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767 lines
44 KiB
C++
767 lines
44 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
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// Copyright (C) 2015, Itseez Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef OPENCV_CORE_HAL_REPLACEMENT_HPP
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#define OPENCV_CORE_HAL_REPLACEMENT_HPP
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#include "opencv2/core/hal/interface.h"
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#if defined __GNUC__
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# pragma GCC diagnostic push
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# pragma GCC diagnostic ignored "-Wunused-parameter"
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#elif defined _MSC_VER
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# pragma warning( push )
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# pragma warning( disable: 4100 )
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#endif
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//! @addtogroup core_hal_interface
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//! @note Define your functions to override default implementations:
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//! @code
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//! #undef hal_add8u
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//! #define hal_add8u my_add8u
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//! @endcode
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//! @{
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/**
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Add: _dst[i] = src1[i] + src2[i]_ @n
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Sub: _dst[i] = src1[i] - src2[i]_
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@param src1_data,src1_step first source image data and step
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@param src2_data,src2_step second source image data and step
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@param dst_data,dst_step destination image data and step
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@param width,height dimensions of the images
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*/
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//! @addtogroup core_hal_interface_addsub Element-wise add and subtract
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//! @{
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inline int hal_ni_add8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_add8s(const schar *src1_data, size_t src1_step, const schar *src2_data, size_t src2_step, schar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_add16u(const ushort *src1_data, size_t src1_step, const ushort *src2_data, size_t src2_step, ushort *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_add16s(const short *src1_data, size_t src1_step, const short *src2_data, size_t src2_step, short *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_add32s(const int *src1_data, size_t src1_step, const int *src2_data, size_t src2_step, int *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_add32f(const float *src1_data, size_t src1_step, const float *src2_data, size_t src2_step, float *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_add64f(const double *src1_data, size_t src1_step, const double *src2_data, size_t src2_step, double *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_sub8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_sub8s(const schar *src1_data, size_t src1_step, const schar *src2_data, size_t src2_step, schar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_sub16u(const ushort *src1_data, size_t src1_step, const ushort *src2_data, size_t src2_step, ushort *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_sub16s(const short *src1_data, size_t src1_step, const short *src2_data, size_t src2_step, short *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_sub32s(const int *src1_data, size_t src1_step, const int *src2_data, size_t src2_step, int *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_sub32f(const float *src1_data, size_t src1_step, const float *src2_data, size_t src2_step, float *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_sub64f(const double *src1_data, size_t src1_step, const double *src2_data, size_t src2_step, double *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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/**
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Minimum: _dst[i] = min(src1[i], src2[i])_ @n
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Maximum: _dst[i] = max(src1[i], src2[i])_
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@param src1_data,src1_step first source image data and step
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@param src2_data,src2_step second source image data and step
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@param dst_data,dst_step destination image data and step
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@param width,height dimensions of the images
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*/
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//! @addtogroup core_hal_interface_minmax Element-wise minimum or maximum
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//! @{
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inline int hal_ni_max8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_max8s(const schar *src1_data, size_t src1_step, const schar *src2_data, size_t src2_step, schar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_max16u(const ushort *src1_data, size_t src1_step, const ushort *src2_data, size_t src2_step, ushort *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_max16s(const short *src1_data, size_t src1_step, const short *src2_data, size_t src2_step, short *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_max32s(const int *src1_data, size_t src1_step, const int *src2_data, size_t src2_step, int *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_max32f(const float *src1_data, size_t src1_step, const float *src2_data, size_t src2_step, float *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_max64f(const double *src1_data, size_t src1_step, const double *src2_data, size_t src2_step, double *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_min8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_min8s(const schar *src1_data, size_t src1_step, const schar *src2_data, size_t src2_step, schar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_min16u(const ushort *src1_data, size_t src1_step, const ushort *src2_data, size_t src2_step, ushort *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_min16s(const short *src1_data, size_t src1_step, const short *src2_data, size_t src2_step, short *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_min32s(const int *src1_data, size_t src1_step, const int *src2_data, size_t src2_step, int *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_min32f(const float *src1_data, size_t src1_step, const float *src2_data, size_t src2_step, float *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_min64f(const double *src1_data, size_t src1_step, const double *src2_data, size_t src2_step, double *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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/**
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Absolute difference: _dst[i] = | src1[i] - src2[i] |_
