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Conflicts: doc/tutorials/features2d/feature_detection/feature_detection.rst modules/bioinspired/doc/retina/index.rst modules/core/include/opencv2/core/core.hpp modules/core/include/opencv2/core/mat.hpp modules/core/include/opencv2/core/operations.hpp modules/core/src/stat.cpp modules/features2d/include/opencv2/features2d/features2d.hpp modules/imgproc/src/filter.cpp modules/legacy/src/dpstereo.cpp modules/nonfree/src/surf.ocl.cpp modules/ocl/doc/image_processing.rst modules/ocl/doc/object_detection.rst modules/ocl/include/opencv2/ocl/ocl.hpp modules/ocl/include/opencv2/ocl/private/util.hpp modules/ocl/src/arithm.cpp modules/ocl/src/canny.cpp modules/ocl/src/filtering.cpp modules/ocl/src/imgproc.cpp modules/ocl/src/initialization.cpp modules/ocl/src/matrix_operations.cpp modules/ocl/src/pyrdown.cpp modules/ocl/src/pyrup.cpp modules/ocl/src/split_merge.cpp modules/ocl/test/test_objdetect.cpp modules/ocl/test/utility.hpp
96 lines
4.1 KiB
ReStructuredText
96 lines
4.1 KiB
ReStructuredText
Object Detection
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=============================
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.. highlight:: cpp
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ocl::OclCascadeClassifier
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-----------------------------
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.. ocv:class:: ocl::OclCascadeClassifier : public CascadeClassifier
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Cascade classifier class used for object detection. Supports HAAR cascade classifier in the form of cross link ::
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class CV_EXPORTS OclCascadeClassifier : public CascadeClassifier
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{
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public:
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void detectMultiScale(oclMat &image, CV_OUT std::vector<cv::Rect>& faces,
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double scaleFactor = 1.1, int minNeighbors = 3, int flags = 0,
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Size minSize = Size(), Size maxSize = Size());
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};
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.. note::
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(Ocl) A face detection example using cascade classifiers can be found at opencv_source_code/samples/ocl/facedetect.cpp
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ocl::OclCascadeClassifier::detectMultiScale
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------------------------------------------------------
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Detects objects of different sizes in the input image.
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.. 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())
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:param faces: Vector of rectangles where each rectangle contains the detected object.
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:param image: Matrix of type CV_8U containing an image where objects should be detected.
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:param scaleFactor: Parameter specifying how much the image size is reduced at each image scale.
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:param minNeighbors: Parameter specifying how many neighbors each candidate rectangle should have to retain it.
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:param flags: Parameter with the same meaning for an old cascade as in the function ``cvHaarDetectObjects``. It is not used for a new cascade.
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:param minSize: Minimum possible object size. Objects smaller than that are ignored.
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:param maxSize: Maximum possible object size. Objects larger than that are ignored.
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The function provides a very similar interface with that in CascadeClassifier class, except using oclMat as input image.
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ocl::MatchTemplateBuf
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-------------------------
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.. ocv:struct:: ocl::MatchTemplateBuf
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Class providing memory buffers for :ocv:func:`ocl::matchTemplate` function, plus it allows to adjust some specific parameters. ::
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struct CV_EXPORTS MatchTemplateBuf
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{
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Size user_block_size;
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oclMat imagef, templf;
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std::vector<oclMat> images;
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std::vector<oclMat> image_sums;
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std::vector<oclMat> image_sqsums;
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};
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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.
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ocl::matchTemplate
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----------------------
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Computes a proximity map for a raster template and an image where the template is searched for.
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.. ocv:function:: void ocl::matchTemplate(const oclMat& image, const oclMat& templ, oclMat& result, int method)
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.. ocv:function:: void ocl::matchTemplate(const oclMat& image, const oclMat& templ, oclMat& result, int method, MatchTemplateBuf &buf)
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:param image: Source image. ``CV_32F`` and ``CV_8U`` depth images (1..4 channels) are supported for now.
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:param templ: Template image with the size and type the same as ``image`` .
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: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*.
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:param method: Specifies the way to compare the template with the image.
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:param buf: Optional buffer to avoid extra memory allocations and to adjust some specific parameters. See :ocv:struct:`ocl::MatchTemplateBuf`.
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The following methods are supported for the ``CV_8U`` depth images for now:
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* ``CV_TM_SQDIFF``
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* ``CV_TM_SQDIFF_NORMED``
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* ``CV_TM_CCORR``
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* ``CV_TM_CCORR_NORMED``
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* ``CV_TM_CCOEFF``
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* ``CV_TM_CCOEFF_NORMED``
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The following methods are supported for the ``CV_32F`` images for now:
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* ``CV_TM_SQDIFF``
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* ``CV_TM_CCORR``
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.. seealso:: :ocv:func:`matchTemplate`
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