*/
GAPI_EXPORTS GMatP resizeP(const GMatP& src, const Size& dsize, int interpolation = cv::INTER_LINEAR);
-/** @brief Creates one 3-channel (4-channel) matrix out of 3(4) single-channel ones.
+/** @brief Creates one 4-channel matrix out of 4 single-channel ones.
The function merges several matrices to make a single multi-channel matrix. That is, each
element of the output matrix will be a concatenation of the elements of the input matrices, where
elements of i-th input matrix are treated as mv[i].channels()-element vectors.
-Input matrix must be of @ref CV_8UC3 (@ref CV_8UC4) type.
+Output matrix must be of @ref CV_8UC4 type.
-The function split3/split4 does the reverse operation.
+The function split4 does the reverse operation.
-@note Function textual ID for merge3 is "org.opencv.core.transform.merge3"
-@note Function textual ID for merge4 is "org.opencv.core.transform.merge4"
+@note
+ - Function textual ID is "org.opencv.core.transform.merge4"
-@param src1 first input matrix to be merged
-@param src2 second input matrix to be merged
-@param src3 third input matrix to be merged
-@param src4 fourth input matrix to be merged
-@sa split4, split3
+@param src1 first input @ref CV_8UC1 matrix to be merged.
+@param src2 second input @ref CV_8UC1 matrix to be merged.
+@param src3 third input @ref CV_8UC1 matrix to be merged.
+@param src4 fourth input @ref CV_8UC1 matrix to be merged.
+@sa merge3, split4, split3
*/
GAPI_EXPORTS GMat merge4(const GMat& src1, const GMat& src2, const GMat& src3, const GMat& src4);
+
+/** @brief Creates one 3-channel matrix out of 3 single-channel ones.
+
+The function merges several matrices to make a single multi-channel matrix. That is, each
+element of the output matrix will be a concatenation of the elements of the input matrices, where
+elements of i-th input matrix are treated as mv[i].channels()-element vectors.
+Output matrix must be of @ref CV_8UC3 type.
+
+The function split3 does the reverse operation.
+
+@note
+ - Function textual ID is "org.opencv.core.transform.merge3"
+
+@param src1 first input @ref CV_8UC1 matrix to be merged.
+@param src2 second input @ref CV_8UC1 matrix to be merged.
+@param src3 third input @ref CV_8UC1 matrix to be merged.
+@sa merge4, split4, split3
+*/
GAPI_EXPORTS GMat merge3(const GMat& src1, const GMat& src2, const GMat& src3);
-/** @brief Divides a 3-channel (4-channel) matrix into 3(4) single-channel matrices.
+/** @brief Divides a 4-channel matrix into 4 single-channel matrices.
-The function splits a 3-channel (4-channel) matrix into 3(4) single-channel matrices:
+The function splits a 4-channel matrix into 4 single-channel matrices:
\f[\texttt{mv} [c](I) = \texttt{src} (I)_c\f]
-All output matrices must be in @ref CV_8UC1.
+All output matrices must be of @ref CV_8UC1 type.
+
+The function merge4 does the reverse operation.
-@note Function textual for split3 ID is "org.opencv.core.transform.split3"
-@note Function textual for split4 ID is "org.opencv.core.transform.split4"
+@note
+ - Function textual ID is "org.opencv.core.transform.split4"
-@param src input @ref CV_8UC4 (@ref CV_8UC3) matrix.
-@sa merge3, merge4
+@param src input @ref CV_8UC4 matrix.
+@sa split3, merge3, merge4
*/
GAPI_EXPORTS std::tuple<GMat, GMat, GMat,GMat> split4(const GMat& src);
+
+/** @brief Divides a 3-channel matrix into 3 single-channel matrices.
+
+The function splits a 3-channel matrix into 3 single-channel matrices:
+\f[\texttt{mv} [c](I) = \texttt{src} (I)_c\f]
+
+All output matrices must be of @ref CV_8UC1 type.
+
+The function merge3 does the reverse operation.
+
+@note
+ - Function textual ID is "org.opencv.core.transform.split3"
+
+@param src input @ref CV_8UC3 matrix.