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@param src1_data,src1_step first source image data and step
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@param src2_data,src2_step second source image data and step
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@param dst_data,dst_step destination image data and step
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@param width,height dimensions of the images
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@param scale additional multiplier
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*/
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//! @addtogroup core_hal_interface_absdiff Element-wise absolute difference
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//! @{
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inline int hal_ni_absdiff8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_absdiff8s(const schar *src1_data, size_t src1_step, const schar *src2_data, size_t src2_step, schar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_absdiff16u(const ushort *src1_data, size_t src1_step, const ushort *src2_data, size_t src2_step, ushort *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_absdiff16s(const short *src1_data, size_t src1_step, const short *src2_data, size_t src2_step, short *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_absdiff32s(const int *src1_data, size_t src1_step, const int *src2_data, size_t src2_step, int *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_absdiff32f(const float *src1_data, size_t src1_step, const float *src2_data, size_t src2_step, float *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_absdiff64f(const double *src1_data, size_t src1_step, const double *src2_data, size_t src2_step, double *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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/**
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Bitwise AND: _dst[i] = src1[i] & src2[i]_ @n
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Bitwise OR: _dst[i] = src1[i] | src2[i]_ @n
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Bitwise XOR: _dst[i] = src1[i] ^ src2[i]_ @n
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Bitwise NOT: _dst[i] = !src[i]_
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@param src1_data,src1_step first source image data and step
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@param src2_data,src2_step second source image data and step
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@param dst_data,dst_step destination image data and step
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@param width,height dimensions of the images
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*/
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//! @addtogroup core_hal_interface_logical Bitwise logical operations
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//! @{
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inline int hal_ni_and8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_or8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_xor8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_not8u(const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step, int width, int height) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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//! @cond IGNORED
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#define cv_hal_add8u hal_ni_add8u
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#define cv_hal_add8s hal_ni_add8s
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#define cv_hal_add16u hal_ni_add16u
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#define cv_hal_add16s hal_ni_add16s
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#define cv_hal_add32s hal_ni_add32s
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#define cv_hal_add32f hal_ni_add32f
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#define cv_hal_add64f hal_ni_add64f
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#define cv_hal_sub8u hal_ni_sub8u
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#define cv_hal_sub8s hal_ni_sub8s
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#define cv_hal_sub16u hal_ni_sub16u
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#define cv_hal_sub16s hal_ni_sub16s
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#define cv_hal_sub32s hal_ni_sub32s
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#define cv_hal_sub32f hal_ni_sub32f
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#define cv_hal_sub64f hal_ni_sub64f
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#define cv_hal_max8u hal_ni_max8u
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#define cv_hal_max8s hal_ni_max8s
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#define cv_hal_max16u hal_ni_max16u
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#define cv_hal_max16s hal_ni_max16s
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#define cv_hal_max32s hal_ni_max32s
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#define cv_hal_max32f hal_ni_max32f
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#define cv_hal_max64f hal_ni_max64f
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#define cv_hal_min8u hal_ni_min8u
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#define cv_hal_min8s hal_ni_min8s
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#define cv_hal_min16u hal_ni_min16u
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#define cv_hal_min16s hal_ni_min16s
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#define cv_hal_min32s hal_ni_min32s
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#define cv_hal_min32f hal_ni_min32f
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#define cv_hal_min64f hal_ni_min64f
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#define cv_hal_absdiff8u hal_ni_absdiff8u
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#define cv_hal_absdiff8s hal_ni_absdiff8s
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#define cv_hal_absdiff16u hal_ni_absdiff16u
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#define cv_hal_absdiff16s hal_ni_absdiff16s
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#define cv_hal_absdiff32s hal_ni_absdiff32s
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#define cv_hal_absdiff32f hal_ni_absdiff32f
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#define cv_hal_absdiff64f hal_ni_absdiff64f
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#define cv_hal_and8u hal_ni_and8u
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#define cv_hal_or8u hal_ni_or8u
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#define cv_hal_xor8u hal_ni_xor8u
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#define cv_hal_not8u hal_ni_not8u
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//! @endcond
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/**
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Compare: _dst[i] = src1[i] op src2[i]_
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@param src1_data,src1_step first source image data and step
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@param src2_data,src2_step second source image data and step
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@param dst_data,dst_step destination image data and step
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@param width,height dimensions of the images
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@param operation one of (CV_HAL_CMP_EQ, CV_HAL_CMP_GT, ...)
