Commit fc307c87 authored by Vsevolod Glumov's avatar Vsevolod Glumov

Improved the public 'non-optimized' duplicates of 'Tegra-optimized' functions.

parent 2e685dcf
......@@ -502,27 +502,27 @@ Sample usage of detecting and drawing chessboard corners: ::
findCirclesGrid
-------------------
Finds the centers in the grid of circles.
Finds centers in the grid of circles.
.. ocv:function:: bool findCirclesGrid( InputArray image, Size patternSize, OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID, const Ptr<FeatureDetector> &blobDetector = new SimpleBlobDetector() )
.. ocv:pyfunction:: cv2.findCirclesGridDefault(image, patternSize[, centers[, flags]]) -> retval, centers
:param image: Grid view of source circles. It must be an 8-bit grayscale or color image.
:param image: grid view of input circles; it must be an 8-bit grayscale or color image.
:param patternSize: Number of circles per a grid row and column ``( patternSize = Size(points_per_row, points_per_colum) )`` .
:param patternSize: number of circles per row and column ``( patternSize = Size(points_per_row, points_per_colum) )``.
:param centers: Output array of detected centers.
:param centers: output array of detected centers.
:param flags: Various operation flags that can be one of the following values:
:param flags: various operation flags that can be one of the following values:
* **CALIB_CB_SYMMETRIC_GRID** Use symmetric pattern of circles.
* **CALIB_CB_SYMMETRIC_GRID** uses symmetric pattern of circles.
* **CALIB_CB_ASYMMETRIC_GRID** Use asymmetric pattern of circles.
* **CALIB_CB_ASYMMETRIC_GRID** uses asymmetric pattern of circles.
* **CALIB_CB_CLUSTERING** Use a special algorithm for grid detection. It is more robust to perspective distortions but much more sensitive to background clutter.
* **CALIB_CB_CLUSTERING** uses a special algorithm for grid detection. It is more robust to perspective distortions but much more sensitive to background clutter.
:param blobDetector: FeatureDetector that finds blobs like dark circles on light background
:param blobDetector: feature detector that finds blobs like dark circles on light background.
The function attempts to determine
......
......@@ -778,7 +778,7 @@ Here are examples of matrix expressions:
Below is the formal description of the ``Mat`` methods.
Mat::Mat
------------
--------
Various Mat constructors
.. ocv:function:: Mat::Mat()
......@@ -861,7 +861,7 @@ often the default constructor is enough, and the proper matrix will be allocated
Mat::~Mat
------------
---------
The Mat destructor.
.. ocv:function:: Mat::~Mat()
......@@ -870,7 +870,7 @@ The matrix destructor calls :ocv:func:`Mat::release` .
Mat::operator =
-------------------
---------------
Provides matrix assignment operators.
.. ocv:function:: Mat& Mat::operator = (const Mat& m)
......@@ -888,7 +888,7 @@ Provides matrix assignment operators.
These are available assignment operators. Since they all are very different, make sure to read the operator parameters description.
Mat::row
------------
--------
Creates a matrix header for the specified matrix row.
.. ocv:function:: Mat Mat::row(int y) const
......@@ -923,7 +923,7 @@ The method makes a new header for the specified matrix row and returns it. This
A.row(j).copyTo(A.row(i));
Mat::col
------------
--------
Creates a matrix header for the specified matrix column.
.. ocv:function:: Mat Mat::col(int x) const
......@@ -935,7 +935,7 @@ The method makes a new header for the specified matrix column and returns it. Th
Mat::rowRange
-----------------
-------------
Creates a matrix header for the specified row span.
.. ocv:function:: Mat Mat::rowRange(int startrow, int endrow) const
......@@ -953,7 +953,7 @@ The method makes a new header for the specified row span of the matrix. Similarl
:ocv:func:`Mat::col` , this is an O(1) operation.
Mat::colRange
-----------------
-------------
Creates a matrix header for the specified row span.
.. ocv:function:: Mat Mat::colRange(int startcol, int endcol) const
......@@ -971,7 +971,7 @@ The method makes a new header for the specified column span of the matrix. Simil
:ocv:func:`Mat::col` , this is an O(1) operation.
Mat::diag
-------------
---------
Extracts a diagonal from a matrix, or creates a diagonal matrix.
.. ocv:function:: Mat Mat::diag( int d=0 ) const
......@@ -991,7 +991,7 @@ The method makes a new header for the specified matrix diagonal. The new matrix
:ocv:func:`Mat::col` , this is an O(1) operation.
