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further docs cleanup

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This commit is contained in:
Vadim Pisarevsky
2011-03-08 22:22:24 +00:00
parent 23416e3db5
commit 73f589e8a5
23 changed files with 1175 additions and 1097 deletions
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64
modules/imgproc/doc/feature_detection.rst
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@@ -3,9 +3,11 @@ Feature Detection
.. index:: Canny
.. _Canny:
Canny
---------
.. c:function:: void Canny( const Mat& image, Mat& edges, double threshold1, double threshold2, int apertureSize=3, bool L2gradient=false )
.. c:function:: void Canny( const Mat& image, Mat& edges, double threshold1, double threshold2, int apertureSize=3, bool L2gradient=false )
Finds edges in an image using Canny algorithm.
@@ -26,9 +28,12 @@ http://en.wikipedia.org/wiki/Canny_edge_detector
.. index:: cornerEigenValsAndVecs
.. _cornerEigenValsAndVecs:
cornerEigenValsAndVecs
--------------------------
.. c:function:: void cornerEigenValsAndVecs( const Mat& src, Mat& dst, int blockSize, int apertureSize, int borderType=BORDER_DEFAULT )
----------------------
.. c:function:: void cornerEigenValsAndVecs( const Mat& src, Mat& dst, int blockSize, int apertureSize, int borderType=BORDER_DEFAULT )
Calculates eigenvalues and eigenvectors of image blocks for corner detection.
@@ -67,11 +72,15 @@ The output of the function can be used for robust edge or corner detection.
See also:
:func:`cornerMinEigenVal`,:func:`cornerHarris`,:func:`preCornerDetect`
.. index:: cornerHarris
.. _cornerHarris:
cornerHarris
----------------
.. c:function:: void cornerHarris( const Mat& src, Mat& dst, int blockSize, int apertureSize, double k, int borderType=BORDER_DEFAULT )
------------
.. c:function:: void cornerHarris( const Mat& src, Mat& dst, int blockSize, int apertureSize, double k, int borderType=BORDER_DEFAULT )
Harris edge detector.
@@ -103,9 +112,12 @@ Corners in the image can be found as the local maxima of this response map.
.. index:: cornerMinEigenVal
.. _cornerMinEigenVal:
cornerMinEigenVal
---------------------
.. c:function:: void cornerMinEigenVal( const Mat& src, Mat& dst, int blockSize, int apertureSize=3, int borderType=BORDER_DEFAULT )
-----------------
.. c:function:: void cornerMinEigenVal( const Mat& src, Mat& dst, int blockSize, int apertureSize=3, int borderType=BORDER_DEFAULT )
Calculates the minimal eigenvalue of gradient matrices for corner detection.
@@ -126,9 +138,11 @@ The function is similar to
.. index:: cornerSubPix
.. _cornerSubPix:
cornerSubPix
----------------
.. c:function:: void cornerSubPix( const Mat& image, vector<Point2f>& corners, Size winSize, Size zeroZone, TermCriteria criteria )
.. c:function:: void cornerSubPix( const Mat& image, vector<Point2f>& corners, Size winSize, Size zeroZone, TermCriteria criteria )
Refines the corner locations.
@@ -182,9 +196,12 @@ The algorithm sets the center of the neighborhood window at this new center
.. index:: goodFeaturesToTrack
.. _goodFeaturesToTrack:
goodFeaturesToTrack
-----------------------
.. c:function:: void goodFeaturesToTrack( const Mat& image, vector<Point2f>& corners, int maxCorners, double qualityLevel, double minDistance, const Mat& mask=Mat(), int blockSize=3, bool useHarrisDetector=false, double k=0.04 )
-------------------
.. c:function:: void goodFeaturesToTrack( const Mat& image, vector<Point2f>& corners, int maxCorners, double qualityLevel, double minDistance, const Mat& mask=Mat(), int blockSize=3, bool useHarrisDetector=false, double k=0.04 )
Determines strong corners on an image.
