Renesas / opencv-lib

openCV library for Renesas RZ/A

Dependents:   RZ_A2M_Mbed_samples

include/opencv2/core/mat.hpp@0:0e0631af0305, 2021-01-29 (annotated)

Committer:
RyoheiHagimoto
Date:
Fri Jan 29 04:53:38 2021 +0000
Revision:
0:0e0631af0305
copied from https://github.com/d-kato/opencv-lib.

Who changed what in which revision?

UserRevisionLine numberNew contents of line
RyoheiHagimoto 0:0e0631af0305 1 /*M///////////////////////////////////////////////////////////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 2 //
RyoheiHagimoto 0:0e0631af0305 3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
RyoheiHagimoto 0:0e0631af0305 4 //
RyoheiHagimoto 0:0e0631af0305 5 // By downloading, copying, installing or using the software you agree to this license.
RyoheiHagimoto 0:0e0631af0305 6 // If you do not agree to this license, do not download, install,
RyoheiHagimoto 0:0e0631af0305 7 // copy or use the software.
RyoheiHagimoto 0:0e0631af0305 8 //
RyoheiHagimoto 0:0e0631af0305 9 //
RyoheiHagimoto 0:0e0631af0305 10 // License Agreement
RyoheiHagimoto 0:0e0631af0305 11 // For Open Source Computer Vision Library
RyoheiHagimoto 0:0e0631af0305 12 //
RyoheiHagimoto 0:0e0631af0305 13 // Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
RyoheiHagimoto 0:0e0631af0305 14 // Copyright (C) 2009, Willow Garage Inc., all rights reserved.
RyoheiHagimoto 0:0e0631af0305 15 // Copyright (C) 2013, OpenCV Foundation, all rights reserved.
RyoheiHagimoto 0:0e0631af0305 16 // Third party copyrights are property of their respective owners.
RyoheiHagimoto 0:0e0631af0305 17 //
RyoheiHagimoto 0:0e0631af0305 18 // Redistribution and use in source and binary forms, with or without modification,
RyoheiHagimoto 0:0e0631af0305 19 // are permitted provided that the following conditions are met:
RyoheiHagimoto 0:0e0631af0305 20 //
RyoheiHagimoto 0:0e0631af0305 21 // * Redistribution's of source code must retain the above copyright notice,
RyoheiHagimoto 0:0e0631af0305 22 // this list of conditions and the following disclaimer.
RyoheiHagimoto 0:0e0631af0305 23 //
RyoheiHagimoto 0:0e0631af0305 24 // * Redistribution's in binary form must reproduce the above copyright notice,
RyoheiHagimoto 0:0e0631af0305 25 // this list of conditions and the following disclaimer in the documentation
RyoheiHagimoto 0:0e0631af0305 26 // and/or other materials provided with the distribution.
RyoheiHagimoto 0:0e0631af0305 27 //
RyoheiHagimoto 0:0e0631af0305 28 // * The name of the copyright holders may not be used to endorse or promote products
RyoheiHagimoto 0:0e0631af0305 29 // derived from this software without specific prior written permission.
RyoheiHagimoto 0:0e0631af0305 30 //
RyoheiHagimoto 0:0e0631af0305 31 // This software is provided by the copyright holders and contributors "as is" and
RyoheiHagimoto 0:0e0631af0305 32 // any express or implied warranties, including, but not limited to, the implied
RyoheiHagimoto 0:0e0631af0305 33 // warranties of merchantability and fitness for a particular purpose are disclaimed.
RyoheiHagimoto 0:0e0631af0305 34 // In no event shall the Intel Corporation or contributors be liable for any direct,
RyoheiHagimoto 0:0e0631af0305 35 // indirect, incidental, special, exemplary, or consequential damages
RyoheiHagimoto 0:0e0631af0305 36 // (including, but not limited to, procurement of substitute goods or services;
RyoheiHagimoto 0:0e0631af0305 37 // loss of use, data, or profits; or business interruption) however caused
RyoheiHagimoto 0:0e0631af0305 38 // and on any theory of liability, whether in contract, strict liability,
RyoheiHagimoto 0:0e0631af0305 39 // or tort (including negligence or otherwise) arising in any way out of
RyoheiHagimoto 0:0e0631af0305 40 // the use of this software, even if advised of the possibility of such damage.
RyoheiHagimoto 0:0e0631af0305 41 //
RyoheiHagimoto 0:0e0631af0305 42 //M*/
RyoheiHagimoto 0:0e0631af0305 43
RyoheiHagimoto 0:0e0631af0305 44 #ifndef OPENCV_CORE_MAT_HPP
RyoheiHagimoto 0:0e0631af0305 45 #define OPENCV_CORE_MAT_HPP
RyoheiHagimoto 0:0e0631af0305 46
RyoheiHagimoto 0:0e0631af0305 47 #ifndef __cplusplus
RyoheiHagimoto 0:0e0631af0305 48 # error mat.hpp header must be compiled as C++
RyoheiHagimoto 0:0e0631af0305 49 #endif
RyoheiHagimoto 0:0e0631af0305 50
RyoheiHagimoto 0:0e0631af0305 51 #include "opencv2/core/matx.hpp"
RyoheiHagimoto 0:0e0631af0305 52 #include "opencv2/core/types.hpp"
RyoheiHagimoto 0:0e0631af0305 53
RyoheiHagimoto 0:0e0631af0305 54 #include "opencv2/core/bufferpool.hpp"
RyoheiHagimoto 0:0e0631af0305 55
RyoheiHagimoto 0:0e0631af0305 56 namespace cv
RyoheiHagimoto 0:0e0631af0305 57 {
RyoheiHagimoto 0:0e0631af0305 58
RyoheiHagimoto 0:0e0631af0305 59 //! @addtogroup core_basic
RyoheiHagimoto 0:0e0631af0305 60 //! @{
RyoheiHagimoto 0:0e0631af0305 61
RyoheiHagimoto 0:0e0631af0305 62 enum { ACCESS_READ=1<<24, ACCESS_WRITE=1<<25,
RyoheiHagimoto 0:0e0631af0305 63 ACCESS_RW=3<<24, ACCESS_MASK=ACCESS_RW, ACCESS_FAST=1<<26 };
RyoheiHagimoto 0:0e0631af0305 64
RyoheiHagimoto 0:0e0631af0305 65 class CV_EXPORTS _OutputArray;
RyoheiHagimoto 0:0e0631af0305 66
RyoheiHagimoto 0:0e0631af0305 67 //////////////////////// Input/Output Array Arguments /////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 68
RyoheiHagimoto 0:0e0631af0305 69 /** @brief This is the proxy class for passing read-only input arrays into OpenCV functions.
RyoheiHagimoto 0:0e0631af0305 70
RyoheiHagimoto 0:0e0631af0305 71 It is defined as:
RyoheiHagimoto 0:0e0631af0305 72 @code
RyoheiHagimoto 0:0e0631af0305 73 typedef const _InputArray& InputArray;
RyoheiHagimoto 0:0e0631af0305 74 @endcode
RyoheiHagimoto 0:0e0631af0305 75 where _InputArray is a class that can be constructed from `Mat`, `Mat_<T>`, `Matx<T, m, n>`,
RyoheiHagimoto 0:0e0631af0305 76 `std::vector<T>`, `std::vector<std::vector<T> >` or `std::vector<Mat>`. It can also be constructed
RyoheiHagimoto 0:0e0631af0305 77 from a matrix expression.
RyoheiHagimoto 0:0e0631af0305 78
RyoheiHagimoto 0:0e0631af0305 79 Since this is mostly implementation-level class, and its interface may change in future versions, we
RyoheiHagimoto 0:0e0631af0305 80 do not describe it in details. There are a few key things, though, that should be kept in mind:
RyoheiHagimoto 0:0e0631af0305 81
RyoheiHagimoto 0:0e0631af0305 82 - When you see in the reference manual or in OpenCV source code a function that takes
RyoheiHagimoto 0:0e0631af0305 83 InputArray, it means that you can actually pass `Mat`, `Matx`, `vector<T>` etc. (see above the
RyoheiHagimoto 0:0e0631af0305 84 complete list).
RyoheiHagimoto 0:0e0631af0305 85 - Optional input arguments: If some of the input arrays may be empty, pass cv::noArray() (or
RyoheiHagimoto 0:0e0631af0305 86 simply cv::Mat() as you probably did before).
RyoheiHagimoto 0:0e0631af0305 87 - The class is designed solely for passing parameters. That is, normally you *should not*
RyoheiHagimoto 0:0e0631af0305 88 declare class members, local and global variables of this type.
RyoheiHagimoto 0:0e0631af0305 89 - If you want to design your own function or a class method that can operate of arrays of
RyoheiHagimoto 0:0e0631af0305 90 multiple types, you can use InputArray (or OutputArray) for the respective parameters. Inside
RyoheiHagimoto 0:0e0631af0305 91 a function you should use _InputArray::getMat() method to construct a matrix header for the
RyoheiHagimoto 0:0e0631af0305 92 array (without copying data). _InputArray::kind() can be used to distinguish Mat from
RyoheiHagimoto 0:0e0631af0305 93 `vector<>` etc., but normally it is not needed.
RyoheiHagimoto 0:0e0631af0305 94
RyoheiHagimoto 0:0e0631af0305 95 Here is how you can use a function that takes InputArray :
RyoheiHagimoto 0:0e0631af0305 96 @code
RyoheiHagimoto 0:0e0631af0305 97 std::vector<Point2f> vec;
RyoheiHagimoto 0:0e0631af0305 98 // points or a circle
RyoheiHagimoto 0:0e0631af0305 99 for( int i = 0; i < 30; i++ )
RyoheiHagimoto 0:0e0631af0305 100 vec.push_back(Point2f((float)(100 + 30*cos(i*CV_PI*2/5)),
RyoheiHagimoto 0:0e0631af0305 101 (float)(100 - 30*sin(i*CV_PI*2/5))));
RyoheiHagimoto 0:0e0631af0305 102 cv::transform(vec, vec, cv::Matx23f(0.707, -0.707, 10, 0.707, 0.707, 20));
RyoheiHagimoto 0:0e0631af0305 103 @endcode
RyoheiHagimoto 0:0e0631af0305 104 That is, we form an STL vector containing points, and apply in-place affine transformation to the
RyoheiHagimoto 0:0e0631af0305 105 vector using the 2x3 matrix created inline as `Matx<float, 2, 3>` instance.
RyoheiHagimoto 0:0e0631af0305 106
RyoheiHagimoto 0:0e0631af0305 107 Here is how such a function can be implemented (for simplicity, we implement a very specific case of
RyoheiHagimoto 0:0e0631af0305 108 it, according to the assertion statement inside) :
RyoheiHagimoto 0:0e0631af0305 109 @code
RyoheiHagimoto 0:0e0631af0305 110 void myAffineTransform(InputArray _src, OutputArray _dst, InputArray _m)
RyoheiHagimoto 0:0e0631af0305 111 {
RyoheiHagimoto 0:0e0631af0305 112 // get Mat headers for input arrays. This is O(1) operation,
RyoheiHagimoto 0:0e0631af0305 113 // unless _src and/or _m are matrix expressions.
RyoheiHagimoto 0:0e0631af0305 114 Mat src = _src.getMat(), m = _m.getMat();
RyoheiHagimoto 0:0e0631af0305 115 CV_Assert( src.type() == CV_32FC2 && m.type() == CV_32F && m.size() == Size(3, 2) );
RyoheiHagimoto 0:0e0631af0305 116
RyoheiHagimoto 0:0e0631af0305 117 // [re]create the output array so that it has the proper size and type.
RyoheiHagimoto 0:0e0631af0305 118 // In case of Mat it calls Mat::create, in case of STL vector it calls vector::resize.
RyoheiHagimoto 0:0e0631af0305 119 _dst.create(src.size(), src.type());
RyoheiHagimoto 0:0e0631af0305 120 Mat dst = _dst.getMat();
RyoheiHagimoto 0:0e0631af0305 121
RyoheiHagimoto 0:0e0631af0305 122 for( int i = 0; i < src.rows; i++ )
RyoheiHagimoto 0:0e0631af0305 123 for( int j = 0; j < src.cols; j++ )
RyoheiHagimoto 0:0e0631af0305 124 {
RyoheiHagimoto 0:0e0631af0305 125 Point2f pt = src.at<Point2f>(i, j);
RyoheiHagimoto 0:0e0631af0305 126 dst.at<Point2f>(i, j) = Point2f(m.at<float>(0, 0)*pt.x +
RyoheiHagimoto 0:0e0631af0305 127 m.at<float>(0, 1)*pt.y +
RyoheiHagimoto 0:0e0631af0305 128 m.at<float>(0, 2),
RyoheiHagimoto 0:0e0631af0305 129 m.at<float>(1, 0)*pt.x +
RyoheiHagimoto 0:0e0631af0305 130 m.at<float>(1, 1)*pt.y +
RyoheiHagimoto 0:0e0631af0305 131 m.at<float>(1, 2));
RyoheiHagimoto 0:0e0631af0305 132 }
RyoheiHagimoto 0:0e0631af0305 133 }
RyoheiHagimoto 0:0e0631af0305 134 @endcode
RyoheiHagimoto 0:0e0631af0305 135 There is another related type, InputArrayOfArrays, which is currently defined as a synonym for
RyoheiHagimoto 0:0e0631af0305 136 InputArray:
RyoheiHagimoto 0:0e0631af0305 137 @code
RyoheiHagimoto 0:0e0631af0305 138 typedef InputArray InputArrayOfArrays;
RyoheiHagimoto 0:0e0631af0305 139 @endcode
RyoheiHagimoto 0:0e0631af0305 140 It denotes function arguments that are either vectors of vectors or vectors of matrices. A separate
RyoheiHagimoto 0:0e0631af0305 141 synonym is needed to generate Python/Java etc. wrappers properly. At the function implementation
RyoheiHagimoto 0:0e0631af0305 142 level their use is similar, but _InputArray::getMat(idx) should be used to get header for the
RyoheiHagimoto 0:0e0631af0305 143 idx-th component of the outer vector and _InputArray::size().area() should be used to find the
RyoheiHagimoto 0:0e0631af0305 144 number of components (vectors/matrices) of the outer vector.
RyoheiHagimoto 0:0e0631af0305 145 */
RyoheiHagimoto 0:0e0631af0305 146 class CV_EXPORTS _InputArray
RyoheiHagimoto 0:0e0631af0305 147 {
RyoheiHagimoto 0:0e0631af0305 148 public:
RyoheiHagimoto 0:0e0631af0305 149 enum {
RyoheiHagimoto 0:0e0631af0305 150 KIND_SHIFT = 16,
RyoheiHagimoto 0:0e0631af0305 151 FIXED_TYPE = 0x8000 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 152 FIXED_SIZE = 0x4000 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 153 KIND_MASK = 31 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 154
RyoheiHagimoto 0:0e0631af0305 155 NONE = 0 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 156 MAT = 1 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 157 MATX = 2 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 158 STD_VECTOR = 3 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 159 STD_VECTOR_VECTOR = 4 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 160 STD_VECTOR_MAT = 5 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 161 EXPR = 6 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 162 OPENGL_BUFFER = 7 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 163 CUDA_HOST_MEM = 8 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 164 CUDA_GPU_MAT = 9 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 165 UMAT =10 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 166 STD_VECTOR_UMAT =11 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 167 STD_BOOL_VECTOR =12 << KIND_SHIFT,
RyoheiHagimoto 0:0e0631af0305 168 STD_VECTOR_CUDA_GPU_MAT = 13 << KIND_SHIFT
RyoheiHagimoto 0:0e0631af0305 169 };
RyoheiHagimoto 0:0e0631af0305 170
RyoheiHagimoto 0:0e0631af0305 171 _InputArray();
RyoheiHagimoto 0:0e0631af0305 172 _InputArray(int _flags, void* _obj);
RyoheiHagimoto 0:0e0631af0305 173 _InputArray(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 174 _InputArray(const MatExpr& expr);
RyoheiHagimoto 0:0e0631af0305 175 _InputArray(const std::vector<Mat>& vec);
RyoheiHagimoto 0:0e0631af0305 176 template<typename _Tp> _InputArray(const Mat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 177 template<typename _Tp> _InputArray(const std::vector<_Tp>& vec);
RyoheiHagimoto 0:0e0631af0305 178 _InputArray(const std::vector<bool>& vec);
RyoheiHagimoto 0:0e0631af0305 179 template<typename _Tp> _InputArray(const std::vector<std::vector<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 180 template<typename _Tp> _InputArray(const std::vector<Mat_<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 181 template<typename _Tp> _InputArray(const _Tp* vec, int n);
RyoheiHagimoto 0:0e0631af0305 182 template<typename _Tp, int m, int n> _InputArray(const Matx<_Tp, m, n>& matx);
RyoheiHagimoto 0:0e0631af0305 183 _InputArray(const double& val);
RyoheiHagimoto 0:0e0631af0305 184 _InputArray(const cuda::GpuMat& d_mat);
RyoheiHagimoto 0:0e0631af0305 185 _InputArray(const std::vector<cuda::GpuMat>& d_mat_array);
RyoheiHagimoto 0:0e0631af0305 186 _InputArray(const ogl::Buffer& buf);
RyoheiHagimoto 0:0e0631af0305 187 _InputArray(const cuda::HostMem& cuda_mem);
RyoheiHagimoto 0:0e0631af0305 188 template<typename _Tp> _InputArray(const cudev::GpuMat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 189 _InputArray(const UMat& um);
RyoheiHagimoto 0:0e0631af0305 190 _InputArray(const std::vector<UMat>& umv);
RyoheiHagimoto 0:0e0631af0305 191
RyoheiHagimoto 0:0e0631af0305 192 Mat getMat(int idx=-1) const;
RyoheiHagimoto 0:0e0631af0305 193 Mat getMat_(int idx=-1) const;
RyoheiHagimoto 0:0e0631af0305 194 UMat getUMat(int idx=-1) const;
RyoheiHagimoto 0:0e0631af0305 195 void getMatVector(std::vector<Mat>& mv) const;
RyoheiHagimoto 0:0e0631af0305 196 void getUMatVector(std::vector<UMat>& umv) const;
RyoheiHagimoto 0:0e0631af0305 197 void getGpuMatVector(std::vector<cuda::GpuMat>& gpumv) const;
RyoheiHagimoto 0:0e0631af0305 198 cuda::GpuMat getGpuMat() const;
RyoheiHagimoto 0:0e0631af0305 199 ogl::Buffer getOGlBuffer() const;
RyoheiHagimoto 0:0e0631af0305 200
RyoheiHagimoto 0:0e0631af0305 201 int getFlags() const;
RyoheiHagimoto 0:0e0631af0305 202 void* getObj() const;
RyoheiHagimoto 0:0e0631af0305 203 Size getSz() const;
RyoheiHagimoto 0:0e0631af0305 204
RyoheiHagimoto 0:0e0631af0305 205 int kind() const;
RyoheiHagimoto 0:0e0631af0305 206 int dims(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 207 int cols(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 208 int rows(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 209 Size size(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 210 int sizend(int* sz, int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 211 bool sameSize(const _InputArray& arr) const;
RyoheiHagimoto 0:0e0631af0305 212 size_t total(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 213 int type(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 214 int depth(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 215 int channels(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 216 bool isContinuous(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 217 bool isSubmatrix(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 218 bool empty() const;
RyoheiHagimoto 0:0e0631af0305 219 void copyTo(const _OutputArray& arr) const;
RyoheiHagimoto 0:0e0631af0305 220 void copyTo(const _OutputArray& arr, const _InputArray & mask) const;
RyoheiHagimoto 0:0e0631af0305 221 size_t offset(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 222 size_t step(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 223 bool isMat() const;
RyoheiHagimoto 0:0e0631af0305 224 bool isUMat() const;
RyoheiHagimoto 0:0e0631af0305 225 bool isMatVector() const;
RyoheiHagimoto 0:0e0631af0305 226 bool isUMatVector() const;
RyoheiHagimoto 0:0e0631af0305 227 bool isMatx() const;
RyoheiHagimoto 0:0e0631af0305 228 bool isVector() const;
RyoheiHagimoto 0:0e0631af0305 229 bool isGpuMatVector() const;
RyoheiHagimoto 0:0e0631af0305 230 ~_InputArray();
RyoheiHagimoto 0:0e0631af0305 231
RyoheiHagimoto 0:0e0631af0305 232 protected:
RyoheiHagimoto 0:0e0631af0305 233 int flags;
RyoheiHagimoto 0:0e0631af0305 234 void* obj;
RyoheiHagimoto 0:0e0631af0305 235 Size sz;
RyoheiHagimoto 0:0e0631af0305 236
RyoheiHagimoto 0:0e0631af0305 237 void init(int _flags, const void* _obj);
RyoheiHagimoto 0:0e0631af0305 238 void init(int _flags, const void* _obj, Size _sz);
RyoheiHagimoto 0:0e0631af0305 239 };
RyoheiHagimoto 0:0e0631af0305 240
RyoheiHagimoto 0:0e0631af0305 241
RyoheiHagimoto 0:0e0631af0305 242 /** @brief This type is very similar to InputArray except that it is used for input/output and output function
RyoheiHagimoto 0:0e0631af0305 243 parameters.
RyoheiHagimoto 0:0e0631af0305 244
RyoheiHagimoto 0:0e0631af0305 245 Just like with InputArray, OpenCV users should not care about OutputArray, they just pass `Mat`,
RyoheiHagimoto 0:0e0631af0305 246 `vector<T>` etc. to the functions. The same limitation as for `InputArray`: *Do not explicitly
RyoheiHagimoto 0:0e0631af0305 247 create OutputArray instances* applies here too.
RyoheiHagimoto 0:0e0631af0305 248
RyoheiHagimoto 0:0e0631af0305 249 If you want to make your function polymorphic (i.e. accept different arrays as output parameters),
RyoheiHagimoto 0:0e0631af0305 250 it is also not very difficult. Take the sample above as the reference. Note that
RyoheiHagimoto 0:0e0631af0305 251 _OutputArray::create() needs to be called before _OutputArray::getMat(). This way you guarantee
RyoheiHagimoto 0:0e0631af0305 252 that the output array is properly allocated.
RyoheiHagimoto 0:0e0631af0305 253
RyoheiHagimoto 0:0e0631af0305 254 Optional output parameters. If you do not need certain output array to be computed and returned to
RyoheiHagimoto 0:0e0631af0305 255 you, pass cv::noArray(), just like you would in the case of optional input array. At the
RyoheiHagimoto 0:0e0631af0305 256 implementation level, use _OutputArray::needed() to check if certain output array needs to be
RyoheiHagimoto 0:0e0631af0305 257 computed or not.
RyoheiHagimoto 0:0e0631af0305 258
RyoheiHagimoto 0:0e0631af0305 259 There are several synonyms for OutputArray that are used to assist automatic Python/Java/... wrapper
RyoheiHagimoto 0:0e0631af0305 260 generators:
RyoheiHagimoto 0:0e0631af0305 261 @code
RyoheiHagimoto 0:0e0631af0305 262 typedef OutputArray OutputArrayOfArrays;
RyoheiHagimoto 0:0e0631af0305 263 typedef OutputArray InputOutputArray;
RyoheiHagimoto 0:0e0631af0305 264 typedef OutputArray InputOutputArrayOfArrays;
RyoheiHagimoto 0:0e0631af0305 265 @endcode
RyoheiHagimoto 0:0e0631af0305 266 */
RyoheiHagimoto 0:0e0631af0305 267 class CV_EXPORTS _OutputArray : public _InputArray
RyoheiHagimoto 0:0e0631af0305 268 {
RyoheiHagimoto 0:0e0631af0305 269 public:
RyoheiHagimoto 0:0e0631af0305 270 enum
RyoheiHagimoto 0:0e0631af0305 271 {
RyoheiHagimoto 0:0e0631af0305 272 DEPTH_MASK_8U = 1 << CV_8U,
RyoheiHagimoto 0:0e0631af0305 273 DEPTH_MASK_8S = 1 << CV_8S,
RyoheiHagimoto 0:0e0631af0305 274 DEPTH_MASK_16U = 1 << CV_16U,
RyoheiHagimoto 0:0e0631af0305 275 DEPTH_MASK_16S = 1 << CV_16S,
RyoheiHagimoto 0:0e0631af0305 276 DEPTH_MASK_32S = 1 << CV_32S,
RyoheiHagimoto 0:0e0631af0305 277 DEPTH_MASK_32F = 1 << CV_32F,
RyoheiHagimoto 0:0e0631af0305 278 DEPTH_MASK_64F = 1 << CV_64F,
RyoheiHagimoto 0:0e0631af0305 279 DEPTH_MASK_ALL = (DEPTH_MASK_64F<<1)-1,
RyoheiHagimoto 0:0e0631af0305 280 DEPTH_MASK_ALL_BUT_8S = DEPTH_MASK_ALL & ~DEPTH_MASK_8S,
RyoheiHagimoto 0:0e0631af0305 281 DEPTH_MASK_FLT = DEPTH_MASK_32F + DEPTH_MASK_64F
RyoheiHagimoto 0:0e0631af0305 282 };
RyoheiHagimoto 0:0e0631af0305 283
RyoheiHagimoto 0:0e0631af0305 284 _OutputArray();
RyoheiHagimoto 0:0e0631af0305 285 _OutputArray(int _flags, void* _obj);
RyoheiHagimoto 0:0e0631af0305 286 _OutputArray(Mat& m);
RyoheiHagimoto 0:0e0631af0305 287 _OutputArray(std::vector<Mat>& vec);
RyoheiHagimoto 0:0e0631af0305 288 _OutputArray(cuda::GpuMat& d_mat);
RyoheiHagimoto 0:0e0631af0305 289 _OutputArray(std::vector<cuda::GpuMat>& d_mat);
RyoheiHagimoto 0:0e0631af0305 290 _OutputArray(ogl::Buffer& buf);
RyoheiHagimoto 0:0e0631af0305 291 _OutputArray(cuda::HostMem& cuda_mem);
RyoheiHagimoto 0:0e0631af0305 292 template<typename _Tp> _OutputArray(cudev::GpuMat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 293 template<typename _Tp> _OutputArray(std::vector<_Tp>& vec);
RyoheiHagimoto 0:0e0631af0305 294 _OutputArray(std::vector<bool>& vec);
RyoheiHagimoto 0:0e0631af0305 295 template<typename _Tp> _OutputArray(std::vector<std::vector<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 296 template<typename _Tp> _OutputArray(std::vector<Mat_<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 297 template<typename _Tp> _OutputArray(Mat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 298 template<typename _Tp> _OutputArray(_Tp* vec, int n);
RyoheiHagimoto 0:0e0631af0305 299 template<typename _Tp, int m, int n> _OutputArray(Matx<_Tp, m, n>& matx);
RyoheiHagimoto 0:0e0631af0305 300 _OutputArray(UMat& m);
RyoheiHagimoto 0:0e0631af0305 301 _OutputArray(std::vector<UMat>& vec);
RyoheiHagimoto 0:0e0631af0305 302
RyoheiHagimoto 0:0e0631af0305 303 _OutputArray(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 304 _OutputArray(const std::vector<Mat>& vec);
RyoheiHagimoto 0:0e0631af0305 305 _OutputArray(const cuda::GpuMat& d_mat);
RyoheiHagimoto 0:0e0631af0305 306 _OutputArray(const std::vector<cuda::GpuMat>& d_mat);
RyoheiHagimoto 0:0e0631af0305 307 _OutputArray(const ogl::Buffer& buf);
RyoheiHagimoto 0:0e0631af0305 308 _OutputArray(const cuda::HostMem& cuda_mem);
RyoheiHagimoto 0:0e0631af0305 309 template<typename _Tp> _OutputArray(const cudev::GpuMat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 310 template<typename _Tp> _OutputArray(const std::vector<_Tp>& vec);
RyoheiHagimoto 0:0e0631af0305 311 template<typename _Tp> _OutputArray(const std::vector<std::vector<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 312 template<typename _Tp> _OutputArray(const std::vector<Mat_<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 313 template<typename _Tp> _OutputArray(const Mat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 314 template<typename _Tp> _OutputArray(const _Tp* vec, int n);
RyoheiHagimoto 0:0e0631af0305 315 template<typename _Tp, int m, int n> _OutputArray(const Matx<_Tp, m, n>& matx);
RyoheiHagimoto 0:0e0631af0305 316 _OutputArray(const UMat& m);
RyoheiHagimoto 0:0e0631af0305 317 _OutputArray(const std::vector<UMat>& vec);
RyoheiHagimoto 0:0e0631af0305 318
RyoheiHagimoto 0:0e0631af0305 319 bool fixedSize() const;
RyoheiHagimoto 0:0e0631af0305 320 bool fixedType() const;
RyoheiHagimoto 0:0e0631af0305 321 bool needed() const;
RyoheiHagimoto 0:0e0631af0305 322 Mat& getMatRef(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 323 UMat& getUMatRef(int i=-1) const;
RyoheiHagimoto 0:0e0631af0305 324 cuda::GpuMat& getGpuMatRef() const;
RyoheiHagimoto 0:0e0631af0305 325 std::vector<cuda::GpuMat>& getGpuMatVecRef() const;
RyoheiHagimoto 0:0e0631af0305 326 ogl::Buffer& getOGlBufferRef() const;
RyoheiHagimoto 0:0e0631af0305 327 cuda::HostMem& getHostMemRef() const;
RyoheiHagimoto 0:0e0631af0305 328 void create(Size sz, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const;
RyoheiHagimoto 0:0e0631af0305 329 void create(int rows, int cols, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const;
RyoheiHagimoto 0:0e0631af0305 330 void create(int dims, const int* size, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const;
RyoheiHagimoto 0:0e0631af0305 331 void createSameSize(const _InputArray& arr, int mtype) const;
RyoheiHagimoto 0:0e0631af0305 332 void release() const;
RyoheiHagimoto 0:0e0631af0305 333 void clear() const;
RyoheiHagimoto 0:0e0631af0305 334 void setTo(const _InputArray& value, const _InputArray & mask = _InputArray()) const;
RyoheiHagimoto 0:0e0631af0305 335
RyoheiHagimoto 0:0e0631af0305 336 void assign(const UMat& u) const;
RyoheiHagimoto 0:0e0631af0305 337 void assign(const Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 338 };
RyoheiHagimoto 0:0e0631af0305 339
RyoheiHagimoto 0:0e0631af0305 340
RyoheiHagimoto 0:0e0631af0305 341 class CV_EXPORTS _InputOutputArray : public _OutputArray
RyoheiHagimoto 0:0e0631af0305 342 {
RyoheiHagimoto 0:0e0631af0305 343 public:
RyoheiHagimoto 0:0e0631af0305 344 _InputOutputArray();
RyoheiHagimoto 0:0e0631af0305 345 _InputOutputArray(int _flags, void* _obj);
RyoheiHagimoto 0:0e0631af0305 346 _InputOutputArray(Mat& m);
RyoheiHagimoto 0:0e0631af0305 347 _InputOutputArray(std::vector<Mat>& vec);
RyoheiHagimoto 0:0e0631af0305 348 _InputOutputArray(cuda::GpuMat& d_mat);
RyoheiHagimoto 0:0e0631af0305 349 _InputOutputArray(ogl::Buffer& buf);
RyoheiHagimoto 0:0e0631af0305 350 _InputOutputArray(cuda::HostMem& cuda_mem);
RyoheiHagimoto 0:0e0631af0305 351 template<typename _Tp> _InputOutputArray(cudev::GpuMat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 352 template<typename _Tp> _InputOutputArray(std::vector<_Tp>& vec);
RyoheiHagimoto 0:0e0631af0305 353 _InputOutputArray(std::vector<bool>& vec);
RyoheiHagimoto 0:0e0631af0305 354 template<typename _Tp> _InputOutputArray(std::vector<std::vector<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 355 template<typename _Tp> _InputOutputArray(std::vector<Mat_<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 356 template<typename _Tp> _InputOutputArray(Mat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 357 template<typename _Tp> _InputOutputArray(_Tp* vec, int n);
RyoheiHagimoto 0:0e0631af0305 358 template<typename _Tp, int m, int n> _InputOutputArray(Matx<_Tp, m, n>& matx);
RyoheiHagimoto 0:0e0631af0305 359 _InputOutputArray(UMat& m);
RyoheiHagimoto 0:0e0631af0305 360 _InputOutputArray(std::vector<UMat>& vec);
RyoheiHagimoto 0:0e0631af0305 361
RyoheiHagimoto 0:0e0631af0305 362 _InputOutputArray(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 363 _InputOutputArray(const std::vector<Mat>& vec);
RyoheiHagimoto 0:0e0631af0305 364 _InputOutputArray(const cuda::GpuMat& d_mat);
RyoheiHagimoto 0:0e0631af0305 365 _InputOutputArray(const std::vector<cuda::GpuMat>& d_mat);
RyoheiHagimoto 0:0e0631af0305 366 _InputOutputArray(const ogl::Buffer& buf);
RyoheiHagimoto 0:0e0631af0305 367 _InputOutputArray(const cuda::HostMem& cuda_mem);
RyoheiHagimoto 0:0e0631af0305 368 template<typename _Tp> _InputOutputArray(const cudev::GpuMat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 369 template<typename _Tp> _InputOutputArray(const std::vector<_Tp>& vec);
RyoheiHagimoto 0:0e0631af0305 370 template<typename _Tp> _InputOutputArray(const std::vector<std::vector<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 371 template<typename _Tp> _InputOutputArray(const std::vector<Mat_<_Tp> >& vec);
RyoheiHagimoto 0:0e0631af0305 372 template<typename _Tp> _InputOutputArray(const Mat_<_Tp>& m);
RyoheiHagimoto 0:0e0631af0305 373 template<typename _Tp> _InputOutputArray(const _Tp* vec, int n);
RyoheiHagimoto 0:0e0631af0305 374 template<typename _Tp, int m, int n> _InputOutputArray(const Matx<_Tp, m, n>& matx);
RyoheiHagimoto 0:0e0631af0305 375 _InputOutputArray(const UMat& m);
RyoheiHagimoto 0:0e0631af0305 376 _InputOutputArray(const std::vector<UMat>& vec);
RyoheiHagimoto 0:0e0631af0305 377 };
RyoheiHagimoto 0:0e0631af0305 378
RyoheiHagimoto 0:0e0631af0305 379 typedef const _InputArray& InputArray;
RyoheiHagimoto 0:0e0631af0305 380 typedef InputArray InputArrayOfArrays;
RyoheiHagimoto 0:0e0631af0305 381 typedef const _OutputArray& OutputArray;
RyoheiHagimoto 0:0e0631af0305 382 typedef OutputArray OutputArrayOfArrays;
RyoheiHagimoto 0:0e0631af0305 383 typedef const _InputOutputArray& InputOutputArray;
RyoheiHagimoto 0:0e0631af0305 384 typedef InputOutputArray InputOutputArrayOfArrays;
RyoheiHagimoto 0:0e0631af0305 385
RyoheiHagimoto 0:0e0631af0305 386 CV_EXPORTS InputOutputArray noArray();
RyoheiHagimoto 0:0e0631af0305 387
RyoheiHagimoto 0:0e0631af0305 388 /////////////////////////////////// MatAllocator //////////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 389
RyoheiHagimoto 0:0e0631af0305 390 //! Usage flags for allocator
RyoheiHagimoto 0:0e0631af0305 391 enum UMatUsageFlags
RyoheiHagimoto 0:0e0631af0305 392 {
RyoheiHagimoto 0:0e0631af0305 393 USAGE_DEFAULT = 0,
RyoheiHagimoto 0:0e0631af0305 394
RyoheiHagimoto 0:0e0631af0305 395 // buffer allocation policy is platform and usage specific
RyoheiHagimoto 0:0e0631af0305 396 USAGE_ALLOCATE_HOST_MEMORY = 1 << 0,
RyoheiHagimoto 0:0e0631af0305 397 USAGE_ALLOCATE_DEVICE_MEMORY = 1 << 1,
RyoheiHagimoto 0:0e0631af0305 398 USAGE_ALLOCATE_SHARED_MEMORY = 1 << 2, // It is not equal to: USAGE_ALLOCATE_HOST_MEMORY | USAGE_ALLOCATE_DEVICE_MEMORY
RyoheiHagimoto 0:0e0631af0305 399
RyoheiHagimoto 0:0e0631af0305 400 __UMAT_USAGE_FLAGS_32BIT = 0x7fffffff // Binary compatibility hint
RyoheiHagimoto 0:0e0631af0305 401 };
RyoheiHagimoto 0:0e0631af0305 402
RyoheiHagimoto 0:0e0631af0305 403 struct CV_EXPORTS UMatData;
RyoheiHagimoto 0:0e0631af0305 404
RyoheiHagimoto 0:0e0631af0305 405 /** @brief Custom array allocator
RyoheiHagimoto 0:0e0631af0305 406 */
RyoheiHagimoto 0:0e0631af0305 407 class CV_EXPORTS MatAllocator
RyoheiHagimoto 0:0e0631af0305 408 {
RyoheiHagimoto 0:0e0631af0305 409 public:
RyoheiHagimoto 0:0e0631af0305 410 MatAllocator() {}
RyoheiHagimoto 0:0e0631af0305 411 virtual ~MatAllocator() {}
RyoheiHagimoto 0:0e0631af0305 412
RyoheiHagimoto 0:0e0631af0305 413 // let's comment it off for now to detect and fix all the uses of allocator
RyoheiHagimoto 0:0e0631af0305 414 //virtual void allocate(int dims, const int* sizes, int type, int*& refcount,
RyoheiHagimoto 0:0e0631af0305 415 // uchar*& datastart, uchar*& data, size_t* step) = 0;
RyoheiHagimoto 0:0e0631af0305 416 //virtual void deallocate(int* refcount, uchar* datastart, uchar* data) = 0;
RyoheiHagimoto 0:0e0631af0305 417 virtual UMatData* allocate(int dims, const int* sizes, int type,
RyoheiHagimoto 0:0e0631af0305 418 void* data, size_t* step, int flags, UMatUsageFlags usageFlags) const = 0;
RyoheiHagimoto 0:0e0631af0305 419 virtual bool allocate(UMatData* data, int accessflags, UMatUsageFlags usageFlags) const = 0;
RyoheiHagimoto 0:0e0631af0305 420 virtual void deallocate(UMatData* data) const = 0;
RyoheiHagimoto 0:0e0631af0305 421 virtual void map(UMatData* data, int accessflags) const;
RyoheiHagimoto 0:0e0631af0305 422 virtual void unmap(UMatData* data) const;
RyoheiHagimoto 0:0e0631af0305 423 virtual void download(UMatData* data, void* dst, int dims, const size_t sz[],
RyoheiHagimoto 0:0e0631af0305 424 const size_t srcofs[], const size_t srcstep[],
RyoheiHagimoto 0:0e0631af0305 425 const size_t dststep[]) const;
RyoheiHagimoto 0:0e0631af0305 426 virtual void upload(UMatData* data, const void* src, int dims, const size_t sz[],
RyoheiHagimoto 0:0e0631af0305 427 const size_t dstofs[], const size_t dststep[],
RyoheiHagimoto 0:0e0631af0305 428 const size_t srcstep[]) const;
RyoheiHagimoto 0:0e0631af0305 429 virtual void copy(UMatData* srcdata, UMatData* dstdata, int dims, const size_t sz[],
RyoheiHagimoto 0:0e0631af0305 430 const size_t srcofs[], const size_t srcstep[],
RyoheiHagimoto 0:0e0631af0305 431 const size_t dstofs[], const size_t dststep[], bool sync) const;
RyoheiHagimoto 0:0e0631af0305 432
RyoheiHagimoto 0:0e0631af0305 433 // default implementation returns DummyBufferPoolController
RyoheiHagimoto 0:0e0631af0305 434 virtual BufferPoolController* getBufferPoolController(const char* id = NULL) const;
RyoheiHagimoto 0:0e0631af0305 435 };
RyoheiHagimoto 0:0e0631af0305 436
RyoheiHagimoto 0:0e0631af0305 437
RyoheiHagimoto 0:0e0631af0305 438 //////////////////////////////// MatCommaInitializer //////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 439
RyoheiHagimoto 0:0e0631af0305 440 /** @brief Comma-separated Matrix Initializer
RyoheiHagimoto 0:0e0631af0305 441
RyoheiHagimoto 0:0e0631af0305 442 The class instances are usually not created explicitly.