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*/
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//! @addtogroup core_hal_interface_compare Element-wise compare
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//! @{
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inline int hal_ni_cmp8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, int operation) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_cmp8s(const schar *src1_data, size_t src1_step, const schar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, int operation) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_cmp16u(const ushort *src1_data, size_t src1_step, const ushort *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, int operation) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_cmp16s(const short *src1_data, size_t src1_step, const short *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, int operation) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_cmp32s(const int *src1_data, size_t src1_step, const int *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, int operation) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_cmp32f(const float *src1_data, size_t src1_step, const float *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, int operation) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_cmp64f(const double *src1_data, size_t src1_step, const double *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, int operation) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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//! @cond IGNORED
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#define cv_hal_cmp8u hal_ni_cmp8u
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#define cv_hal_cmp8s hal_ni_cmp8s
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#define cv_hal_cmp16u hal_ni_cmp16u
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#define cv_hal_cmp16s hal_ni_cmp16s
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#define cv_hal_cmp32s hal_ni_cmp32s
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#define cv_hal_cmp32f hal_ni_cmp32f
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#define cv_hal_cmp64f hal_ni_cmp64f
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//! @endcond
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/**
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Multiply: _dst[i] = scale * src1[i] * src2[i]_
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@param src1_data,src1_step first source image data and step
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@param src2_data,src2_step second source image data and step
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@param dst_data,dst_step destination image data and step
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@param width,height dimensions of the images
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@param scale additional multiplier
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*/
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//! @addtogroup core_hal_interface_multiply Element-wise multiply
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//! @{
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inline int hal_ni_mul8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_mul8s(const schar *src1_data, size_t src1_step, const schar *src2_data, size_t src2_step, schar *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_mul16u(const ushort *src1_data, size_t src1_step, const ushort *src2_data, size_t src2_step, ushort *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_mul16s(const short *src1_data, size_t src1_step, const short *src2_data, size_t src2_step, short *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_mul32s(const int *src1_data, size_t src1_step, const int *src2_data, size_t src2_step, int *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_mul32f(const float *src1_data, size_t src1_step, const float *src2_data, size_t src2_step, float *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_mul64f(const double *src1_data, size_t src1_step, const double *src2_data, size_t src2_step, double *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
/**
|
|
Divide: _dst[i] = scale * src1[i] / src2[i]_
|
|
@param src1_data,src1_step first source image data and step
|
|
@param src2_data,src2_step second source image data and step
|
|
@param dst_data,dst_step destination image data and step
|
|
@param width,height dimensions of the images
|
|
@param scale additional multiplier
|
|
*/
|
|
//! @addtogroup core_hal_interface_divide Element-wise divide
|
|
//! @{
|
|
inline int hal_ni_div8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_div8s(const schar *src1_data, size_t src1_step, const schar *src2_data, size_t src2_step, schar *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_div16u(const ushort *src1_data, size_t src1_step, const ushort *src2_data, size_t src2_step, ushort *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_div16s(const short *src1_data, size_t src1_step, const short *src2_data, size_t src2_step, short *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_div32s(const int *src1_data, size_t src1_step, const int *src2_data, size_t src2_step, int *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_div32f(const float *src1_data, size_t src1_step, const float *src2_data, size_t src2_step, float *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_div64f(const double *src1_data, size_t src1_step, const double *src2_data, size_t src2_step, double *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
/**
|
|
Computes reciprocial: _dst[i] = scale / src[i]_
|
|
@param src_data,src_step source image data and step
