_32F, 1);
    break;
  default:
    rb_raise(rb_eArgError, "source depth should be CV_8U or CV_32F.");
  }

  try {
    cvLaplace(self_ptr, CVARR(dest), NUM2INT(aperture_size));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#laplace2(<i>ksize = 1, scale = 1, delta = 0</i>)) ⇒ Object

Calculates first, second, third or mixed image derivatives using extended Sobel operator. self should be single-channel 8bit unsigned or 32bit floating-point.



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# File 'ext/opencv/cvmat.cpp', line 3770

VALUE
rb_laplace2(int argc, VALUE *argv, VALUE self)
{
  VALUE dest, delta, ksize, scale;
  int ddepth;
  rb_scan_args(argc, argv, "03", &ksize, &scale, &delta);

  CvMat* self_ptr = CVMAT(self);
  if(CV_MAT_DEPTH(self_ptr->type) == CV_8U) {
  	ddepth = CV_16S; // An 8U datatype would overflow due to negative derivative values
  } else {
  	ddepth = CV_MAT_DEPTH(self_ptr->type);
  }

	dest = new_mat_kind_object(cvGetSize(self_ptr), self, ddepth, 1);

	if(NIL_P(ksize)) ksize = INT2FIX(1);
	if(NIL_P(scale)) scale = 1.0;
	if(NIL_P(delta)) delta = 0.0;

  try {
    const cv::Mat selfMat(CVMAT(self)); // WBH convert openCv1-style cvMat to openCv2-style cv::Mat
    cv::Mat destMat(CVMAT(dest));
    cv::Laplacian(selfMat, destMat, ddepth, ksize, scale, delta);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#le(val) ⇒ CvMat

Performs the per-element comparison “less than or equal” of two arrays or an array and scalar value.

Parameters:

  • val (CvMat, CvScalar, Number) —

    Array, scalar or number to compare

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2200

VALUE
rb_le(VALUE self, VALUE val)
{
  VALUE dest = new_mat_kind_object(cvGetSize(CVARR(self)), self, CV_8U, 1);
  return rb_cmp_internal(self, val, dest, CV_CMP_LE);
}

#line(p1, p2, options = nil) ⇒ CvMat

Returns an image that is drawn a line segment connecting two points.

Parameters:

  • p1 (CvPoint) —

    First point of the line segment.

  • p2 (CvPoint) —

    Second point of the line segment.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3086

VALUE
rb_line(int argc, VALUE *argv, VALUE self)
{
  return rb_line_bang(argc, argv, rb_rcv_clone(self));
}

#line!(p1, p2, options = nil) ⇒ CvMat

Draws a line segment connecting two points.

Parameters:

  • p1 (CvPoint) —

    First point of the line segment.

  • p2 (CvPoint) —

    Second point of the line segment.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 3109

VALUE
rb_line_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE p1, p2, drawing_option;
  rb_scan_args(argc, argv, "21", &p1, &p2, &drawing_option);
  drawing_option = DRAWING_OPTION(drawing_option);
  try {
    cvLine(CVARR(self), VALUE_TO_CVPOINT(p1), VALUE_TO_CVPOINT(p2),
	   DO_COLOR(drawing_option),
	   DO_THICKNESS(drawing_option),
	   DO_LINE_TYPE(drawing_option),
	   DO_SHIFT(drawing_option));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#log ⇒ Object

Calculates the natural logarithm of every array element



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# File 'ext/opencv/cvmat.cpp', line 2343

VALUE
rb_log(VALUE self)
{
  VALUE dest = new_mat_kind_object(cvGetSize(CVARR(self)), self);
  try {
    const cv::Mat selfMat(CVMAT(self));
    cv::Mat destMat(CVMAT(dest));

    cv::log(selfMat, destMat);

  } catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#log_polar(size, center, magnitude, flags = CV_INTER_LINEAR|CV_WARP_FILL_OUTLIERS) ⇒ CvMat

Remaps an image to log-polar space.

Parameters:

  • size (CvSize) —

    Size of the destination image.

  • center (CvPoint2D32f) —

    The transformation center; where the output precision is maximal.

  • magnitude (Number) —

    Magnitude scale parameter.

  • flags (Integer) (defaults to: CV_INTER_LINEAR|CV_WARP_FILL_OUTLIERS) —

    A combination of interpolation methods and the following optional flags:

    • CV_WARP_FILL_OUTLIERS - fills all of the destination image pixels. If some of them correspond to outliers in the source image, they are set to zero.

    • CV_WARP_INVERSE_MAP - performs inverse transformation.

Returns:

  • (CvMat) —

    Destination image.



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# File 'ext/opencv/cvmat.cpp', line 4432

VALUE
rb_log_polar(int argc, VALUE *argv, VALUE self)
{
  VALUE dst_size, center, m, flags;
  rb_scan_args(argc, argv, "31", &dst_size, &center, &m, &flags);
  int _flags = NIL_P(flags) ? (CV_INTER_LINEAR | CV_WARP_FILL_OUTLIERS) : NUM2INT(flags);
  VALUE dest = new_mat_kind_object(VALUE_TO_CVSIZE(dst_size), self);
  try {
    cvLogPolar(CVARR(self), CVARR(dest), VALUE_TO_CVPOINT2D32F(center), NUM2DBL(m), _flags);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#lt(val) ⇒ CvMat

Performs the per-element comparison “less than” of two arrays or an array and scalar value.

Parameters:

  • val (CvMat, CvScalar, Number) —

    Array, scalar or number to compare

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2184

VALUE
rb_lt(VALUE self, VALUE val)
{
  VALUE dest = new_mat_kind_object(cvGetSize(CVARR(self)), self, CV_8U, 1);
  return rb_cmp_internal(self, val, dest, CV_CMP_LT);
}

#lut(lut) ⇒ CvMat

Performs a look-up table transform of an array.

Parameters:

  • lut (CvMat) —

    Look-up table of 256 elements. In case of multi-channel source array, the table should either have a single channel (in this case the same table is used for all channels) or the same number of channels as in the source array.

Returns:

  • (CvMat) —

    Transformed array



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# File 'ext/opencv/cvmat.cpp', line 1677

VALUE
rb_lut(VALUE self, VALUE lut)
{
  VALUE dest = copy(self);
  try {
    cvLUT(CVARR(self), CVARR(dest), CVARR_WITH_CHECK(lut));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#magnitude(y) ⇒ Object

Calculates the magnitude of 2D vectors



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# File 'ext/opencv/cvmat.cpp', line 2365

VALUE
rb_magnitude(VALUE self, VALUE y)
{
  VALUE dest = new_mat_kind_object(cvGetSize(CVARR(self)), self);
  try {
    const cv::Mat selfMat(CVMAT(self));
    const cv::Mat yMat(CVMAT(y));
    cv::Mat destMat(CVMAT(dest));

    cv::magnitude(selfMat, yMat, destMat);

  } catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#mat_mul(val, shiftvec = nil) ⇒ CvMat Also known as: *

Calculates the product of two arrays.

dst = self * val + shiftvec

Parameters:

  • val (CvMat) —

    Array to multiply

  • shiftvec (CvMat) —

    Optional translation vector

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 1876

VALUE
rb_mat_mul(int argc, VALUE *argv, VALUE self)
{
  VALUE val, shiftvec, dest;
  rb_scan_args(argc, argv, "11", &val, &shiftvec);
  CvArr* self_ptr = CVARR(self);  
  dest = new_mat_kind_object(cvGetSize(self_ptr), self);
  try {
    if (NIL_P(shiftvec))
      cvMatMul(self_ptr, CVARR_WITH_CHECK(val), CVARR(dest));
    else
      cvMatMulAdd(self_ptr, CVARR_WITH_CHECK(val), CVARR_WITH_CHECK(shiftvec), CVARR(dest));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#match_shapes(object, method) ⇒ Float

Compares two shapes(self and object). object should be CvMat or CvContour.

A - object1, B - object2:

  • method=CV_CONTOURS_MATCH_I1

    I1(A,B)=sumi=1..7abs(1/mAi - 1/mBi)

  • method=CV_CONTOURS_MATCH_I2

    I2(A,B)=sumi=1..7abs(mAi - mBi)

  • method=CV_CONTOURS_MATCH_I3

    I3(A,B)=sumi=1..7abs(mAi - mBi)/abs(mAi)

Returns:

  • (Float) 


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# File 'ext/opencv/cvmat.cpp', line 5950

VALUE
rb_match_shapes(int argc, VALUE *argv, VALUE self)
{
  VALUE object, method, param;
  rb_scan_args(argc, argv, "21", &object, &method, &param);
  int method_flag = CVMETHOD("COMPARISON_METHOD", method);
  if (!(rb_obj_is_kind_of(object, cCvMat::rb_class()) || rb_obj_is_kind_of(object, cCvContour::rb_class())))
    rb_raise(rb_eTypeError, "argument 1 (shape) should be %s or %s",
	     rb_class2name(cCvMat::rb_class()), rb_class2name(cCvContour::rb_class()));
  double result = 0;
  try {
    result = cvMatchShapes(CVARR(self), CVARR(object), method_flag);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_float_new(result);
}

#match_template(template, method = CV_TM_SQDIFF) ⇒ Object

Compares template against overlapped image regions.

After the match_template finishes comparison, the best matches can be found as global minimums (CV_TM_SQDIFF) or maximums(CV_TM_CCORR or CV_TM_CCOEFF) using CvMat#min_max_loc. In case of color image and template summation in both numerator and each sum in denominator is done over all the channels (and separate mean values are used for each channel).

Parameters:

  • template (CvMat) —

    Searched template. It must be not greater than the source image and have the same data type.

  • method (Integer) (defaults to: CV_TM_SQDIFF) —

    Parameter specifying the comparison method.

    • CV_TM_SQDIFF

    • CV_TM_SQDIFF_NORMED

    • CV_TM_CCORR

    • CV_TM_CCORR_NORMED

    • CV_TM_CCOEFF

    • CV_TM_CCOEFF_NORMED



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# File 'ext/opencv/cvmat.cpp', line 5909

VALUE
rb_match_template(int argc, VALUE *argv, VALUE self)
{
  VALUE templ, method;
  int method_flag;
  if (rb_scan_args(argc, argv, "11", &templ, &method) == 1)
    method_flag = CV_TM_SQDIFF;
  else
    method_flag = CVMETHOD("MATCH_TEMPLATE_METHOD", method);

  CvArr* self_ptr = CVARR(self);
  CvArr* templ_ptr = CVARR_WITH_CHECK(templ);
  VALUE result = Qnil;
  try {
    CvSize src_size = cvGetSize(self_ptr);
    CvSize template_size = cvGetSize(templ_ptr);
    result = cCvMat::new_object(src_size.height - template_size.height + 1,
				src_size.width - template_size.width + 1,
				CV_32FC1);
    cvMatchTemplate(self_ptr, templ_ptr, CVARR(result), method_flag);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return result;
}

#max(anothermat) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 2555

VALUE
rb_max(int argc, VALUE *argv, VALUE self)
{
  VALUE second_mat, dest;
  rb_scan_args(argc, argv, "1", &second_mat);
  dest = copy(self);
  try {
    cvMax(CVARR(self), CVARR(second_mat), CVARR(dest));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#mean_shift(window, criteria) ⇒ Object

Implements CAMSHIFT object tracking algrorithm. First, it finds an object center using mean_shift and, after that, calculates the object size and orientation.