Mat::clone
--------------
----------
Creates a full copy of the array and the underlying data.
.. ocv:function:: Mat Mat::clone() const
......@@ -1000,7 +1000,7 @@ The method creates a full copy of the array. The original ``step[]`` is not take
Mat::copyTo
---------------
-----------
Copies the matrix to another one.
.. ocv:function:: void Mat::copyTo( OutputArray m ) const
......@@ -1022,18 +1022,18 @@ When the operation mask is specified, and the ``Mat::create`` call shown above r
.. _Mat::convertTo:
Mat::convertTo
------------------
--------------
Converts an array to another data type with optional scaling.
.. ocv:function:: void Mat::convertTo( OutputArray m, int rtype, double alpha=1, double beta=0 ) const
:param m: Destination matrix. If it does not have a proper size or type before the operation, it is reallocated.
:param m: output matrix; if it does not have a proper size or type before the operation, it is reallocated.
:param rtype: Desired destination matrix type or, rather, the depth since the number of channels are the same as the source has. If ``rtype`` is negative, the destination matrix will have the same type as the source.
:param rtype: desired output matrix type or, rather, the depth since the number of channels are the same as the input has; if ``rtype`` is negative, the output matrix will have the same type as the input.
:param alpha: Optional scale factor.
:param alpha: optional scale factor.
:param beta: Optional delta added to the scaled values.
:param beta: optional delta added to the scaled values.
The method converts source pixel values to the target data type. ``saturate_cast<>`` is applied at the end to avoid possible overflows:
......@@ -1043,7 +1043,7 @@ The method converts source pixel values to the target data type. ``saturate_cast
Mat::assignTo
-----------------
-------------
Provides a functional form of ``convertTo``.
.. ocv:function:: void Mat::assignTo( Mat& m, int type=-1 ) const
......@@ -1056,7 +1056,7 @@ This is an internally used method called by the
:ref:`MatrixExpressions` engine.
Mat::setTo
--------------
----------
Sets all or some of the array elements to the specified value.
.. ocv:function:: Mat& Mat::setTo( InputArray value, InputArray mask=noArray() )
......@@ -1067,7 +1067,7 @@ Sets all or some of the array elements to the specified value.
Mat::reshape
----------------
------------
Changes the shape and/or the number of channels of a 2D matrix without copying the data.
.. ocv:function:: Mat Mat::reshape(int cn, int rows=0) const
......@@ -1100,7 +1100,7 @@ For example, if there is a set of 3D points stored as an STL vector, and you wan
Mat::t
----------
------
Transposes a matrix.
.. ocv:function:: MatExpr Mat::t() const
......@@ -1112,7 +1112,7 @@ The method performs matrix transposition by means of matrix expressions. It does
Mat::inv
------------
--------
Inverses a matrix.
.. ocv:function:: MatExpr Mat::inv(int method=DECOMP_LU) const
......@@ -1129,7 +1129,7 @@ The method performs a matrix inversion by means of matrix expressions. This mean
Mat::mul
------------
--------
Performs an element-wise multiplication or division of the two matrices.
.. ocv:function:: MatExpr Mat::mul(InputArray m, double scale=1) const
......@@ -1146,7 +1146,7 @@ Example: ::
Mat::cross
--------------
----------
Computes a cross-product of two 3-element vectors.
.. ocv:function:: Mat Mat::cross(InputArray m) const
......@@ -1157,18 +1157,18 @@ The method computes a cross-product of two 3-element vectors. The vectors must b
Mat::dot
------------
--------
Computes a dot-product of two vectors.
.. ocv:function:: double Mat::dot(InputArray m) const
:param m: Another dot-product operand.
:param m: another dot-product operand.
The method computes a dot-product of two matrices. If the matrices are not single-column or single-row vectors, the top-to-bottom left-to-right scan ordering is used to treat them as 1D vectors. The vectors must have the same size and type. If the matrices have more than one channel, the dot products from all the channels are summed together.
Mat::zeros
--------------
----------
Returns a zero array of the specified size and type.
.. ocv:function:: static MatExpr Mat::zeros(int rows, int cols, int type)
......@@ -1443,7 +1443,7 @@ The operators make a new header for the specified sub-array of ``*this`` . They
Mat::operator CvMat
-----------------------
-------------------
Creates the ``CvMat`` header for the matrix.
