Fix warnings from documentation build
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@ -94,7 +94,7 @@ Code
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* Loads an image
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* Loads an image
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* Convert the original to HSV format and separate only *Hue* channel to be used for the Histogram (using the OpenCV function :mix_channels:`mixChannels <>`)
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* Convert the original to HSV format and separate only *Hue* channel to be used for the Histogram (using the OpenCV function :mix_channels:`mixChannels <>`)
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* Let the user to enter the number of bins to be used in the calculation of the histogram.
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* Let the user to enter the number of bins to be used in the calculation of the histogram.
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* Calculate the histogram (and update it if the bins change) and the backprojection of the same image.
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* Calculate the histogram (and update it if the bins change) and the backprojection of the same image.
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* Display the backprojection and the histogram in windows.
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* Display the backprojection and the histogram in windows.
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* **Downloadable code**:
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* **Downloadable code**:
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File diff suppressed because one or more lines are too long
@ -4,24 +4,24 @@ Command Line Parser
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.. highlight:: cpp
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.. highlight:: cpp
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CommandLineParser
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CommandLineParser
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--------
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-----------------
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.. ocv:class:: CommandLineParser
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.. ocv:class:: CommandLineParser
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The CommandLineParser class is designed for command line arguments parsing
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The CommandLineParser class is designed for command line arguments parsing
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.. ocv:function:: CommandLineParser::CommandLineParser(int argc, const char * const argv[], const std::string keys)
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.. ocv:function:: CommandLineParser::CommandLineParser( int argc, const char* const argv[], const string& keys )
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:param argc:
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:param argc:
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:param argv:
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:param argv:
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:param keys:
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:param keys:
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.. ocv:function:: T CommandLineParser::get<T>(const std::string& name, bool space_delete = true)
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.. ocv:function:: template<typename T> T CommandLineParser::get<T>(const std::string& name, bool space_delete = true)
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:param name:
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:param name:
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:param space_delete:
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:param space_delete:
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.. ocv:function:: T CommandLineParser::get<T>(int index, bool space_delete = true)
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.. ocv:function:: template<typename T> T CommandLineParser::get<T>(int index, bool space_delete = true)
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:param index:
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:param index:
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:param space_delete:
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:param space_delete:
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@ -33,7 +33,7 @@ The CommandLineParser class is designed for command line arguments parsing
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.. ocv:function:: bool CommandLineParser::check()
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.. ocv:function:: bool CommandLineParser::check()
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.. ocv:function:: void CommandLineParser::about(std::string message)
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.. ocv:function:: void CommandLineParser::about( const string& message )
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:param message:
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:param message:
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@ -220,10 +220,6 @@ After each weak classifier evaluation, the sample trace at the point :math:`t` i
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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]_.
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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]_.
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.. [BJ05] Lubomir Bourdev and Jonathan Brandt. tRobust Object Detection Via Soft Cascade. IEEE CVPR, 2005.
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.. [BMTG12] Rodrigo Benenson, Markus Mathias, Radu Timofte and Luc Van Gool. Pedestrian detection at 100 frames per second. IEEE CVPR, 2012.
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gpu::SCascade
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gpu::SCascade
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-----------------------------------------------
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-----------------------------------------------
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.. ocv:class:: gpu::SCascade : public Algorithm
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.. ocv:class:: gpu::SCascade : public Algorithm
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@ -26,8 +26,8 @@ The sample has been rejected if it fall rejection threshold. So stageless cascad
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softcascade::Detector
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softcascade::Detector
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-------------------
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---------------------
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.. ocv:class:: Detector : public Algorithm
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.. ocv:class:: softcascade::Detector : public Algorithm
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Implementation of soft (stageless) cascaded detector. ::
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Implementation of soft (stageless) cascaded detector. ::
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@ -7,22 +7,18 @@ The video stabilization module contains a set of functions and classes for globa
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videostab::MotionModel
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videostab::MotionModel
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----------------------
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----------------------
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Describes motion model between two point clouds.
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Describes motion model between two point clouds.
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::
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.. ocv:enum:: videostab::MotionModel
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enum MotionModel
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.. ocv:emember:: MM_TRANSLATION = 0
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{
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.. ocv:emember:: MM_TRANSLATION_AND_SCALE = 1
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MM_TRANSLATION = 0,
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.. ocv:emember:: MM_ROTATION = 2
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MM_TRANSLATION_AND_SCALE = 1,
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.. ocv:emember:: MM_RIGID = 3
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MM_ROTATION = 2,
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.. ocv:emember:: MM_SIMILARITY = 4
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MM_RIGID = 3,
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.. ocv:emember:: MM_AFFINE = 5
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MM_SIMILARITY = 4,
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.. ocv:emember:: MM_HOMOGRAPHY = 6
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MM_AFFINE = 5,
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.. ocv:emember:: MM_UNKNOWN = 7
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MM_HOMOGRAPHY = 6,
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MM_UNKNOWN = 7
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};
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videostab::RansacParams
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videostab::RansacParams
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@ -34,7 +30,7 @@ Describes RANSAC method parameters.