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# File 'ext/opencv/cvmat.cpp', line 5977

VALUE
rb_mean_shift(VALUE self, VALUE window, VALUE criteria)
{
  VALUE comp = cCvConnectedComp::new_object();
  try {
    cvMeanShift(CVARR(self), VALUE_TO_CVRECT(window), VALUE_TO_CVTERMCRITERIA(criteria), CVCONNECTEDCOMP(comp));    
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return comp;
}

#min(anothermat) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 2535

VALUE
rb_min(int argc, VALUE *argv, VALUE self)
{
  VALUE second_mat, dest;
  rb_scan_args(argc, argv, "1", &second_mat);
  dest = copy(self);
  try {
    cvMin(CVARR(self), CVARR(second_mat), CVARR(dest));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#min_max_loc(mask = nil) ⇒ Array<Number, CvPoint>

Finds the global minimum and maximum in an array.

Parameters:

  • mask (CvMat) —

    Optional mask used to select a sub-array.

Returns:

  • (Array<Number, CvPoint>) —

    [min_val, max_val, min_loc, max_loc], where min_val, max_val are minimum, maximum values as Number and min_loc, max_loc are minimum, maximum locations as CvPoint, respectively.



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# File 'ext/opencv/cvmat.cpp', line 2513

VALUE
rb_min_max_loc(int argc, VALUE *argv, VALUE self)
{
  VALUE mask, min_loc, max_loc;
  double min_val = 0.0, max_val = 0.0;
  rb_scan_args(argc, argv, "01", &mask);
  min_loc = cCvPoint::new_object();
  max_loc = cCvPoint::new_object();
  try {
    cvMinMaxLoc(CVARR(self), &min_val, &max_val, CVPOINT(min_loc), CVPOINT(max_loc), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_ary_new3(4, rb_float_new(min_val), rb_float_new(max_val), min_loc, max_loc);
}

#moments ⇒ Object

Calculates moments.



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# File 'ext/opencv/cvmat.cpp', line 5607

VALUE
rb_moments(int argc, VALUE *argv, VALUE self)
{
  VALUE is_binary;
  rb_scan_args(argc, argv, "01", &is_binary);
  CvArr *self_ptr = CVARR(self);
  VALUE moments = Qnil;
  try {
    moments = cCvMoments::new_object(self_ptr, TRUE_OR_FALSE(is_binary, 0));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_ary_new3(1, moments);
}

#morphology(operation, element = nil, iteration = 1) ⇒ CvMat

Performs advanced morphological transformations using erosion and dilation as basic operations.

Parameters:

  • operation (Integer) —

    Type of morphological operation.

    • CV_MOP_OPEN - Opening

    • CV_MOP_CLOSE - Closing

    • CV_MOP_GRADIENT - Morphological gradient

    • CV_MOP_TOPHAT - Top hat

    • CV_MOP_BLACKHAT - Black hat

  • element (IplConvKernel) —

    Structuring element.

  • iteration (Integer) —

    Number of times erosion and dilation are applied.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 4550

VALUE
rb_morphology(int argc, VALUE *argv, VALUE self)
{
  VALUE element, iteration, operation_val;
  rb_scan_args(argc, argv, "12", &operation_val, &element, &iteration);

  int operation = CVMETHOD("MORPHOLOGICAL_OPERATION", operation_val, -1);
  CvArr* self_ptr = CVARR(self);
  CvSize size = cvGetSize(self_ptr);
  VALUE dest = new_mat_kind_object(size, self);
  IplConvKernel* kernel = NIL_P(element) ? NULL : IPLCONVKERNEL_WITH_CHECK(element);
  try {
    if (operation == CV_MOP_GRADIENT) {
      CvMat* temp = rb_cvCreateMat(size.height, size.width, cvGetElemType(self_ptr));
      cvMorphologyEx(self_ptr, CVARR(dest), temp, kernel, CV_MOP_GRADIENT, IF_INT(iteration, 1));
      cvReleaseMat(&temp);
    }
    else {
      cvMorphologyEx(self_ptr, CVARR(dest), 0, kernel, operation, IF_INT(iteration, 1));
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return dest;
}

#mul(val, scale = 1.0) ⇒ CvMat

Calculates the per-element scaled product of two arrays.

Parameters:

  • val (CvMat, CvScalar) —

    Array or scalar to multiply

  • scale (Number) —

    Optional scale factor.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 1818

VALUE
rb_mul(int argc, VALUE *argv, VALUE self)
{
  VALUE val, scale, dest;
  if (rb_scan_args(argc, argv, "11", &val, &scale) < 2)
    scale = rb_float_new(1.0);
  dest = new_mat_kind_object(cvGetSize(CVARR(self)), self);
  try {
    if (rb_obj_is_kind_of(val, rb_klass))
      cvMul(CVARR(self), CVARR(val), CVARR(dest), NUM2DBL(scale));
    else {
      CvScalar scl = VALUE_TO_CVSCALAR(val);
      VALUE mat = new_object(cvGetSize(CVARR(self)), cvGetElemType(CVARR(self)));
      cvSet(CVARR(mat), scl);
      cvMul(CVARR(self), CVARR(mat), CVARR(dest), NUM2DBL(scale));
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#mul_transposed(options) ⇒ CvMat

Calculates the product of a matrix and its transposition.

This function calculates the product of self and its transposition:

if :order = 0
  dst = scale * (self - delta) * (self - delta)T
otherwise
  dst = scale * (self - delta)T * (self - delta)

Parameters:

  • options (Hash) —

    Options

Options Hash (options):

  • :order (Integer) — default: 0 —

    Flag specifying the multiplication ordering, should be 0 or 1.

  • :delta (CvMat) — default: nil —

    Optional delta matrix subtracted from source before the multiplication.

  • :scale (Number) — default: 1.0 —

    Optional scale factor for the matrix product.

Returns:

  • (CvMat) —

    Result array.



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# File 'ext/opencv/cvmat.cpp', line 2716

VALUE
rb_mul_transposed(int argc, VALUE *argv, VALUE self)
{
  VALUE options = Qnil;
  VALUE _delta = Qnil, _scale = Qnil, _order = Qnil;

  if (rb_scan_args(argc, argv, "01", &options) > 0) {
    Check_Type(options, T_HASH);
    _delta = LOOKUP_HASH(options, "delta");
    _scale = LOOKUP_HASH(options, "scale");
    _order = LOOKUP_HASH(options, "order");
  }

  CvArr* delta = NIL_P(_delta) ? NULL : CVARR_WITH_CHECK(_delta);
  double scale = NIL_P(_scale) ? 1.0 : NUM2DBL(_scale);
  int order = NIL_P(_order) ? 0 : NUM2INT(_order);
  CvArr* self_ptr = CVARR(self);
  VALUE dest = new_mat_kind_object(cvGetSize(self_ptr), self);
  try {
    cvMulTransposed(self_ptr, CVARR(dest), order, delta, scale);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return dest;
}

#ne(val) ⇒ CvMat

Performs the per-element comparison “not equal” of two arrays or an array and scalar value.

Parameters:

  • val (CvMat, CvScalar, Number) —

    Array, scalar or number to compare

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2216

VALUE
rb_ne(VALUE self, VALUE val)
{
  VALUE dest = new_mat_kind_object(cvGetSize(CVARR(self)), self, CV_8U, 1);
  return rb_cmp_internal(self, val, dest, CV_CMP_NE);
}

#normalize(alpha = 1.0, beta = 0.0, norm_type = NORM_L2, dtype = -1, mask = nil) ⇒ CvMat

Normalizes the norm or value range of an array.

Parameters:

  • alpha (Number) (defaults to: 1.0) —

    Norm value to normalize to or the lower range boundary in case of the range normalization.

  • beta (Number) (defaults to: 0.0) —

    Upper range boundary in case of the range normalization. It is not used for the norm normalization.

  • norm_type (Integer) (defaults to: NORM_L2) —

    Normalization type.

  • dtype (Integer) (defaults to: -1) —

    when negative, the output array has the same type as src; otherwise, it has the same number of channels as src and the depth

  • mask (CvMat) (defaults to: nil) —

    Optional operation mask.

Returns:

  • (CvMat) —

    Normalized array.



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# File 'ext/opencv/cvmat.cpp', line 2302

VALUE
rb_normalize(int argc, VALUE *argv, VALUE self)
{
  VALUE alpha_val, beta_val, norm_type_val, dtype_val, mask_val;
  rb_scan_args(argc, argv, "05", &alpha_val, &beta_val, &norm_type_val, &dtype_val, &mask_val);

  double alpha = NIL_P(alpha_val) ? 1.0 : NUM2DBL(alpha_val);
  double beta = NIL_P(beta_val) ? 0.0 : NUM2DBL(beta_val);
  int norm_type = NIL_P(norm_type_val) ? cv::NORM_L2 : NUM2INT(norm_type_val);
  int dtype = NIL_P(dtype_val) ? -1 : NUM2INT(dtype_val);
  VALUE dst;

  try {
    cv::Mat self_mat(CVMAT(self));
    cv::Mat dst_mat;

    if (NIL_P(mask_val)) {
      cv::normalize(self_mat, dst_mat, alpha, beta, norm_type, dtype);
    }
    else {
      cv::Mat mask(MASK(mask_val));
      cv::normalize(self_mat, dst_mat, alpha, beta, norm_type, dtype, mask);
    }
    dst = new_mat_kind_object(cvGetSize(CVARR(self)), self, dst_mat.depth(), dst_mat.channels());

    CvMat tmp = dst_mat;
    cvCopy(&tmp, CVMAT(dst));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return dst;
}

#not ⇒ CvMat

Returns an array which elements are bit-wise invertion of source array.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2066

VALUE
rb_not(VALUE self)
{
  return rb_not_bang(copy(self));
}

#not! ⇒ CvMat

Inverts every bit of an array.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2079

VALUE
rb_not_bang(VALUE self)
{
  try {
    cvNot(CVARR(self), CVARR(self));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#optical_flow_bm(prev[,velx = nil][,vely = nil][,option]) ⇒ Array

Calculates optical flow for two images (previous -> self) using block matching method. Return horizontal component of the optical flow and vertical component of the optical flow. prev is previous image. velx is previous velocity field of x-axis, and vely is previous velocity field of y-axis.

options

  • :block_size -> should be CvSize (default is CvSize(4,4))

    Size of basic blocks that are compared.

  • :shift_size -> should be CvSize (default is CvSize(1,1))

    Block coordinate increments.

  • :max_range -> should be CvSize (default is CVSize(4,4))

    Size of the scanned neighborhood in pixels around block.

note: option’s default value is CvMat::OPTICAL_FLOW_BM_OPTION.

Velocity is computed for every block, but not for every pixel, so velocity image pixels correspond to input image blocks. input/output velocity field’s size should be (self.width / block_size.width)x(self.height / block_size.height). e.g. image.size is 320x240 and block_size is 4x4, velocity field’s size is 80x60.

