Open Source Computer Vision Library
https://opencv.org/
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401 lines
12 KiB
401 lines
12 KiB
/*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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// 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_PRECOMP_H__ |
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#define __OPENCV_PRECOMP_H__ |
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#include "opencv2/opencv_modules.hpp" |
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#include "cvconfig.h" |
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#include "opencv2/core/utility.hpp" |
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#include "opencv2/core/core_c.h" |
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#include "opencv2/core/cuda.hpp" |
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#include "opencv2/core/opengl.hpp" |
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#include "opencv2/core/va_intel.hpp" |
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#include "opencv2/core/private.hpp" |
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#include "opencv2/core/private.cuda.hpp" |
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#ifdef HAVE_OPENCL |
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#include "opencv2/core/ocl.hpp" |
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#endif |
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#include <assert.h> |
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#include <ctype.h> |
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#include <float.h> |
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#include <limits.h> |
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#include <math.h> |
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#include <stdarg.h> |
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#include <stdio.h> |
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#include <stdlib.h> |
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#include <string.h> |
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#include <algorithm> |
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#include <cmath> |
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#include <cstdlib> |
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#include <limits> |
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#include <float.h> |
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#include <cstring> |
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#include <cassert> |
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#define USE_SSE2 (cv::checkHardwareSupport(CV_CPU_SSE2)) |
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#define USE_SSE4_2 (cv::checkHardwareSupport(CV_CPU_SSE4_2)) |
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#define USE_AVX (cv::checkHardwareSupport(CV_CPU_AVX)) |
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#define USE_AVX2 (cv::checkHardwareSupport(CV_CPU_AVX2)) |
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#include "opencv2/core/hal/hal.hpp" |
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#include "opencv2/core/hal/intrin.hpp" |
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#include "opencv2/core/sse_utils.hpp" |
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#include "opencv2/core/neon_utils.hpp" |
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#include "opencv2/core/vsx_utils.hpp" |
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#include "hal_replacement.hpp" |
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#ifdef HAVE_TEGRA_OPTIMIZATION |
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#include "opencv2/core/core_tegra.hpp" |
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#else |
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#define GET_OPTIMIZED(func) (func) |
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#endif |
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namespace cv |
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{ |
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// -128.f ... 255.f |
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extern const float g_8x32fTab[]; |
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#define CV_8TO32F(x) cv::g_8x32fTab[(x)+128] |
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extern const ushort g_8x16uSqrTab[]; |
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#define CV_SQR_8U(x) cv::g_8x16uSqrTab[(x)+255] |
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extern const uchar g_Saturate8u[]; |
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#define CV_FAST_CAST_8U(t) (assert(-256 <= (t) && (t) <= 512), cv::g_Saturate8u[(t)+256]) |
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#define CV_MIN_8U(a,b) ((a) - CV_FAST_CAST_8U((a) - (b))) |
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#define CV_MAX_8U(a,b) ((a) + CV_FAST_CAST_8U((b) - (a))) |
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template<typename T1, typename T2=T1, typename T3=T1> struct OpAdd |
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{ |
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typedef T1 type1; |
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typedef T2 type2; |
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typedef T3 rtype; |
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T3 operator ()(const T1 a, const T2 b) const { return saturate_cast<T3>(a + b); } |
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}; |
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template<typename T1, typename T2=T1, typename T3=T1> struct OpSub |
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{ |
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typedef T1 type1; |
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typedef T2 type2; |
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typedef T3 rtype; |
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T3 operator ()(const T1 a, const T2 b) const { return saturate_cast<T3>(a - b); } |
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}; |
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template<typename T1, typename T2=T1, typename T3=T1> struct OpRSub |
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{ |
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typedef T1 type1; |
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typedef T2 type2; |
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typedef T3 rtype; |
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T3 operator ()(const T1 a, const T2 b) const { return saturate_cast<T3>(b - a); } |
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}; |
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template<typename T> struct OpMin |
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{ |
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typedef T type1; |
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typedef T type2; |
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typedef T rtype; |
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T operator ()(const T a, const T b) const { return std::min(a, b); } |
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}; |
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template<typename T> struct OpMax |
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{ |
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typedef T type1; |
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typedef T type2; |
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typedef T rtype; |
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T operator ()(const T a, const T b) const { return std::max(a, b); } |
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}; |
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template<typename T> struct OpAbsDiff |
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{ |
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typedef T type1; |
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typedef T type2; |
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typedef T rtype; |
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T operator()(T a, T b) const { return a > b ? a - b : b - a; } |
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}; |
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// specializations to prevent "-0" results |
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template<> struct OpAbsDiff<float> |
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{ |
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typedef float type1; |