.. ocv:function:: Mat::operator CvMat() const
......@@ -1462,7 +1462,7 @@ where ``mycvOldFunc`` is a function written to work with OpenCV 1.x data structu
Mat::operator IplImage
--------------------------
----------------------
Creates the ``IplImage`` header for the matrix.
.. ocv:function:: Mat::operator IplImage() const
......@@ -1470,7 +1470,7 @@ Creates the ``IplImage`` header for the matrix.
The operator creates the ``IplImage`` header for the matrix without copying the underlying data. You should make sure than the original matrix is not deallocated while the ``IplImage`` header is used. Similarly to ``Mat::operator CvMat`` , the operator is useful for intermixing the new and the old OpenCV API's.
Mat::total
--------------
----------
Returns the total number of array elements.
.. ocv:function:: size_t Mat::total() const
......@@ -1478,7 +1478,7 @@ Returns the total number of array elements.
The method returns the number of array elements (a number of pixels if the array represents an image).
Mat::isContinuous
---------------------
-----------------
Reports whether the matrix is continuous or not.
.. ocv:function:: bool Mat::isContinuous() const
......@@ -1576,7 +1576,7 @@ The method returns a matrix element type. This is an identifier compatible with
Mat::depth
--------------
----------
Returns the depth of a matrix element.
.. ocv:function:: int Mat::depth() const
......@@ -1599,7 +1599,7 @@ The method returns the identifier of the matrix element depth (the type of each
Mat::channels
-----------------
-------------
Returns the number of matrix channels.
.. ocv:function:: int Mat::channels() const
......@@ -1608,7 +1608,7 @@ The method returns the number of matrix channels.
Mat::step1
--------------
----------
Returns a normalized step.
.. ocv:function:: size_t Mat::step1( int i=0 ) const
......@@ -1618,7 +1618,7 @@ The method returns a matrix step divided by
Mat::size
-------------
---------
Returns a matrix size.
.. ocv:function:: Size Mat::size() const
......@@ -1627,7 +1627,7 @@ The method returns a matrix size: ``Size(cols, rows)`` . When the matrix is more
Mat::empty
--------------
----------
Returns ``true`` if the array has no elements.
.. ocv:function:: bool Mat::empty() const
......@@ -1636,7 +1636,7 @@ The method returns ``true`` if ``Mat::total()`` is 0 or if ``Mat::data`` is NULL
Mat::ptr
------------
--------
Returns a pointer to the specified matrix row.
.. ocv:function:: uchar* Mat::ptr(int i0=0)
......@@ -1654,7 +1654,7 @@ The methods return ``uchar*`` or typed pointer to the specified matrix row. See
Mat::at
-----------
-------
Returns a reference to the specified array element.
.. ocv:function:: template<typename T> T& Mat::at(int i) const
......
This diff is collapsed.
......@@ -4,18 +4,18 @@ Feature Detection and Description
.. highlight:: cpp
FAST
--------
----
Detects corners using the FAST algorithm
.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression=true, type=FastFeatureDetector::TYPE_9_16 )
:param image: Image where keypoints (corners) are detected.
:param image: grayscale image where keypoints (corners) are detected.
:param keypoints: Keypoints detected on the image.
:param keypoints: keypoints detected on the image.
:param threshold: Threshold on difference between intensity of the central pixel and pixels on a circle around this pixel. See the algorithm description below.
:param threshold: threshold on difference between intensity of the central pixel and pixels of a circle around this pixel.
:param nonmaxSupression: If it is true, non-maximum suppression is applied to detected corners (keypoints).
:param nonmaxSupression: if true, non-maximum suppression is applied to detected corners (keypoints).
:param type: one of the three neighborhoods as defined in the paper: ``FastFeatureDetector::TYPE_9_16``, ``FastFeatureDetector::TYPE_7_12``, ``FastFeatureDetector::TYPE_5_8``
......
......@@ -17,17 +17,17 @@ Finds edges in an image using the [Canny86]_ algorithm.
.. ocv:pyoldfunction:: cv.Canny(image, edges, threshold1, threshold2, aperture_size=3) -> None
:param image: Single-channel 8-bit input image.
:param image: single-channel 8-bit input image.
:param edges: Output edge map. It has the same size and type as ``image`` .
:param edges: output edge map; it has the same size and type as ``image`` .
:param threshold1: First threshold for the hysteresis procedure.
:param threshold1: first threshold for the hysteresis procedure.
:param threshold2: Second threshold for the hysteresis procedure.