+@sa split4, merge3, merge4
+*/
GAPI_EXPORTS_W std::tuple<GMat, GMat, GMat> split3(const GMat& src);
/** @brief Applies a generic geometrical transformation to an image.
cvFloor(y)) and \f$map_2\f$ contains indices in a table of interpolation coefficients.
Output image must be of the same size and depth as input one.
-@note Function textual ID is "org.opencv.core.transform.remap"
+@note
+ - Function textual ID is "org.opencv.core.transform.remap"
+ - Due to current implementation limitations the size of an input and output images should be less than 32767x32767.
@param src Source image.
@param map1 The first map of either (x,y) points or just x values having the type CV_16SC2,
borderMode=BORDER_TRANSPARENT, it means that the pixels in the destination image that
corresponds to the "outliers" in the source image are not modified by the function.
@param borderValue Value used in case of a constant border. By default, it is 0.
-@note
-Due to current implementation limitations the size of an input and output images should be less than 32767x32767.
*/
GAPI_EXPORTS GMat remap(const GMat& src, const Mat& map1, const Mat& map2,
int interpolation, int borderMode = BORDER_CONSTANT,
Supported matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref CV_16SC1, @ref CV_32FC1.
Output image must have the same type, size, and number of channels as the input image.
-@note In case of floating-point computation, rounding to nearest even is procedeed
+@note
+ - In case of floating-point computation, rounding to nearest even is procedeed
if hardware supports it (if not - to nearest value).
-
-@note Function textual ID is "org.opencv.imgproc.filters.sepfilter"
+ - Function textual ID is "org.opencv.imgproc.filters.sepfilter"
@param src Source image.
@param ddepth desired depth of the destination image (the following combinations of src.depth() and ddepth are supported:
Supported matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref CV_16SC1, @ref CV_32FC1.
Output image must have the same size and number of channels an input image.
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
-
-@note Function textual ID is "org.opencv.imgproc.filters.filter2D"
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.filter2D"
@param src input image.
@param ddepth desired depth of the destination image
Supported input matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref CV_16SC1, @ref CV_32FC1.
Output image must have the same type, size, and number of channels as the input image.
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
-
-@note Function textual ID is "org.opencv.imgproc.filters.boxfilter"
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.boxfilter"
@param src Source image.
@param dtype the output image depth (-1 to set the input image data type).
Supported input matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref CV_16SC1, @ref CV_32FC1.
Output image must have the same type, size, and number of channels as the input image.
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
-
-@note Function textual ID is "org.opencv.imgproc.filters.blur"
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.blur"
@param src Source image.
@param ksize blurring kernel size.
Supported input matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref CV_16SC1, @ref CV_32FC1.
Output image must have the same type, size, and number of channels as the input image.
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
-
-@note Function textual ID is "org.opencv.imgproc.filters.gaussianBlur"
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.gaussianBlur"
@param src input image;
@param ksize Gaussian kernel size. ksize.width and ksize.height can differ but they both must be
The function smoothes an image using the median filter with the \f$\texttt{ksize} \times
\texttt{ksize}\f$ aperture. Each channel of a multi-channel image is processed independently.
Output image must have the same type, size, and number of channels as the input image.
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
The median filter uses cv::BORDER_REPLICATE internally to cope with border pixels, see cv::BorderTypes
-
-@note Function textual ID is "org.opencv.imgproc.filters.medianBlur"
+ - Function textual ID is "org.opencv.imgproc.filters.medianBlur"
@param src input matrix (image)
@param ksize aperture linear size; it must be odd and greater than 1, for example: 3, 5, 7 ...
Erosion can be applied several (iterations) times. In case of multi-channel images, each channel is processed independently.
Supported input matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref CV_16SC1, and @ref CV_32FC1.
Output image must have the same type, size, and number of channels as the input image.
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
-
-@note Function textual ID is "org.opencv.imgproc.filters.erode"
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.erode"
@param src input image
@param kernel structuring element used for erosion; if `element=Mat()`, a `3 x 3` rectangular
Erosion can be applied several (iterations) times. In case of multi-channel images, each channel is processed independently.