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typedef float type2; |
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typedef float rtype; |
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float operator()(float a, float b) const { return std::abs(a - b); } |
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}; |
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template<> struct OpAbsDiff<double> |
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{ |
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typedef double type1; |
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typedef double type2; |
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typedef double rtype; |
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double operator()(double a, double b) const { return std::abs(a - b); } |
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}; |
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template<typename T> struct OpAnd |
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{ |
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typedef T type1; |
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typedef T type2; |
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typedef T rtype; |
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T operator()( T a, T b ) const { return a & b; } |
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}; |
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template<typename T> struct OpOr |
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{ |
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typedef T type1; |
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typedef T type2; |
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typedef T rtype; |
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T operator()( T a, T b ) const { return a | b; } |
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}; |
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template<typename T> struct OpXor |
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{ |
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typedef T type1; |
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typedef T type2; |
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typedef T rtype; |
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T operator()( T a, T b ) const { return a ^ b; } |
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}; |
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template<typename T> struct OpNot |
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{ |
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typedef T type1; |
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typedef T type2; |
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typedef T rtype; |
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T operator()( T a, T ) const { return ~a; } |
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}; |
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template<> inline uchar OpAdd<uchar>::operator ()(uchar a, uchar b) const |
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{ return CV_FAST_CAST_8U(a + b); } |
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template<> inline uchar OpSub<uchar>::operator ()(uchar a, uchar b) const |
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{ return CV_FAST_CAST_8U(a - b); } |
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template<> inline short OpAbsDiff<short>::operator ()(short a, short b) const |
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{ return saturate_cast<short>(std::abs(a - b)); } |
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template<> inline schar OpAbsDiff<schar>::operator ()(schar a, schar b) const |
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{ return saturate_cast<schar>(std::abs(a - b)); } |
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template<> inline uchar OpMin<uchar>::operator ()(uchar a, uchar b) const { return CV_MIN_8U(a, b); } |
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template<> inline uchar OpMax<uchar>::operator ()(uchar a, uchar b) const { return CV_MAX_8U(a, b); } |
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typedef void (*UnaryFunc)(const uchar* src1, size_t step1, |
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uchar* dst, size_t step, Size sz, |
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void*); |
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typedef void (*BinaryFunc)(const uchar* src1, size_t step1, |
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const uchar* src2, size_t step2, |
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uchar* dst, size_t step, Size sz, |
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void*); |
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typedef void (*BinaryFuncC)(const uchar* src1, size_t step1, |
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const uchar* src2, size_t step2, |
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uchar* dst, size_t step, int width, int height, |
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void*); |
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BinaryFunc getConvertFunc(int sdepth, int ddepth); |
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BinaryFunc getConvertScaleFunc(int sdepth, int ddepth); |
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BinaryFunc getCopyMaskFunc(size_t esz); |
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/* default memory block for sparse array elements */ |
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#define CV_SPARSE_MAT_BLOCK (1<<12) |
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/* initial hash table size */ |
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#define CV_SPARSE_HASH_SIZE0 (1<<10) |
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/* maximal average node_count/hash_size ratio beyond which hash table is resized */ |
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#define CV_SPARSE_HASH_RATIO 3 |
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// There is some mess in code with vectors representation. |
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// Both vector-column / vector-rows are used with dims=2 (as Mat2D always). |
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// Reshape matrices if necessary (in case of vectors) and returns size with scaled width. |
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Size getContinuousSize2D(Mat& m1, int widthScale=1); |
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Size getContinuousSize2D(Mat& m1, Mat& m2, int widthScale=1); |
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Size getContinuousSize2D(Mat& m1, Mat& m2, Mat& m3, int widthScale=1); |
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void setSize( Mat& m, int _dims, const int* _sz, const size_t* _steps, bool autoSteps=false ); |
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void finalizeHdr(Mat& m); |
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int updateContinuityFlag(int flags, int dims, const int* size, const size_t* step); |
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struct NoVec |
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{ |
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size_t operator()(const void*, const void*, void*, size_t) const { return 0; } |
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}; |
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#define CV_SPLIT_MERGE_MAX_BLOCK_SIZE(cn) ((INT_MAX/4)/(cn)) // HAL implementation accepts 'int' len, so INT_MAX doesn't work here |
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enum { BLOCK_SIZE = 1024 }; |
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#if defined HAVE_IPP && (IPP_VERSION_X100 >= 700) |
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#define ARITHM_USE_IPP 1 |
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#else |
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#define ARITHM_USE_IPP 0 |
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#endif |
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inline bool checkScalar(const Mat& sc, int atype, int sckind, int akind) |
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{ |
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if( sc.dims > 2 || !sc.isContinuous() ) |
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return false; |
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Size sz = sc.size(); |
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if(sz.width != 1 && sz.height != 1) |