Returns:

  • (Array) 


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# File 'ext/opencv/cvmat.cpp', line 6206

VALUE
rb_optical_flow_bm(int argc, VALUE *argv, VALUE self)
{
  VALUE prev, velx, vely, options;
  rb_scan_args(argc, argv, "13", &prev, &velx, &vely, &options);
  options = OPTICAL_FLOW_BM_OPTION(options);
  CvArr* self_ptr = CVARR(self);
  CvSize block_size = BM_BLOCK_SIZE(options);
  CvSize shift_size = BM_SHIFT_SIZE(options);
  CvSize max_range  = BM_MAX_RANGE(options);

  int use_previous = 0;
  try {
    CvSize image_size = cvGetSize(self_ptr);
    CvSize velocity_size = cvSize((image_size.width - block_size.width + shift_size.width) / shift_size.width,
				  (image_size.height - block_size.height + shift_size.height) / shift_size.height);
    CvMat *velx_ptr, *vely_ptr;
    if (NIL_P(velx) && NIL_P(vely)) {
      int type = CV_MAKETYPE(CV_32F, 1);
      velx = cCvMat::new_object(velocity_size, type);
      vely = cCvMat::new_object(velocity_size, type);
      velx_ptr = CVMAT(velx);
      vely_ptr = CVMAT(vely);
    }
    else {
      use_previous = 1;
      velx_ptr = CVMAT_WITH_CHECK(velx);
      vely_ptr = CVMAT_WITH_CHECK(vely);
    }
    cvCalcOpticalFlowBM(CVMAT_WITH_CHECK(prev), self_ptr,
			block_size, shift_size, max_range, use_previous,
			velx_ptr, vely_ptr);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_ary_new3(2, velx, vely);
}

#optical_flow_hs(prev[,velx = nil][,vely = nil][,options]) ⇒ Array

Calculates optical flow for two images (previous -> self) using Horn & Schunck algorithm. Return horizontal component of the optical flow and vertical component of the optical flow. prev is previous image velx is previous velocity field of x-axis, and vely is previous velocity field of y-axis.

options

  • :lambda -> should be Float (default is 0.0005)

    Lagrangian multiplier.

  • :criteria -> should be CvTermCriteria object (default is CvTermCriteria(1, 0.001))

    Criteria of termination of velocity computing.

note: option’s default value is CvMat::OPTICAL_FLOW_HS_OPTION.

sample code

velx, vely = nil, nil
while true
  current = capture.query
  velx, vely = current.optical_flow_hs(prev, velx, vely) if prev
  prev = current
end

Returns:

  • (Array) 


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# File 'ext/opencv/cvmat.cpp', line 6121

VALUE
rb_optical_flow_hs(int argc, VALUE *argv, VALUE self)
{
  VALUE prev, velx, vely, options;
  int use_previous = 0;
  rb_scan_args(argc, argv, "13", &prev, &velx, &vely, &options);
  options = OPTICAL_FLOW_HS_OPTION(options);
  CvMat *velx_ptr, *vely_ptr;
  CvArr* self_ptr = CVARR(self);
  try {
    if (NIL_P(velx) && NIL_P(vely)) {
      CvSize size = cvGetSize(self_ptr);
      int type = CV_MAKETYPE(CV_32F, 1);
      velx = cCvMat::new_object(size, type);
      vely = cCvMat::new_object(size, type);
      velx_ptr = CVMAT(velx);
      vely_ptr = CVMAT(vely);
    }
    else {
      use_previous = 1;
      velx_ptr = CVMAT_WITH_CHECK(velx);
      vely_ptr = CVMAT_WITH_CHECK(vely);
    }
    cvCalcOpticalFlowHS(CVMAT_WITH_CHECK(prev), self_ptr, use_previous, velx_ptr, vely_ptr,
			HS_LAMBDA(options), HS_CRITERIA(options));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_ary_new3(2, velx, vely);
}

#optical_flow_lk(prev, win_size) ⇒ Array

Calculates optical flow for two images (previous -> self) using Lucas & Kanade algorithm Return horizontal component of the optical flow and vertical component of the optical flow.

win_size is size of the averaging window used for grouping pixels.

Returns:

  • (Array) 


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# File 'ext/opencv/cvmat.cpp', line 6162

VALUE
rb_optical_flow_lk(VALUE self, VALUE prev, VALUE win_size)
{
  VALUE velx = Qnil;
  VALUE vely = Qnil;
  try {
    CvArr* self_ptr = CVARR(self);
    CvSize size = cvGetSize(self_ptr);
    int type = CV_MAKETYPE(CV_32F, 1);
    velx = cCvMat::new_object(size, type);
    vely = cCvMat::new_object(size, type);
    cvCalcOpticalFlowLK(CVMAT_WITH_CHECK(prev), self_ptr, VALUE_TO_CVSIZE(win_size),
			CVARR(velx), CVARR(vely));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return rb_ary_new3(2, velx, vely);
}

#or(val, mask = nil) ⇒ CvMat Also known as: |

Calculates the per-element bit-wise disjunction of two arrays or an array and a scalar.

Parameters:

  • val (CvMat, CvScalar) —

    Array or scalar to calculate bit-wise disjunction

  • mask (CvMat) —

    Optional operation mask, 8-bit single channel array, that specifies elements of the destination array to be changed.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2012

VALUE
rb_or(int argc, VALUE *argv, VALUE self)
{
  VALUE val, mask, dest;
  rb_scan_args(argc, argv, "11", &val, &mask);
  dest = copy(self);
  try {
    if (rb_obj_is_kind_of(val, rb_klass))
      cvOr(CVARR(self), CVARR(val), CVARR(dest), MASK(mask));
    else
      cvOrS(CVARR(self), VALUE_TO_CVSCALAR(val), CVARR(dest), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#perspective_transform(mat) ⇒ CvMat

Performs the perspective matrix transformation of vectors.

Parameters:

  • mat (CvMat) —

    3x3 or 4x4 floating-point transformation matrix.

Returns:

  • (CvMat) —

    Transformed vector.



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# File 'ext/opencv/cvmat.cpp', line 2684

VALUE
rb_perspective_transform(VALUE self, VALUE mat)
{
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvPerspectiveTransform(self_ptr, CVARR(dest), CVMAT_WITH_CHECK(mat));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#pixel_value(index) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 1041

VALUE
rb_pixel_value(VALUE self, VALUE index)
{
  CvScalar scalar = cvGet1D(CVARR(self), NUM2INT(index));
	return rb_float_new(scalar.val[0]);
}

#poly_line(points, options = nil) ⇒ CvMat

Returns an image that is drawn several polygonal curves.

Parameters:

  • points (Array<CvPoint>) —

    Array of polygonal curves.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :is_closed (Boolean) —

    Indicates whether the polylines must be drawn closed. If closed, the method draws the line from the last vertex of every contour to the first vertex.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3533

VALUE
rb_poly_line(int argc, VALUE *argv, VALUE self)
{
  return rb_poly_line_bang(argc, argv, rb_rcv_clone(self));
}

#poly_line!(points, options = nil) ⇒ CvMat

Draws several polygonal curves.

Parameters:

  • points (Array<CvPoint>) —

    Array of polygonal curves.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :is_closed (Boolean) —

    Indicates whether the polylines must be drawn closed. If closed, the method draws the line from the last vertex of every contour to the first vertex.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 3559

VALUE
rb_poly_line_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE polygons, drawing_option;
  VALUE points;
  int i, j;
  int num_polygons;
  int *num_points;
  CvPoint **p;

  rb_scan_args(argc, argv, "11", &polygons, &drawing_option);
  Check_Type(polygons, T_ARRAY);
  drawing_option = DRAWING_OPTION(drawing_option);
  num_polygons = RARRAY_LEN(polygons);
  num_points = RB_ALLOC_N(int, num_polygons);
  p = RB_ALLOC_N(CvPoint*, num_polygons);

  for (j = 0; j < num_polygons; ++j) {
    points = rb_ary_entry(polygons, j);
    Check_Type(points, T_ARRAY);
    num_points[j] = RARRAY_LEN(points);
    p[j] = RB_ALLOC_N(CvPoint, num_points[j]);
    for (i = 0; i < num_points[j]; ++i) {
      p[j][i] = VALUE_TO_CVPOINT(rb_ary_entry(points, i));
    }
  }

  try {
    cvPolyLine(CVARR(self), p, num_points, num_polygons,
	       DO_IS_CLOSED(drawing_option),
	       DO_COLOR(drawing_option),
	       DO_THICKNESS(drawing_option),
	       DO_LINE_TYPE(drawing_option),
	       DO_SHIFT(drawing_option));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return self;
}

#pre_corner_detect(aperture_size = 3) ⇒ CvMat

Calculates a feature map for corner detection.

Parameters:

  • aperture_size (Integer) —

    Aperture size for the sobel operator.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3849

VALUE
rb_pre_corner_detect(int argc, VALUE *argv, VALUE self)
{
  VALUE aperture_size, dest = Qnil;
  if (rb_scan_args(argc, argv, "01", &aperture_size) < 1)
    aperture_size = INT2FIX(3);

  CvArr *self_ptr = CVARR(self);
  try {
    dest = new_object(cvGetSize(self_ptr), CV_MAKETYPE(CV_32F, 1));
    cvPreCornerDetect(self_ptr, CVARR(dest), NUM2INT(aperture_size));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#put_text(text, org, font, color = CvColor::Black) ⇒ CvMat

Returns an image which is drawn a text string.

Parameters:

  • text (String) —

    Text string to be drawn.

  • org (CvPoint) —

    Bottom-left corner of the text string in the image.

  • font (CvFont) —

    CvFont object.

  • color (CvScalar) —

    Text color.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3613

VALUE
rb_put_text(int argc, VALUE* argv, VALUE self)
{
  return rb_put_text_bang(argc, argv, rb_rcv_clone(self));
}

#put_text!(text, org, font, color = CvColor::Black) ⇒ CvMat

Draws a text string.

Parameters:

  • text (String) —

    Text string to be drawn.

  • org (CvPoint) —

    Bottom-left corner of the text string in the image.

  • font (CvFont) —

    CvFont object.

  • color (CvScalar) —

    Text color.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 3630

VALUE
rb_put_text_bang(int argc, VALUE* argv, VALUE self)
{
  VALUE _text, _point, _font, _color;
  rb_scan_args(argc, argv, "31", &_text, &_point, &_font, &_color);
  CvScalar color = NIL_P(_color) ? CV_RGB(0, 0, 0) : VALUE_TO_CVSCALAR(_color);
  try {
    cvPutText(CVARR(self), StringValueCStr(_text), VALUE_TO_CVPOINT(_point),
	      CVFONT_WITH_CHECK(_font), color);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#pyr_down([filter = :gaussian_5x5]) ⇒ Object

Return downsamples image.

This operation performs downsampling step of Gaussian pyramid decomposition. First it convolves source image with the specified filter and then downsamples the image by rejecting even rows and columns.

note: filter - only :gaussian_5x5 is currently supported.



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# File 'ext/opencv/cvmat.cpp', line 5053

VALUE
rb_pyr_down(int argc, VALUE *argv, VALUE self)
{
  int filter = CV_GAUSSIAN_5x5;
  if (argc > 0) {
    VALUE filter_type = argv[0];
    switch (TYPE(filter_type)) {
    case T_SYMBOL:
      // currently suport CV_GAUSSIAN_5x5 only.
      break;
    default:
      raise_typeerror(filter_type, rb_cSymbol);
    }
  }
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  try {
    CvSize original_size = cvGetSize(self_ptr);
    CvSize size = { original_size.width >> 1, original_size.height >> 1 };
    dest = new_mat_kind_object(size, self);
    cvPyrDown(self_ptr, CVARR(dest), filter);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#pyr_mean_shift_filtering(sp, sr[,max_level = 1][termcrit = CvTermCriteria.new(5,1)]) ⇒ Object

Does meanshift image segmentation.

sp - The spatial window radius.
sr - The color window radius.
max_level - Maximum level of the pyramid for the segmentation.
termcrit - Termination criteria: when to stop meanshift iterations.

