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Merge pull request #509 from taka-no-me:fix_docs_master

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Andrey Kamaev 2013-02-20 15:50:47 +04:00 committed by OpenCV Buildbot
commit 0ccdc5b4af
14 changed files with 153 additions and 162 deletions
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10
doc/check_docs2.py
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@ -38,7 +38,7 @@ doc_signatures_whitelist = [
"CvArr", "CvFileStorage",
# other
"InputArray", "OutputArray",
] + ["CvSubdiv2D", "CvQuadEdge2D", "CvSubdiv2DPoint", "cvDrawContours"]
]
defines = ["cvGraphEdgeIdx", "cvFree", "CV_Assert", "cvSqrt", "cvGetGraphVtx", "cvGraphVtxIdx",
"cvCaptureFromFile", "cvCaptureFromCAM", "cvCalcBackProjectPatch", "cvCalcBackProject",
@ -156,9 +156,10 @@ def formatSignature(s):
argtype = re.sub(r"\s+(\*|&)$", "\\1", arg[0])
bidx = argtype.find('[')
if bidx < 0:
_str += argtype + " "
_str += argtype
else:
_srt += argtype[:bidx]
_str += argtype[:bidx]
_str += " "
if arg[1]:
_str += arg[1]
else:
@ -326,6 +327,7 @@ def process_module(module, path):
flookup[fn[0]] = flookup_entry
if do_python_crosscheck:
pyclsnamespaces = ["cv." + x[3:].replace(".", "_") for x in clsnamespaces]
for name, doc in rst.iteritems():
decls = doc.get("decls")
if not decls:
@ -394,7 +396,7 @@ def process_module(module, path):
pname = signature[1][4:signature[1].find('(')]
cvname = "cv." + pname
parent = None
for cl in clsnamespaces:
for cl in pyclsnamespaces:
if cvname.startswith(cl + "."):
if cl.startswith(parent or ""):
parent = cl

2
doc/tutorials/introduction/how_to_write_a_tutorial/how_to_write_a_tutorial.rst
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File diff suppressed because one or more lines are too long

2
modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst
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@ -685,7 +685,7 @@ findEssentialMat
------------------
Calculates an essential matrix from the corresponding points in two images.
.. ocv:function:: Mat findEssentialMat( InputArray points1, InputArray points2, double focal = 1.0, Point2d pp = Point2d(0, 0), int method = FM_RANSAC, double prob = 0.999, double threshold = 1.0, OutputArray mask = noArray() )
.. ocv:function:: Mat findEssentialMat( InputArray points1, InputArray points2, double focal=1.0, Point2d pp=Point2d(0, 0), int method=CV_RANSAC, double prob=0.999, double threshold=1.0, OutputArray mask=noArray() )
:param points1: Array of ``N`` ``(N >= 5)`` 2D points from the first image. The point coordinates should be floating-point (single or double precision).

10
modules/core/doc/command_line_parser.rst
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@ -4,24 +4,24 @@ Command Line Parser
.. highlight:: cpp
CommandLineParser
--------
-----------------
.. ocv:class:: CommandLineParser
The CommandLineParser class is designed for command line arguments parsing
.. ocv:function:: CommandLineParser::CommandLineParser(int argc, const char * const argv[], const std::string keys)
.. ocv:function:: CommandLineParser::CommandLineParser( int argc, const char* const argv[], const string& keys )
:param argc:
:param argv:
:param keys:
.. ocv:function:: T CommandLineParser::get<T>(const std::string& name, bool space_delete = true)
.. ocv:function:: template<typename T> T CommandLineParser::get<T>(const std::string& name, bool space_delete = true)
:param name:
:param space_delete:
.. ocv:function:: T CommandLineParser::get<T>(int index, bool space_delete = true)
.. ocv:function:: template<typename T> T CommandLineParser::get<T>(int index, bool space_delete = true)
:param index:
:param space_delete:
@ -33,7 +33,7 @@ The CommandLineParser class is designed for command line arguments parsing
.. ocv:function:: bool CommandLineParser::check()
.. ocv:function:: void CommandLineParser::about(std::string message)
.. ocv:function:: void CommandLineParser::about( const string& message )
:param message:

2
modules/core/doc/operations_on_arrays.rst
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@ -692,7 +692,7 @@ cvarrToMat
----------
Converts ``CvMat``, ``IplImage`` , or ``CvMatND`` to ``Mat``.
.. ocv:function:: Mat cvarrToMat( const CvArr* arr, bool copyData=false, bool allowND=true, int coiMode=0 )
.. ocv:function:: Mat cvarrToMat( const CvArr* arr, bool copyData=false, bool allowND=true, int coiMode=0, AutoBuffer<double>* buf=0 )
:param arr: input ``CvMat``, ``IplImage`` , or ``CvMatND``.

3
modules/features2d/doc/feature_detection_and_description.rst
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@ -7,7 +7,8 @@ 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 )
.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression=true )
.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression, int type )
:param image: grayscale image where keypoints (corners) are detected.

6
modules/gpu/doc/image_processing.rst
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@ -703,14 +703,10 @@ Calculates histogram for one channel 8-bit image.
.. ocv:function:: void gpu::calcHist(const GpuMat& src, GpuMat& hist, Stream& stream = Stream::Null())
.. ocv:function:: void gpu::calcHist(const GpuMat& src, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null())
:param src: Source image.
:param hist: Destination histogram with one row, 256 columns, and the ``CV_32SC1`` type.
:param buf: Optional buffer to avoid extra memory allocations (for many calls with the same sizes).
:param stream: Stream for the asynchronous version.
@ -721,8 +717,6 @@ Equalizes the histogram of a grayscale image.
.. ocv:function:: void gpu::equalizeHist(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null())
.. ocv:function:: void gpu::equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, Stream& stream = Stream::Null())
.. ocv:function:: void gpu::equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null())
:param src: Source image.

4
modules/gpu/doc/object_detection.rst
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@ -220,10 +220,6 @@ After each weak classifier evaluation, the sample trace at the point :math:`t` i
The sample has been rejected if it fall rejection threshold. So stageless cascade allows to reject not-object sample as soon as possible. Another meaning of the sample trace is a confidence with that sample recognized as desired object. At each :math:`t` that confidence depend on all previous weak classifier. This feature of soft cascade is resulted in more accurate detection. The original formulation of soft cascade can be found in [BJ05]_.
.. [BJ05] Lubomir Bourdev and Jonathan Brandt. tRobust Object Detection Via Soft Cascade. IEEE CVPR, 2005.
.. [BMTG12] Rodrigo Benenson, Markus Mathias, Radu Timofte and Luc Van Gool. Pedestrian detection at 100 frames per second. IEEE CVPR, 2012.
gpu::SCascade
-----------------------------------------------
.. ocv:class:: gpu::SCascade : public Algorithm

4
modules/gpu/include/opencv2/gpu/gpu.hpp
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@ -881,7 +881,7 @@ CV_EXPORTS void HoughCirclesDownload(const GpuMat& d_circles, OutputArray h_circ
//! finds arbitrary template in the grayscale image using Generalized Hough Transform
//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.
class CV_EXPORTS GeneralizedHough_GPU : public Algorithm
class CV_EXPORTS GeneralizedHough_GPU : public cv::Algorithm
{
public:
static Ptr<GeneralizedHough_GPU> create(int method);
@ -1554,7 +1554,7 @@ protected:
};
// Implementation of soft (stage-less) cascaded detector.
class CV_EXPORTS SCascade : public Algorithm
class CV_EXPORTS SCascade : public cv::Algorithm
{
public:

2
modules/java/generator/rst_parser.py
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@ -1,7 +1,7 @@
#/usr/bin/env python
import os, sys, re, string, fnmatch
allmodules = ["core", "flann", "imgproc", "ml", "highgui", "video", "features2d", "calib3d", "objdetect", "legacy", "contrib", "gpu", "androidcamera", "java", "python", "stitching", "ts", "photo", "nonfree", "videostab", "ocl"]
allmodules = ["core", "flann", "imgproc", "ml", "highgui", "video", "features2d", "calib3d", "objdetect", "legacy", "contrib", "gpu", "androidcamera", "java", "python", "stitching", "ts", "photo", "nonfree", "videostab", "ocl", "softcascade"]
verbose = False
show_warnings = True
show_errors = True

74
modules/softcascade/doc/softcascade_detector.rst
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@ -25,37 +25,37 @@ The sample has been rejected if it fall rejection threshold. So stageless cascad
.. [BMTG12] Rodrigo Benenson, Markus Mathias, Radu Timofte and Luc Van Gool. Pedestrian detection at 100 frames per second. IEEE CVPR, 2012.
Detector
-------------------
.. ocv:class:: Detector
softcascade::Detector
---------------------
.. ocv:class:: softcascade::Detector : public Algorithm
Implementation of soft (stageless) cascaded detector. ::
class CV_EXPORTS_W Detector : public Algorithm
class Detector : public Algorithm
{
public:
enum { NO_REJECT = 1, DOLLAR = 2, /*PASCAL = 4,*/ DEFAULT = NO_REJECT};
CV_WRAP Detector(double minScale = 0.4, double maxScale = 5., int scales = 55, int rejCriteria = 1);
CV_WRAP virtual ~Detector();
Detector(double minScale = 0.4, double maxScale = 5., int scales = 55, int rejCriteria = 1);
virtual ~Detector();
cv::AlgorithmInfo* info() const;
CV_WRAP virtual bool load(const FileNode& fileNode);
CV_WRAP virtual void read(const FileNode& fileNode);
virtual bool load(const FileNode& fileNode);
virtual void read(const FileNode& fileNode);
virtual void detect(InputArray image, InputArray rois, std::vector<Detection>& objects) const;
CV_WRAP virtual void detect(InputArray image, InputArray rois, CV_OUT OutputArray rects, CV_OUT OutputArray confs) const;
virtual void detect(InputArray image, InputArray rois, CV_OUT OutputArray rects, CV_OUT OutputArray confs) const;
}
Detector::Detector
softcascade::Detector::Detector
----------------------------------------
An empty cascade will be created.
.. ocv:function:: Detector::Detector(float minScale = 0.4f, float maxScale = 5.f, int scales = 55, int rejCriteria = 1)
.. ocv:function:: softcascade::Detector::Detector( double minScale=0.4, double maxScale=5., int scales=55, int rejCriteria=1 )
.. ocv:pyfunction:: cv2.Detector.Detector(minScale[, maxScale[, scales[, rejCriteria]]]) -> cascade
.. ocv:pyfunction:: cv2.softcascade_Detector([minScale[, maxScale[, scales[, rejCriteria]]]]) -> <softcascade_Detector object>
:param minScale: a minimum scale relative to the original size of the image on which cascade will be applied.
@ -67,35 +67,35 @@ An empty cascade will be created.
Detector::~Detector
softcascade::Detector::~Detector
-----------------------------------------
Destructor for Detector.
.. ocv:function:: Detector::~Detector()
.. ocv:function:: softcascade::Detector::~Detector()
Detector::load
--------------------------
softcascade::Detector::load
---------------------------
