return ''
def parse_definition(self, parser):
+ parent_class = self.env.temp_data.get('ocv:parent')
+ if parent_class is None:
+ parser.fail("missing parent structure/class")
return parser.parse_member_object()
def describe_signature(self, signode, obj):
.. ocv:struct:: CvMemStorage
-A storage for various OpenCV dynamic data structures, such as ``CvSeq``, ``CvSet`` etc.
+ A storage for various OpenCV dynamic data structures, such as ``CvSeq``, ``CvSet`` etc.
- .. ocv:member:: CvMemBlock* bottom
+ .. ocv:member:: CvMemBlock* bottom
- the first memory block in the double-linked list of blocks
+ the first memory block in the double-linked list of blocks
- .. ocv:member:: CvMemBlock* top
+ .. ocv:member:: CvMemBlock* top
- the current partially allocated memory block in the list of blocks
+ the current partially allocated memory block in the list of blocks
- .. ocv:member:: CvMemStorage* parent
+ .. ocv:member:: CvMemStorage* parent
- the parent storage (if any) from which the new memory blocks are borrowed.
+ the parent storage (if any) from which the new memory blocks are borrowed.
- .. ocv:member:: int free_space
+ .. ocv:member:: int free_space
- number of free bytes in the ``top`` block
+ number of free bytes in the ``top`` block
- .. ocv:member:: int block_size
+ .. ocv:member:: int block_size
- the total size of the memory blocks
+ the total size of the memory blocks
Memory storage is a low-level structure used to store dynamically growing data structures such as sequences, contours, graphs, subdivisions, etc. It is organized as a list of memory blocks of equal size -
``bottom`` field is the beginning of the list of blocks and ``top`` is the currently used block, but not necessarily the last block of the list. All blocks between ``bottom`` and ``top``, not including the
.. ocv:struct:: CvSeq
-Dynamically growing sequence.
+ Dynamically growing sequence.
- .. ocv:member:: int flags
+ .. ocv:member:: int flags
- sequence flags, including the sequence signature (CV_SEQ_MAGIC_VAL or CV_SET_MAGIC_VAL), type of the elements and some other information about the sequence.
+ sequence flags, including the sequence signature (CV_SEQ_MAGIC_VAL or CV_SET_MAGIC_VAL), type of the elements and some other information about the sequence.
- .. ocv:member:: int header_size
+ .. ocv:member:: int header_size
- size of the sequence header. It should be sizeof(CvSeq) at minimum. See :ocv:cfunc:`CreateSeq`.
+ size of the sequence header. It should be sizeof(CvSeq) at minimum. See :ocv:cfunc:`CreateSeq`.
- .. ocv:member:: CvSeq* h_prev
- .. ocv:member:: CvSeq* h_next
- .. ocv:member:: CvSeq* v_prev
- .. ocv:member:: CvSeq* v_next
+ .. ocv:member:: CvSeq* h_prev
+ .. ocv:member:: CvSeq* h_next
+ .. ocv:member:: CvSeq* v_prev
+ .. ocv:member:: CvSeq* v_next
- pointers to another sequences in a sequence tree. Sequence trees are used to store hierarchical contour structures, retrieved by :ocv:cfunc:`FindContours`
+ pointers to another sequences in a sequence tree. Sequence trees are used to store hierarchical contour structures, retrieved by :ocv:cfunc:`FindContours`
- .. ocv:member:: int total
+ .. ocv:member:: int total
- the number of sequence elements
+ the number of sequence elements
- .. ocv:member:: int elem_size
+ .. ocv:member:: int elem_size
- size of each sequence element in bytes
+ size of each sequence element in bytes
- .. ocv:member:: CvMemStorage* storage
+ .. ocv:member:: CvMemStorage* storage
- memory storage where the sequence resides. It can be a NULL pointer.
+ memory storage where the sequence resides. It can be a NULL pointer.
- .. ocv:member:: CvSeqBlock* first
+ .. ocv:member:: CvSeqBlock* first
- pointer to the first data block
+ pointer to the first data block
The structure ``CvSeq`` is a base for all of OpenCV dynamic data structures.
There are two types of sequences - dense and sparse. The base type for dense
.. ocv:struct:: CvPoint
-2D point with integer coordinates (usually zero-based).
+ 2D point with integer coordinates (usually zero-based).
- .. ocv:member:: int x
+ .. ocv:member:: int x
- x-coordinate
+ x-coordinate
- .. ocv:member:: int y
+ .. ocv:member:: int y
- y-coordinate
+ y-coordinate
.. ocv:cfunction:: CvPoint cvPoint( int x, int y )
.. ocv:struct:: CvPoint2D32f
-2D point with floating-point coordinates.
+ 2D point with floating-point coordinates.
- .. ocv:member:: float x
+ .. ocv:member:: float x
- x-coordinate
+ x-coordinate
- .. ocv:member:: float y
+ .. ocv:member:: float y
- y-coordinate
+ y-coordinate
.. ocv:cfunction:: CvPoint2D32f cvPoint2D32f( double x, double y )
.. ocv:struct:: CvPoint3D32f
-3D point with floating-point coordinates
+ 3D point with floating-point coordinates
- .. ocv:member:: float x
+ .. ocv:member:: float x
- x-coordinate
+ x-coordinate
- .. ocv:member:: float y
+ .. ocv:member:: float y
- y-coordinate
+ y-coordinate
- .. ocv:member:: float z
+ .. ocv:member:: float z
- z-coordinate
+ z-coordinate
.. ocv:cfunction:: CvPoint3D32f cvPoint3D32f( double x, double y, double z )
.. ocv:struct:: CvPoint2D64f
-2D point with double-precision floating-point coordinates.
+ 2D point with double-precision floating-point coordinates.
- .. ocv:member:: double x
+ .. ocv:member:: double x
- x-coordinate
+ x-coordinate
- .. ocv:member:: double y
+ .. ocv:member:: double y
- y-coordinate
+ y-coordinate
.. ocv:cfunction:: CvPoint2D64f cvPoint2D64f( double x, double y )
.. ocv:struct:: CvPoint3D64f
-3D point with double-precision floating-point coordinates.
