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255 lines
8.0 KiB
C++
255 lines
8.0 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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// 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/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/private.hpp"
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#include "opencv2/core/private.cuda.hpp"
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#include "opencv2/core/ocl.hpp"
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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 <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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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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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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BinaryFunc getConvertFunc(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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// -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 char* g_HersheyGlyphs[];
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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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#if defined WIN32 || defined _WIN32
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void deleteThreadAllocData();
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void deleteThreadData();
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#endif
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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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inline Size getContinuousSize( const Mat& m1, int widthScale=1 )
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{
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return m1.isContinuous() ? Size(m1.cols*m1.rows*widthScale, 1) :
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Size(m1.cols*widthScale, m1.rows);
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}
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inline Size getContinuousSize( const Mat& m1, const Mat& m2, int widthScale=1 )
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{
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return (m1.flags & m2.flags & Mat::CONTINUOUS_FLAG) != 0 ?
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Size(m1.cols*m1.rows*widthScale, 1) : Size(m1.cols*widthScale, m1.rows);
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}
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inline Size getContinuousSize( const Mat& m1, const Mat& m2,
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const Mat& m3, int widthScale=1 )
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{
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return (m1.flags & m2.flags & m3.flags & Mat::CONTINUOUS_FLAG) != 0 ?
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Size(m1.cols*m1.rows*widthScale, 1) : Size(m1.cols*widthScale, m1.rows);
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}
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inline Size getContinuousSize( const Mat& m1, const Mat& m2,
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const Mat& m3, const Mat& m4,
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int widthScale=1 )
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{
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return (m1.flags & m2.flags & m3.flags & m4.flags & Mat::CONTINUOUS_FLAG) != 0 ?
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Size(m1.cols*m1.rows*widthScale, 1) : Size(m1.cols*widthScale, m1.rows);
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}
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inline Size getContinuousSize( const Mat& m1, const Mat& m2,
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const Mat& m3, const Mat& m4,
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const Mat& m5, int widthScale=1 )
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{
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return (m1.flags & m2.flags & m3.flags & m4.flags & m5.flags & Mat::CONTINUOUS_FLAG) != 0 ?
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Size(m1.cols*m1.rows*widthScale, 1) : Size(m1.cols*widthScale, m1.rows);
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}
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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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extern volatile bool USE_SSE2;
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extern volatile bool USE_SSE4_2;
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extern volatile bool USE_AVX;
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enum { BLOCK_SIZE = 1024 };
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#if defined HAVE_IPP && (IPP_VERSION_MAJOR >= 7)
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#define ARITHM_USE_IPP 1
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#define IF_IPP(then_call, else_call) then_call
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#else
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#define ARITHM_USE_IPP 0
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#define IF_IPP(then_call, else_call) else_call
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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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struct TLSData
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{
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TLSData();
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RNG rng;
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int device;
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ocl::Queue oclQueue;
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int useOpenCL; // 1 - use, 0 - do not use, -1 - auto/not initialized
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static TLSData* get();
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};
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namespace ocl
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{
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MatAllocator* getOpenCLAllocator();
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}
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}
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#endif /*_CXCORE_INTERNAL_H_*/
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