Supported input matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref CV_16SC1, and @ref CV_32FC1.
Output image must have the same type, size, and number of channels as the input image.
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.erode"
@param src input image
@param iterations number of times erosion is applied.
Dilation can be applied several (iterations) times. In case of multi-channel images, each channel is processed independently.
Supported input matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref CV_16SC1, and @ref CV_32FC1.
Output image must have the same type, size, and number of channels as the input image.
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
-
-@note Function textual ID is "org.opencv.imgproc.filters.dilate"
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.dilate"
@param src input image.
@param kernel structuring element used for dilation; if elemenat=Mat(), a 3 x 3 rectangular
Dilation can be applied several (iterations) times. In case of multi-channel images, each channel is processed independently.
Supported input matrix data types are @ref CV_8UC1, @ref CV_8UC3, @ref CV_16UC1, @ref CV_16SC1, and @ref CV_32FC1.
Output image must have the same type, size, and number of channels as the input image.
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
-
-@note Function textual ID is "org.opencv.imgproc.filters.dilate"
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.dilate"
@param src input image.
@param iterations number of times dilation is applied.
Any of the operations can be done in-place. In case of multi-channel images, each channel is
processed independently.
-@note Function textual ID is "org.opencv.imgproc.filters.morphologyEx"
+@note
+ - Function textual ID is "org.opencv.imgproc.filters.morphologyEx"
+ - The number of iterations is the number of times erosion or dilatation operation will be
+applied. For instance, an opening operation (#MORPH_OPEN) with two iterations is equivalent to
+apply successively: erode -> erode -> dilate -> dilate
+(and not erode -> dilate -> erode -> dilate).
@param src Input image.
@param op Type of a morphological operation, see #MorphTypes
@param borderValue Border value in case of a constant border. The default value has a special
meaning.
@sa dilate, erode, getStructuringElement
-@note The number of iterations is the number of times erosion or dilatation operation will be
-applied. For instance, an opening operation (#MORPH_OPEN) with two iterations is equivalent to
-apply successively: erode -> erode -> dilate -> dilate
-(and not erode -> dilate -> erode -> dilate).
*/
GAPI_EXPORTS GMat morphologyEx(const GMat &src, const MorphTypes op, const Mat &kernel,
const Point &anchor = Point(-1,-1),
\f[\vecthreethree{-1}{-2}{-1}{0}{0}{0}{1}{2}{1}\f]
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
-
-@note Function textual ID is "org.opencv.imgproc.filters.sobel"
+@note
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.sobel"
@param src input image.
@param ddepth output image depth, see @ref filter_depths "combinations"; in the case of
\f[\vecthreethree{-1}{-2}{-1}{0}{0}{0}{1}{2}{1}\f]
-@note First returned matrix correspons to dx derivative while the second one to dy.
-
-@note Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
-
-@note Function textual ID is "org.opencv.imgproc.filters.sobelxy"
+@note
+ - First returned matrix correspons to dx derivative while the second one to dy.
+ - Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
+ - Function textual ID is "org.opencv.imgproc.filters.sobelxy"
@param src input image.
@param ddepth output image depth, see @ref filter_depths "combinations"; in the case of
The function can be used to initialize a point-based tracker of an object.
-@note If the function is called with different values A and B of the parameter qualityLevel , and
+@note
+ - If the function is called with different values A and B of the parameter qualityLevel , and
A \> B, the vector of returned corners with qualityLevel=A will be the prefix of the output vector
with qualityLevel=B .
-
-@note Function textual ID is "org.opencv.imgproc.feature.goodFeaturesToTrack"
+ - Function textual ID is "org.opencv.imgproc.feature.goodFeaturesToTrack"
@param image Input 8-bit or floating-point 32-bit, single-channel image.
@param maxCorners Maximum number of corners to return. If there are more corners than are found,
- Transform the image using \f$H'\f$ as a look-up table: \f$\texttt{dst}(x,y) = H'(\texttt{src}(x,y))\f$
The algorithm normalizes the brightness and increases the contrast of the image.