+ 3D point with double-precision floating-point coordinates.
- .. ocv:member:: double x
+ .. ocv:member:: double x
- x-coordinate
+ x-coordinate
- .. ocv:member:: double y
+ .. ocv:member:: double y
- y-coordinate
+ y-coordinate
- .. ocv:member:: double z
+ .. ocv:member:: double z
.. ocv:cfunction:: CvPoint3D64f cvPoint3D64f( double x, double y, double z )
.. ocv:struct:: CvSize
-Size of a rectangle or an image.
+ Size of a rectangle or an image.
- .. ocv:member:: int width
+ .. ocv:member:: int width
- Width of the rectangle
+ Width of the rectangle
- .. ocv:member:: int height
+ .. ocv:member:: int height
- Height of the rectangle
+ Height of the rectangle
.. ocv:cfunction:: CvSize cvSize( int width, int height )
.. ocv:struct:: CvSize2D32f
-Sub-pixel accurate size of a rectangle.
+ Sub-pixel accurate size of a rectangle.
- .. ocv:member:: float width
+ .. ocv:member:: float width
- Width of the rectangle
+ Width of the rectangle
- .. ocv:member:: float height
+ .. ocv:member:: float height
- Height of the rectangle
+ Height of the rectangle
.. ocv:cfunction:: CvSize2D32f cvSize2D32f( double width, double height )
.. ocv:struct:: CvRect
-Stores coordinates of a rectangle.
+ Stores coordinates of a rectangle.
- .. ocv:member:: int x
+ .. ocv:member:: int x
- x-coordinate of the top-left corner
+ x-coordinate of the top-left corner
- .. ocv:member:: int y
+ .. ocv:member:: int y
- y-coordinate of the top-left corner (sometimes bottom-left corner)
+ y-coordinate of the top-left corner (sometimes bottom-left corner)
- .. ocv:member:: int width
+ .. ocv:member:: int width
- Width of the rectangle
+ Width of the rectangle
- .. ocv:member:: int height
+ .. ocv:member:: int height
- Height of the rectangle
+ Height of the rectangle
.. ocv:cfunction:: CvRect cvRect( int x, int y, int width, int height )
.. ocv:struct:: CvBox2D
-Stores coordinates of a rotated rectangle.
+ Stores coordinates of a rotated rectangle.
- .. ocv:member:: CvPoint2D32f center
+ .. ocv:member:: CvPoint2D32f center
- Center of the box
+ Center of the box
- .. ocv:member:: CvSize2D32f size
+ .. ocv:member:: CvSize2D32f size
- Box width and height
+ Box width and height
- .. ocv:member:: float angle
+ .. ocv:member:: float angle
- Angle between the horizontal axis and the first side (i.e. length) in degrees
+ Angle between the horizontal axis and the first side (i.e. length) in degrees
.. seealso:: :ocv:class:`RotatedRect`
.. ocv:struct:: CvScalar
-A container for 1-,2-,3- or 4-tuples of doubles.
+ A container for 1-,2-,3- or 4-tuples of doubles.
- .. ocv:member:: double[4] val
+ .. ocv:member:: double[4] val
.. ocv::cfunction:: CvScalar cvScalar( double val0, double val1=0, double val2=0, double val3=0 )
.. ocv:struct:: CvTermCriteria
-Termination criteria for iterative algorithms.
+ Termination criteria for iterative algorithms.
- .. ocv:member:: int type
+ .. ocv:member:: int type
- type of the termination criteria, one of:
+ type of the termination criteria, one of:
- * ``CV_TERMCRIT_ITER`` - stop the algorithm after ``max_iter`` iterations at maximum.
+ * ``CV_TERMCRIT_ITER`` - stop the algorithm after ``max_iter`` iterations at maximum.
- * ``CV_TERMCRIT_EPS`` - stop the algorithm after the achieved algorithm-dependent accuracy becomes lower than ``epsilon``.
+ * ``CV_TERMCRIT_EPS`` - stop the algorithm after the achieved algorithm-dependent accuracy becomes lower than ``epsilon``.
- * ``CV_TERMCRIT_ITER+CV_TERMCRIT_EPS`` - stop the algorithm after ``max_iter`` iterations or when the achieved accuracy is lower than ``epsilon``, whichever comes the earliest.
+ * ``CV_TERMCRIT_ITER+CV_TERMCRIT_EPS`` - stop the algorithm after ``max_iter`` iterations or when the achieved accuracy is lower than ``epsilon``, whichever comes the earliest.
- .. ocv:member:: int max_iter
+ .. ocv:member:: int max_iter
- Maximum number of iterations
+ Maximum number of iterations
- .. ocv:member:: double epsilon
+ .. ocv:member:: double epsilon
- Required accuracy
+ Required accuracy
.. seealso:: :ocv:class:`TermCriteria`
.. ocv:struct:: CvMat
-A multi-channel dense matrix.
+ A multi-channel dense matrix.
- .. ocv:member:: int type
+ .. ocv:member:: int type
- ``CvMat`` signature (``CV_MAT_MAGIC_VAL``) plus type of the elements. Type of the matrix elements can be retrieved using ``CV_MAT_TYPE`` macro: ::
+ ``CvMat`` signature (``CV_MAT_MAGIC_VAL``) plus type of the elements. Type of the matrix elements can be retrieved using ``CV_MAT_TYPE`` macro: ::
- int type = CV_MAT_TYPE(matrix->type);
+ int type = CV_MAT_TYPE(matrix->type);
- For description of possible matrix elements, see :ocv:class:`Mat`.
+ For description of possible matrix elements, see :ocv:class:`Mat`.