Load cascade from FileNode.
.. ocv:function:: bool Detector::load(const FileNode& fileNode)
.. ocv:function:: bool softcascade::Detector::load(const FileNode& fileNode)
.. ocv:pyfunction:: cv2.Detector.load(fileNode)
.. ocv:pyfunction:: cv2.softcascade_Detector.load(fileNode) -> retval
:param fileNode: File node from which the soft cascade are read.
Detector::detect
---------------------------
softcascade::Detector::detect
-----------------------------
Apply cascade to an input frame and return the vector of Detection objects.
.. ocv:function:: void Detector::detect(InputArray image, InputArray rois, std::vector<Detection>& objects) const
.. ocv:function:: void softcascade::Detector::detect(InputArray image, InputArray rois, std::vector<Detection>& objects) const
.. ocv:function:: void Detector::detect(InputArray image, InputArray rois, OutputArray rects, OutputArray confs) const
.. ocv:function:: void softcascade::Detector::detect(InputArray image, InputArray rois, OutputArray rects, OutputArray confs) const
.. ocv:pyfunction:: cv2.Detector.detect(image, rois) -> (rects, confs)
.. ocv:pyfunction:: cv2.softcascade_Detector.detect(image, rois[, rects[, confs]]) -> rects, confs
:param image: a frame on which detector will be applied.
@ -108,37 +108,39 @@ Apply cascade to an input frame and return the vector of Detection objects.
:param confs: an output array of confidence for detected objects. i-th bounding rectangle corresponds i-th confidence.
ChannelFeatureBuilder
---------------------
.. ocv:class:: ChannelFeatureBuilder
softcascade::ChannelFeatureBuilder
----------------------------------
.. ocv:class:: softcascade::ChannelFeatureBuilder : public Algorithm
Public interface for of soft (stageless) cascaded detector. ::
class CV_EXPORTS_W ChannelFeatureBuilder : public Algorithm
class ChannelFeatureBuilder : public Algorithm
{
public:
virtual ~ChannelFeatureBuilder();
CV_WRAP_AS(compute) virtual void operator()(InputArray src, CV_OUT OutputArray channels) const = 0;
virtual void operator()(InputArray src, CV_OUT OutputArray channels) const = 0;
CV_WRAP static cv::Ptr<ChannelFeatureBuilder> create();
static cv::Ptr<ChannelFeatureBuilder> create();
};
ChannelFeatureBuilder:~ChannelFeatureBuilder
--------------------------------------------
softcascade::ChannelFeatureBuilder:~ChannelFeatureBuilder
---------------------------------------------------------
Destructor for ChannelFeatureBuilder.
.. ocv:function:: ChannelFeatureBuilder::~ChannelFeatureBuilder()
.. ocv:function:: softcascade::ChannelFeatureBuilder::~ChannelFeatureBuilder()
.. ocv:pyfunction:: cv2.softcascade_ChannelFeatureBuilder_create() -> retval
ChannelFeatureBuilder::operator()
---------------------------------
softcascade::ChannelFeatureBuilder::operator()
----------------------------------------------
Create channel feature integrals for input image.
.. ocv:function:: void ChannelFeatureBuilder::operator()(InputArray src, OutputArray channels) const
.. ocv:function:: void softcascade::ChannelFeatureBuilder::operator()(InputArray src, OutputArray channels) const
.. ocv:pyfunction:: cv2.ChannelFeatureBuilder.compute(src, channels) -> None
.. ocv:pyfunction:: cv2.softcascade_ChannelFeatureBuilder.compute(src, channels) -> None
:param src source frame