This method is implements the filtering stage of meanshift segmentation, that is, the output of the function is the filtered “posterized” image with color gradients and fine-grain texture flattened. At every pixel (X,Y) of the input image (or down-sized input image, see below) the function executes meanshift iterations, that is, the pixel (X,Y) neighborhood in the joint space-color hyperspace is considered:

{(x,y): X-sp≤x≤X+sp && Y-sp≤y≤Y+sp && ||(R,G,B)-(r,g,b)|| ≤ sr},

where (R,G,B) and (r,g,b) are the vectors of color components at (X,Y) and (x,y), respectively (though, the algorithm does not depend on the color space used, so any 3-component color space can be used instead). Over the neighborhood the average spatial value (X’,Y’) and average color vector (R’,G’,B’) are found and they act as the neighborhood center on the next iteration:

(X,Y)~(X',Y'), (R,G,B)~(R',G',B').

After the iterations over, the color components of the initial pixel (that is, the pixel from where the iterations started) are set to the final value (average color at the last iteration):

I(X,Y) <- (R*,G*,B*).

Then max_level > 0, the gaussian pyramid of max_level+1 levels is built, and the above procedure is run on the smallest layer. After that, the results are propagated to the larger layer and the iterations are run again only on those pixels where the layer colors differ much (>sr) from the lower-resolution layer, that is, the boundaries of the color regions are clarified.

Note, that the results will be actually different from the ones obtained by running the meanshift procedure on the whole original image (i.e. when max_level==0).



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# File 'ext/opencv/cvmat.cpp', line 5428

VALUE
rb_pyr_mean_shift_filtering(int argc, VALUE *argv, VALUE self)
{
  VALUE spatial_window_radius, color_window_radius, max_level, termcrit;
  rb_scan_args(argc, argv, "22", &spatial_window_radius, &color_window_radius, &max_level, &termcrit);
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvPyrMeanShiftFiltering(self_ptr, CVARR(dest),
			    NUM2DBL(spatial_window_radius),
			    NUM2DBL(color_window_radius),
			    IF_INT(max_level, 1),
			    NIL_P(termcrit) ? cvTermCriteria(CV_TERMCRIT_ITER + CV_TERMCRIT_EPS, 5, 1)
			    : VALUE_TO_CVTERMCRITERIA(termcrit));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#pyr_up([filter = :gaussian_5x5]) ⇒ Object

Return upsamples image.

This operation performs up-sampling step of Gaussian pyramid decomposition. First it upsamples the source image by injecting even zero rows and columns and then convolves result with the specified filter multiplied by 4 for interpolation. So the destination image is four times larger than the source image.

note: filter - only :gaussian_5x5 is currently supported.



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# File 'ext/opencv/cvmat.cpp', line 5094

VALUE
rb_pyr_up(int argc, VALUE *argv, VALUE self)
{
  VALUE filter_type;
  rb_scan_args(argc, argv, "01", &filter_type);
  int filter = CV_GAUSSIAN_5x5;
  if (argc > 0) {
    switch (TYPE(filter_type)) {
    case T_SYMBOL:
      // currently suport CV_GAUSSIAN_5x5 only.
      break;
    default:
      raise_typeerror(filter_type, rb_cSymbol);
    }
  }
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  try {
    CvSize original_size = cvGetSize(self_ptr);
    CvSize size = { original_size.width << 1, original_size.height << 1 };
    dest = new_mat_kind_object(size, self);
    cvPyrUp(self_ptr, CVARR(dest), filter);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#quadrangle_sub_pix(map_matrix, size = self.size) ⇒ CvMat

Note:

CvMat#quadrangle_sub_pix is similar to CvMat#warp_affine, but the outliers are extrapolated using replication border mode.

Applies an affine transformation to an image.

Parameters:

  • map_matrix (CvMat) —

    2x3 transformation matrix.

  • size (CvSize) —

    Size of the output image.

Returns:

  • (CvMat) —

    Output image that has the size size and the same type as self.



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# File 'ext/opencv/cvmat.cpp', line 4150

VALUE
rb_quadrangle_sub_pix(int argc, VALUE *argv, VALUE self)
{
  VALUE map_matrix, size;
  VALUE dest = Qnil;
  CvSize _size;
  CvArr* self_ptr = CVARR(self);
  try {
    if (rb_scan_args(argc, argv, "11", &map_matrix, &size) < 2)
      _size = cvGetSize(self_ptr);
    else
      _size = VALUE_TO_CVSIZE(size);
    dest = new_mat_kind_object(_size, self);
    cvGetQuadrangleSubPix(self_ptr, CVARR(dest), CVMAT_WITH_CHECK(map_matrix));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#rand_shuffle(seed = -1, iter_factor = 1) ⇒ CvMat

Returns shuffled matrix by swapping randomly chosen pairs of the matrix elements on each iteration (where each element may contain several components in case of multi-channel arrays)

Parameters:

  • seed (Integer) —

    Integer value used to initiate a random sequence

  • iter_factor (Integer) —

    The relative parameter that characterizes intensity of the shuffling performed. The number of iterations (i.e. pairs swapped) is round(iter_factor*rows(mat)*cols(mat)), so iter_factor = 0 means that no shuffling is done, iter_factor = 1 means that the function swaps rows(mat)*cols(mat) random pairs etc

Returns:

  • (CvMat) —

    Shuffled matrix



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# File 'ext/opencv/cvmat.cpp', line 1633

VALUE
rb_rand_shuffle(int argc, VALUE *argv, VALUE self)
{
  return rb_rand_shuffle_bang(argc, argv, copy(self));
}

#rand_shuffle!(seed = -1, iter_factor = 1) ⇒ CvMat

Shuffles the matrix by swapping randomly chosen pairs of the matrix elements on each iteration (where each element may contain several components in case of multi-channel arrays)

Parameters:

  • seed (Integer) —

    Integer value used to initiate a random sequence

  • iter_factor (Integer) —

    The relative parameter that characterizes intensity of the shuffling performed. The number of iterations (i.e. pairs swapped) is round(iter_factor*rows(mat)*cols(mat)), so iter_factor = 0 means that no shuffling is done, iter_factor = 1 means that the function swaps rows(mat)*cols(mat) random pairs etc

Returns:

  • (CvMat) —

    Shuffled matrix



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# File 'ext/opencv/cvmat.cpp', line 1648

VALUE
rb_rand_shuffle_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE seed, iter;
  rb_scan_args(argc, argv, "02", &seed, &iter);
  try {
    if (NIL_P(seed))
      cvRandShuffle(CVARR(self), NULL, IF_INT(iter, 1));
    else {
      CvRNG rng = cvRNG(rb_num2ll(seed));
      cvRandShuffle(CVARR(self), &rng, IF_INT(iter, 1));
    }
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#range(start, end) ⇒ CvMat

Returns initialized matrix as following:

arr(i,j)=(end-start)*(i*cols(arr)+j)/(cols(arr)*rows(arr))

Parameters:

  • start (Number) —

    The lower inclusive boundary of the range

  • end (Number) —

    The upper exclusive boundary of the range

Returns:

  • (CvMat) —

    Initialized matrix



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# File 'ext/opencv/cvmat.cpp', line 1407

VALUE
rb_range(VALUE self, VALUE start, VALUE end)
{
  return rb_range_bang(copy(self), start, end);
}

#range!(start, end) ⇒ CvMat

Initializes the matrix as following:

arr(i,j)=(end-start)*(i*cols(arr)+j)/(cols(arr)*rows(arr))

Parameters:

  • start (Number) —

    The lower inclusive boundary of the range

  • end (Number) —

    The upper exclusive boundary of the range

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1421

VALUE
rb_range_bang(VALUE self, VALUE start, VALUE end)
{
  try {
    cvRange(CVARR(self), NUM2DBL(start), NUM2DBL(end));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#clone ⇒ CvMat

Makes a clone of an object.

Returns:

  • (CvMat) —

    Clone of the object



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# File 'ext/opencv/cvmat.cpp', line 496

VALUE
rb_rcv_clone(VALUE self)
{
  VALUE clone = rb_obj_clone(self);
  try {
    DATA_PTR(clone) = cvClone(CVARR(self));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return clone;
}

#rect_sub_pix(center, size = self.size) ⇒ CvMat

Retrieves a pixel rectangle from an image with sub-pixel accuracy.

Parameters:

  • center (CvPoint2D32f) —

    Floating point coordinates of the center of the extracted rectangle within the source image. The center must be inside the image.

  • size (CvSize) —

    Size of the extracted patch.

Returns:

  • (CvMat) —

    Extracted patch that has the size size and the same number of channels as self.



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# File 'ext/opencv/cvmat.cpp', line 4118

VALUE
rb_rect_sub_pix(int argc, VALUE *argv, VALUE self)
{
  VALUE center, size;
  VALUE dest = Qnil;
  CvSize _size;
  CvArr* self_ptr = CVARR(self);
  try {
    if (rb_scan_args(argc, argv, "11", &center, &size) < 2)
      _size = cvGetSize(self_ptr);
    else
      _size = VALUE_TO_CVSIZE(size);
    dest = new_mat_kind_object(_size, self);
    cvGetRectSubPix(self_ptr, CVARR(dest), VALUE_TO_CVPOINT2D32F(center));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#rectangle(p1, p2, options = nil) ⇒ CvMat

Returns an image that is drawn a simple, thick, or filled up-right rectangle.

Parameters:

  • p1 (CvPoint) —

    Vertex of the rectangle.

  • p2 (CvPoint) —

    Vertex of the rectangle opposite to p1.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 3145

VALUE
rb_rectangle(int argc, VALUE *argv, VALUE self)
{
  return rb_rectangle_bang(argc, argv, rb_rcv_clone(self));
}

#rectangle!(p1, p2, options = nil) ⇒ CvMat

Draws a simple, thick, or filled up-right rectangle.

Parameters:

  • p1 (CvPoint) —

    Vertex of the rectangle.

  • p2 (CvPoint) —

    Vertex of the rectangle opposite to p1.

  • options (Hash) (defaults to: nil) —

    Drawing options

Options Hash (options):

  • :color (CvScalar) —

    Line color.

  • :thickness (Integer) —

    Line thickness.

  • :line_type (Integer) —

    Type of the line.

    • 8 - 8-connected line.

    • 4 - 4-connected line.

    • CV_AA - Antialiased line.

  • :shift (Integer) —

    Number of fractional bits in the point coordinates.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 3168

VALUE
rb_rectangle_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE p1, p2, drawing_option;
  rb_scan_args(argc, argv, "21", &p1, &p2, &drawing_option);
  drawing_option = DRAWING_OPTION(drawing_option);
  try {
    cvRectangle(CVARR(self), VALUE_TO_CVPOINT(p1), VALUE_TO_CVPOINT(p2),
		DO_COLOR(drawing_option),
		DO_THICKNESS(drawing_option),
		DO_LINE_TYPE(drawing_option),
		DO_SHIFT(drawing_option));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#remap(mapx, mapy, flags = CV_INTER_LINEAR|CV_WARP_FILL_OUTLIERS, fillval = 0) ⇒ CvMat

Applies a generic geometrical transformation to an image.