@@ -239,8 +256,11 @@ See also: :func:`cornerMinEigenVal`, :func:`cornerHarris`, :func:`calcOpticalFlo
.. index:: HoughCircles
.. _HoughCircles:
HoughCircles
----------------
------------
.. c:function:: void HoughCircles( Mat& image, vector<Vec3f>& circles, int method, double dp, double minDist, double param1=100, double param2=100, int minRadius=0, int maxRadius=0 )
Finds circles in a grayscale image using a Hough transform.
@@ -300,11 +320,15 @@ Note that usually the function detects the circles' centers well, however it may
See also:
:func:`fitEllipse`,:func:`minEnclosingCircle`
.. index:: HoughLines
.. _HoughLines:
HoughLines
--------------
.. c:function:: void HoughLines( Mat& image, vector<Vec2f>& lines, double rho, double theta, int threshold, double srn=0, double stn=0 )
----------
.. c:function:: void HoughLines( Mat& image, vector<Vec2f>& lines, double rho, double theta, int threshold, double srn=0, double stn=0 )
Finds lines in a binary image using standard Hough transform.
@@ -327,9 +351,12 @@ The function implements standard or standard multi-scale Hough transform algorit
.. index:: HoughLinesP
.. _HoughLinesP:
HoughLinesP
---------------
.. c:function:: void HoughLinesP( Mat& image, vector<Vec4i>& lines, double rho, double theta, int threshold, double minLineLength=0, double maxLineGap=0 )
-----------
.. c:function:: void HoughLinesP( Mat& image, vector<Vec4i>& lines, double rho, double theta, int threshold, double minLineLength=0, double maxLineGap=0 )
Finds lines segments in a binary image using probabilistic Hough transform.
@@ -414,9 +441,12 @@ And this is the output of the above program in the case of probabilistic Hough t
.. index:: preCornerDetect
.. _preCornerDetect:
preCornerDetect
-------------------
.. c:function:: void preCornerDetect( const Mat& src, Mat& dst, int apertureSize, int borderType=BORDER_DEFAULT )
---------------
.. c:function:: void preCornerDetect( const Mat& src, Mat& dst, int apertureSize, int borderType=BORDER_DEFAULT )
Calculates the feature map for corner detection

70
modules/imgproc/doc/geometric_transformations.rst
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@@ -34,19 +34,25 @@ The actual implementations of the geometrical transformations, from the most gen
.. index:: convertMaps
.. _convertMaps:
convertMaps
---------------
.. c:function:: void convertMaps( const Mat\& map1, const Mat\& map2, Mat\& dstmap1, Mat\& dstmap2, int dstmap1type, bool nninterpolation=false )
-----------
.. c:function:: void convertMaps( const Mat& map1, const Mat& map2, Mat& dstmap1, Mat& dstmap2, int dstmap1type, bool nninterpolation=false )
Converts image transformation maps from one representation to another
:param map1: The first input map of type ``CV_16SC2`` or ``CV_32FC1`` or ``CV_32FC2``
:param map2: The second input map of type ``CV_16UC1`` or ``CV_32FC1`` or none (empty matrix), respectively
:param dstmap1: The first output map; will have type ``dstmap1type`` and the same size as ``src``
:param dstmap2: The second output map
:param dstmap1type: The type of the first output map; should be ``CV_16SC2`` , ``CV_32FC1`` or ``CV_32FC2``
:param dstmap1type: The type of the first output map; should be ``CV_16SC2`` , ``CV_32FC1`` or ``CV_32FC2``
:param nninterpolation: Indicates whether the fixed-point maps will be used for nearest-neighbor or for more complex interpolation
The function converts a pair of maps for
@@ -64,8 +70,11 @@ The function converts a pair of maps for
See also:
:func:`remap`,:func:`undisort`,:func:`initUndistortRectifyMap`
.. index:: getAffineTransform
