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提交 bb8198ab 编写于 作者: V Vadim Pisarevsky
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continued cleaning up the docs and fixing hyperlinks (".. index:: <name>" and... 

continued cleaning up the docs and fixing hyperlinks (".. index:: <name>" and ".. _<name>:" are not needed anymore)
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Showing with 574 addition and 1132 deletion
modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst
浏览文件 @ bb8198ab
......@@ -103,8 +103,6 @@ The functions below use the above model to do the following:
.. index:: calibrateCamera
.. _calibrateCamera:
calibrateCamera
---------------
......@@ -186,8 +184,6 @@ See Also:
.. index:: calibrationMatrixValues
.. _calibrationMatrixValues:
calibrationMatrixValues
-----------------------
.. cpp:function:: void calibrationMatrixValues( InputArray cameraMatrix, Size imageSize, double apertureWidth, double apertureHeight, double& fovx, double& fovy, double& focalLength, Point2d& principalPoint, double& aspectRatio )
......@@ -216,8 +212,6 @@ The function computes various useful camera characteristics from the previously
.. index:: composeRT
.. _composeRT:
composeRT
-------------
......@@ -253,8 +247,6 @@ The functions are used inside :ref:`stereoCalibrate` but can also be used in you
.. index:: computeCorrespondEpilines
.. _computeCorrespondEpilines:
computeCorrespondEpilines
-----------------------------
.. cpp:function:: void computeCorrespondEpilines( InputArray points, int whichImage, InputArray F, OutputArray lines )
......@@ -374,8 +366,6 @@ The function is based on
.. index:: drawChessboardCorners
.. _drawChessboardCorners:
drawChessboardCorners
-------------------------
.. cpp:function:: void drawChessboardCorners( InputOutputArray image, Size patternSize, InputArray corners, bool patternWasFound )
......@@ -384,18 +374,16 @@ drawChessboardCorners
:param image: Destination image. It must be an 8-bit color image.
:param patternSize: Number of inner corners per a chessboard row and column. ``(patternSize = cv::Size(points_per_row,points_per_column) = cv::Size(rows,columns) )``
:param patternSize: Number of inner corners per a chessboard row and column ``(patternSize = cv::Size(points_per_row,points_per_column))``
:param corners: Array of detected corners. This should be an output from ``findChessboardCorners`` wrapped in ``cv::Mat()`` .
:param corners: Array of detected corners, the output of ``findChessboardCorners``.
:param patternWasFound: Parameter indicating whether the complete board was found or not. The return value :ref:`FindChessboardCorners` may be passed here.
:param patternWasFound: Parameter indicating whether the complete board was found or not. The return value of :cpp:func:`findChessboardCorners` should be passed here.
The function draws individual chessboard corners detected either as red circles if the board was not found, or as colored corners connected with lines if the board was found.
.. index:: findChessboardCorners
.. _findChessboardCorners:
findChessboardCorners
-------------------------
.. cpp:function:: bool findChessboardCorners( InputArray image, Size patternSize, OutputArray corners, int flags=CV_CALIB_CB_ADAPTIVE_THRESH+CV_CALIB_CB_NORMALIZE_IMAGE )
......@@ -454,8 +442,6 @@ The function requires white space (like a square-thick border, the wider the bet
.. index:: findCirclesGrid
.. _findCirclesGrid:
findCirclesGrid
-------------------
.. cpp:function:: bool findCirclesGrid( InputArray image, Size patternSize, OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID, const Ptr<FeatureDetector> &blobDetector = new SimpleBlobDetector() )
......@@ -501,8 +487,6 @@ The function requires white space (like a square-thick border, the wider the bet
.. index:: solvePnP
.. _solvePnP:
solvePnP
------------
.. cpp:function:: void solvePnP( InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false )
......@@ -528,8 +512,6 @@ The function estimates the object pose given a set of object points, their corre
.. index:: solvePnPRansac
.. _solvePnPRansac:
solvePnPRansac
------------------
......@@ -564,8 +546,6 @@ The function estimates an object pose given a set of object points, their corres
.. index:: findFundamentalMat
.. _findFundamentalMat:
findFundamentalMat
----------------------
.. cpp:function:: Mat findFundamentalMat( InputArray points1, InputArray points2, int method=FM_RANSAC, double param1=3., double param2=0.99, OutputArray mask=noArray() )
......@@ -755,8 +735,6 @@ the optimal new camera matrix based on the free scaling parameter. By varying t
.. index:: initCameraMatrix2D
.. _initCameraMatrix2D:
initCameraMatrix2D
----------------------
.. cpp:function:: Mat initCameraMatrix2D( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, double aspectRatio=1.)
......@@ -776,8 +754,6 @@ Currently, the function only supports planar calibration patterns, which are pat
.. index:: matMulDeriv
.. _matMulDeriv:
matMulDeriv
---------------
......@@ -799,8 +775,6 @@ The function computes partial derivatives of the elements of the matrix product
.. index:: projectPoints
.. _projectPoints:
projectPoints
-----------------
......@@ -843,8 +817,6 @@ By setting ``rvec=tvec=(0,0,0)`` or by setting ``cameraMatrix`` to a 3x3 identi
.. index:: reprojectImageTo3D
.. _reprojectImageTo3D:
reprojectImageTo3D
----------------------
......@@ -903,8 +875,6 @@ that could be used in OpenGL.