Parameters:

  • mapx (CvMat) —

    The first map of either (x,y) points or just x values having the type CV_16SC2, CV_32FC1, or CV_32FC2.

  • mapy (CvMat) —

    The second map of y values having the type CV_16UC1, CV_32FC1, or none (empty map if mapx is (x,y) points), respectively.

  • flags (Integer) (defaults to: CV_INTER_LINEAR|CV_WARP_FILL_OUTLIERS) —

    Combination of interpolation methods (CV_INTER_LINEAR or CV_INTER_NEAREST) and the optional flag CV_WARP_INVERSE_MAP, that sets map_matrix as the inverse transformation.

  • fillval (Number, CvScalar) (defaults to: 0) —

    Value used in case of a constant border.

Returns:

  • (CvMat) —

    Output image.



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# File 'ext/opencv/cvmat.cpp', line 4398

VALUE
rb_remap(int argc, VALUE *argv, VALUE self)
{
  VALUE mapx, mapy, flags_val, option, fillval;
  if (rb_scan_args(argc, argv, "23", &mapx, &mapy, &flags_val, &option, &fillval) < 5)
    fillval = INT2FIX(0);
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  int flags = NIL_P(flags_val) ? (CV_INTER_LINEAR | CV_WARP_FILL_OUTLIERS) : NUM2INT(flags_val);
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvRemap(self_ptr, CVARR(dest), CVARR_WITH_CHECK(mapx), CVARR_WITH_CHECK(mapy),
	    flags, VALUE_TO_CVSCALAR(fillval));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#repeat(dst) ⇒ CvMat

Fills the destination array with repeated copies of the source array.

Parameters:

  • dst (CvMat) —

    Destination array of the same type as self.

Returns:

  • (CvMat) —

    Destination array



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# File 'ext/opencv/cvmat.cpp', line 1472

VALUE
rb_repeat(VALUE self, VALUE object)
{
  try {
    cvRepeat(CVARR(self), CVARR_WITH_CHECK(object));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return object;
}

#reshape(cn, rows = 0) ⇒ CvMat

Changes shape of matrix/image without copying data.

Examples:

mat = CvMat.new(3, 3, CV_8U, 3)  #=> 3x3 3-channel matrix
vec = mat.reshape(:rows => 1)    #=> 1x9 3-channel matrix
ch1 = mat.reshape(:channel => 1) #=> 9x3 1-channel matrix

Parameters:

  • cn (Integer) —

    New number of channels. If the parameter is 0, the number of channels remains the same.

  • rows (Integer) (defaults to: 0) —

    New number of rows. If the parameter is 0, the number of rows remains the same.

Returns:

  • (CvMat) —

    Changed matrix



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# File 'ext/opencv/cvmat.cpp', line 1445

VALUE
rb_reshape(VALUE self, VALUE hash)
{
  Check_Type(hash, T_HASH);
  VALUE channel = rb_hash_aref(hash, ID2SYM(rb_intern("channel")));
  VALUE rows = rb_hash_aref(hash, ID2SYM(rb_intern("rows")));
  CvMat *mat = NULL;
  try {
    mat = cvReshape(CVARR(self), RB_CVALLOC(CvMat), NIL_P(channel) ? 0 : NUM2INT(channel),
		    NIL_P(rows) ? 0 : NUM2INT(rows));
  }
  catch (cv::Exception& e) {
    if (mat != NULL)
      cvReleaseMat(&mat);
    raise_cverror(e);
  }
  return DEPEND_OBJECT(rb_klass, mat, self);
}

#resize(size, interpolation = :linear) ⇒ CvMat

Resizes an image.

Parameters:

  • size (CvSize) —

    Output image size.

  • interpolation (Symbol) —

    Interpolation method:

    • CV_INTER_NN - A nearest-neighbor interpolation

    • CV_INTER_LINEAR - A bilinear interpolation (used by default)

    • CV_INTER_AREA - Resampling using pixel area relation. It may be a preferred method for image decimation, as it gives moire’-free results. But when the image is zoomed, it is similar to the :nn method.

    • CV_INTER_CUBIC - A bicubic interpolation over 4x4 pixel neighborhood

    • CV_INTER_LANCZOS4 - A Lanczos interpolation over 8x8 pixel neighborhood

Returns:

  • (CvMat) —

    Output image.



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# File 'ext/opencv/cvmat.cpp', line 4187

VALUE
rb_resize(int argc, VALUE *argv, VALUE self)
{
  VALUE size, interpolation;
  rb_scan_args(argc, argv, "11", &size, &interpolation);
  VALUE dest = new_mat_kind_object(VALUE_TO_CVSIZE(size), self);
  int method = NIL_P(interpolation) ? CV_INTER_LINEAR : NUM2INT(interpolation);

  try {
    cvResize(CVARR(self), CVARR(dest), method);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#save_image(filename) ⇒ CvMat Also known as: save

Saves an image to a specified file. The image format is chosen based on the filename extension.

Parameters:

  • filename (String) —

    Name of the file

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1258

VALUE
rb_save_image(int argc, VALUE *argv, VALUE self)
{
  VALUE _filename, _params;
  rb_scan_args(argc, argv, "11", &_filename, &_params);
  Check_Type(_filename, T_STRING);
  int *params = NULL;
  if (!NIL_P(_params)) {
    params = hash_to_format_specific_param(_params);
  }

  try {
    cvSaveImage(StringValueCStr(_filename), CVARR(self), params);
  }
  catch (cv::Exception& e) {
    if (params != NULL) {
      free(params);
      params = NULL;
    }
    raise_cverror(e);
  }
  if (params != NULL) {
    free(params);
    params = NULL;
  }

  return self;
}

#sobel(<i>xorder, yorder[,aperture_size = 3]) ⇒ Object

Calculates first, second, third or mixed image derivatives using extended Sobel operator. self should be single-channel 8bit unsigned or 32bit floating-point.



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# File 'ext/opencv/cvmat.cpp', line 3695

VALUE
rb_scharr(int argc, VALUE *argv, VALUE self)
{
  VALUE xorder, yorder, aperture_size, dest, scale;
  rb_scan_args(argc, argv, "3", &xorder, &yorder, &scale);
  //  aperture_size = INT2FIX(3);
  CvMat* self_ptr = CVMAT(self);
  switch(CV_MAT_DEPTH(self_ptr->type)) {
  case CV_8U:
    dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_16S, 1);
    break;
  case CV_32F:
    dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_32F, 1);
    break;
  default:
    rb_raise(rb_eArgError, "source depth should be CV_8U or CV_32F.");
    break;
  }

  try {
    const cv::Mat selfMat(CVMAT(self)); // WBH convert openCv1-style cvMat to openCv2-style cv::Mat
    cv::Mat destMat(CVMAT(dest));
    cv::Scharr(selfMat, destMat, CV_MAT_DEPTH(self_ptr->type), NUM2INT(xorder), NUM2INT(yorder), scale);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#sdv(mask = nil) ⇒ CvScalar

Calculates a standard deviation of array elements.

Parameters:

  • mask (CvMat) —

    Optional operation mask.

Returns:

  • (CvScalar) —

    The standard deviation of array elements.



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# File 'ext/opencv/cvmat.cpp', line 2488

VALUE
rb_sdv(int argc, VALUE *argv, VALUE self)
{
  VALUE mask, std_dev;
  rb_scan_args(argc, argv, "01", &mask);
  std_dev = cCvScalar::new_object();
  try {
    cvAvgSdv(CVARR(self), NULL, CVSCALAR(std_dev), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return std_dev;
}

#set(value, mask = nil) ⇒ CvMat Also known as: fill

Returns a matrix which is set every element to a given value. The function copies the scalar value to every selected element of the destination array:

mat[I] = value if mask(I) != 0

Parameters:

  • value (CvScalar) —

    Fill value

  • mask (CvMat) —

    Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

Returns:

  • (CvMat) —

    Matrix which is set every element to a given value.



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# File 'ext/opencv/cvmat.cpp', line 1220

VALUE
rb_set(int argc, VALUE *argv, VALUE self)
{
  return rb_set_bang(argc, argv, copy(self));
}

#set!(value, mask = nil) ⇒ CvMat Also known as: fill!

Sets every element of the matrix to a given value. The function copies the scalar value to every selected element of the destination array:

mat[I] = value if mask(I) != 0

Parameters:

  • value (CvScalar) —

    Fill value

  • mask (CvMat) —

    Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1236

VALUE
rb_set_bang(int argc, VALUE *argv, VALUE self)
{
  VALUE value, mask;
  rb_scan_args(argc, argv, "11", &value, &mask);
  try {
    cvSet(CVARR(self), VALUE_TO_CVSCALAR(value), MASK(mask));    
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#set_data(data) ⇒ CvMat

Assigns user data to the array header

Parameters:

  • data (Array<Integer>) —

    User data

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1133

VALUE
rb_set_data(VALUE self, VALUE data)
{
  CvMat *self_ptr = CVMAT(self);
  int depth = CV_MAT_DEPTH(self_ptr->type);

  if (TYPE(data) == T_STRING) {
    if (!CV_IS_MAT_CONT(self_ptr->type))
      rb_raise(rb_eArgError, "CvMat must be continuous");
      
    const int dataLength = RSTRING_LEN(data);
    if (dataLength != self_ptr->width * self_ptr->height * CV_ELEM_SIZE(self_ptr->type))
      rb_raise(rb_eArgError, "Invalid data string length");
    
    memcpy(self_ptr->data.ptr, RSTRING_PTR(data), dataLength);
    
  } else {
    data = rb_funcall(data, rb_intern("flatten"), 0);
    
    const int DATA_LEN = RARRAY_LEN(data);
   
    void* array = NULL;
  
    switch (depth) {
    case CV_8U:
      array = rb_cvAlloc(sizeof(uchar) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((uchar*)array)[i] = (uchar)(NUM2INT(rb_ary_entry(data, i)));
      break;
    case CV_8S:
      array = rb_cvAlloc(sizeof(char) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((char*)array)[i] = (char)(NUM2INT(rb_ary_entry(data, i)));
      break;
    case CV_16U:
      array = rb_cvAlloc(sizeof(ushort) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((ushort*)array)[i] = (ushort)(NUM2INT(rb_ary_entry(data, i)));
      break;
    case CV_16S:
      array = rb_cvAlloc(sizeof(short) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((short*)array)[i] = (short)(NUM2INT(rb_ary_entry(data, i)));
      break;
    case CV_32S:
      array = rb_cvAlloc(sizeof(int) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((int*)array)[i] = NUM2INT(rb_ary_entry(data, i));
      break;
    case CV_32F:
      array = rb_cvAlloc(sizeof(float) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((float*)array)[i] = (float)NUM2DBL(rb_ary_entry(data, i));
      break;
    case CV_64F:
      array = rb_cvAlloc(sizeof(double) * DATA_LEN);
      for (int i = 0; i < DATA_LEN; ++i)
        ((double*)array)[i] = NUM2DBL(rb_ary_entry(data, i));
      break;
    default:
      rb_raise(rb_eArgError, "Invalid CvMat depth");
      break;
    }

    try {
      cvSetData(self_ptr, array, self_ptr->step);    
    }
    catch (cv::Exception& e) {
      raise_cverror(e);
    }
  }

  return self;
}

#set_zero ⇒ CvMat Also known as: clear, zero

Returns cleared array.

