opencv/modules/cudaimgproc/doc/imgproc.rst

Image Processing
================

.. highlight:: cpp



cuda::CannyEdgeDetector
-----------------------
.. ocv:class:: cuda::CannyEdgeDetector : public Algorithm

Base class for Canny Edge Detector. ::

    class CV_EXPORTS CannyEdgeDetector : public Algorithm
    {
    public:
        virtual void detect(InputArray image, OutputArray edges) = 0;
        virtual void detect(InputArray dx, InputArray dy, OutputArray edges) = 0;

        virtual void setLowThreshold(double low_thresh) = 0;
        virtual double getLowThreshold() const = 0;

        virtual void setHighThreshold(double high_thresh) = 0;
        virtual double getHighThreshold() const = 0;

        virtual void setAppertureSize(int apperture_size) = 0;
        virtual int getAppertureSize() const = 0;

        virtual void setL2Gradient(bool L2gradient) = 0;
        virtual bool getL2Gradient() const = 0;
    };



cuda::CannyEdgeDetector::detect
-------------------------------
Finds edges in an image using the [Canny86]_ algorithm.

.. ocv:function:: void cuda::CannyEdgeDetector::detect(InputArray image, OutputArray edges)

.. ocv:function:: void cuda::CannyEdgeDetector::detect(InputArray dx, InputArray dy, OutputArray edges)

    :param image: Single-channel 8-bit input image.

    :param dx: First derivative of image in the vertical direction. Support only ``CV_32S`` type.

    :param dy: First derivative of image in the horizontal direction. Support only ``CV_32S`` type.

    :param edges: Output edge map. It has the same size and type as  ``image`` .



cuda::createCannyEdgeDetector
-----------------------------
Creates implementation for :ocv:class:`cuda::CannyEdgeDetector` .

.. ocv:function:: Ptr<CannyEdgeDetector> cuda::createCannyEdgeDetector(double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false)

    :param low_thresh: First threshold for the hysteresis procedure.

    :param high_thresh: Second threshold for the hysteresis procedure.

    :param apperture_size: Aperture size for the  :ocv:func:`Sobel`  operator.

    :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`` ).



cuda::meanShiftFiltering
------------------------
Performs mean-shift filtering for each point of the source image.

.. ocv:function:: void cuda::meanShiftFiltering(InputArray src, OutputArray dst, int sp, int sr, TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1), Stream& stream = Stream::Null())

    :param src: Source image. Only  ``CV_8UC4`` images are supported for now.

    :param dst: Destination image containing the color of mapped points. It has the same size and type as  ``src`` .

    :param sp: Spatial window radius.

    :param sr: Color window radius.

    :param criteria: Termination criteria. See :ocv:class:`TermCriteria`.

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.



cuda::meanShiftProc
-------------------
Performs a mean-shift procedure and stores information about processed points (their colors and positions) in two images.

.. ocv:function:: void cuda::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())

    :param src: Source image. Only  ``CV_8UC4`` images are supported for now.

    :param dstr: Destination image containing the color of mapped points. The size and type is the same as  ``src`` .

    :param dstsp: Destination image containing the position of mapped points. The size is the same as  ``src`` size. The type is  ``CV_16SC2`` .

    :param sp: Spatial window radius.

    :param sr: Color window radius.

    :param criteria: Termination criteria. See :ocv:class:`TermCriteria`.

.. seealso:: :ocv:func:`cuda::meanShiftFiltering`



cuda::meanShiftSegmentation
---------------------------
Performs a mean-shift segmentation of the source image and eliminates small segments.

.. ocv:function:: void cuda::meanShiftSegmentation(InputArray src, OutputArray dst, int sp, int sr, int minsize, TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1))

    :param src: Source image. Only  ``CV_8UC4`` images are supported for now.

    :param dst: Segmented image with the same size and type as  ``src`` (host memory).

    :param sp: Spatial window radius.

    :param sr: Color window radius.

    :param minsize: Minimum segment size. Smaller segments are merged.

    :param criteria: Termination criteria. See :ocv:class:`TermCriteria`.



cuda::TemplateMatching
----------------------
.. ocv:class:: cuda::TemplateMatching : public Algorithm

Base class for Template Matching. ::

    class CV_EXPORTS TemplateMatching : public Algorithm
    {
    public:
        virtual void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null()) = 0;
    };



cuda::TemplateMatching::match
-----------------------------
Computes a proximity map for a raster template and an image where the template is searched for.

.. ocv:function:: void cuda::TemplateMatching::match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null())

    :param image: Source image.

    :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 stream: Stream for the asynchronous version.



cuda::createTemplateMatching
----------------------------
Creates implementation for :ocv:class:`cuda::TemplateMatching` .

.. ocv:function:: Ptr<TemplateMatching> cuda::createTemplateMatching(int srcType, int method, Size user_block_size = Size())

    :param srcType: Input source type. ``CV_32F`` and  ``CV_8U`` depth images (1..4 channels) are supported for now.

    :param method: Specifies the way to compare the template with the image.

    :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.

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`



cuda::bilateralFilter
---------------------
Performs bilateral filtering of passed image

.. ocv:function:: void cuda::bilateralFilter(InputArray src, OutputArray dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode=BORDER_DEFAULT, Stream& stream=Stream::Null())

    :param src: Source image. Supports only (channles != 2 && depth() != CV_8S && depth() != CV_32S && depth() != CV_64F).

    :param dst: Destination imagwe.

    :param kernel_size: Kernel window size.

    :param sigma_color: Filter sigma in the color space.

    :param sigma_spatial:  Filter sigma in the coordinate space.

    :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.

    :param stream: Stream for the asynchronous version.

.. seealso:: :ocv:func:`bilateralFilter`



cuda::blendLinear
-----------------
Performs linear blending of two images.

.. ocv:function:: void cuda::blendLinear(InputArray img1, InputArray img2, InputArray weights1, InputArray weights2, OutputArray result, Stream& stream = Stream::Null())

    :param img1: First image. Supports only ``CV_8U`` and ``CV_32F`` depth.

    :param img2: Second image. Must have the same size and the same type as ``img1`` .

    :param weights1: Weights for first image. Must have tha same size as ``img1`` . Supports only ``CV_32F`` type.

    :param weights2: Weights for second image. Must have tha same size as ``img2`` . Supports only ``CV_32F`` type.

    :param result: Destination image.

    :param stream: Stream for the asynchronous version.