RyoheiHagimoto 0:0e0631af0305 443 Instead, they are created on "matrix << firstValue" operator.
RyoheiHagimoto 0:0e0631af0305 444
RyoheiHagimoto 0:0e0631af0305 445 The sample below initializes 2x2 rotation matrix:
RyoheiHagimoto 0:0e0631af0305 446
RyoheiHagimoto 0:0e0631af0305 447 \code
RyoheiHagimoto 0:0e0631af0305 448 double angle = 30, a = cos(angle*CV_PI/180), b = sin(angle*CV_PI/180);
RyoheiHagimoto 0:0e0631af0305 449 Mat R = (Mat_<double>(2,2) << a, -b, b, a);
RyoheiHagimoto 0:0e0631af0305 450 \endcode
RyoheiHagimoto 0:0e0631af0305 451 */
RyoheiHagimoto 0:0e0631af0305 452 template<typename _Tp> class MatCommaInitializer_
RyoheiHagimoto 0:0e0631af0305 453 {
RyoheiHagimoto 0:0e0631af0305 454 public:
RyoheiHagimoto 0:0e0631af0305 455 //! the constructor, created by "matrix << firstValue" operator, where matrix is cv::Mat
RyoheiHagimoto 0:0e0631af0305 456 MatCommaInitializer_(Mat_<_Tp>* _m);
RyoheiHagimoto 0:0e0631af0305 457 //! the operator that takes the next value and put it to the matrix
RyoheiHagimoto 0:0e0631af0305 458 template<typename T2> MatCommaInitializer_<_Tp>& operator , (T2 v);
RyoheiHagimoto 0:0e0631af0305 459 //! another form of conversion operator
RyoheiHagimoto 0:0e0631af0305 460 operator Mat_<_Tp>() const;
RyoheiHagimoto 0:0e0631af0305 461 protected:
RyoheiHagimoto 0:0e0631af0305 462 MatIterator_<_Tp> it;
RyoheiHagimoto 0:0e0631af0305 463 };
RyoheiHagimoto 0:0e0631af0305 464
RyoheiHagimoto 0:0e0631af0305 465
RyoheiHagimoto 0:0e0631af0305 466 /////////////////////////////////////// Mat ///////////////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 467
RyoheiHagimoto 0:0e0631af0305 468 // note that umatdata might be allocated together
RyoheiHagimoto 0:0e0631af0305 469 // with the matrix data, not as a separate object.
RyoheiHagimoto 0:0e0631af0305 470 // therefore, it does not have constructor or destructor;
RyoheiHagimoto 0:0e0631af0305 471 // it should be explicitly initialized using init().
RyoheiHagimoto 0:0e0631af0305 472 struct CV_EXPORTS UMatData
RyoheiHagimoto 0:0e0631af0305 473 {
RyoheiHagimoto 0:0e0631af0305 474 enum { COPY_ON_MAP=1, HOST_COPY_OBSOLETE=2,
RyoheiHagimoto 0:0e0631af0305 475 DEVICE_COPY_OBSOLETE=4, TEMP_UMAT=8, TEMP_COPIED_UMAT=24,
RyoheiHagimoto 0:0e0631af0305 476 USER_ALLOCATED=32, DEVICE_MEM_MAPPED=64};
RyoheiHagimoto 0:0e0631af0305 477 UMatData(const MatAllocator* allocator);
RyoheiHagimoto 0:0e0631af0305 478 ~UMatData();
RyoheiHagimoto 0:0e0631af0305 479
RyoheiHagimoto 0:0e0631af0305 480 // provide atomic access to the structure
RyoheiHagimoto 0:0e0631af0305 481 void lock();
RyoheiHagimoto 0:0e0631af0305 482 void unlock();
RyoheiHagimoto 0:0e0631af0305 483
RyoheiHagimoto 0:0e0631af0305 484 bool hostCopyObsolete() const;
RyoheiHagimoto 0:0e0631af0305 485 bool deviceCopyObsolete() const;
RyoheiHagimoto 0:0e0631af0305 486 bool deviceMemMapped() const;
RyoheiHagimoto 0:0e0631af0305 487 bool copyOnMap() const;
RyoheiHagimoto 0:0e0631af0305 488 bool tempUMat() const;
RyoheiHagimoto 0:0e0631af0305 489 bool tempCopiedUMat() const;
RyoheiHagimoto 0:0e0631af0305 490 void markHostCopyObsolete(bool flag);
RyoheiHagimoto 0:0e0631af0305 491 void markDeviceCopyObsolete(bool flag);
RyoheiHagimoto 0:0e0631af0305 492 void markDeviceMemMapped(bool flag);
RyoheiHagimoto 0:0e0631af0305 493
RyoheiHagimoto 0:0e0631af0305 494 const MatAllocator* prevAllocator;
RyoheiHagimoto 0:0e0631af0305 495 const MatAllocator* currAllocator;
RyoheiHagimoto 0:0e0631af0305 496 int urefcount;
RyoheiHagimoto 0:0e0631af0305 497 int refcount;
RyoheiHagimoto 0:0e0631af0305 498 uchar* data;
RyoheiHagimoto 0:0e0631af0305 499 uchar* origdata;
RyoheiHagimoto 0:0e0631af0305 500 size_t size;
RyoheiHagimoto 0:0e0631af0305 501
RyoheiHagimoto 0:0e0631af0305 502 int flags;
RyoheiHagimoto 0:0e0631af0305 503 void* handle;
RyoheiHagimoto 0:0e0631af0305 504 void* userdata;
RyoheiHagimoto 0:0e0631af0305 505 int allocatorFlags_;
RyoheiHagimoto 0:0e0631af0305 506 int mapcount;
RyoheiHagimoto 0:0e0631af0305 507 UMatData* originalUMatData;
RyoheiHagimoto 0:0e0631af0305 508 };
RyoheiHagimoto 0:0e0631af0305 509
RyoheiHagimoto 0:0e0631af0305 510
RyoheiHagimoto 0:0e0631af0305 511 struct CV_EXPORTS UMatDataAutoLock
RyoheiHagimoto 0:0e0631af0305 512 {
RyoheiHagimoto 0:0e0631af0305 513 explicit UMatDataAutoLock(UMatData* u);
RyoheiHagimoto 0:0e0631af0305 514 ~UMatDataAutoLock();
RyoheiHagimoto 0:0e0631af0305 515 UMatData* u;
RyoheiHagimoto 0:0e0631af0305 516 };
RyoheiHagimoto 0:0e0631af0305 517
RyoheiHagimoto 0:0e0631af0305 518
RyoheiHagimoto 0:0e0631af0305 519 struct CV_EXPORTS MatSize
RyoheiHagimoto 0:0e0631af0305 520 {
RyoheiHagimoto 0:0e0631af0305 521 explicit MatSize(int* _p);
RyoheiHagimoto 0:0e0631af0305 522 Size operator()() const;
RyoheiHagimoto 0:0e0631af0305 523 const int& operator[](int i) const;
RyoheiHagimoto 0:0e0631af0305 524 int& operator[](int i);
RyoheiHagimoto 0:0e0631af0305 525 operator const int*() const;
RyoheiHagimoto 0:0e0631af0305 526 bool operator == (const MatSize& sz) const;
RyoheiHagimoto 0:0e0631af0305 527 bool operator != (const MatSize& sz) const;
RyoheiHagimoto 0:0e0631af0305 528
RyoheiHagimoto 0:0e0631af0305 529 int* p;
RyoheiHagimoto 0:0e0631af0305 530 };
RyoheiHagimoto 0:0e0631af0305 531
RyoheiHagimoto 0:0e0631af0305 532 struct CV_EXPORTS MatStep
RyoheiHagimoto 0:0e0631af0305 533 {
RyoheiHagimoto 0:0e0631af0305 534 MatStep();
RyoheiHagimoto 0:0e0631af0305 535 explicit MatStep(size_t s);
RyoheiHagimoto 0:0e0631af0305 536 const size_t& operator[](int i) const;
RyoheiHagimoto 0:0e0631af0305 537 size_t& operator[](int i);
RyoheiHagimoto 0:0e0631af0305 538 operator size_t() const;
RyoheiHagimoto 0:0e0631af0305 539 MatStep& operator = (size_t s);
RyoheiHagimoto 0:0e0631af0305 540
RyoheiHagimoto 0:0e0631af0305 541 size_t* p;
RyoheiHagimoto 0:0e0631af0305 542 size_t buf[2];
RyoheiHagimoto 0:0e0631af0305 543 protected:
RyoheiHagimoto 0:0e0631af0305 544 MatStep& operator = (const MatStep&);
RyoheiHagimoto 0:0e0631af0305 545 };
RyoheiHagimoto 0:0e0631af0305 546
RyoheiHagimoto 0:0e0631af0305 547 /** @example cout_mat.cpp
RyoheiHagimoto 0:0e0631af0305 548 An example demonstrating the serial out capabilities of cv::Mat
RyoheiHagimoto 0:0e0631af0305 549 */
RyoheiHagimoto 0:0e0631af0305 550
RyoheiHagimoto 0:0e0631af0305 551 /** @brief n-dimensional dense array class
RyoheiHagimoto 0:0e0631af0305 552
RyoheiHagimoto 0:0e0631af0305 553 The class Mat represents an n-dimensional dense numerical single-channel or multi-channel array. It
RyoheiHagimoto 0:0e0631af0305 554 can be used to store real or complex-valued vectors and matrices, grayscale or color images, voxel
RyoheiHagimoto 0:0e0631af0305 555 volumes, vector fields, point clouds, tensors, histograms (though, very high-dimensional histograms
RyoheiHagimoto 0:0e0631af0305 556 may be better stored in a SparseMat ). The data layout of the array `M` is defined by the array
RyoheiHagimoto 0:0e0631af0305 557 `M.step[]`, so that the address of element \f$(i_0,...,i_{M.dims-1})\f$, where \f$0\leq i_k<M.size[k]\f$, is
RyoheiHagimoto 0:0e0631af0305 558 computed as:
RyoheiHagimoto 0:0e0631af0305 559 \f[addr(M_{i_0,...,i_{M.dims-1}}) = M.data + M.step[0]*i_0 + M.step[1]*i_1 + ... + M.step[M.dims-1]*i_{M.dims-1}\f]
RyoheiHagimoto 0:0e0631af0305 560 In case of a 2-dimensional array, the above formula is reduced to:
RyoheiHagimoto 0:0e0631af0305 561 \f[addr(M_{i,j}) = M.data + M.step[0]*i + M.step[1]*j\f]
RyoheiHagimoto 0:0e0631af0305 562 Note that `M.step[i] >= M.step[i+1]` (in fact, `M.step[i] >= M.step[i+1]*M.size[i+1]` ). This means
RyoheiHagimoto 0:0e0631af0305 563 that 2-dimensional matrices are stored row-by-row, 3-dimensional matrices are stored plane-by-plane,
RyoheiHagimoto 0:0e0631af0305 564 and so on. M.step[M.dims-1] is minimal and always equal to the element size M.elemSize() .
RyoheiHagimoto 0:0e0631af0305 565
RyoheiHagimoto 0:0e0631af0305 566 So, the data layout in Mat is fully compatible with CvMat, IplImage, and CvMatND types from OpenCV
RyoheiHagimoto 0:0e0631af0305 567 1.x. It is also compatible with the majority of dense array types from the standard toolkits and
RyoheiHagimoto 0:0e0631af0305 568 SDKs, such as Numpy (ndarray), Win32 (independent device bitmaps), and others, that is, with any
RyoheiHagimoto 0:0e0631af0305 569 array that uses *steps* (or *strides*) to compute the position of a pixel. Due to this
RyoheiHagimoto 0:0e0631af0305 570 compatibility, it is possible to make a Mat header for user-allocated data and process it in-place
RyoheiHagimoto 0:0e0631af0305 571 using OpenCV functions.
RyoheiHagimoto 0:0e0631af0305 572
RyoheiHagimoto 0:0e0631af0305 573 There are many different ways to create a Mat object. The most popular options are listed below:
RyoheiHagimoto 0:0e0631af0305 574
RyoheiHagimoto 0:0e0631af0305 575 - Use the create(nrows, ncols, type) method or the similar Mat(nrows, ncols, type[, fillValue])
RyoheiHagimoto 0:0e0631af0305 576 constructor. A new array of the specified size and type is allocated. type has the same meaning as
RyoheiHagimoto 0:0e0631af0305 577 in the cvCreateMat method. For example, CV_8UC1 means a 8-bit single-channel array, CV_32FC2
RyoheiHagimoto 0:0e0631af0305 578 means a 2-channel (complex) floating-point array, and so on.
RyoheiHagimoto 0:0e0631af0305 579 @code
RyoheiHagimoto 0:0e0631af0305 580 // make a 7x7 complex matrix filled with 1+3j.
RyoheiHagimoto 0:0e0631af0305 581 Mat M(7,7,CV_32FC2,Scalar(1,3));
RyoheiHagimoto 0:0e0631af0305 582 // and now turn M to a 100x60 15-channel 8-bit matrix.
RyoheiHagimoto 0:0e0631af0305 583 // The old content will be deallocated
RyoheiHagimoto 0:0e0631af0305 584 M.create(100,60,CV_8UC(15));
RyoheiHagimoto 0:0e0631af0305 585 @endcode
RyoheiHagimoto 0:0e0631af0305 586 As noted in the introduction to this chapter, create() allocates only a new array when the shape
RyoheiHagimoto 0:0e0631af0305 587 or type of the current array are different from the specified ones.
RyoheiHagimoto 0:0e0631af0305 588
RyoheiHagimoto 0:0e0631af0305 589 - Create a multi-dimensional array:
RyoheiHagimoto 0:0e0631af0305 590 @code
RyoheiHagimoto 0:0e0631af0305 591 // create a 100x100x100 8-bit array
RyoheiHagimoto 0:0e0631af0305 592 int sz[] = {100, 100, 100};
RyoheiHagimoto 0:0e0631af0305 593 Mat bigCube(3, sz, CV_8U, Scalar::all(0));
RyoheiHagimoto 0:0e0631af0305 594 @endcode
RyoheiHagimoto 0:0e0631af0305 595 It passes the number of dimensions =1 to the Mat constructor but the created array will be
RyoheiHagimoto 0:0e0631af0305 596 2-dimensional with the number of columns set to 1. So, Mat::dims is always \>= 2 (can also be 0
RyoheiHagimoto 0:0e0631af0305 597 when the array is empty).
RyoheiHagimoto 0:0e0631af0305 598
RyoheiHagimoto 0:0e0631af0305 599 - Use a copy constructor or assignment operator where there can be an array or expression on the
RyoheiHagimoto 0:0e0631af0305 600 right side (see below). As noted in the introduction, the array assignment is an O(1) operation
RyoheiHagimoto 0:0e0631af0305 601 because it only copies the header and increases the reference counter. The Mat::clone() method can
RyoheiHagimoto 0:0e0631af0305 602 be used to get a full (deep) copy of the array when you need it.
RyoheiHagimoto 0:0e0631af0305 603
RyoheiHagimoto 0:0e0631af0305 604 - Construct a header for a part of another array. It can be a single row, single column, several
RyoheiHagimoto 0:0e0631af0305 605 rows, several columns, rectangular region in the array (called a *minor* in algebra) or a
RyoheiHagimoto 0:0e0631af0305 606 diagonal. Such operations are also O(1) because the new header references the same data. You can
RyoheiHagimoto 0:0e0631af0305 607 actually modify a part of the array using this feature, for example:
RyoheiHagimoto 0:0e0631af0305 608 @code
RyoheiHagimoto 0:0e0631af0305 609 // add the 5-th row, multiplied by 3 to the 3rd row
RyoheiHagimoto 0:0e0631af0305 610 M.row(3) = M.row(3) + M.row(5)*3;
RyoheiHagimoto 0:0e0631af0305 611 // now copy the 7-th column to the 1-st column
RyoheiHagimoto 0:0e0631af0305 612 // M.col(1) = M.col(7); // this will not work
RyoheiHagimoto 0:0e0631af0305 613 Mat M1 = M.col(1);
RyoheiHagimoto 0:0e0631af0305 614 M.col(7).copyTo(M1);
RyoheiHagimoto 0:0e0631af0305 615 // create a new 320x240 image
RyoheiHagimoto 0:0e0631af0305 616 Mat img(Size(320,240),CV_8UC3);
RyoheiHagimoto 0:0e0631af0305 617 // select a ROI
RyoheiHagimoto 0:0e0631af0305 618 Mat roi(img, Rect(10,10,100,100));
RyoheiHagimoto 0:0e0631af0305 619 // fill the ROI with (0,255,0) (which is green in RGB space);
RyoheiHagimoto 0:0e0631af0305 620 // the original 320x240 image will be modified
RyoheiHagimoto 0:0e0631af0305 621 roi = Scalar(0,255,0);
RyoheiHagimoto 0:0e0631af0305 622 @endcode
RyoheiHagimoto 0:0e0631af0305 623 Due to the additional datastart and dataend members, it is possible to compute a relative
RyoheiHagimoto 0:0e0631af0305 624 sub-array position in the main *container* array using locateROI():
RyoheiHagimoto 0:0e0631af0305 625 @code
RyoheiHagimoto 0:0e0631af0305 626 Mat A = Mat::eye(10, 10, CV_32S);
RyoheiHagimoto 0:0e0631af0305 627 // extracts A columns, 1 (inclusive) to 3 (exclusive).
RyoheiHagimoto 0:0e0631af0305 628 Mat B = A(Range::all(), Range(1, 3));
RyoheiHagimoto 0:0e0631af0305 629 // extracts B rows, 5 (inclusive) to 9 (exclusive).
RyoheiHagimoto 0:0e0631af0305 630 // that is, C \~ A(Range(5, 9), Range(1, 3))
RyoheiHagimoto 0:0e0631af0305 631 Mat C = B(Range(5, 9), Range::all());
RyoheiHagimoto 0:0e0631af0305 632 Size size; Point ofs;
RyoheiHagimoto 0:0e0631af0305 633 C.locateROI(size, ofs);
RyoheiHagimoto 0:0e0631af0305 634 // size will be (width=10,height=10) and the ofs will be (x=1, y=5)
RyoheiHagimoto 0:0e0631af0305 635 @endcode
RyoheiHagimoto 0:0e0631af0305 636 As in case of whole matrices, if you need a deep copy, use the `clone()` method of the extracted
RyoheiHagimoto 0:0e0631af0305 637 sub-matrices.
RyoheiHagimoto 0:0e0631af0305 638
RyoheiHagimoto 0:0e0631af0305 639 - Make a header for user-allocated data. It can be useful to do the following:
RyoheiHagimoto 0:0e0631af0305 640 -# Process "foreign" data using OpenCV (for example, when you implement a DirectShow\* filter or
RyoheiHagimoto 0:0e0631af0305 641 a processing module for gstreamer, and so on). For example:
RyoheiHagimoto 0:0e0631af0305 642 @code
RyoheiHagimoto 0:0e0631af0305 643 void process_video_frame(const unsigned char* pixels,
RyoheiHagimoto 0:0e0631af0305 644 int width, int height, int step)
RyoheiHagimoto 0:0e0631af0305 645 {
RyoheiHagimoto 0:0e0631af0305 646 Mat img(height, width, CV_8UC3, pixels, step);
RyoheiHagimoto 0:0e0631af0305 647 GaussianBlur(img, img, Size(7,7), 1.5, 1.5);
RyoheiHagimoto 0:0e0631af0305 648 }
RyoheiHagimoto 0:0e0631af0305 649 @endcode
RyoheiHagimoto 0:0e0631af0305 650 -# Quickly initialize small matrices and/or get a super-fast element access.
RyoheiHagimoto 0:0e0631af0305 651 @code
RyoheiHagimoto 0:0e0631af0305 652 double m[3][3] = {{a, b, c}, {d, e, f}, {g, h, i}};
RyoheiHagimoto 0:0e0631af0305 653 Mat M = Mat(3, 3, CV_64F, m).inv();
RyoheiHagimoto 0:0e0631af0305 654 @endcode
RyoheiHagimoto 0:0e0631af0305 655 .
RyoheiHagimoto 0:0e0631af0305 656 Partial yet very common cases of this *user-allocated data* case are conversions from CvMat and
RyoheiHagimoto 0:0e0631af0305 657 IplImage to Mat. For this purpose, there is function cv::cvarrToMat taking pointers to CvMat or
RyoheiHagimoto 0:0e0631af0305 658 IplImage and the optional flag indicating whether to copy the data or not.
RyoheiHagimoto 0:0e0631af0305 659 @snippet samples/cpp/image.cpp iplimage
RyoheiHagimoto 0:0e0631af0305 660
RyoheiHagimoto 0:0e0631af0305 661 - Use MATLAB-style array initializers, zeros(), ones(), eye(), for example:
RyoheiHagimoto 0:0e0631af0305 662 @code
RyoheiHagimoto 0:0e0631af0305 663 // create a double-precision identity martix and add it to M.
RyoheiHagimoto 0:0e0631af0305 664 M += Mat::eye(M.rows, M.cols, CV_64F);
RyoheiHagimoto 0:0e0631af0305 665 @endcode
RyoheiHagimoto 0:0e0631af0305 666
RyoheiHagimoto 0:0e0631af0305 667 - Use a comma-separated initializer:
RyoheiHagimoto 0:0e0631af0305 668 @code
RyoheiHagimoto 0:0e0631af0305 669 // create a 3x3 double-precision identity matrix
RyoheiHagimoto 0:0e0631af0305 670 Mat M = (Mat_<double>(3,3) << 1, 0, 0, 0, 1, 0, 0, 0, 1);
RyoheiHagimoto 0:0e0631af0305 671 @endcode
RyoheiHagimoto 0:0e0631af0305 672 With this approach, you first call a constructor of the Mat class with the proper parameters, and
RyoheiHagimoto 0:0e0631af0305 673 then you just put `<< operator` followed by comma-separated values that can be constants,
RyoheiHagimoto 0:0e0631af0305 674 variables, expressions, and so on. Also, note the extra parentheses required to avoid compilation
RyoheiHagimoto 0:0e0631af0305 675 errors.
RyoheiHagimoto 0:0e0631af0305 676
RyoheiHagimoto 0:0e0631af0305 677 Once the array is created, it is automatically managed via a reference-counting mechanism. If the
RyoheiHagimoto 0:0e0631af0305 678 array header is built on top of user-allocated data, you should handle the data by yourself. The
RyoheiHagimoto 0:0e0631af0305 679 array data is deallocated when no one points to it. If you want to release the data pointed by a
RyoheiHagimoto 0:0e0631af0305 680 array header before the array destructor is called, use Mat::release().
RyoheiHagimoto 0:0e0631af0305 681
RyoheiHagimoto 0:0e0631af0305 682 The next important thing to learn about the array class is element access. This manual already
RyoheiHagimoto 0:0e0631af0305 683 described how to compute an address of each array element. Normally, you are not required to use the
RyoheiHagimoto 0:0e0631af0305 684 formula directly in the code. If you know the array element type (which can be retrieved using the
RyoheiHagimoto 0:0e0631af0305 685 method Mat::type() ), you can access the element \f$M_{ij}\f$ of a 2-dimensional array as:
RyoheiHagimoto 0:0e0631af0305 686 @code
RyoheiHagimoto 0:0e0631af0305 687 M.at<double>(i,j) += 1.f;
RyoheiHagimoto 0:0e0631af0305 688 @endcode
RyoheiHagimoto 0:0e0631af0305 689 assuming that `M` is a double-precision floating-point array. There are several variants of the method
RyoheiHagimoto 0:0e0631af0305 690 at for a different number of dimensions.
RyoheiHagimoto 0:0e0631af0305 691
RyoheiHagimoto 0:0e0631af0305 692 If you need to process a whole row of a 2D array, the most efficient way is to get the pointer to
RyoheiHagimoto 0:0e0631af0305 693 the row first, and then just use the plain C operator [] :
RyoheiHagimoto 0:0e0631af0305 694 @code
RyoheiHagimoto 0:0e0631af0305 695 // compute sum of positive matrix elements
RyoheiHagimoto 0:0e0631af0305 696 // (assuming that M isa double-precision matrix)
RyoheiHagimoto 0:0e0631af0305 697 double sum=0;
RyoheiHagimoto 0:0e0631af0305 698 for(int i = 0; i < M.rows; i++)
RyoheiHagimoto 0:0e0631af0305 699 {
RyoheiHagimoto 0:0e0631af0305 700 const double* Mi = M.ptr<double>(i);
RyoheiHagimoto 0:0e0631af0305 701 for(int j = 0; j < M.cols; j++)
RyoheiHagimoto 0:0e0631af0305 702 sum += std::max(Mi[j], 0.);
RyoheiHagimoto 0:0e0631af0305 703 }
RyoheiHagimoto 0:0e0631af0305 704 @endcode
RyoheiHagimoto 0:0e0631af0305 705 Some operations, like the one above, do not actually depend on the array shape. They just process
RyoheiHagimoto 0:0e0631af0305 706 elements of an array one by one (or elements from multiple arrays that have the same coordinates,
RyoheiHagimoto 0:0e0631af0305 707 for example, array addition). Such operations are called *element-wise*. It makes sense to check
RyoheiHagimoto 0:0e0631af0305 708 whether all the input/output arrays are continuous, namely, have no gaps at the end of each row. If
RyoheiHagimoto 0:0e0631af0305 709 yes, process them as a long single row:
RyoheiHagimoto 0:0e0631af0305 710 @code
RyoheiHagimoto 0:0e0631af0305 711 // compute the sum of positive matrix elements, optimized variant
RyoheiHagimoto 0:0e0631af0305 712 double sum=0;
RyoheiHagimoto 0:0e0631af0305 713 int cols = M.cols, rows = M.rows;
RyoheiHagimoto 0:0e0631af0305 714 if(M.isContinuous())
RyoheiHagimoto 0:0e0631af0305 715 {
RyoheiHagimoto 0:0e0631af0305 716 cols *= rows;
RyoheiHagimoto 0:0e0631af0305 717 rows = 1;
RyoheiHagimoto 0:0e0631af0305 718 }
RyoheiHagimoto 0:0e0631af0305 719 for(int i = 0; i < rows; i++)
RyoheiHagimoto 0:0e0631af0305 720 {
RyoheiHagimoto 0:0e0631af0305 721 const double* Mi = M.ptr<double>(i);
RyoheiHagimoto 0:0e0631af0305 722 for(int j = 0; j < cols; j++)
RyoheiHagimoto 0:0e0631af0305 723 sum += std::max(Mi[j], 0.);
RyoheiHagimoto 0:0e0631af0305 724 }
RyoheiHagimoto 0:0e0631af0305 725 @endcode
RyoheiHagimoto 0:0e0631af0305 726 In case of the continuous matrix, the outer loop body is executed just once. So, the overhead is
RyoheiHagimoto 0:0e0631af0305 727 smaller, which is especially noticeable in case of small matrices.
RyoheiHagimoto 0:0e0631af0305 728
RyoheiHagimoto 0:0e0631af0305 729 Finally, there are STL-style iterators that are smart enough to skip gaps between successive rows:
RyoheiHagimoto 0:0e0631af0305 730 @code
RyoheiHagimoto 0:0e0631af0305 731 // compute sum of positive matrix elements, iterator-based variant
RyoheiHagimoto 0:0e0631af0305 732 double sum=0;
RyoheiHagimoto 0:0e0631af0305 733 MatConstIterator_<double> it = M.begin<double>(), it_end = M.end<double>();
RyoheiHagimoto 0:0e0631af0305 734 for(; it != it_end; ++it)
RyoheiHagimoto 0:0e0631af0305 735 sum += std::max(*it, 0.);
RyoheiHagimoto 0:0e0631af0305 736 @endcode
RyoheiHagimoto 0:0e0631af0305 737 The matrix iterators are random-access iterators, so they can be passed to any STL algorithm,
RyoheiHagimoto 0:0e0631af0305 738 including std::sort().
RyoheiHagimoto 0:0e0631af0305 739 */
RyoheiHagimoto 0:0e0631af0305 740 class CV_EXPORTS Mat
RyoheiHagimoto 0:0e0631af0305 741 {
RyoheiHagimoto 0:0e0631af0305 742 public:
RyoheiHagimoto 0:0e0631af0305 743 /**
RyoheiHagimoto 0:0e0631af0305 744 These are various constructors that form a matrix. As noted in the AutomaticAllocation, often
RyoheiHagimoto 0:0e0631af0305 745 the default constructor is enough, and the proper matrix will be allocated by an OpenCV function.
RyoheiHagimoto 0:0e0631af0305 746 The constructed matrix can further be assigned to another matrix or matrix expression or can be
RyoheiHagimoto 0:0e0631af0305 747 allocated with Mat::create . In the former case, the old content is de-referenced.
RyoheiHagimoto 0:0e0631af0305 748 */
RyoheiHagimoto 0:0e0631af0305 749 Mat();
RyoheiHagimoto 0:0e0631af0305 750
RyoheiHagimoto 0:0e0631af0305 751 /** @overload
RyoheiHagimoto 0:0e0631af0305 752 @param rows Number of rows in a 2D array.
RyoheiHagimoto 0:0e0631af0305 753 @param cols Number of columns in a 2D array.
RyoheiHagimoto 0:0e0631af0305 754 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 755 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 756 */
RyoheiHagimoto 0:0e0631af0305 757 Mat(int rows, int cols, int type);
RyoheiHagimoto 0:0e0631af0305 758
RyoheiHagimoto 0:0e0631af0305 759 /** @overload
RyoheiHagimoto 0:0e0631af0305 760 @param size 2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the
RyoheiHagimoto 0:0e0631af0305 761 number of columns go in the reverse order.
RyoheiHagimoto 0:0e0631af0305 762 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 763 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 764 */
RyoheiHagimoto 0:0e0631af0305 765 Mat(Size size, int type);
RyoheiHagimoto 0:0e0631af0305 766
RyoheiHagimoto 0:0e0631af0305 767 /** @overload
RyoheiHagimoto 0:0e0631af0305 768 @param rows Number of rows in a 2D array.
RyoheiHagimoto 0:0e0631af0305 769 @param cols Number of columns in a 2D array.
RyoheiHagimoto 0:0e0631af0305 770 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 771 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 772 @param s An optional value to initialize each matrix element with. To set all the matrix elements to
RyoheiHagimoto 0:0e0631af0305 773 the particular value after the construction, use the assignment operator
RyoheiHagimoto 0:0e0631af0305 774 Mat::operator=(const Scalar& value) .
RyoheiHagimoto 0:0e0631af0305 775 */
RyoheiHagimoto 0:0e0631af0305 776 Mat(int rows, int cols, int type, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 777
RyoheiHagimoto 0:0e0631af0305 778 /** @overload
RyoheiHagimoto 0:0e0631af0305 779 @param size 2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the
RyoheiHagimoto 0:0e0631af0305 780 number of columns go in the reverse order.
RyoheiHagimoto 0:0e0631af0305 781 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 782 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 783 @param s An optional value to initialize each matrix element with. To set all the matrix elements to
RyoheiHagimoto 0:0e0631af0305 784 the particular value after the construction, use the assignment operator
RyoheiHagimoto 0:0e0631af0305 785 Mat::operator=(const Scalar& value) .
RyoheiHagimoto 0:0e0631af0305 786 */
RyoheiHagimoto 0:0e0631af0305 787 Mat(Size size, int type, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 788
RyoheiHagimoto 0:0e0631af0305 789 /** @overload
RyoheiHagimoto 0:0e0631af0305 790 @param ndims Array dimensionality.
RyoheiHagimoto 0:0e0631af0305 791 @param sizes Array of integers specifying an n-dimensional array shape.
RyoheiHagimoto 0:0e0631af0305 792 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 793 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 794 */
RyoheiHagimoto 0:0e0631af0305 795 Mat(int ndims, const int* sizes, int type);
RyoheiHagimoto 0:0e0631af0305 796
RyoheiHagimoto 0:0e0631af0305 797 /** @overload
RyoheiHagimoto 0:0e0631af0305 798 @param sizes Array of integers specifying an n-dimensional array shape.
RyoheiHagimoto 0:0e0631af0305 799 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 800 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 801 */
RyoheiHagimoto 0:0e0631af0305 802 Mat(const std::vector<int>& sizes, int type);
RyoheiHagimoto 0:0e0631af0305 803
RyoheiHagimoto 0:0e0631af0305 804 /** @overload
RyoheiHagimoto 0:0e0631af0305 805 @param ndims Array dimensionality.
RyoheiHagimoto 0:0e0631af0305 806 @param sizes Array of integers specifying an n-dimensional array shape.
RyoheiHagimoto 0:0e0631af0305 807 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 808 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 809 @param s An optional value to initialize each matrix element with. To set all the matrix elements to
RyoheiHagimoto 0:0e0631af0305 810 the particular value after the construction, use the assignment operator
RyoheiHagimoto 0:0e0631af0305 811 Mat::operator=(const Scalar& value) .
RyoheiHagimoto 0:0e0631af0305 812 */
RyoheiHagimoto 0:0e0631af0305 813 Mat(int ndims, const int* sizes, int type, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 814
RyoheiHagimoto 0:0e0631af0305 815 /** @overload
RyoheiHagimoto 0:0e0631af0305 816 @param sizes Array of integers specifying an n-dimensional array shape.
RyoheiHagimoto 0:0e0631af0305 817 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 818 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 819 @param s An optional value to initialize each matrix element with. To set all the matrix elements to
RyoheiHagimoto 0:0e0631af0305 820 the particular value after the construction, use the assignment operator
RyoheiHagimoto 0:0e0631af0305 821 Mat::operator=(const Scalar& value) .
RyoheiHagimoto 0:0e0631af0305 822 */
RyoheiHagimoto 0:0e0631af0305 823 Mat(const std::vector<int>& sizes, int type, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 824
RyoheiHagimoto 0:0e0631af0305 825
RyoheiHagimoto 0:0e0631af0305 826 /** @overload
RyoheiHagimoto 0:0e0631af0305 827 @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
RyoheiHagimoto 0:0e0631af0305 828 by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
RyoheiHagimoto 0:0e0631af0305 829 associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
RyoheiHagimoto 0:0e0631af0305 830 formed using such a constructor, you also modify the corresponding elements of m . If you want to
RyoheiHagimoto 0:0e0631af0305 831 have an independent copy of the sub-array, use Mat::clone() .
RyoheiHagimoto 0:0e0631af0305 832 */
RyoheiHagimoto 0:0e0631af0305 833 Mat(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 834
RyoheiHagimoto 0:0e0631af0305 835 /** @overload
RyoheiHagimoto 0:0e0631af0305 836 @param rows Number of rows in a 2D array.
RyoheiHagimoto 0:0e0631af0305 837 @param cols Number of columns in a 2D array.
RyoheiHagimoto 0:0e0631af0305 838 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 839 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 840 @param data Pointer to the user data. Matrix constructors that take data and step parameters do not
RyoheiHagimoto 0:0e0631af0305 841 allocate matrix data. Instead, they just initialize the matrix header that points to the specified
RyoheiHagimoto 0:0e0631af0305 842 data, which means that no data is copied. This operation is very efficient and can be used to
RyoheiHagimoto 0:0e0631af0305 843 process external data using OpenCV functions. The external data is not automatically deallocated, so
RyoheiHagimoto 0:0e0631af0305 844 you should take care of it.
RyoheiHagimoto 0:0e0631af0305 845 @param step Number of bytes each matrix row occupies. The value should include the padding bytes at
RyoheiHagimoto 0:0e0631af0305 846 the end of each row, if any. If the parameter is missing (set to AUTO_STEP ), no padding is assumed
RyoheiHagimoto 0:0e0631af0305 847 and the actual step is calculated as cols*elemSize(). See Mat::elemSize.
RyoheiHagimoto 0:0e0631af0305 848 */
RyoheiHagimoto 0:0e0631af0305 849 Mat(int rows, int cols, int type, void* data, size_t step=AUTO_STEP);
RyoheiHagimoto 0:0e0631af0305 850
RyoheiHagimoto 0:0e0631af0305 851 /** @overload
RyoheiHagimoto 0:0e0631af0305 852 @param size 2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the
RyoheiHagimoto 0:0e0631af0305 853 number of columns go in the reverse order.
RyoheiHagimoto 0:0e0631af0305 854 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 855 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 856 @param data Pointer to the user data. Matrix constructors that take data and step parameters do not
RyoheiHagimoto 0:0e0631af0305 857 allocate matrix data. Instead, they just initialize the matrix header that points to the specified
RyoheiHagimoto 0:0e0631af0305 858 data, which means that no data is copied. This operation is very efficient and can be used to
RyoheiHagimoto 0:0e0631af0305 859 process external data using OpenCV functions. The external data is not automatically deallocated, so
RyoheiHagimoto 0:0e0631af0305 860 you should take care of it.
RyoheiHagimoto 0:0e0631af0305 861 @param step Number of bytes each matrix row occupies. The value should include the padding bytes at
RyoheiHagimoto 0:0e0631af0305 862 the end of each row, if any. If the parameter is missing (set to AUTO_STEP ), no padding is assumed
RyoheiHagimoto 0:0e0631af0305 863 and the actual step is calculated as cols*elemSize(). See Mat::elemSize.
RyoheiHagimoto 0:0e0631af0305 864 */
RyoheiHagimoto 0:0e0631af0305 865 Mat(Size size, int type, void* data, size_t step=AUTO_STEP);
RyoheiHagimoto 0:0e0631af0305 866
RyoheiHagimoto 0:0e0631af0305 867 /** @overload
RyoheiHagimoto 0:0e0631af0305 868 @param ndims Array dimensionality.
RyoheiHagimoto 0:0e0631af0305 869 @param sizes Array of integers specifying an n-dimensional array shape.
RyoheiHagimoto 0:0e0631af0305 870 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 871 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 872 @param data Pointer to the user data. Matrix constructors that take data and step parameters do not
RyoheiHagimoto 0:0e0631af0305 873 allocate matrix data. Instead, they just initialize the matrix header that points to the specified
RyoheiHagimoto 0:0e0631af0305 874 data, which means that no data is copied. This operation is very efficient and can be used to
RyoheiHagimoto 0:0e0631af0305 875 process external data using OpenCV functions. The external data is not automatically deallocated, so
RyoheiHagimoto 0:0e0631af0305 876 you should take care of it.
RyoheiHagimoto 0:0e0631af0305 877 @param steps Array of ndims-1 steps in case of a multi-dimensional array (the last step is always
RyoheiHagimoto 0:0e0631af0305 878 set to the element size). If not specified, the matrix is assumed to be continuous.
RyoheiHagimoto 0:0e0631af0305 879 */
RyoheiHagimoto 0:0e0631af0305 880 Mat(int ndims, const int* sizes, int type, void* data, const size_t* steps=0);
RyoheiHagimoto 0:0e0631af0305 881
RyoheiHagimoto 0:0e0631af0305 882 /** @overload
RyoheiHagimoto 0:0e0631af0305 883 @param sizes Array of integers specifying an n-dimensional array shape.
RyoheiHagimoto 0:0e0631af0305 884 @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
RyoheiHagimoto 0:0e0631af0305 885 CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
RyoheiHagimoto 0:0e0631af0305 886 @param data Pointer to the user data. Matrix constructors that take data and step parameters do not
RyoheiHagimoto 0:0e0631af0305 887 allocate matrix data. Instead, they just initialize the matrix header that points to the specified
RyoheiHagimoto 0:0e0631af0305 888 data, which means that no data is copied. This operation is very efficient and can be used to
RyoheiHagimoto 0:0e0631af0305 889 process external data using OpenCV functions. The external data is not automatically deallocated, so
RyoheiHagimoto 0:0e0631af0305 890 you should take care of it.