.. _getAffineTransform:
getAffineTransform
----------------------
.. c:function:: Mat getAffineTransform( const Point2f src[], const Point2f dst[] )
@@ -76,8 +85,7 @@ getAffineTransform
:param dst: Coordinates of the corresponding triangle vertices in the destination image
The function calculates the
:math:`2 \times 3` matrix of an affine transform such that:
The function calculates the :math:`2 \times 3` matrix of an affine transform such that:
.. math::
@@ -93,11 +101,15 @@ where
See also:
:func:`warpAffine`,:func:`transform`
.. index:: getPerspectiveTransform
.. _getPerspectiveTransform:
getPerspectiveTransform
---------------------------
.. c:function:: Mat getPerspectiveTransform( const Point2f src[], const Point2f dst[] )
.. c:function:: Mat getPerspectiveTransform( const Point2f src[], const Point2f dst[] )
Calculates the perspective transform from 4 pairs of the corresponding points
@@ -105,8 +117,7 @@ getPerspectiveTransform
:param dst: Coordinates of the corresponding quadrangle vertices in the destination image
The function calculates the
:math:`3 \times 3` matrix of a perspective transform such that:
The function calculates the :math:`3 \times 3` matrix of a perspective transform such that:
.. math::
@@ -122,11 +133,14 @@ where
See also:
:func:`findHomography`,:func:`warpPerspective`,:func:`perspectiveTransform`
.. index:: getRectSubPix
.. getRectSubPix:
getRectSubPix
-----------------
.. c:function:: void getRectSubPix( const Mat\& image, Size patchSize, Point2f center, Mat\& dst, int patchType=-1 )
.. c:function:: void getRectSubPix( const Mat& image, Size patchSize, Point2f center, Mat& dst, int patchType=-1 )
Retrieves the pixel rectangle from an image with sub-pixel accuracy
@@ -156,8 +170,11 @@ the pixel values outside of the image.
See also:
:func:`warpAffine`,:func:`warpPerspective`
.. index:: getRotationMatrix2D
.. _getRotationMatrix2D:
getRotationMatrix2D
-----------------------
.. c:function:: Mat getRotationMatrix2D( Point2f center, double angle, double scale )
@@ -186,11 +203,14 @@ The transformation maps the rotation center to itself. If this is not the purpos
See also:
:func:`getAffineTransform`,:func:`warpAffine`,:func:`transform`
.. index:: invertAffineTransform
.. _invertAffineTransform:
invertAffineTransform
-------------------------
.. c:function:: void invertAffineTransform(const Mat\& M, Mat\& iM)
.. c:function:: void invertAffineTransform(const Mat& M, Mat& iM)
Inverts an affine transformation
@@ -210,18 +230,21 @@ The result will also be a
.. index:: remap
.. _remap:
remap
---------
.. c:function:: void remap( const Mat\& src, Mat\& dst, const Mat\& map1, const Mat\& map2, int interpolation, int borderMode=BORDER_CONSTANT, const Scalar\& borderValue=Scalar())
-----
.. c:function:: void remap( const Mat& src, Mat& dst, const Mat& map1, const Mat& map2, int interpolation, int borderMode=BORDER_CONSTANT, const Scalar& borderValue=Scalar())
Applies a generic geometrical transformation to an image.
:param src: Source image
:param dst: Destination image. It will have the same size as ``map1`` and the same type as ``src``
:param map1: The first map of either ``(x,y)`` points or just ``x`` values having type ``CV_16SC2`` , ``CV_32FC1`` or ``CV_32FC2`` . See :func:`convertMaps` for converting floating point representation to fixed-point for speed.
:param map1: The first map of either ``(x,y)`` points or just ``x`` values having type ``CV_16SC2`` , ``CV_32FC1`` or ``CV_32FC2`` . See :func:`convertMaps` for converting floating point representation to fixed-point for speed.