Returns:

  • (CvMat) —

    Cleared array



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# File 'ext/opencv/cvmat.cpp', line 1333

VALUE
rb_set_zero(VALUE self)
{
  return rb_set_zero_bang(copy(self));
}

#set_zero! ⇒ CvMat Also known as: clear!, zero!

Clears the array.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 1345

VALUE
rb_set_zero_bang(VALUE self)
{
  try {
    cvSetZero(CVARR(self));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return self;
}

#size ⇒ CvSize

Returns size of the matrix

Returns:

  • (CvSize) —

    Size of the matrix



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# File 'ext/opencv/cvmat.cpp', line 935

VALUE
rb_size(VALUE self)
{
  CvSize size;
  try {
    size = cvGetSize(CVARR(self));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return cCvSize::new_object(size);
}

#smooth(smoothtype, size1 = 3, size2 = 0, sigma1 = 0, sigma2 = 0) ⇒ CvMat

Smooths the image in one of several ways.

Parameters:

  • smoothtype (Integer) —

    Type of the smoothing.

    • CV_BLUR_NO_SCALE - linear convolution with size1 x size2 box kernel (all 1’s). If you want to smooth different pixels with different-size box kernels, you can use the integral image that is computed using CvMat#integral.

    • CV_BLUR - linear convolution with size1 x size2 box kernel (all 1’s) with subsequent scaling by 1 / (size1 x size1).

    • CV_GAUSSIAN - linear convolution with a size1 x size2 Gaussian kernel.

    • CV_MEDIAN - median filter with a size1 x size1 square aperture

    • CV_BILATERAL - bilateral filter with a size1 x size1 square aperture, color sigma = sigma1 and spatial sigma = sigma2. If size1 = 0, the aperture square side is set to CvMat#round(sigma2 * 1.5) * 2 + 1.

  • size1 (Integer) (defaults to: 3) —

    The first parameter of the smoothing operation, the aperture width. Must be a positive odd number (1, 3, 5, …)

  • size2 (Integer) (defaults to: 0) —

    The second parameter of the smoothing operation, the aperture height. Ignored by CV_MEDIAN and CV_BILATERAL methods. In the case of simple scaled/non-scaled and Gaussian blur if size2 is zero, it is set to size1. Otherwise it must be a positive odd number.

  • sigma1 (Integer) (defaults to: 0) —

    In the case of a Gaussian parameter this parameter may specify Gaussian sigma (standard deviation). If it is zero, it is calculated from the kernel size.

Returns:

  • (CvMat) —

    The destination image.



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# File 'ext/opencv/cvmat.cpp', line 4715

VALUE
rb_smooth(int argc, VALUE *argv, VALUE self)
{
  VALUE smoothtype, p1, p2, p3, p4;
  rb_scan_args(argc, argv, "14", &smoothtype, &p1, &p2, &p3, &p4);
  int _smoothtype = CVMETHOD("SMOOTHING_TYPE", smoothtype, -1);
  
  VALUE (*smooth_func)(int c, VALUE* v, VALUE s);
  argc--;
  switch (_smoothtype) {
  case CV_BLUR_NO_SCALE:
    smooth_func = rb_smooth_blur_no_scale;
    argc = (argc > 2) ? 2 : argc;
    break;
  case CV_BLUR:
    smooth_func = rb_smooth_blur;
    argc = (argc > 2) ? 2 : argc;
    break;
  case CV_GAUSSIAN:
    smooth_func = rb_smooth_gaussian;
    break;
  case CV_MEDIAN:
    smooth_func = rb_smooth_median;
    argc = (argc > 1) ? 1 : argc;
    break;
  case CV_BILATERAL:
    smooth_func = rb_smooth_bilateral;
    argc = (argc > 4) ? 4 : argc;
    break;
  default:
    smooth_func = rb_smooth_gaussian;
    break;
  }
  VALUE result = Qnil;
  try {
    result = (*smooth_func)(argc, argv + 1, self);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return result;
}

#snake_image(points, alpha, beta, gamma, window, criteria[, calc_gradient = true]) ⇒ Object

Updates snake in order to minimize its total energy that is a sum of internal energy that depends on contour shape (the smoother contour is, the smaller internal energy is) and external energy that depends on the energy field and reaches minimum at the local energy extremums that correspond to the image edges in case of image gradient.

The parameter criteria.epsilon is used to define the minimal number of points that must be moved during any iteration to keep the iteration process running.

If at some iteration the number of moved points is less than criteria.epsilon or the function performed criteria.max_iter iterations, the function terminates.

points

Contour points (snake).

alpha

Weight[s] of continuity energy, single float or array of length floats, one per each contour point.

beta

Weight[s] of curvature energy, similar to alpha.

gamma

Weight[s] of image energy, similar to alpha.

window

Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd.

criteria

Termination criteria.

calc_gradient

Gradient flag. If not 0, the function calculates gradient magnitude for every image pixel and consideres
it as the energy field, otherwise the input image itself is considered.



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# File 'ext/opencv/cvmat.cpp', line 6044

VALUE
rb_snake_image(int argc, VALUE *argv, VALUE self)
{
  VALUE points, alpha, beta, gamma, window, criteria, calc_gradient;
  rb_scan_args(argc, argv, "61", &points, &alpha, &beta, &gamma, &window, &criteria, &calc_gradient);
  CvPoint *pointset = 0;
  int length = CVPOINTS_FROM_POINT_SET(points, &pointset);
  int coeff = (TYPE(alpha) == T_ARRAY && TYPE(beta) == T_ARRAY && TYPE(gamma) == T_ARRAY) ? CV_ARRAY : CV_VALUE;
  float *a = 0, *b = 0, *c = 0;
  IplImage stub;
  int i;
  if (coeff == CV_VALUE) {
    float buff_a, buff_b, buff_c;
    buff_a = (float)NUM2DBL(alpha);
    buff_b = (float)NUM2DBL(beta);
    buff_c = (float)NUM2DBL(gamma);
    a = &buff_a;
    b = &buff_b;
    c = &buff_c;
  }
  else { // CV_ARRAY
    if ((RARRAY_LEN(alpha) != length) ||
	(RARRAY_LEN(beta) != length) ||
	(RARRAY_LEN(gamma) != length))
      rb_raise(rb_eArgError, "alpha, beta, gamma should be same size of points");
    a = RB_ALLOC_N(float, length);
    b = RB_ALLOC_N(float, length);
    c = RB_ALLOC_N(float, length);
    for (i = 0; i < length; ++i) {
      a[i] = (float)NUM2DBL(RARRAY_PTR(alpha)[i]);
      b[i] = (float)NUM2DBL(RARRAY_PTR(beta)[i]);
      c[i] = (float)NUM2DBL(RARRAY_PTR(gamma)[i]);
    }
  }
  CvSize win = VALUE_TO_CVSIZE(window);
  CvTermCriteria tc = VALUE_TO_CVTERMCRITERIA(criteria);
  try {
    cvSnakeImage(cvGetImage(CVARR(self), &stub), pointset, length,
		 a, b, c, coeff, win, tc, IF_BOOL(calc_gradient, 1, 0, 1));
  }
  catch (cv::Exception& e) {
    if (pointset != NULL)
      cvFree(&pointset);
    raise_cverror(e);
  }
  VALUE result = rb_ary_new2(length);
  for (i = 0; i < length; ++i)
    rb_ary_push(result, cCvPoint::new_object(pointset[i]));
  cvFree(&pointset);
  
  return result;
}

#sobel(xorder, yorder, aperture_size = 3) ⇒ CvMat

Calculates the first, second, third, or mixed image derivatives using an extended Sobel operator.

Parameters:

  • xorder (Integer) —

    Order of the derivative x.

  • yorder (Integer) —

    Order of the derivative y.

  • aperture_size (Integer) —

    Size of the extended Sobel kernel; it must be 1, 3, 5, or 7.

Returns:

  • (CvMat) —

    Output image.



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# File 'ext/opencv/cvmat.cpp', line 3656

VALUE
rb_sobel(int argc, VALUE *argv, VALUE self)
{
  VALUE xorder, yorder, dest, ksize;
  rb_scan_args(argc, argv, "3", &xorder, &yorder, &ksize);
  //  aperture_size = INT2FIX(3);
  CvMat* self_ptr = CVMAT(self);
  switch(CV_MAT_DEPTH(self_ptr->type)) {
  case CV_8U:
    dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_8U, 1);
    break;
  case CV_32F:
    dest = new_mat_kind_object(cvGetSize(self_ptr), self, CV_32F, 1);
    break;
  default:
    rb_raise(rb_eArgError, "source depth should be CV_8U or CV_32F.");
    break;
  }

  try {
    const cv::Mat selfMat(CVMAT(self)); // WBH convert openCv1-style cvMat to openCv2-style cv::Mat
    cv::Mat destMat(CVMAT(dest));
    cv::Sobel(selfMat, destMat, CV_MAT_DEPTH(self_ptr->type), NUM2INT(xorder), NUM2INT(yorder), NUM2INT(ksize));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#split ⇒ Array<CvMat>

Divides a multi-channel array into several single-channel arrays.

Examples:

img = CvMat.new(640, 480, CV_8U, 3) #=> 3-channel image
a = img.split                       #=> [img-ch1, img-ch2, img-ch3]

Returns:

  • (Array<CvMat>) —

    Array of single-channel arrays

See Also:



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# File 'ext/opencv/cvmat.cpp', line 1547

VALUE
rb_split(VALUE self)
{
  CvArr* self_ptr = CVARR(self);
  int type = cvGetElemType(self_ptr);
  int depth = CV_MAT_DEPTH(type), channel = CV_MAT_CN(type);
  VALUE dest = rb_ary_new2(channel);
  try {
    CvArr *dest_ptr[] = { NULL, NULL, NULL, NULL };
    CvSize size = cvGetSize(self_ptr);
    for (int i = 0; i < channel; ++i) {
      VALUE tmp = new_mat_kind_object(size, self, depth, 1);
      rb_ary_store(dest, i, tmp);
      dest_ptr[i] = CVARR(tmp);
    }
    cvSplit(self_ptr, dest_ptr[0], dest_ptr[1], dest_ptr[2], dest_ptr[3]);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return dest;
}

#sqrt ⇒ Object

Calculates a square root of array elements.



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# File 'ext/opencv/cvmat.cpp', line 1847

VALUE
rb_sqrt(VALUE self)
{
  CvArr* self_ptr = CVARR(self);
  VALUE dest = new_mat_kind_object(cvGetSize(self_ptr), self);

  try {
    const cv::Mat srcMat(CVMAT(self));
    cv::Mat dstMat(CVMAT(dest));
    cv::sqrt(srcMat, dstMat);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return dest;
}

#square? ⇒ Boolean

Returns whether the matrix is a square.

Returns:

  • (Boolean) —

    If width = height, returns true. if not, returns false.



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# File 'ext/opencv/cvmat.cpp', line 674

VALUE
rb_square_q(VALUE self)
{
  CvMat *mat = CVMAT(self);
  return mat->width == mat->height ? Qtrue : Qfalse;
}

#sub(val, mask = nil) ⇒ CvMat Also known as: -

Calculates the per-element difference between two arrays or array and a scalar.