RyoheiHagimoto 0:0e0631af0305 891 @param steps Array of ndims-1 steps in case of a multi-dimensional array (the last step is always
RyoheiHagimoto 0:0e0631af0305 892 set to the element size). If not specified, the matrix is assumed to be continuous.
RyoheiHagimoto 0:0e0631af0305 893 */
RyoheiHagimoto 0:0e0631af0305 894 Mat(const std::vector<int>& sizes, int type, void* data, const size_t* steps=0);
RyoheiHagimoto 0:0e0631af0305 895
RyoheiHagimoto 0:0e0631af0305 896 /** @overload
RyoheiHagimoto 0:0e0631af0305 897 @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
RyoheiHagimoto 0:0e0631af0305 898 by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
RyoheiHagimoto 0:0e0631af0305 899 associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
RyoheiHagimoto 0:0e0631af0305 900 formed using such a constructor, you also modify the corresponding elements of m . If you want to
RyoheiHagimoto 0:0e0631af0305 901 have an independent copy of the sub-array, use Mat::clone() .
RyoheiHagimoto 0:0e0631af0305 902 @param rowRange Range of the m rows to take. As usual, the range start is inclusive and the range
RyoheiHagimoto 0:0e0631af0305 903 end is exclusive. Use Range::all() to take all the rows.
RyoheiHagimoto 0:0e0631af0305 904 @param colRange Range of the m columns to take. Use Range::all() to take all the columns.
RyoheiHagimoto 0:0e0631af0305 905 */
RyoheiHagimoto 0:0e0631af0305 906 Mat(const Mat& m, const Range& rowRange, const Range& colRange=Range::all());
RyoheiHagimoto 0:0e0631af0305 907
RyoheiHagimoto 0:0e0631af0305 908 /** @overload
RyoheiHagimoto 0:0e0631af0305 909 @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
RyoheiHagimoto 0:0e0631af0305 910 by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
RyoheiHagimoto 0:0e0631af0305 911 associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
RyoheiHagimoto 0:0e0631af0305 912 formed using such a constructor, you also modify the corresponding elements of m . If you want to
RyoheiHagimoto 0:0e0631af0305 913 have an independent copy of the sub-array, use Mat::clone() .
RyoheiHagimoto 0:0e0631af0305 914 @param roi Region of interest.
RyoheiHagimoto 0:0e0631af0305 915 */
RyoheiHagimoto 0:0e0631af0305 916 Mat(const Mat& m, const Rect& roi);
RyoheiHagimoto 0:0e0631af0305 917
RyoheiHagimoto 0:0e0631af0305 918 /** @overload
RyoheiHagimoto 0:0e0631af0305 919 @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
RyoheiHagimoto 0:0e0631af0305 920 by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
RyoheiHagimoto 0:0e0631af0305 921 associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
RyoheiHagimoto 0:0e0631af0305 922 formed using such a constructor, you also modify the corresponding elements of m . If you want to
RyoheiHagimoto 0:0e0631af0305 923 have an independent copy of the sub-array, use Mat::clone() .
RyoheiHagimoto 0:0e0631af0305 924 @param ranges Array of selected ranges of m along each dimensionality.
RyoheiHagimoto 0:0e0631af0305 925 */
RyoheiHagimoto 0:0e0631af0305 926 Mat(const Mat& m, const Range* ranges);
RyoheiHagimoto 0:0e0631af0305 927
RyoheiHagimoto 0:0e0631af0305 928 /** @overload
RyoheiHagimoto 0:0e0631af0305 929 @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
RyoheiHagimoto 0:0e0631af0305 930 by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
RyoheiHagimoto 0:0e0631af0305 931 associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
RyoheiHagimoto 0:0e0631af0305 932 formed using such a constructor, you also modify the corresponding elements of m . If you want to
RyoheiHagimoto 0:0e0631af0305 933 have an independent copy of the sub-array, use Mat::clone() .
RyoheiHagimoto 0:0e0631af0305 934 @param ranges Array of selected ranges of m along each dimensionality.
RyoheiHagimoto 0:0e0631af0305 935 */
RyoheiHagimoto 0:0e0631af0305 936 Mat(const Mat& m, const std::vector<Range>& ranges);
RyoheiHagimoto 0:0e0631af0305 937
RyoheiHagimoto 0:0e0631af0305 938 /** @overload
RyoheiHagimoto 0:0e0631af0305 939 @param vec STL vector whose elements form the matrix. The matrix has a single column and the number
RyoheiHagimoto 0:0e0631af0305 940 of rows equal to the number of vector elements. Type of the matrix matches the type of vector
RyoheiHagimoto 0:0e0631af0305 941 elements. The constructor can handle arbitrary types, for which there is a properly declared
RyoheiHagimoto 0:0e0631af0305 942 DataType . This means that the vector elements must be primitive numbers or uni-type numerical
RyoheiHagimoto 0:0e0631af0305 943 tuples of numbers. Mixed-type structures are not supported. The corresponding constructor is
RyoheiHagimoto 0:0e0631af0305 944 explicit. Since STL vectors are not automatically converted to Mat instances, you should write
RyoheiHagimoto 0:0e0631af0305 945 Mat(vec) explicitly. Unless you copy the data into the matrix ( copyData=true ), no new elements
RyoheiHagimoto 0:0e0631af0305 946 will be added to the vector because it can potentially yield vector data reallocation, and, thus,
RyoheiHagimoto 0:0e0631af0305 947 the matrix data pointer will be invalid.
RyoheiHagimoto 0:0e0631af0305 948 @param copyData Flag to specify whether the underlying data of the STL vector should be copied
RyoheiHagimoto 0:0e0631af0305 949 to (true) or shared with (false) the newly constructed matrix. When the data is copied, the
RyoheiHagimoto 0:0e0631af0305 950 allocated buffer is managed using Mat reference counting mechanism. While the data is shared,
RyoheiHagimoto 0:0e0631af0305 951 the reference counter is NULL, and you should not deallocate the data until the matrix is not
RyoheiHagimoto 0:0e0631af0305 952 destructed.
RyoheiHagimoto 0:0e0631af0305 953 */
RyoheiHagimoto 0:0e0631af0305 954 template<typename _Tp> explicit Mat(const std::vector<_Tp>& vec, bool copyData=false);
RyoheiHagimoto 0:0e0631af0305 955
RyoheiHagimoto 0:0e0631af0305 956 /** @overload
RyoheiHagimoto 0:0e0631af0305 957 */
RyoheiHagimoto 0:0e0631af0305 958 template<typename _Tp, int n> explicit Mat(const Vec<_Tp, n>& vec, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 959
RyoheiHagimoto 0:0e0631af0305 960 /** @overload
RyoheiHagimoto 0:0e0631af0305 961 */
RyoheiHagimoto 0:0e0631af0305 962 template<typename _Tp, int m, int n> explicit Mat(const Matx<_Tp, m, n>& mtx, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 963
RyoheiHagimoto 0:0e0631af0305 964 /** @overload
RyoheiHagimoto 0:0e0631af0305 965 */
RyoheiHagimoto 0:0e0631af0305 966 template<typename _Tp> explicit Mat(const Point_<_Tp>& pt, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 967
RyoheiHagimoto 0:0e0631af0305 968 /** @overload
RyoheiHagimoto 0:0e0631af0305 969 */
RyoheiHagimoto 0:0e0631af0305 970 template<typename _Tp> explicit Mat(const Point3_<_Tp>& pt, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 971
RyoheiHagimoto 0:0e0631af0305 972 /** @overload
RyoheiHagimoto 0:0e0631af0305 973 */
RyoheiHagimoto 0:0e0631af0305 974 template<typename _Tp> explicit Mat(const MatCommaInitializer_<_Tp>& commaInitializer);
RyoheiHagimoto 0:0e0631af0305 975
RyoheiHagimoto 0:0e0631af0305 976 //! download data from GpuMat
RyoheiHagimoto 0:0e0631af0305 977 explicit Mat(const cuda::GpuMat& m);
RyoheiHagimoto 0:0e0631af0305 978
RyoheiHagimoto 0:0e0631af0305 979 //! destructor - calls release()
RyoheiHagimoto 0:0e0631af0305 980 ~Mat();
RyoheiHagimoto 0:0e0631af0305 981
RyoheiHagimoto 0:0e0631af0305 982 /** @brief assignment operators
RyoheiHagimoto 0:0e0631af0305 983
RyoheiHagimoto 0:0e0631af0305 984 These are available assignment operators. Since they all are very different, make sure to read the
RyoheiHagimoto 0:0e0631af0305 985 operator parameters description.
RyoheiHagimoto 0:0e0631af0305 986 @param m Assigned, right-hand-side matrix. Matrix assignment is an O(1) operation. This means that
RyoheiHagimoto 0:0e0631af0305 987 no data is copied but the data is shared and the reference counter, if any, is incremented. Before
RyoheiHagimoto 0:0e0631af0305 988 assigning new data, the old data is de-referenced via Mat::release .
RyoheiHagimoto 0:0e0631af0305 989 */
RyoheiHagimoto 0:0e0631af0305 990 Mat& operator = (const Mat& m);
RyoheiHagimoto 0:0e0631af0305 991
RyoheiHagimoto 0:0e0631af0305 992 /** @overload
RyoheiHagimoto 0:0e0631af0305 993 @param expr Assigned matrix expression object. As opposite to the first form of the assignment
RyoheiHagimoto 0:0e0631af0305 994 operation, the second form can reuse already allocated matrix if it has the right size and type to
RyoheiHagimoto 0:0e0631af0305 995 fit the matrix expression result. It is automatically handled by the real function that the matrix
RyoheiHagimoto 0:0e0631af0305 996 expressions is expanded to. For example, C=A+B is expanded to add(A, B, C), and add takes care of
RyoheiHagimoto 0:0e0631af0305 997 automatic C reallocation.
RyoheiHagimoto 0:0e0631af0305 998 */
RyoheiHagimoto 0:0e0631af0305 999 Mat& operator = (const MatExpr& expr);
RyoheiHagimoto 0:0e0631af0305 1000
RyoheiHagimoto 0:0e0631af0305 1001 //! retrieve UMat from Mat
RyoheiHagimoto 0:0e0631af0305 1002 UMat getUMat(int accessFlags, UMatUsageFlags usageFlags = USAGE_DEFAULT) const;
RyoheiHagimoto 0:0e0631af0305 1003
RyoheiHagimoto 0:0e0631af0305 1004 /** @brief Creates a matrix header for the specified matrix row.
RyoheiHagimoto 0:0e0631af0305 1005
RyoheiHagimoto 0:0e0631af0305 1006 The method makes a new header for the specified matrix row and returns it. This is an O(1)
RyoheiHagimoto 0:0e0631af0305 1007 operation, regardless of the matrix size. The underlying data of the new matrix is shared with the
RyoheiHagimoto 0:0e0631af0305 1008 original matrix. Here is the example of one of the classical basic matrix processing operations,
RyoheiHagimoto 0:0e0631af0305 1009 axpy, used by LU and many other algorithms:
RyoheiHagimoto 0:0e0631af0305 1010 @code
RyoheiHagimoto 0:0e0631af0305 1011 inline void matrix_axpy(Mat& A, int i, int j, double alpha)
RyoheiHagimoto 0:0e0631af0305 1012 {
RyoheiHagimoto 0:0e0631af0305 1013 A.row(i) += A.row(j)*alpha;
RyoheiHagimoto 0:0e0631af0305 1014 }
RyoheiHagimoto 0:0e0631af0305 1015 @endcode
RyoheiHagimoto 0:0e0631af0305 1016 @note In the current implementation, the following code does not work as expected:
RyoheiHagimoto 0:0e0631af0305 1017 @code
RyoheiHagimoto 0:0e0631af0305 1018 Mat A;
RyoheiHagimoto 0:0e0631af0305 1019 ...
RyoheiHagimoto 0:0e0631af0305 1020 A.row(i) = A.row(j); // will not work
RyoheiHagimoto 0:0e0631af0305 1021 @endcode
RyoheiHagimoto 0:0e0631af0305 1022 This happens because A.row(i) forms a temporary header that is further assigned to another header.
RyoheiHagimoto 0:0e0631af0305 1023 Remember that each of these operations is O(1), that is, no data is copied. Thus, the above
RyoheiHagimoto 0:0e0631af0305 1024 assignment is not true if you may have expected the j-th row to be copied to the i-th row. To
RyoheiHagimoto 0:0e0631af0305 1025 achieve that, you should either turn this simple assignment into an expression or use the
RyoheiHagimoto 0:0e0631af0305 1026 Mat::copyTo method:
RyoheiHagimoto 0:0e0631af0305 1027 @code
RyoheiHagimoto 0:0e0631af0305 1028 Mat A;
RyoheiHagimoto 0:0e0631af0305 1029 ...
RyoheiHagimoto 0:0e0631af0305 1030 // works, but looks a bit obscure.
RyoheiHagimoto 0:0e0631af0305 1031 A.row(i) = A.row(j) + 0;
RyoheiHagimoto 0:0e0631af0305 1032 // this is a bit longer, but the recommended method.
RyoheiHagimoto 0:0e0631af0305 1033 A.row(j).copyTo(A.row(i));
RyoheiHagimoto 0:0e0631af0305 1034 @endcode
RyoheiHagimoto 0:0e0631af0305 1035 @param y A 0-based row index.
RyoheiHagimoto 0:0e0631af0305 1036 */
RyoheiHagimoto 0:0e0631af0305 1037 Mat row(int y) const;
RyoheiHagimoto 0:0e0631af0305 1038
RyoheiHagimoto 0:0e0631af0305 1039 /** @brief Creates a matrix header for the specified matrix column.
RyoheiHagimoto 0:0e0631af0305 1040
RyoheiHagimoto 0:0e0631af0305 1041 The method makes a new header for the specified matrix column and returns it. This is an O(1)
RyoheiHagimoto 0:0e0631af0305 1042 operation, regardless of the matrix size. The underlying data of the new matrix is shared with the
RyoheiHagimoto 0:0e0631af0305 1043 original matrix. See also the Mat::row description.
RyoheiHagimoto 0:0e0631af0305 1044 @param x A 0-based column index.
RyoheiHagimoto 0:0e0631af0305 1045 */
RyoheiHagimoto 0:0e0631af0305 1046 Mat col(int x) const;
RyoheiHagimoto 0:0e0631af0305 1047
RyoheiHagimoto 0:0e0631af0305 1048 /** @brief Creates a matrix header for the specified row span.
RyoheiHagimoto 0:0e0631af0305 1049
RyoheiHagimoto 0:0e0631af0305 1050 The method makes a new header for the specified row span of the matrix. Similarly to Mat::row and
RyoheiHagimoto 0:0e0631af0305 1051 Mat::col , this is an O(1) operation.
RyoheiHagimoto 0:0e0631af0305 1052 @param startrow An inclusive 0-based start index of the row span.
RyoheiHagimoto 0:0e0631af0305 1053 @param endrow An exclusive 0-based ending index of the row span.
RyoheiHagimoto 0:0e0631af0305 1054 */
RyoheiHagimoto 0:0e0631af0305 1055 Mat rowRange(int startrow, int endrow) const;
RyoheiHagimoto 0:0e0631af0305 1056
RyoheiHagimoto 0:0e0631af0305 1057 /** @overload
RyoheiHagimoto 0:0e0631af0305 1058 @param r Range structure containing both the start and the end indices.
RyoheiHagimoto 0:0e0631af0305 1059 */
RyoheiHagimoto 0:0e0631af0305 1060 Mat rowRange(const Range& r) const;
RyoheiHagimoto 0:0e0631af0305 1061
RyoheiHagimoto 0:0e0631af0305 1062 /** @brief Creates a matrix header for the specified column span.
RyoheiHagimoto 0:0e0631af0305 1063
RyoheiHagimoto 0:0e0631af0305 1064 The method makes a new header for the specified column span of the matrix. Similarly to Mat::row and
RyoheiHagimoto 0:0e0631af0305 1065 Mat::col , this is an O(1) operation.
RyoheiHagimoto 0:0e0631af0305 1066 @param startcol An inclusive 0-based start index of the column span.
RyoheiHagimoto 0:0e0631af0305 1067 @param endcol An exclusive 0-based ending index of the column span.
RyoheiHagimoto 0:0e0631af0305 1068 */
RyoheiHagimoto 0:0e0631af0305 1069 Mat colRange(int startcol, int endcol) const;
RyoheiHagimoto 0:0e0631af0305 1070
RyoheiHagimoto 0:0e0631af0305 1071 /** @overload
RyoheiHagimoto 0:0e0631af0305 1072 @param r Range structure containing both the start and the end indices.
RyoheiHagimoto 0:0e0631af0305 1073 */
RyoheiHagimoto 0:0e0631af0305 1074 Mat colRange(const Range& r) const;
RyoheiHagimoto 0:0e0631af0305 1075
RyoheiHagimoto 0:0e0631af0305 1076 /** @brief Extracts a diagonal from a matrix
RyoheiHagimoto 0:0e0631af0305 1077
RyoheiHagimoto 0:0e0631af0305 1078 The method makes a new header for the specified matrix diagonal. The new matrix is represented as a
RyoheiHagimoto 0:0e0631af0305 1079 single-column matrix. Similarly to Mat::row and Mat::col, this is an O(1) operation.
RyoheiHagimoto 0:0e0631af0305 1080 @param d index of the diagonal, with the following values:
RyoheiHagimoto 0:0e0631af0305 1081 - `d=0` is the main diagonal.
RyoheiHagimoto 0:0e0631af0305 1082 - `d>0` is a diagonal from the lower half. For example, d=1 means the diagonal is set
RyoheiHagimoto 0:0e0631af0305 1083 immediately below the main one.
RyoheiHagimoto 0:0e0631af0305 1084 - `d<0` is a diagonal from the upper half. For example, d=-1 means the diagonal is set
RyoheiHagimoto 0:0e0631af0305 1085 immediately above the main one.
RyoheiHagimoto 0:0e0631af0305 1086 */
RyoheiHagimoto 0:0e0631af0305 1087 Mat diag(int d=0) const;
RyoheiHagimoto 0:0e0631af0305 1088
RyoheiHagimoto 0:0e0631af0305 1089 /** @brief creates a diagonal matrix
RyoheiHagimoto 0:0e0631af0305 1090
RyoheiHagimoto 0:0e0631af0305 1091 The method creates a square diagonal matrix from specified main diagonal.
RyoheiHagimoto 0:0e0631af0305 1092 @param d One-dimensional matrix that represents the main diagonal.
RyoheiHagimoto 0:0e0631af0305 1093 */
RyoheiHagimoto 0:0e0631af0305 1094 static Mat diag(const Mat& d);
RyoheiHagimoto 0:0e0631af0305 1095
RyoheiHagimoto 0:0e0631af0305 1096 /** @brief Creates a full copy of the array and the underlying data.
RyoheiHagimoto 0:0e0631af0305 1097
RyoheiHagimoto 0:0e0631af0305 1098 The method creates a full copy of the array. The original step[] is not taken into account. So, the
RyoheiHagimoto 0:0e0631af0305 1099 array copy is a continuous array occupying total()*elemSize() bytes.
RyoheiHagimoto 0:0e0631af0305 1100 */
RyoheiHagimoto 0:0e0631af0305 1101 Mat clone() const;
RyoheiHagimoto 0:0e0631af0305 1102
RyoheiHagimoto 0:0e0631af0305 1103 /** @brief Copies the matrix to another one.
RyoheiHagimoto 0:0e0631af0305 1104
RyoheiHagimoto 0:0e0631af0305 1105 The method copies the matrix data to another matrix. Before copying the data, the method invokes :
RyoheiHagimoto 0:0e0631af0305 1106 @code
RyoheiHagimoto 0:0e0631af0305 1107 m.create(this->size(), this->type());
RyoheiHagimoto 0:0e0631af0305 1108 @endcode
RyoheiHagimoto 0:0e0631af0305 1109 so that the destination matrix is reallocated if needed. While m.copyTo(m); works flawlessly, the
RyoheiHagimoto 0:0e0631af0305 1110 function does not handle the case of a partial overlap between the source and the destination
RyoheiHagimoto 0:0e0631af0305 1111 matrices.
RyoheiHagimoto 0:0e0631af0305 1112
RyoheiHagimoto 0:0e0631af0305 1113 When the operation mask is specified, if the Mat::create call shown above reallocates the matrix,
RyoheiHagimoto 0:0e0631af0305 1114 the newly allocated matrix is initialized with all zeros before copying the data.
RyoheiHagimoto 0:0e0631af0305 1115 @param m Destination matrix. If it does not have a proper size or type before the operation, it is
RyoheiHagimoto 0:0e0631af0305 1116 reallocated.
RyoheiHagimoto 0:0e0631af0305 1117 */
RyoheiHagimoto 0:0e0631af0305 1118 void copyTo( OutputArray m ) const;
RyoheiHagimoto 0:0e0631af0305 1119
RyoheiHagimoto 0:0e0631af0305 1120 /** @overload
RyoheiHagimoto 0:0e0631af0305 1121 @param m Destination matrix. If it does not have a proper size or type before the operation, it is
RyoheiHagimoto 0:0e0631af0305 1122 reallocated.
RyoheiHagimoto 0:0e0631af0305 1123 @param mask Operation mask. Its non-zero elements indicate which matrix elements need to be copied.
RyoheiHagimoto 0:0e0631af0305 1124 The mask has to be of type CV_8U and can have 1 or multiple channels.
RyoheiHagimoto 0:0e0631af0305 1125 */
RyoheiHagimoto 0:0e0631af0305 1126 void copyTo( OutputArray m, InputArray mask ) const;
RyoheiHagimoto 0:0e0631af0305 1127
RyoheiHagimoto 0:0e0631af0305 1128 /** @brief Converts an array to another data type with optional scaling.
RyoheiHagimoto 0:0e0631af0305 1129
RyoheiHagimoto 0:0e0631af0305 1130 The method converts source pixel values to the target data type. saturate_cast\<\> is applied at
RyoheiHagimoto 0:0e0631af0305 1131 the end to avoid possible overflows:
RyoheiHagimoto 0:0e0631af0305 1132
RyoheiHagimoto 0:0e0631af0305 1133 \f[m(x,y) = saturate \_ cast<rType>( \alpha (*this)(x,y) + \beta )\f]
RyoheiHagimoto 0:0e0631af0305 1134 @param m output matrix; if it does not have a proper size or type before the operation, it is
RyoheiHagimoto 0:0e0631af0305 1135 reallocated.
RyoheiHagimoto 0:0e0631af0305 1136 @param rtype desired output matrix type or, rather, the depth since the number of channels are the
RyoheiHagimoto 0:0e0631af0305 1137 same as the input has; if rtype is negative, the output matrix will have the same type as the input.
RyoheiHagimoto 0:0e0631af0305 1138 @param alpha optional scale factor.
RyoheiHagimoto 0:0e0631af0305 1139 @param beta optional delta added to the scaled values.
RyoheiHagimoto 0:0e0631af0305 1140 */
RyoheiHagimoto 0:0e0631af0305 1141 void convertTo( OutputArray m, int rtype, double alpha=1, double beta=0 ) const;
RyoheiHagimoto 0:0e0631af0305 1142
RyoheiHagimoto 0:0e0631af0305 1143 /** @brief Provides a functional form of convertTo.
RyoheiHagimoto 0:0e0631af0305 1144
RyoheiHagimoto 0:0e0631af0305 1145 This is an internally used method called by the @ref MatrixExpressions engine.
RyoheiHagimoto 0:0e0631af0305 1146 @param m Destination array.
RyoheiHagimoto 0:0e0631af0305 1147 @param type Desired destination array depth (or -1 if it should be the same as the source type).
RyoheiHagimoto 0:0e0631af0305 1148 */
RyoheiHagimoto 0:0e0631af0305 1149 void assignTo( Mat& m, int type=-1 ) const;
RyoheiHagimoto 0:0e0631af0305 1150
RyoheiHagimoto 0:0e0631af0305 1151 /** @brief Sets all or some of the array elements to the specified value.
RyoheiHagimoto 0:0e0631af0305 1152 @param s Assigned scalar converted to the actual array type.
RyoheiHagimoto 0:0e0631af0305 1153 */
RyoheiHagimoto 0:0e0631af0305 1154 Mat& operator = (const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 1155
RyoheiHagimoto 0:0e0631af0305 1156 /** @brief Sets all or some of the array elements to the specified value.
RyoheiHagimoto 0:0e0631af0305 1157
RyoheiHagimoto 0:0e0631af0305 1158 This is an advanced variant of the Mat::operator=(const Scalar& s) operator.
RyoheiHagimoto 0:0e0631af0305 1159 @param value Assigned scalar converted to the actual array type.
RyoheiHagimoto 0:0e0631af0305 1160 @param mask Operation mask of the same size as \*this.
RyoheiHagimoto 0:0e0631af0305 1161 */
RyoheiHagimoto 0:0e0631af0305 1162 Mat& setTo(InputArray value, InputArray mask=noArray());
RyoheiHagimoto 0:0e0631af0305 1163
RyoheiHagimoto 0:0e0631af0305 1164 /** @brief Changes the shape and/or the number of channels of a 2D matrix without copying the data.
RyoheiHagimoto 0:0e0631af0305 1165
RyoheiHagimoto 0:0e0631af0305 1166 The method makes a new matrix header for \*this elements. The new matrix may have a different size
RyoheiHagimoto 0:0e0631af0305 1167 and/or different number of channels. Any combination is possible if:
RyoheiHagimoto 0:0e0631af0305 1168 - No extra elements are included into the new matrix and no elements are excluded. Consequently,
RyoheiHagimoto 0:0e0631af0305 1169 the product rows\*cols\*channels() must stay the same after the transformation.
RyoheiHagimoto 0:0e0631af0305 1170 - No data is copied. That is, this is an O(1) operation. Consequently, if you change the number of
RyoheiHagimoto 0:0e0631af0305 1171 rows, or the operation changes the indices of elements row in some other way, the matrix must be
RyoheiHagimoto 0:0e0631af0305 1172 continuous. See Mat::isContinuous .
RyoheiHagimoto 0:0e0631af0305 1173
RyoheiHagimoto 0:0e0631af0305 1174 For example, if there is a set of 3D points stored as an STL vector, and you want to represent the
RyoheiHagimoto 0:0e0631af0305 1175 points as a 3xN matrix, do the following:
RyoheiHagimoto 0:0e0631af0305 1176 @code
RyoheiHagimoto 0:0e0631af0305 1177 std::vector<Point3f> vec;
RyoheiHagimoto 0:0e0631af0305 1178 ...
RyoheiHagimoto 0:0e0631af0305 1179 Mat pointMat = Mat(vec). // convert vector to Mat, O(1) operation
RyoheiHagimoto 0:0e0631af0305 1180 reshape(1). // make Nx3 1-channel matrix out of Nx1 3-channel.
RyoheiHagimoto 0:0e0631af0305 1181 // Also, an O(1) operation
RyoheiHagimoto 0:0e0631af0305 1182 t(); // finally, transpose the Nx3 matrix.
RyoheiHagimoto 0:0e0631af0305 1183 // This involves copying all the elements
RyoheiHagimoto 0:0e0631af0305 1184 @endcode
RyoheiHagimoto 0:0e0631af0305 1185 @param cn New number of channels. If the parameter is 0, the number of channels remains the same.
RyoheiHagimoto 0:0e0631af0305 1186 @param rows New number of rows. If the parameter is 0, the number of rows remains the same.
RyoheiHagimoto 0:0e0631af0305 1187 */
RyoheiHagimoto 0:0e0631af0305 1188 Mat reshape(int cn, int rows=0) const;
RyoheiHagimoto 0:0e0631af0305 1189
RyoheiHagimoto 0:0e0631af0305 1190 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1191 Mat reshape(int cn, int newndims, const int* newsz) const;
RyoheiHagimoto 0:0e0631af0305 1192
RyoheiHagimoto 0:0e0631af0305 1193 /** @brief Transposes a matrix.
RyoheiHagimoto 0:0e0631af0305 1194
RyoheiHagimoto 0:0e0631af0305 1195 The method performs matrix transposition by means of matrix expressions. It does not perform the
RyoheiHagimoto 0:0e0631af0305 1196 actual transposition but returns a temporary matrix transposition object that can be further used as
RyoheiHagimoto 0:0e0631af0305 1197 a part of more complex matrix expressions or can be assigned to a matrix:
RyoheiHagimoto 0:0e0631af0305 1198 @code
RyoheiHagimoto 0:0e0631af0305 1199 Mat A1 = A + Mat::eye(A.size(), A.type())*lambda;
RyoheiHagimoto 0:0e0631af0305 1200 Mat C = A1.t()*A1; // compute (A + lambda*I)^t * (A + lamda*I)
RyoheiHagimoto 0:0e0631af0305 1201 @endcode
RyoheiHagimoto 0:0e0631af0305 1202 */
RyoheiHagimoto 0:0e0631af0305 1203 MatExpr t() const;
RyoheiHagimoto 0:0e0631af0305 1204
RyoheiHagimoto 0:0e0631af0305 1205 /** @brief Inverses a matrix.
RyoheiHagimoto 0:0e0631af0305 1206
RyoheiHagimoto 0:0e0631af0305 1207 The method performs a matrix inversion by means of matrix expressions. This means that a temporary
RyoheiHagimoto 0:0e0631af0305 1208 matrix inversion object is returned by the method and can be used further as a part of more complex
RyoheiHagimoto 0:0e0631af0305 1209 matrix expressions or can be assigned to a matrix.
RyoheiHagimoto 0:0e0631af0305 1210 @param method Matrix inversion method. One of cv::DecompTypes
RyoheiHagimoto 0:0e0631af0305 1211 */
RyoheiHagimoto 0:0e0631af0305 1212 MatExpr inv(int method=DECOMP_LU) const;
RyoheiHagimoto 0:0e0631af0305 1213
RyoheiHagimoto 0:0e0631af0305 1214 /** @brief Performs an element-wise multiplication or division of the two matrices.
RyoheiHagimoto 0:0e0631af0305 1215
RyoheiHagimoto 0:0e0631af0305 1216 The method returns a temporary object encoding per-element array multiplication, with optional
RyoheiHagimoto 0:0e0631af0305 1217 scale. Note that this is not a matrix multiplication that corresponds to a simpler "\*" operator.
RyoheiHagimoto 0:0e0631af0305 1218
RyoheiHagimoto 0:0e0631af0305 1219 Example:
RyoheiHagimoto 0:0e0631af0305 1220 @code
RyoheiHagimoto 0:0e0631af0305 1221 Mat C = A.mul(5/B); // equivalent to divide(A, B, C, 5)
RyoheiHagimoto 0:0e0631af0305 1222 @endcode
RyoheiHagimoto 0:0e0631af0305 1223 @param m Another array of the same type and the same size as \*this, or a matrix expression.
RyoheiHagimoto 0:0e0631af0305 1224 @param scale Optional scale factor.
RyoheiHagimoto 0:0e0631af0305 1225 */
RyoheiHagimoto 0:0e0631af0305 1226 MatExpr mul(InputArray m, double scale=1) const;
RyoheiHagimoto 0:0e0631af0305 1227
RyoheiHagimoto 0:0e0631af0305 1228 /** @brief Computes a cross-product of two 3-element vectors.
RyoheiHagimoto 0:0e0631af0305 1229
RyoheiHagimoto 0:0e0631af0305 1230 The method computes a cross-product of two 3-element vectors. The vectors must be 3-element
RyoheiHagimoto 0:0e0631af0305 1231 floating-point vectors of the same shape and size. The result is another 3-element vector of the
RyoheiHagimoto 0:0e0631af0305 1232 same shape and type as operands.
RyoheiHagimoto 0:0e0631af0305 1233 @param m Another cross-product operand.
RyoheiHagimoto 0:0e0631af0305 1234 */
RyoheiHagimoto 0:0e0631af0305 1235 Mat cross(InputArray m) const;
RyoheiHagimoto 0:0e0631af0305 1236
RyoheiHagimoto 0:0e0631af0305 1237 /** @brief Computes a dot-product of two vectors.
RyoheiHagimoto 0:0e0631af0305 1238
RyoheiHagimoto 0:0e0631af0305 1239 The method computes a dot-product of two matrices. If the matrices are not single-column or
RyoheiHagimoto 0:0e0631af0305 1240 single-row vectors, the top-to-bottom left-to-right scan ordering is used to treat them as 1D
RyoheiHagimoto 0:0e0631af0305 1241 vectors. The vectors must have the same size and type. If the matrices have more than one channel,
RyoheiHagimoto 0:0e0631af0305 1242 the dot products from all the channels are summed together.
RyoheiHagimoto 0:0e0631af0305 1243 @param m another dot-product operand.
RyoheiHagimoto 0:0e0631af0305 1244 */
RyoheiHagimoto 0:0e0631af0305 1245 double dot(InputArray m) const;
RyoheiHagimoto 0:0e0631af0305 1246
RyoheiHagimoto 0:0e0631af0305 1247 /** @brief Returns a zero array of the specified size and type.
RyoheiHagimoto 0:0e0631af0305 1248
RyoheiHagimoto 0:0e0631af0305 1249 The method returns a Matlab-style zero array initializer. It can be used to quickly form a constant
RyoheiHagimoto 0:0e0631af0305 1250 array as a function parameter, part of a matrix expression, or as a matrix initializer. :
RyoheiHagimoto 0:0e0631af0305 1251 @code
RyoheiHagimoto 0:0e0631af0305 1252 Mat A;
RyoheiHagimoto 0:0e0631af0305 1253 A = Mat::zeros(3, 3, CV_32F);
RyoheiHagimoto 0:0e0631af0305 1254 @endcode
RyoheiHagimoto 0:0e0631af0305 1255 In the example above, a new matrix is allocated only if A is not a 3x3 floating-point matrix.
RyoheiHagimoto 0:0e0631af0305 1256 Otherwise, the existing matrix A is filled with zeros.
RyoheiHagimoto 0:0e0631af0305 1257 @param rows Number of rows.
RyoheiHagimoto 0:0e0631af0305 1258 @param cols Number of columns.
RyoheiHagimoto 0:0e0631af0305 1259 @param type Created matrix type.
RyoheiHagimoto 0:0e0631af0305 1260 */
RyoheiHagimoto 0:0e0631af0305 1261 static MatExpr zeros(int rows, int cols, int type);
RyoheiHagimoto 0:0e0631af0305 1262
RyoheiHagimoto 0:0e0631af0305 1263 /** @overload
RyoheiHagimoto 0:0e0631af0305 1264 @param size Alternative to the matrix size specification Size(cols, rows) .
RyoheiHagimoto 0:0e0631af0305 1265 @param type Created matrix type.
RyoheiHagimoto 0:0e0631af0305 1266 */
RyoheiHagimoto 0:0e0631af0305 1267 static MatExpr zeros(Size size, int type);
RyoheiHagimoto 0:0e0631af0305 1268
RyoheiHagimoto 0:0e0631af0305 1269 /** @overload
RyoheiHagimoto 0:0e0631af0305 1270 @param ndims Array dimensionality.
RyoheiHagimoto 0:0e0631af0305 1271 @param sz Array of integers specifying the array shape.
RyoheiHagimoto 0:0e0631af0305 1272 @param type Created matrix type.
RyoheiHagimoto 0:0e0631af0305 1273 */
RyoheiHagimoto 0:0e0631af0305 1274 static MatExpr zeros(int ndims, const int* sz, int type);
RyoheiHagimoto 0:0e0631af0305 1275
RyoheiHagimoto 0:0e0631af0305 1276 /** @brief Returns an array of all 1's of the specified size and type.
RyoheiHagimoto 0:0e0631af0305 1277
RyoheiHagimoto 0:0e0631af0305 1278 The method returns a Matlab-style 1's array initializer, similarly to Mat::zeros. Note that using
RyoheiHagimoto 0:0e0631af0305 1279 this method you can initialize an array with an arbitrary value, using the following Matlab idiom:
RyoheiHagimoto 0:0e0631af0305 1280 @code
RyoheiHagimoto 0:0e0631af0305 1281 Mat A = Mat::ones(100, 100, CV_8U)*3; // make 100x100 matrix filled with 3.
RyoheiHagimoto 0:0e0631af0305 1282 @endcode
RyoheiHagimoto 0:0e0631af0305 1283 The above operation does not form a 100x100 matrix of 1's and then multiply it by 3. Instead, it
RyoheiHagimoto 0:0e0631af0305 1284 just remembers the scale factor (3 in this case) and use it when actually invoking the matrix
RyoheiHagimoto 0:0e0631af0305 1285 initializer.
RyoheiHagimoto 0:0e0631af0305 1286 @param rows Number of rows.
RyoheiHagimoto 0:0e0631af0305 1287 @param cols Number of columns.
RyoheiHagimoto 0:0e0631af0305 1288 @param type Created matrix type.
RyoheiHagimoto 0:0e0631af0305 1289 */
RyoheiHagimoto 0:0e0631af0305 1290 static MatExpr ones(int rows, int cols, int type);
RyoheiHagimoto 0:0e0631af0305 1291
RyoheiHagimoto 0:0e0631af0305 1292 /** @overload
RyoheiHagimoto 0:0e0631af0305 1293 @param size Alternative to the matrix size specification Size(cols, rows) .
RyoheiHagimoto 0:0e0631af0305 1294 @param type Created matrix type.
RyoheiHagimoto 0:0e0631af0305 1295 */
RyoheiHagimoto 0:0e0631af0305 1296 static MatExpr ones(Size size, int type);
RyoheiHagimoto 0:0e0631af0305 1297
RyoheiHagimoto 0:0e0631af0305 1298 /** @overload
RyoheiHagimoto 0:0e0631af0305 1299 @param ndims Array dimensionality.
RyoheiHagimoto 0:0e0631af0305 1300 @param sz Array of integers specifying the array shape.
RyoheiHagimoto 0:0e0631af0305 1301 @param type Created matrix type.
RyoheiHagimoto 0:0e0631af0305 1302 */
RyoheiHagimoto 0:0e0631af0305 1303 static MatExpr ones(int ndims, const int* sz, int type);
RyoheiHagimoto 0:0e0631af0305 1304
RyoheiHagimoto 0:0e0631af0305 1305 /** @brief Returns an identity matrix of the specified size and type.
RyoheiHagimoto 0:0e0631af0305 1306
RyoheiHagimoto 0:0e0631af0305 1307 The method returns a Matlab-style identity matrix initializer, similarly to Mat::zeros. Similarly to
RyoheiHagimoto 0:0e0631af0305 1308 Mat::ones, you can use a scale operation to create a scaled identity matrix efficiently:
RyoheiHagimoto 0:0e0631af0305 1309 @code
RyoheiHagimoto 0:0e0631af0305 1310 // make a 4x4 diagonal matrix with 0.1's on the diagonal.
RyoheiHagimoto 0:0e0631af0305 1311 Mat A = Mat::eye(4, 4, CV_32F)*0.1;
RyoheiHagimoto 0:0e0631af0305 1312 @endcode
RyoheiHagimoto 0:0e0631af0305 1313 @param rows Number of rows.
RyoheiHagimoto 0:0e0631af0305 1314 @param cols Number of columns.
RyoheiHagimoto 0:0e0631af0305 1315 @param type Created matrix type.
RyoheiHagimoto 0:0e0631af0305 1316 */
RyoheiHagimoto 0:0e0631af0305 1317 static MatExpr eye(int rows, int cols, int type);
RyoheiHagimoto 0:0e0631af0305 1318
RyoheiHagimoto 0:0e0631af0305 1319 /** @overload
RyoheiHagimoto 0:0e0631af0305 1320 @param size Alternative matrix size specification as Size(cols, rows) .