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return false; |
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int cn = CV_MAT_CN(atype); |
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if( akind == _InputArray::MATX && sckind != _InputArray::MATX ) |
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return false; |
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return sz == Size(1, 1) || sz == Size(1, cn) || sz == Size(cn, 1) || |
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(sz == Size(1, 4) && sc.type() == CV_64F && cn <= 4); |
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} |
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inline bool checkScalar(InputArray sc, int atype, int sckind, int akind) |
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{ |
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if( sc.dims() > 2 || !sc.isContinuous() ) |
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return false; |
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Size sz = sc.size(); |
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if(sz.width != 1 && sz.height != 1) |
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return false; |
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int cn = CV_MAT_CN(atype); |
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if( akind == _InputArray::MATX && sckind != _InputArray::MATX ) |
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return false; |
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return sz == Size(1, 1) || sz == Size(1, cn) || sz == Size(cn, 1) || |
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(sz == Size(1, 4) && sc.type() == CV_64F && cn <= 4); |
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} |
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void convertAndUnrollScalar( const Mat& sc, int buftype, uchar* scbuf, size_t blocksize ); |
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#ifdef CV_COLLECT_IMPL_DATA |
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struct ImplCollector |
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{ |
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ImplCollector() |
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{ |
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useCollection = false; |
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implFlags = 0; |
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} |
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bool useCollection; // enable/disable impl data collection |
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int implFlags; |
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std::vector<int> implCode; |
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std::vector<String> implFun; |
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cv::Mutex mutex; |
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}; |
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#endif |
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struct CoreTLSData |
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{ |
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CoreTLSData() : |
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//#ifdef HAVE_OPENCL |
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device(0), useOpenCL(-1), |
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//#endif |
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useIPP(-1), |
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useIPP_NE(-1) |
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#ifdef HAVE_TEGRA_OPTIMIZATION |
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,useTegra(-1) |
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#endif |
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#ifdef HAVE_OPENVX |
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,useOpenVX(-1) |
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#endif |
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{} |
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RNG rng; |
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//#ifdef HAVE_OPENCL |
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int device; // device index of an array of devices in a context, see also Device::getDefault |
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ocl::Queue oclQueue; // the queue used for running a kernel, see also getQueue, Kernel::run |
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int useOpenCL; // 1 - use, 0 - do not use, -1 - auto/not initialized |
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//#endif |
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int useIPP; // 1 - use, 0 - do not use, -1 - auto/not initialized |
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int useIPP_NE; // 1 - use, 0 - do not use, -1 - auto/not initialized |
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#ifdef HAVE_TEGRA_OPTIMIZATION |
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int useTegra; // 1 - use, 0 - do not use, -1 - auto/not initialized |
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#endif |
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#ifdef HAVE_OPENVX |
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int useOpenVX; // 1 - use, 0 - do not use, -1 - auto/not initialized |
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#endif |
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}; |
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CoreTLSData& getCoreTlsData(); |
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#if defined(BUILD_SHARED_LIBS) |
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#if defined _WIN32 || defined WINCE |
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#define CL_RUNTIME_EXPORT __declspec(dllexport) |
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#elif defined __GNUC__ && __GNUC__ >= 4 |
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#define CL_RUNTIME_EXPORT __attribute__ ((visibility ("default"))) |
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#else |
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#define CL_RUNTIME_EXPORT |
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#endif |
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#else |
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#define CL_RUNTIME_EXPORT |
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#endif |
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extern CV_EXPORTS |
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bool __termination; // skip some cleanups, because process is terminating |
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// (for example, if ExitProcess() was already called) |
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cv::Mutex& getInitializationMutex(); |
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/// @brief Returns timestamp in nanoseconds since program launch |
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int64 getTimestampNS(); |
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// TODO Memory barriers? |
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#define CV_SINGLETON_LAZY_INIT_(TYPE, INITIALIZER, RET_VALUE) \ |
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static TYPE* volatile instance = NULL; \ |
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if (instance == NULL) \ |
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{ \ |
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cv::AutoLock lock(cv::getInitializationMutex()); \ |
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if (instance == NULL) \ |
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instance = INITIALIZER; \ |
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} \ |
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return RET_VALUE; |
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#define CV_SINGLETON_LAZY_INIT(TYPE, INITIALIZER) CV_SINGLETON_LAZY_INIT_(TYPE, INITIALIZER, instance) |
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#define CV_SINGLETON_LAZY_INIT_REF(TYPE, INITIALIZER) CV_SINGLETON_LAZY_INIT_(TYPE, INITIALIZER, *instance) |
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CV_EXPORTS void releaseTlsStorageThread(); |
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int cv_snprintf(char* buf, int len, const char* fmt, ...); |
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int cv_vsnprintf(char* buf, int len, const char* fmt, va_list args); |
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} |
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#endif /*_CXCORE_INTERNAL_H_*/
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