|
|
@param dst_data,dst_step destination image data and step
|
|
@param width,height dimensions of the images
|
|
@param scale additional multiplier
|
|
*/
|
|
//! @addtogroup core_hal_interface_reciprocial Element-wise reciprocial
|
|
//! @{
|
|
inline int hal_ni_recip8u(const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_recip8s(const schar *src_data, size_t src_step, schar *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_recip16u(const ushort *src_data, size_t src_step, ushort *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_recip16s(const short *src_data, size_t src_step, short *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_recip32s(const int *src_data, size_t src_step, int *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_recip32f(const float *src_data, size_t src_step, float *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_recip64f(const double *src_data, size_t src_step, double *dst_data, size_t dst_step, int width, int height, double scale) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_mul8u hal_ni_mul8u
|
|
#define cv_hal_mul8s hal_ni_mul8s
|
|
#define cv_hal_mul16u hal_ni_mul16u
|
|
#define cv_hal_mul16s hal_ni_mul16s
|
|
#define cv_hal_mul32s hal_ni_mul32s
|
|
#define cv_hal_mul32f hal_ni_mul32f
|
|
#define cv_hal_mul64f hal_ni_mul64f
|
|
#define cv_hal_div8u hal_ni_div8u
|
|
#define cv_hal_div8s hal_ni_div8s
|
|
#define cv_hal_div16u hal_ni_div16u
|
|
#define cv_hal_div16s hal_ni_div16s
|
|
#define cv_hal_div32s hal_ni_div32s
|
|
#define cv_hal_div32f hal_ni_div32f
|
|
#define cv_hal_div64f hal_ni_div64f
|
|
#define cv_hal_recip8u hal_ni_recip8u
|
|
#define cv_hal_recip8s hal_ni_recip8s
|
|
#define cv_hal_recip16u hal_ni_recip16u
|
|
#define cv_hal_recip16s hal_ni_recip16s
|
|
#define cv_hal_recip32s hal_ni_recip32s
|
|
#define cv_hal_recip32f hal_ni_recip32f
|
|
#define cv_hal_recip64f hal_ni_recip64f
|
|
//! @endcond
|
|
|
|
/**
|
|
Computes weighted sum of two arrays using formula: _dst[i] = a * src1[i] + b * src2[i] + c_
|
|
@param src1_data,src1_step first source image data and step
|
|
@param src2_data,src2_step second source image data and step
|
|
@param dst_data,dst_step destination image data and step
|
|
@param width,height dimensions of the images
|
|
@param scalars numbers _a_, _b_, and _c_
|
|
*/
|
|
//! @addtogroup core_hal_interface_addWeighted Element-wise weighted sum
|
|
//! @{
|
|
inline int hal_ni_addWeighted8u(const uchar *src1_data, size_t src1_step, const uchar *src2_data, size_t src2_step, uchar *dst_data, size_t dst_step, int width, int height, const double scalars[3]) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_addWeighted8s(const schar *src1_data, size_t src1_step, const schar *src2_data, size_t src2_step, schar *dst_data, size_t dst_step, int width, int height, const double scalars[3]) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_addWeighted16u(const ushort *src1_data, size_t src1_step, const ushort *src2_data, size_t src2_step, ushort *dst_data, size_t dst_step, int width, int height, const double scalars[3]) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_addWeighted16s(const short *src1_data, size_t src1_step, const short *src2_data, size_t src2_step, short *dst_data, size_t dst_step, int width, int height, const double scalars[3]) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_addWeighted32s(const int *src1_data, size_t src1_step, const int *src2_data, size_t src2_step, int *dst_data, size_t dst_step, int width, int height, const double scalars[3]) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_addWeighted32f(const float *src1_data, size_t src1_step, const float *src2_data, size_t src2_step, float *dst_data, size_t dst_step, int width, int height, const double scalars[3]) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_addWeighted64f(const double *src1_data, size_t src1_step, const double *src2_data, size_t src2_step, double *dst_data, size_t dst_step, int width, int height, const double scalars[3]) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_addWeighted8u hal_ni_addWeighted8u
|
|
#define cv_hal_addWeighted8s hal_ni_addWeighted8s
|
|
#define cv_hal_addWeighted16u hal_ni_addWeighted16u
|
|
#define cv_hal_addWeighted16s hal_ni_addWeighted16s
|
|
#define cv_hal_addWeighted32s hal_ni_addWeighted32s
|
|
#define cv_hal_addWeighted32f hal_ni_addWeighted32f
|
|
#define cv_hal_addWeighted64f hal_ni_addWeighted64f
|
|
//! @endcond
|
|
|
|
/**
|
|
@param src_data array of interleaved values (__len__ x __cn__ items) [ B, G, R, B, G, R, ...]
|
|
@param dst_data array of pointers to destination arrays (__cn__ items x __len__ items) [ [B, B, ...], [G, G, ...], [R, R, ...] ]
|
|
@param len number of elements
|
|
@param cn number of channels
|
|
*/
|
|
//! @addtogroup core_hal_interface_split Channel split
|
|
//! @{
|
|
inline int hal_ni_split8u(const uchar *src_data, uchar **dst_data, int len, int cn) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_split16u(const ushort *src_data, ushort **dst_data, int len, int cn) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_split32s(const int *src_data, int **dst_data, int len, int cn) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_split64s(const int64 *src_data, int64 **dst_data, int len, int cn) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_split8u hal_ni_split8u
|
|
#define cv_hal_split16u hal_ni_split16u
|
|
#define cv_hal_split32s hal_ni_split32s
|
|
#define cv_hal_split64s hal_ni_split64s
|
|
//! @endcond
|
|
|
|
/**
|
|
@param src_data array of pointers to source arrays (__cn__ items x __len__ items) [ [B, B, ...], [G, G, ...], [R, R, ...] ]
|
|
@param dst_data destination array of interleaved values (__len__ x __cn__ items) [ B, G, R, B, G, R, ...]
