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fixed docs

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This commit is contained in:
Konstantin Matskevich 2014-02-05 10:49:56 +04:00
parent b0f617bc01
commit a0ccb46a7f
5 changed files with 42 additions and 42 deletions
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12
modules/core/doc/drawing_functions.rst
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@ -34,7 +34,7 @@ circle
----------
Draws a circle.
.. ocv:function:: void circle( Mat& img, Point center, int radius, const Scalar& color, int thickness=1, int lineType=LINE_8, int shift=0 )
.. ocv:function:: void circle( InputOutputArray img, Point center, int radius, const Scalar& color, int thickness=1, int lineType=LINE_8, int shift=0 )
.. ocv:pyfunction:: cv2.circle(img, center, radius, color[, thickness[, lineType[, shift]]]) -> img
@ -83,9 +83,9 @@ ellipse
-----------
Draws a simple or thick elliptic arc or fills an ellipse sector.
.. ocv:function:: void ellipse( Mat& img, Point center, Size axes, double angle, double startAngle, double endAngle, const Scalar& color, int thickness=1, int lineType=LINE_8, int shift=0 )
.. ocv:function:: void ellipse( InputOutputArray img, Point center, Size axes, double angle, double startAngle, double endAngle, const Scalar& color, int thickness=1, int lineType=LINE_8, int shift=0 )
.. ocv:function:: void ellipse( Mat& img, const RotatedRect& box, const Scalar& color, int thickness=1, int lineType=LINE_8 )
.. ocv:function:: void ellipse( InputOutputArray img, const RotatedRect& box, const Scalar& color, int thickness=1, int lineType=LINE_8 )
.. ocv:pyfunction:: cv2.ellipse(img, center, axes, angle, startAngle, endAngle, color[, thickness[, lineType[, shift]]]) -> img
@ -331,7 +331,7 @@ line
--------
Draws a line segment connecting two points.
.. ocv:function:: void line( Mat& img, Point pt1, Point pt2, const Scalar& color, int thickness=1, int lineType=LINE_8, int shift=0 )
.. ocv:function:: void line( InputOutputArray img, Point pt1, Point pt2, const Scalar& color, int thickness=1, int lineType=LINE_8, int shift=0 )
.. ocv:pyfunction:: cv2.line(img, pt1, pt2, color[, thickness[, lineType[, shift]]]) -> img
@ -417,7 +417,7 @@ rectangle
-------------
Draws a simple, thick, or filled up-right rectangle.
.. ocv:function:: void rectangle( Mat& img, Point pt1, Point pt2, const Scalar& color, int thickness=1, int lineType=LINE_8, int shift=0 )
.. ocv:function:: void rectangle( InputOutputArray img, Point pt1, Point pt2, const Scalar& color, int thickness=1, int lineType=LINE_8, int shift=0 )
.. ocv:function:: void rectangle( Mat& img, Rect rec, const Scalar& color, int thickness=1, int lineType=LINE_8, int shift=0 )
@ -570,7 +570,7 @@ putText
-----------
Draws a text string.
.. ocv:function:: void putText( Mat& img, const String& text, Point org, int fontFace, double fontScale, Scalar color, int thickness=1, int lineType=LINE_8, bool bottomLeftOrigin=false )
.. ocv:function:: void putText( InputOutputArray img, const String& text, Point org, int fontFace, double fontScale, Scalar color, int thickness=1, int lineType=LINE_8, bool bottomLeftOrigin=false )
.. ocv:pyfunction:: cv2.putText(img, text, org, fontFace, fontScale, color[, thickness[, lineType[, bottomLeftOrigin]]]) -> None

12
modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst
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@ -25,10 +25,10 @@ Abstract base class for computing descriptors for image keypoints. ::
public:
virtual ~DescriptorExtractor();
void compute( const Mat& image, vector<KeyPoint>& keypoints,
Mat& descriptors ) const;
void compute( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints,
vector<Mat>& descriptors ) const;
void compute( InputArray image, vector<KeyPoint>& keypoints,
OutputArray descriptors ) const;
void compute( InputArraysOfArrays images, vector<vector<KeyPoint> >& keypoints,
OutputArrayOfArrays descriptors ) const;
virtual void read( const FileNode& );
virtual void write( FileStorage& ) const;
@ -57,9 +57,9 @@ DescriptorExtractor::compute
--------------------------------
Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
.. ocv:function:: void DescriptorExtractor::compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const
.. ocv:function:: void DescriptorExtractor::compute( InputArray image, vector<KeyPoint>& keypoints, OutputArrays descriptors ) const
.. ocv:function:: void DescriptorExtractor::compute( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints, vector<Mat>& descriptors ) const
.. ocv:function:: void DescriptorExtractor::compute( InputArrayOfArrays images, vector<vector<KeyPoint> >& keypoints, OutputArraysOfArrays descriptors ) const
.. ocv:pyfunction:: cv2.DescriptorExtractor_create.compute(image, keypoints[, descriptors]) -> keypoints, descriptors