- .. ocv:member:: int step
+ .. ocv:member:: int step
- Full row length in bytes
+ Full row length in bytes
- .. ocv:member:: int* refcount
+ .. ocv:member:: int* refcount
- Underlying data reference counter
+ Underlying data reference counter
- .. ocv:member:: union data
+ .. ocv:member:: union data
- Pointers to the actual matrix data:
+ Pointers to the actual matrix data:
- * ptr - pointer to 8-bit unsigned elements
- * s - pointer to 16-bit signed elements
- * i - pointer to 32-bit signed elements
- * fl - pointer to 32-bit floating-point elements
- * db - pointer to 64-bit floating-point elements
+ * ptr - pointer to 8-bit unsigned elements
+ * s - pointer to 16-bit signed elements
+ * i - pointer to 32-bit signed elements
+ * fl - pointer to 32-bit floating-point elements
+ * db - pointer to 64-bit floating-point elements
- .. ocv:member:: int rows
+ .. ocv:member:: int rows
- Number of rows
+ Number of rows
- .. ocv:member:: int cols
+ .. ocv:member:: int cols
- Number of columns
+ Number of columns
Matrix elements are stored row by row. Element (i, j) (i - 0-based row index, j - 0-based column index) of a matrix can be retrieved or modified using ``CV_MAT_ELEM`` macro: ::
.. ocv:struct:: CvMatND
-Multi-dimensional dense multi-channel array.
+ Multi-dimensional dense multi-channel array.
- .. ocv:member:: int type
+ .. ocv:member:: int type
- A ``CvMatND`` signature (``CV_MATND_MAGIC_VAL``) plus the type of elements. Type of the matrix elements can be retrieved using ``CV_MAT_TYPE`` macro: ::
+ A ``CvMatND`` signature (``CV_MATND_MAGIC_VAL``) plus the type of elements. Type of the matrix elements can be retrieved using ``CV_MAT_TYPE`` macro: ::
- int type = CV_MAT_TYPE(ndmatrix->type);
+ int type = CV_MAT_TYPE(ndmatrix->type);
- .. ocv:member:: int dims
+ .. ocv:member:: int dims
- The number of array dimensions
+ The number of array dimensions
- .. ocv:member:: int* refcount
+ .. ocv:member:: int* refcount
- Underlying data reference counter
+ Underlying data reference counter
- .. ocv:member:: union data
+ .. ocv:member:: union data
- Pointers to the actual matrix data
+ Pointers to the actual matrix data
- * ptr - pointer to 8-bit unsigned elements
- * s - pointer to 16-bit signed elements
- * i - pointer to 32-bit signed elements
- * fl - pointer to 32-bit floating-point elements
- * db - pointer to 64-bit floating-point elements
+ * ptr - pointer to 8-bit unsigned elements
+ * s - pointer to 16-bit signed elements
+ * i - pointer to 32-bit signed elements
+ * fl - pointer to 32-bit floating-point elements
+ * db - pointer to 64-bit floating-point elements
- .. ocv:member:: array dim
+ .. ocv:member:: array dim
- Arrays of pairs (array size along the i-th dimension, distance between neighbor elements along i-th dimension): ::
+ Arrays of pairs (array size along the i-th dimension, distance between neighbor elements along i-th dimension): ::
- for(int i = 0; i < ndmatrix->dims; i++)
- printf("size[i] = %d, step[i] = %d\n", ndmatrix->dim[i].size, ndmatrix->dim[i].step);
+ for(int i = 0; i < ndmatrix->dims; i++)
+ printf("size[i] = %d, step[i] = %d\n", ndmatrix->dim[i].size, ndmatrix->dim[i].step);
``CvMatND`` is now obsolete; consider using :ocv:class:`Mat` instead.
.. ocv:struct:: CvSparseMat
-Multi-dimensional sparse multi-channel array.
+ Multi-dimensional sparse multi-channel array.
- .. ocv:member:: int type
+ .. ocv:member:: int type
- A ``CvSparseMat`` signature (CV_SPARSE_MAT_MAGIC_VAL) plus the type of sparse matrix elements. Similarly to ``CvMat`` and ``CvMatND``, use ``CV_MAT_TYPE()`` to retrieve type of the elements.
+ A ``CvSparseMat`` signature (CV_SPARSE_MAT_MAGIC_VAL) plus the type of sparse matrix elements. Similarly to ``CvMat`` and ``CvMatND``, use ``CV_MAT_TYPE()`` to retrieve type of the elements.
- .. ocv:member:: int dims
+ .. ocv:member:: int dims
- Number of dimensions
+ Number of dimensions
- .. ocv:member:: int* refcount
+ .. ocv:member:: int* refcount
- Underlying reference counter. Not used.
+ Underlying reference counter. Not used.
- .. ocv:member:: CvSet* heap
+ .. ocv:member:: CvSet* heap
- A pool of hash table nodes
+ A pool of hash table nodes
- .. ocv:member:: void** hashtable
+ .. ocv:member:: void** hashtable
- The hash table. Each entry is a list of nodes.
+ The hash table. Each entry is a list of nodes.
- .. ocv:member:: int hashsize
+ .. ocv:member:: int hashsize
- Size of the hash table
+ Size of the hash table
- .. ocv:member:: int[] size
+ .. ocv:member:: int[] size
- Array of dimension sizes
+ Array of dimension sizes
IplImage
--------
.. ocv:struct:: IplImage
-IPL image header
+ IPL image header
- .. ocv:member:: int nSize
+ .. ocv:member:: int nSize
- ``sizeof(IplImage)``
+ ``sizeof(IplImage)``
- .. ocv:member:: int ID
+ .. ocv:member:: int ID
- Version, always equals 0
+ Version, always equals 0
- .. ocv:member:: int nChannels
+ .. ocv:member:: int nChannels
- Number of channels. Most OpenCV functions support 1-4 channels.
+ Number of channels. Most OpenCV functions support 1-4 channels.
- .. ocv:member:: int alphaChannel
+ .. ocv:member:: int alphaChannel
- Ignored by OpenCV
+ Ignored by OpenCV
- .. ocv:member:: int depth
+ .. ocv:member:: int depth
- Channel depth in bits + the optional sign bit ( ``IPL_DEPTH_SIGN`` ). The supported depths are:
+ Channel depth in bits + the optional sign bit ( ``IPL_DEPTH_SIGN`` ). The supported depths are:
- * ``IPL_DEPTH_8U`` - unsigned 8-bit integer. Equivalent to ``CV_8U`` in matrix types.
