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232 lines
8.4 KiB
ReStructuredText
232 lines
8.4 KiB
ReStructuredText
Image Processing
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================
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.. highlight:: cpp
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gpu::CannyEdgeDetector
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----------------------
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.. ocv:class:: gpu::CannyEdgeDetector : public Algorithm
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Base class for Canny Edge Detector. ::
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class CV_EXPORTS CannyEdgeDetector : public Algorithm
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{
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public:
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virtual void detect(InputArray image, OutputArray edges) = 0;
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virtual void detect(InputArray dx, InputArray dy, OutputArray edges) = 0;
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virtual void setLowThreshold(double low_thresh) = 0;
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virtual double getLowThreshold() const = 0;
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virtual void setHighThreshold(double high_thresh) = 0;
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virtual double getHighThreshold() const = 0;
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virtual void setAppertureSize(int apperture_size) = 0;
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virtual int getAppertureSize() const = 0;
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virtual void setL2Gradient(bool L2gradient) = 0;
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virtual bool getL2Gradient() const = 0;
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};
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gpu::CannyEdgeDetector::detect
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------------------------------
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Finds edges in an image using the [Canny86]_ algorithm.
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.. ocv:function:: void gpu::CannyEdgeDetector::detect(InputArray image, OutputArray edges)
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.. ocv:function:: void gpu::CannyEdgeDetector::detect(InputArray dx, InputArray dy, OutputArray edges)
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:param image: Single-channel 8-bit input image.
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:param dx: First derivative of image in the vertical direction. Support only ``CV_32S`` type.
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:param dy: First derivative of image in the horizontal direction. Support only ``CV_32S`` type.
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:param edges: Output edge map. It has the same size and type as ``image`` .
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gpu::createCannyEdgeDetector
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----------------------------
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Creates implementation for :ocv:class:`gpu::CannyEdgeDetector` .
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.. ocv:function:: Ptr<CannyEdgeDetector> gpu::createCannyEdgeDetector(double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false)
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:param low_thresh: First threshold for the hysteresis procedure.
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:param high_thresh: Second threshold for the hysteresis procedure.
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:param apperture_size: Aperture size for the :ocv:func:`Sobel` operator.
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:param L2gradient: Flag indicating whether a more accurate :math:`L_2` norm :math:`=\sqrt{(dI/dx)^2 + (dI/dy)^2}` should be used to compute the image gradient magnitude ( ``L2gradient=true`` ), or a faster default :math:`L_1` norm :math:`=|dI/dx|+|dI/dy|` is enough ( ``L2gradient=false`` ).
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gpu::meanShiftFiltering
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-----------------------
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Performs mean-shift filtering for each point of the source image.
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.. ocv:function:: void gpu::meanShiftFiltering(InputArray src, OutputArray dst, int sp, int sr, TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1), Stream& stream = Stream::Null())
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:param src: Source image. Only ``CV_8UC4`` images are supported for now.
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:param dst: Destination image containing the color of mapped points. It has the same size and type as ``src`` .
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:param sp: Spatial window radius.
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:param sr: Color window radius.
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:param criteria: Termination criteria. See :ocv:class:`TermCriteria`.
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It maps each point of the source image into another point. As a result, you have a new color and new position of each point.
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gpu::meanShiftProc
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------------------
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Performs a mean-shift procedure and stores information about processed points (their colors and positions) in two images.
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.. ocv:function:: void gpu::meanShiftProc(InputArray src, OutputArray dstr, OutputArray dstsp, int sp, int sr, TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1), Stream& stream = Stream::Null())
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:param src: Source image. Only ``CV_8UC4`` images are supported for now.
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:param dstr: Destination image containing the color of mapped points. The size and type is the same as ``src`` .
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:param dstsp: Destination image containing the position of mapped points. The size is the same as ``src`` size. The type is ``CV_16SC2`` .
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:param sp: Spatial window radius.
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:param sr: Color window radius.
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:param criteria: Termination criteria. See :ocv:class:`TermCriteria`.
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.. seealso:: :ocv:func:`gpu::meanShiftFiltering`
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gpu::meanShiftSegmentation
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--------------------------
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Performs a mean-shift segmentation of the source image and eliminates small segments.
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.. ocv:function:: void gpu::meanShiftSegmentation(InputArray src, OutputArray dst, int sp, int sr, int minsize, TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1))
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:param src: Source image. Only ``CV_8UC4`` images are supported for now.
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:param dst: Segmented image with the same size and type as ``src`` (host memory).
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:param sp: Spatial window radius.
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:param sr: Color window radius.
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:param minsize: Minimum segment size. Smaller segments are merged.
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:param criteria: Termination criteria. See :ocv:class:`TermCriteria`.
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gpu::TemplateMatching
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---------------------
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.. ocv:class:: gpu::TemplateMatching : public Algorithm
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Base class for Template Matching. ::
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class CV_EXPORTS TemplateMatching : public Algorithm
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{
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public:
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virtual void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null()) = 0;
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};
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gpu::TemplateMatching::match
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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 gpu::TemplateMatching::match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null())
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:param image: Source image.
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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 stream: Stream for the asynchronous version.
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gpu::createTemplateMatching
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---------------------------
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Creates implementation for :ocv:class:`gpu::TemplateMatching` .
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.. ocv:function:: Ptr<TemplateMatching> gpu::createTemplateMatching(int srcType, int method, Size user_block_size = Size())
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:param srcType: Input source type. ``CV_32F`` and ``CV_8U`` depth images (1..4 channels) are supported for now.
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:param method: Specifies the way to compare the template with the image.
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:param user_block_size: You can use field `user_block_size` to set specific block size. 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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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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gpu::bilateralFilter
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--------------------
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Performs bilateral filtering of passed image
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.. ocv:function:: void gpu::bilateralFilter(InputArray src, OutputArray dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode=BORDER_DEFAULT, Stream& stream=Stream::Null())
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:param src: Source image. Supports only (channles != 2 && depth() != CV_8S && depth() != CV_32S && depth() != CV_64F).
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:param dst: Destination imagwe.
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:param kernel_size: Kernel window size.
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:param sigma_color: Filter sigma in the color space.
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:param sigma_spatial: Filter sigma in the coordinate space.
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:param borderMode: Border type. See :ocv:func:`borderInterpolate` for details. ``BORDER_REFLECT101`` , ``BORDER_REPLICATE`` , ``BORDER_CONSTANT`` , ``BORDER_REFLECT`` and ``BORDER_WRAP`` are supported for now.
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:param stream: Stream for the asynchronous version.
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.. seealso:: :ocv:func:`bilateralFilter`
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gpu::blendLinear
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-------------------
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Performs linear blending of two images.
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.. ocv:function:: void gpu::blendLinear(InputArray img1, InputArray img2, InputArray weights1, InputArray weights2, OutputArray result, Stream& stream = Stream::Null())
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:param img1: First image. Supports only ``CV_8U`` and ``CV_32F`` depth.
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:param img2: Second image. Must have the same size and the same type as ``img1`` .
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:param weights1: Weights for first image. Must have tha same size as ``img1`` . Supports only ``CV_32F`` type.
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:param weights2: Weights for second image. Must have tha same size as ``img2`` . Supports only ``CV_32F`` type.
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:param result: Destination image.
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:param stream: Stream for the asynchronous version.
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