44
modules/features2d/doc/common_interfaces_of_generic_descriptor_matchers.rst
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@ -29,7 +29,7 @@ Abstract interface for extracting and matching a keypoint descriptor. There are
GenericDescriptorMatcher();
virtual ~GenericDescriptorMatcher();
virtual void add( const vector<Mat>& images,
virtual void add( InputArrayOfArrays images,
vector<vector<KeyPoint> >& keypoints );
const vector<Mat>& getTrainImages() const;
@ -40,36 +40,36 @@ Abstract interface for extracting and matching a keypoint descriptor. There are
virtual bool isMaskSupported() = 0;
void classify( const Mat& queryImage,
void classify( InputArray queryImage,
vector<KeyPoint>& queryKeypoints,
const Mat& trainImage,
vector<KeyPoint>& trainKeypoints ) const;
void classify( const Mat& queryImage,
void classify( InputArray queryImage,
vector<KeyPoint>& queryKeypoints );
/*
* Group of methods to match keypoints from an image pair.
*/
void match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
const Mat& trainImage, vector<KeyPoint>& trainKeypoints,
void match( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
InputArray trainImage, vector<KeyPoint>& trainKeypoints,
vector<DMatch>& matches, const Mat& mask=Mat() ) const;
void knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
const Mat& trainImage, vector<KeyPoint>& trainKeypoints,
void knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
InputArray trainImage, vector<KeyPoint>& trainKeypoints,
vector<vector<DMatch> >& matches, int k,
const Mat& mask=Mat(), bool compactResult=false ) const;
void radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
const Mat& trainImage, vector<KeyPoint>& trainKeypoints,
void radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
InputArray trainImage, vector<KeyPoint>& trainKeypoints,
vector<vector<DMatch> >& matches, float maxDistance,
const Mat& mask=Mat(), bool compactResult=false ) const;
/*
* Group of methods to match keypoints from one image to an image set.
*/
void match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
void match( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() );
void knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
void knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
vector<vector<DMatch> >& matches, int k,
const vector<Mat>& masks=vector<Mat>(), bool compactResult=false );
void radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
void radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
vector<vector<DMatch> >& matches, float maxDistance,
const vector<Mat>& masks=vector<Mat>(), bool compactResult=false );
@ -89,7 +89,7 @@ GenericDescriptorMatcher::add
---------------------------------
Adds images and their keypoints to the training collection stored in the class instance.
.. ocv:function:: void GenericDescriptorMatcher::add( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints )
.. ocv:function:: void GenericDescriptorMatcher::add( InputArrayOfArrays images, vector<vector<KeyPoint> >& keypoints )
:param images: Image collection.
@ -142,9 +142,9 @@ GenericDescriptorMatcher::classify
--------------------------------------
Classifies keypoints from a query set.
.. ocv:function:: void GenericDescriptorMatcher::classify( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints ) const
.. ocv:function:: void GenericDescriptorMatcher::classify( InputArray queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints ) const
.. ocv:function:: void GenericDescriptorMatcher::classify( const Mat& queryImage, vector<KeyPoint>& queryKeypoints )
.. ocv:function:: void GenericDescriptorMatcher::classify( InputArray queryImage, vector<KeyPoint>& queryKeypoints )
:param queryImage: Query image.
@ -170,9 +170,9 @@ GenericDescriptorMatcher::match
-----------------------------------
Finds the best match in the training set for each keypoint from the query set.
.. ocv:function:: void GenericDescriptorMatcher::match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints, vector<DMatch>& matches, const Mat& mask=Mat() ) const
.. ocv:function:: void GenericDescriptorMatcher::match(InputArray queryImage, vector<KeyPoint>& queryKeypoints, InputArray trainImage, vector<KeyPoint>& trainKeypoints, vector<DMatch>& matches, const Mat& mask=Mat() ) const
.. ocv:function:: void GenericDescriptorMatcher::match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() )
.. ocv:function:: void GenericDescriptorMatcher::match( InputArray queryImage, vector<KeyPoint>& queryKeypoints, vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() )
:param queryImage: Query image.
@ -196,9 +196,9 @@ GenericDescriptorMatcher::knnMatch
--------------------------------------
Finds the ``k`` best matches for each query keypoint.
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, int k, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, InputArray trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, int k, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, int k, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, int k, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
The methods are extended variants of ``GenericDescriptorMatch::match``. The parameters are similar, and the semantics is similar to ``DescriptorMatcher::knnMatch``. But this class does not require explicitly computed keypoint descriptors.
@ -208,9 +208,9 @@ GenericDescriptorMatcher::radiusMatch
-----------------------------------------
For each query keypoint, finds the training keypoints not farther than the specified distance.
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const Mat& trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, InputArray trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
The methods are similar to ``DescriptorMatcher::radius``. But this class does not require explicitly computed keypoint descriptors.
@ -254,7 +254,7 @@ Class used for matching descriptors that can be described as vectors in a finite
VectorDescriptorMatcher( const Ptr<DescriptorExtractor>& extractor, const Ptr<DescriptorMatcher>& matcher );
virtual ~VectorDescriptorMatcher();
virtual void add( const vector<Mat>& imgCollection,
virtual void add( InputArrayOfArrays imgCollection,
vector<vector<KeyPoint> >& pointCollection );
virtual void clear();
virtual void train();