- * ``IPL_DEPTH_8S`` - signed 8-bit integer. Equivalent to ``CV_8S`` in matrix types.
- * ``IPL_DEPTH_16U`` - unsigned 16-bit integer. Equivalent to ``CV_16U`` in matrix types.
- * ``IPL_DEPTH_16S`` - signed 8-bit integer. Equivalent to ``CV_16S`` in matrix types.
- * ``IPL_DEPTH_32S`` - signed 32-bit integer. Equivalent to ``CV_32S`` in matrix types.
- * ``IPL_DEPTH_32F`` - single-precision floating-point number. Equivalent to ``CV_32F`` in matrix types.
- * ``IPL_DEPTH_64F`` - double-precision floating-point number. Equivalent to ``CV_64F`` in matrix types.
+ * ``IPL_DEPTH_8U`` - unsigned 8-bit integer. Equivalent to ``CV_8U`` in matrix types.
+ * ``IPL_DEPTH_8S`` - signed 8-bit integer. Equivalent to ``CV_8S`` in matrix types.
+ * ``IPL_DEPTH_16U`` - unsigned 16-bit integer. Equivalent to ``CV_16U`` in matrix types.
+ * ``IPL_DEPTH_16S`` - signed 8-bit integer. Equivalent to ``CV_16S`` in matrix types.
+ * ``IPL_DEPTH_32S`` - signed 32-bit integer. Equivalent to ``CV_32S`` in matrix types.
+ * ``IPL_DEPTH_32F`` - single-precision floating-point number. Equivalent to ``CV_32F`` in matrix types.
+ * ``IPL_DEPTH_64F`` - double-precision floating-point number. Equivalent to ``CV_64F`` in matrix types.
- .. ocv:member:: char[] colorModel
+ .. ocv:member:: char[] colorModel
- Ignored by OpenCV.
+ Ignored by OpenCV.
- .. ocv:member:: char[] channelSeq
+ .. ocv:member:: char[] channelSeq
- Ignored by OpenCV
+ Ignored by OpenCV
- .. ocv:member:: int dataOrder
+ .. ocv:member:: int dataOrder
- 0 = ``IPL_DATA_ORDER_PIXEL`` - interleaved color channels, 1 - separate color channels. :ocv:cfunc:`CreateImage` only creates images with interleaved channels. For example, the usual layout of a color image is: :math:`b_{00} g_{00} r_{00} b_{10} g_{10} r_{10} ...`
+ 0 = ``IPL_DATA_ORDER_PIXEL`` - interleaved color channels, 1 - separate color channels. :ocv:cfunc:`CreateImage` only creates images with interleaved channels. For example, the usual layout of a color image is: :math:`b_{00} g_{00} r_{00} b_{10} g_{10} r_{10} ...`
- .. ocv:member:: int origin
+ .. ocv:member:: int origin
- 0 - top-left origin, 1 - bottom-left origin (Windows bitmap style)
+ 0 - top-left origin, 1 - bottom-left origin (Windows bitmap style)
- .. ocv:member:: int align
+ .. ocv:member:: int align
- Alignment of image rows (4 or 8). OpenCV ignores this and uses widthStep instead.
+ Alignment of image rows (4 or 8). OpenCV ignores this and uses widthStep instead.
- .. ocv:member:: int width
+ .. ocv:member:: int width
- Image width in pixels
+ Image width in pixels
- .. ocv:member:: int height
+ .. ocv:member:: int height
- Image height in pixels
+ Image height in pixels
- .. ocv:member:: IplROI* roi
+ .. ocv:member:: IplROI* roi
- Region Of Interest (ROI). If not NULL, only this image region will be processed.
+ Region Of Interest (ROI). If not NULL, only this image region will be processed.
- .. ocv:member:: IplImage* maskROI
+ .. ocv:member:: IplImage* maskROI
- Must be NULL in OpenCV
+ Must be NULL in OpenCV
- .. ocv:member:: void* imageId
+ .. ocv:member:: void* imageId
- Must be NULL in OpenCV
+ Must be NULL in OpenCV
- .. ocv:member:: void* tileInfo
+ .. ocv:member:: void* tileInfo
- Must be NULL in OpenCV
+ Must be NULL in OpenCV
- .. ocv:member:: int imageSize
+ .. ocv:member:: int imageSize
- Image data size in bytes. For interleaved data, this equals :math:`\texttt{image->height} \cdot \texttt{image->widthStep}`
+ Image data size in bytes. For interleaved data, this equals :math:`\texttt{image->height} \cdot \texttt{image->widthStep}`
- .. ocv:member:: char* imageData
+ .. ocv:member:: char* imageData
- A pointer to the aligned image data. Do not assign imageData directly. Use :ocv:cfunc:`SetData`.
+ A pointer to the aligned image data. Do not assign imageData directly. Use :ocv:cfunc:`SetData`.
- .. ocv:member:: int widthStep
+ .. ocv:member:: int widthStep
- The size of an aligned image row, in bytes.
+ The size of an aligned image row, in bytes.
- .. ocv:member:: int[] BorderMode
+ .. ocv:member:: int[] BorderMode
- Border completion mode, ignored by OpenCV
+ Border completion mode, ignored by OpenCV
- .. ocv:member:: int[] BorderConst
+ .. ocv:member:: int[] BorderConst
- Constant border value, ignored by OpenCV
+ Constant border value, ignored by OpenCV
- .. ocv:member:: char* imageDataOrigin
+ .. ocv:member:: char* imageDataOrigin
- A pointer to the origin of the image data (not necessarily aligned). This is used for image deallocation.
+ A pointer to the origin of the image data (not necessarily aligned). This is used for image deallocation.
The ``IplImage`` is taken from the Intel Image Processing Library, in which the format is native. OpenCV only supports a subset of possible ``IplImage`` formats, as outlined in the parameter list above.