RyoheiHagimoto 0:0e0631af0305 1321 @param type Created matrix type.
RyoheiHagimoto 0:0e0631af0305 1322 */
RyoheiHagimoto 0:0e0631af0305 1323 static MatExpr eye(Size size, int type);
RyoheiHagimoto 0:0e0631af0305 1324
RyoheiHagimoto 0:0e0631af0305 1325 /** @brief Allocates new array data if needed.
RyoheiHagimoto 0:0e0631af0305 1326
RyoheiHagimoto 0:0e0631af0305 1327 This is one of the key Mat methods. Most new-style OpenCV functions and methods that produce arrays
RyoheiHagimoto 0:0e0631af0305 1328 call this method for each output array. The method uses the following algorithm:
RyoheiHagimoto 0:0e0631af0305 1329
RyoheiHagimoto 0:0e0631af0305 1330 -# If the current array shape and the type match the new ones, return immediately. Otherwise,
RyoheiHagimoto 0:0e0631af0305 1331 de-reference the previous data by calling Mat::release.
RyoheiHagimoto 0:0e0631af0305 1332 -# Initialize the new header.
RyoheiHagimoto 0:0e0631af0305 1333 -# Allocate the new data of total()\*elemSize() bytes.
RyoheiHagimoto 0:0e0631af0305 1334 -# Allocate the new, associated with the data, reference counter and set it to 1.
RyoheiHagimoto 0:0e0631af0305 1335
RyoheiHagimoto 0:0e0631af0305 1336 Such a scheme makes the memory management robust and efficient at the same time and helps avoid
RyoheiHagimoto 0:0e0631af0305 1337 extra typing for you. This means that usually there is no need to explicitly allocate output arrays.
RyoheiHagimoto 0:0e0631af0305 1338 That is, instead of writing:
RyoheiHagimoto 0:0e0631af0305 1339 @code
RyoheiHagimoto 0:0e0631af0305 1340 Mat color;
RyoheiHagimoto 0:0e0631af0305 1341 ...
RyoheiHagimoto 0:0e0631af0305 1342 Mat gray(color.rows, color.cols, color.depth());
RyoheiHagimoto 0:0e0631af0305 1343 cvtColor(color, gray, COLOR_BGR2GRAY);
RyoheiHagimoto 0:0e0631af0305 1344 @endcode
RyoheiHagimoto 0:0e0631af0305 1345 you can simply write:
RyoheiHagimoto 0:0e0631af0305 1346 @code
RyoheiHagimoto 0:0e0631af0305 1347 Mat color;
RyoheiHagimoto 0:0e0631af0305 1348 ...
RyoheiHagimoto 0:0e0631af0305 1349 Mat gray;
RyoheiHagimoto 0:0e0631af0305 1350 cvtColor(color, gray, COLOR_BGR2GRAY);
RyoheiHagimoto 0:0e0631af0305 1351 @endcode
RyoheiHagimoto 0:0e0631af0305 1352 because cvtColor, as well as the most of OpenCV functions, calls Mat::create() for the output array
RyoheiHagimoto 0:0e0631af0305 1353 internally.
RyoheiHagimoto 0:0e0631af0305 1354 @param rows New number of rows.
RyoheiHagimoto 0:0e0631af0305 1355 @param cols New number of columns.
RyoheiHagimoto 0:0e0631af0305 1356 @param type New matrix type.
RyoheiHagimoto 0:0e0631af0305 1357 */
RyoheiHagimoto 0:0e0631af0305 1358 void create(int rows, int cols, int type);
RyoheiHagimoto 0:0e0631af0305 1359
RyoheiHagimoto 0:0e0631af0305 1360 /** @overload
RyoheiHagimoto 0:0e0631af0305 1361 @param size Alternative new matrix size specification: Size(cols, rows)
RyoheiHagimoto 0:0e0631af0305 1362 @param type New matrix type.
RyoheiHagimoto 0:0e0631af0305 1363 */
RyoheiHagimoto 0:0e0631af0305 1364 void create(Size size, int type);
RyoheiHagimoto 0:0e0631af0305 1365
RyoheiHagimoto 0:0e0631af0305 1366 /** @overload
RyoheiHagimoto 0:0e0631af0305 1367 @param ndims New array dimensionality.
RyoheiHagimoto 0:0e0631af0305 1368 @param sizes Array of integers specifying a new array shape.
RyoheiHagimoto 0:0e0631af0305 1369 @param type New matrix type.
RyoheiHagimoto 0:0e0631af0305 1370 */
RyoheiHagimoto 0:0e0631af0305 1371 void create(int ndims, const int* sizes, int type);
RyoheiHagimoto 0:0e0631af0305 1372
RyoheiHagimoto 0:0e0631af0305 1373 /** @overload
RyoheiHagimoto 0:0e0631af0305 1374 @param sizes Array of integers specifying a new array shape.
RyoheiHagimoto 0:0e0631af0305 1375 @param type New matrix type.
RyoheiHagimoto 0:0e0631af0305 1376 */
RyoheiHagimoto 0:0e0631af0305 1377 void create(const std::vector<int>& sizes, int type);
RyoheiHagimoto 0:0e0631af0305 1378
RyoheiHagimoto 0:0e0631af0305 1379 /** @brief Increments the reference counter.
RyoheiHagimoto 0:0e0631af0305 1380
RyoheiHagimoto 0:0e0631af0305 1381 The method increments the reference counter associated with the matrix data. If the matrix header
RyoheiHagimoto 0:0e0631af0305 1382 points to an external data set (see Mat::Mat ), the reference counter is NULL, and the method has no
RyoheiHagimoto 0:0e0631af0305 1383 effect in this case. Normally, to avoid memory leaks, the method should not be called explicitly. It
RyoheiHagimoto 0:0e0631af0305 1384 is called implicitly by the matrix assignment operator. The reference counter increment is an atomic
RyoheiHagimoto 0:0e0631af0305 1385 operation on the platforms that support it. Thus, it is safe to operate on the same matrices
RyoheiHagimoto 0:0e0631af0305 1386 asynchronously in different threads.
RyoheiHagimoto 0:0e0631af0305 1387 */
RyoheiHagimoto 0:0e0631af0305 1388 void addref();
RyoheiHagimoto 0:0e0631af0305 1389
RyoheiHagimoto 0:0e0631af0305 1390 /** @brief Decrements the reference counter and deallocates the matrix if needed.
RyoheiHagimoto 0:0e0631af0305 1391
RyoheiHagimoto 0:0e0631af0305 1392 The method decrements the reference counter associated with the matrix data. When the reference
RyoheiHagimoto 0:0e0631af0305 1393 counter reaches 0, the matrix data is deallocated and the data and the reference counter pointers
RyoheiHagimoto 0:0e0631af0305 1394 are set to NULL's. If the matrix header points to an external data set (see Mat::Mat ), the
RyoheiHagimoto 0:0e0631af0305 1395 reference counter is NULL, and the method has no effect in this case.
RyoheiHagimoto 0:0e0631af0305 1396
RyoheiHagimoto 0:0e0631af0305 1397 This method can be called manually to force the matrix data deallocation. But since this method is
RyoheiHagimoto 0:0e0631af0305 1398 automatically called in the destructor, or by any other method that changes the data pointer, it is
RyoheiHagimoto 0:0e0631af0305 1399 usually not needed. The reference counter decrement and check for 0 is an atomic operation on the
RyoheiHagimoto 0:0e0631af0305 1400 platforms that support it. Thus, it is safe to operate on the same matrices asynchronously in
RyoheiHagimoto 0:0e0631af0305 1401 different threads.
RyoheiHagimoto 0:0e0631af0305 1402 */
RyoheiHagimoto 0:0e0631af0305 1403 void release();
RyoheiHagimoto 0:0e0631af0305 1404
RyoheiHagimoto 0:0e0631af0305 1405 //! deallocates the matrix data
RyoheiHagimoto 0:0e0631af0305 1406 void deallocate();
RyoheiHagimoto 0:0e0631af0305 1407 //! internal use function; properly re-allocates _size, _step arrays
RyoheiHagimoto 0:0e0631af0305 1408 void copySize(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 1409
RyoheiHagimoto 0:0e0631af0305 1410 /** @brief Reserves space for the certain number of rows.
RyoheiHagimoto 0:0e0631af0305 1411
RyoheiHagimoto 0:0e0631af0305 1412 The method reserves space for sz rows. If the matrix already has enough space to store sz rows,
RyoheiHagimoto 0:0e0631af0305 1413 nothing happens. If the matrix is reallocated, the first Mat::rows rows are preserved. The method
RyoheiHagimoto 0:0e0631af0305 1414 emulates the corresponding method of the STL vector class.
RyoheiHagimoto 0:0e0631af0305 1415 @param sz Number of rows.
RyoheiHagimoto 0:0e0631af0305 1416 */
RyoheiHagimoto 0:0e0631af0305 1417 void reserve(size_t sz);
RyoheiHagimoto 0:0e0631af0305 1418
RyoheiHagimoto 0:0e0631af0305 1419 /** @brief Changes the number of matrix rows.
RyoheiHagimoto 0:0e0631af0305 1420
RyoheiHagimoto 0:0e0631af0305 1421 The methods change the number of matrix rows. If the matrix is reallocated, the first
RyoheiHagimoto 0:0e0631af0305 1422 min(Mat::rows, sz) rows are preserved. The methods emulate the corresponding methods of the STL
RyoheiHagimoto 0:0e0631af0305 1423 vector class.
RyoheiHagimoto 0:0e0631af0305 1424 @param sz New number of rows.
RyoheiHagimoto 0:0e0631af0305 1425 */
RyoheiHagimoto 0:0e0631af0305 1426 void resize(size_t sz);
RyoheiHagimoto 0:0e0631af0305 1427
RyoheiHagimoto 0:0e0631af0305 1428 /** @overload
RyoheiHagimoto 0:0e0631af0305 1429 @param sz New number of rows.
RyoheiHagimoto 0:0e0631af0305 1430 @param s Value assigned to the newly added elements.
RyoheiHagimoto 0:0e0631af0305 1431 */
RyoheiHagimoto 0:0e0631af0305 1432 void resize(size_t sz, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 1433
RyoheiHagimoto 0:0e0631af0305 1434 //! internal function
RyoheiHagimoto 0:0e0631af0305 1435 void push_back_(const void* elem);
RyoheiHagimoto 0:0e0631af0305 1436
RyoheiHagimoto 0:0e0631af0305 1437 /** @brief Adds elements to the bottom of the matrix.
RyoheiHagimoto 0:0e0631af0305 1438
RyoheiHagimoto 0:0e0631af0305 1439 The methods add one or more elements to the bottom of the matrix. They emulate the corresponding
RyoheiHagimoto 0:0e0631af0305 1440 method of the STL vector class. When elem is Mat , its type and the number of columns must be the
RyoheiHagimoto 0:0e0631af0305 1441 same as in the container matrix.
RyoheiHagimoto 0:0e0631af0305 1442 @param elem Added element(s).
RyoheiHagimoto 0:0e0631af0305 1443 */
RyoheiHagimoto 0:0e0631af0305 1444 template<typename _Tp> void push_back(const _Tp& elem);
RyoheiHagimoto 0:0e0631af0305 1445
RyoheiHagimoto 0:0e0631af0305 1446 /** @overload
RyoheiHagimoto 0:0e0631af0305 1447 @param elem Added element(s).
RyoheiHagimoto 0:0e0631af0305 1448 */
RyoheiHagimoto 0:0e0631af0305 1449 template<typename _Tp> void push_back(const Mat_<_Tp>& elem);
RyoheiHagimoto 0:0e0631af0305 1450
RyoheiHagimoto 0:0e0631af0305 1451 /** @overload
RyoheiHagimoto 0:0e0631af0305 1452 @param m Added line(s).
RyoheiHagimoto 0:0e0631af0305 1453 */
RyoheiHagimoto 0:0e0631af0305 1454 void push_back(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 1455
RyoheiHagimoto 0:0e0631af0305 1456 /** @brief Removes elements from the bottom of the matrix.
RyoheiHagimoto 0:0e0631af0305 1457
RyoheiHagimoto 0:0e0631af0305 1458 The method removes one or more rows from the bottom of the matrix.
RyoheiHagimoto 0:0e0631af0305 1459 @param nelems Number of removed rows. If it is greater than the total number of rows, an exception
RyoheiHagimoto 0:0e0631af0305 1460 is thrown.
RyoheiHagimoto 0:0e0631af0305 1461 */
RyoheiHagimoto 0:0e0631af0305 1462 void pop_back(size_t nelems=1);
RyoheiHagimoto 0:0e0631af0305 1463
RyoheiHagimoto 0:0e0631af0305 1464 /** @brief Locates the matrix header within a parent matrix.
RyoheiHagimoto 0:0e0631af0305 1465
RyoheiHagimoto 0:0e0631af0305 1466 After you extracted a submatrix from a matrix using Mat::row, Mat::col, Mat::rowRange,
RyoheiHagimoto 0:0e0631af0305 1467 Mat::colRange, and others, the resultant submatrix points just to the part of the original big
RyoheiHagimoto 0:0e0631af0305 1468 matrix. However, each submatrix contains information (represented by datastart and dataend
RyoheiHagimoto 0:0e0631af0305 1469 fields) that helps reconstruct the original matrix size and the position of the extracted
RyoheiHagimoto 0:0e0631af0305 1470 submatrix within the original matrix. The method locateROI does exactly that.
RyoheiHagimoto 0:0e0631af0305 1471 @param wholeSize Output parameter that contains the size of the whole matrix containing *this*
RyoheiHagimoto 0:0e0631af0305 1472 as a part.
RyoheiHagimoto 0:0e0631af0305 1473 @param ofs Output parameter that contains an offset of *this* inside the whole matrix.
RyoheiHagimoto 0:0e0631af0305 1474 */
RyoheiHagimoto 0:0e0631af0305 1475 void locateROI( Size& wholeSize, Point& ofs ) const;
RyoheiHagimoto 0:0e0631af0305 1476
RyoheiHagimoto 0:0e0631af0305 1477 /** @brief Adjusts a submatrix size and position within the parent matrix.
RyoheiHagimoto 0:0e0631af0305 1478
RyoheiHagimoto 0:0e0631af0305 1479 The method is complimentary to Mat::locateROI . The typical use of these functions is to determine
RyoheiHagimoto 0:0e0631af0305 1480 the submatrix position within the parent matrix and then shift the position somehow. Typically, it
RyoheiHagimoto 0:0e0631af0305 1481 can be required for filtering operations when pixels outside of the ROI should be taken into
RyoheiHagimoto 0:0e0631af0305 1482 account. When all the method parameters are positive, the ROI needs to grow in all directions by the
RyoheiHagimoto 0:0e0631af0305 1483 specified amount, for example:
RyoheiHagimoto 0:0e0631af0305 1484 @code
RyoheiHagimoto 0:0e0631af0305 1485 A.adjustROI(2, 2, 2, 2);
RyoheiHagimoto 0:0e0631af0305 1486 @endcode
RyoheiHagimoto 0:0e0631af0305 1487 In this example, the matrix size is increased by 4 elements in each direction. The matrix is shifted
RyoheiHagimoto 0:0e0631af0305 1488 by 2 elements to the left and 2 elements up, which brings in all the necessary pixels for the
RyoheiHagimoto 0:0e0631af0305 1489 filtering with the 5x5 kernel.
RyoheiHagimoto 0:0e0631af0305 1490
RyoheiHagimoto 0:0e0631af0305 1491 adjustROI forces the adjusted ROI to be inside of the parent matrix that is boundaries of the
RyoheiHagimoto 0:0e0631af0305 1492 adjusted ROI are constrained by boundaries of the parent matrix. For example, if the submatrix A is
RyoheiHagimoto 0:0e0631af0305 1493 located in the first row of a parent matrix and you called A.adjustROI(2, 2, 2, 2) then A will not
RyoheiHagimoto 0:0e0631af0305 1494 be increased in the upward direction.
RyoheiHagimoto 0:0e0631af0305 1495
RyoheiHagimoto 0:0e0631af0305 1496 The function is used internally by the OpenCV filtering functions, like filter2D , morphological
RyoheiHagimoto 0:0e0631af0305 1497 operations, and so on.
RyoheiHagimoto 0:0e0631af0305 1498 @param dtop Shift of the top submatrix boundary upwards.
RyoheiHagimoto 0:0e0631af0305 1499 @param dbottom Shift of the bottom submatrix boundary downwards.
RyoheiHagimoto 0:0e0631af0305 1500 @param dleft Shift of the left submatrix boundary to the left.
RyoheiHagimoto 0:0e0631af0305 1501 @param dright Shift of the right submatrix boundary to the right.
RyoheiHagimoto 0:0e0631af0305 1502 @sa copyMakeBorder
RyoheiHagimoto 0:0e0631af0305 1503 */
RyoheiHagimoto 0:0e0631af0305 1504 Mat& adjustROI( int dtop, int dbottom, int dleft, int dright );
RyoheiHagimoto 0:0e0631af0305 1505
RyoheiHagimoto 0:0e0631af0305 1506 /** @brief Extracts a rectangular submatrix.
RyoheiHagimoto 0:0e0631af0305 1507
RyoheiHagimoto 0:0e0631af0305 1508 The operators make a new header for the specified sub-array of \*this . They are the most
RyoheiHagimoto 0:0e0631af0305 1509 generalized forms of Mat::row, Mat::col, Mat::rowRange, and Mat::colRange . For example,
RyoheiHagimoto 0:0e0631af0305 1510 `A(Range(0, 10), Range::all())` is equivalent to `A.rowRange(0, 10)`. Similarly to all of the above,
RyoheiHagimoto 0:0e0631af0305 1511 the operators are O(1) operations, that is, no matrix data is copied.
RyoheiHagimoto 0:0e0631af0305 1512 @param rowRange Start and end row of the extracted submatrix. The upper boundary is not included. To
RyoheiHagimoto 0:0e0631af0305 1513 select all the rows, use Range::all().
RyoheiHagimoto 0:0e0631af0305 1514 @param colRange Start and end column of the extracted submatrix. The upper boundary is not included.
RyoheiHagimoto 0:0e0631af0305 1515 To select all the columns, use Range::all().
RyoheiHagimoto 0:0e0631af0305 1516 */
RyoheiHagimoto 0:0e0631af0305 1517 Mat operator()( Range rowRange, Range colRange ) const;
RyoheiHagimoto 0:0e0631af0305 1518
RyoheiHagimoto 0:0e0631af0305 1519 /** @overload
RyoheiHagimoto 0:0e0631af0305 1520 @param roi Extracted submatrix specified as a rectangle.
RyoheiHagimoto 0:0e0631af0305 1521 */
RyoheiHagimoto 0:0e0631af0305 1522 Mat operator()( const Rect& roi ) const;
RyoheiHagimoto 0:0e0631af0305 1523
RyoheiHagimoto 0:0e0631af0305 1524 /** @overload
RyoheiHagimoto 0:0e0631af0305 1525 @param ranges Array of selected ranges along each array dimension.
RyoheiHagimoto 0:0e0631af0305 1526 */
RyoheiHagimoto 0:0e0631af0305 1527 Mat operator()( const Range* ranges ) const;
RyoheiHagimoto 0:0e0631af0305 1528
RyoheiHagimoto 0:0e0631af0305 1529 /** @overload
RyoheiHagimoto 0:0e0631af0305 1530 @param ranges Array of selected ranges along each array dimension.
RyoheiHagimoto 0:0e0631af0305 1531 */
RyoheiHagimoto 0:0e0631af0305 1532 Mat operator()(const std::vector<Range>& ranges) const;
RyoheiHagimoto 0:0e0631af0305 1533
RyoheiHagimoto 0:0e0631af0305 1534 // //! converts header to CvMat; no data is copied
RyoheiHagimoto 0:0e0631af0305 1535 // operator CvMat() const;
RyoheiHagimoto 0:0e0631af0305 1536 // //! converts header to CvMatND; no data is copied
RyoheiHagimoto 0:0e0631af0305 1537 // operator CvMatND() const;
RyoheiHagimoto 0:0e0631af0305 1538 // //! converts header to IplImage; no data is copied
RyoheiHagimoto 0:0e0631af0305 1539 // operator IplImage() const;
RyoheiHagimoto 0:0e0631af0305 1540
RyoheiHagimoto 0:0e0631af0305 1541 template<typename _Tp> operator std::vector<_Tp>() const;
RyoheiHagimoto 0:0e0631af0305 1542 template<typename _Tp, int n> operator Vec<_Tp, n>() const;
RyoheiHagimoto 0:0e0631af0305 1543 template<typename _Tp, int m, int n> operator Matx<_Tp, m, n>() const;
RyoheiHagimoto 0:0e0631af0305 1544
RyoheiHagimoto 0:0e0631af0305 1545 /** @brief Reports whether the matrix is continuous or not.
RyoheiHagimoto 0:0e0631af0305 1546
RyoheiHagimoto 0:0e0631af0305 1547 The method returns true if the matrix elements are stored continuously without gaps at the end of
RyoheiHagimoto 0:0e0631af0305 1548 each row. Otherwise, it returns false. Obviously, 1x1 or 1xN matrices are always continuous.
RyoheiHagimoto 0:0e0631af0305 1549 Matrices created with Mat::create are always continuous. But if you extract a part of the matrix
RyoheiHagimoto 0:0e0631af0305 1550 using Mat::col, Mat::diag, and so on, or constructed a matrix header for externally allocated data,
RyoheiHagimoto 0:0e0631af0305 1551 such matrices may no longer have this property.
RyoheiHagimoto 0:0e0631af0305 1552
RyoheiHagimoto 0:0e0631af0305 1553 The continuity flag is stored as a bit in the Mat::flags field and is computed automatically when
RyoheiHagimoto 0:0e0631af0305 1554 you construct a matrix header. Thus, the continuity check is a very fast operation, though
RyoheiHagimoto 0:0e0631af0305 1555 theoretically it could be done as follows:
RyoheiHagimoto 0:0e0631af0305 1556 @code
RyoheiHagimoto 0:0e0631af0305 1557 // alternative implementation of Mat::isContinuous()
RyoheiHagimoto 0:0e0631af0305 1558 bool myCheckMatContinuity(const Mat& m)
RyoheiHagimoto 0:0e0631af0305 1559 {
RyoheiHagimoto 0:0e0631af0305 1560 //return (m.flags & Mat::CONTINUOUS_FLAG) != 0;
RyoheiHagimoto 0:0e0631af0305 1561 return m.rows == 1 || m.step == m.cols*m.elemSize();
RyoheiHagimoto 0:0e0631af0305 1562 }
RyoheiHagimoto 0:0e0631af0305 1563 @endcode
RyoheiHagimoto 0:0e0631af0305 1564 The method is used in quite a few of OpenCV functions. The point is that element-wise operations
RyoheiHagimoto 0:0e0631af0305 1565 (such as arithmetic and logical operations, math functions, alpha blending, color space
RyoheiHagimoto 0:0e0631af0305 1566 transformations, and others) do not depend on the image geometry. Thus, if all the input and output
RyoheiHagimoto 0:0e0631af0305 1567 arrays are continuous, the functions can process them as very long single-row vectors. The example
RyoheiHagimoto 0:0e0631af0305 1568 below illustrates how an alpha-blending function can be implemented:
RyoheiHagimoto 0:0e0631af0305 1569 @code
RyoheiHagimoto 0:0e0631af0305 1570 template<typename T>
RyoheiHagimoto 0:0e0631af0305 1571 void alphaBlendRGBA(const Mat& src1, const Mat& src2, Mat& dst)
RyoheiHagimoto 0:0e0631af0305 1572 {
RyoheiHagimoto 0:0e0631af0305 1573 const float alpha_scale = (float)std::numeric_limits<T>::max(),
RyoheiHagimoto 0:0e0631af0305 1574 inv_scale = 1.f/alpha_scale;
RyoheiHagimoto 0:0e0631af0305 1575
RyoheiHagimoto 0:0e0631af0305 1576 CV_Assert( src1.type() == src2.type() &&
RyoheiHagimoto 0:0e0631af0305 1577 src1.type() == CV_MAKETYPE(DataType<T>::depth, 4) &&
RyoheiHagimoto 0:0e0631af0305 1578 src1.size() == src2.size());
RyoheiHagimoto 0:0e0631af0305 1579 Size size = src1.size();
RyoheiHagimoto 0:0e0631af0305 1580 dst.create(size, src1.type());
RyoheiHagimoto 0:0e0631af0305 1581
RyoheiHagimoto 0:0e0631af0305 1582 // here is the idiom: check the arrays for continuity and,
RyoheiHagimoto 0:0e0631af0305 1583 // if this is the case,
RyoheiHagimoto 0:0e0631af0305 1584 // treat the arrays as 1D vectors
RyoheiHagimoto 0:0e0631af0305 1585 if( src1.isContinuous() && src2.isContinuous() && dst.isContinuous() )
RyoheiHagimoto 0:0e0631af0305 1586 {
RyoheiHagimoto 0:0e0631af0305 1587 size.width *= size.height;
RyoheiHagimoto 0:0e0631af0305 1588 size.height = 1;
RyoheiHagimoto 0:0e0631af0305 1589 }
RyoheiHagimoto 0:0e0631af0305 1590 size.width *= 4;
RyoheiHagimoto 0:0e0631af0305 1591
RyoheiHagimoto 0:0e0631af0305 1592 for( int i = 0; i < size.height; i++ )
RyoheiHagimoto 0:0e0631af0305 1593 {
RyoheiHagimoto 0:0e0631af0305 1594 // when the arrays are continuous,
RyoheiHagimoto 0:0e0631af0305 1595 // the outer loop is executed only once
RyoheiHagimoto 0:0e0631af0305 1596 const T* ptr1 = src1.ptr<T>(i);
RyoheiHagimoto 0:0e0631af0305 1597 const T* ptr2 = src2.ptr<T>(i);
RyoheiHagimoto 0:0e0631af0305 1598 T* dptr = dst.ptr<T>(i);
RyoheiHagimoto 0:0e0631af0305 1599
RyoheiHagimoto 0:0e0631af0305 1600 for( int j = 0; j < size.width; j += 4 )
RyoheiHagimoto 0:0e0631af0305 1601 {
RyoheiHagimoto 0:0e0631af0305 1602 float alpha = ptr1[j+3]*inv_scale, beta = ptr2[j+3]*inv_scale;
RyoheiHagimoto 0:0e0631af0305 1603 dptr[j] = saturate_cast<T>(ptr1[j]*alpha + ptr2[j]*beta);
RyoheiHagimoto 0:0e0631af0305 1604 dptr[j+1] = saturate_cast<T>(ptr1[j+1]*alpha + ptr2[j+1]*beta);
RyoheiHagimoto 0:0e0631af0305 1605 dptr[j+2] = saturate_cast<T>(ptr1[j+2]*alpha + ptr2[j+2]*beta);
RyoheiHagimoto 0:0e0631af0305 1606 dptr[j+3] = saturate_cast<T>((1 - (1-alpha)*(1-beta))*alpha_scale);
RyoheiHagimoto 0:0e0631af0305 1607 }
RyoheiHagimoto 0:0e0631af0305 1608 }
RyoheiHagimoto 0:0e0631af0305 1609 }
RyoheiHagimoto 0:0e0631af0305 1610 @endcode
RyoheiHagimoto 0:0e0631af0305 1611 This approach, while being very simple, can boost the performance of a simple element-operation by
RyoheiHagimoto 0:0e0631af0305 1612 10-20 percents, especially if the image is rather small and the operation is quite simple.
RyoheiHagimoto 0:0e0631af0305 1613
RyoheiHagimoto 0:0e0631af0305 1614 Another OpenCV idiom in this function, a call of Mat::create for the destination array, that
RyoheiHagimoto 0:0e0631af0305 1615 allocates the destination array unless it already has the proper size and type. And while the newly
RyoheiHagimoto 0:0e0631af0305 1616 allocated arrays are always continuous, you still need to check the destination array because
RyoheiHagimoto 0:0e0631af0305 1617 Mat::create does not always allocate a new matrix.
RyoheiHagimoto 0:0e0631af0305 1618 */
RyoheiHagimoto 0:0e0631af0305 1619 bool isContinuous() const;
RyoheiHagimoto 0:0e0631af0305 1620
RyoheiHagimoto 0:0e0631af0305 1621 //! returns true if the matrix is a submatrix of another matrix
RyoheiHagimoto 0:0e0631af0305 1622 bool isSubmatrix() const;
RyoheiHagimoto 0:0e0631af0305 1623
RyoheiHagimoto 0:0e0631af0305 1624 /** @brief Returns the matrix element size in bytes.
RyoheiHagimoto 0:0e0631af0305 1625
RyoheiHagimoto 0:0e0631af0305 1626 The method returns the matrix element size in bytes. For example, if the matrix type is CV_16SC3 ,
RyoheiHagimoto 0:0e0631af0305 1627 the method returns 3\*sizeof(short) or 6.
RyoheiHagimoto 0:0e0631af0305 1628 */
RyoheiHagimoto 0:0e0631af0305 1629 size_t elemSize() const;
RyoheiHagimoto 0:0e0631af0305 1630
RyoheiHagimoto 0:0e0631af0305 1631 /** @brief Returns the size of each matrix element channel in bytes.
RyoheiHagimoto 0:0e0631af0305 1632
RyoheiHagimoto 0:0e0631af0305 1633 The method returns the matrix element channel size in bytes, that is, it ignores the number of
RyoheiHagimoto 0:0e0631af0305 1634 channels. For example, if the matrix type is CV_16SC3 , the method returns sizeof(short) or 2.
RyoheiHagimoto 0:0e0631af0305 1635 */
RyoheiHagimoto 0:0e0631af0305 1636 size_t elemSize1() const;
RyoheiHagimoto 0:0e0631af0305 1637
RyoheiHagimoto 0:0e0631af0305 1638 /** @brief Returns the type of a matrix element.
RyoheiHagimoto 0:0e0631af0305 1639
RyoheiHagimoto 0:0e0631af0305 1640 The method returns a matrix element type. This is an identifier compatible with the CvMat type
RyoheiHagimoto 0:0e0631af0305 1641 system, like CV_16SC3 or 16-bit signed 3-channel array, and so on.
RyoheiHagimoto 0:0e0631af0305 1642 */
RyoheiHagimoto 0:0e0631af0305 1643 int type() const;
RyoheiHagimoto 0:0e0631af0305 1644
RyoheiHagimoto 0:0e0631af0305 1645 /** @brief Returns the depth of a matrix element.
RyoheiHagimoto 0:0e0631af0305 1646
RyoheiHagimoto 0:0e0631af0305 1647 The method returns the identifier of the matrix element depth (the type of each individual channel).
RyoheiHagimoto 0:0e0631af0305 1648 For example, for a 16-bit signed element array, the method returns CV_16S . A complete list of
RyoheiHagimoto 0:0e0631af0305 1649 matrix types contains the following values:
RyoheiHagimoto 0:0e0631af0305 1650 - CV_8U - 8-bit unsigned integers ( 0..255 )
RyoheiHagimoto 0:0e0631af0305 1651 - CV_8S - 8-bit signed integers ( -128..127 )
RyoheiHagimoto 0:0e0631af0305 1652 - CV_16U - 16-bit unsigned integers ( 0..65535 )
RyoheiHagimoto 0:0e0631af0305 1653 - CV_16S - 16-bit signed integers ( -32768..32767 )
RyoheiHagimoto 0:0e0631af0305 1654 - CV_32S - 32-bit signed integers ( -2147483648..2147483647 )
RyoheiHagimoto 0:0e0631af0305 1655 - CV_32F - 32-bit floating-point numbers ( -FLT_MAX..FLT_MAX, INF, NAN )
RyoheiHagimoto 0:0e0631af0305 1656 - CV_64F - 64-bit floating-point numbers ( -DBL_MAX..DBL_MAX, INF, NAN )
RyoheiHagimoto 0:0e0631af0305 1657 */
RyoheiHagimoto 0:0e0631af0305 1658 int depth() const;
RyoheiHagimoto 0:0e0631af0305 1659
RyoheiHagimoto 0:0e0631af0305 1660 /** @brief Returns the number of matrix channels.
RyoheiHagimoto 0:0e0631af0305 1661
RyoheiHagimoto 0:0e0631af0305 1662 The method returns the number of matrix channels.
RyoheiHagimoto 0:0e0631af0305 1663 */
RyoheiHagimoto 0:0e0631af0305 1664 int channels() const;
RyoheiHagimoto 0:0e0631af0305 1665
RyoheiHagimoto 0:0e0631af0305 1666 /** @brief Returns a normalized step.
RyoheiHagimoto 0:0e0631af0305 1667
RyoheiHagimoto 0:0e0631af0305 1668 The method returns a matrix step divided by Mat::elemSize1() . It can be useful to quickly access an
RyoheiHagimoto 0:0e0631af0305 1669 arbitrary matrix element.
RyoheiHagimoto 0:0e0631af0305 1670 */
RyoheiHagimoto 0:0e0631af0305 1671 size_t step1(int i=0) const;
RyoheiHagimoto 0:0e0631af0305 1672
RyoheiHagimoto 0:0e0631af0305 1673 /** @brief Returns true if the array has no elements.
RyoheiHagimoto 0:0e0631af0305 1674
RyoheiHagimoto 0:0e0631af0305 1675 The method returns true if Mat::total() is 0 or if Mat::data is NULL. Because of pop_back() and
RyoheiHagimoto 0:0e0631af0305 1676 resize() methods `M.total() == 0` does not imply that `M.data == NULL`.
RyoheiHagimoto 0:0e0631af0305 1677 */
RyoheiHagimoto 0:0e0631af0305 1678 bool empty() const;
RyoheiHagimoto 0:0e0631af0305 1679
RyoheiHagimoto 0:0e0631af0305 1680 /** @brief Returns the total number of array elements.
RyoheiHagimoto 0:0e0631af0305 1681
RyoheiHagimoto 0:0e0631af0305 1682 The method returns the number of array elements (a number of pixels if the array represents an
RyoheiHagimoto 0:0e0631af0305 1683 image).
RyoheiHagimoto 0:0e0631af0305 1684 */
RyoheiHagimoto 0:0e0631af0305 1685 size_t total() const;
RyoheiHagimoto 0:0e0631af0305 1686
RyoheiHagimoto 0:0e0631af0305 1687 //! returns N if the matrix is 1-channel (N x ptdim) or ptdim-channel (1 x N) or (N x 1); negative number otherwise
RyoheiHagimoto 0:0e0631af0305 1688 int checkVector(int elemChannels, int depth=-1, bool requireContinuous=true) const;
RyoheiHagimoto 0:0e0631af0305 1689
RyoheiHagimoto 0:0e0631af0305 1690 /** @brief Returns a pointer to the specified matrix row.
RyoheiHagimoto 0:0e0631af0305 1691
RyoheiHagimoto 0:0e0631af0305 1692 The methods return `uchar*` or typed pointer to the specified matrix row. See the sample in
RyoheiHagimoto 0:0e0631af0305 1693 Mat::isContinuous to know how to use these methods.
RyoheiHagimoto 0:0e0631af0305 1694 @param i0 A 0-based row index.
RyoheiHagimoto 0:0e0631af0305 1695 */
RyoheiHagimoto 0:0e0631af0305 1696 uchar* ptr(int i0=0);
RyoheiHagimoto 0:0e0631af0305 1697 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1698 const uchar* ptr(int i0=0) const;
RyoheiHagimoto 0:0e0631af0305 1699
RyoheiHagimoto 0:0e0631af0305 1700 /** @overload
RyoheiHagimoto 0:0e0631af0305 1701 @param row Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1702 @param col Index along the dimension 1
RyoheiHagimoto 0:0e0631af0305 1703 */
RyoheiHagimoto 0:0e0631af0305 1704 uchar* ptr(int row, int col);
RyoheiHagimoto 0:0e0631af0305 1705 /** @overload
RyoheiHagimoto 0:0e0631af0305 1706 @param row Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1707 @param col Index along the dimension 1
RyoheiHagimoto 0:0e0631af0305 1708 */
RyoheiHagimoto 0:0e0631af0305 1709 const uchar* ptr(int row, int col) const;
RyoheiHagimoto 0:0e0631af0305 1710
RyoheiHagimoto 0:0e0631af0305 1711 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1712 uchar* ptr(int i0, int i1, int i2);
RyoheiHagimoto 0:0e0631af0305 1713 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1714 const uchar* ptr(int i0, int i1, int i2) const;
RyoheiHagimoto 0:0e0631af0305 1715
RyoheiHagimoto 0:0e0631af0305 1716 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1717 uchar* ptr(const int* idx);
RyoheiHagimoto 0:0e0631af0305 1718 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1719 const uchar* ptr(const int* idx) const;
RyoheiHagimoto 0:0e0631af0305 1720 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1721 template<int n> uchar* ptr(const Vec<int, n>& idx);
RyoheiHagimoto 0:0e0631af0305 1722 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1723 template<int n> const uchar* ptr(const Vec<int, n>& idx) const;
RyoheiHagimoto 0:0e0631af0305 1724
RyoheiHagimoto 0:0e0631af0305 1725 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1726 template<typename _Tp> _Tp* ptr(int i0=0);
RyoheiHagimoto 0:0e0631af0305 1727 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1728 template<typename _Tp> const _Tp* ptr(int i0=0) const;
RyoheiHagimoto 0:0e0631af0305 1729 /** @overload
RyoheiHagimoto 0:0e0631af0305 1730 @param row Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1731 @param col Index along the dimension 1
RyoheiHagimoto 0:0e0631af0305 1732 */
RyoheiHagimoto 0:0e0631af0305 1733 template<typename _Tp> _Tp* ptr(int row, int col);
RyoheiHagimoto 0:0e0631af0305 1734 /** @overload
RyoheiHagimoto 0:0e0631af0305 1735 @param row Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1736 @param col Index along the dimension 1
RyoheiHagimoto 0:0e0631af0305 1737 */
RyoheiHagimoto 0:0e0631af0305 1738 template<typename _Tp> const _Tp* ptr(int row, int col) const;
RyoheiHagimoto 0:0e0631af0305 1739 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1740 template<typename _Tp> _Tp* ptr(int i0, int i1, int i2);
RyoheiHagimoto 0:0e0631af0305 1741 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1742 template<typename _Tp> const _Tp* ptr(int i0, int i1, int i2) const;
RyoheiHagimoto 0:0e0631af0305 1743 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1744 template<typename _Tp> _Tp* ptr(const int* idx);
RyoheiHagimoto 0:0e0631af0305 1745 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1746 template<typename _Tp> const _Tp* ptr(const int* idx) const;
RyoheiHagimoto 0:0e0631af0305 1747 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1748 template<typename _Tp, int n> _Tp* ptr(const Vec<int, n>& idx);
RyoheiHagimoto 0:0e0631af0305 1749 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1750 template<typename _Tp, int n> const _Tp* ptr(const Vec<int, n>& idx) const;
RyoheiHagimoto 0:0e0631af0305 1751
RyoheiHagimoto 0:0e0631af0305 1752 /** @brief Returns a reference to the specified array element.
RyoheiHagimoto 0:0e0631af0305 1753
RyoheiHagimoto 0:0e0631af0305 1754 The template methods return a reference to the specified array element. For the sake of higher
RyoheiHagimoto 0:0e0631af0305 1755 performance, the index range checks are only performed in the Debug configuration.
RyoheiHagimoto 0:0e0631af0305 1756
RyoheiHagimoto 0:0e0631af0305 1757 Note that the variants with a single index (i) can be used to access elements of single-row or
RyoheiHagimoto 0:0e0631af0305 1758 single-column 2-dimensional arrays. That is, if, for example, A is a 1 x N floating-point matrix and
RyoheiHagimoto 0:0e0631af0305 1759 B is an M x 1 integer matrix, you can simply write `A.at<float>(k+4)` and `B.at<int>(2*i+1)`
RyoheiHagimoto 0:0e0631af0305 1760 instead of `A.at<float>(0,k+4)` and `B.at<int>(2*i+1,0)`, respectively.
