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Merge pull request #18969 from OrestChura:oc/fix_notes_returns

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[G-API] Multiple return/note fix

* Fix doxygen:
 - multiple return
 - multiple notes

* Addressing comments
 - divide description of split(merge)3/4
pull/19066/head
Orest Chura 4 years ago committed by GitHub
parent 619cc01ca1
commit f41327df0c
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  1. 76
      modules/gapi/include/opencv2/gapi/core.hpp
  2. 129
      modules/gapi/include/opencv2/gapi/imgproc.hpp
  3. 12
      modules/gapi/include/opencv2/gapi/video.hpp

76
modules/gapi/include/opencv2/gapi/core.hpp
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@ -1508,41 +1508,77 @@ Output image size will have the size dsize, the depth of output is the same as o
*/
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.
@ -1560,7 +1596,9 @@ convert from floating to fixed-point representations of a map is that they can y
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,
@ -1573,8 +1611,6 @@ and #INTER_LINEAR_EXACT are not supported by this function.
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,

129
modules/gapi/include/opencv2/gapi/imgproc.hpp
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@ -503,10 +503,10 @@ kernel kernelY. The final result is returned.
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:
@ -545,9 +545,9 @@ anchor.y - 1)`.
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
@ -582,9 +582,9 @@ algorithms, and so on). If you need to compute pixel sums over variable-size win
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).
@ -611,9 +611,9 @@ true, borderType)`.
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.
@ -639,9 +639,9 @@ Output image must have the same type and number of channels an input 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.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
@ -664,10 +664,10 @@ GAPI_EXPORTS GMat gaussianBlur(const GMat& src, const Size& ksize, double sigmaX
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 ...
@ -685,9 +685,9 @@ shape of a pixel neighborhood over which the minimum is taken:
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
@ -709,7 +709,9 @@ The function erodes the source image using the rectangular structuring element w
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.
@ -730,9 +732,9 @@ shape of a pixel neighborhood over which the maximum is taken:
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
@ -757,9 +759,9 @@ shape of a pixel neighborhood over which the maximum is taken:
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.
@ -780,7 +782,12 @@ basic operations.
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
@ -792,10 +799,6 @@ the kernel center.
@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),
@ -832,9 +835,9 @@ The second case corresponds to a kernel of:
\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
@ -883,11 +886,10 @@ The second case corresponds to a kernel 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
@ -1010,11 +1012,11 @@ described in @cite Shi94
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,
@ -1059,9 +1061,9 @@ The function equalizes the histogram of the input image using the following algo
- 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.
*/
@ -1121,8 +1123,9 @@ image of labels ( @ref CV_32SC1 ). If #RETR_FLOODFILL -- @ref CV_32SC1 supports
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
@ -1146,14 +1149,14 @@ of gray-scale image.
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);
@ -1199,14 +1202,13 @@ The algorithm is based on the M-estimator ( <http://en.wikipedia.org/wiki/M-esti
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
@ -1272,14 +1274,13 @@ The algorithm is based on the M-estimator ( <http://en.wikipedia.org/wiki/M-esti
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

12
modules/gapi/include/opencv2/gapi/video.hpp
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@ -150,8 +150,9 @@ G_TYPED_KERNEL(GBackgroundSubtractor, <GMat(GMat, BackgroundSubtractorParams)>,
@param tryReuseInputImage put ROI of input image into the pyramid if possible. You can pass false
to force data copying.
@return output pyramid.
@return number of levels in constructed pyramid. Can be less than maxLevel.
@return
- output pyramid.
- number of levels in constructed pyramid. Can be less than maxLevel.
*/
GAPI_EXPORTS std::tuple<GArray<GMat>, GScalar>
buildOpticalFlowPyramid(const GMat &img,
@ -198,11 +199,12 @@ by number of pixels in a window; if this value is less than minEigThreshold, the
feature is filtered out and its flow is not processed, so it allows to remove bad points and get a
performance boost.
@return GArray of 2D points (with single-precision floating-point coordinates)
@return
- GArray of 2D points (with single-precision floating-point coordinates)
containing the calculated new positions of input features in the second image.
@return status GArray (of unsigned chars); each element of the vector is set to 1 if
- status GArray (of unsigned chars); each element of the vector is set to 1 if
the flow for the corresponding features has been found, otherwise, it is set to 0.
@return GArray of errors (doubles); each element of the vector is set to an error for the
- GArray of errors (doubles); each element of the vector is set to an error for the
corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't
found then the error is not defined (use the status parameter to find such cases).
*/

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