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introduced new RST/Sphinx domain ocv.

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This commit is contained in:
Vadim Pisarevsky
2011-06-16 12:48:23 +00:00
parent 4f3fb040a4
commit 8d8ef596c8
48 changed files with 2823 additions and 1691 deletions
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54
modules/features2d/doc/feature_detection_and_description.rst
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@@ -7,7 +7,7 @@ Feature Detection and Description
FAST
--------
.. cpp:function:: void FAST( const Mat& image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression=true )
.. ocv:function:: void FAST( const Mat& image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression=true )
Detects corners using the FAST algorithm by E. Rosten (*Machine learning for high-speed corner detection*, 2006).
@@ -25,7 +25,7 @@ FAST
MSER
----
.. cpp:class:: MSER
.. ocv:class:: MSER
Maximally stable extremal region extractor ::
@@ -54,7 +54,7 @@ http://en.wikipedia.org/wiki/Maximally_stable_extremal_regions).
StarDetector
------------
.. cpp:class:: StarDetector
.. ocv:class:: StarDetector
Class implementing the Star keypoint detector ::
@@ -93,7 +93,7 @@ The class implements a modified version of the ``CenSurE`` keypoint detector des
SIFT
----
.. cpp:class:: SIFT
.. ocv:class:: SIFT
Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) approach ::
@@ -183,7 +183,7 @@ Class for extracting keypoints and computing descriptors using the Scale Invaria
SURF
----
.. cpp:class:: SURF
.. ocv:class:: SURF
Class for extracting Speeded Up Robust Features from an image ::
@@ -223,7 +223,7 @@ The algorithm can be used for object tracking and localization, image stitching,
ORB
----
.. cpp:class:: ORB
.. ocv:class:: ORB
Class for extracting ORB features and descriptors from an image ::
@@ -281,7 +281,7 @@ The class implements ORB
RandomizedTree
--------------
.. cpp:class:: RandomizedTree
.. ocv:class:: RandomizedTree
Class containing a base structure for ``RTreeClassifier`` ::
@@ -355,11 +355,11 @@ Class containing a base structure for ``RTreeClassifier`` ::
RandomizedTree::train
-------------------------
.. cpp:function:: void train(std::vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int depth, int views, size_t reduced_num_dim, int num_quant_bits)
.. ocv:function:: void train(std::vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int depth, int views, size_t reduced_num_dim, int num_quant_bits)
Trains a randomized tree using an input set of keypoints.
.. cpp:function:: void train(std::vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int depth, int views, size_t reduced_num_dim, int num_quant_bits)
.. ocv:function:: void train(std::vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int depth, int views, size_t reduced_num_dim, int num_quant_bits)
:param base_set: Vector of the ``BaseKeypoint`` type. It contains image keypoints used for training.
@@ -379,9 +379,9 @@ RandomizedTree::train
RandomizedTree::read
------------------------
.. cpp:function:: read(const char* file_name, int num_quant_bits)
.. ocv:function:: read(const char* file_name, int num_quant_bits)
.. cpp:function:: read(std::istream &is, int num_quant_bits)
.. ocv:function:: read(std::istream &is, int num_quant_bits)
Reads a pre-saved randomized tree from a file or stream.
@@ -395,11 +395,11 @@ RandomizedTree::read
RandomizedTree::write
-------------------------
.. cpp:function:: void write(const char* file_name) const
.. ocv:function:: void write(const char* file_name) const
Writes the current randomized tree to a file or stream.
.. cpp:function:: void write(std::ostream \&os) const
.. ocv:function:: void write(std::ostream \&os) const
:param file_name: Name of the file where randomized tree data is stored.
@@ -409,7 +409,7 @@ RandomizedTree::write
RandomizedTree::applyQuantization
-------------------------------------
.. cpp:function:: void applyQuantization(int num_quant_bits)
.. ocv:function:: void applyQuantization(int num_quant_bits)
Applies quantization to the current randomized tree.