64
modules/softcascade/doc/softcascade_training.rst
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@ -7,13 +7,13 @@ Soft Cascade Detector Training
--------------------------------------------
Octave
-----------------
.. ocv:class:: Octave
softcascade::Octave
-------------------
.. ocv:class:: softcascade::Octave : public Algorithm
Public interface for soft cascade training algorithm. ::
class CV_EXPORTS Octave : public Algorithm
class Octave : public Algorithm
{
public:
@ -37,17 +37,17 @@ Public interface for soft cascade training algorithm. ::
Octave::~Octave
softcascade::Octave::~Octave
---------------------------------------
Destructor for Octave.
.. ocv:function:: Octave::~Octave()
.. ocv:function:: softcascade::Octave::~Octave()
Octave::train
------------------------
softcascade::Octave::train
--------------------------
.. ocv:function:: bool Octave::train(const Dataset* dataset, const FeaturePool* pool, int weaks, int treeDepth)
.. ocv:function:: bool softcascade::Octave::train(const Dataset* dataset, const FeaturePool* pool, int weaks, int treeDepth)
:param dataset an object that allows communicate for training set.
@ -59,19 +59,19 @@ Octave::train
Octave::setRejectThresholds
--------------------------------------
softcascade::Octave::setRejectThresholds
----------------------------------------
.. ocv:function:: void Octave::setRejectThresholds(OutputArray thresholds)
.. ocv:function:: void softcascade::Octave::setRejectThresholds(OutputArray thresholds)
:param thresholds an output array of resulted rejection vector. Have same size as number of trained stages.
Octave::write
------------------------
softcascade::Octave::write
--------------------------
.. ocv:function:: void Octave::train(cv::FileStorage &fs, const FeaturePool* pool, InputArray thresholds) const
.. ocv:function:: void Octave::train( CvFileStorage* fs, string name) const
.. ocv:function:: void softcascade::Octave::train(cv::FileStorage &fs, const FeaturePool* pool, InputArray thresholds) const
.. ocv:function:: void softcascade::Octave::train( CvFileStorage* fs, string name) const
:param fs an output file storage to store trained detector.
@ -82,13 +82,13 @@ Octave::write
:param name a name of root node for trained detector.
FeaturePool
-----------
.. ocv:class:: FeaturePool
softcascade::FeaturePool
------------------------
.. ocv:class:: softcascade::FeaturePool
Public interface for feature pool. This is a hight level abstraction for training random feature pool. ::
class CV_EXPORTS FeaturePool
class FeaturePool
{
public:
@ -99,42 +99,42 @@ Public interface for feature pool. This is a hight level abstraction for trainin
};
FeaturePool::size
-----------------
softcascade::FeaturePool::size
------------------------------
Returns size of feature pool.
.. ocv:function:: int FeaturePool::size() const
.. ocv:function:: int softcascade::FeaturePool::size() const
FeaturePool::~FeaturePool
-------------------------
softcascade::FeaturePool::~FeaturePool
--------------------------------------
FeaturePool destructor.
.. ocv:function:: int FeaturePool::~FeaturePool()
.. ocv:function:: softcascade::FeaturePool::~FeaturePool()
FeaturePool::write
------------------
softcascade::FeaturePool::write
-------------------------------
Write specified feature from feature pool to file storage.
.. ocv:function:: void FeaturePool::write( cv::FileStorage& fs, int index) const
.. ocv:function:: void softcascade::FeaturePool::write( cv::FileStorage& fs, int index) const
:param fs an output file storage to store feature.
:param index an index of feature that should be stored.
FeaturePool::apply
------------------
softcascade::FeaturePool::apply
-------------------------------
Compute feature on integral channel image.
.. ocv:function:: float FeaturePool::apply(int fi, int si, const Mat& channels) const
.. ocv:function:: float softcascade::FeaturePool::apply(int fi, int si, const Mat& channels) const
:param fi an index of feature that should be computed.