:param map2: The second map of ``y`` values having type ``CV_16UC1`` , ``CV_32FC1`` or none (empty map if map1 is ``(x,y)`` points), respectively
:param map2: The second map of ``y`` values having type ``CV_16UC1`` , ``CV_32FC1`` or none (empty map if map1 is ``(x,y)`` points), respectively
:param interpolation: The interpolation method, see :func:`resize` . The method ``INTER_AREA`` is not supported by this function
@@ -252,9 +275,12 @@ This function can not operate in-place.
.. index:: resize
.. _resize:
resize
----------
.. c:function:: void resize( const Mat\& src, Mat\& dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR )
.. c:function:: void resize( const Mat& src, Mat& dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR )
Resizes an image
@@ -313,9 +339,11 @@ See also:
.. index:: warpAffine
.. _warpAffine:
warpAffine
--------------
.. c:function:: void warpAffine( const Mat\& src, Mat\& dst, const Mat\& M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar\& borderValue=Scalar())
.. c:function:: void warpAffine( const Mat& src, Mat& dst, const Mat& M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar& borderValue=Scalar())
Applies an affine transformation to an image.
@@ -337,7 +365,7 @@ The function ``warpAffine`` transforms the source image using the specified matr
.. math::
\texttt{dst} (x,y) = \texttt{src} ( \texttt{M} _{11} x + \texttt{M} _{12} y + \texttt{M} _{13}, \texttt{M} _{21} x + \texttt{M} _{22} y + \texttt{M} _{23})
\texttt{dst} (x,y) = \texttt{src} ( \texttt{M} _{11} x + \texttt{M} _{12} y + \texttt{M} _{13}, \texttt{M} _{21} x + \texttt{M} _{22} y + \texttt{M} _{23})
when the flag ``WARP_INVERSE_MAP`` is set. Otherwise, the transformation is first inverted with
:func:`invertAffineTransform` and then put in the formula above instead of ``M`` .
@@ -345,11 +373,14 @@ The function can not operate in-place.
See also:
:func:`warpPerspective`,:func:`resize`,:func:`remap`,:func:`getRectSubPix`,:func:`transform`
.. index:: warpPerspective
.. _warpPerspective:
warpPerspective
-------------------
.. c:function:: void warpPerspective( const Mat\& src, Mat\& dst, const Mat\& M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar\& borderValue=Scalar())
.. c:function:: void warpPerspective( const Mat& src, Mat& dst, const Mat& M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar& borderValue=Scalar())
Applies a perspective transformation to an image.
@@ -378,4 +409,5 @@ when the flag ``WARP_INVERSE_MAP`` is set. Otherwise, the transformation is firs
The function can not operate in-place.
See also:
:func:`warpAffine`,:func:`resize`,:func:`remap`,:func:`getRectSubPix`,:func:`perspectiveTransform`
:func:`warpAffine`,:func:`resize`,:func:`remap`,:func:`getRectSubPix`,:func:`perspectiveTransform`

12
modules/imgproc/doc/histograms.rst
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@@ -3,6 +3,8 @@ Histograms
.. index:: calcHist
.. _calcHist:
calcHist
------------
.. c:function:: void calcHist( const Mat* arrays, int narrays, const int* channels, const Mat\& mask, MatND\& hist, int dims, const int* histSize, const float** ranges, bool uniform=true, bool accumulate=false )
@@ -95,6 +97,8 @@ input arrays. The sample below shows how to compute 2D Hue-Saturation histogram
.. index:: calcBackProject
.. _calcBackProject:
calcBackProject
-------------------
.. c:function:: void calcBackProject( const Mat* arrays, int narrays, const int* channels, const MatND\& hist, Mat\& backProject, const float** ranges, double scale=1, bool uniform=true )
@@ -133,10 +137,14 @@ That is the approximate algorithm of
See also:
:func:`calcHist`
.. index:: compareHist
.. _compareHist:
compareHist
---------------
-----------
.. c:function:: double compareHist( const MatND\& H1, const MatND\& H2, int method )
.. c:function:: double compareHist( const SparseMat\& H1, const SparseMat\& H2, int method )
@@ -199,6 +207,8 @@ While the function works well with 1-, 2-, 3-dimensional dense histograms, it ma
.. index:: equalizeHist
.. _equalizeHist:
equalizeHist
----------------
.. c:function:: void equalizeHist( const Mat\& src, Mat\& dst )

30
modules/imgproc/doc/miscellaneous_transformations.rst
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@@ -3,6 +3,8 @@ Miscellaneous Image Transformations
.. index:: adaptiveThreshold
.. _adaptiveThreshold:
adaptiveThreshold
---------------------
.. c:function:: void adaptiveThreshold( const Mat& src, Mat& dst, double maxValue, int adaptiveMethod, int thresholdType, int blockSize, double C )
@@ -56,8 +58,12 @@ The function can process the image in-place.
