:param image:Matrix of type CV_8U containing an image where objects should be detected.
:param imageobjectsBuff:Buffer to store detected objects (rectangles). If it is empty, it is allocated with the defaultsize. If not empty, the function searches not more than N objects, where N = sizeof(objectsBufers data)/sizeof(cv::Rect).
: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 minSize:Minimum possible object size. Objects smaller than that are ignored.
Detects objects of different sizes in the input image,only tested for face detection now. The function returns the number of detected objects.
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.
: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.