.. ocv:struct:: CvFileNode
-File storage node. When XML/YAML file is read, it is first parsed and stored in the memory as a hierarchical collection of nodes. Each node can be a "leaf", that is, contain a single number or a string, or be a collection of other nodes. Collections are also referenced to as "structures" in the data writing functions. There can be named collections (mappings), where each element has a name and is accessed by a name, and ordered collections (sequences), where elements do not have names, but rather accessed by index.
+ File storage node. When XML/YAML file is read, it is first parsed and stored in the memory as a hierarchical collection of nodes. Each node can be a "leaf", that is, contain a single number or a string, or be a collection of other nodes. Collections are also referenced to as "structures" in the data writing functions. There can be named collections (mappings), where each element has a name and is accessed by a name, and ordered collections (sequences), where elements do not have names, but rather accessed by index.
- .. ocv:member:: int tag
+ .. ocv:member:: int tag
- type of the file node:
+ type of the file node:
- * CV_NODE_NONE - empty node
- * CV_NODE_INT - an integer
- * CV_NODE_REAL - a floating-point number
- * CV_NODE_STR - text string
- * CV_NODE_SEQ - a sequence
- * CV_NODE_MAP - a mapping
+ * CV_NODE_NONE - empty node
+ * CV_NODE_INT - an integer
+ * CV_NODE_REAL - a floating-point number
+ * CV_NODE_STR - text string
+ * CV_NODE_SEQ - a sequence
+ * CV_NODE_MAP - a mapping
- type of the node can be retrieved using ``CV_NODE_TYPE(node->tag)`` macro.
+ type of the node can be retrieved using ``CV_NODE_TYPE(node->tag)`` macro.
- .. ocv:member:: CvTypeInfo* info
+ .. ocv:member:: CvTypeInfo* info
- optional pointer to the user type information. If you look at the matrix representation in XML and YAML, shown above, you may notice ``type_id="opencv-matrix"`` or ``!!opencv-matrix`` strings. They are used to specify that the certain element of a file is a representation of a data structure of certain type ("opencv-matrix" corresponds to :ocv:struct:`CvMat`). When a file is parsed, such type identifiers are passed to :ocv:cfunc:`FindType` to find type information and the pointer to it is stored in the file node. See :ocv:struct:`CvTypeInfo` for more details.
+ optional pointer to the user type information. If you look at the matrix representation in XML and YAML, shown above, you may notice ``type_id="opencv-matrix"`` or ``!!opencv-matrix`` strings. They are used to specify that the certain element of a file is a representation of a data structure of certain type ("opencv-matrix" corresponds to :ocv:struct:`CvMat`). When a file is parsed, such type identifiers are passed to :ocv:cfunc:`FindType` to find type information and the pointer to it is stored in the file node. See :ocv:struct:`CvTypeInfo` for more details.
- .. ocv:member:: union data
+ .. ocv:member:: union data
- the node data, declared as: ::
+ the node data, declared as: ::
- union
- {
- double f; /* scalar floating-point number */
- int i; /* scalar integer number */
- CvString str; /* text string */
- CvSeq* seq; /* sequence (ordered collection of file nodes) */
- struct CvMap* map; /* map (collection of named file nodes) */
- } data;
+ union
+ {
+ double f; /* scalar floating-point number */
+ int i; /* scalar integer number */
+ CvString str; /* text string */
+ CvSeq* seq; /* sequence (ordered collection of file nodes) */
+ struct CvMap* map; /* map (collection of named file nodes) */
+ } data;
- ..
+ ..
- Primitive nodes are read using :ocv:cfunc:`ReadInt`, :ocv:cfunc:`ReadReal` and :ocv:cfunc:`ReadString`. Sequences are read by iterating through ``node->data.seq`` (see "Dynamic Data Structures" section). Mappings are read using :ocv:cfunc:`GetFileNodeByName`. Nodes with the specified type (so that ``node->info != NULL``) can be read using :ocv:cfunc:`Read`.
+ Primitive nodes are read using :ocv:cfunc:`ReadInt`, :ocv:cfunc:`ReadReal` and :ocv:cfunc:`ReadString`. Sequences are read by iterating through ``node->data.seq`` (see "Dynamic Data Structures" section). Mappings are read using :ocv:cfunc:`GetFileNodeByName`. Nodes with the specified type (so that ``node->info != NULL``) can be read using :ocv:cfunc:`Read`.
CvAttrList
----------
BFMatcher
-----------------
-.. ocv:class::BFMatcher : public DescriptorMatcher
+.. ocv:class:: BFMatcher : public DescriptorMatcher
Brute-force descriptor matcher. For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one. This descriptor matcher supports masking permissible matches of descriptor sets.
--------
.. ocv:class:: KeyPoint
-Data structure for salient point detectors.
+ Data structure for salient point detectors.
- .. ocv:member:: Point2f pt
+ .. ocv:member:: Point2f pt
- coordinates of the keypoint
+ coordinates of the keypoint
- .. ocv:member:: float size
+ .. ocv:member:: float size
- diameter of the meaningful keypoint neighborhood
+ diameter of the meaningful keypoint neighborhood
- .. ocv:member:: float angle
+ .. ocv:member:: float angle
- computed orientation of the keypoint (-1 if not applicable)
+ computed orientation of the keypoint (-1 if not applicable)
- .. ocv:member:: float response
+ .. ocv:member:: float response
- the response by which the most strong keypoints have been selected. Can be used for further sorting or subsampling
+ the response by which the most strong keypoints have been selected. Can be used for further sorting or subsampling
- .. ocv:member:: int octave
+ .. ocv:member:: int octave
- octave (pyramid layer) from which the keypoint has been extracted
+ octave (pyramid layer) from which the keypoint has been extracted
- .. ocv:member:: int class_id
+ .. ocv:member:: int class_id
- object id that can be used to clustered keypoints by an object they belong to
+ object id that can be used to clustered keypoints by an object they belong to
KeyPoint::KeyPoint
------------------
:param ccorr: Flags to evaluate cross-correlation instead of convolution.