RyoheiHagimoto 0:0e0631af0305 1761
RyoheiHagimoto 0:0e0631af0305 1762 The example below initializes a Hilbert matrix:
RyoheiHagimoto 0:0e0631af0305 1763 @code
RyoheiHagimoto 0:0e0631af0305 1764 Mat H(100, 100, CV_64F);
RyoheiHagimoto 0:0e0631af0305 1765 for(int i = 0; i < H.rows; i++)
RyoheiHagimoto 0:0e0631af0305 1766 for(int j = 0; j < H.cols; j++)
RyoheiHagimoto 0:0e0631af0305 1767 H.at<double>(i,j)=1./(i+j+1);
RyoheiHagimoto 0:0e0631af0305 1768 @endcode
RyoheiHagimoto 0:0e0631af0305 1769
RyoheiHagimoto 0:0e0631af0305 1770 Keep in mind that the size identifier used in the at operator cannot be chosen at random. It depends
RyoheiHagimoto 0:0e0631af0305 1771 on the image from which you are trying to retrieve the data. The table below gives a better insight in this:
RyoheiHagimoto 0:0e0631af0305 1772 - If matrix is of type `CV_8U` then use `Mat.at<uchar>(y,x)`.
RyoheiHagimoto 0:0e0631af0305 1773 - If matrix is of type `CV_8S` then use `Mat.at<schar>(y,x)`.
RyoheiHagimoto 0:0e0631af0305 1774 - If matrix is of type `CV_16U` then use `Mat.at<ushort>(y,x)`.
RyoheiHagimoto 0:0e0631af0305 1775 - If matrix is of type `CV_16S` then use `Mat.at<short>(y,x)`.
RyoheiHagimoto 0:0e0631af0305 1776 - If matrix is of type `CV_32S` then use `Mat.at<int>(y,x)`.
RyoheiHagimoto 0:0e0631af0305 1777 - If matrix is of type `CV_32F` then use `Mat.at<float>(y,x)`.
RyoheiHagimoto 0:0e0631af0305 1778 - If matrix is of type `CV_64F` then use `Mat.at<double>(y,x)`.
RyoheiHagimoto 0:0e0631af0305 1779
RyoheiHagimoto 0:0e0631af0305 1780 @param i0 Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1781 */
RyoheiHagimoto 0:0e0631af0305 1782 template<typename _Tp> _Tp& at(int i0=0);
RyoheiHagimoto 0:0e0631af0305 1783 /** @overload
RyoheiHagimoto 0:0e0631af0305 1784 @param i0 Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1785 */
RyoheiHagimoto 0:0e0631af0305 1786 template<typename _Tp> const _Tp& at(int i0=0) const;
RyoheiHagimoto 0:0e0631af0305 1787 /** @overload
RyoheiHagimoto 0:0e0631af0305 1788 @param row Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1789 @param col Index along the dimension 1
RyoheiHagimoto 0:0e0631af0305 1790 */
RyoheiHagimoto 0:0e0631af0305 1791 template<typename _Tp> _Tp& at(int row, int col);
RyoheiHagimoto 0:0e0631af0305 1792 /** @overload
RyoheiHagimoto 0:0e0631af0305 1793 @param row Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1794 @param col Index along the dimension 1
RyoheiHagimoto 0:0e0631af0305 1795 */
RyoheiHagimoto 0:0e0631af0305 1796 template<typename _Tp> const _Tp& at(int row, int col) const;
RyoheiHagimoto 0:0e0631af0305 1797
RyoheiHagimoto 0:0e0631af0305 1798 /** @overload
RyoheiHagimoto 0:0e0631af0305 1799 @param i0 Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1800 @param i1 Index along the dimension 1
RyoheiHagimoto 0:0e0631af0305 1801 @param i2 Index along the dimension 2
RyoheiHagimoto 0:0e0631af0305 1802 */
RyoheiHagimoto 0:0e0631af0305 1803 template<typename _Tp> _Tp& at(int i0, int i1, int i2);
RyoheiHagimoto 0:0e0631af0305 1804 /** @overload
RyoheiHagimoto 0:0e0631af0305 1805 @param i0 Index along the dimension 0
RyoheiHagimoto 0:0e0631af0305 1806 @param i1 Index along the dimension 1
RyoheiHagimoto 0:0e0631af0305 1807 @param i2 Index along the dimension 2
RyoheiHagimoto 0:0e0631af0305 1808 */
RyoheiHagimoto 0:0e0631af0305 1809 template<typename _Tp> const _Tp& at(int i0, int i1, int i2) const;
RyoheiHagimoto 0:0e0631af0305 1810
RyoheiHagimoto 0:0e0631af0305 1811 /** @overload
RyoheiHagimoto 0:0e0631af0305 1812 @param idx Array of Mat::dims indices.
RyoheiHagimoto 0:0e0631af0305 1813 */
RyoheiHagimoto 0:0e0631af0305 1814 template<typename _Tp> _Tp& at(const int* idx);
RyoheiHagimoto 0:0e0631af0305 1815 /** @overload
RyoheiHagimoto 0:0e0631af0305 1816 @param idx Array of Mat::dims indices.
RyoheiHagimoto 0:0e0631af0305 1817 */
RyoheiHagimoto 0:0e0631af0305 1818 template<typename _Tp> const _Tp& at(const int* idx) const;
RyoheiHagimoto 0:0e0631af0305 1819
RyoheiHagimoto 0:0e0631af0305 1820 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1821 template<typename _Tp, int n> _Tp& at(const Vec<int, n>& idx);
RyoheiHagimoto 0:0e0631af0305 1822 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1823 template<typename _Tp, int n> const _Tp& at(const Vec<int, n>& idx) const;
RyoheiHagimoto 0:0e0631af0305 1824
RyoheiHagimoto 0:0e0631af0305 1825 /** @overload
RyoheiHagimoto 0:0e0631af0305 1826 special versions for 2D arrays (especially convenient for referencing image pixels)
RyoheiHagimoto 0:0e0631af0305 1827 @param pt Element position specified as Point(j,i) .
RyoheiHagimoto 0:0e0631af0305 1828 */
RyoheiHagimoto 0:0e0631af0305 1829 template<typename _Tp> _Tp& at(Point pt);
RyoheiHagimoto 0:0e0631af0305 1830 /** @overload
RyoheiHagimoto 0:0e0631af0305 1831 special versions for 2D arrays (especially convenient for referencing image pixels)
RyoheiHagimoto 0:0e0631af0305 1832 @param pt Element position specified as Point(j,i) .
RyoheiHagimoto 0:0e0631af0305 1833 */
RyoheiHagimoto 0:0e0631af0305 1834 template<typename _Tp> const _Tp& at(Point pt) const;
RyoheiHagimoto 0:0e0631af0305 1835
RyoheiHagimoto 0:0e0631af0305 1836 /** @brief Returns the matrix iterator and sets it to the first matrix element.
RyoheiHagimoto 0:0e0631af0305 1837
RyoheiHagimoto 0:0e0631af0305 1838 The methods return the matrix read-only or read-write iterators. The use of matrix iterators is very
RyoheiHagimoto 0:0e0631af0305 1839 similar to the use of bi-directional STL iterators. In the example below, the alpha blending
RyoheiHagimoto 0:0e0631af0305 1840 function is rewritten using the matrix iterators:
RyoheiHagimoto 0:0e0631af0305 1841 @code
RyoheiHagimoto 0:0e0631af0305 1842 template<typename T>
RyoheiHagimoto 0:0e0631af0305 1843 void alphaBlendRGBA(const Mat& src1, const Mat& src2, Mat& dst)
RyoheiHagimoto 0:0e0631af0305 1844 {
RyoheiHagimoto 0:0e0631af0305 1845 typedef Vec<T, 4> VT;
RyoheiHagimoto 0:0e0631af0305 1846
RyoheiHagimoto 0:0e0631af0305 1847 const float alpha_scale = (float)std::numeric_limits<T>::max(),
RyoheiHagimoto 0:0e0631af0305 1848 inv_scale = 1.f/alpha_scale;
RyoheiHagimoto 0:0e0631af0305 1849
RyoheiHagimoto 0:0e0631af0305 1850 CV_Assert( src1.type() == src2.type() &&
RyoheiHagimoto 0:0e0631af0305 1851 src1.type() == DataType<VT>::type &&
RyoheiHagimoto 0:0e0631af0305 1852 src1.size() == src2.size());
RyoheiHagimoto 0:0e0631af0305 1853 Size size = src1.size();
RyoheiHagimoto 0:0e0631af0305 1854 dst.create(size, src1.type());
RyoheiHagimoto 0:0e0631af0305 1855
RyoheiHagimoto 0:0e0631af0305 1856 MatConstIterator_<VT> it1 = src1.begin<VT>(), it1_end = src1.end<VT>();
RyoheiHagimoto 0:0e0631af0305 1857 MatConstIterator_<VT> it2 = src2.begin<VT>();
RyoheiHagimoto 0:0e0631af0305 1858 MatIterator_<VT> dst_it = dst.begin<VT>();
RyoheiHagimoto 0:0e0631af0305 1859
RyoheiHagimoto 0:0e0631af0305 1860 for( ; it1 != it1_end; ++it1, ++it2, ++dst_it )
RyoheiHagimoto 0:0e0631af0305 1861 {
RyoheiHagimoto 0:0e0631af0305 1862 VT pix1 = *it1, pix2 = *it2;
RyoheiHagimoto 0:0e0631af0305 1863 float alpha = pix1[3]*inv_scale, beta = pix2[3]*inv_scale;
RyoheiHagimoto 0:0e0631af0305 1864 *dst_it = VT(saturate_cast<T>(pix1[0]*alpha + pix2[0]*beta),
RyoheiHagimoto 0:0e0631af0305 1865 saturate_cast<T>(pix1[1]*alpha + pix2[1]*beta),
RyoheiHagimoto 0:0e0631af0305 1866 saturate_cast<T>(pix1[2]*alpha + pix2[2]*beta),
RyoheiHagimoto 0:0e0631af0305 1867 saturate_cast<T>((1 - (1-alpha)*(1-beta))*alpha_scale));
RyoheiHagimoto 0:0e0631af0305 1868 }
RyoheiHagimoto 0:0e0631af0305 1869 }
RyoheiHagimoto 0:0e0631af0305 1870 @endcode
RyoheiHagimoto 0:0e0631af0305 1871 */
RyoheiHagimoto 0:0e0631af0305 1872 template<typename _Tp> MatIterator_<_Tp> begin();
RyoheiHagimoto 0:0e0631af0305 1873 template<typename _Tp> MatConstIterator_<_Tp> begin() const;
RyoheiHagimoto 0:0e0631af0305 1874
RyoheiHagimoto 0:0e0631af0305 1875 /** @brief Returns the matrix iterator and sets it to the after-last matrix element.
RyoheiHagimoto 0:0e0631af0305 1876
RyoheiHagimoto 0:0e0631af0305 1877 The methods return the matrix read-only or read-write iterators, set to the point following the last
RyoheiHagimoto 0:0e0631af0305 1878 matrix element.
RyoheiHagimoto 0:0e0631af0305 1879 */
RyoheiHagimoto 0:0e0631af0305 1880 template<typename _Tp> MatIterator_<_Tp> end();
RyoheiHagimoto 0:0e0631af0305 1881 template<typename _Tp> MatConstIterator_<_Tp> end() const;
RyoheiHagimoto 0:0e0631af0305 1882
RyoheiHagimoto 0:0e0631af0305 1883 /** @brief Runs the given functor over all matrix elements in parallel.
RyoheiHagimoto 0:0e0631af0305 1884
RyoheiHagimoto 0:0e0631af0305 1885 The operation passed as argument has to be a function pointer, a function object or a lambda(C++11).
RyoheiHagimoto 0:0e0631af0305 1886
RyoheiHagimoto 0:0e0631af0305 1887 Example 1. All of the operations below put 0xFF the first channel of all matrix elements:
RyoheiHagimoto 0:0e0631af0305 1888 @code
RyoheiHagimoto 0:0e0631af0305 1889 Mat image(1920, 1080, CV_8UC3);
RyoheiHagimoto 0:0e0631af0305 1890 typedef cv::Point3_<uint8_t> Pixel;
RyoheiHagimoto 0:0e0631af0305 1891
RyoheiHagimoto 0:0e0631af0305 1892 // first. raw pointer access.
RyoheiHagimoto 0:0e0631af0305 1893 for (int r = 0; r < image.rows; ++r) {
RyoheiHagimoto 0:0e0631af0305 1894 Pixel* ptr = image.ptr<Pixel>(0, r);
RyoheiHagimoto 0:0e0631af0305 1895 const Pixel* ptr_end = ptr + image.cols;
RyoheiHagimoto 0:0e0631af0305 1896 for (; ptr != ptr_end; ++ptr) {
RyoheiHagimoto 0:0e0631af0305 1897 ptr->x = 255;
RyoheiHagimoto 0:0e0631af0305 1898 }
RyoheiHagimoto 0:0e0631af0305 1899 }
RyoheiHagimoto 0:0e0631af0305 1900
RyoheiHagimoto 0:0e0631af0305 1901 // Using MatIterator. (Simple but there are a Iterator's overhead)
RyoheiHagimoto 0:0e0631af0305 1902 for (Pixel &p : cv::Mat_<Pixel>(image)) {
RyoheiHagimoto 0:0e0631af0305 1903 p.x = 255;
RyoheiHagimoto 0:0e0631af0305 1904 }
RyoheiHagimoto 0:0e0631af0305 1905
RyoheiHagimoto 0:0e0631af0305 1906 // Parallel execution with function object.
RyoheiHagimoto 0:0e0631af0305 1907 struct Operator {
RyoheiHagimoto 0:0e0631af0305 1908 void operator ()(Pixel &pixel, const int * position) {
RyoheiHagimoto 0:0e0631af0305 1909 pixel.x = 255;
RyoheiHagimoto 0:0e0631af0305 1910 }
RyoheiHagimoto 0:0e0631af0305 1911 };
RyoheiHagimoto 0:0e0631af0305 1912 image.forEach<Pixel>(Operator());
RyoheiHagimoto 0:0e0631af0305 1913
RyoheiHagimoto 0:0e0631af0305 1914 // Parallel execution using C++11 lambda.
RyoheiHagimoto 0:0e0631af0305 1915 image.forEach<Pixel>([](Pixel &p, const int * position) -> void {
RyoheiHagimoto 0:0e0631af0305 1916 p.x = 255;
RyoheiHagimoto 0:0e0631af0305 1917 });
RyoheiHagimoto 0:0e0631af0305 1918 @endcode
RyoheiHagimoto 0:0e0631af0305 1919 Example 2. Using the pixel's position:
RyoheiHagimoto 0:0e0631af0305 1920 @code
RyoheiHagimoto 0:0e0631af0305 1921 // Creating 3D matrix (255 x 255 x 255) typed uint8_t
RyoheiHagimoto 0:0e0631af0305 1922 // and initialize all elements by the value which equals elements position.
RyoheiHagimoto 0:0e0631af0305 1923 // i.e. pixels (x,y,z) = (1,2,3) is (b,g,r) = (1,2,3).
RyoheiHagimoto 0:0e0631af0305 1924
RyoheiHagimoto 0:0e0631af0305 1925 int sizes[] = { 255, 255, 255 };
RyoheiHagimoto 0:0e0631af0305 1926 typedef cv::Point3_<uint8_t> Pixel;
RyoheiHagimoto 0:0e0631af0305 1927
RyoheiHagimoto 0:0e0631af0305 1928 Mat_<Pixel> image = Mat::zeros(3, sizes, CV_8UC3);
RyoheiHagimoto 0:0e0631af0305 1929
RyoheiHagimoto 0:0e0631af0305 1930 image.forEach<Pixel>([&](Pixel& pixel, const int position[]) -> void {
RyoheiHagimoto 0:0e0631af0305 1931 pixel.x = position[0];
RyoheiHagimoto 0:0e0631af0305 1932 pixel.y = position[1];
RyoheiHagimoto 0:0e0631af0305 1933 pixel.z = position[2];
RyoheiHagimoto 0:0e0631af0305 1934 });
RyoheiHagimoto 0:0e0631af0305 1935 @endcode
RyoheiHagimoto 0:0e0631af0305 1936 */
RyoheiHagimoto 0:0e0631af0305 1937 template<typename _Tp, typename Functor> void forEach(const Functor& operation);
RyoheiHagimoto 0:0e0631af0305 1938 /** @overload */
RyoheiHagimoto 0:0e0631af0305 1939 template<typename _Tp, typename Functor> void forEach(const Functor& operation) const;
RyoheiHagimoto 0:0e0631af0305 1940
RyoheiHagimoto 0:0e0631af0305 1941 #ifdef CV_CXX_MOVE_SEMANTICS
RyoheiHagimoto 0:0e0631af0305 1942 Mat(Mat&& m);
RyoheiHagimoto 0:0e0631af0305 1943 Mat& operator = (Mat&& m);
RyoheiHagimoto 0:0e0631af0305 1944 #endif
RyoheiHagimoto 0:0e0631af0305 1945
RyoheiHagimoto 0:0e0631af0305 1946 enum { MAGIC_VAL = 0x42FF0000, AUTO_STEP = 0, CONTINUOUS_FLAG = CV_MAT_CONT_FLAG, SUBMATRIX_FLAG = CV_SUBMAT_FLAG };
RyoheiHagimoto 0:0e0631af0305 1947 enum { MAGIC_MASK = 0xFFFF0000, TYPE_MASK = 0x00000FFF, DEPTH_MASK = 7 };
RyoheiHagimoto 0:0e0631af0305 1948
RyoheiHagimoto 0:0e0631af0305 1949 /*! includes several bit-fields:
RyoheiHagimoto 0:0e0631af0305 1950 - the magic signature
RyoheiHagimoto 0:0e0631af0305 1951 - continuity flag
RyoheiHagimoto 0:0e0631af0305 1952 - depth
RyoheiHagimoto 0:0e0631af0305 1953 - number of channels
RyoheiHagimoto 0:0e0631af0305 1954 */
RyoheiHagimoto 0:0e0631af0305 1955 int flags;
RyoheiHagimoto 0:0e0631af0305 1956 //! the matrix dimensionality, >= 2
RyoheiHagimoto 0:0e0631af0305 1957 int dims;
RyoheiHagimoto 0:0e0631af0305 1958 //! the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
RyoheiHagimoto 0:0e0631af0305 1959 int rows, cols;
RyoheiHagimoto 0:0e0631af0305 1960 //! pointer to the data
RyoheiHagimoto 0:0e0631af0305 1961 uchar* data;
RyoheiHagimoto 0:0e0631af0305 1962
RyoheiHagimoto 0:0e0631af0305 1963 //! helper fields used in locateROI and adjustROI
RyoheiHagimoto 0:0e0631af0305 1964 const uchar* datastart;
RyoheiHagimoto 0:0e0631af0305 1965 const uchar* dataend;
RyoheiHagimoto 0:0e0631af0305 1966 const uchar* datalimit;
RyoheiHagimoto 0:0e0631af0305 1967
RyoheiHagimoto 0:0e0631af0305 1968 //! custom allocator
RyoheiHagimoto 0:0e0631af0305 1969 MatAllocator* allocator;
RyoheiHagimoto 0:0e0631af0305 1970 //! and the standard allocator
RyoheiHagimoto 0:0e0631af0305 1971 static MatAllocator* getStdAllocator();
RyoheiHagimoto 0:0e0631af0305 1972 static MatAllocator* getDefaultAllocator();
RyoheiHagimoto 0:0e0631af0305 1973 static void setDefaultAllocator(MatAllocator* allocator);
RyoheiHagimoto 0:0e0631af0305 1974
RyoheiHagimoto 0:0e0631af0305 1975 //! interaction with UMat
RyoheiHagimoto 0:0e0631af0305 1976 UMatData* u;
RyoheiHagimoto 0:0e0631af0305 1977
RyoheiHagimoto 0:0e0631af0305 1978 MatSize size;
RyoheiHagimoto 0:0e0631af0305 1979 MatStep step;
RyoheiHagimoto 0:0e0631af0305 1980
RyoheiHagimoto 0:0e0631af0305 1981 protected:
RyoheiHagimoto 0:0e0631af0305 1982 template<typename _Tp, typename Functor> void forEach_impl(const Functor& operation);
RyoheiHagimoto 0:0e0631af0305 1983 };
RyoheiHagimoto 0:0e0631af0305 1984
RyoheiHagimoto 0:0e0631af0305 1985
RyoheiHagimoto 0:0e0631af0305 1986 ///////////////////////////////// Mat_<_Tp> ////////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 1987
RyoheiHagimoto 0:0e0631af0305 1988 /** @brief Template matrix class derived from Mat
RyoheiHagimoto 0:0e0631af0305 1989
RyoheiHagimoto 0:0e0631af0305 1990 @code
RyoheiHagimoto 0:0e0631af0305 1991 template<typename _Tp> class Mat_ : public Mat
RyoheiHagimoto 0:0e0631af0305 1992 {
RyoheiHagimoto 0:0e0631af0305 1993 public:
RyoheiHagimoto 0:0e0631af0305 1994 // ... some specific methods
RyoheiHagimoto 0:0e0631af0305 1995 // and
RyoheiHagimoto 0:0e0631af0305 1996 // no new extra fields
RyoheiHagimoto 0:0e0631af0305 1997 };
RyoheiHagimoto 0:0e0631af0305 1998 @endcode
RyoheiHagimoto 0:0e0631af0305 1999 The class `Mat_<_Tp>` is a *thin* template wrapper on top of the Mat class. It does not have any
RyoheiHagimoto 0:0e0631af0305 2000 extra data fields. Nor this class nor Mat has any virtual methods. Thus, references or pointers to
RyoheiHagimoto 0:0e0631af0305 2001 these two classes can be freely but carefully converted one to another. For example:
RyoheiHagimoto 0:0e0631af0305 2002 @code
RyoheiHagimoto 0:0e0631af0305 2003 // create a 100x100 8-bit matrix
RyoheiHagimoto 0:0e0631af0305 2004 Mat M(100,100,CV_8U);
RyoheiHagimoto 0:0e0631af0305 2005 // this will be compiled fine. no any data conversion will be done.
RyoheiHagimoto 0:0e0631af0305 2006 Mat_<float>& M1 = (Mat_<float>&)M;
RyoheiHagimoto 0:0e0631af0305 2007 // the program is likely to crash at the statement below
RyoheiHagimoto 0:0e0631af0305 2008 M1(99,99) = 1.f;
RyoheiHagimoto 0:0e0631af0305 2009 @endcode
RyoheiHagimoto 0:0e0631af0305 2010 While Mat is sufficient in most cases, Mat_ can be more convenient if you use a lot of element
RyoheiHagimoto 0:0e0631af0305 2011 access operations and if you know matrix type at the compilation time. Note that
RyoheiHagimoto 0:0e0631af0305 2012 `Mat::at(int y,int x)` and `Mat_::operator()(int y,int x)` do absolutely the same
RyoheiHagimoto 0:0e0631af0305 2013 and run at the same speed, but the latter is certainly shorter:
RyoheiHagimoto 0:0e0631af0305 2014 @code
RyoheiHagimoto 0:0e0631af0305 2015 Mat_<double> M(20,20);
RyoheiHagimoto 0:0e0631af0305 2016 for(int i = 0; i < M.rows; i++)
RyoheiHagimoto 0:0e0631af0305 2017 for(int j = 0; j < M.cols; j++)
RyoheiHagimoto 0:0e0631af0305 2018 M(i,j) = 1./(i+j+1);
RyoheiHagimoto 0:0e0631af0305 2019 Mat E, V;
RyoheiHagimoto 0:0e0631af0305 2020 eigen(M,E,V);
RyoheiHagimoto 0:0e0631af0305 2021 cout << E.at<double>(0,0)/E.at<double>(M.rows-1,0);
RyoheiHagimoto 0:0e0631af0305 2022 @endcode
RyoheiHagimoto 0:0e0631af0305 2023 To use Mat_ for multi-channel images/matrices, pass Vec as a Mat_ parameter:
RyoheiHagimoto 0:0e0631af0305 2024 @code
RyoheiHagimoto 0:0e0631af0305 2025 // allocate a 320x240 color image and fill it with green (in RGB space)
RyoheiHagimoto 0:0e0631af0305 2026 Mat_<Vec3b> img(240, 320, Vec3b(0,255,0));
RyoheiHagimoto 0:0e0631af0305 2027 // now draw a diagonal white line
RyoheiHagimoto 0:0e0631af0305 2028 for(int i = 0; i < 100; i++)
RyoheiHagimoto 0:0e0631af0305 2029 img(i,i)=Vec3b(255,255,255);
RyoheiHagimoto 0:0e0631af0305 2030 // and now scramble the 2nd (red) channel of each pixel
RyoheiHagimoto 0:0e0631af0305 2031 for(int i = 0; i < img.rows; i++)
RyoheiHagimoto 0:0e0631af0305 2032 for(int j = 0; j < img.cols; j++)
RyoheiHagimoto 0:0e0631af0305 2033 img(i,j)[2] ^= (uchar)(i ^ j);
RyoheiHagimoto 0:0e0631af0305 2034 @endcode
RyoheiHagimoto 0:0e0631af0305 2035 */
RyoheiHagimoto 0:0e0631af0305 2036 template<typename _Tp> class Mat_ : public Mat
RyoheiHagimoto 0:0e0631af0305 2037 {
RyoheiHagimoto 0:0e0631af0305 2038 public:
RyoheiHagimoto 0:0e0631af0305 2039 typedef _Tp value_type;
RyoheiHagimoto 0:0e0631af0305 2040 typedef typename DataType<_Tp>::channel_type channel_type;
RyoheiHagimoto 0:0e0631af0305 2041 typedef MatIterator_<_Tp> iterator;
RyoheiHagimoto 0:0e0631af0305 2042 typedef MatConstIterator_<_Tp> const_iterator;
RyoheiHagimoto 0:0e0631af0305 2043
RyoheiHagimoto 0:0e0631af0305 2044 //! default constructor
RyoheiHagimoto 0:0e0631af0305 2045 Mat_();
RyoheiHagimoto 0:0e0631af0305 2046 //! equivalent to Mat(_rows, _cols, DataType<_Tp>::type)
RyoheiHagimoto 0:0e0631af0305 2047 Mat_(int _rows, int _cols);
RyoheiHagimoto 0:0e0631af0305 2048 //! constructor that sets each matrix element to specified value
RyoheiHagimoto 0:0e0631af0305 2049 Mat_(int _rows, int _cols, const _Tp& value);
RyoheiHagimoto 0:0e0631af0305 2050 //! equivalent to Mat(_size, DataType<_Tp>::type)
RyoheiHagimoto 0:0e0631af0305 2051 explicit Mat_(Size _size);
RyoheiHagimoto 0:0e0631af0305 2052 //! constructor that sets each matrix element to specified value
RyoheiHagimoto 0:0e0631af0305 2053 Mat_(Size _size, const _Tp& value);
RyoheiHagimoto 0:0e0631af0305 2054 //! n-dim array constructor
RyoheiHagimoto 0:0e0631af0305 2055 Mat_(int _ndims, const int* _sizes);
RyoheiHagimoto 0:0e0631af0305 2056 //! n-dim array constructor that sets each matrix element to specified value
RyoheiHagimoto 0:0e0631af0305 2057 Mat_(int _ndims, const int* _sizes, const _Tp& value);
RyoheiHagimoto 0:0e0631af0305 2058 //! copy/conversion contructor. If m is of different type, it's converted
RyoheiHagimoto 0:0e0631af0305 2059 Mat_(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 2060 //! copy constructor
RyoheiHagimoto 0:0e0631af0305 2061 Mat_(const Mat_& m);
RyoheiHagimoto 0:0e0631af0305 2062 //! constructs a matrix on top of user-allocated data. step is in bytes(!!!), regardless of the type
RyoheiHagimoto 0:0e0631af0305 2063 Mat_(int _rows, int _cols, _Tp* _data, size_t _step=AUTO_STEP);
RyoheiHagimoto 0:0e0631af0305 2064 //! constructs n-dim matrix on top of user-allocated data. steps are in bytes(!!!), regardless of the type
RyoheiHagimoto 0:0e0631af0305 2065 Mat_(int _ndims, const int* _sizes, _Tp* _data, const size_t* _steps=0);
RyoheiHagimoto 0:0e0631af0305 2066 //! selects a submatrix
RyoheiHagimoto 0:0e0631af0305 2067 Mat_(const Mat_& m, const Range& rowRange, const Range& colRange=Range::all());
RyoheiHagimoto 0:0e0631af0305 2068 //! selects a submatrix
RyoheiHagimoto 0:0e0631af0305 2069 Mat_(const Mat_& m, const Rect& roi);
RyoheiHagimoto 0:0e0631af0305 2070 //! selects a submatrix, n-dim version
RyoheiHagimoto 0:0e0631af0305 2071 Mat_(const Mat_& m, const Range* ranges);
RyoheiHagimoto 0:0e0631af0305 2072 //! selects a submatrix, n-dim version
RyoheiHagimoto 0:0e0631af0305 2073 Mat_(const Mat_& m, const std::vector<Range>& ranges);
RyoheiHagimoto 0:0e0631af0305 2074 //! from a matrix expression
RyoheiHagimoto 0:0e0631af0305 2075 explicit Mat_(const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 2076 //! makes a matrix out of Vec, std::vector, Point_ or Point3_. The matrix will have a single column
RyoheiHagimoto 0:0e0631af0305 2077 explicit Mat_(const std::vector<_Tp>& vec, bool copyData=false);
RyoheiHagimoto 0:0e0631af0305 2078 template<int n> explicit Mat_(const Vec<typename DataType<_Tp>::channel_type, n>& vec, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 2079 template<int m, int n> explicit Mat_(const Matx<typename DataType<_Tp>::channel_type, m, n>& mtx, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 2080 explicit Mat_(const Point_<typename DataType<_Tp>::channel_type>& pt, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 2081 explicit Mat_(const Point3_<typename DataType<_Tp>::channel_type>& pt, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 2082 explicit Mat_(const MatCommaInitializer_<_Tp>& commaInitializer);
RyoheiHagimoto 0:0e0631af0305 2083
RyoheiHagimoto 0:0e0631af0305 2084 Mat_& operator = (const Mat& m);
RyoheiHagimoto 0:0e0631af0305 2085 Mat_& operator = (const Mat_& m);
RyoheiHagimoto 0:0e0631af0305 2086 //! set all the elements to s.
RyoheiHagimoto 0:0e0631af0305 2087 Mat_& operator = (const _Tp& s);
RyoheiHagimoto 0:0e0631af0305 2088 //! assign a matrix expression
RyoheiHagimoto 0:0e0631af0305 2089 Mat_& operator = (const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 2090
RyoheiHagimoto 0:0e0631af0305 2091 //! iterators; they are smart enough to skip gaps in the end of rows
RyoheiHagimoto 0:0e0631af0305 2092 iterator begin();
RyoheiHagimoto 0:0e0631af0305 2093 iterator end();
RyoheiHagimoto 0:0e0631af0305 2094 const_iterator begin() const;
RyoheiHagimoto 0:0e0631af0305 2095 const_iterator end() const;
RyoheiHagimoto 0:0e0631af0305 2096
RyoheiHagimoto 0:0e0631af0305 2097 //! template methods for for operation over all matrix elements.
RyoheiHagimoto 0:0e0631af0305 2098 // the operations take care of skipping gaps in the end of rows (if any)
RyoheiHagimoto 0:0e0631af0305 2099 template<typename Functor> void forEach(const Functor& operation);
RyoheiHagimoto 0:0e0631af0305 2100 template<typename Functor> void forEach(const Functor& operation) const;
RyoheiHagimoto 0:0e0631af0305 2101
RyoheiHagimoto 0:0e0631af0305 2102 //! equivalent to Mat::create(_rows, _cols, DataType<_Tp>::type)
RyoheiHagimoto 0:0e0631af0305 2103 void create(int _rows, int _cols);
RyoheiHagimoto 0:0e0631af0305 2104 //! equivalent to Mat::create(_size, DataType<_Tp>::type)
RyoheiHagimoto 0:0e0631af0305 2105 void create(Size _size);
RyoheiHagimoto 0:0e0631af0305 2106 //! equivalent to Mat::create(_ndims, _sizes, DatType<_Tp>::type)
RyoheiHagimoto 0:0e0631af0305 2107 void create(int _ndims, const int* _sizes);
RyoheiHagimoto 0:0e0631af0305 2108 //! cross-product
RyoheiHagimoto 0:0e0631af0305 2109 Mat_ cross(const Mat_& m) const;
RyoheiHagimoto 0:0e0631af0305 2110 //! data type conversion
RyoheiHagimoto 0:0e0631af0305 2111 template<typename T2> operator Mat_<T2>() const;
RyoheiHagimoto 0:0e0631af0305 2112 //! overridden forms of Mat::row() etc.
RyoheiHagimoto 0:0e0631af0305 2113 Mat_ row(int y) const;
RyoheiHagimoto 0:0e0631af0305 2114 Mat_ col(int x) const;
RyoheiHagimoto 0:0e0631af0305 2115 Mat_ diag(int d=0) const;
RyoheiHagimoto 0:0e0631af0305 2116 Mat_ clone() const;
RyoheiHagimoto 0:0e0631af0305 2117
RyoheiHagimoto 0:0e0631af0305 2118 //! overridden forms of Mat::elemSize() etc.
RyoheiHagimoto 0:0e0631af0305 2119 size_t elemSize() const;
RyoheiHagimoto 0:0e0631af0305 2120 size_t elemSize1() const;
RyoheiHagimoto 0:0e0631af0305 2121 int type() const;
RyoheiHagimoto 0:0e0631af0305 2122 int depth() const;
RyoheiHagimoto 0:0e0631af0305 2123 int channels() const;
RyoheiHagimoto 0:0e0631af0305 2124 size_t step1(int i=0) const;
RyoheiHagimoto 0:0e0631af0305 2125 //! returns step()/sizeof(_Tp)
RyoheiHagimoto 0:0e0631af0305 2126 size_t stepT(int i=0) const;
RyoheiHagimoto 0:0e0631af0305 2127
RyoheiHagimoto 0:0e0631af0305 2128 //! overridden forms of Mat::zeros() etc. Data type is omitted, of course
RyoheiHagimoto 0:0e0631af0305 2129 static MatExpr zeros(int rows, int cols);
RyoheiHagimoto 0:0e0631af0305 2130 static MatExpr zeros(Size size);
RyoheiHagimoto 0:0e0631af0305 2131 static MatExpr zeros(int _ndims, const int* _sizes);
RyoheiHagimoto 0:0e0631af0305 2132 static MatExpr ones(int rows, int cols);
RyoheiHagimoto 0:0e0631af0305 2133 static MatExpr ones(Size size);
RyoheiHagimoto 0:0e0631af0305 2134 static MatExpr ones(int _ndims, const int* _sizes);
RyoheiHagimoto 0:0e0631af0305 2135 static MatExpr eye(int rows, int cols);
RyoheiHagimoto 0:0e0631af0305 2136 static MatExpr eye(Size size);
RyoheiHagimoto 0:0e0631af0305 2137
RyoheiHagimoto 0:0e0631af0305 2138 //! some more overriden methods
RyoheiHagimoto 0:0e0631af0305 2139 Mat_& adjustROI( int dtop, int dbottom, int dleft, int dright );
RyoheiHagimoto 0:0e0631af0305 2140 Mat_ operator()( const Range& rowRange, const Range& colRange ) const;
RyoheiHagimoto 0:0e0631af0305 2141 Mat_ operator()( const Rect& roi ) const;
RyoheiHagimoto 0:0e0631af0305 2142 Mat_ operator()( const Range* ranges ) const;
RyoheiHagimoto 0:0e0631af0305 2143 Mat_ operator()(const std::vector<Range>& ranges) const;
RyoheiHagimoto 0:0e0631af0305 2144
RyoheiHagimoto 0:0e0631af0305 2145 //! more convenient forms of row and element access operators
RyoheiHagimoto 0:0e0631af0305 2146 _Tp* operator [](int y);
RyoheiHagimoto 0:0e0631af0305 2147 const _Tp* operator [](int y) const;
RyoheiHagimoto 0:0e0631af0305 2148
RyoheiHagimoto 0:0e0631af0305 2149 //! returns reference to the specified element
RyoheiHagimoto 0:0e0631af0305 2150 _Tp& operator ()(const int* idx);
RyoheiHagimoto 0:0e0631af0305 2151 //! returns read-only reference to the specified element
RyoheiHagimoto 0:0e0631af0305 2152 const _Tp& operator ()(const int* idx) const;
RyoheiHagimoto 0:0e0631af0305 2153
RyoheiHagimoto 0:0e0631af0305 2154 //! returns reference to the specified element
RyoheiHagimoto 0:0e0631af0305 2155 template<int n> _Tp& operator ()(const Vec<int, n>& idx);
RyoheiHagimoto 0:0e0631af0305 2156 //! returns read-only reference to the specified element
RyoheiHagimoto 0:0e0631af0305 2157 template<int n> const _Tp& operator ()(const Vec<int, n>& idx) const;
RyoheiHagimoto 0:0e0631af0305 2158
RyoheiHagimoto 0:0e0631af0305 2159 //! returns reference to the specified element (1D case)
RyoheiHagimoto 0:0e0631af0305 2160 _Tp& operator ()(int idx0);
RyoheiHagimoto 0:0e0631af0305 2161 //! returns read-only reference to the specified element (1D case)
RyoheiHagimoto 0:0e0631af0305 2162 const _Tp& operator ()(int idx0) const;
RyoheiHagimoto 0:0e0631af0305 2163 //! returns reference to the specified element (2D case)
RyoheiHagimoto 0:0e0631af0305 2164 _Tp& operator ()(int row, int col);
RyoheiHagimoto 0:0e0631af0305 2165 //! returns read-only reference to the specified element (2D case)
RyoheiHagimoto 0:0e0631af0305 2166 const _Tp& operator ()(int row, int col) const;
RyoheiHagimoto 0:0e0631af0305 2167 //! returns reference to the specified element (3D case)
RyoheiHagimoto 0:0e0631af0305 2168 _Tp& operator ()(int idx0, int idx1, int idx2);
RyoheiHagimoto 0:0e0631af0305 2169 //! returns read-only reference to the specified element (3D case)
RyoheiHagimoto 0:0e0631af0305 2170 const _Tp& operator ()(int idx0, int idx1, int idx2) const;
RyoheiHagimoto 0:0e0631af0305 2171
RyoheiHagimoto 0:0e0631af0305 2172 _Tp& operator ()(Point pt);
RyoheiHagimoto 0:0e0631af0305 2173 const _Tp& operator ()(Point pt) const;
RyoheiHagimoto 0:0e0631af0305 2174
RyoheiHagimoto 0:0e0631af0305 2175 //! conversion to vector.
