6b5ac42a9b
Conflicts: modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst modules/features2d/doc/object_categorization.rst modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst modules/gpu/doc/image_filtering.rst modules/gpu/doc/image_processing.rst modules/gpu/doc/video.rst modules/imgproc/doc/miscellaneous_transformations.rst modules/imgproc/doc/object_detection.rst modules/imgproc/doc/structural_analysis_and_shape_descriptors.rst modules/imgproc/src/samplers.cpp modules/ml/doc/k_nearest_neighbors.rst modules/nonfree/doc/feature_detection.rst modules/ocl/include/opencv2/ocl/ocl.hpp modules/photo/doc/inpainting.rst modules/ts/include/opencv2/ts.hpp platforms/scripts/camera_build.conf samples/android/camera-calibration/AndroidManifest.xml
94 lines
4.0 KiB
ReStructuredText
94 lines
4.0 KiB
ReStructuredText
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:
|
|
void detectMultiScale(oclMat &image, CV_OUT std::vector<cv::Rect>& faces,
|
|
double scaleFactor = 1.1, int minNeighbors = 3, int flags = 0,
|
|
Size minSize = Size(), Size maxSize = Size());
|
|
};
|
|
|
|
.. 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:: void ocl::OclCascadeClassifier::detectMultiScale(oclMat &image, std::vector<cv::Rect>& faces, double scaleFactor = 1.1, int minNeighbors = 3, int flags = 0, Size minSize = Size(), Size maxSize = Size())
|
|
|
|
:param image: Matrix of type CV_8U containing an image where objects should be detected.
|
|
|
|
:param faces: Vector of rectangles where each rectangle contains the detected object.
|
|
|
|
: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.
|
|
|
|
: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`
|