|
|
@param len number of elements
|
|
@param cn number of channels
|
|
*/
|
|
//! @addtogroup core_hal_interface_merge Channel merge
|
|
//! @{
|
|
inline int hal_ni_merge8u(const uchar **src_data, uchar *dst_data, int len, int cn) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_merge16u(const ushort **src_data, ushort *dst_data, int len, int cn) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_merge32s(const int **src_data, int *dst_data, int len, int cn) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_merge64s(const int64 **src_data, int64 *dst_data, int len, int cn) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_merge8u hal_ni_merge8u
|
|
#define cv_hal_merge16u hal_ni_merge16u
|
|
#define cv_hal_merge32s hal_ni_merge32s
|
|
#define cv_hal_merge64s hal_ni_merge64s
|
|
//! @endcond
|
|
|
|
|
|
/**
|
|
@param y,x source Y and X arrays
|
|
@param dst destination array
|
|
@param len length of arrays
|
|
@param angleInDegrees if set to true return angles in degrees, otherwise in radians
|
|
*/
|
|
//! @addtogroup core_hal_interface_fastAtan Atan calculation
|
|
//! @{
|
|
inline int hal_ni_fastAtan32f(const float* y, const float* x, float* dst, int len, bool angleInDegrees) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_fastAtan64f(const double* y, const double* x, double* dst, int len, bool angleInDegrees) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_fastAtan32f hal_ni_fastAtan32f
|
|
#define cv_hal_fastAtan64f hal_ni_fastAtan64f
|
|
//! @endcond
|
|
|
|
|
|
/**
|
|
@param x,y source X and Y arrays
|
|
@param dst destination array
|
|
@param len length of arrays
|
|
*/
|
|
//! @addtogroup core_hal_interface_magnitude Magnitude calculation
|
|
//! @{
|
|
inline int hal_ni_magnitude32f(const float *x, const float *y, float *dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_magnitude64f(const double *x, const double *y, double *dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_magnitude32f hal_ni_magnitude32f
|
|
#define cv_hal_magnitude64f hal_ni_magnitude64f
|
|
//! @endcond
|
|
|
|
|
|
/**
|
|
@param src source array
|
|
@param dst destination array
|
|
@param len length of arrays
|
|
*/
|
|
//! @addtogroup core_hal_interface_invSqrt Inverse square root calculation
|
|
//! @{
|
|
inline int hal_ni_invSqrt32f(const float* src, float* dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_invSqrt64f(const double* src, double* dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_invSqrt32f hal_ni_invSqrt32f
|
|
#define cv_hal_invSqrt64f hal_ni_invSqrt64f
|
|
//! @endcond
|
|
|
|
|
|
/**
|
|
@param src source array
|
|
@param dst destination array
|
|
@param len length of arrays
|
|
*/
|
|
//! @addtogroup core_hal_interface_sqrt Square root calculation
|
|
//! @{
|
|
inline int hal_ni_sqrt32f(const float* src, float* dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_sqrt64f(const double* src, double* dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_sqrt32f hal_ni_sqrt32f
|
|
#define cv_hal_sqrt64f hal_ni_sqrt64f
|
|
//! @endcond
|
|
|
|
|
|
/**
|
|
@param src source array
|
|
@param dst destination array
|
|
@param len length of arrays
|
|
*/
|
|
//! @addtogroup core_hal_interface_log Natural logarithm calculation
|
|
//! @{
|
|
inline int hal_ni_log32f(const float* src, float* dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_log64f(const double* src, double* dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_log32f hal_ni_log32f
|
|
#define cv_hal_log64f hal_ni_log64f
|
|
//! @endcond
|
|
|
|
|
|
/**
|
|
@param src source array
|
|
@param dst destination array
|
|
@param len length of arrays
|
|
*/
|
|
//! @addtogroup core_hal_interface_exp Exponent calculation
|
|
//! @{
|
|
inline int hal_ni_exp32f(const float* src, float* dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
inline int hal_ni_exp64f(const double* src, double* dst, int len) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
//! @}
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_exp32f hal_ni_exp32f
|
|
#define cv_hal_exp64f hal_ni_exp64f
|
|
//! @endcond
|
|
|
|
|
|
/**
|
|
@brief Dummy structure storing DFT/DCT context
|
|
|
|
Users can convert this pointer to any type they want. Initialisation and destruction should be made in Init and Free function implementations correspondingly.
|
|
Example:
|
|
@code{.cpp}
|
|
int my_hal_dftInit2D(cvhalDFT **context, ...) {
|
|
*context = static_cast<cvhalDFT*>(new MyFilterData());
|
|
//... init
|
|
}
|
|
|
|
int my_hal_dftFree2D(cvhalDFT *context) {
|
|
MyFilterData *c = static_cast<MyFilterData*>(context);
|
|
delete c;
|
|
}
|
|
@endcode
|
|
*/
|
|
struct cvhalDFT {};
|
|
|
|
/**
|
|
@param context double pointer to context storing all necessary data
|
|
@param len transformed array length
|
|
@param count estimated transformation count
|
|
@param depth array type (CV_32F or CV_64F)
|
|
@param flags algorithm options (combination of CV_HAL_DFT_INVERSE, CV_HAL_DFT_SCALE, ...)
|
|
@param needBuffer pointer to boolean variable, if valid pointer provided, then variable value should be set to true to signal that additional memory buffer is needed for operations
|
|
*/
|
|
inline int hal_ni_dftInit1D(cvhalDFT **context, int len, int count, int depth, int flags, bool *needBuffer) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
/**
|
|
@param context pointer to context storing all necessary data
|
|
@param src source data
|
|
@param dst destination data
|
|
*/
|
|
inline int hal_ni_dft1D(cvhalDFT *context, const uchar *src, uchar *dst) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
/**
|
|
@param context pointer to context storing all necessary data
|
|
*/
|
|
inline int hal_ni_dftFree1D(cvhalDFT *context) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_dftInit1D hal_ni_dftInit1D
|
|
#define cv_hal_dft1D hal_ni_dft1D
|
|
#define cv_hal_dftFree1D hal_ni_dftFree1D
|
|
//! @endcond
|
|
|
|
/**
|
|
@param context double pointer to context storing all necessary data
|
|
@param width,height image dimensions
|
|
@param depth image type (CV_32F or CV64F)
|
|
@param src_channels number of channels in input image
|
|
@param dst_channels number of channels in output image
|
|
@param flags algorithm options (combination of CV_HAL_DFT_INVERSE, ...)