RyoheiHagimoto 0:0e0631af0305 2176 operator std::vector<_Tp>() const;
RyoheiHagimoto 0:0e0631af0305 2177 //! conversion to Vec
RyoheiHagimoto 0:0e0631af0305 2178 template<int n> operator Vec<typename DataType<_Tp>::channel_type, n>() const;
RyoheiHagimoto 0:0e0631af0305 2179 //! conversion to Matx
RyoheiHagimoto 0:0e0631af0305 2180 template<int m, int n> operator Matx<typename DataType<_Tp>::channel_type, m, n>() const;
RyoheiHagimoto 0:0e0631af0305 2181
RyoheiHagimoto 0:0e0631af0305 2182 #ifdef CV_CXX_MOVE_SEMANTICS
RyoheiHagimoto 0:0e0631af0305 2183 Mat_(Mat_&& m);
RyoheiHagimoto 0:0e0631af0305 2184 Mat_& operator = (Mat_&& m);
RyoheiHagimoto 0:0e0631af0305 2185
RyoheiHagimoto 0:0e0631af0305 2186 Mat_(Mat&& m);
RyoheiHagimoto 0:0e0631af0305 2187 Mat_& operator = (Mat&& m);
RyoheiHagimoto 0:0e0631af0305 2188
RyoheiHagimoto 0:0e0631af0305 2189 Mat_(MatExpr&& e);
RyoheiHagimoto 0:0e0631af0305 2190 #endif
RyoheiHagimoto 0:0e0631af0305 2191 };
RyoheiHagimoto 0:0e0631af0305 2192
RyoheiHagimoto 0:0e0631af0305 2193 typedef Mat_<uchar> Mat1b;
RyoheiHagimoto 0:0e0631af0305 2194 typedef Mat_<Vec2b> Mat2b;
RyoheiHagimoto 0:0e0631af0305 2195 typedef Mat_<Vec3b> Mat3b;
RyoheiHagimoto 0:0e0631af0305 2196 typedef Mat_<Vec4b> Mat4b;
RyoheiHagimoto 0:0e0631af0305 2197
RyoheiHagimoto 0:0e0631af0305 2198 typedef Mat_<short> Mat1s;
RyoheiHagimoto 0:0e0631af0305 2199 typedef Mat_<Vec2s> Mat2s;
RyoheiHagimoto 0:0e0631af0305 2200 typedef Mat_<Vec3s> Mat3s;
RyoheiHagimoto 0:0e0631af0305 2201 typedef Mat_<Vec4s> Mat4s;
RyoheiHagimoto 0:0e0631af0305 2202
RyoheiHagimoto 0:0e0631af0305 2203 typedef Mat_<ushort> Mat1w;
RyoheiHagimoto 0:0e0631af0305 2204 typedef Mat_<Vec2w> Mat2w;
RyoheiHagimoto 0:0e0631af0305 2205 typedef Mat_<Vec3w> Mat3w;
RyoheiHagimoto 0:0e0631af0305 2206 typedef Mat_<Vec4w> Mat4w;
RyoheiHagimoto 0:0e0631af0305 2207
RyoheiHagimoto 0:0e0631af0305 2208 typedef Mat_<int> Mat1i;
RyoheiHagimoto 0:0e0631af0305 2209 typedef Mat_<Vec2i> Mat2i;
RyoheiHagimoto 0:0e0631af0305 2210 typedef Mat_<Vec3i> Mat3i;
RyoheiHagimoto 0:0e0631af0305 2211 typedef Mat_<Vec4i> Mat4i;
RyoheiHagimoto 0:0e0631af0305 2212
RyoheiHagimoto 0:0e0631af0305 2213 typedef Mat_<float> Mat1f;
RyoheiHagimoto 0:0e0631af0305 2214 typedef Mat_<Vec2f> Mat2f;
RyoheiHagimoto 0:0e0631af0305 2215 typedef Mat_<Vec3f> Mat3f;
RyoheiHagimoto 0:0e0631af0305 2216 typedef Mat_<Vec4f> Mat4f;
RyoheiHagimoto 0:0e0631af0305 2217
RyoheiHagimoto 0:0e0631af0305 2218 typedef Mat_<double> Mat1d;
RyoheiHagimoto 0:0e0631af0305 2219 typedef Mat_<Vec2d> Mat2d;
RyoheiHagimoto 0:0e0631af0305 2220 typedef Mat_<Vec3d> Mat3d;
RyoheiHagimoto 0:0e0631af0305 2221 typedef Mat_<Vec4d> Mat4d;
RyoheiHagimoto 0:0e0631af0305 2222
RyoheiHagimoto 0:0e0631af0305 2223 /** @todo document */
RyoheiHagimoto 0:0e0631af0305 2224 class CV_EXPORTS UMat
RyoheiHagimoto 0:0e0631af0305 2225 {
RyoheiHagimoto 0:0e0631af0305 2226 public:
RyoheiHagimoto 0:0e0631af0305 2227 //! default constructor
RyoheiHagimoto 0:0e0631af0305 2228 UMat(UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2229 //! constructs 2D matrix of the specified size and type
RyoheiHagimoto 0:0e0631af0305 2230 // (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.)
RyoheiHagimoto 0:0e0631af0305 2231 UMat(int rows, int cols, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2232 UMat(Size size, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2233 //! constucts 2D matrix and fills it with the specified value _s.
RyoheiHagimoto 0:0e0631af0305 2234 UMat(int rows, int cols, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2235 UMat(Size size, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2236
RyoheiHagimoto 0:0e0631af0305 2237 //! constructs n-dimensional matrix
RyoheiHagimoto 0:0e0631af0305 2238 UMat(int ndims, const int* sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2239 UMat(int ndims, const int* sizes, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2240
RyoheiHagimoto 0:0e0631af0305 2241 //! copy constructor
RyoheiHagimoto 0:0e0631af0305 2242 UMat(const UMat& m);
RyoheiHagimoto 0:0e0631af0305 2243
RyoheiHagimoto 0:0e0631af0305 2244 //! creates a matrix header for a part of the bigger matrix
RyoheiHagimoto 0:0e0631af0305 2245 UMat(const UMat& m, const Range& rowRange, const Range& colRange=Range::all());
RyoheiHagimoto 0:0e0631af0305 2246 UMat(const UMat& m, const Rect& roi);
RyoheiHagimoto 0:0e0631af0305 2247 UMat(const UMat& m, const Range* ranges);
RyoheiHagimoto 0:0e0631af0305 2248 UMat(const UMat& m, const std::vector<Range>& ranges);
RyoheiHagimoto 0:0e0631af0305 2249 //! builds matrix from std::vector with or without copying the data
RyoheiHagimoto 0:0e0631af0305 2250 template<typename _Tp> explicit UMat(const std::vector<_Tp>& vec, bool copyData=false);
RyoheiHagimoto 0:0e0631af0305 2251 //! builds matrix from cv::Vec; the data is copied by default
RyoheiHagimoto 0:0e0631af0305 2252 template<typename _Tp, int n> explicit UMat(const Vec<_Tp, n>& vec, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 2253 //! builds matrix from cv::Matx; the data is copied by default
RyoheiHagimoto 0:0e0631af0305 2254 template<typename _Tp, int m, int n> explicit UMat(const Matx<_Tp, m, n>& mtx, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 2255 //! builds matrix from a 2D point
RyoheiHagimoto 0:0e0631af0305 2256 template<typename _Tp> explicit UMat(const Point_<_Tp>& pt, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 2257 //! builds matrix from a 3D point
RyoheiHagimoto 0:0e0631af0305 2258 template<typename _Tp> explicit UMat(const Point3_<_Tp>& pt, bool copyData=true);
RyoheiHagimoto 0:0e0631af0305 2259 //! builds matrix from comma initializer
RyoheiHagimoto 0:0e0631af0305 2260 template<typename _Tp> explicit UMat(const MatCommaInitializer_<_Tp>& commaInitializer);
RyoheiHagimoto 0:0e0631af0305 2261
RyoheiHagimoto 0:0e0631af0305 2262 //! destructor - calls release()
RyoheiHagimoto 0:0e0631af0305 2263 ~UMat();
RyoheiHagimoto 0:0e0631af0305 2264 //! assignment operators
RyoheiHagimoto 0:0e0631af0305 2265 UMat& operator = (const UMat& m);
RyoheiHagimoto 0:0e0631af0305 2266
RyoheiHagimoto 0:0e0631af0305 2267 Mat getMat(int flags) const;
RyoheiHagimoto 0:0e0631af0305 2268
RyoheiHagimoto 0:0e0631af0305 2269 //! returns a new matrix header for the specified row
RyoheiHagimoto 0:0e0631af0305 2270 UMat row(int y) const;
RyoheiHagimoto 0:0e0631af0305 2271 //! returns a new matrix header for the specified column
RyoheiHagimoto 0:0e0631af0305 2272 UMat col(int x) const;
RyoheiHagimoto 0:0e0631af0305 2273 //! ... for the specified row span
RyoheiHagimoto 0:0e0631af0305 2274 UMat rowRange(int startrow, int endrow) const;
RyoheiHagimoto 0:0e0631af0305 2275 UMat rowRange(const Range& r) const;
RyoheiHagimoto 0:0e0631af0305 2276 //! ... for the specified column span
RyoheiHagimoto 0:0e0631af0305 2277 UMat colRange(int startcol, int endcol) const;
RyoheiHagimoto 0:0e0631af0305 2278 UMat colRange(const Range& r) const;
RyoheiHagimoto 0:0e0631af0305 2279 //! ... for the specified diagonal
RyoheiHagimoto 0:0e0631af0305 2280 // (d=0 - the main diagonal,
RyoheiHagimoto 0:0e0631af0305 2281 // >0 - a diagonal from the lower half,
RyoheiHagimoto 0:0e0631af0305 2282 // <0 - a diagonal from the upper half)
RyoheiHagimoto 0:0e0631af0305 2283 UMat diag(int d=0) const;
RyoheiHagimoto 0:0e0631af0305 2284 //! constructs a square diagonal matrix which main diagonal is vector "d"
RyoheiHagimoto 0:0e0631af0305 2285 static UMat diag(const UMat& d);
RyoheiHagimoto 0:0e0631af0305 2286
RyoheiHagimoto 0:0e0631af0305 2287 //! returns deep copy of the matrix, i.e. the data is copied
RyoheiHagimoto 0:0e0631af0305 2288 UMat clone() const;
RyoheiHagimoto 0:0e0631af0305 2289 //! copies the matrix content to "m".
RyoheiHagimoto 0:0e0631af0305 2290 // It calls m.create(this->size(), this->type()).
RyoheiHagimoto 0:0e0631af0305 2291 void copyTo( OutputArray m ) const;
RyoheiHagimoto 0:0e0631af0305 2292 //! copies those matrix elements to "m" that are marked with non-zero mask elements.
RyoheiHagimoto 0:0e0631af0305 2293 void copyTo( OutputArray m, InputArray mask ) const;
RyoheiHagimoto 0:0e0631af0305 2294 //! converts matrix to another datatype with optional scalng. See cvConvertScale.
RyoheiHagimoto 0:0e0631af0305 2295 void convertTo( OutputArray m, int rtype, double alpha=1, double beta=0 ) const;
RyoheiHagimoto 0:0e0631af0305 2296
RyoheiHagimoto 0:0e0631af0305 2297 void assignTo( UMat& m, int type=-1 ) const;
RyoheiHagimoto 0:0e0631af0305 2298
RyoheiHagimoto 0:0e0631af0305 2299 //! sets every matrix element to s
RyoheiHagimoto 0:0e0631af0305 2300 UMat& operator = (const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 2301 //! sets some of the matrix elements to s, according to the mask
RyoheiHagimoto 0:0e0631af0305 2302 UMat& setTo(InputArray value, InputArray mask=noArray());
RyoheiHagimoto 0:0e0631af0305 2303 //! creates alternative matrix header for the same data, with different
RyoheiHagimoto 0:0e0631af0305 2304 // number of channels and/or different number of rows. see cvReshape.
RyoheiHagimoto 0:0e0631af0305 2305 UMat reshape(int cn, int rows=0) const;
RyoheiHagimoto 0:0e0631af0305 2306 UMat reshape(int cn, int newndims, const int* newsz) const;
RyoheiHagimoto 0:0e0631af0305 2307
RyoheiHagimoto 0:0e0631af0305 2308 //! matrix transposition by means of matrix expressions
RyoheiHagimoto 0:0e0631af0305 2309 UMat t() const;
RyoheiHagimoto 0:0e0631af0305 2310 //! matrix inversion by means of matrix expressions
RyoheiHagimoto 0:0e0631af0305 2311 UMat inv(int method=DECOMP_LU) const;
RyoheiHagimoto 0:0e0631af0305 2312 //! per-element matrix multiplication by means of matrix expressions
RyoheiHagimoto 0:0e0631af0305 2313 UMat mul(InputArray m, double scale=1) const;
RyoheiHagimoto 0:0e0631af0305 2314
RyoheiHagimoto 0:0e0631af0305 2315 //! computes dot-product
RyoheiHagimoto 0:0e0631af0305 2316 double dot(InputArray m) const;
RyoheiHagimoto 0:0e0631af0305 2317
RyoheiHagimoto 0:0e0631af0305 2318 //! Matlab-style matrix initialization
RyoheiHagimoto 0:0e0631af0305 2319 static UMat zeros(int rows, int cols, int type);
RyoheiHagimoto 0:0e0631af0305 2320 static UMat zeros(Size size, int type);
RyoheiHagimoto 0:0e0631af0305 2321 static UMat zeros(int ndims, const int* sz, int type);
RyoheiHagimoto 0:0e0631af0305 2322 static UMat ones(int rows, int cols, int type);
RyoheiHagimoto 0:0e0631af0305 2323 static UMat ones(Size size, int type);
RyoheiHagimoto 0:0e0631af0305 2324 static UMat ones(int ndims, const int* sz, int type);
RyoheiHagimoto 0:0e0631af0305 2325 static UMat eye(int rows, int cols, int type);
RyoheiHagimoto 0:0e0631af0305 2326 static UMat eye(Size size, int type);
RyoheiHagimoto 0:0e0631af0305 2327
RyoheiHagimoto 0:0e0631af0305 2328 //! allocates new matrix data unless the matrix already has specified size and type.
RyoheiHagimoto 0:0e0631af0305 2329 // previous data is unreferenced if needed.
RyoheiHagimoto 0:0e0631af0305 2330 void create(int rows, int cols, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2331 void create(Size size, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2332 void create(int ndims, const int* sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2333 void create(const std::vector<int>& sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
RyoheiHagimoto 0:0e0631af0305 2334
RyoheiHagimoto 0:0e0631af0305 2335 //! increases the reference counter; use with care to avoid memleaks
RyoheiHagimoto 0:0e0631af0305 2336 void addref();
RyoheiHagimoto 0:0e0631af0305 2337 //! decreases reference counter;
RyoheiHagimoto 0:0e0631af0305 2338 // deallocates the data when reference counter reaches 0.
RyoheiHagimoto 0:0e0631af0305 2339 void release();
RyoheiHagimoto 0:0e0631af0305 2340
RyoheiHagimoto 0:0e0631af0305 2341 //! deallocates the matrix data
RyoheiHagimoto 0:0e0631af0305 2342 void deallocate();
RyoheiHagimoto 0:0e0631af0305 2343 //! internal use function; properly re-allocates _size, _step arrays
RyoheiHagimoto 0:0e0631af0305 2344 void copySize(const UMat& m);
RyoheiHagimoto 0:0e0631af0305 2345
RyoheiHagimoto 0:0e0631af0305 2346 //! locates matrix header within a parent matrix. See below
RyoheiHagimoto 0:0e0631af0305 2347 void locateROI( Size& wholeSize, Point& ofs ) const;
RyoheiHagimoto 0:0e0631af0305 2348 //! moves/resizes the current matrix ROI inside the parent matrix.
RyoheiHagimoto 0:0e0631af0305 2349 UMat& adjustROI( int dtop, int dbottom, int dleft, int dright );
RyoheiHagimoto 0:0e0631af0305 2350 //! extracts a rectangular sub-matrix
RyoheiHagimoto 0:0e0631af0305 2351 // (this is a generalized form of row, rowRange etc.)
RyoheiHagimoto 0:0e0631af0305 2352 UMat operator()( Range rowRange, Range colRange ) const;
RyoheiHagimoto 0:0e0631af0305 2353 UMat operator()( const Rect& roi ) const;
RyoheiHagimoto 0:0e0631af0305 2354 UMat operator()( const Range* ranges ) const;
RyoheiHagimoto 0:0e0631af0305 2355 UMat operator()(const std::vector<Range>& ranges) const;
RyoheiHagimoto 0:0e0631af0305 2356
RyoheiHagimoto 0:0e0631af0305 2357 //! returns true iff the matrix data is continuous
RyoheiHagimoto 0:0e0631af0305 2358 // (i.e. when there are no gaps between successive rows).
RyoheiHagimoto 0:0e0631af0305 2359 // similar to CV_IS_MAT_CONT(cvmat->type)
RyoheiHagimoto 0:0e0631af0305 2360 bool isContinuous() const;
RyoheiHagimoto 0:0e0631af0305 2361
RyoheiHagimoto 0:0e0631af0305 2362 //! returns true if the matrix is a submatrix of another matrix
RyoheiHagimoto 0:0e0631af0305 2363 bool isSubmatrix() const;
RyoheiHagimoto 0:0e0631af0305 2364
RyoheiHagimoto 0:0e0631af0305 2365 //! returns element size in bytes,
RyoheiHagimoto 0:0e0631af0305 2366 // similar to CV_ELEM_SIZE(cvmat->type)
RyoheiHagimoto 0:0e0631af0305 2367 size_t elemSize() const;
RyoheiHagimoto 0:0e0631af0305 2368 //! returns the size of element channel in bytes.
RyoheiHagimoto 0:0e0631af0305 2369 size_t elemSize1() const;
RyoheiHagimoto 0:0e0631af0305 2370 //! returns element type, similar to CV_MAT_TYPE(cvmat->type)
RyoheiHagimoto 0:0e0631af0305 2371 int type() const;
RyoheiHagimoto 0:0e0631af0305 2372 //! returns element type, similar to CV_MAT_DEPTH(cvmat->type)
RyoheiHagimoto 0:0e0631af0305 2373 int depth() const;
RyoheiHagimoto 0:0e0631af0305 2374 //! returns element type, similar to CV_MAT_CN(cvmat->type)
RyoheiHagimoto 0:0e0631af0305 2375 int channels() const;
RyoheiHagimoto 0:0e0631af0305 2376 //! returns step/elemSize1()
RyoheiHagimoto 0:0e0631af0305 2377 size_t step1(int i=0) const;
RyoheiHagimoto 0:0e0631af0305 2378 //! returns true if matrix data is NULL
RyoheiHagimoto 0:0e0631af0305 2379 bool empty() const;
RyoheiHagimoto 0:0e0631af0305 2380 //! returns the total number of matrix elements
RyoheiHagimoto 0:0e0631af0305 2381 size_t total() const;
RyoheiHagimoto 0:0e0631af0305 2382
RyoheiHagimoto 0:0e0631af0305 2383 //! returns N if the matrix is 1-channel (N x ptdim) or ptdim-channel (1 x N) or (N x 1); negative number otherwise
RyoheiHagimoto 0:0e0631af0305 2384 int checkVector(int elemChannels, int depth=-1, bool requireContinuous=true) const;
RyoheiHagimoto 0:0e0631af0305 2385
RyoheiHagimoto 0:0e0631af0305 2386 #ifdef CV_CXX_MOVE_SEMANTICS
RyoheiHagimoto 0:0e0631af0305 2387 UMat(UMat&& m);
RyoheiHagimoto 0:0e0631af0305 2388 UMat& operator = (UMat&& m);
RyoheiHagimoto 0:0e0631af0305 2389 #endif
RyoheiHagimoto 0:0e0631af0305 2390
RyoheiHagimoto 0:0e0631af0305 2391 void* handle(int accessFlags) const;
RyoheiHagimoto 0:0e0631af0305 2392 void ndoffset(size_t* ofs) const;
RyoheiHagimoto 0:0e0631af0305 2393
RyoheiHagimoto 0:0e0631af0305 2394 enum { MAGIC_VAL = 0x42FF0000, AUTO_STEP = 0, CONTINUOUS_FLAG = CV_MAT_CONT_FLAG, SUBMATRIX_FLAG = CV_SUBMAT_FLAG };
RyoheiHagimoto 0:0e0631af0305 2395 enum { MAGIC_MASK = 0xFFFF0000, TYPE_MASK = 0x00000FFF, DEPTH_MASK = 7 };
RyoheiHagimoto 0:0e0631af0305 2396
RyoheiHagimoto 0:0e0631af0305 2397 /*! includes several bit-fields:
RyoheiHagimoto 0:0e0631af0305 2398 - the magic signature
RyoheiHagimoto 0:0e0631af0305 2399 - continuity flag
RyoheiHagimoto 0:0e0631af0305 2400 - depth
RyoheiHagimoto 0:0e0631af0305 2401 - number of channels
RyoheiHagimoto 0:0e0631af0305 2402 */
RyoheiHagimoto 0:0e0631af0305 2403 int flags;
RyoheiHagimoto 0:0e0631af0305 2404 //! the matrix dimensionality, >= 2
RyoheiHagimoto 0:0e0631af0305 2405 int dims;
RyoheiHagimoto 0:0e0631af0305 2406 //! the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
RyoheiHagimoto 0:0e0631af0305 2407 int rows, cols;
RyoheiHagimoto 0:0e0631af0305 2408
RyoheiHagimoto 0:0e0631af0305 2409 //! custom allocator
RyoheiHagimoto 0:0e0631af0305 2410 MatAllocator* allocator;
RyoheiHagimoto 0:0e0631af0305 2411 UMatUsageFlags usageFlags; // usage flags for allocator
RyoheiHagimoto 0:0e0631af0305 2412 //! and the standard allocator
RyoheiHagimoto 0:0e0631af0305 2413 static MatAllocator* getStdAllocator();
RyoheiHagimoto 0:0e0631af0305 2414
RyoheiHagimoto 0:0e0631af0305 2415 // black-box container of UMat data
RyoheiHagimoto 0:0e0631af0305 2416 UMatData* u;
RyoheiHagimoto 0:0e0631af0305 2417
RyoheiHagimoto 0:0e0631af0305 2418 // offset of the submatrix (or 0)
RyoheiHagimoto 0:0e0631af0305 2419 size_t offset;
RyoheiHagimoto 0:0e0631af0305 2420
RyoheiHagimoto 0:0e0631af0305 2421 MatSize size;
RyoheiHagimoto 0:0e0631af0305 2422 MatStep step;
RyoheiHagimoto 0:0e0631af0305 2423
RyoheiHagimoto 0:0e0631af0305 2424 protected:
RyoheiHagimoto 0:0e0631af0305 2425 };
RyoheiHagimoto 0:0e0631af0305 2426
RyoheiHagimoto 0:0e0631af0305 2427
RyoheiHagimoto 0:0e0631af0305 2428 /////////////////////////// multi-dimensional sparse matrix //////////////////////////
RyoheiHagimoto 0:0e0631af0305 2429
RyoheiHagimoto 0:0e0631af0305 2430 /** @brief The class SparseMat represents multi-dimensional sparse numerical arrays.
RyoheiHagimoto 0:0e0631af0305 2431
RyoheiHagimoto 0:0e0631af0305 2432 Such a sparse array can store elements of any type that Mat can store. *Sparse* means that only
RyoheiHagimoto 0:0e0631af0305 2433 non-zero elements are stored (though, as a result of operations on a sparse matrix, some of its
RyoheiHagimoto 0:0e0631af0305 2434 stored elements can actually become 0. It is up to you to detect such elements and delete them
RyoheiHagimoto 0:0e0631af0305 2435 using SparseMat::erase ). The non-zero elements are stored in a hash table that grows when it is
RyoheiHagimoto 0:0e0631af0305 2436 filled so that the search time is O(1) in average (regardless of whether element is there or not).
RyoheiHagimoto 0:0e0631af0305 2437 Elements can be accessed using the following methods:
RyoheiHagimoto 0:0e0631af0305 2438 - Query operations (SparseMat::ptr and the higher-level SparseMat::ref, SparseMat::value and
RyoheiHagimoto 0:0e0631af0305 2439 SparseMat::find), for example:
RyoheiHagimoto 0:0e0631af0305 2440 @code
RyoheiHagimoto 0:0e0631af0305 2441 const int dims = 5;
RyoheiHagimoto 0:0e0631af0305 2442 int size[5] = {10, 10, 10, 10, 10};
RyoheiHagimoto 0:0e0631af0305 2443 SparseMat sparse_mat(dims, size, CV_32F);
RyoheiHagimoto 0:0e0631af0305 2444 for(int i = 0; i < 1000; i++)
RyoheiHagimoto 0:0e0631af0305 2445 {
RyoheiHagimoto 0:0e0631af0305 2446 int idx[dims];
RyoheiHagimoto 0:0e0631af0305 2447 for(int k = 0; k < dims; k++)
RyoheiHagimoto 0:0e0631af0305 2448 idx[k] = rand() % size[k];
RyoheiHagimoto 0:0e0631af0305 2449 sparse_mat.ref<float>(idx) += 1.f;
RyoheiHagimoto 0:0e0631af0305 2450 }
RyoheiHagimoto 0:0e0631af0305 2451 cout << "nnz = " << sparse_mat.nzcount() << endl;
RyoheiHagimoto 0:0e0631af0305 2452 @endcode
RyoheiHagimoto 0:0e0631af0305 2453 - Sparse matrix iterators. They are similar to MatIterator but different from NAryMatIterator.
RyoheiHagimoto 0:0e0631af0305 2454 That is, the iteration loop is familiar to STL users:
RyoheiHagimoto 0:0e0631af0305 2455 @code
RyoheiHagimoto 0:0e0631af0305 2456 // prints elements of a sparse floating-point matrix
RyoheiHagimoto 0:0e0631af0305 2457 // and the sum of elements.
RyoheiHagimoto 0:0e0631af0305 2458 SparseMatConstIterator_<float>
RyoheiHagimoto 0:0e0631af0305 2459 it = sparse_mat.begin<float>(),
RyoheiHagimoto 0:0e0631af0305 2460 it_end = sparse_mat.end<float>();
RyoheiHagimoto 0:0e0631af0305 2461 double s = 0;
RyoheiHagimoto 0:0e0631af0305 2462 int dims = sparse_mat.dims();
RyoheiHagimoto 0:0e0631af0305 2463 for(; it != it_end; ++it)
RyoheiHagimoto 0:0e0631af0305 2464 {
RyoheiHagimoto 0:0e0631af0305 2465 // print element indices and the element value
RyoheiHagimoto 0:0e0631af0305 2466 const SparseMat::Node* n = it.node();
RyoheiHagimoto 0:0e0631af0305 2467 printf("(");
RyoheiHagimoto 0:0e0631af0305 2468 for(int i = 0; i < dims; i++)
RyoheiHagimoto 0:0e0631af0305 2469 printf("%d%s", n->idx[i], i < dims-1 ? ", " : ")");
RyoheiHagimoto 0:0e0631af0305 2470 printf(": %g\n", it.value<float>());
RyoheiHagimoto 0:0e0631af0305 2471 s += *it;
RyoheiHagimoto 0:0e0631af0305 2472 }
RyoheiHagimoto 0:0e0631af0305 2473 printf("Element sum is %g\n", s);
RyoheiHagimoto 0:0e0631af0305 2474 @endcode
RyoheiHagimoto 0:0e0631af0305 2475 If you run this loop, you will notice that elements are not enumerated in a logical order
RyoheiHagimoto 0:0e0631af0305 2476 (lexicographical, and so on). They come in the same order as they are stored in the hash table
RyoheiHagimoto 0:0e0631af0305 2477 (semi-randomly). You may collect pointers to the nodes and sort them to get the proper ordering.
RyoheiHagimoto 0:0e0631af0305 2478 Note, however, that pointers to the nodes may become invalid when you add more elements to the
RyoheiHagimoto 0:0e0631af0305 2479 matrix. This may happen due to possible buffer reallocation.
RyoheiHagimoto 0:0e0631af0305 2480 - Combination of the above 2 methods when you need to process 2 or more sparse matrices
RyoheiHagimoto 0:0e0631af0305 2481 simultaneously. For example, this is how you can compute unnormalized cross-correlation of the 2
RyoheiHagimoto 0:0e0631af0305 2482 floating-point sparse matrices:
RyoheiHagimoto 0:0e0631af0305 2483 @code
RyoheiHagimoto 0:0e0631af0305 2484 double cross_corr(const SparseMat& a, const SparseMat& b)
RyoheiHagimoto 0:0e0631af0305 2485 {
RyoheiHagimoto 0:0e0631af0305 2486 const SparseMat *_a = &a, *_b = &b;
RyoheiHagimoto 0:0e0631af0305 2487 // if b contains less elements than a,
RyoheiHagimoto 0:0e0631af0305 2488 // it is faster to iterate through b
RyoheiHagimoto 0:0e0631af0305 2489 if(_a->nzcount() > _b->nzcount())
RyoheiHagimoto 0:0e0631af0305 2490 std::swap(_a, _b);
RyoheiHagimoto 0:0e0631af0305 2491 SparseMatConstIterator_<float> it = _a->begin<float>(),
RyoheiHagimoto 0:0e0631af0305 2492 it_end = _a->end<float>();
RyoheiHagimoto 0:0e0631af0305 2493 double ccorr = 0;
RyoheiHagimoto 0:0e0631af0305 2494 for(; it != it_end; ++it)
RyoheiHagimoto 0:0e0631af0305 2495 {
RyoheiHagimoto 0:0e0631af0305 2496 // take the next element from the first matrix
RyoheiHagimoto 0:0e0631af0305 2497 float avalue = *it;
RyoheiHagimoto 0:0e0631af0305 2498 const Node* anode = it.node();
RyoheiHagimoto 0:0e0631af0305 2499 // and try to find an element with the same index in the second matrix.
RyoheiHagimoto 0:0e0631af0305 2500 // since the hash value depends only on the element index,
RyoheiHagimoto 0:0e0631af0305 2501 // reuse the hash value stored in the node
RyoheiHagimoto 0:0e0631af0305 2502 float bvalue = _b->value<float>(anode->idx,&anode->hashval);
RyoheiHagimoto 0:0e0631af0305 2503 ccorr += avalue*bvalue;
RyoheiHagimoto 0:0e0631af0305 2504 }
RyoheiHagimoto 0:0e0631af0305 2505 return ccorr;
RyoheiHagimoto 0:0e0631af0305 2506 }
RyoheiHagimoto 0:0e0631af0305 2507 @endcode
RyoheiHagimoto 0:0e0631af0305 2508 */
RyoheiHagimoto 0:0e0631af0305 2509 class CV_EXPORTS SparseMat
RyoheiHagimoto 0:0e0631af0305 2510 {
RyoheiHagimoto 0:0e0631af0305 2511 public:
RyoheiHagimoto 0:0e0631af0305 2512 typedef SparseMatIterator iterator;
RyoheiHagimoto 0:0e0631af0305 2513 typedef SparseMatConstIterator const_iterator;
RyoheiHagimoto 0:0e0631af0305 2514
RyoheiHagimoto 0:0e0631af0305 2515 enum { MAGIC_VAL=0x42FD0000, MAX_DIM=32, HASH_SCALE=0x5bd1e995, HASH_BIT=0x80000000 };
RyoheiHagimoto 0:0e0631af0305 2516
RyoheiHagimoto 0:0e0631af0305 2517 //! the sparse matrix header
RyoheiHagimoto 0:0e0631af0305 2518 struct CV_EXPORTS Hdr
RyoheiHagimoto 0:0e0631af0305 2519 {
RyoheiHagimoto 0:0e0631af0305 2520 Hdr(int _dims, const int* _sizes, int _type);
RyoheiHagimoto 0:0e0631af0305 2521 void clear();
RyoheiHagimoto 0:0e0631af0305 2522 int refcount;
RyoheiHagimoto 0:0e0631af0305 2523 int dims;
RyoheiHagimoto 0:0e0631af0305 2524 int valueOffset;
RyoheiHagimoto 0:0e0631af0305 2525 size_t nodeSize;
RyoheiHagimoto 0:0e0631af0305 2526 size_t nodeCount;
RyoheiHagimoto 0:0e0631af0305 2527 size_t freeList;
RyoheiHagimoto 0:0e0631af0305 2528 std::vector<uchar> pool;
RyoheiHagimoto 0:0e0631af0305 2529 std::vector<size_t> hashtab;
RyoheiHagimoto 0:0e0631af0305 2530 int size[MAX_DIM];
RyoheiHagimoto 0:0e0631af0305 2531 };
RyoheiHagimoto 0:0e0631af0305 2532
RyoheiHagimoto 0:0e0631af0305 2533 //! sparse matrix node - element of a hash table
RyoheiHagimoto 0:0e0631af0305 2534 struct CV_EXPORTS Node
RyoheiHagimoto 0:0e0631af0305 2535 {
RyoheiHagimoto 0:0e0631af0305 2536 //! hash value
RyoheiHagimoto 0:0e0631af0305 2537 size_t hashval;
RyoheiHagimoto 0:0e0631af0305 2538 //! index of the next node in the same hash table entry
RyoheiHagimoto 0:0e0631af0305 2539 size_t next;
RyoheiHagimoto 0:0e0631af0305 2540 //! index of the matrix element
RyoheiHagimoto 0:0e0631af0305 2541 int idx[MAX_DIM];
RyoheiHagimoto 0:0e0631af0305 2542 };
RyoheiHagimoto 0:0e0631af0305 2543
RyoheiHagimoto 0:0e0631af0305 2544 /** @brief Various SparseMat constructors.
RyoheiHagimoto 0:0e0631af0305 2545 */
RyoheiHagimoto 0:0e0631af0305 2546 SparseMat();
RyoheiHagimoto 0:0e0631af0305 2547
RyoheiHagimoto 0:0e0631af0305 2548 /** @overload
RyoheiHagimoto 0:0e0631af0305 2549 @param dims Array dimensionality.
RyoheiHagimoto 0:0e0631af0305 2550 @param _sizes Sparce matrix size on all dementions.
RyoheiHagimoto 0:0e0631af0305 2551 @param _type Sparse matrix data type.
RyoheiHagimoto 0:0e0631af0305 2552 */
RyoheiHagimoto 0:0e0631af0305 2553 SparseMat(int dims, const int* _sizes, int _type);
RyoheiHagimoto 0:0e0631af0305 2554
RyoheiHagimoto 0:0e0631af0305 2555 /** @overload
RyoheiHagimoto 0:0e0631af0305 2556 @param m Source matrix for copy constructor. If m is dense matrix (ocvMat) then it will be converted
RyoheiHagimoto 0:0e0631af0305 2557 to sparse representation.
RyoheiHagimoto 0:0e0631af0305 2558 */
RyoheiHagimoto 0:0e0631af0305 2559 SparseMat(const SparseMat& m);
RyoheiHagimoto 0:0e0631af0305 2560
RyoheiHagimoto 0:0e0631af0305 2561 /** @overload
RyoheiHagimoto 0:0e0631af0305 2562 @param m Source matrix for copy constructor. If m is dense matrix (ocvMat) then it will be converted
RyoheiHagimoto 0:0e0631af0305 2563 to sparse representation.
RyoheiHagimoto 0:0e0631af0305 2564 */
RyoheiHagimoto 0:0e0631af0305 2565 explicit SparseMat(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 2566
RyoheiHagimoto 0:0e0631af0305 2567 //! the destructor
RyoheiHagimoto 0:0e0631af0305 2568 ~SparseMat();
RyoheiHagimoto 0:0e0631af0305 2569
RyoheiHagimoto 0:0e0631af0305 2570 //! assignment operator. This is O(1) operation, i.e. no data is copied
RyoheiHagimoto 0:0e0631af0305 2571 SparseMat& operator = (const SparseMat& m);
RyoheiHagimoto 0:0e0631af0305 2572 //! equivalent to the corresponding constructor
RyoheiHagimoto 0:0e0631af0305 2573 SparseMat& operator = (const Mat& m);
RyoheiHagimoto 0:0e0631af0305 2574
RyoheiHagimoto 0:0e0631af0305 2575 //! creates full copy of the matrix
RyoheiHagimoto 0:0e0631af0305 2576 SparseMat clone() const;
RyoheiHagimoto 0:0e0631af0305 2577
RyoheiHagimoto 0:0e0631af0305 2578 //! copies all the data to the destination matrix. All the previous content of m is erased
RyoheiHagimoto 0:0e0631af0305 2579 void copyTo( SparseMat& m ) const;
RyoheiHagimoto 0:0e0631af0305 2580 //! converts sparse matrix to dense matrix.
RyoheiHagimoto 0:0e0631af0305 2581 void copyTo( Mat& m ) const;
RyoheiHagimoto 0:0e0631af0305 2582 //! multiplies all the matrix elements by the specified scale factor alpha and converts the results to the specified data type
RyoheiHagimoto 0:0e0631af0305 2583 void convertTo( SparseMat& m, int rtype, double alpha=1 ) const;
RyoheiHagimoto 0:0e0631af0305 2584 //! converts sparse matrix to dense n-dim matrix with optional type conversion and scaling.
RyoheiHagimoto 0:0e0631af0305 2585 /*!
RyoheiHagimoto 0:0e0631af0305 2586 @param [out] m - output matrix; if it does not have a proper size or type before the operation,
RyoheiHagimoto 0:0e0631af0305 2587 it is reallocated
RyoheiHagimoto 0:0e0631af0305 2588 @param [in] rtype – desired output matrix type or, rather, the depth since the number of channels
RyoheiHagimoto 0:0e0631af0305 2589 are the same as the input has; if rtype is negative, the output matrix will have the
RyoheiHagimoto 0:0e0631af0305 2590 same type as the input.
RyoheiHagimoto 0:0e0631af0305 2591 @param [in] alpha – optional scale factor
RyoheiHagimoto 0:0e0631af0305 2592 @param [in] beta – optional delta added to the scaled values
RyoheiHagimoto 0:0e0631af0305 2593 */
RyoheiHagimoto 0:0e0631af0305 2594 void convertTo( Mat& m, int rtype, double alpha=1, double beta=0 ) const;
RyoheiHagimoto 0:0e0631af0305 2595
RyoheiHagimoto 0:0e0631af0305 2596 // not used now
RyoheiHagimoto 0:0e0631af0305 2597 void assignTo( SparseMat& m, int type=-1 ) const;
RyoheiHagimoto 0:0e0631af0305 2598
RyoheiHagimoto 0:0e0631af0305 2599 //! reallocates sparse matrix.
RyoheiHagimoto 0:0e0631af0305 2600 /*!
RyoheiHagimoto 0:0e0631af0305 2601 If the matrix already had the proper size and type,
RyoheiHagimoto 0:0e0631af0305 2602 it is simply cleared with clear(), otherwise,
RyoheiHagimoto 0:0e0631af0305 2603 the old matrix is released (using release()) and the new one is allocated.
RyoheiHagimoto 0:0e0631af0305 2604 */
RyoheiHagimoto 0:0e0631af0305 2605 void create(int dims, const int* _sizes, int _type);
RyoheiHagimoto 0:0e0631af0305 2606 //! sets all the sparse matrix elements to 0, which means clearing the hash table.
RyoheiHagimoto 0:0e0631af0305 2607 void clear();
RyoheiHagimoto 0:0e0631af0305 2608 //! manually increments the reference counter to the header.
RyoheiHagimoto 0:0e0631af0305 2609 void addref();
RyoheiHagimoto 0:0e0631af0305 2610 // decrements the header reference counter. When the counter reaches 0, the header and all the underlying data are deallocated.
RyoheiHagimoto 0:0e0631af0305 2611 void release();
RyoheiHagimoto 0:0e0631af0305 2612
RyoheiHagimoto 0:0e0631af0305 2613 //! converts sparse matrix to the old-style representation; all the elements are copied.