Parameters:

  • val (CvMat, CvScalar) —

    Array or scalar to subtract

  • mask (CvMat) —

    Optional operation mask, 8-bit single channel array, that specifies elements of the destination array to be changed.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 1791

VALUE
rb_sub(int argc, VALUE *argv, VALUE self)
{
  VALUE val, mask, dest;
  rb_scan_args(argc, argv, "11", &val, &mask);
  dest = copy(self);
  try {
    if (rb_obj_is_kind_of(val, rb_klass))
      cvSub(CVARR(self), CVARR(val), CVARR(dest), MASK(mask));
    else
      cvSubS(CVARR(self), VALUE_TO_CVSCALAR(val), CVARR(dest), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#sub_rect(rect) ⇒ CvMat #sub_rect(topleft, size) ⇒ CvMat #sub_rect(x, y, width, height) ⇒ CvMat Also known as: subrect

Returns matrix corresponding to the rectangular sub-array of input image or matrix

Overloads:

  • #sub_rect(rect) ⇒ CvMat

    Parameters:

    • rect (CvRect) —

      Zero-based coordinates of the rectangle of interest.

  • #sub_rect(topleft, size) ⇒ CvMat

    Parameters:

    • topleft (CvPoint) —

      Top-left coordinates of the rectangle of interest

    • size (CvSize) —

      Size of the rectangle of interest

  • #sub_rect(x, y, width, height) ⇒ CvMat

    Parameters:

    • x (Integer) —

      X-coordinate of the rectangle of interest

    • y (Integer) —

      Y-coordinate of the rectangle of interest

    • width (Integer) —

      Width of the rectangle of interest

    • height (Integer) —

      Height of the rectangle of interest

Returns:

  • (CvMat) —

    Sub-array of matrix



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# File 'ext/opencv/cvmat.cpp', line 722

VALUE
rb_sub_rect(VALUE self, VALUE args)
{
  CvRect area;
  CvPoint topleft;
  CvSize size;
  switch(RARRAY_LEN(args)) {
  case 1:
    area = VALUE_TO_CVRECT(RARRAY_PTR(args)[0]);
    break;
  case 2:
    topleft = VALUE_TO_CVPOINT(RARRAY_PTR(args)[0]);
    size = VALUE_TO_CVSIZE(RARRAY_PTR(args)[1]);
    area.x = topleft.x;
    area.y = topleft.y;
    area.width = size.width;
    area.height = size.height;
    break;
  case 4:
    area.x = NUM2INT(RARRAY_PTR(args)[0]);
    area.y = NUM2INT(RARRAY_PTR(args)[1]);
    area.width = NUM2INT(RARRAY_PTR(args)[2]);
    area.height = NUM2INT(RARRAY_PTR(args)[3]);
    break;
  default:
    rb_raise(rb_eArgError, "wrong number of arguments (%ld of 1 or 2 or 4)", RARRAY_LEN(args));
  }

  CvMat* mat = NULL;
  try {
    mat = cvGetSubRect(CVARR(self), RB_CVALLOC(CvMat), area);
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return DEPEND_OBJECT(rb_klass, mat, self);
}

#subspace_project(w, mean) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 6514

VALUE
rb_subspace_project(VALUE self, VALUE w, VALUE mean)
{
  VALUE projection;
  try {
    cv::Mat w_mat(CVMAT_WITH_CHECK(w));
    cv::Mat mean_mat(CVMAT_WITH_CHECK(mean));
    cv::Mat self_mat(CVMAT(self));
    cv::Mat pmat = cv::subspaceProject(w_mat, mean_mat, self_mat);
    projection = new_object(pmat.rows, pmat.cols, pmat.type());
    CvMat tmp = pmat;
    cvCopy(&tmp, CVMAT(projection));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return projection;
}

#subspace_reconstruct(w, mean) ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 6538

VALUE
rb_subspace_reconstruct(VALUE self, VALUE w, VALUE mean)
{
  VALUE result;
  try {
    cv::Mat w_mat(CVMAT_WITH_CHECK(w));
    cv::Mat mean_mat(CVMAT_WITH_CHECK(mean));
    cv::Mat self_mat(CVMAT(self));
    cv::Mat rmat = cv::subspaceReconstruct(w_mat, mean_mat, self_mat);
    result = new_object(rmat.rows, rmat.cols, rmat.type());
    CvMat tmp = rmat;
    cvCopy(&tmp, CVMAT(result));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }

  return result;
}

#sum ⇒ CvScalar

Calculates the sum of array elements.

Returns:

  • (CvScalar) —

    The sum of array elements.



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# File 'ext/opencv/cvmat.cpp', line 2409

VALUE
rb_sum(VALUE self)
{
  CvScalar sum;
  try {
    sum = cvSum(CVARR(self));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return cCvScalar::new_object(sum);
}

#svd(flag = 0) ⇒ Array<CvMat>

Performs SVD of a matrix

Parameters:

  • flag (Integer) —

    Operation flags.

    • CV_SVD_MODIFY_A - Use the algorithm to modify the decomposed matrix. It can save space and speed up processing.

    • CV_SVD_U_T - Indicate that only a vector of singular values w is to be computed, while u and v will be set to empty matrices.

    • CV_SVD_V_T - When the matrix is not square, by default the algorithm produces u and v matrices of sufficiently large size for the further A reconstruction. If, however, CV_SVD_V_T flag is specified, u and v will be full-size square orthogonal matrices.

Returns:

  • (Array<CvMat>) —

    Array of the computed values [w, u, v], where

    • w - Computed singular values

    • u - Computed left singular vectors

    • v - Computed right singular vectors



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# File 'ext/opencv/cvmat.cpp', line 2879

VALUE
rb_svd(int argc, VALUE *argv, VALUE self)
{
  VALUE _flag = Qnil;
  int flag = 0;
  if (rb_scan_args(argc, argv, "01", &_flag) > 0) {
    flag = NUM2INT(_flag);
  }

  CvMat* self_ptr = CVMAT(self);
  VALUE w = new_mat_kind_object(cvSize(self_ptr->cols, self_ptr->rows), self);
  
  int rows = 0;
  int cols = 0;
  if (flag & CV_SVD_U_T) {
    rows = MIN(self_ptr->rows, self_ptr->cols);
    cols = self_ptr->rows;
  }
  else {
    rows = self_ptr->rows;
    cols = MIN(self_ptr->rows, self_ptr->cols);
  }
  VALUE u = new_mat_kind_object(cvSize(cols, rows), self);

  if (flag & CV_SVD_V_T) {
    rows = MIN(self_ptr->rows, self_ptr->cols);
    cols = self_ptr->cols;
  }
  else {
    rows = self_ptr->cols;
    cols = MIN(self_ptr->rows, self_ptr->cols);
  }
  VALUE v = new_mat_kind_object(cvSize(cols, rows), self);

  cvSVD(self_ptr, CVARR(w), CVARR(u), CVARR(v), flag);

  return rb_ary_new3(3, w, u, v);
}

#threshold(threshold, max_value, threshold_type) ⇒ CvMat #threshold(threshold, max_value, threshold_type, use_otsu) ⇒ Array<CvMat, Number>

Applies a fixed-level threshold to each array element.

Examples:

mat = CvMat.new(3, 3, CV_8U, 1)
mat.set_data([1, 2, 3, 4, 5, 6, 7, 8, 9])
mat #=> [1, 2, 3,
         4, 5, 6,
         7, 8, 9]
result = mat.threshold(4, 7, CV_THRESH_BINARY)
result #=> [0, 0, 0,
            0, 7, 7,
            7, 7, 7]

Overloads:

  • #threshold(threshold, max_value, threshold_type) ⇒ CvMat

    Returns Output array of the same size and type as self.

    Parameters:

    • threshold (Number) —

      Threshold value.

    • max_value (Number) —

      Maximum value to use with the CV_THRESH_BINARY and CV_THRESH_BINARY_INV thresholding types.

    • threshold_type (Integer) —

      Thresholding type

      • CV_THRESH_BINARY

      • CV_THRESH_BINARY_INV

      • CV_THRESH_TRUNC

      • CV_THRESH_TOZERO

      • CV_THRESH_TOZERO_INV

    Returns:

    • (CvMat) —

      Output array of the same size and type as self.

  • #threshold(threshold, max_value, threshold_type, use_otsu) ⇒ Array<CvMat, Number>

    Returns Output array and Otsu’s threshold.

    Parameters:

    • threshold (Number) —

      Threshold value.

    • max_value (Number) —

      Maximum value to use with the CV_THRESH_BINARY and CV_THRESH_BINARY_INV thresholding types.

    • threshold_type (Integer) —

      Thresholding type

      • CV_THRESH_BINARY

      • CV_THRESH_BINARY_INV

      • CV_THRESH_TRUNC

      • CV_THRESH_TOZERO

      • CV_THRESH_TOZERO_INV

    • use_otsu (Boolean) —

      Determines the optimal threshold value using the Otsu’s algorithm

    Returns:

    • (Array<CvMat, Number>) —

      Output array and Otsu’s threshold.



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# File 'ext/opencv/cvmat.cpp', line 4939

VALUE
rb_threshold(int argc, VALUE *argv, VALUE self)
{
  VALUE threshold, max_value, threshold_type, use_otsu;
  rb_scan_args(argc, argv, "31", &threshold, &max_value, &threshold_type, &use_otsu);
  const int INVALID_TYPE = -1;
  int type = CVMETHOD("THRESHOLD_TYPE", threshold_type, INVALID_TYPE);
  if (type == INVALID_TYPE)
    rb_raise(rb_eArgError, "Invalid threshold type.");
  
  return rb_threshold_internal(type, threshold, max_value, use_otsu, self);
}

#to_16s ⇒ CvMat

Converts the matrix to 16bit signed.

Returns:

  • (CvMat) —

    Converted matrix which depth is 16bit signed. The size and channels of the new matrix are same as the source.



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# File 'ext/opencv/cvmat.cpp', line 610

VALUE
rb_to_16s(VALUE self)
{
  return rb_to_X_internal(self, CV_16S);
}

#to_16u ⇒ CvMat

Converts the matrix to 16bit unsigned.

Returns:

  • (CvMat) —

    Converted matrix which depth is 16bit unsigned. The size and channels of the new matrix are same as the source.



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# File 'ext/opencv/cvmat.cpp', line 598

VALUE rb_to_16u(VALUE self)
{
  return rb_to_X_internal(self, CV_16U);
}

#to_32f ⇒ CvMat

Converts the matrix to 32bit float.

Returns:

  • (CvMat) —

    Converted matrix which depth is 32bit float. The size and channels of the new matrix are same as the source.



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# File 'ext/opencv/cvmat.cpp', line 636

VALUE
rb_to_32f(VALUE self)
{
  return rb_to_X_internal(self, CV_32F);
}

#to_32s ⇒ CvMat

Converts the matrix to 32bit signed.

Returns:

  • (CvMat) —

    Converted matrix which depth is 32bit signed. The size and channels of the new matrix are same as the source.



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# File 'ext/opencv/cvmat.cpp', line 623

VALUE
rb_to_32s(VALUE self)
{
  return rb_to_X_internal(self, CV_32S);
}

#to_64f ⇒ CvMat

Converts the matrix to 64bit float.