.. index:: Rodrigues
.. _Rodrigues:
Rodrigues
-------------
.. cpp:function:: void Rodrigues(InputArray src, OutputArray dst, OutputArray jacobian=noArray())
......@@ -936,8 +906,6 @@ used in the global 3D geometry optimization procedures like
.. index:: StereoBM
.. _StereoBM:
StereoBM
--------
.. c:type:: StereoBM
......@@ -973,8 +941,6 @@ The class is a C++ wrapper for the associated functions. In particular, ``Stereo
.. index:: StereoBM::operator ()
.. _StereoBM::operator ():
StereoBM::operator ()
-----------------------
......@@ -995,8 +961,6 @@ The method executes the BM algorithm on a rectified stereo pair. See the ``stere
.. index:: StereoSGBM
.. _StereoSGBM:
StereoSGBM
----------
......@@ -1042,8 +1006,6 @@ The class implements the modified H. Hirschmuller algorithm HH08 that differs fr
.. index:: StereoSGBM::StereoSGBM
.. _StereoSGBM::StereoSGBM:
StereoSGBM::StereoSGBM
--------------------------
.. cpp:function:: StereoSGBM::StereoSGBM()
......@@ -1076,8 +1038,6 @@ The first constructor initializes ``StereoSGBM`` with all the default parameters
.. index:: StereoSGBM::operator ()
.. _StereoSGBM::operator ():
StereoSGBM::operator ()
-----------------------
......@@ -1099,8 +1059,6 @@ The method is not constant, so you should not use the same ``StereoSGBM`` instan
.. index:: stereoCalibrate
.. _stereoCalibrate:
stereoCalibrate
-------------------
.. cpp:function:: double stereoCalibrate( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, Size imageSize, OutputArray R, OutputArray T, OutputArray E, OutputArray F, TermCriteria term_crit = TermCriteria(TermCriteria::COUNT+ TermCriteria::EPS, 30, 1e-6), int flags=CALIB_FIX_INTRINSIC )
......@@ -1265,8 +1223,6 @@ See below the screenshot from the ``stereo_calib.cpp`` sample. Some red horizont
.. index:: stereoRectifyUncalibrated
.. _stereoRectifyUncalibrated:
stereoRectifyUncalibrated
-----------------------------
.. cpp:function:: bool stereoRectifyUncalibrated( InputArray points1, InputArray points2, InputArray F, Size imgSize, OutputArray H1, OutputArray H2, double threshold=5 )
......
modules/ml/doc/boosting.rst
浏览文件 @ bb8198ab
......@@ -43,21 +43,21 @@ Different variants of boosting are known as Discrete Adaboost, Real AdaBoost, Lo
:math:`m` =
:math:`1,2,...,M` :
##.
#.
Fit the classifier
:math:`f_m(x) \in{-1,1}` , using weights
:math:`w_i` on the training data.
##.
#.
Compute
:math:`err_m = E_w [1_{(y =\neq f_m(x))}], c_m = log((1 - err_m)/err_m)` .
##.
#.
Set
:math:`w_i \Leftarrow w_i exp[c_m 1_{(y_i \neq f_m(x_i))}], i = 1,2,...,N,` and renormalize so that
:math:`\Sigma i w_i = 1` .
##.
#.
Output the classifier sign
:math:`[\Sigma m = 1M c_m f_m(x)]` .
......@@ -153,67 +153,11 @@ In case of LogitBoost and Gentle AdaBoost, each weak predictor is a regression t
.. index:: CvBoost
.. _CvBoost:
CvBoost
-------
.. c:type:: CvBoost
Boosted tree classifier ::
class CvBoost : public CvStatModel
{
public:
// Boosting type
enum { DISCRETE=0, REAL=1, LOGIT=2, GENTLE=3 };
// Splitting criteria
enum { DEFAULT=0, GINI=1, MISCLASS=3, SQERR=4 };
CvBoost();
virtual ~CvBoost();
CvBoost( const Mat& _train_data, int _tflag,
const Mat& _responses, const Mat& _var_idx=0,
const Mat& _sample_idx=0, const Mat& _var_type=0,
const Mat& _missing_mask=0,
CvBoostParams params=CvBoostParams() );
virtual bool train( const Mat& _train_data, int _tflag,
const Mat& _responses, const Mat& _var_idx=0,
const Mat& _sample_idx=0, const Mat& _var_type=0,
const Mat& _missing_mask=0,
CvBoostParams params=CvBoostParams(),
bool update=false );
virtual float predict( const Mat& _sample, const Mat& _missing=0,
Mat& weak_responses=0, CvSlice slice=CV_WHOLE_SEQ,
bool raw_mode=false ) const;
virtual void prune( CvSlice slice );
virtual void clear();
virtual void write( CvFileStorage* storage, const char* name );
virtual void read( CvFileStorage* storage, CvFileNode* node );
CvSeq* get_weak_predictors();
const CvBoostParams& get_params() const;
...
protected:
virtual bool set_params( const CvBoostParams& _params );
virtual void update_weights( CvBoostTree* tree );
virtual void trim_weights();
virtual void write_params( CvFileStorage* fs );
virtual void read_params( CvFileStorage* fs, CvFileNode* node );
CvDTreeTrainData* data;
CvBoostParams params;
CvSeq* weak;
...
};
.. cpp:class:: CvBoost
Boosted tree classifier, derived from :cpp:class:`CvStatModel`
.. index:: CvBoost::train
......
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