46
modules/videostab/doc/global_motion.rst
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@ -7,22 +7,18 @@ The video stabilization module contains a set of functions and classes for globa
videostab::MotionModel
----------------------
Describes motion model between two point clouds.
::
.. ocv:enum:: videostab::MotionModel
enum MotionModel
{
MM_TRANSLATION = 0,
MM_TRANSLATION_AND_SCALE = 1,
MM_ROTATION = 2,
MM_RIGID = 3,
MM_SIMILARITY = 4,
MM_AFFINE = 5,
MM_HOMOGRAPHY = 6,
MM_UNKNOWN = 7
};
.. ocv:emember:: MM_TRANSLATION = 0
.. ocv:emember:: MM_TRANSLATION_AND_SCALE = 1
.. ocv:emember:: MM_ROTATION = 2
.. ocv:emember:: MM_RIGID = 3
.. ocv:emember:: MM_SIMILARITY = 4
.. ocv:emember:: MM_AFFINE = 5
.. ocv:emember:: MM_HOMOGRAPHY = 6
.. ocv:emember:: MM_UNKNOWN = 7
videostab::RansacParams
@ -34,7 +30,7 @@ Describes RANSAC method parameters.
::
struct CV_EXPORTS RansacParams
struct RansacParams
{
int size; // subset size
float thresh; // max error to classify as inlier
@ -87,7 +83,7 @@ videostab::RansacParams::default2dMotion
.. ocv:function:: static RansacParams videostab::RansacParams::default2dMotion(MotionModel model)
:param model: Motion model. See :ocv:class:`videostab::MotionModel`.
:param model: Motion model. See :ocv:enum:`videostab::MotionModel`.
:return: Default RANSAC method parameters for the given motion model.
@ -123,9 +119,9 @@ Estimates best global motion between two 2D point clouds robustly (using RANSAC
:param points1: Destination set of 2D points (``32F``).
:param model: Motion model. See :ocv:class:`videostab::MotionModel`.
:param model: Motion model. See :ocv:enum:`videostab::MotionModel`.
:param params: RANSAC method parameters. See :ocv:class:`videostab::RansacParams`.
:param params: RANSAC method parameters. See :ocv:struct:`videostab::RansacParams`.
:param rmse: Final root-mean-square error.
@ -157,7 +153,7 @@ Base class for all global motion estimation methods.
::
class CV_EXPORTS MotionEstimatorBase
class MotionEstimatorBase
{
public:
virtual ~MotionEstimatorBase();
@ -176,16 +172,16 @@ Sets motion model.
.. ocv:function:: void videostab::MotionEstimatorBase::setMotionModel(MotionModel val)
:param val: Motion model. See :ocv:class:`videostab::MotionModel`.
:param val: Motion model. See :ocv:enum:`videostab::MotionModel`.
videostab::MotionEstimatorBase::motionModel
----------------------------------------------
-------------------------------------------
.. ocv:function:: MotionModel videostab::MotionEstimatorBase::motionModel() const
:return: Motion model. See :ocv:class:`videostab::MotionModel`.
:return: Motion model. See :ocv:enum:`videostab::MotionModel`.
videostab::MotionEstimatorBase::estimate
@ -213,7 +209,7 @@ Describes a robust RANSAC-based global 2D motion estimation method which minimiz
::
class CV_EXPORTS MotionEstimatorRansacL2 : public MotionEstimatorBase
class MotionEstimatorRansacL2 : public MotionEstimatorBase
{
public:
MotionEstimatorRansacL2(MotionModel model = MM_AFFINE);
@ -239,7 +235,7 @@ Describes a global 2D motion estimation method which minimizes L1 error.
::
class CV_EXPORTS MotionEstimatorL1 : public MotionEstimatorBase
class MotionEstimatorL1 : public MotionEstimatorBase
{
public:
MotionEstimatorL1(MotionModel model = MM_AFFINE);
@ -257,7 +253,7 @@ Base class for global 2D motion estimation methods which take frames as input.
::
class CV_EXPORTS ImageMotionEstimatorBase
class ImageMotionEstimatorBase
{
public:
virtual ~ImageMotionEstimatorBase();
@ -278,7 +274,7 @@ Describes a global 2D motion estimation method which uses keypoints detection an
::
class CV_EXPORTS KeypointBasedMotionEstimator : public ImageMotionEstimatorBase
class KeypointBasedMotionEstimator : public ImageMotionEstimatorBase
{
public:
KeypointBasedMotionEstimator(Ptr<MotionEstimatorBase> estimator);