- :param buf: Optional buffer to avoid extra memory allocations and to adjust some specific parameters. See :ocv:class:`gpu::ConvolveBuf`.
+ :param buf: Optional buffer to avoid extra memory allocations and to adjust some specific parameters. See :ocv:struct:`gpu::ConvolveBuf`.
:param stream: Stream for the asynchronous version.
:param method: Specifies the way to compare the template with the image.
- :param buf: Optional buffer to avoid extra memory allocations and to adjust some specific parameters. See :ocv:class:`gpu::MatchTemplateBuf`.
+ :param buf: Optional buffer to avoid extra memory allocations and to adjust some specific parameters. See :ocv:struct:`gpu::MatchTemplateBuf`.
:param stream: Stream for the asynchronous version.
Boosting training parameters.
+ There is one structure member that you can set directly:
+
+ .. ocv:member:: int split_criteria
+
+ Splitting criteria used to choose optimal splits during a weak tree construction. Possible values are:
+
+ * **CvBoost::DEFAULT** Use the default for the particular boosting method, see below.
+ * **CvBoost::GINI** Use Gini index. This is default option for Real AdaBoost; may be also used for Discrete AdaBoost.
+ * **CvBoost::MISCLASS** Use misclassification rate. This is default option for Discrete AdaBoost; may be also used for Real AdaBoost.
+ * **CvBoost::SQERR** Use least squares criteria. This is default and the only option for LogitBoost and Gentle AdaBoost.
+
The structure is derived from :ocv:class:`CvDTreeParams` but not all of the decision tree parameters are supported. In particular, cross-validation is not supported.
All parameters are public. You can initialize them by a constructor and then override some of them directly if you want.
See :ocv:func:`CvDTreeParams::CvDTreeParams` for description of other parameters.
-Also there is one structure member that you can set directly:
-
-.. ocv:member:: int split_criteria
-
- Splitting criteria used to choose optimal splits during a weak tree construction. Possible values are:
-
- * **CvBoost::DEFAULT** Use the default for the particular boosting method, see below.
- * **CvBoost::GINI** Use Gini index. This is default option for Real AdaBoost; may be also used for Discrete AdaBoost.
- * **CvBoost::MISCLASS** Use misclassification rate. This is default option for Discrete AdaBoost; may be also used for Real AdaBoost.
- * **CvBoost::SQERR** Use least squares criteria. This is default and the only option for LogitBoost and Gentle AdaBoost.
-
Default parameters are:
::
.. ocv:struct:: CvDTreeSplit
-The structure represents a possible decision tree node split. It has public members:
+ The structure represents a possible decision tree node split. It has public members:
-.. ocv:member:: int var_idx
+ .. ocv:member:: int var_idx
- Index of variable on which the split is created.
+ Index of variable on which the split is created.
-.. ocv:member:: int inversed
+ .. ocv:member:: int inversed
- If it is not null then inverse split rule is used that is left and right branches are exchanged in the rule expressions below.
+ If it is not null then inverse split rule is used that is left and right branches are exchanged in the rule expressions below.
-.. ocv:member:: float quality
+ .. ocv:member:: float quality
- The split quality, a positive number. It is used to choose the best primary split, then to choose and sort the surrogate splits. After the tree is constructed, it is also used to compute variable importance.
+ The split quality, a positive number. It is used to choose the best primary split, then to choose and sort the surrogate splits. After the tree is constructed, it is also used to compute variable importance.
-.. ocv:member:: CvDTreeSplit* next
+ .. ocv:member:: CvDTreeSplit* next
- Pointer to the next split in the node list of splits.
+ Pointer to the next split in the node list of splits.
-.. ocv:member:: int[] subset
+ .. ocv:member:: int[] subset
- Bit array indicating the value subset in case of split on a categorical variable. The rule is: ::
+ Bit array indicating the value subset in case of split on a categorical variable. The rule is: ::
if var_value in subset
then next_node <- left
else next_node <- right
-.. ocv:member:: float ord::c
+ .. ocv:member:: float ord::c
- The threshold value in case of split on an ordered variable. The rule is: ::
+ The threshold value in case of split on an ordered variable. The rule is: ::
if var_value < ord.c
then next_node<-left
else next_node<-right
-.. ocv:member:: int ord::split_point
+ .. ocv:member:: int ord::split_point
- Used internally by the training algorithm.
+ Used internally by the training algorithm.
CvDTreeNode
-----------
.. ocv:struct:: CvDTreeNode
-The structure represents a node in a decision tree. It has public members:
+ The structure represents a node in a decision tree. It has public members:
-.. ocv:member:: int class_idx
+ .. ocv:member:: int class_idx
Class index normalized to 0..class_count-1 range and assigned to the node. It is used internally in classification trees and tree ensembles.
-.. ocv:member:: int Tn
+ .. ocv:member:: int Tn
Tree index in a ordered sequence of pruned trees. The indices are used during and after the pruning procedure. The root node has the maximum value ``Tn`` of the whole tree, child nodes have ``Tn`` less than or equal to the parent's ``Tn``, and nodes with :math:`Tn \leq CvDTree::pruned\_tree\_idx` are not used at prediction stage (the corresponding branches are considered as cut-off), even if they have not been physically deleted from the tree at the pruning stage.
-.. ocv:member:: double value
+ .. ocv:member:: double value
Value at the node: a class label in case of classification or estimated function value in case of regression.
-.. ocv:member:: CvDTreeNode* parent
+ .. ocv:member:: CvDTreeNode* parent
Pointer to the parent node.
-.. ocv:member:: CvDTreeNode* left
+ .. ocv:member:: CvDTreeNode* left
Pointer to the left child node.
-.. ocv:member:: CvDTreeNode* right
+ .. ocv:member:: CvDTreeNode* right
Pointer to the right child node.
-.. ocv:member:: CvDTreeSplit* split
+ .. ocv:member:: CvDTreeSplit* split
Pointer to the first (primary) split in the node list of splits.
