pub struct MatExpr { /* private fields */ }Expand description
Matrix expression representation @anchor MatrixExpressions This is a list of implemented matrix operations that can be combined in arbitrary complex expressions (here A, B stand for matrices ( Mat ), s for a scalar ( Scalar ), alpha for a real-valued scalar ( double )):
- Addition, subtraction, negation:
A+B,A-B,A+s,A-s,s+A,s-A,-A - Scaling:
A*alpha - Per-element multiplication and division:
A.mul(B),A/B,alpha/A - Matrix multiplication:
A*B - Transposition:
A.t()(means AT) - Matrix inversion and pseudo-inversion, solving linear systems and least-squares problems:
A.inv([method]) (~ A<sup>-1</sup>),A.inv([method])*B (~ X: AX=B) - Comparison:
A cmpop B,A cmpop alpha,alpha cmpop A, where cmpop is one of>,>=,==,!=,<=,<. The result of comparison is an 8-bit single channel mask whose elements are set to 255 (if the particular element or pair of elements satisfy the condition) or
- Bitwise logical operations:
A logicop B,A logicop s,s logicop A,~A, where logicop is one of&,|,^. - Element-wise minimum and maximum:
min(A, B),min(A, alpha),max(A, B),max(A, alpha) - Element-wise absolute value:
abs(A) - Cross-product, dot-product:
A.cross(B),A.dot(B) - Any function of matrix or matrices and scalars that returns a matrix or a scalar, such as norm, mean, sum, countNonZero, trace, determinant, repeat, and others.
- Matrix initializers ( Mat::eye(), Mat::zeros(), Mat::ones() ), matrix comma-separated initializers, matrix constructors and operators that extract sub-matrices (see Mat description).
- Mat_<destination_type>() constructors to cast the result to the proper type.
Note: Comma-separated initializers and probably some other operations may require additional
explicit Mat() or Mat_
Here are examples of matrix expressions:
// compute pseudo-inverse of A, equivalent to A.inv(DECOMP_SVD)
SVD svd(A);
Mat pinvA = svd.vt.t()*Mat::diag(1./svd.w)*svd.u.t();
// compute the new vector of parameters in the Levenberg-Marquardt algorithm
x -= (A.t()*A + lambda*Mat::eye(A.cols,A.cols,A.type())).inv(DECOMP_CHOLESKY)*(A.t()*err);
// sharpen image using "unsharp mask" algorithm
Mat blurred; double sigma = 1, threshold = 5, amount = 1;
GaussianBlur(img, blurred, Size(), sigma, sigma);
Mat lowContrastMask = abs(img - blurred) < threshold;
Mat sharpened = img*(1+amount) + blurred*(-amount);
img.copyTo(sharpened, lowContrastMask);
Implementations§
Trait Implementations§
source§impl Boxed for MatExpr
impl Boxed for MatExpr
source§impl ElemMul<MatExprResult<&Mat>> for &MatExpr
impl ElemMul<MatExprResult<&Mat>> for &MatExpr
type Output = MatExprResult<MatExpr>
fn elem_mul(self, rhs: MatExprResult<&Mat>) -> Self::Output
source§impl ElemMul<MatExprResult<&Mat>> for MatExpr
impl ElemMul<MatExprResult<&Mat>> for MatExpr
type Output = MatExprResult<MatExpr>
fn elem_mul(self, rhs: MatExprResult<&Mat>) -> Self::Output
source§impl ElemMul<MatExprResult<&MatExpr>> for &MatExpr
impl ElemMul<MatExprResult<&MatExpr>> for &MatExpr
type Output = MatExprResult<MatExpr>
fn elem_mul(self, rhs: MatExprResult<&MatExpr>) -> Self::Output
source§impl ElemMul<MatExprResult<&MatExpr>> for MatExpr
impl ElemMul<MatExprResult<&MatExpr>> for MatExpr
type Output = MatExprResult<MatExpr>
fn elem_mul(self, rhs: MatExprResult<&MatExpr>) -> Self::Output
source§impl ElemMul<MatExprResult<Mat>> for &MatExpr
impl ElemMul<MatExprResult<Mat>> for &MatExpr
type Output = MatExprResult<MatExpr>
fn elem_mul(self, rhs: MatExprResult<Mat>) -> Self::Output
source§impl ElemMul<MatExprResult<Mat>> for MatExpr
impl ElemMul<MatExprResult<Mat>> for MatExpr
type Output = MatExprResult<MatExpr>
fn elem_mul(self, rhs: MatExprResult<Mat>) -> Self::Output
source§impl ElemMul<MatExprResult<MatExpr>> for &MatExpr
impl ElemMul<MatExprResult<MatExpr>> for &MatExpr
type Output = MatExprResult<MatExpr>
fn elem_mul(self, rhs: MatExprResult<MatExpr>) -> Self::Output
source§impl ElemMul<MatExprResult<MatExpr>> for MatExpr
impl ElemMul<MatExprResult<MatExpr>> for MatExpr
type Output = MatExprResult<MatExpr>
fn elem_mul(self, rhs: MatExprResult<MatExpr>) -> Self::Output
source§impl MatExprTrait for MatExpr
impl MatExprTrait for MatExpr
fn as_raw_mut_MatExpr(&mut self) -> *mut c_void
fn set_flags(&mut self, val: i32)
fn set_a(&mut self, val: Mat)
fn set_b(&mut self, val: Mat)
fn set_c(&mut self, val: Mat)
fn set_alpha(&mut self, val: f64)
fn set_beta(&mut self, val: f64)
fn set_s(&mut self, val: Scalar)
fn swap(&mut self, b: &mut MatExpr) -> Result<()>
source§impl MatExprTraitConst for MatExpr
impl MatExprTraitConst for MatExpr
fn as_raw_MatExpr(&self) -> *const c_void
fn flags(&self) -> i32
fn a(&self) -> Mat
fn b(&self) -> Mat
fn c(&self) -> Mat
fn alpha(&self) -> f64
fn beta(&self) -> f64
fn s(&self) -> Scalar
fn to_mat(&self) -> Result<Mat>
fn size(&self) -> Result<Size>
fn typ(&self) -> Result<i32>
fn row(&self, y: i32) -> Result<MatExpr>
fn col(&self, x: i32) -> Result<MatExpr>
fn apply(&self, row_range: &Range, col_range: &Range) -> Result<MatExpr>
fn apply_1(&self, roi: Rect) -> Result<MatExpr>
fn t(&self) -> Result<MatExpr>
source§fn mul_matexpr(&self, e: &MatExpr, scale: f64) -> Result<MatExpr>
fn mul_matexpr(&self, e: &MatExpr, scale: f64) -> Result<MatExpr>
C++ default parameters Read more
fn cross(&self, m: &Mat) -> Result<Mat>
fn dot(&self, m: &Mat) -> Result<f64>
source§impl ToInputArray for &MatExpr
impl ToInputArray for &MatExpr
fn input_array(&self) -> Result<_InputArray>
source§impl ToInputArray for MatExpr
impl ToInputArray for MatExpr
fn input_array(&self) -> Result<_InputArray>
impl Send for MatExpr
Auto Trait Implementations§
impl RefUnwindSafe for MatExpr
impl !Sync for MatExpr
impl Unpin for MatExpr
impl UnwindSafe for MatExpr
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more