See also:
:func:`threshold`,:func:`blur`,:func:`GaussianBlur`
.. index:: cvtColor
.. _cvtColor:
cvtColor
------------
.. c:function:: void cvtColor( const Mat& src, Mat& dst, int code, int dstCn=0 )
@@ -389,6 +395,8 @@ The function can do the following transformations:
.. index:: distanceTransform
.. _distanceTransform:
distanceTransform
---------------------
.. c:function:: void distanceTransform( const Mat& src, Mat& dst, int distanceType, int maskSize )
@@ -457,6 +465,8 @@ Currently, this second variant can only use the approximate distance transform a
.. index:: floodFill
.. _floodFill:
floodFill
-------------
.. c:function:: int floodFill( Mat& image, Point seed, Scalar newVal, Rect* rect=0, Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), int flags=4 )
@@ -540,8 +550,11 @@ By using these functions you can either mark a connected component with the spec
See also:
:func:`findContours`
.. index:: inpaint
.. _inpaint:
inpaint
-----------
.. c:function:: void inpaint( const Mat& src, const Mat& inpaintMask, Mat& dst, double inpaintRadius, int flags )
@@ -568,6 +581,8 @@ for more details.
.. index:: integral
.. _integral:
integral
------------
.. c:function:: void integral( const Mat& image, Mat& sum, int sdepth=-1 )
@@ -620,6 +635,8 @@ As a practical example, the next figure shows the calculation of the integral of
.. index:: threshold
.. _threshold:
threshold
-------------
.. c:function:: double threshold( const Mat& src, Mat& dst, double thresh, double maxVal, int thresholdType )
@@ -684,8 +701,11 @@ Currently, Otsu's method is implemented only for 8-bit images.
See also:
:func:`adaptiveThreshold`,:func:`findContours`,:func:`compare`,:func:`min`,:func:`max`
.. index:: watershed
.. _watershed:
watershed
-------------
.. c:function:: void watershed( const Mat& image, Mat& markers )
@@ -723,10 +743,14 @@ can be found in OpenCV samples directory; see ``watershed.cpp`` demo.
See also:
:func:`findContours`
.. index:: grabCut
.. _grabCut:
grabCut
-----------
-------
.. c:function:: void grabCut(const Mat& image, Mat& mask, Rect rect, Mat& bgdModel, Mat& fgdModel, int iterCount, int mode )
Runs GrabCut algorithm
@@ -756,7 +780,5 @@ grabCut
* **GC_EVAL** The value means that algorithm should just resume.
The function implements the `GrabCut <http://en.wikipedia.org/wiki/GrabCut>`_
image segmentation algorithm.
The function implements the `GrabCut image segmentation algorithm <http://en.wikipedia.org/wiki/GrabCut>`_.
See the sample grabcut.cpp on how to use the function.

5
modules/imgproc/doc/planar_subdivisions.rst
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@@ -1,5 +0,0 @@
Planar Subdivisions
===================
.. highlight:: cpp