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Object Detection
=============================
.. highlight:: cpp
ocl::OclCascadeClassifier
-----------------------------
.. ocv:class:: ocl::OclCascadeClassifier : public CascadeClassifier
Cascade classifier class used for object detection. Supports HAAR cascade classifier in the form of cross link ::
class CV_EXPORTS OclCascadeClassifier : public CascadeClassifier
{
public:
OclCascadeClassifier(){};
~OclCascadeClassifier(){};
CvSeq* oclHaarDetectObjects(oclMat &gimg, CvMemStorage *storage, double scaleFactor,
int minNeighbors, int flags, CvSize minSize = cvSize(0, 0),
CvSize maxSize = cvSize(0, 0));
};
.. note::
(Ocl) A face detection example using cascade classifiers can be found at opencv_source_code/samples/ocl/facedetect.cpp
ocl::OclCascadeClassifier::oclHaarDetectObjects
------------------------------------------------------
Detects objects of different sizes in the input image.
.. ocv:function:: CvSeq* ocl::OclCascadeClassifier::oclHaarDetectObjects(oclMat &gimg, CvMemStorage *storage, double scaleFactor, int minNeighbors, int flags, CvSize minSize = cvSize(0, 0), CvSize maxSize = cvSize(0, 0))
:param gimage: Matrix of type CV_8U containing an image where objects should be detected.
:param scaleFactor: Parameter specifying how much the image size is reduced at each image scale.
:param minNeighbors: Parameter specifying how many neighbors each candidate rectangle should have to retain it.
:param flags: Parameter with the same meaning for an old cascade as in the function ``cvHaarDetectObjects``. It is not used for a new cascade.
:param minSize: Minimum possible object size. Objects smaller than that are ignored.
:param maxSize: Maximum possible object size. Objects larger than that are ignored.
The function provides a very similar interface with that in CascadeClassifier class, except using oclMat as input image.
ocl::MatchTemplateBuf
-------------------------
.. ocv:struct:: ocl::MatchTemplateBuf
Class providing memory buffers for :ocv:func:`ocl::matchTemplate` function, plus it allows to adjust some specific parameters. ::
struct CV_EXPORTS MatchTemplateBuf
{
Size user_block_size;
oclMat imagef, templf;
std::vector<oclMat> images;
std::vector<oclMat> image_sums;
std::vector<oclMat> image_sqsums;
};
You can use field `user_block_size` to set specific block size for :ocv:func:`ocl::matchTemplate` function. If you leave its default value `Size(0,0)` then automatic estimation of block size will be used (which is optimized for speed). By varying `user_block_size` you can reduce memory requirements at the cost of speed.
ocl::matchTemplate
----------------------
Computes a proximity map for a raster template and an image where the template is searched for.
.. ocv:function:: void ocl::matchTemplate(const oclMat& image, const oclMat& templ, oclMat& result, int method)
.. ocv:function:: void ocl::matchTemplate(const oclMat& image, const oclMat& templ, oclMat& result, int method, MatchTemplateBuf &buf)
:param image: Source image. ``CV_32F`` and ``CV_8U`` depth images (1..4 channels) are supported for now.
:param templ: Template image with the size and type the same as ``image`` .
:param result: Map containing comparison results ( ``CV_32FC1`` ). If ``image`` is *W x H* and ``templ`` is *w x h*, then ``result`` must be *W-w+1 x H-h+1*.
: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:struct:`ocl::MatchTemplateBuf`.
The following methods are supported for the ``CV_8U`` depth images for now:
* ``CV_TM_SQDIFF``
* ``CV_TM_SQDIFF_NORMED``
* ``CV_TM_CCORR``
* ``CV_TM_CCORR_NORMED``
* ``CV_TM_CCOEFF``
* ``CV_TM_CCOEFF_NORMED``
The following methods are supported for the ``CV_32F`` images for now:
* ``CV_TM_SQDIFF``
* ``CV_TM_CCORR``
.. seealso:: :ocv:func:`matchTemplate`
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