|
|
@param nonzero_rows number of nonzero rows in image, can be used for optimization
|
|
*/
|
|
inline int hal_ni_dftInit2D(cvhalDFT **context, int width, int height, int depth, int src_channels, int dst_channels, int flags, int nonzero_rows) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
/**
|
|
@param context pointer to context storing all necessary data
|
|
@param src_data,src_step source image data and step
|
|
@param dst_data,dst_step destination image data and step
|
|
*/
|
|
inline int hal_ni_dft2D(cvhalDFT *context, const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
/**
|
|
@param context pointer to context storing all necessary data
|
|
*/
|
|
inline int hal_ni_dftFree2D(cvhalDFT *context) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_dftInit2D hal_ni_dftInit2D
|
|
#define cv_hal_dft2D hal_ni_dft2D
|
|
#define cv_hal_dftFree2D hal_ni_dftFree2D
|
|
//! @endcond
|
|
|
|
/**
|
|
@param context double pointer to context storing all necessary data
|
|
@param width,height image dimensions
|
|
@param depth image type (CV_32F or CV64F)
|
|
@param flags algorithm options (combination of CV_HAL_DFT_INVERSE, ...)
|
|
*/
|
|
inline int hal_ni_dctInit2D(cvhalDFT **context, int width, int height, int depth, int flags) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
/**
|
|
@param context pointer to context storing all necessary data
|
|
@param src_data,src_step source image data and step
|
|
@param dst_data,dst_step destination image data and step
|
|
*/
|
|
inline int hal_ni_dct2D(cvhalDFT *context, const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
/**
|
|
@param context pointer to context storing all necessary data
|
|
*/
|
|
inline int hal_ni_dctFree2D(cvhalDFT *context) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
|
|
|
|
//! @cond IGNORED
|
|
#define cv_hal_dctInit2D hal_ni_dctInit2D
|
|
#define cv_hal_dct2D hal_ni_dct2D
|
|
#define cv_hal_dctFree2D hal_ni_dctFree2D
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//! @endcond
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/**
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Performs \f$LU\f$ decomposition of square matrix \f$A=P*L*U\f$ (where \f$P\f$ is permutation matrix) and solves matrix equation \f$A*X=B\f$.
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Function returns the \f$sign\f$ of permutation \f$P\f$ via parameter info.
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@param src1 pointer to input matrix \f$A\f$ stored in row major order. After finish of work src1 contains at least \f$U\f$ part of \f$LU\f$
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decomposition which is appropriate for determainant calculation: \f$det(A)=sign*\prod_{j=1}^{M}a_{jj}\f$.
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@param src1_step number of bytes between two consequent rows of matrix \f$A\f$.
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@param m size of square matrix \f$A\f$.
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@param src2 pointer to \f$M\times N\f$ matrix \f$B\f$ which is the right-hand side of system \f$A*X=B\f$. \f$B\f$ stored in row major order.
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If src2 is null pointer only \f$LU\f$ decomposition will be performed. After finish of work src2 contains solution \f$X\f$ of system \f$A*X=B\f$.
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@param src2_step number of bytes between two consequent rows of matrix \f$B\f$.
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@param n number of right-hand vectors in \f$M\times N\f$ matrix \f$B\f$.
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@param info indicates success of decomposition. If *info is equals to zero decomposition failed, othervise *info is equals to \f$sign\f$.
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*/
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//! @addtogroup core_hal_interface_decomp_lu LU matrix decomposition
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//! @{
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inline int hal_ni_LU32f(float* src1, size_t src1_step, int m, float* src2, size_t src2_step, int n, int* info) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_LU64f(double* src1, size_t src1_step, int m, double* src2, size_t src2_step, int n, int* info) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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/**
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Performs Cholesky decomposition of matrix \f$A = L*L^T\f$ and solves matrix equation \f$A*X=B\f$.
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@param src1 pointer to input matrix \f$A\f$ stored in row major order. After finish of work src1 contains lower triangular matrix \f$L\f$.
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@param src1_step number of bytes between two consequent rows of matrix \f$A\f$.
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@param m size of square matrix \f$A\f$.
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@param src2 pointer to \f$M\times N\f$ matrix \f$B\f$ which is the right-hand side of system \f$A*X=B\f$. B stored in row major order.
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If src2 is null pointer only Cholesky decomposition will be performed. After finish of work src2 contains solution \f$X\f$ of system \f$A*X=B\f$.
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@param src2_step number of bytes between two consequent rows of matrix \f$B\f$.