Returns:

  • (CvMat) —

    Converted matrix which depth is 64bit float. The size and channels of the new matrix are same as the source.



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# File 'ext/opencv/cvmat.cpp', line 649

VALUE
rb_to_64f(VALUE self)
{
  return rb_to_X_internal(self, CV_64F);
}

#to_8s ⇒ CvMat

Converts the matrix to 8bit signed.

Returns:

  • (CvMat) —

    Converted matrix which depth is 8bit signed. The size and channels of the new matrix are same as the source.



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# File 'ext/opencv/cvmat.cpp', line 585

VALUE
rb_to_8s(VALUE self)
{
  return rb_to_X_internal(self, CV_8S);
}

#to_8u ⇒ CvMat

Converts the matrix to 8bit unsigned.

Returns:

  • (CvMat) —

    Converted matrix which depth is 8bit unsigned. The size and channels of the new matrix are same as the source.



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# File 'ext/opencv/cvmat.cpp', line 572

VALUE
rb_to_8u(VALUE self)
{
  return rb_to_X_internal(self, CV_8U);
}

#to_CvMat ⇒ CvMat

Converts an object to CvMat

Returns:

  • (CvMat) —

    Converted matrix



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# File 'ext/opencv/cvmat.cpp', line 689

VALUE
rb_to_CvMat(VALUE self)
{
  // CvMat#to_CvMat aborts when self's class is CvMat.
  if (CLASS_OF(self) == rb_klass)
    return self;

  CvMat *mat = NULL;
  try {
    mat = cvGetMat(CVARR(self), RB_CVALLOC(CvMat));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return DEPEND_OBJECT(rb_klass, mat, self);
}

#to_IplConvKernel(anchor) ⇒ IplConvKernel

Creates a structuring element from the matrix for morphological operations.

Parameters:

  • anchor (CvPoint) —

    Anchor position within the element

Returns:



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# File 'ext/opencv/cvmat.cpp', line 404

VALUE
rb_to_IplConvKernel(VALUE self, VALUE anchor)
{
  CvMat *src = CVMAT(self);
  CvPoint p = VALUE_TO_CVPOINT(anchor);
  IplConvKernel *kernel = rb_cvCreateStructuringElementEx(src->cols, src->rows, p.x, p.y,
							  CV_SHAPE_CUSTOM, src->data.i);
  return DEPEND_OBJECT(cIplConvKernel::rb_class(), kernel, self);
}

#to_s ⇒ String

Returns String representation of the matrix.

Returns:

  • (String) —

    String representation of the matrix



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# File 'ext/opencv/cvmat.cpp', line 353

VALUE
rb_to_s(VALUE self)
{
  const int i = 6;
  VALUE str[i];
  str[0] = rb_str_new2("<%s:%dx%d,depth=%s,channel=%d>");
  str[1] = rb_str_new2(rb_class2name(CLASS_OF(self)));
  str[2] = rb_width(self);
  str[3] = rb_height(self);
  str[4] = rb_depth(self);
  str[5] = rb_channel(self);
  return rb_f_sprintf(i, str);
}

#trace ⇒ CvScalar

Returns the trace of a matrix.

Returns:



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# File 'ext/opencv/cvmat.cpp', line 2752

VALUE
rb_trace(VALUE self)
{
  CvScalar scalar;
  try {
    scalar = cvTrace(CVARR(self));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return cCvScalar::new_object(scalar);
}

#transform(transmat, shiftvec = nil) ⇒ CvMat

Performs the matrix transformation of every array element.

Parameters:

  • transmat (CvMat) —

    Transformation 2x2 or 2x3 floating-point matrix.

  • shiftvec (CvMat) —

    Optional translation vector.

Returns:

  • (CvMat) —

    Transformed array.



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# File 'ext/opencv/cvmat.cpp', line 2658

VALUE
rb_transform(int argc, VALUE *argv, VALUE self)
{
  VALUE transmat, shiftvec;
  rb_scan_args(argc, argv, "11", &transmat, &shiftvec);
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvTransform(self_ptr, CVARR(dest), CVMAT_WITH_CHECK(transmat),
		NIL_P(shiftvec) ? NULL : CVMAT_WITH_CHECK(shiftvec));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#transpose ⇒ CvMat Also known as: t

Transposes a matrix.

Returns:

  • (CvMat) —

    Transposed matrix.



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# File 'ext/opencv/cvmat.cpp', line 2772

VALUE
rb_transpose(VALUE self)
{
  CvMat* self_ptr = CVMAT(self);
  VALUE dest = new_mat_kind_object(cvSize(self_ptr->rows, self_ptr->cols), self);
  try {
    cvTranspose(self_ptr, CVARR(dest));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#vector? ⇒ Boolean

Returns whether the matrix is a vector.

Returns:

  • (Boolean) —

    If width or height of the matrix is 1, returns true. if not, returns false.



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# File 'ext/opencv/cvmat.cpp', line 661

VALUE
rb_vector_q(VALUE self)
{
  CvMat *mat = CVMAT(self);
  return (mat->width == 1|| mat->height == 1) ? Qtrue : Qfalse;
}

#vector_magnitude! ⇒ Object 



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# File 'ext/opencv/cvmat.cpp', line 1066

VALUE
rb_vector_magnitude(VALUE self)
{
  CvMat* self_ptr = CVMAT(self);
  int type = self_ptr->type, depth = CV_MAT_DEPTH(type), channel = CV_MAT_CN(type);

  CvArr* mat_ptr = CVARR(self);
	CvScalar this_scalar;
	CvSize arrSize = cvGetSize(CVARR(self));
	for(int i=0;i<(arrSize.height*arrSize.width)-1;i++) {
		this_scalar = cvGet1D(mat_ptr, i);

		int sum_of_squares = this_scalar.val[0]*this_scalar.val[0] + this_scalar.val[1]*this_scalar.val[1] + this_scalar.val[2]*this_scalar.val[2];
		cvSet1D(CVARR(self), i, cvScalar(sqrt(sum_of_squares), 0, 0, 0));
	}

	return self;
}

#warp_affine(map_matrix, flags = CV_INTER_LINEAR|CV_WARP_FILL_OUTLIERS, fillval = 0) ⇒ CvMat

Applies an affine transformation to an image.

Parameters:

  • map_matrix (CvMat) —

    2x3 transformation matrix.

  • flags (Integer) —

    Combination of interpolation methods (#see resize) and the optional flag WARP_INVERSE_MAP that means that map_matrix is the inverse transformation.

  • fillval (Number, CvScalar) —

    Value used in case of a constant border.

Returns:

  • (CvMat) —

    Output image that has the size size and the same type as self.



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# File 'ext/opencv/cvmat.cpp', line 4215

VALUE
rb_warp_affine(int argc, VALUE *argv, VALUE self)
{
  VALUE map_matrix, flags_val, fill_value;
  VALUE dest = Qnil;
  if (rb_scan_args(argc, argv, "12", &map_matrix, &flags_val, &fill_value) < 3)
    fill_value = INT2FIX(0);
  CvArr* self_ptr = CVARR(self);
  int flags = NIL_P(flags_val) ? (CV_INTER_LINEAR | CV_WARP_FILL_OUTLIERS) : NUM2INT(flags_val);
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvWarpAffine(self_ptr, CVARR(dest), CVMAT_WITH_CHECK(map_matrix),
		 flags, VALUE_TO_CVSCALAR(fill_value));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#warp_perspective(map_matrix, flags = CV_INTER_LINEAR|CV_WARP_FILL_OUTLIERS, fillval = 0) ⇒ CvMat

Applies a perspective transformation to an image.

Parameters:

  • map_matrix (CvMat) —

    3x3 transformation matrix.

  • flags (Integer) (defaults to: CV_INTER_LINEAR|CV_WARP_FILL_OUTLIERS) —

    Combination of interpolation methods (CV_INTER_LINEAR or CV_INTER_NEAREST) and the optional flag CV_WARP_INVERSE_MAP, that sets map_matrix as the inverse transformation.

  • fillval (Number, CvScalar) (defaults to: 0) —

    Value used in case of a constant border.

Returns:

  • (CvMat) —

    Output image.



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# File 'ext/opencv/cvmat.cpp', line 4364

VALUE
rb_warp_perspective(int argc, VALUE *argv, VALUE self)
{
  VALUE map_matrix, flags_val, option, fillval;
  if (rb_scan_args(argc, argv, "13", &map_matrix, &flags_val, &option, &fillval) < 4)
    fillval = INT2FIX(0);
  CvArr* self_ptr = CVARR(self);
  VALUE dest = Qnil;
  int flags = NIL_P(flags_val) ? (CV_INTER_LINEAR | CV_WARP_FILL_OUTLIERS) : NUM2INT(flags_val);
  try {
    dest = new_mat_kind_object(cvGetSize(self_ptr), self);
    cvWarpPerspective(self_ptr, CVARR(dest), CVMAT_WITH_CHECK(map_matrix),
		      flags, VALUE_TO_CVSCALAR(fillval));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#watershed(markers) ⇒ CvMat

Performs a marker-based image segmentation using the watershed algorithm.

Parameters:

  • markers (CvMat) —

    Input 32-bit single-channel image of markers. It should have the same size as self

Returns:

  • (CvMat) —

    Output image



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# File 'ext/opencv/cvmat.cpp', line 5458

VALUE
rb_watershed(VALUE self, VALUE markers)
{
  try {
    cvWatershed(CVARR(self), CVARR_WITH_CHECK(markers));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return markers;
}

#width ⇒ Integer Also known as: columns, cols

Returns number of columns of the matrix.

Returns:

  • (Integer) —

    Number of columns of the matrix



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# File 'ext/opencv/cvmat.cpp', line 438

VALUE
rb_width(VALUE self)
{
  return INT2NUM(CVMAT(self)->width);
}

#xor(val, mask = nil) ⇒ CvMat Also known as: ^

Calculates the per-element bit-wise “exclusive or” operation on two arrays or an array and a scalar.

Parameters:

  • val (CvMat, CvScalar) —

    Array or scalar to calculate bit-wise xor operation.

  • mask (CvMat) —

    Optional operation mask, 8-bit single channel array, that specifies elements of the destination array to be changed.

Returns:

  • (CvMat) —

    Result array



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# File 'ext/opencv/cvmat.cpp', line 2041

VALUE
rb_xor(int argc, VALUE *argv, VALUE self)
{
  VALUE val, mask, dest;
  rb_scan_args(argc, argv, "11", &val, &mask);
  dest = copy(self);
  try {
    if (rb_obj_is_kind_of(val, rb_klass))
      cvXor(CVARR(self), CVARR(val), CVARR(dest), MASK(mask));
    else
      cvXorS(CVARR(self), VALUE_TO_CVSCALAR(val), CVARR(dest), MASK(mask));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return dest;
}

#zero?(x, y) ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'ext/opencv/cvmat.cpp', line 1048

VALUE
rb_zero_q(VALUE self, VALUE x, VALUE y)
{
  CvScalar scalar;
  try {
    scalar = cvGet2D(CVARR(self), NUM2INT(y), NUM2INT(x));
  }
  catch (cv::Exception& e) {
    raise_cverror(e);
  }
  return (scalar.val[0] == 0 && scalar.val[1] == 0 && scalar.val[2] == 0 && scalar.val[3] == 0) ? Qtrue : Qfalse;
}