RyoheiHagimoto 0:0e0631af0305 2614 //operator CvSparseMat*() const;
RyoheiHagimoto 0:0e0631af0305 2615 //! returns the size of each element in bytes (not including the overhead - the space occupied by SparseMat::Node elements)
RyoheiHagimoto 0:0e0631af0305 2616 size_t elemSize() const;
RyoheiHagimoto 0:0e0631af0305 2617 //! returns elemSize()/channels()
RyoheiHagimoto 0:0e0631af0305 2618 size_t elemSize1() const;
RyoheiHagimoto 0:0e0631af0305 2619
RyoheiHagimoto 0:0e0631af0305 2620 //! returns type of sparse matrix elements
RyoheiHagimoto 0:0e0631af0305 2621 int type() const;
RyoheiHagimoto 0:0e0631af0305 2622 //! returns the depth of sparse matrix elements
RyoheiHagimoto 0:0e0631af0305 2623 int depth() const;
RyoheiHagimoto 0:0e0631af0305 2624 //! returns the number of channels
RyoheiHagimoto 0:0e0631af0305 2625 int channels() const;
RyoheiHagimoto 0:0e0631af0305 2626
RyoheiHagimoto 0:0e0631af0305 2627 //! returns the array of sizes, or NULL if the matrix is not allocated
RyoheiHagimoto 0:0e0631af0305 2628 const int* size() const;
RyoheiHagimoto 0:0e0631af0305 2629 //! returns the size of i-th matrix dimension (or 0)
RyoheiHagimoto 0:0e0631af0305 2630 int size(int i) const;
RyoheiHagimoto 0:0e0631af0305 2631 //! returns the matrix dimensionality
RyoheiHagimoto 0:0e0631af0305 2632 int dims() const;
RyoheiHagimoto 0:0e0631af0305 2633 //! returns the number of non-zero elements (=the number of hash table nodes)
RyoheiHagimoto 0:0e0631af0305 2634 size_t nzcount() const;
RyoheiHagimoto 0:0e0631af0305 2635
RyoheiHagimoto 0:0e0631af0305 2636 //! computes the element hash value (1D case)
RyoheiHagimoto 0:0e0631af0305 2637 size_t hash(int i0) const;
RyoheiHagimoto 0:0e0631af0305 2638 //! computes the element hash value (2D case)
RyoheiHagimoto 0:0e0631af0305 2639 size_t hash(int i0, int i1) const;
RyoheiHagimoto 0:0e0631af0305 2640 //! computes the element hash value (3D case)
RyoheiHagimoto 0:0e0631af0305 2641 size_t hash(int i0, int i1, int i2) const;
RyoheiHagimoto 0:0e0631af0305 2642 //! computes the element hash value (nD case)
RyoheiHagimoto 0:0e0631af0305 2643 size_t hash(const int* idx) const;
RyoheiHagimoto 0:0e0631af0305 2644
RyoheiHagimoto 0:0e0631af0305 2645 //!@{
RyoheiHagimoto 0:0e0631af0305 2646 /*!
RyoheiHagimoto 0:0e0631af0305 2647 specialized variants for 1D, 2D, 3D cases and the generic_type one for n-D case.
RyoheiHagimoto 0:0e0631af0305 2648 return pointer to the matrix element.
RyoheiHagimoto 0:0e0631af0305 2649 - if the element is there (it's non-zero), the pointer to it is returned
RyoheiHagimoto 0:0e0631af0305 2650 - if it's not there and createMissing=false, NULL pointer is returned
RyoheiHagimoto 0:0e0631af0305 2651 - if it's not there and createMissing=true, then the new element
RyoheiHagimoto 0:0e0631af0305 2652 is created and initialized with 0. Pointer to it is returned
RyoheiHagimoto 0:0e0631af0305 2653 - if the optional hashval pointer is not NULL, the element hash value is
RyoheiHagimoto 0:0e0631af0305 2654 not computed, but *hashval is taken instead.
RyoheiHagimoto 0:0e0631af0305 2655 */
RyoheiHagimoto 0:0e0631af0305 2656 //! returns pointer to the specified element (1D case)
RyoheiHagimoto 0:0e0631af0305 2657 uchar* ptr(int i0, bool createMissing, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2658 //! returns pointer to the specified element (2D case)
RyoheiHagimoto 0:0e0631af0305 2659 uchar* ptr(int i0, int i1, bool createMissing, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2660 //! returns pointer to the specified element (3D case)
RyoheiHagimoto 0:0e0631af0305 2661 uchar* ptr(int i0, int i1, int i2, bool createMissing, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2662 //! returns pointer to the specified element (nD case)
RyoheiHagimoto 0:0e0631af0305 2663 uchar* ptr(const int* idx, bool createMissing, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2664 //!@}
RyoheiHagimoto 0:0e0631af0305 2665
RyoheiHagimoto 0:0e0631af0305 2666 //!@{
RyoheiHagimoto 0:0e0631af0305 2667 /*!
RyoheiHagimoto 0:0e0631af0305 2668 return read-write reference to the specified sparse matrix element.
RyoheiHagimoto 0:0e0631af0305 2669
RyoheiHagimoto 0:0e0631af0305 2670 `ref<_Tp>(i0,...[,hashval])` is equivalent to `*(_Tp*)ptr(i0,...,true[,hashval])`.
RyoheiHagimoto 0:0e0631af0305 2671 The methods always return a valid reference.
RyoheiHagimoto 0:0e0631af0305 2672 If the element did not exist, it is created and initialiazed with 0.
RyoheiHagimoto 0:0e0631af0305 2673 */
RyoheiHagimoto 0:0e0631af0305 2674 //! returns reference to the specified element (1D case)
RyoheiHagimoto 0:0e0631af0305 2675 template<typename _Tp> _Tp& ref(int i0, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2676 //! returns reference to the specified element (2D case)
RyoheiHagimoto 0:0e0631af0305 2677 template<typename _Tp> _Tp& ref(int i0, int i1, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2678 //! returns reference to the specified element (3D case)
RyoheiHagimoto 0:0e0631af0305 2679 template<typename _Tp> _Tp& ref(int i0, int i1, int i2, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2680 //! returns reference to the specified element (nD case)
RyoheiHagimoto 0:0e0631af0305 2681 template<typename _Tp> _Tp& ref(const int* idx, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2682 //!@}
RyoheiHagimoto 0:0e0631af0305 2683
RyoheiHagimoto 0:0e0631af0305 2684 //!@{
RyoheiHagimoto 0:0e0631af0305 2685 /*!
RyoheiHagimoto 0:0e0631af0305 2686 return value of the specified sparse matrix element.
RyoheiHagimoto 0:0e0631af0305 2687
RyoheiHagimoto 0:0e0631af0305 2688 `value<_Tp>(i0,...[,hashval])` is equivalent to
RyoheiHagimoto 0:0e0631af0305 2689 @code
RyoheiHagimoto 0:0e0631af0305 2690 { const _Tp* p = find<_Tp>(i0,...[,hashval]); return p ? *p : _Tp(); }
RyoheiHagimoto 0:0e0631af0305 2691 @endcode
RyoheiHagimoto 0:0e0631af0305 2692
RyoheiHagimoto 0:0e0631af0305 2693 That is, if the element did not exist, the methods return 0.
RyoheiHagimoto 0:0e0631af0305 2694 */
RyoheiHagimoto 0:0e0631af0305 2695 //! returns value of the specified element (1D case)
RyoheiHagimoto 0:0e0631af0305 2696 template<typename _Tp> _Tp value(int i0, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2697 //! returns value of the specified element (2D case)
RyoheiHagimoto 0:0e0631af0305 2698 template<typename _Tp> _Tp value(int i0, int i1, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2699 //! returns value of the specified element (3D case)
RyoheiHagimoto 0:0e0631af0305 2700 template<typename _Tp> _Tp value(int i0, int i1, int i2, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2701 //! returns value of the specified element (nD case)
RyoheiHagimoto 0:0e0631af0305 2702 template<typename _Tp> _Tp value(const int* idx, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2703 //!@}
RyoheiHagimoto 0:0e0631af0305 2704
RyoheiHagimoto 0:0e0631af0305 2705 //!@{
RyoheiHagimoto 0:0e0631af0305 2706 /*!
RyoheiHagimoto 0:0e0631af0305 2707 Return pointer to the specified sparse matrix element if it exists
RyoheiHagimoto 0:0e0631af0305 2708
RyoheiHagimoto 0:0e0631af0305 2709 `find<_Tp>(i0,...[,hashval])` is equivalent to `(_const Tp*)ptr(i0,...false[,hashval])`.
RyoheiHagimoto 0:0e0631af0305 2710
RyoheiHagimoto 0:0e0631af0305 2711 If the specified element does not exist, the methods return NULL.
RyoheiHagimoto 0:0e0631af0305 2712 */
RyoheiHagimoto 0:0e0631af0305 2713 //! returns pointer to the specified element (1D case)
RyoheiHagimoto 0:0e0631af0305 2714 template<typename _Tp> const _Tp* find(int i0, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2715 //! returns pointer to the specified element (2D case)
RyoheiHagimoto 0:0e0631af0305 2716 template<typename _Tp> const _Tp* find(int i0, int i1, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2717 //! returns pointer to the specified element (3D case)
RyoheiHagimoto 0:0e0631af0305 2718 template<typename _Tp> const _Tp* find(int i0, int i1, int i2, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2719 //! returns pointer to the specified element (nD case)
RyoheiHagimoto 0:0e0631af0305 2720 template<typename _Tp> const _Tp* find(const int* idx, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2721 //!@}
RyoheiHagimoto 0:0e0631af0305 2722
RyoheiHagimoto 0:0e0631af0305 2723 //! erases the specified element (2D case)
RyoheiHagimoto 0:0e0631af0305 2724 void erase(int i0, int i1, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2725 //! erases the specified element (3D case)
RyoheiHagimoto 0:0e0631af0305 2726 void erase(int i0, int i1, int i2, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2727 //! erases the specified element (nD case)
RyoheiHagimoto 0:0e0631af0305 2728 void erase(const int* idx, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2729
RyoheiHagimoto 0:0e0631af0305 2730 //!@{
RyoheiHagimoto 0:0e0631af0305 2731 /*!
RyoheiHagimoto 0:0e0631af0305 2732 return the sparse matrix iterator pointing to the first sparse matrix element
RyoheiHagimoto 0:0e0631af0305 2733 */
RyoheiHagimoto 0:0e0631af0305 2734 //! returns the sparse matrix iterator at the matrix beginning
RyoheiHagimoto 0:0e0631af0305 2735 SparseMatIterator begin();
RyoheiHagimoto 0:0e0631af0305 2736 //! returns the sparse matrix iterator at the matrix beginning
RyoheiHagimoto 0:0e0631af0305 2737 template<typename _Tp> SparseMatIterator_<_Tp> begin();
RyoheiHagimoto 0:0e0631af0305 2738 //! returns the read-only sparse matrix iterator at the matrix beginning
RyoheiHagimoto 0:0e0631af0305 2739 SparseMatConstIterator begin() const;
RyoheiHagimoto 0:0e0631af0305 2740 //! returns the read-only sparse matrix iterator at the matrix beginning
RyoheiHagimoto 0:0e0631af0305 2741 template<typename _Tp> SparseMatConstIterator_<_Tp> begin() const;
RyoheiHagimoto 0:0e0631af0305 2742 //!@}
RyoheiHagimoto 0:0e0631af0305 2743 /*!
RyoheiHagimoto 0:0e0631af0305 2744 return the sparse matrix iterator pointing to the element following the last sparse matrix element
RyoheiHagimoto 0:0e0631af0305 2745 */
RyoheiHagimoto 0:0e0631af0305 2746 //! returns the sparse matrix iterator at the matrix end
RyoheiHagimoto 0:0e0631af0305 2747 SparseMatIterator end();
RyoheiHagimoto 0:0e0631af0305 2748 //! returns the read-only sparse matrix iterator at the matrix end
RyoheiHagimoto 0:0e0631af0305 2749 SparseMatConstIterator end() const;
RyoheiHagimoto 0:0e0631af0305 2750 //! returns the typed sparse matrix iterator at the matrix end
RyoheiHagimoto 0:0e0631af0305 2751 template<typename _Tp> SparseMatIterator_<_Tp> end();
RyoheiHagimoto 0:0e0631af0305 2752 //! returns the typed read-only sparse matrix iterator at the matrix end
RyoheiHagimoto 0:0e0631af0305 2753 template<typename _Tp> SparseMatConstIterator_<_Tp> end() const;
RyoheiHagimoto 0:0e0631af0305 2754
RyoheiHagimoto 0:0e0631af0305 2755 //! returns the value stored in the sparse martix node
RyoheiHagimoto 0:0e0631af0305 2756 template<typename _Tp> _Tp& value(Node* n);
RyoheiHagimoto 0:0e0631af0305 2757 //! returns the value stored in the sparse martix node
RyoheiHagimoto 0:0e0631af0305 2758 template<typename _Tp> const _Tp& value(const Node* n) const;
RyoheiHagimoto 0:0e0631af0305 2759
RyoheiHagimoto 0:0e0631af0305 2760 ////////////// some internal-use methods ///////////////
RyoheiHagimoto 0:0e0631af0305 2761 Node* node(size_t nidx);
RyoheiHagimoto 0:0e0631af0305 2762 const Node* node(size_t nidx) const;
RyoheiHagimoto 0:0e0631af0305 2763
RyoheiHagimoto 0:0e0631af0305 2764 uchar* newNode(const int* idx, size_t hashval);
RyoheiHagimoto 0:0e0631af0305 2765 void removeNode(size_t hidx, size_t nidx, size_t previdx);
RyoheiHagimoto 0:0e0631af0305 2766 void resizeHashTab(size_t newsize);
RyoheiHagimoto 0:0e0631af0305 2767
RyoheiHagimoto 0:0e0631af0305 2768 int flags;
RyoheiHagimoto 0:0e0631af0305 2769 Hdr* hdr;
RyoheiHagimoto 0:0e0631af0305 2770 };
RyoheiHagimoto 0:0e0631af0305 2771
RyoheiHagimoto 0:0e0631af0305 2772
RyoheiHagimoto 0:0e0631af0305 2773
RyoheiHagimoto 0:0e0631af0305 2774 ///////////////////////////////// SparseMat_<_Tp> ////////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 2775
RyoheiHagimoto 0:0e0631af0305 2776 /** @brief Template sparse n-dimensional array class derived from SparseMat
RyoheiHagimoto 0:0e0631af0305 2777
RyoheiHagimoto 0:0e0631af0305 2778 SparseMat_ is a thin wrapper on top of SparseMat created in the same way as Mat_ . It simplifies
RyoheiHagimoto 0:0e0631af0305 2779 notation of some operations:
RyoheiHagimoto 0:0e0631af0305 2780 @code
RyoheiHagimoto 0:0e0631af0305 2781 int sz[] = {10, 20, 30};
RyoheiHagimoto 0:0e0631af0305 2782 SparseMat_<double> M(3, sz);
RyoheiHagimoto 0:0e0631af0305 2783 ...
RyoheiHagimoto 0:0e0631af0305 2784 M.ref(1, 2, 3) = M(4, 5, 6) + M(7, 8, 9);
RyoheiHagimoto 0:0e0631af0305 2785 @endcode
RyoheiHagimoto 0:0e0631af0305 2786 */
RyoheiHagimoto 0:0e0631af0305 2787 template<typename _Tp> class SparseMat_ : public SparseMat
RyoheiHagimoto 0:0e0631af0305 2788 {
RyoheiHagimoto 0:0e0631af0305 2789 public:
RyoheiHagimoto 0:0e0631af0305 2790 typedef SparseMatIterator_<_Tp> iterator;
RyoheiHagimoto 0:0e0631af0305 2791 typedef SparseMatConstIterator_<_Tp> const_iterator;
RyoheiHagimoto 0:0e0631af0305 2792
RyoheiHagimoto 0:0e0631af0305 2793 //! the default constructor
RyoheiHagimoto 0:0e0631af0305 2794 SparseMat_();
RyoheiHagimoto 0:0e0631af0305 2795 //! the full constructor equivelent to SparseMat(dims, _sizes, DataType<_Tp>::type)
RyoheiHagimoto 0:0e0631af0305 2796 SparseMat_(int dims, const int* _sizes);
RyoheiHagimoto 0:0e0631af0305 2797 //! the copy constructor. If DataType<_Tp>.type != m.type(), the m elements are converted
RyoheiHagimoto 0:0e0631af0305 2798 SparseMat_(const SparseMat& m);
RyoheiHagimoto 0:0e0631af0305 2799 //! the copy constructor. This is O(1) operation - no data is copied
RyoheiHagimoto 0:0e0631af0305 2800 SparseMat_(const SparseMat_& m);
RyoheiHagimoto 0:0e0631af0305 2801 //! converts dense matrix to the sparse form
RyoheiHagimoto 0:0e0631af0305 2802 SparseMat_(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 2803 //! converts the old-style sparse matrix to the C++ class. All the elements are copied
RyoheiHagimoto 0:0e0631af0305 2804 //SparseMat_(const CvSparseMat* m);
RyoheiHagimoto 0:0e0631af0305 2805 //! the assignment operator. If DataType<_Tp>.type != m.type(), the m elements are converted
RyoheiHagimoto 0:0e0631af0305 2806 SparseMat_& operator = (const SparseMat& m);
RyoheiHagimoto 0:0e0631af0305 2807 //! the assignment operator. This is O(1) operation - no data is copied
RyoheiHagimoto 0:0e0631af0305 2808 SparseMat_& operator = (const SparseMat_& m);
RyoheiHagimoto 0:0e0631af0305 2809 //! converts dense matrix to the sparse form
RyoheiHagimoto 0:0e0631af0305 2810 SparseMat_& operator = (const Mat& m);
RyoheiHagimoto 0:0e0631af0305 2811
RyoheiHagimoto 0:0e0631af0305 2812 //! makes full copy of the matrix. All the elements are duplicated
RyoheiHagimoto 0:0e0631af0305 2813 SparseMat_ clone() const;
RyoheiHagimoto 0:0e0631af0305 2814 //! equivalent to cv::SparseMat::create(dims, _sizes, DataType<_Tp>::type)
RyoheiHagimoto 0:0e0631af0305 2815 void create(int dims, const int* _sizes);
RyoheiHagimoto 0:0e0631af0305 2816 //! converts sparse matrix to the old-style CvSparseMat. All the elements are copied
RyoheiHagimoto 0:0e0631af0305 2817 //operator CvSparseMat*() const;
RyoheiHagimoto 0:0e0631af0305 2818
RyoheiHagimoto 0:0e0631af0305 2819 //! returns type of the matrix elements
RyoheiHagimoto 0:0e0631af0305 2820 int type() const;
RyoheiHagimoto 0:0e0631af0305 2821 //! returns depth of the matrix elements
RyoheiHagimoto 0:0e0631af0305 2822 int depth() const;
RyoheiHagimoto 0:0e0631af0305 2823 //! returns the number of channels in each matrix element
RyoheiHagimoto 0:0e0631af0305 2824 int channels() const;
RyoheiHagimoto 0:0e0631af0305 2825
RyoheiHagimoto 0:0e0631af0305 2826 //! equivalent to SparseMat::ref<_Tp>(i0, hashval)
RyoheiHagimoto 0:0e0631af0305 2827 _Tp& ref(int i0, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2828 //! equivalent to SparseMat::ref<_Tp>(i0, i1, hashval)
RyoheiHagimoto 0:0e0631af0305 2829 _Tp& ref(int i0, int i1, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2830 //! equivalent to SparseMat::ref<_Tp>(i0, i1, i2, hashval)
RyoheiHagimoto 0:0e0631af0305 2831 _Tp& ref(int i0, int i1, int i2, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2832 //! equivalent to SparseMat::ref<_Tp>(idx, hashval)
RyoheiHagimoto 0:0e0631af0305 2833 _Tp& ref(const int* idx, size_t* hashval=0);
RyoheiHagimoto 0:0e0631af0305 2834
RyoheiHagimoto 0:0e0631af0305 2835 //! equivalent to SparseMat::value<_Tp>(i0, hashval)
RyoheiHagimoto 0:0e0631af0305 2836 _Tp operator()(int i0, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2837 //! equivalent to SparseMat::value<_Tp>(i0, i1, hashval)
RyoheiHagimoto 0:0e0631af0305 2838 _Tp operator()(int i0, int i1, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2839 //! equivalent to SparseMat::value<_Tp>(i0, i1, i2, hashval)
RyoheiHagimoto 0:0e0631af0305 2840 _Tp operator()(int i0, int i1, int i2, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2841 //! equivalent to SparseMat::value<_Tp>(idx, hashval)
RyoheiHagimoto 0:0e0631af0305 2842 _Tp operator()(const int* idx, size_t* hashval=0) const;
RyoheiHagimoto 0:0e0631af0305 2843
RyoheiHagimoto 0:0e0631af0305 2844 //! returns sparse matrix iterator pointing to the first sparse matrix element
RyoheiHagimoto 0:0e0631af0305 2845 SparseMatIterator_<_Tp> begin();
RyoheiHagimoto 0:0e0631af0305 2846 //! returns read-only sparse matrix iterator pointing to the first sparse matrix element
RyoheiHagimoto 0:0e0631af0305 2847 SparseMatConstIterator_<_Tp> begin() const;
RyoheiHagimoto 0:0e0631af0305 2848 //! returns sparse matrix iterator pointing to the element following the last sparse matrix element
RyoheiHagimoto 0:0e0631af0305 2849 SparseMatIterator_<_Tp> end();
RyoheiHagimoto 0:0e0631af0305 2850 //! returns read-only sparse matrix iterator pointing to the element following the last sparse matrix element
RyoheiHagimoto 0:0e0631af0305 2851 SparseMatConstIterator_<_Tp> end() const;
RyoheiHagimoto 0:0e0631af0305 2852 };
RyoheiHagimoto 0:0e0631af0305 2853
RyoheiHagimoto 0:0e0631af0305 2854
RyoheiHagimoto 0:0e0631af0305 2855
RyoheiHagimoto 0:0e0631af0305 2856 ////////////////////////////////// MatConstIterator //////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 2857
RyoheiHagimoto 0:0e0631af0305 2858 class CV_EXPORTS MatConstIterator
RyoheiHagimoto 0:0e0631af0305 2859 {
RyoheiHagimoto 0:0e0631af0305 2860 public:
RyoheiHagimoto 0:0e0631af0305 2861 typedef uchar* value_type;
RyoheiHagimoto 0:0e0631af0305 2862 typedef ptrdiff_t difference_type;
RyoheiHagimoto 0:0e0631af0305 2863 typedef const uchar** pointer;
RyoheiHagimoto 0:0e0631af0305 2864 typedef uchar* reference;
RyoheiHagimoto 0:0e0631af0305 2865
RyoheiHagimoto 0:0e0631af0305 2866 #ifndef OPENCV_NOSTL
RyoheiHagimoto 0:0e0631af0305 2867 typedef std::random_access_iterator_tag iterator_category;
RyoheiHagimoto 0:0e0631af0305 2868 #endif
RyoheiHagimoto 0:0e0631af0305 2869
RyoheiHagimoto 0:0e0631af0305 2870 //! default constructor
RyoheiHagimoto 0:0e0631af0305 2871 MatConstIterator();
RyoheiHagimoto 0:0e0631af0305 2872 //! constructor that sets the iterator to the beginning of the matrix
RyoheiHagimoto 0:0e0631af0305 2873 MatConstIterator(const Mat* _m);
RyoheiHagimoto 0:0e0631af0305 2874 //! constructor that sets the iterator to the specified element of the matrix
RyoheiHagimoto 0:0e0631af0305 2875 MatConstIterator(const Mat* _m, int _row, int _col=0);
RyoheiHagimoto 0:0e0631af0305 2876 //! constructor that sets the iterator to the specified element of the matrix
RyoheiHagimoto 0:0e0631af0305 2877 MatConstIterator(const Mat* _m, Point _pt);
RyoheiHagimoto 0:0e0631af0305 2878 //! constructor that sets the iterator to the specified element of the matrix
RyoheiHagimoto 0:0e0631af0305 2879 MatConstIterator(const Mat* _m, const int* _idx);
RyoheiHagimoto 0:0e0631af0305 2880 //! copy constructor
RyoheiHagimoto 0:0e0631af0305 2881 MatConstIterator(const MatConstIterator& it);
RyoheiHagimoto 0:0e0631af0305 2882
RyoheiHagimoto 0:0e0631af0305 2883 //! copy operator
RyoheiHagimoto 0:0e0631af0305 2884 MatConstIterator& operator = (const MatConstIterator& it);
RyoheiHagimoto 0:0e0631af0305 2885 //! returns the current matrix element
RyoheiHagimoto 0:0e0631af0305 2886 const uchar* operator *() const;
RyoheiHagimoto 0:0e0631af0305 2887 //! returns the i-th matrix element, relative to the current
RyoheiHagimoto 0:0e0631af0305 2888 const uchar* operator [](ptrdiff_t i) const;
RyoheiHagimoto 0:0e0631af0305 2889
RyoheiHagimoto 0:0e0631af0305 2890 //! shifts the iterator forward by the specified number of elements
RyoheiHagimoto 0:0e0631af0305 2891 MatConstIterator& operator += (ptrdiff_t ofs);
RyoheiHagimoto 0:0e0631af0305 2892 //! shifts the iterator backward by the specified number of elements
RyoheiHagimoto 0:0e0631af0305 2893 MatConstIterator& operator -= (ptrdiff_t ofs);
RyoheiHagimoto 0:0e0631af0305 2894 //! decrements the iterator
RyoheiHagimoto 0:0e0631af0305 2895 MatConstIterator& operator --();
RyoheiHagimoto 0:0e0631af0305 2896 //! decrements the iterator
RyoheiHagimoto 0:0e0631af0305 2897 MatConstIterator operator --(int);
RyoheiHagimoto 0:0e0631af0305 2898 //! increments the iterator
RyoheiHagimoto 0:0e0631af0305 2899 MatConstIterator& operator ++();
RyoheiHagimoto 0:0e0631af0305 2900 //! increments the iterator
RyoheiHagimoto 0:0e0631af0305 2901 MatConstIterator operator ++(int);
RyoheiHagimoto 0:0e0631af0305 2902 //! returns the current iterator position
RyoheiHagimoto 0:0e0631af0305 2903 Point pos() const;
RyoheiHagimoto 0:0e0631af0305 2904 //! returns the current iterator position
RyoheiHagimoto 0:0e0631af0305 2905 void pos(int* _idx) const;
RyoheiHagimoto 0:0e0631af0305 2906
RyoheiHagimoto 0:0e0631af0305 2907 ptrdiff_t lpos() const;
RyoheiHagimoto 0:0e0631af0305 2908 void seek(ptrdiff_t ofs, bool relative = false);
RyoheiHagimoto 0:0e0631af0305 2909 void seek(const int* _idx, bool relative = false);
RyoheiHagimoto 0:0e0631af0305 2910
RyoheiHagimoto 0:0e0631af0305 2911 const Mat* m;
RyoheiHagimoto 0:0e0631af0305 2912 size_t elemSize;
RyoheiHagimoto 0:0e0631af0305 2913 const uchar* ptr;
RyoheiHagimoto 0:0e0631af0305 2914 const uchar* sliceStart;
RyoheiHagimoto 0:0e0631af0305 2915 const uchar* sliceEnd;
RyoheiHagimoto 0:0e0631af0305 2916 };
RyoheiHagimoto 0:0e0631af0305 2917
RyoheiHagimoto 0:0e0631af0305 2918
RyoheiHagimoto 0:0e0631af0305 2919
RyoheiHagimoto 0:0e0631af0305 2920 ////////////////////////////////// MatConstIterator_ /////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 2921
RyoheiHagimoto 0:0e0631af0305 2922 /** @brief Matrix read-only iterator
RyoheiHagimoto 0:0e0631af0305 2923 */
RyoheiHagimoto 0:0e0631af0305 2924 template<typename _Tp>
RyoheiHagimoto 0:0e0631af0305 2925 class MatConstIterator_ : public MatConstIterator
RyoheiHagimoto 0:0e0631af0305 2926 {
RyoheiHagimoto 0:0e0631af0305 2927 public:
RyoheiHagimoto 0:0e0631af0305 2928 typedef _Tp value_type;
RyoheiHagimoto 0:0e0631af0305 2929 typedef ptrdiff_t difference_type;
RyoheiHagimoto 0:0e0631af0305 2930 typedef const _Tp* pointer;
RyoheiHagimoto 0:0e0631af0305 2931 typedef const _Tp& reference;
RyoheiHagimoto 0:0e0631af0305 2932
RyoheiHagimoto 0:0e0631af0305 2933 #ifndef OPENCV_NOSTL
RyoheiHagimoto 0:0e0631af0305 2934 typedef std::random_access_iterator_tag iterator_category;
RyoheiHagimoto 0:0e0631af0305 2935 #endif
RyoheiHagimoto 0:0e0631af0305 2936
RyoheiHagimoto 0:0e0631af0305 2937 //! default constructor
RyoheiHagimoto 0:0e0631af0305 2938 MatConstIterator_();
RyoheiHagimoto 0:0e0631af0305 2939 //! constructor that sets the iterator to the beginning of the matrix
RyoheiHagimoto 0:0e0631af0305 2940 MatConstIterator_(const Mat_<_Tp>* _m);
RyoheiHagimoto 0:0e0631af0305 2941 //! constructor that sets the iterator to the specified element of the matrix
RyoheiHagimoto 0:0e0631af0305 2942 MatConstIterator_(const Mat_<_Tp>* _m, int _row, int _col=0);
RyoheiHagimoto 0:0e0631af0305 2943 //! constructor that sets the iterator to the specified element of the matrix
RyoheiHagimoto 0:0e0631af0305 2944 MatConstIterator_(const Mat_<_Tp>* _m, Point _pt);
RyoheiHagimoto 0:0e0631af0305 2945 //! constructor that sets the iterator to the specified element of the matrix
RyoheiHagimoto 0:0e0631af0305 2946 MatConstIterator_(const Mat_<_Tp>* _m, const int* _idx);
RyoheiHagimoto 0:0e0631af0305 2947 //! copy constructor
RyoheiHagimoto 0:0e0631af0305 2948 MatConstIterator_(const MatConstIterator_& it);
RyoheiHagimoto 0:0e0631af0305 2949
RyoheiHagimoto 0:0e0631af0305 2950 //! copy operator
RyoheiHagimoto 0:0e0631af0305 2951 MatConstIterator_& operator = (const MatConstIterator_& it);
RyoheiHagimoto 0:0e0631af0305 2952 //! returns the current matrix element
RyoheiHagimoto 0:0e0631af0305 2953 const _Tp& operator *() const;
RyoheiHagimoto 0:0e0631af0305 2954 //! returns the i-th matrix element, relative to the current
RyoheiHagimoto 0:0e0631af0305 2955 const _Tp& operator [](ptrdiff_t i) const;
RyoheiHagimoto 0:0e0631af0305 2956
RyoheiHagimoto 0:0e0631af0305 2957 //! shifts the iterator forward by the specified number of elements
RyoheiHagimoto 0:0e0631af0305 2958 MatConstIterator_& operator += (ptrdiff_t ofs);
RyoheiHagimoto 0:0e0631af0305 2959 //! shifts the iterator backward by the specified number of elements
RyoheiHagimoto 0:0e0631af0305 2960 MatConstIterator_& operator -= (ptrdiff_t ofs);
RyoheiHagimoto 0:0e0631af0305 2961 //! decrements the iterator
RyoheiHagimoto 0:0e0631af0305 2962 MatConstIterator_& operator --();
RyoheiHagimoto 0:0e0631af0305 2963 //! decrements the iterator
RyoheiHagimoto 0:0e0631af0305 2964 MatConstIterator_ operator --(int);
RyoheiHagimoto 0:0e0631af0305 2965 //! increments the iterator
RyoheiHagimoto 0:0e0631af0305 2966 MatConstIterator_& operator ++();
RyoheiHagimoto 0:0e0631af0305 2967 //! increments the iterator
RyoheiHagimoto 0:0e0631af0305 2968 MatConstIterator_ operator ++(int);
RyoheiHagimoto 0:0e0631af0305 2969 //! returns the current iterator position
RyoheiHagimoto 0:0e0631af0305 2970 Point pos() const;
RyoheiHagimoto 0:0e0631af0305 2971 };
RyoheiHagimoto 0:0e0631af0305 2972
RyoheiHagimoto 0:0e0631af0305 2973
RyoheiHagimoto 0:0e0631af0305 2974
RyoheiHagimoto 0:0e0631af0305 2975 //////////////////////////////////// MatIterator_ ////////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 2976
RyoheiHagimoto 0:0e0631af0305 2977 /** @brief Matrix read-write iterator
RyoheiHagimoto 0:0e0631af0305 2978 */
RyoheiHagimoto 0:0e0631af0305 2979 template<typename _Tp>
RyoheiHagimoto 0:0e0631af0305 2980 class MatIterator_ : public MatConstIterator_<_Tp>
RyoheiHagimoto 0:0e0631af0305 2981 {
RyoheiHagimoto 0:0e0631af0305 2982 public:
RyoheiHagimoto 0:0e0631af0305 2983 typedef _Tp* pointer;
RyoheiHagimoto 0:0e0631af0305 2984 typedef _Tp& reference;
RyoheiHagimoto 0:0e0631af0305 2985
RyoheiHagimoto 0:0e0631af0305 2986 #ifndef OPENCV_NOSTL
RyoheiHagimoto 0:0e0631af0305 2987 typedef std::random_access_iterator_tag iterator_category;
RyoheiHagimoto 0:0e0631af0305 2988 #endif
RyoheiHagimoto 0:0e0631af0305 2989
RyoheiHagimoto 0:0e0631af0305 2990 //! the default constructor
RyoheiHagimoto 0:0e0631af0305 2991 MatIterator_();
RyoheiHagimoto 0:0e0631af0305 2992 //! constructor that sets the iterator to the beginning of the matrix
RyoheiHagimoto 0:0e0631af0305 2993 MatIterator_(Mat_<_Tp>* _m);
RyoheiHagimoto 0:0e0631af0305 2994 //! constructor that sets the iterator to the specified element of the matrix
RyoheiHagimoto 0:0e0631af0305 2995 MatIterator_(Mat_<_Tp>* _m, int _row, int _col=0);
RyoheiHagimoto 0:0e0631af0305 2996 //! constructor that sets the iterator to the specified element of the matrix
RyoheiHagimoto 0:0e0631af0305 2997 MatIterator_(Mat_<_Tp>* _m, Point _pt);
RyoheiHagimoto 0:0e0631af0305 2998 //! constructor that sets the iterator to the specified element of the matrix
RyoheiHagimoto 0:0e0631af0305 2999 MatIterator_(Mat_<_Tp>* _m, const int* _idx);
RyoheiHagimoto 0:0e0631af0305 3000 //! copy constructor
RyoheiHagimoto 0:0e0631af0305 3001 MatIterator_(const MatIterator_& it);
RyoheiHagimoto 0:0e0631af0305 3002 //! copy operator
RyoheiHagimoto 0:0e0631af0305 3003 MatIterator_& operator = (const MatIterator_<_Tp>& it );
RyoheiHagimoto 0:0e0631af0305 3004
RyoheiHagimoto 0:0e0631af0305 3005 //! returns the current matrix element
RyoheiHagimoto 0:0e0631af0305 3006 _Tp& operator *() const;
RyoheiHagimoto 0:0e0631af0305 3007 //! returns the i-th matrix element, relative to the current
RyoheiHagimoto 0:0e0631af0305 3008 _Tp& operator [](ptrdiff_t i) const;
RyoheiHagimoto 0:0e0631af0305 3009
RyoheiHagimoto 0:0e0631af0305 3010 //! shifts the iterator forward by the specified number of elements
RyoheiHagimoto 0:0e0631af0305 3011 MatIterator_& operator += (ptrdiff_t ofs);
RyoheiHagimoto 0:0e0631af0305 3012 //! shifts the iterator backward by the specified number of elements
RyoheiHagimoto 0:0e0631af0305 3013 MatIterator_& operator -= (ptrdiff_t ofs);
RyoheiHagimoto 0:0e0631af0305 3014 //! decrements the iterator
RyoheiHagimoto 0:0e0631af0305 3015 MatIterator_& operator --();
RyoheiHagimoto 0:0e0631af0305 3016 //! decrements the iterator
RyoheiHagimoto 0:0e0631af0305 3017 MatIterator_ operator --(int);
RyoheiHagimoto 0:0e0631af0305 3018 //! increments the iterator
RyoheiHagimoto 0:0e0631af0305 3019 MatIterator_& operator ++();
RyoheiHagimoto 0:0e0631af0305 3020 //! increments the iterator
RyoheiHagimoto 0:0e0631af0305 3021 MatIterator_ operator ++(int);
RyoheiHagimoto 0:0e0631af0305 3022 };
RyoheiHagimoto 0:0e0631af0305 3023
RyoheiHagimoto 0:0e0631af0305 3024
RyoheiHagimoto 0:0e0631af0305 3025
RyoheiHagimoto 0:0e0631af0305 3026 /////////////////////////////// SparseMatConstIterator ///////////////////////////////
RyoheiHagimoto 0:0e0631af0305 3027
RyoheiHagimoto 0:0e0631af0305 3028 /** @brief Read-Only Sparse Matrix Iterator.
RyoheiHagimoto 0:0e0631af0305 3029
RyoheiHagimoto 0:0e0631af0305 3030 Here is how to use the iterator to compute the sum of floating-point sparse matrix elements:
RyoheiHagimoto 0:0e0631af0305 3031
RyoheiHagimoto 0:0e0631af0305 3032 \code
RyoheiHagimoto 0:0e0631af0305 3033 SparseMatConstIterator it = m.begin(), it_end = m.end();
RyoheiHagimoto 0:0e0631af0305 3034 double s = 0;
RyoheiHagimoto 0:0e0631af0305 3035 CV_Assert( m.type() == CV_32F );
RyoheiHagimoto 0:0e0631af0305 3036 for( ; it != it_end; ++it )
RyoheiHagimoto 0:0e0631af0305 3037 s += it.value<float>();
RyoheiHagimoto 0:0e0631af0305 3038 \endcode
RyoheiHagimoto 0:0e0631af0305 3039 */
RyoheiHagimoto 0:0e0631af0305 3040 class CV_EXPORTS SparseMatConstIterator
RyoheiHagimoto 0:0e0631af0305 3041 {
RyoheiHagimoto 0:0e0631af0305 3042 public:
RyoheiHagimoto 0:0e0631af0305 3043 //! the default constructor
RyoheiHagimoto 0:0e0631af0305 3044 SparseMatConstIterator();
RyoheiHagimoto 0:0e0631af0305 3045 //! the full constructor setting the iterator to the first sparse matrix element
RyoheiHagimoto 0:0e0631af0305 3046 SparseMatConstIterator(const SparseMat* _m);
RyoheiHagimoto 0:0e0631af0305 3047 //! the copy constructor
RyoheiHagimoto 0:0e0631af0305 3048 SparseMatConstIterator(const SparseMatConstIterator& it);
RyoheiHagimoto 0:0e0631af0305 3049
RyoheiHagimoto 0:0e0631af0305 3050 //! the assignment operator
RyoheiHagimoto 0:0e0631af0305 3051 SparseMatConstIterator& operator = (const SparseMatConstIterator& it);
RyoheiHagimoto 0:0e0631af0305 3052
RyoheiHagimoto 0:0e0631af0305 3053 //! template method returning the current matrix element
RyoheiHagimoto 0:0e0631af0305 3054 template<typename _Tp> const _Tp& value() const;
RyoheiHagimoto 0:0e0631af0305 3055 //! returns the current node of the sparse matrix. it.node->idx is the current element index
RyoheiHagimoto 0:0e0631af0305 3056 const SparseMat::Node* node() const;
RyoheiHagimoto 0:0e0631af0305 3057
RyoheiHagimoto 0:0e0631af0305 3058 //! moves iterator to the previous element
RyoheiHagimoto 0:0e0631af0305 3059 SparseMatConstIterator& operator --();
RyoheiHagimoto 0:0e0631af0305 3060 //! moves iterator to the previous element
RyoheiHagimoto 0:0e0631af0305 3061 SparseMatConstIterator operator --(int);
RyoheiHagimoto 0:0e0631af0305 3062 //! moves iterator to the next element
RyoheiHagimoto 0:0e0631af0305 3063 SparseMatConstIterator& operator ++();
RyoheiHagimoto 0:0e0631af0305 3064 //! moves iterator to the next element
RyoheiHagimoto 0:0e0631af0305 3065 SparseMatConstIterator operator ++(int);
RyoheiHagimoto 0:0e0631af0305 3066
RyoheiHagimoto 0:0e0631af0305 3067 //! moves iterator to the element after the last element
RyoheiHagimoto 0:0e0631af0305 3068 void seekEnd();
RyoheiHagimoto 0:0e0631af0305 3069
RyoheiHagimoto 0:0e0631af0305 3070 const SparseMat* m;
RyoheiHagimoto 0:0e0631af0305 3071 size_t hashidx;
RyoheiHagimoto 0:0e0631af0305 3072 uchar* ptr;
RyoheiHagimoto 0:0e0631af0305 3073 };
RyoheiHagimoto 0:0e0631af0305 3074
RyoheiHagimoto 0:0e0631af0305 3075
RyoheiHagimoto 0:0e0631af0305 3076
RyoheiHagimoto 0:0e0631af0305 3077 ////////////////////////////////// SparseMatIterator /////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 3078
RyoheiHagimoto 0:0e0631af0305 3079 /** @brief Read-write Sparse Matrix Iterator
RyoheiHagimoto 0:0e0631af0305 3080
RyoheiHagimoto 0:0e0631af0305 3081 The class is similar to cv::SparseMatConstIterator,
RyoheiHagimoto 0:0e0631af0305 3082 but can be used for in-place modification of the matrix elements.