:param threshold2: second threshold for the hysteresis procedure.
:param apertureSize: Aperture size for the :ocv:func:`Sobel` operator.
:param apertureSize: aperture size for the :ocv:func:`Sobel` operator.
:param L2gradient: Flag indicating whether a more accurate :math:`L_2` norm :math:`=\sqrt{(dI/dx)^2 + (dI/dy)^2}` should be used to compute the image gradient magnitude ( ``L2gradient=true`` ), or a faster default :math:`L_1` norm :math:`=|dI/dx|+|dI/dy|` is enough ( ``L2gradient=false`` ).
:param L2gradient: a flag, indicating whether a more accurate :math:`L_2` norm :math:`=\sqrt{(dI/dx)^2 + (dI/dy)^2}` should be used to calculate the image gradient magnitude ( ``L2gradient=true`` ), or whether the default :math:`L_1` norm :math:`=|dI/dx|+|dI/dy|` is enough ( ``L2gradient=false`` ).
The function finds edges in the input image ``image`` and marks them in the output map ``edges`` using the Canny algorithm. The smallest value between ``threshold1`` and ``threshold2`` is used for edge linking. The largest value is used to find initial segments of strong edges. See
http://en.wikipedia.org/wiki/Canny_edge_detector
......
This diff is collapsed.
......@@ -356,7 +356,7 @@ This function cannot operate in-place.
resize
----------
------
Resizes an image.
.. ocv:function:: void resize( InputArray src, OutputArray dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR )
......@@ -366,11 +366,11 @@ Resizes an image.
.. ocv:cfunction:: void cvResize( const CvArr* src, CvArr* dst, int interpolation=CV_INTER_LINEAR )
.. ocv:pyoldfunction:: cv.Resize(src, dst, interpolation=CV_INTER_LINEAR)-> None
:param src: Source image.
:param src: input image.
:param dst: Destination image. It has the size ``dsize`` (when it is non-zero) or the size computed from ``src.size()`` , ``fx`` , and ``fy`` . The type of ``dst`` is the same as of ``src`` .
:param dst: output image; it has the size ``dsize`` (when it is non-zero) or the size computed from ``src.size()``, ``fx``, and ``fy``; the type of ``dst`` is the same as of ``src``.
:param dsize: Destination image size. If it is zero, it is computed as:
:param dsize: output image size; if it equals zero, it is computed as:
.. math::
......@@ -379,19 +379,19 @@ Resizes an image.
Either ``dsize`` or both ``fx`` and ``fy`` must be non-zero.
:param fx: Scale factor along the horizontal axis. When it is 0, it is computed as
:param fx: scale factor along the horizontal axis; when it equals 0, it is computed as
.. math::
\texttt{(double)dsize.width/src.cols}
:param fy: Scale factor along the vertical axis. When it is 0, it is computed as
:param fy: scale factor along the vertical axis; when it equals 0, it is computed as
.. math::
\texttt{(double)dsize.height/src.rows}
:param interpolation: Interpolation method:
:param interpolation: interpolation method:
* **INTER_NEAREST** - a nearest-neighbor interpolation
......@@ -425,7 +425,7 @@ To shrink an image, it will generally look best with CV_INTER_AREA interpolation
warpAffine
--------------
----------
Applies an affine transformation to an image.
.. ocv:function:: void warpAffine( InputArray src, OutputArray dst, InputArray M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar& borderValue=Scalar())
......@@ -440,19 +440,19 @@ Applies an affine transformation to an image.
.. ocv:pyoldfunction:: cv.GetQuadrangleSubPix(src, dst, mapMatrix)-> None
:param src: Source image.
:param src: input image.
:param dst: Destination image that has the size ``dsize`` and the same type as ``src`` .
:param dst: output image that has the size ``dsize`` and the same type as ``src`` .
:param M: :math:`2\times 3` transformation matrix.
:param M: :math:`2\times 3` transformation matrix.
:param dsize: Size of the destination image.
:param dsize: size of the output image.
:param flags: Combination of interpolation methods (see :ocv:func:`resize` ) and the optional flag ``WARP_INVERSE_MAP`` that means that ``M`` is the inverse transformation ( :math:`\texttt{dst}\rightarrow\texttt{src}` ).
:param flags: combination of interpolation methods (see :ocv:func:`resize` ) and the optional flag ``WARP_INVERSE_MAP`` that means that ``M`` is the inverse transformation ( :math:`\texttt{dst}\rightarrow\texttt{src}` ).