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::
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::
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struct CV_EXPORTS RansacParams
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struct RansacParams
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{
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{
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int size; // subset size
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int size; // subset size
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float thresh; // max error to classify as inlier
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float thresh; // max error to classify as inlier
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@ -87,7 +83,7 @@ videostab::RansacParams::default2dMotion
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.. ocv:function:: static RansacParams videostab::RansacParams::default2dMotion(MotionModel model)
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.. ocv:function:: static RansacParams videostab::RansacParams::default2dMotion(MotionModel model)
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:param model: Motion model. See :ocv:class:`videostab::MotionModel`.
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:param model: Motion model. See :ocv:enum:`videostab::MotionModel`.
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:return: Default RANSAC method parameters for the given motion model.
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:return: Default RANSAC method parameters for the given motion model.
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@ -123,9 +119,9 @@ Estimates best global motion between two 2D point clouds robustly (using RANSAC
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:param points1: Destination set of 2D points (``32F``).
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:param points1: Destination set of 2D points (``32F``).
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:param model: Motion model. See :ocv:class:`videostab::MotionModel`.
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:param model: Motion model. See :ocv:enum:`videostab::MotionModel`.
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:param params: RANSAC method parameters. See :ocv:class:`videostab::RansacParams`.
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:param params: RANSAC method parameters. See :ocv:struct:`videostab::RansacParams`.
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:param rmse: Final root-mean-square error.
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:param rmse: Final root-mean-square error.
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@ -157,7 +153,7 @@ Base class for all global motion estimation methods.
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::
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::
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class CV_EXPORTS MotionEstimatorBase
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class MotionEstimatorBase
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{
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{
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public:
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public:
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virtual ~MotionEstimatorBase();
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virtual ~MotionEstimatorBase();
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@ -176,16 +172,16 @@ Sets motion model.
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.. ocv:function:: void videostab::MotionEstimatorBase::setMotionModel(MotionModel val)
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.. ocv:function:: void videostab::MotionEstimatorBase::setMotionModel(MotionModel val)
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:param val: Motion model. See :ocv:class:`videostab::MotionModel`.
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:param val: Motion model. See :ocv:enum:`videostab::MotionModel`.
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videostab::MotionEstimatorBase::motionModel
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videostab::MotionEstimatorBase::motionModel
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----------------------------------------------
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-------------------------------------------
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.. ocv:function:: MotionModel videostab::MotionEstimatorBase::motionModel() const
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.. ocv:function:: MotionModel videostab::MotionEstimatorBase::motionModel() const
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:return: Motion model. See :ocv:class:`videostab::MotionModel`.
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:return: Motion model. See :ocv:enum:`videostab::MotionModel`.
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videostab::MotionEstimatorBase::estimate
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videostab::MotionEstimatorBase::estimate
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@ -213,7 +209,7 @@ Describes a robust RANSAC-based global 2D motion estimation method which minimiz
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::
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::
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class CV_EXPORTS MotionEstimatorRansacL2 : public MotionEstimatorBase
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class MotionEstimatorRansacL2 : public MotionEstimatorBase
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{
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{
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public:
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public:
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MotionEstimatorRansacL2(MotionModel model = MM_AFFINE);
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MotionEstimatorRansacL2(MotionModel model = MM_AFFINE);
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@ -239,7 +235,7 @@ Describes a global 2D motion estimation method which minimizes L1 error.
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::
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::
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class CV_EXPORTS MotionEstimatorL1 : public MotionEstimatorBase
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class MotionEstimatorL1 : public MotionEstimatorBase
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{
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{
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public:
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public:
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MotionEstimatorL1(MotionModel model = MM_AFFINE);
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MotionEstimatorL1(MotionModel model = MM_AFFINE);
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@ -257,7 +253,7 @@ Base class for global 2D motion estimation methods which take frames as input.
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::
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::
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class CV_EXPORTS ImageMotionEstimatorBase
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class ImageMotionEstimatorBase
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{
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{
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public:
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public:
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virtual ~ImageMotionEstimatorBase();
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virtual ~ImageMotionEstimatorBase();
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@ -278,7 +274,7 @@ Describes a global 2D motion estimation method which uses keypoints detection an
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::
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::
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class CV_EXPORTS KeypointBasedMotionEstimator : public ImageMotionEstimatorBase
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class KeypointBasedMotionEstimator : public ImageMotionEstimatorBase
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{
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{
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public:
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public:
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KeypointBasedMotionEstimator(Ptr<MotionEstimatorBase> estimator);
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KeypointBasedMotionEstimator(Ptr<MotionEstimatorBase> estimator);
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