RyoheiHagimoto 0:0e0631af0305 3083 */
RyoheiHagimoto 0:0e0631af0305 3084 class CV_EXPORTS SparseMatIterator : public SparseMatConstIterator
RyoheiHagimoto 0:0e0631af0305 3085 {
RyoheiHagimoto 0:0e0631af0305 3086 public:
RyoheiHagimoto 0:0e0631af0305 3087 //! the default constructor
RyoheiHagimoto 0:0e0631af0305 3088 SparseMatIterator();
RyoheiHagimoto 0:0e0631af0305 3089 //! the full constructor setting the iterator to the first sparse matrix element
RyoheiHagimoto 0:0e0631af0305 3090 SparseMatIterator(SparseMat* _m);
RyoheiHagimoto 0:0e0631af0305 3091 //! the full constructor setting the iterator to the specified sparse matrix element
RyoheiHagimoto 0:0e0631af0305 3092 SparseMatIterator(SparseMat* _m, const int* idx);
RyoheiHagimoto 0:0e0631af0305 3093 //! the copy constructor
RyoheiHagimoto 0:0e0631af0305 3094 SparseMatIterator(const SparseMatIterator& it);
RyoheiHagimoto 0:0e0631af0305 3095
RyoheiHagimoto 0:0e0631af0305 3096 //! the assignment operator
RyoheiHagimoto 0:0e0631af0305 3097 SparseMatIterator& operator = (const SparseMatIterator& it);
RyoheiHagimoto 0:0e0631af0305 3098 //! returns read-write reference to the current sparse matrix element
RyoheiHagimoto 0:0e0631af0305 3099 template<typename _Tp> _Tp& value() const;
RyoheiHagimoto 0:0e0631af0305 3100 //! returns pointer to the current sparse matrix node. it.node->idx is the index of the current element (do not modify it!)
RyoheiHagimoto 0:0e0631af0305 3101 SparseMat::Node* node() const;
RyoheiHagimoto 0:0e0631af0305 3102
RyoheiHagimoto 0:0e0631af0305 3103 //! moves iterator to the next element
RyoheiHagimoto 0:0e0631af0305 3104 SparseMatIterator& operator ++();
RyoheiHagimoto 0:0e0631af0305 3105 //! moves iterator to the next element
RyoheiHagimoto 0:0e0631af0305 3106 SparseMatIterator operator ++(int);
RyoheiHagimoto 0:0e0631af0305 3107 };
RyoheiHagimoto 0:0e0631af0305 3108
RyoheiHagimoto 0:0e0631af0305 3109
RyoheiHagimoto 0:0e0631af0305 3110
RyoheiHagimoto 0:0e0631af0305 3111 /////////////////////////////// SparseMatConstIterator_ //////////////////////////////
RyoheiHagimoto 0:0e0631af0305 3112
RyoheiHagimoto 0:0e0631af0305 3113 /** @brief Template Read-Only Sparse Matrix Iterator Class.
RyoheiHagimoto 0:0e0631af0305 3114
RyoheiHagimoto 0:0e0631af0305 3115 This is the derived from SparseMatConstIterator class that
RyoheiHagimoto 0:0e0631af0305 3116 introduces more convenient operator *() for accessing the current element.
RyoheiHagimoto 0:0e0631af0305 3117 */
RyoheiHagimoto 0:0e0631af0305 3118 template<typename _Tp> class SparseMatConstIterator_ : public SparseMatConstIterator
RyoheiHagimoto 0:0e0631af0305 3119 {
RyoheiHagimoto 0:0e0631af0305 3120 public:
RyoheiHagimoto 0:0e0631af0305 3121
RyoheiHagimoto 0:0e0631af0305 3122 #ifndef OPENCV_NOSTL
RyoheiHagimoto 0:0e0631af0305 3123 typedef std::forward_iterator_tag iterator_category;
RyoheiHagimoto 0:0e0631af0305 3124 #endif
RyoheiHagimoto 0:0e0631af0305 3125
RyoheiHagimoto 0:0e0631af0305 3126 //! the default constructor
RyoheiHagimoto 0:0e0631af0305 3127 SparseMatConstIterator_();
RyoheiHagimoto 0:0e0631af0305 3128 //! the full constructor setting the iterator to the first sparse matrix element
RyoheiHagimoto 0:0e0631af0305 3129 SparseMatConstIterator_(const SparseMat_<_Tp>* _m);
RyoheiHagimoto 0:0e0631af0305 3130 SparseMatConstIterator_(const SparseMat* _m);
RyoheiHagimoto 0:0e0631af0305 3131 //! the copy constructor
RyoheiHagimoto 0:0e0631af0305 3132 SparseMatConstIterator_(const SparseMatConstIterator_& it);
RyoheiHagimoto 0:0e0631af0305 3133
RyoheiHagimoto 0:0e0631af0305 3134 //! the assignment operator
RyoheiHagimoto 0:0e0631af0305 3135 SparseMatConstIterator_& operator = (const SparseMatConstIterator_& it);
RyoheiHagimoto 0:0e0631af0305 3136 //! the element access operator
RyoheiHagimoto 0:0e0631af0305 3137 const _Tp& operator *() const;
RyoheiHagimoto 0:0e0631af0305 3138
RyoheiHagimoto 0:0e0631af0305 3139 //! moves iterator to the next element
RyoheiHagimoto 0:0e0631af0305 3140 SparseMatConstIterator_& operator ++();
RyoheiHagimoto 0:0e0631af0305 3141 //! moves iterator to the next element
RyoheiHagimoto 0:0e0631af0305 3142 SparseMatConstIterator_ operator ++(int);
RyoheiHagimoto 0:0e0631af0305 3143 };
RyoheiHagimoto 0:0e0631af0305 3144
RyoheiHagimoto 0:0e0631af0305 3145
RyoheiHagimoto 0:0e0631af0305 3146
RyoheiHagimoto 0:0e0631af0305 3147 ///////////////////////////////// SparseMatIterator_ /////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 3148
RyoheiHagimoto 0:0e0631af0305 3149 /** @brief Template Read-Write Sparse Matrix Iterator Class.
RyoheiHagimoto 0:0e0631af0305 3150
RyoheiHagimoto 0:0e0631af0305 3151 This is the derived from cv::SparseMatConstIterator_ class that
RyoheiHagimoto 0:0e0631af0305 3152 introduces more convenient operator *() for accessing the current element.
RyoheiHagimoto 0:0e0631af0305 3153 */
RyoheiHagimoto 0:0e0631af0305 3154 template<typename _Tp> class SparseMatIterator_ : public SparseMatConstIterator_<_Tp>
RyoheiHagimoto 0:0e0631af0305 3155 {
RyoheiHagimoto 0:0e0631af0305 3156 public:
RyoheiHagimoto 0:0e0631af0305 3157
RyoheiHagimoto 0:0e0631af0305 3158 #ifndef OPENCV_NOSTL
RyoheiHagimoto 0:0e0631af0305 3159 typedef std::forward_iterator_tag iterator_category;
RyoheiHagimoto 0:0e0631af0305 3160 #endif
RyoheiHagimoto 0:0e0631af0305 3161
RyoheiHagimoto 0:0e0631af0305 3162 //! the default constructor
RyoheiHagimoto 0:0e0631af0305 3163 SparseMatIterator_();
RyoheiHagimoto 0:0e0631af0305 3164 //! the full constructor setting the iterator to the first sparse matrix element
RyoheiHagimoto 0:0e0631af0305 3165 SparseMatIterator_(SparseMat_<_Tp>* _m);
RyoheiHagimoto 0:0e0631af0305 3166 SparseMatIterator_(SparseMat* _m);
RyoheiHagimoto 0:0e0631af0305 3167 //! the copy constructor
RyoheiHagimoto 0:0e0631af0305 3168 SparseMatIterator_(const SparseMatIterator_& it);
RyoheiHagimoto 0:0e0631af0305 3169
RyoheiHagimoto 0:0e0631af0305 3170 //! the assignment operator
RyoheiHagimoto 0:0e0631af0305 3171 SparseMatIterator_& operator = (const SparseMatIterator_& it);
RyoheiHagimoto 0:0e0631af0305 3172 //! returns the reference to the current element
RyoheiHagimoto 0:0e0631af0305 3173 _Tp& operator *() const;
RyoheiHagimoto 0:0e0631af0305 3174
RyoheiHagimoto 0:0e0631af0305 3175 //! moves the iterator to the next element
RyoheiHagimoto 0:0e0631af0305 3176 SparseMatIterator_& operator ++();
RyoheiHagimoto 0:0e0631af0305 3177 //! moves the iterator to the next element
RyoheiHagimoto 0:0e0631af0305 3178 SparseMatIterator_ operator ++(int);
RyoheiHagimoto 0:0e0631af0305 3179 };
RyoheiHagimoto 0:0e0631af0305 3180
RyoheiHagimoto 0:0e0631af0305 3181
RyoheiHagimoto 0:0e0631af0305 3182
RyoheiHagimoto 0:0e0631af0305 3183 /////////////////////////////////// NAryMatIterator //////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 3184
RyoheiHagimoto 0:0e0631af0305 3185 /** @brief n-ary multi-dimensional array iterator.
RyoheiHagimoto 0:0e0631af0305 3186
RyoheiHagimoto 0:0e0631af0305 3187 Use the class to implement unary, binary, and, generally, n-ary element-wise operations on
RyoheiHagimoto 0:0e0631af0305 3188 multi-dimensional arrays. Some of the arguments of an n-ary function may be continuous arrays, some
RyoheiHagimoto 0:0e0631af0305 3189 may be not. It is possible to use conventional MatIterator 's for each array but incrementing all of
RyoheiHagimoto 0:0e0631af0305 3190 the iterators after each small operations may be a big overhead. In this case consider using
RyoheiHagimoto 0:0e0631af0305 3191 NAryMatIterator to iterate through several matrices simultaneously as long as they have the same
RyoheiHagimoto 0:0e0631af0305 3192 geometry (dimensionality and all the dimension sizes are the same). On each iteration `it.planes[0]`,
RyoheiHagimoto 0:0e0631af0305 3193 `it.planes[1]`,... will be the slices of the corresponding matrices.
RyoheiHagimoto 0:0e0631af0305 3194
RyoheiHagimoto 0:0e0631af0305 3195 The example below illustrates how you can compute a normalized and threshold 3D color histogram:
RyoheiHagimoto 0:0e0631af0305 3196 @code
RyoheiHagimoto 0:0e0631af0305 3197 void computeNormalizedColorHist(const Mat& image, Mat& hist, int N, double minProb)
RyoheiHagimoto 0:0e0631af0305 3198 {
RyoheiHagimoto 0:0e0631af0305 3199 const int histSize[] = {N, N, N};
RyoheiHagimoto 0:0e0631af0305 3200
RyoheiHagimoto 0:0e0631af0305 3201 // make sure that the histogram has a proper size and type
RyoheiHagimoto 0:0e0631af0305 3202 hist.create(3, histSize, CV_32F);
RyoheiHagimoto 0:0e0631af0305 3203
RyoheiHagimoto 0:0e0631af0305 3204 // and clear it
RyoheiHagimoto 0:0e0631af0305 3205 hist = Scalar(0);
RyoheiHagimoto 0:0e0631af0305 3206
RyoheiHagimoto 0:0e0631af0305 3207 // the loop below assumes that the image
RyoheiHagimoto 0:0e0631af0305 3208 // is a 8-bit 3-channel. check it.
RyoheiHagimoto 0:0e0631af0305 3209 CV_Assert(image.type() == CV_8UC3);
RyoheiHagimoto 0:0e0631af0305 3210 MatConstIterator_<Vec3b> it = image.begin<Vec3b>(),
RyoheiHagimoto 0:0e0631af0305 3211 it_end = image.end<Vec3b>();
RyoheiHagimoto 0:0e0631af0305 3212 for( ; it != it_end; ++it )
RyoheiHagimoto 0:0e0631af0305 3213 {
RyoheiHagimoto 0:0e0631af0305 3214 const Vec3b& pix = *it;
RyoheiHagimoto 0:0e0631af0305 3215 hist.at<float>(pix[0]*N/256, pix[1]*N/256, pix[2]*N/256) += 1.f;
RyoheiHagimoto 0:0e0631af0305 3216 }
RyoheiHagimoto 0:0e0631af0305 3217
RyoheiHagimoto 0:0e0631af0305 3218 minProb *= image.rows*image.cols;
RyoheiHagimoto 0:0e0631af0305 3219
RyoheiHagimoto 0:0e0631af0305 3220 // initialize iterator (the style is different from STL).
RyoheiHagimoto 0:0e0631af0305 3221 // after initialization the iterator will contain
RyoheiHagimoto 0:0e0631af0305 3222 // the number of slices or planes the iterator will go through.
RyoheiHagimoto 0:0e0631af0305 3223 // it simultaneously increments iterators for several matrices
RyoheiHagimoto 0:0e0631af0305 3224 // supplied as a null terminated list of pointers
RyoheiHagimoto 0:0e0631af0305 3225 const Mat* arrays[] = {&hist, 0};
RyoheiHagimoto 0:0e0631af0305 3226 Mat planes[1];
RyoheiHagimoto 0:0e0631af0305 3227 NAryMatIterator itNAry(arrays, planes, 1);
RyoheiHagimoto 0:0e0631af0305 3228 double s = 0;
RyoheiHagimoto 0:0e0631af0305 3229 // iterate through the matrix. on each iteration
RyoheiHagimoto 0:0e0631af0305 3230 // itNAry.planes[i] (of type Mat) will be set to the current plane
RyoheiHagimoto 0:0e0631af0305 3231 // of the i-th n-dim matrix passed to the iterator constructor.
RyoheiHagimoto 0:0e0631af0305 3232 for(int p = 0; p < itNAry.nplanes; p++, ++itNAry)
RyoheiHagimoto 0:0e0631af0305 3233 {
RyoheiHagimoto 0:0e0631af0305 3234 threshold(itNAry.planes[0], itNAry.planes[0], minProb, 0, THRESH_TOZERO);
RyoheiHagimoto 0:0e0631af0305 3235 s += sum(itNAry.planes[0])[0];
RyoheiHagimoto 0:0e0631af0305 3236 }
RyoheiHagimoto 0:0e0631af0305 3237
RyoheiHagimoto 0:0e0631af0305 3238 s = 1./s;
RyoheiHagimoto 0:0e0631af0305 3239 itNAry = NAryMatIterator(arrays, planes, 1);
RyoheiHagimoto 0:0e0631af0305 3240 for(int p = 0; p < itNAry.nplanes; p++, ++itNAry)
RyoheiHagimoto 0:0e0631af0305 3241 itNAry.planes[0] *= s;
RyoheiHagimoto 0:0e0631af0305 3242 }
RyoheiHagimoto 0:0e0631af0305 3243 @endcode
RyoheiHagimoto 0:0e0631af0305 3244 */
RyoheiHagimoto 0:0e0631af0305 3245 class CV_EXPORTS NAryMatIterator
RyoheiHagimoto 0:0e0631af0305 3246 {
RyoheiHagimoto 0:0e0631af0305 3247 public:
RyoheiHagimoto 0:0e0631af0305 3248 //! the default constructor
RyoheiHagimoto 0:0e0631af0305 3249 NAryMatIterator();
RyoheiHagimoto 0:0e0631af0305 3250 //! the full constructor taking arbitrary number of n-dim matrices
RyoheiHagimoto 0:0e0631af0305 3251 NAryMatIterator(const Mat** arrays, uchar** ptrs, int narrays=-1);
RyoheiHagimoto 0:0e0631af0305 3252 //! the full constructor taking arbitrary number of n-dim matrices
RyoheiHagimoto 0:0e0631af0305 3253 NAryMatIterator(const Mat** arrays, Mat* planes, int narrays=-1);
RyoheiHagimoto 0:0e0631af0305 3254 //! the separate iterator initialization method
RyoheiHagimoto 0:0e0631af0305 3255 void init(const Mat** arrays, Mat* planes, uchar** ptrs, int narrays=-1);
RyoheiHagimoto 0:0e0631af0305 3256
RyoheiHagimoto 0:0e0631af0305 3257 //! proceeds to the next plane of every iterated matrix
RyoheiHagimoto 0:0e0631af0305 3258 NAryMatIterator& operator ++();
RyoheiHagimoto 0:0e0631af0305 3259 //! proceeds to the next plane of every iterated matrix (postfix increment operator)
RyoheiHagimoto 0:0e0631af0305 3260 NAryMatIterator operator ++(int);
RyoheiHagimoto 0:0e0631af0305 3261
RyoheiHagimoto 0:0e0631af0305 3262 //! the iterated arrays
RyoheiHagimoto 0:0e0631af0305 3263 const Mat** arrays;
RyoheiHagimoto 0:0e0631af0305 3264 //! the current planes
RyoheiHagimoto 0:0e0631af0305 3265 Mat* planes;
RyoheiHagimoto 0:0e0631af0305 3266 //! data pointers
RyoheiHagimoto 0:0e0631af0305 3267 uchar** ptrs;
RyoheiHagimoto 0:0e0631af0305 3268 //! the number of arrays
RyoheiHagimoto 0:0e0631af0305 3269 int narrays;
RyoheiHagimoto 0:0e0631af0305 3270 //! the number of hyper-planes that the iterator steps through
RyoheiHagimoto 0:0e0631af0305 3271 size_t nplanes;
RyoheiHagimoto 0:0e0631af0305 3272 //! the size of each segment (in elements)
RyoheiHagimoto 0:0e0631af0305 3273 size_t size;
RyoheiHagimoto 0:0e0631af0305 3274 protected:
RyoheiHagimoto 0:0e0631af0305 3275 int iterdepth;
RyoheiHagimoto 0:0e0631af0305 3276 size_t idx;
RyoheiHagimoto 0:0e0631af0305 3277 };
RyoheiHagimoto 0:0e0631af0305 3278
RyoheiHagimoto 0:0e0631af0305 3279
RyoheiHagimoto 0:0e0631af0305 3280
RyoheiHagimoto 0:0e0631af0305 3281 ///////////////////////////////// Matrix Expressions /////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 3282
RyoheiHagimoto 0:0e0631af0305 3283 class CV_EXPORTS MatOp
RyoheiHagimoto 0:0e0631af0305 3284 {
RyoheiHagimoto 0:0e0631af0305 3285 public:
RyoheiHagimoto 0:0e0631af0305 3286 MatOp();
RyoheiHagimoto 0:0e0631af0305 3287 virtual ~MatOp();
RyoheiHagimoto 0:0e0631af0305 3288
RyoheiHagimoto 0:0e0631af0305 3289 virtual bool elementWise(const MatExpr& expr) const;
RyoheiHagimoto 0:0e0631af0305 3290 virtual void assign(const MatExpr& expr, Mat& m, int type=-1) const = 0;
RyoheiHagimoto 0:0e0631af0305 3291 virtual void roi(const MatExpr& expr, const Range& rowRange,
RyoheiHagimoto 0:0e0631af0305 3292 const Range& colRange, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3293 virtual void diag(const MatExpr& expr, int d, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3294 virtual void augAssignAdd(const MatExpr& expr, Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 3295 virtual void augAssignSubtract(const MatExpr& expr, Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 3296 virtual void augAssignMultiply(const MatExpr& expr, Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 3297 virtual void augAssignDivide(const MatExpr& expr, Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 3298 virtual void augAssignAnd(const MatExpr& expr, Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 3299 virtual void augAssignOr(const MatExpr& expr, Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 3300 virtual void augAssignXor(const MatExpr& expr, Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 3301
RyoheiHagimoto 0:0e0631af0305 3302 virtual void add(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3303 virtual void add(const MatExpr& expr1, const Scalar& s, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3304
RyoheiHagimoto 0:0e0631af0305 3305 virtual void subtract(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3306 virtual void subtract(const Scalar& s, const MatExpr& expr, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3307
RyoheiHagimoto 0:0e0631af0305 3308 virtual void multiply(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res, double scale=1) const;
RyoheiHagimoto 0:0e0631af0305 3309 virtual void multiply(const MatExpr& expr1, double s, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3310
RyoheiHagimoto 0:0e0631af0305 3311 virtual void divide(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res, double scale=1) const;
RyoheiHagimoto 0:0e0631af0305 3312 virtual void divide(double s, const MatExpr& expr, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3313
RyoheiHagimoto 0:0e0631af0305 3314 virtual void abs(const MatExpr& expr, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3315
RyoheiHagimoto 0:0e0631af0305 3316 virtual void transpose(const MatExpr& expr, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3317 virtual void matmul(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3318 virtual void invert(const MatExpr& expr, int method, MatExpr& res) const;
RyoheiHagimoto 0:0e0631af0305 3319
RyoheiHagimoto 0:0e0631af0305 3320 virtual Size size(const MatExpr& expr) const;
RyoheiHagimoto 0:0e0631af0305 3321 virtual int type(const MatExpr& expr) const;
RyoheiHagimoto 0:0e0631af0305 3322 };
RyoheiHagimoto 0:0e0631af0305 3323
RyoheiHagimoto 0:0e0631af0305 3324 /** @brief Matrix expression representation
RyoheiHagimoto 0:0e0631af0305 3325 @anchor MatrixExpressions
RyoheiHagimoto 0:0e0631af0305 3326 This is a list of implemented matrix operations that can be combined in arbitrary complex
RyoheiHagimoto 0:0e0631af0305 3327 expressions (here A, B stand for matrices ( Mat ), s for a scalar ( Scalar ), alpha for a
RyoheiHagimoto 0:0e0631af0305 3328 real-valued scalar ( double )):
RyoheiHagimoto 0:0e0631af0305 3329 - Addition, subtraction, negation: `A+B`, `A-B`, `A+s`, `A-s`, `s+A`, `s-A`, `-A`
RyoheiHagimoto 0:0e0631af0305 3330 - Scaling: `A*alpha`
RyoheiHagimoto 0:0e0631af0305 3331 - Per-element multiplication and division: `A.mul(B)`, `A/B`, `alpha/A`
RyoheiHagimoto 0:0e0631af0305 3332 - Matrix multiplication: `A*B`
RyoheiHagimoto 0:0e0631af0305 3333 - Transposition: `A.t()` (means A<sup>T</sup>)
RyoheiHagimoto 0:0e0631af0305 3334 - Matrix inversion and pseudo-inversion, solving linear systems and least-squares problems:
RyoheiHagimoto 0:0e0631af0305 3335 `A.inv([method]) (~ A<sup>-1</sup>)`, `A.inv([method])*B (~ X: AX=B)`
RyoheiHagimoto 0:0e0631af0305 3336 - Comparison: `A cmpop B`, `A cmpop alpha`, `alpha cmpop A`, where *cmpop* is one of
RyoheiHagimoto 0:0e0631af0305 3337 `>`, `>=`, `==`, `!=`, `<=`, `<`. The result of comparison is an 8-bit single channel mask whose
RyoheiHagimoto 0:0e0631af0305 3338 elements are set to 255 (if the particular element or pair of elements satisfy the condition) or
RyoheiHagimoto 0:0e0631af0305 3339 0.
RyoheiHagimoto 0:0e0631af0305 3340 - Bitwise logical operations: `A logicop B`, `A logicop s`, `s logicop A`, `~A`, where *logicop* is one of
RyoheiHagimoto 0:0e0631af0305 3341 `&`, `|`, `^`.
RyoheiHagimoto 0:0e0631af0305 3342 - Element-wise minimum and maximum: `min(A, B)`, `min(A, alpha)`, `max(A, B)`, `max(A, alpha)`
RyoheiHagimoto 0:0e0631af0305 3343 - Element-wise absolute value: `abs(A)`
RyoheiHagimoto 0:0e0631af0305 3344 - Cross-product, dot-product: `A.cross(B)`, `A.dot(B)`
RyoheiHagimoto 0:0e0631af0305 3345 - Any function of matrix or matrices and scalars that returns a matrix or a scalar, such as norm,
RyoheiHagimoto 0:0e0631af0305 3346 mean, sum, countNonZero, trace, determinant, repeat, and others.
RyoheiHagimoto 0:0e0631af0305 3347 - Matrix initializers ( Mat::eye(), Mat::zeros(), Mat::ones() ), matrix comma-separated
RyoheiHagimoto 0:0e0631af0305 3348 initializers, matrix constructors and operators that extract sub-matrices (see Mat description).
RyoheiHagimoto 0:0e0631af0305 3349 - Mat_<destination_type>() constructors to cast the result to the proper type.
RyoheiHagimoto 0:0e0631af0305 3350 @note Comma-separated initializers and probably some other operations may require additional
RyoheiHagimoto 0:0e0631af0305 3351 explicit Mat() or Mat_<T>() constructor calls to resolve a possible ambiguity.
RyoheiHagimoto 0:0e0631af0305 3352
RyoheiHagimoto 0:0e0631af0305 3353 Here are examples of matrix expressions:
RyoheiHagimoto 0:0e0631af0305 3354 @code
RyoheiHagimoto 0:0e0631af0305 3355 // compute pseudo-inverse of A, equivalent to A.inv(DECOMP_SVD)
RyoheiHagimoto 0:0e0631af0305 3356 SVD svd(A);
RyoheiHagimoto 0:0e0631af0305 3357 Mat pinvA = svd.vt.t()*Mat::diag(1./svd.w)*svd.u.t();
RyoheiHagimoto 0:0e0631af0305 3358
RyoheiHagimoto 0:0e0631af0305 3359 // compute the new vector of parameters in the Levenberg-Marquardt algorithm
RyoheiHagimoto 0:0e0631af0305 3360 x -= (A.t()*A + lambda*Mat::eye(A.cols,A.cols,A.type())).inv(DECOMP_CHOLESKY)*(A.t()*err);
RyoheiHagimoto 0:0e0631af0305 3361
RyoheiHagimoto 0:0e0631af0305 3362 // sharpen image using "unsharp mask" algorithm
RyoheiHagimoto 0:0e0631af0305 3363 Mat blurred; double sigma = 1, threshold = 5, amount = 1;
RyoheiHagimoto 0:0e0631af0305 3364 GaussianBlur(img, blurred, Size(), sigma, sigma);
RyoheiHagimoto 0:0e0631af0305 3365 Mat lowContrastMask = abs(img - blurred) < threshold;
RyoheiHagimoto 0:0e0631af0305 3366 Mat sharpened = img*(1+amount) + blurred*(-amount);
RyoheiHagimoto 0:0e0631af0305 3367 img.copyTo(sharpened, lowContrastMask);
RyoheiHagimoto 0:0e0631af0305 3368 @endcode
RyoheiHagimoto 0:0e0631af0305 3369 */
RyoheiHagimoto 0:0e0631af0305 3370 class CV_EXPORTS MatExpr
RyoheiHagimoto 0:0e0631af0305 3371 {
RyoheiHagimoto 0:0e0631af0305 3372 public:
RyoheiHagimoto 0:0e0631af0305 3373 MatExpr();
RyoheiHagimoto 0:0e0631af0305 3374 explicit MatExpr(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 3375
RyoheiHagimoto 0:0e0631af0305 3376 MatExpr(const MatOp* _op, int _flags, const Mat& _a = Mat(), const Mat& _b = Mat(),
RyoheiHagimoto 0:0e0631af0305 3377 const Mat& _c = Mat(), double _alpha = 1, double _beta = 1, const Scalar& _s = Scalar());
RyoheiHagimoto 0:0e0631af0305 3378
RyoheiHagimoto 0:0e0631af0305 3379 operator Mat() const;
RyoheiHagimoto 0:0e0631af0305 3380 template<typename _Tp> operator Mat_<_Tp>() const;
RyoheiHagimoto 0:0e0631af0305 3381
RyoheiHagimoto 0:0e0631af0305 3382 Size size() const;
RyoheiHagimoto 0:0e0631af0305 3383 int type() const;
RyoheiHagimoto 0:0e0631af0305 3384
RyoheiHagimoto 0:0e0631af0305 3385 MatExpr row(int y) const;
RyoheiHagimoto 0:0e0631af0305 3386 MatExpr col(int x) const;
RyoheiHagimoto 0:0e0631af0305 3387 MatExpr diag(int d = 0) const;
RyoheiHagimoto 0:0e0631af0305 3388 MatExpr operator()( const Range& rowRange, const Range& colRange ) const;
RyoheiHagimoto 0:0e0631af0305 3389 MatExpr operator()( const Rect& roi ) const;
RyoheiHagimoto 0:0e0631af0305 3390
RyoheiHagimoto 0:0e0631af0305 3391 MatExpr t() const;
RyoheiHagimoto 0:0e0631af0305 3392 MatExpr inv(int method = DECOMP_LU) const;
RyoheiHagimoto 0:0e0631af0305 3393 MatExpr mul(const MatExpr& e, double scale=1) const;
RyoheiHagimoto 0:0e0631af0305 3394 MatExpr mul(const Mat& m, double scale=1) const;
RyoheiHagimoto 0:0e0631af0305 3395
RyoheiHagimoto 0:0e0631af0305 3396 Mat cross(const Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 3397 double dot(const Mat& m) const;
RyoheiHagimoto 0:0e0631af0305 3398
RyoheiHagimoto 0:0e0631af0305 3399 const MatOp* op;
RyoheiHagimoto 0:0e0631af0305 3400 int flags;
RyoheiHagimoto 0:0e0631af0305 3401
RyoheiHagimoto 0:0e0631af0305 3402 Mat a, b, c;
RyoheiHagimoto 0:0e0631af0305 3403 double alpha, beta;
RyoheiHagimoto 0:0e0631af0305 3404 Scalar s;
RyoheiHagimoto 0:0e0631af0305 3405 };
RyoheiHagimoto 0:0e0631af0305 3406
RyoheiHagimoto 0:0e0631af0305 3407 //! @} core_basic
RyoheiHagimoto 0:0e0631af0305 3408
RyoheiHagimoto 0:0e0631af0305 3409 //! @relates cv::MatExpr
RyoheiHagimoto 0:0e0631af0305 3410 //! @{
RyoheiHagimoto 0:0e0631af0305 3411 CV_EXPORTS MatExpr operator + (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3412 CV_EXPORTS MatExpr operator + (const Mat& a, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 3413 CV_EXPORTS MatExpr operator + (const Scalar& s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3414 CV_EXPORTS MatExpr operator + (const MatExpr& e, const Mat& m);
RyoheiHagimoto 0:0e0631af0305 3415 CV_EXPORTS MatExpr operator + (const Mat& m, const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3416 CV_EXPORTS MatExpr operator + (const MatExpr& e, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 3417 CV_EXPORTS MatExpr operator + (const Scalar& s, const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3418 CV_EXPORTS MatExpr operator + (const MatExpr& e1, const MatExpr& e2);
RyoheiHagimoto 0:0e0631af0305 3419
RyoheiHagimoto 0:0e0631af0305 3420 CV_EXPORTS MatExpr operator - (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3421 CV_EXPORTS MatExpr operator - (const Mat& a, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 3422 CV_EXPORTS MatExpr operator - (const Scalar& s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3423 CV_EXPORTS MatExpr operator - (const MatExpr& e, const Mat& m);
RyoheiHagimoto 0:0e0631af0305 3424 CV_EXPORTS MatExpr operator - (const Mat& m, const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3425 CV_EXPORTS MatExpr operator - (const MatExpr& e, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 3426 CV_EXPORTS MatExpr operator - (const Scalar& s, const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3427 CV_EXPORTS MatExpr operator - (const MatExpr& e1, const MatExpr& e2);
RyoheiHagimoto 0:0e0631af0305 3428
RyoheiHagimoto 0:0e0631af0305 3429 CV_EXPORTS MatExpr operator - (const Mat& m);
RyoheiHagimoto 0:0e0631af0305 3430 CV_EXPORTS MatExpr operator - (const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3431
RyoheiHagimoto 0:0e0631af0305 3432 CV_EXPORTS MatExpr operator * (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3433 CV_EXPORTS MatExpr operator * (const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3434 CV_EXPORTS MatExpr operator * (double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3435 CV_EXPORTS MatExpr operator * (const MatExpr& e, const Mat& m);
RyoheiHagimoto 0:0e0631af0305 3436 CV_EXPORTS MatExpr operator * (const Mat& m, const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3437 CV_EXPORTS MatExpr operator * (const MatExpr& e, double s);
RyoheiHagimoto 0:0e0631af0305 3438 CV_EXPORTS MatExpr operator * (double s, const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3439 CV_EXPORTS MatExpr operator * (const MatExpr& e1, const MatExpr& e2);
RyoheiHagimoto 0:0e0631af0305 3440
RyoheiHagimoto 0:0e0631af0305 3441 CV_EXPORTS MatExpr operator / (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3442 CV_EXPORTS MatExpr operator / (const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3443 CV_EXPORTS MatExpr operator / (double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3444 CV_EXPORTS MatExpr operator / (const MatExpr& e, const Mat& m);
RyoheiHagimoto 0:0e0631af0305 3445 CV_EXPORTS MatExpr operator / (const Mat& m, const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3446 CV_EXPORTS MatExpr operator / (const MatExpr& e, double s);
RyoheiHagimoto 0:0e0631af0305 3447 CV_EXPORTS MatExpr operator / (double s, const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3448 CV_EXPORTS MatExpr operator / (const MatExpr& e1, const MatExpr& e2);
RyoheiHagimoto 0:0e0631af0305 3449
RyoheiHagimoto 0:0e0631af0305 3450 CV_EXPORTS MatExpr operator < (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3451 CV_EXPORTS MatExpr operator < (const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3452 CV_EXPORTS MatExpr operator < (double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3453
RyoheiHagimoto 0:0e0631af0305 3454 CV_EXPORTS MatExpr operator <= (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3455 CV_EXPORTS MatExpr operator <= (const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3456 CV_EXPORTS MatExpr operator <= (double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3457
RyoheiHagimoto 0:0e0631af0305 3458 CV_EXPORTS MatExpr operator == (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3459 CV_EXPORTS MatExpr operator == (const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3460 CV_EXPORTS MatExpr operator == (double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3461
RyoheiHagimoto 0:0e0631af0305 3462 CV_EXPORTS MatExpr operator != (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3463 CV_EXPORTS MatExpr operator != (const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3464 CV_EXPORTS MatExpr operator != (double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3465
RyoheiHagimoto 0:0e0631af0305 3466 CV_EXPORTS MatExpr operator >= (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3467 CV_EXPORTS MatExpr operator >= (const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3468 CV_EXPORTS MatExpr operator >= (double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3469
RyoheiHagimoto 0:0e0631af0305 3470 CV_EXPORTS MatExpr operator > (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3471 CV_EXPORTS MatExpr operator > (const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3472 CV_EXPORTS MatExpr operator > (double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3473
RyoheiHagimoto 0:0e0631af0305 3474 CV_EXPORTS MatExpr operator & (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3475 CV_EXPORTS MatExpr operator & (const Mat& a, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 3476 CV_EXPORTS MatExpr operator & (const Scalar& s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3477
RyoheiHagimoto 0:0e0631af0305 3478 CV_EXPORTS MatExpr operator | (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3479 CV_EXPORTS MatExpr operator | (const Mat& a, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 3480 CV_EXPORTS MatExpr operator | (const Scalar& s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3481
RyoheiHagimoto 0:0e0631af0305 3482 CV_EXPORTS MatExpr operator ^ (const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3483 CV_EXPORTS MatExpr operator ^ (const Mat& a, const Scalar& s);
RyoheiHagimoto 0:0e0631af0305 3484 CV_EXPORTS MatExpr operator ^ (const Scalar& s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3485
RyoheiHagimoto 0:0e0631af0305 3486 CV_EXPORTS MatExpr operator ~(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 3487
RyoheiHagimoto 0:0e0631af0305 3488 CV_EXPORTS MatExpr min(const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3489 CV_EXPORTS MatExpr min(const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3490 CV_EXPORTS MatExpr min(double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3491
RyoheiHagimoto 0:0e0631af0305 3492 CV_EXPORTS MatExpr max(const Mat& a, const Mat& b);
RyoheiHagimoto 0:0e0631af0305 3493 CV_EXPORTS MatExpr max(const Mat& a, double s);
RyoheiHagimoto 0:0e0631af0305 3494 CV_EXPORTS MatExpr max(double s, const Mat& a);
RyoheiHagimoto 0:0e0631af0305 3495
RyoheiHagimoto 0:0e0631af0305 3496 /** @brief Calculates an absolute value of each matrix element.
RyoheiHagimoto 0:0e0631af0305 3497
RyoheiHagimoto 0:0e0631af0305 3498 abs is a meta-function that is expanded to one of absdiff or convertScaleAbs forms:
RyoheiHagimoto 0:0e0631af0305 3499 - C = abs(A-B) is equivalent to `absdiff(A, B, C)`
RyoheiHagimoto 0:0e0631af0305 3500 - C = abs(A) is equivalent to `absdiff(A, Scalar::all(0), C)`
RyoheiHagimoto 0:0e0631af0305 3501 - C = `Mat_<Vec<uchar,n> >(abs(A*alpha + beta))` is equivalent to `convertScaleAbs(A, C, alpha,
RyoheiHagimoto 0:0e0631af0305 3502 beta)`
RyoheiHagimoto 0:0e0631af0305 3503
RyoheiHagimoto 0:0e0631af0305 3504 The output matrix has the same size and the same type as the input one except for the last case,
RyoheiHagimoto 0:0e0631af0305 3505 where C is depth=CV_8U .
RyoheiHagimoto 0:0e0631af0305 3506 @param m matrix.
RyoheiHagimoto 0:0e0631af0305 3507 @sa @ref MatrixExpressions, absdiff, convertScaleAbs
RyoheiHagimoto 0:0e0631af0305 3508 */
RyoheiHagimoto 0:0e0631af0305 3509 CV_EXPORTS MatExpr abs(const Mat& m);
RyoheiHagimoto 0:0e0631af0305 3510 /** @overload
RyoheiHagimoto 0:0e0631af0305 3511 @param e matrix expression.
RyoheiHagimoto 0:0e0631af0305 3512 */
RyoheiHagimoto 0:0e0631af0305 3513 CV_EXPORTS MatExpr abs(const MatExpr& e);
RyoheiHagimoto 0:0e0631af0305 3514 //! @} relates cv::MatExpr
RyoheiHagimoto 0:0e0631af0305 3515
RyoheiHagimoto 0:0e0631af0305 3516 } // cv
RyoheiHagimoto 0:0e0631af0305 3517
RyoheiHagimoto 0:0e0631af0305 3518 #include "opencv2/core/mat.inl.hpp"
RyoheiHagimoto 0:0e0631af0305 3519
RyoheiHagimoto 0:0e0631af0305 3520 #endif // OPENCV_CORE_MAT_HPP