-.. ocv:member:: int sample_count
+ .. ocv:member:: int sample_count
The number of samples that fall into the node at the training stage. It is used to resolve the difficult cases - when the variable for the primary split is missing and all the variables for other surrogate splits are missing too. In this case the sample is directed to the left if ``left->sample_count > right->sample_count`` and to the right otherwise.
-.. ocv:member:: int depth
+ .. ocv:member:: int depth
Depth of the node. The root node depth is 0, the child nodes depth is the parent's depth + 1.
----------
.. ocv:class:: CvERTrees : public CvRTrees
- The class implements the Extremely randomized trees algorithm. ``CvERTrees`` is inherited from :ocv:class:`CvRTrees` and has the same interface, so see description of :ocv:class:`CvRTrees` class to get details. To set the training parameters of Extremely randomized trees the same class :ocv:class:`CvRTParams` is used.
+ The class implements the Extremely randomized trees algorithm. ``CvERTrees`` is inherited from :ocv:class:`CvRTrees` and has the same interface, so see description of :ocv:class:`CvRTrees` class to get details. To set the training parameters of Extremely randomized trees the same class :ocv:struct:`CvRTParams` is used.
---------------------
.. ocv:struct:: CvANN_MLP_TrainParams
-Parameters of the MLP training algorithm. You can initialize the structure by a constructor or the individual parameters can be adjusted after the structure is created.
+ Parameters of the MLP training algorithm. You can initialize the structure by a constructor or the individual parameters can be adjusted after the structure is created.
-The back-propagation algorithm parameters:
+ The back-propagation algorithm parameters:
-.. ocv:member:: double bp_dw_scale
+ .. ocv:member:: double bp_dw_scale
- Strength of the weight gradient term. The recommended value is about 0.1.
+ Strength of the weight gradient term. The recommended value is about 0.1.
-.. ocv:member:: double bp_moment_scale
+ .. ocv:member:: double bp_moment_scale
- Strength of the momentum term (the difference between weights on the 2 previous iterations). This parameter provides some inertia to smooth the random fluctuations of the weights. It can vary from 0 (the feature is disabled) to 1 and beyond. The value 0.1 or so is good enough
+ Strength of the momentum term (the difference between weights on the 2 previous iterations). This parameter provides some inertia to smooth the random fluctuations of the weights. It can vary from 0 (the feature is disabled) to 1 and beyond. The value 0.1 or so is good enough
-The RPROP algorithm parameters (see [RPROP93]_ for details):
+ The RPROP algorithm parameters (see [RPROP93]_ for details):
-.. ocv:member:: double rp_dw0
+ .. ocv:member:: double rp_dw0
- Initial value :math:`\Delta_0` of update-values :math:`\Delta_{ij}`.
+ Initial value :math:`\Delta_0` of update-values :math:`\Delta_{ij}`.
-.. ocv:member:: double rp_dw_plus
+ .. ocv:member:: double rp_dw_plus
- Increase factor :math:`\eta^+`. It must be >1.
+ Increase factor :math:`\eta^+`. It must be >1.
-.. ocv:member:: double rp_dw_minus
+ .. ocv:member:: double rp_dw_minus
- Decrease factor :math:`\eta^-`. It must be <1.
+ Decrease factor :math:`\eta^-`. It must be <1.
-.. ocv:member:: double rp_dw_min
+ .. ocv:member:: double rp_dw_min
- Update-values lower limit :math:`\Delta_{min}`. It must be positive.
+ Update-values lower limit :math:`\Delta_{min}`. It must be positive.
-.. ocv:member:: double rp_dw_max
+ .. ocv:member:: double rp_dw_max
- Update-values upper limit :math:`\Delta_{max}`. It must be >1.
+ Update-values upper limit :math:`\Delta_{max}`. It must be >1.
CvANN_MLP_TrainParams::CvANN_MLP_TrainParams
-----------
.. ocv:struct:: CvParamGrid
-The structure represents the logarithmic grid range of statmodel parameters. It is used for optimizing statmodel accuracy by varying model parameters, the accuracy estimate being computed by cross-validation.
+ The structure represents the logarithmic grid range of statmodel parameters. It is used for optimizing statmodel accuracy by varying model parameters, the accuracy estimate being computed by cross-validation.
-.. ocv:member:: double CvParamGrid::min_val
+ .. ocv:member:: double CvParamGrid::min_val
- Minimum value of the statmodel parameter.
+ Minimum value of the statmodel parameter.
-.. ocv:member:: double CvParamGrid::max_val
+ .. ocv:member:: double CvParamGrid::max_val
- Maximum value of the statmodel parameter.
+ Maximum value of the statmodel parameter.
-.. ocv:member:: double CvParamGrid::step
+ .. ocv:member:: double CvParamGrid::step
- Logarithmic step for iterating the statmodel parameter.
+ Logarithmic step for iterating the statmodel parameter.
The grid determines the following iteration sequence of the statmodel parameter values:
----
.. ocv:class:: SURF : public Feature2D
-Class for extracting Speeded Up Robust Features from an image [Bay06]_. The class is derived from ``CvSURFParams`` structure, which specifies the algorithm parameters:
+ Class for extracting Speeded Up Robust Features from an image [Bay06]_. The class is derived from ``CvSURFParams`` structure, which specifies the algorithm parameters:
- .. ocv:member:: int extended
+ .. ocv:member:: int extended
- * 0 means that the basic descriptors (64 elements each) shall be computed
- * 1 means that the extended descriptors (128 elements each) shall be computed
+ * 0 means that the basic descriptors (64 elements each) shall be computed
+ * 1 means that the extended descriptors (128 elements each) shall be computed
- .. ocv:member:: int upright
+ .. ocv:member:: int upright
- * 0 means that detector computes orientation of each feature.
- * 1 means that the orientation is not computed (which is much, much faster). For example, if you match images from a stereo pair, or do image stitching, the matched features likely have very similar angles, and you can speed up feature extraction by setting ``upright=1``.
+ * 0 means that detector computes orientation of each feature.
+ * 1 means that the orientation is not computed (which is much, much faster). For example, if you match images from a stereo pair, or do image stitching, the matched features likely have very similar angles, and you can speed up feature extraction by setting ``upright=1``.
