DataType : Convert the C++ data type to the corresponding opencv data type
enum { CV_8U= 0 , CV_8S= 1 , CV_16U= 2 , CV_16S= 3 , CV_32S= 4 , CV_32F= 5 , CV_64F= 6 };
// allocates a 30x40 floating-point matrix // CV_32F Mat A(30, 40, DataType<float>::type); Mat B = Mat_<std::complex<double> >(3, 3); // the statement below will print 6, 2 /*, that is depth == CV_64F, channels == 2*/ CV_64FC2 cout << B.depth() << ", " << B.channels() << endl;
Point_2D point coordinates (x,y)
typedef Point_<int> Point2i; typedef Point2i Point; typedef Point_<float> Point2f; typedef Point_<double> Point2d;
Point3_ 3-dimensional point coordinates (x, y, z)
typedef Point3_<int> Point3i; typedef Point3_<float> Point3f; typedef Point3_<double> Point3d;
Size_size (width, height)
typedef Size_<int> Size2i; typedef Size2i Size; typedef Size_<float> Size2f;
Rect_rectangular area (x,y,width,height), (x,y) upper left corner coordinates, range [x, x + width), [y, y + height)
rect = rect ± point //矩形偏移(shifting a rectangle by a certain offset) rect = rect ± size //改变大小(expanding or shrinking a rectangle by a certain amount) rect += point, rect -= point, rect += size, rect -= size //(augmenting operations) rect = rect1 & rect2 //矩形交集(rectangle intersection) rect = rect1 | rect2 //包含r1r2的最小矩形(minimum area rectangle containing rect2 and rect3 ) rect &= rect1, rect |= rect1 //(and the corresponding augmenting operations) rect == rect1, rect != rect1 //(rectangle comparison)
RotatedRect rotated rectangle
RotatedRect::RotatedRect(const Point2f& center, const Size2f& size, float angle)// 中心点（不是左上角坐标），尺寸，旋转角度 RotatedRect rRect = RotatedRect(Point2f(100,100), Size2f(100,50), 30);
Matx 小矩阵
template<typename_Tp, int m, int n> class Matx {...}; typedef Matx<float, 1, 2> Matx12f; typedef Matx<double, 1, 2> Matx12d; ... typedef Matx<float, 1, 6> Matx16f; typedef Matx<double, 1, 6> Matx16d; typedef Matx<float, 2, 1> Matx21f; typedef Matx<double, 2, 1> Matx21d; ... typedef Matx<float, 6, 1> Matx61f; typedef Matx<double, 6, 1> Matx61d; typedef Matx<float, 2, 2> Matx22f; typedef Matx<double, 2, 2> Matx22d; ... typedef Matx<float, 6, 6> Matx66f; typedef Matx<double, 6, 6> Matx66d; Matx33f m(1, 2, 3, 4, 5, 6, 7, 8, 9); cout << sum(Mat(m*m.t())) << endl;//Matx转化为Mat
Vec 短向量，基于Matx
template<typename_Tp, int n> class Vec : public Matx<_Tp, n, 1> {...}; typedef Vec<uchar, 2> Vec2b; typedef Vec<uchar, 3> Vec3b; typedef Vec<uchar, 4> Vec4b; typedef Vec<short, 2> Vec2s; typedef Vec<short, 3> Vec3s; typedef Vec<short, 4> Vec4s; typedef Vec<int, 2> Vec2i; typedef Vec<int, 3> Vec3i; typedef Vec<int, 4> Vec4i; typedef Vec<float, 2> Vec2f; typedef Vec<float, 3> Vec3f; typedef Vec<float, 4> Vec4f; typedef Vec<float, 6> Vec6f; typedef Vec<double, 2> Vec2d; typedef Vec<double, 3> Vec3d; typedef Vec<double, 4> Vec4d; typedef Vec<double, 6> Vec6d;
Scalar_ 四维向量
template<typename_Tp> class Scalar_: public Vec<_Tp, 4> { ... }; typedef Scalar_<double> Scalar;
Range 范围，（start, end）
Mat m(300,300,CV32F); Mat part = m(Range::all(), Range(20, 200)); // 相当于matlab的m(:, 20 : 199)
对于自定义的函数，可以用如下方法来支持Range
void my_function(..., const Range& r, ....) { if(r == Range::all()) { // process all the data, 使用全部数据 } else { // process [r.start, r.end)，根据r中定义, 处理数据 start : end - 1 } }
Mat 矩阵结构
- M.data 数据区域的指针
- M.dims 矩阵维度
- M.sizes 维度
- M.elemSize() 每个元素占的字节空间大小，与元素类型相关，如CV_8U
- M.step[] 用来计算元素地址， M.step[i] 表示所有比i大的维度所占空间大小
M.step[i] >= M.step[i+1]*M.sizes[i+1]; //这里大于是因为数据空间可能有空白
- 2-dimensional matrices are stored row-by-row
- 3-dimensional matrices are stored plane-by-plane
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)
创建数组：
// make a 7x7 complex matrix filled with 1+3j. Mat M(7,7,CV_32FC2,Scalar(1,3)); // and now turn M to a 100x60 15-channel 8-bit matrix. // The old content will be deallocated M.create(100,60,CV_8UC(15)); // create a 100x100x100 8-bit array int sz[] = {100, 100, 100}; Mat bigCube(3, sz, CV_8U, Scalar::all(0));
创建特殊矩阵：
- diag
- ones
- zeros
- eye
属性相关：
- rows
- cols
- begin
- end
- at
- size
- depth
- type
- elemSize
- total
矩阵操作：
- t
- inv
- mul
- cross
- dot
- reshape
- resize
- reserve
- push_back
- pop_back
Assignment related:
- clone
- copyTo
- convertTo
- assignTo
- setTo