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@param n number of right-hand vectors in \f$M\times N\f$ matrix \f$B\f$.
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@param info indicates success of decomposition. If *info is false decomposition failed.
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*/
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//! @addtogroup core_hal_interface_decomp_cholesky Cholesky matrix decomposition
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//! @{
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inline int hal_ni_Cholesky32f(float* src1, size_t src1_step, int m, float* src2, size_t src2_step, int n, bool* info) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_Cholesky64f(double* src1, size_t src1_step, int m, double* src2, size_t src2_step, int n, bool* info) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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/**
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Performs singular value decomposition of \f$M\times N\f$(\f$M>N\f$) matrix \f$A = U*\Sigma*V^T\f$.
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@param src pointer to input \f$M\times N\f$ matrix \f$A\f$ stored in column major order.
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After finish of work src will be filled with rows of \f$U\f$ or not modified (depends of flag CV_HAL_SVD_MODIFY_A).
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@param src_step number of bytes between two consequent columns of matrix \f$A\f$.
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@param w pointer to array for singular values of matrix \f$A\f$ (i. e. first \f$N\f$ diagonal elements of matrix \f$\Sigma\f$).
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@param u pointer to output \f$M\times N\f$ or \f$M\times M\f$ matrix \f$U\f$ (size depends of flags). Pointer must be valid if flag CV_HAL_SVD_MODIFY_A not used.
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@param u_step number of bytes between two consequent rows of matrix \f$U\f$.
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@param vt pointer to array for \f$N\times N\f$ matrix \f$V^T\f$.
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@param vt_step number of bytes between two consequent rows of matrix \f$V^T\f$.
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@param m number fo rows in matrix \f$A\f$.
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@param n number of columns in matrix \f$A\f$.
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@param flags algorithm options (combination of CV_HAL_SVD_FULL_UV, ...).
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*/
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//! @addtogroup core_hal_interface_decomp_svd Singular value matrix decomposition
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//! @{
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inline int hal_ni_SVD32f(float* src, size_t src_step, float* w, float* u, size_t u_step, float* vt, size_t vt_step, int m, int n, int flags) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_SVD64f(double* src, size_t src_step, double* w, double* u, size_t u_step, double* vt, size_t vt_step, int m, int n, int flags) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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/**
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Performs QR decomposition of \f$M\times N\f$(\f$M>N\f$) matrix \f$A = Q*R\f$ and solves matrix equation \f$A*X=B\f$.
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@param src1 pointer to input matrix \f$A\f$ stored in row major order. After finish of work src1 contains upper triangular \f$N\times N\f$ matrix \f$R\f$.
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Lower triangle of src1 will be filled with vectors of elementary reflectors. See @cite VandLec and Lapack's DGEQRF documentation for details.
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@param src1_step number of bytes between two consequent rows of matrix \f$A\f$.
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@param m number fo rows in matrix \f$A\f$.
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@param n number of columns in matrix \f$A\f$.
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@param k number of right-hand vectors in \f$M\times K\f$ matrix \f$B\f$.
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@param src2 pointer to \f$M\times K\f$ matrix \f$B\f$ which is the right-hand side of system \f$A*X=B\f$. \f$B\f$ stored in row major order.
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If src2 is null pointer only QR decomposition will be performed. Otherwise system will be solved and src1 will be used as temporary buffer, so
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after finish of work src2 contains solution \f$X\f$ of system \f$A*X=B\f$.
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@param src2_step number of bytes between two consequent rows of matrix \f$B\f$.
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@param dst pointer to continiuos \f$N\times 1\f$ array for scalar factors of elementary reflectors. See @cite VandLec for details.
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@param info indicates success of decomposition. If *info is zero decomposition failed.
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*/
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//! @addtogroup core_hal_interface_decomp_qr QR matrix decomposition
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//! @{
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inline int hal_ni_QR32f(float* src1, size_t src1_step, int m, int n, int k, float* src2, size_t src2_step, float* dst, int* info) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_QR64f(double* src1, size_t src1_step, int m, int n, int k, double* src2, size_t src2_step, double* dst, int* info) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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//! @cond IGNORED
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#define cv_hal_LU32f hal_ni_LU32f
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#define cv_hal_LU64f hal_ni_LU64f
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#define cv_hal_Cholesky32f hal_ni_Cholesky32f
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#define cv_hal_Cholesky64f hal_ni_Cholesky64f
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#define cv_hal_SVD32f hal_ni_SVD32f
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#define cv_hal_SVD64f hal_ni_SVD64f
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#define cv_hal_QR32f hal_ni_QR32f
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#define cv_hal_QR64f hal_ni_QR64f
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//! @endcond
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/**
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The function performs generalized matrix multiplication similar to the gemm functions in BLAS level 3:
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\f$D = \alpha*AB+\beta*C\f$
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@param src1 pointer to input \f$M\times N\f$ matrix \f$A\f$ or \f$A^T\f$ stored in row major order.