- .. ocv:member:: double hessianThreshold
+ .. ocv:member:: double hessianThreshold
- Threshold for the keypoint detector. Only features, whose hessian is larger than ``hessianThreshold`` are retained by the detector. Therefore, the larger the value, the less keypoints you will get. A good default value could be from 300 to 500, depending from the image contrast.
+ Threshold for the keypoint detector. Only features, whose hessian is larger than ``hessianThreshold`` are retained by the detector. Therefore, the larger the value, the less keypoints you will get. A good default value could be from 300 to 500, depending from the image contrast.
- .. ocv:member:: int nOctaves
+ .. ocv:member:: int nOctaves
- The number of a gaussian pyramid octaves that the detector uses. It is set to 4 by default. If you want to get very large features, use the larger value. If you want just small features, decrease it.
+ The number of a gaussian pyramid octaves that the detector uses. It is set to 4 by default. If you want to get very large features, use the larger value. If you want just small features, decrease it.
- .. ocv:member:: int nOctaveLayers
+ .. ocv:member:: int nOctaveLayers
- The number of images within each octave of a gaussian pyramid. It is set to 2 by default.
+ The number of images within each octave of a gaussian pyramid. It is set to 2 by default.
.. [Bay06] Bay, H. and Tuytelaars, T. and Van Gool, L. "SURF: Speeded Up Robust Features", 9th European Conference on Computer Vision, 2006
--------------------
.. ocv:struct:: CvLSVMFilterPosition
-Structure describes the position of the filter in the feature pyramid.
+ Structure describes the position of the filter in the feature pyramid.
- .. ocv:member:: unsigned int l
+ .. ocv:member:: unsigned int l
- level in the feature pyramid
+ level in the feature pyramid
- .. ocv:member:: unsigned int x
+ .. ocv:member:: unsigned int x
- x-coordinate in level l
+ x-coordinate in level l
- .. ocv:member:: unsigned int y
+ .. ocv:member:: unsigned int y
- y-coordinate in level l
+ y-coordinate in level l
CvLSVMFilterObject
------------------
.. ocv:struct:: CvLSVMFilterObject
-Description of the filter, which corresponds to the part of the object.
+ Description of the filter, which corresponds to the part of the object.
- .. ocv:member:: CvLSVMFilterPosition V
+ .. ocv:member:: CvLSVMFilterPosition V
- ideal (penalty = 0) position of the partial filter
- from the root filter position (V_i in the paper)
+ ideal (penalty = 0) position of the partial filter
+ from the root filter position (V_i in the paper)
- .. ocv:member:: float fineFunction[4]
+ .. ocv:member:: float fineFunction[4]
- vector describes penalty function (d_i in the paper)
- pf[0] * x + pf[1] * y + pf[2] * x^2 + pf[3] * y^2
+ vector describes penalty function (d_i in the paper)
+ pf[0] * x + pf[1] * y + pf[2] * x^2 + pf[3] * y^2
- .. ocv:member:: int sizeX
- .. ocv:member:: int sizeY
+ .. ocv:member:: int sizeX
+ .. ocv:member:: int sizeY
- Rectangular map (sizeX x sizeY),
- every cell stores feature vector (dimension = p)
+ Rectangular map (sizeX x sizeY),
+ every cell stores feature vector (dimension = p)
- .. ocv:member:: int numFeatures
+ .. ocv:member:: int numFeatures
- number of features
+ number of features
- .. ocv:member:: float *H
+ .. ocv:member:: float *H
- matrix of feature vectors to set and get
- feature vectors (i,j) used formula H[(j * sizeX + i) * p + k],
- where k - component of feature vector in cell (i, j)
+ matrix of feature vectors to set and get
+ feature vectors (i,j) used formula H[(j * sizeX + i) * p + k],
+ where k - component of feature vector in cell (i, j)
CvLatentSvmDetector
-------------------
.. ocv:struct:: CvLatentSvmDetector
-Structure contains internal representation of trained Latent SVM detector.
+ Structure contains internal representation of trained Latent SVM detector.
- .. ocv:member:: int num_filters
+ .. ocv:member:: int num_filters
- total number of filters (root plus part) in model
+ total number of filters (root plus part) in model
- .. ocv:member:: int num_components
+ .. ocv:member:: int num_components
- number of components in model
+ number of components in model
- .. ocv:member:: int* num_part_filters
+ .. ocv:member:: int* num_part_filters
- array containing number of part filters for each component
+ array containing number of part filters for each component
- .. ocv:member:: CvLSVMFilterObject** filters
+ .. ocv:member:: CvLSVMFilterObject** filters
- root and part filters for all model components
+ root and part filters for all model components
- .. ocv:member:: float* b
+ .. ocv:member:: float* b
- biases for all model components
+ biases for all model components
- .. ocv:member:: float score_threshold
+ .. ocv:member:: float score_threshold
- confidence level threshold
+ confidence level threshold
CvObjectDetection
-----------------
.. ocv:struct:: CvObjectDetection
-Structure contains the bounding box and confidence level for detected object.
+ Structure contains the bounding box and confidence level for detected object.
- .. ocv:member:: CvRect rect
+ .. ocv:member:: CvRect rect
- bounding box for a detected object
+ bounding box for a detected object
- .. ocv:member:: float score
+ .. ocv:member:: float score
- confidence level
+ confidence level
cvLoadLatentSvmDetector
----------------------------------
.. ocv:struct:: LatentSvmDetector::ObjectDetection
-Structure contains the detection information.
+ Structure contains the detection information.
- .. ocv:member:: Rect rect
+ .. ocv:member:: Rect rect
- bounding box for a detected object
+ bounding box for a detected object
- .. ocv:member:: float score
+ .. ocv:member:: float score
- confidence level
+ confidence level
- .. ocv:member:: int classID
+ .. ocv:member:: int classID
- class (model or detector) ID that detect an object
+ class (model or detector) ID that detect an object
LatentSvmDetector::LatentSvmDetector
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