-@note The returned image is of the same size and type as input.
-
-@note Function textual ID is "org.opencv.imgproc.equalizeHist"
+@note
+ - The returned image is of the same size and type as input.
+ - Function textual ID is "org.opencv.imgproc.equalizeHist"
@param src Source 8-bit single channel image.
*/
contours are extracted from the image ROI and then they should be analyzed in the whole image
context.
-@return GArray of detected contours. Each contour is stored as a GArray of points.
-@return Optional output GArray of cv::Vec4i, containing information about the image topology.
+@return
+ - GArray of detected contours. Each contour is stored as a GArray of points.
+ - Optional output GArray of cv::Vec4i, containing information about the image topology.
It has as many elements as the number of contours. For each i-th contour contours[i], the elements
hierarchy[i][0] , hierarchy[i][1] , hierarchy[i][2] , and hierarchy[i][3] are set to 0-based
indices in contours of the next and previous contours at the same hierarchical level, the first
The function calculates and returns the minimal up-right bounding rectangle for the specified
point set or non-zero pixels of gray-scale image.
-@note Function textual ID is "org.opencv.imgproc.shape.boundingRectMat"
+@note
+ - Function textual ID is "org.opencv.imgproc.shape.boundingRectMat"
+ - In case of a 2D points' set given, Mat should be 2-dimensional, have a single row or column
+if there are 2 channels, or have 2 columns if there is a single channel. Mat should have either
+@ref CV_32S or @ref CV_32F depth
@param src Input gray-scale image @ref CV_8UC1; or input set of @ref CV_32S or @ref CV_32F
2D points stored in Mat.
-
-@note In case of a 2D points' set given, Mat should be 2-dimensional, have a single row or column
-if there are 2 channels, or have 2 columns if there is a single channel. Mat should have either
-@ref CV_32S or @ref CV_32F depth
*/
GAPI_EXPORTS GOpaque<Rect> boundingRect(const GMat& src);
that iteratively fits the line using the weighted least-squares algorithm. After each iteration the
weights \f$w_i\f$ are adjusted to be inversely proportional to \f$\rho(r_i)\f$ .
-@note Function textual ID is "org.opencv.imgproc.shape.fitLine2DMat"
+@note
+ - Function textual ID is "org.opencv.imgproc.shape.fitLine2DMat"
+ - In case of an N-dimentional points' set given, Mat should be 2-dimensional, have a single row
+or column if there are N channels, or have N columns if there is a single channel.
@param src Input set of 2D points stored in one of possible containers: Mat,
std::vector<cv::Point2i>, std::vector<cv::Point2f>, std::vector<cv::Point2d>.
-
-@note In case of an N-dimentional points' set given, Mat should be 2-dimensional, have a single row
-or column if there are N channels, or have N columns if there is a single channel.
-
@param distType Distance used by the M-estimator, see #DistanceTypes. @ref DIST_USER
and @ref DIST_C are not suppored.
@param param Numerical parameter ( C ) for some types of distances. If it is 0, an optimal value
that iteratively fits the line using the weighted least-squares algorithm. After each iteration the
weights \f$w_i\f$ are adjusted to be inversely proportional to \f$\rho(r_i)\f$ .
-@note Function textual ID is "org.opencv.imgproc.shape.fitLine3DMat"
+@note
+ - Function textual ID is "org.opencv.imgproc.shape.fitLine3DMat"
+ - In case of an N-dimentional points' set given, Mat should be 2-dimensional, have a single row
+or column if there are N channels, or have N columns if there is a single channel.
@param src Input set of 3D points stored in one of possible containers: Mat,
std::vector<cv::Point3i>, std::vector<cv::Point3f>, std::vector<cv::Point3d>.
-
-@note In case of an N-dimentional points' set given, Mat should be 2-dimensional, have a single row
-or column if there are N channels, or have N columns if there is a single channel.
-
@param distType Distance used by the M-estimator, see #DistanceTypes. @ref DIST_USER
and @ref DIST_C are not suppored.
@param param Numerical parameter ( C ) for some types of distances. If it is 0, an optimal value