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Open Source Computer Vision Library
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94 lines
4.1 KiB
94 lines
4.1 KiB
Object Detection |
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============================= |
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.. highlight:: cpp |
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ocl::OclCascadeClassifier |
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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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OclCascadeClassifier() {}; |
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~OclCascadeClassifier() {}; |
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CvSeq *oclHaarDetectObjects(oclMat &gimg, CvMemStorage *storage, |
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double scaleFactor,int minNeighbors, |
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int flags, CvSize minSize = cvSize(0, 0), |
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CvSize maxSize = cvSize(0, 0)); |
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}; |
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.. Sample code:: |
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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::oclHaarDetectObjects |
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Returns the detected objects by a list of rectangles |
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.. 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)) |
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:param image: Matrix of type CV_8U containing an image where objects should be detected. |
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: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). |
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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 minSize: Minimum possible object size. Objects smaller than that are ignored. |
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Detects objects of different sizes in the input image,only tested for face detection now. The function returns the number of detected objects. |
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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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