@@ -421,7 +421,7 @@ RandomizedTree::applyQuantization
RTreeNode
---------
.. cpp:class:: RTreeNode
.. ocv:class:: RTreeNode
Class containing a base structure for ``RandomizedTree`` ::
@@ -449,7 +449,7 @@ Class containing a base structure for ``RandomizedTree`` ::
RTreeClassifier
---------------
.. cpp:class:: RTreeClassifier
.. ocv:class:: RTreeClassifier
Class containing ``RTreeClassifier``. It represents the Calonder descriptor that was originally introduced by Michael Calonder. ::
@@ -519,11 +519,11 @@ Class containing ``RTreeClassifier``. It represents the Calonder descriptor that
RTreeClassifier::train
--------------------------
.. cpp:function:: void train(vector<BaseKeypoint> const& base_set, RNG& rng, int num_trees = RTreeClassifier::DEFAULT_TREES, int depth = DEFAULT_DEPTH, int views = DEFAULT_VIEWS, size_t reduced_num_dim = DEFAULT_REDUCED_NUM_DIM, int num_quant_bits = DEFAULT_NUM_QUANT_BITS, bool print_status = true)
.. ocv:function:: void train(vector<BaseKeypoint> const& base_set, RNG& rng, int num_trees = RTreeClassifier::DEFAULT_TREES, int depth = DEFAULT_DEPTH, int views = DEFAULT_VIEWS, size_t reduced_num_dim = DEFAULT_REDUCED_NUM_DIM, int num_quant_bits = DEFAULT_NUM_QUANT_BITS, bool print_status = true)
Trains a randomized tree classifier using an input set of keypoints.
.. cpp:function:: void train(vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int num_trees = RTreeClassifier::DEFAULT_TREES, int depth = DEFAULT_DEPTH, int views = DEFAULT_VIEWS, size_t reduced_num_dim = DEFAULT_REDUCED_NUM_DIM, int num_quant_bits = DEFAULT_NUM_QUANT_BITS, bool print_status = true)
.. ocv:function:: void train(vector<BaseKeypoint> const& base_set, RNG& rng, PatchGenerator& make_patch, int num_trees = RTreeClassifier::DEFAULT_TREES, int depth = DEFAULT_DEPTH, int views = DEFAULT_VIEWS, size_t reduced_num_dim = DEFAULT_REDUCED_NUM_DIM, int num_quant_bits = DEFAULT_NUM_QUANT_BITS, bool print_status = true)
:param base_set: Vector of the ``BaseKeypoint`` type. It contains image keypoints used for training.
@@ -547,11 +547,11 @@ RTreeClassifier::train
RTreeClassifier::getSignature
---------------------------------
.. cpp:function:: void getSignature(IplImage *patch, uchar *sig)
.. ocv:function:: void getSignature(IplImage *patch, uchar *sig)
Returns a signature for an image patch.
.. cpp:function:: void getSignature(IplImage *patch, float *sig)
.. ocv:function:: void getSignature(IplImage *patch, float *sig)
:param patch: Image patch to calculate the signature for.
:param sig: Output signature (array dimension is ``reduced_num_dim)`` .
@@ -561,7 +561,7 @@ RTreeClassifier::getSignature
RTreeClassifier::getSparseSignature
---------------------------------------
.. cpp:function:: void getSparseSignature(IplImage *patch, float *sig, float thresh)
.. ocv:function:: void getSparseSignature(IplImage *patch, float *sig, float thresh)
Returns a signature for an image patch similarly to ``getSignature`` but uses a threshold for removing all signature elements below the threshold so that the signature is compressed.
@@ -575,7 +575,7 @@ RTreeClassifier::getSparseSignature
RTreeClassifier::countNonZeroElements
-----------------------------------------
.. cpp:function:: static int countNonZeroElements(float *vec, int n, double tol=1e-10)
.. ocv:function:: static int countNonZeroElements(float *vec, int n, double tol=1e-10)
Returns the number of non-zero elements in an input array.
@@ -589,11 +589,11 @@ RTreeClassifier::countNonZeroElements
RTreeClassifier::read
-------------------------
.. cpp:function:: read(const char* file_name)
.. ocv:function:: read(const char* file_name)
Reads a pre-saved ``RTreeClassifier`` from a file or stream.
.. cpp:function:: read(std::istream& is)
.. ocv:function:: read(std::istream& is)
:param file_name: Name of the file that contains randomized tree data.
@@ -603,11 +603,11 @@ RTreeClassifier::read
RTreeClassifier::write
--------------------------
.. cpp:function:: void write(const char* file_name) const
.. ocv:function:: void write(const char* file_name) const
Writes the current ``RTreeClassifier`` to a file or stream.
.. cpp:function:: void write(std::ostream &os) const
.. ocv:function:: void write(std::ostream &os) const
:param file_name: Name of the file where randomized tree data is stored.
@@ -617,7 +617,7 @@ RTreeClassifier::write
RTreeClassifier::setQuantization
------------------------------------
.. cpp:function:: void setQuantization(int num_quant_bits)
.. ocv:function:: void setQuantization(int num_quant_bits)
Applies quantization to the current randomized tree.