:param borderMode: Pixel extrapolation method (see :ocv:func:`borderInterpolate` ). When \ ``borderMode=BORDER_TRANSPARENT`` , it means that the pixels in the destination image corresponding to the "outliers" in the source image are not modified by the function.
:param borderMode: pixel extrapolation method (see :ocv:func:`borderInterpolate`); when \ ``borderMode=BORDER_TRANSPARENT`` , it means that the pixels in the destination image corresponding 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.
:param borderValue: value used in case of a constant border; by default, it is 0.
The function ``warpAffine`` transforms the source image using the specified matrix:
......@@ -476,7 +476,7 @@ The function cannot operate in-place.
.. note:: ``cvGetQuadrangleSubPix`` is similar to ``cvWarpAffine``, but the outliers are extrapolated using replication border mode.
warpPerspective
-------------------
---------------
Applies a perspective transformation to an image.
.. ocv:function:: void warpPerspective( InputArray src, OutputArray dst, InputArray M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar& borderValue=Scalar())
......@@ -487,19 +487,19 @@ Applies a perspective transformation to an image.
.. ocv:pyoldfunction:: cv.WarpPerspective(src, dst, mapMatrix, flags=CV_INNER_LINEAR+CV_WARP_FILL_OUTLIERS, fillval=(0, 0, 0, 0))-> None
:param src: Source image.
:param src: input image.
:param dst: Destination image that has the size ``dsize`` and the same type as ``src`` .
:param dst: output image that has the size ``dsize`` and the same type as ``src`` .
:param M: :math:`3\times 3` transformation matrix.
:param dsize: Size of the destination image.
:param dsize: size of the output image.
:param flags: Combination of interpolation methods (see :ocv:func:`resize` ) and the optional flag ``WARP_INVERSE_MAP`` that means that ``M`` is the inverse transformation ( :math:`\texttt{dst}\rightarrow\texttt{src}` ).
:param flags: combination of interpolation methods (``INTER_LINEAR`` or ``INTER_NEAREST``) and the optional flag ``WARP_INVERSE_MAP``, that sets ``M`` as the inverse transformation ( :math:`\texttt{dst}\rightarrow\texttt{src}` ).
:param borderMode: Pixel extrapolation method (see :ocv:func:`borderInterpolate` ). When \ ``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 borderMode: pixel extrapolation method (``BORDER_CONSTANT`` or ``BORDER_REPLICATE``).
:param borderValue: Value used in case of a constant border. By default, it is 0.
:param borderValue: value used in case of a constant border; by default, it equals 0.
The function ``warpPerspective`` transforms the source image using the specified matrix:
......@@ -524,7 +524,7 @@ The function cannot operate in-place.
initUndistortRectifyMap
---------------------------
-----------------------
Computes the undistortion and rectification transformation map.
.. ocv:function:: void initUndistortRectifyMap( InputArray cameraMatrix, InputArray distCoeffs, InputArray R, InputArray newCameraMatrix, Size size, int m1type, OutputArray map1, OutputArray map2 )
......
......@@ -71,7 +71,7 @@ The function can process the image in-place.
cvtColor
------------
--------
Converts an image from one color space to another.
.. ocv:function:: void cvtColor( InputArray src, OutputArray dst, int code, int dstCn=0 )
......@@ -81,13 +81,13 @@ Converts an image from one color space to another.
.. ocv:cfunction:: void cvCvtColor( const CvArr* src, CvArr* dst, int code )
.. ocv:pyoldfunction:: cv.CvtColor(src, dst, code)-> None
:param src: Source image: 8-bit unsigned, 16-bit unsigned ( ``CV_16UC...`` ), or single-precision floating-point.
:param src: input image: 8-bit unsigned, 16-bit unsigned ( ``CV_16UC...`` ), or single-precision floating-point.
:param dst: Destination image of the same size and depth as ``src`` .
:param dst: output image of the same size and depth as ``src``.
:param code: Color space conversion code. See the description below.
:param code: color space conversion code (see the description below).
:param dstCn: Number of channels in the destination image. If the parameter is 0, the number of the channels is derived automatically from ``src`` and ``code`` .
:param dstCn: number of channels in the destination image; if the parameter is 0, the number of the channels is derived automatically from ``src`` and ``code`` .
The function converts an input image from one color
space to another. In case of a transformation to-from RGB color space, the order of the channels should be specified explicitly (RGB or BGR).