6
modules/features2d/doc/drawing_function_of_keypoints_and_matches.rst
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@ -7,9 +7,9 @@ drawMatches
---------------
Draws the found matches of keypoints from two images.
.. ocv:function:: void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1, const Mat& img2, const vector<KeyPoint>& keypoints2, const vector<DMatch>& matches1to2, Mat& outImg, const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), const vector<char>& matchesMask=vector<char>(), int flags=DrawMatchesFlags::DEFAULT )
.. ocv:function:: void drawMatches( InputArray img1, const vector<KeyPoint>& keypoints1, InputArray img2, const vector<KeyPoint>& keypoints2, const vector<DMatch>& matches1to2, InputOutputArray outImg, const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), const vector<char>& matchesMask=vector<char>(), int flags=DrawMatchesFlags::DEFAULT )
.. ocv:function:: void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1, const Mat& img2, const vector<KeyPoint>& keypoints2, const vector<vector<DMatch> >& matches1to2, Mat& outImg, const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), const vector<vector<char> >& matchesMask=vector<vector<char> >(), int flags=DrawMatchesFlags::DEFAULT )
.. ocv:function:: void drawMatches( InputArray img1, const vector<KeyPoint>& keypoints1, InputArray img2, const vector<KeyPoint>& keypoints2, const vector<vector<DMatch> >& matches1to2, InputOutputArray outImg, const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), const vector<vector<char> >& matchesMask=vector<vector<char> >(), int flags=DrawMatchesFlags::DEFAULT )
.. ocv:pyfunction:: cv2.drawMatches(img1, keypoints1, img2, keypoints2, matches1to2[, outImg[, matchColor[, singlePointColor[, matchesMask[, flags]]]]]) -> outImg
@ -69,7 +69,7 @@ drawKeypoints
-----------------
Draws keypoints.
.. ocv:function:: void drawKeypoints( const Mat& image, const vector<KeyPoint>& keypoints, Mat& outImage, const Scalar& color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT )
.. ocv:function:: void drawKeypoints( InputArray image, const vector<KeyPoint>& keypoints, InputOutputArray outImage, const Scalar& color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT )
.. ocv:pyfunction:: cv2.drawKeypoints(image, keypoints[, outImage[, color[, flags]]]) -> outImage

10
modules/features2d/doc/object_categorization.rst
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@ -129,11 +129,11 @@ The class declaration is the following: ::
void setVocabulary( const Mat& vocabulary );
const Mat& getVocabulary() const;
void compute( const Mat& image, vector<KeyPoint>& keypoints,
Mat& imgDescriptor,
void compute( InputArray image, vector<KeyPoint>& keypoints,
InputOutputArray imgDescriptor,
vector<vector<int> >* pointIdxsOfClusters=0,
Mat* descriptors=0 );
void compute( const Mat& descriptors, Mat& imgDescriptor,
void compute( InputArray descriptors, InputOutputArray imgDescriptor,
std::vector<std::vector<int> >* pointIdxsOfClusters=0 );
int descriptorSize() const;
int descriptorType() const;
@ -180,8 +180,8 @@ BOWImgDescriptorExtractor::compute
--------------------------------------
Computes an image descriptor using the set visual vocabulary.
.. ocv:function:: void BOWImgDescriptorExtractor::compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& imgDescriptor, vector<vector<int> >* pointIdxsOfClusters=0, Mat* descriptors=0 )
.. ocv:function:: void BOWImgDescriptorExtractor::compute( const Mat& keypointDescriptors, Mat& imgDescriptor, std::vector<std::vector<int> >* pointIdxsOfClusters=0 )
.. ocv:function:: void BOWImgDescriptorExtractor::compute( InputArray image, vector<KeyPoint>& keypoints, InputOutputArray imgDescriptor, vector<vector<int> >* pointIdxsOfClusters=0, Mat* descriptors=0 )
.. ocv:function:: void BOWImgDescriptorExtractor::compute( InputArray keypointDescriptors, InputOutputArray imgDescriptor, std::vector<std::vector<int> >* pointIdxsOfClusters=0 )
:param image: Image, for which the descriptor is computed.