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@param src1_step number of bytes between two consequent rows of matrix \f$A\f$ or \f$A^T\f$.
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@param src2 pointer to input \f$N\times K\f$ matrix \f$B\f$ or \f$B^T\f$ stored in row major order.
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@param src2_step number of bytes between two consequent rows of matrix \f$B\f$ or \f$B^T\f$.
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@param alpha \f$\alpha\f$ multiplier before \f$AB\f$
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@param src3 pointer to input \f$M\times K\f$ matrix \f$C\f$ or \f$C^T\f$ stored in row major order.
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@param src3_step number of bytes between two consequent rows of matrix \f$C\f$ or \f$C^T\f$.
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@param beta \f$\beta\f$ multiplier before \f$C\f$
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@param dst pointer to input \f$M\times K\f$ matrix \f$D\f$ stored in row major order.
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@param dst_step number of bytes between two consequent rows of matrix \f$D\f$.
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@param m number of rows in matrix \f$A\f$ or \f$A^T\f$, equals to number of rows in matrix \f$D\f$
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@param n number of columns in matrix \f$A\f$ or \f$A^T\f$
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@param k number of columns in matrix \f$B\f$ or \f$B^T\f$, equals to number of columns in matrix \f$D\f$
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@param flags algorithm options (combination of CV_HAL_GEMM_1_T, ...).
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*/
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//! @addtogroup core_hal_interface_matrix_multiplication Matrix multiplication
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//! @{
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inline int hal_ni_gemm32f(const float* src1, size_t src1_step, const float* src2, size_t src2_step,
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float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step,
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int m, int n, int k, int flags) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_gemm64f(const double* src1, size_t src1_step, const double* src2, size_t src2_step,
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double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step,
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int m, int n, int k, int flags) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_gemm32fc(const float* src1, size_t src1_step, const float* src2, size_t src2_step,
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float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step,
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int m, int n, int k, int flags) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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inline int hal_ni_gemm64fc(const double* src1, size_t src1_step, const double* src2, size_t src2_step,
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double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step,
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int m, int n, int k, int flags) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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//! @}
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//! @cond IGNORED
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#define cv_hal_gemm32f hal_ni_gemm32f
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#define cv_hal_gemm64f hal_ni_gemm64f
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|
#define cv_hal_gemm32fc hal_ni_gemm32fc
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|
#define cv_hal_gemm64fc hal_ni_gemm64fc
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//! @endcond
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/**
|
|
@brief Finds the global minimum and maximum in an array.
|
|
@param src_data,src_step Source image
|
|
@param width,height Source image dimensions
|
|
@param depth Depth of source image
|
|
@param minVal,maxVal Pointer to the returned global minimum and maximum in an array.
|
|
@param minIdx,maxIdx Pointer to the returned minimum and maximum location.
|
|
@param mask Specified array region.
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|
*/
|
|
inline int hal_ni_minMaxIdx(const uchar* src_data, size_t src_step, int width, int height, int depth, double* minVal, double* maxVal,
|
|
int* minIdx, int* maxIdx, uchar* mask) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
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|
//! @cond IGNORED
|
|
#define cv_hal_minMaxIdx hal_ni_minMaxIdx
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|
//! @endcond
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|
//! @}
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|
#if defined __GNUC__
|
|
# pragma GCC diagnostic pop
|
|
#elif defined _MSC_VER
|
|
# pragma warning( pop )
|
|
#endif
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|
|
#include "hal_internal.hpp"
|
|
#include "custom_hal.hpp"
|
|
|
|
//! @cond IGNORED
|
|
#define CALL_HAL_RET(name, fun, retval, ...) \
|
|
{ \
|
|
int res = __CV_EXPAND(fun(__VA_ARGS__, &retval)); \
|
|
if (res == CV_HAL_ERROR_OK) \
|
|
return retval; \
|
|
else if (res != CV_HAL_ERROR_NOT_IMPLEMENTED) \
|
|
CV_Error_(cv::Error::StsInternal, \
|
|
("HAL implementation " CVAUX_STR(name) " ==> " CVAUX_STR(fun) " returned %d (0x%08x)", res, res)); \
|
|
}
|
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|
|
|
#define CALL_HAL(name, fun, ...) \
|
|
{ \
|
|
int res = __CV_EXPAND(fun(__VA_ARGS__)); \
|
|
if (res == CV_HAL_ERROR_OK) \
|
|
return; \
|
|
else if (res != CV_HAL_ERROR_NOT_IMPLEMENTED) \
|
|
CV_Error_(cv::Error::StsInternal, \
|
|
("HAL implementation " CVAUX_STR(name) " ==> " CVAUX_STR(fun) " returned %d (0x%08x)", res, res)); \
|
|
}
|
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//! @endcond
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|
#endif
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