......@@ -408,7 +408,7 @@ The function can do the following transformations:
distanceTransform
---------------------
-----------------
Calculates the distance to the closest zero pixel for each pixel of the source image.
.. ocv:function:: void distanceTransform( InputArray src, OutputArray dst, int distanceType, int maskSize )
......@@ -481,7 +481,7 @@ That is, the function provides a very fast way to compute the Voronoi diagram fo
Currently, the second variant can use only the approximate distance transform algorithm, i.e. ``maskSize=CV_DIST_MASK_PRECISE`` is not supported yet.
floodFill
-------------
---------
Fills a connected component with the given color.
.. ocv:function:: int floodFill( InputOutputArray image, Point seedPoint, Scalar newVal, Rect* rect=0, Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), int flags=4 )
......@@ -586,7 +586,7 @@ Use these functions to either mark a connected component with the specified colo
integral
------------
--------
Calculates the integral of an image.
.. ocv:function:: void integral( InputArray src, OutputArray sum, int sdepth=-1 )
......@@ -605,15 +605,15 @@ Calculates the integral of an image.
.. ocv:pyoldfunction:: cv.Integral(image, sum, sqsum=None, tiltedSum=None)-> None
:param image: Source image as :math:`W \times H` , 8-bit or floating-point (32f or 64f).
:param image: input image as :math:`W \times H`, 8-bit or floating-point (32f or 64f).
:param sum: Integral image as :math:`(W+1)\times (H+1)` , 32-bit integer or floating-point (32f or 64f).
:param sum: integral image as :math:`(W+1)\times (H+1)` , 32-bit integer or floating-point (32f or 64f).
:param sqsum: Integral image for squared pixel values. It is :math:`(W+1)\times (H+1)`, double-precision floating-point (64f) array.
:param sqsum: integral image for squared pixel values; it is :math:`(W+1)\times (H+1)`, double-precision floating-point (64f) array.
:param tilted: Integral for the image rotated by 45 degrees. It is :math:`(W+1)\times (H+1)` array with the same data type as ``sum``.
:param tilted: integral for the image rotated by 45 degrees; it is :math:`(W+1)\times (H+1)` array with the same data type as ``sum``.
:param sdepth: Desired depth of the integral and the tilted integral images, ``CV_32S``, ``CV_32F``, or ``CV_64F``.
:param sdepth: desired depth of the integral and the tilted integral images, ``CV_32S``, ``CV_32F``, or ``CV_64F``.
The functions calculate one or more integral images for the source image as follows:
......@@ -646,7 +646,7 @@ As a practical example, the next figure shows the calculation of the integral of
threshold
-------------
---------
Applies a fixed-level threshold to each array element.
.. ocv:function:: double threshold( InputArray src, OutputArray dst, double thresh, double maxval, int type )
......@@ -657,15 +657,15 @@ Applies a fixed-level threshold to each array element.
.. ocv:pyoldfunction:: cv.Threshold(src, dst, threshold, maxValue, thresholdType)-> None
:param src: Source array (single-channel, 8-bit or 32-bit floating point).
:param src: input array (single-channel, 8-bit or 32-bit floating point).
:param dst: Destination array of the same size and type as ``src`` .
:param dst: output array of the same size and type as ``src``.
:param thresh: Threshold value.
:param thresh: treshold value.
:param maxval: Maximum value to use with the ``THRESH_BINARY`` and ``THRESH_BINARY_INV`` thresholding types.
:param maxval: maximum value to use with the ``THRESH_BINARY`` and ``THRESH_BINARY_INV`` thresholding types.
:param type: Thresholding type (see the details below).
:param type: thresholding type (see the details below).
The function applies fixed-level thresholding
to a single-channel array. The function is typically used to get a
......@@ -724,7 +724,7 @@ Currently, the Otsu's method is implemented only for 8-bit images.
watershed
-------------
---------
Performs a marker-based image segmentation using the watershed algorithm.
.. ocv:function:: void watershed( InputArray image, InputOutputArray markers )
......
......@@ -204,11 +204,11 @@ This method must implement matching logic in order to make the wrappers `detail:
.. ocv:function:: void detail::FeaturesMatcher::match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo& matches_info)
:param features1: First image features
:param features1: first image features
:param features2: Second image features
:param features2: second image features
:param matches_info: Found matches
:param matches_info: found matches
detail::BestOf2NearestMatcher
-----------------------------
......
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