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 images; std::vector image_sums; std::vector 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`