pub fn mean_std_dev(src: &dyn core::ToInputArray, mean: &mut dyn core::ToOutputArray, stddev: &mut dyn core::ToOutputArray, mask: &dyn core::ToInputArray) -> Result<()> {
	input_array_arg!(src);
	output_array_arg!(mean);
	output_array_arg!(stddev);
	input_array_arg!(mask);
	unsafe { sys::cv_meanStdDev_const__InputArrayX_const__OutputArrayX_const__OutputArrayX_const__InputArrayX(src.as_raw__InputArray(), mean.as_raw__OutputArray(), stddev.as_raw__OutputArray(), mask.as_raw__InputArray()) }.into_result()
}
/// Calculates a mean and standard deviation of array elements.
/// 
/// The function cv::meanStdDev calculates the mean and the standard deviation M
/// of array elements independently for each channel and returns it via the
/// output parameters:
/// ![block formula](https://latex.codecogs.com/png.latex?%5Cbegin%7Barray%7D%7Bl%7D%20N%20%3D%20%20%5Csum%20%5F%7BI%2C%20%5Ctexttt%7Bmask%7D%20%28I%29%20%20%5Cne%200%7D%201%20%5C%5C%20%5Ctexttt%7Bmean%7D%20%5Fc%20%3D%20%20%5Cfrac%7B%5Csum%5F%7B%20I%3A%20%5C%3B%20%5Ctexttt%7Bmask%7D%28I%29%20%5Cne%200%7D%20%5Ctexttt%7Bsrc%7D%20%28I%29%5Fc%7D%7BN%7D%20%5C%5C%20%5Ctexttt%7Bstddev%7D%20%5Fc%20%3D%20%20%5Csqrt%7B%5Cfrac%7B%5Csum%5F%7B%20I%3A%20%5C%3B%20%5Ctexttt%7Bmask%7D%28I%29%20%5Cne%200%7D%20%5Cleft%20%28%20%5Ctexttt%7Bsrc%7D%20%28I%29%5Fc%20%2D%20%20%5Ctexttt%7Bmean%7D%20%5Fc%20%5Cright%20%29%5E2%7D%7BN%7D%7D%20%5Cend%7Barray%7D)
/// When all the mask elements are 0's, the function returns
/// mean=stddev=Scalar::all(0).
/// 
/// Note: The calculated standard deviation is only the diagonal of the
/// complete normalized covariance matrix. If the full matrix is needed, you
/// can reshape the multi-channel array M x N to the single-channel array
/// M\*N x mtx.channels() (only possible when the matrix is continuous) and
/// then pass the matrix to calcCovarMatrix .
/// ## Parameters
/// * src: input array that should have from 1 to 4 channels so that the results can be stored in
/// Scalar_ 's.
/// * mean: output parameter: calculated mean value.
/// * stddev: output parameter: calculated standard deviation.
/// * mask: optional operation mask.
/// ## See also
/// countNonZero, mean, norm, minMaxLoc, calcCovarMatrix
/// 
/// ## C++ default parameters
/// * mask: noArray()
Calculates a mean and standard deviation of array elements.

The calculated standard deviation is only the diagonal of the
complete normalized covariance matrix. If the full matrix is needed, you
can reshape the multi-channel array M x N to the single-channel array
M\*N x mtx.channels() (only possible when the matrix is continuous) and
then pass the matrix to calcCovarMatrix .
Calculates a mean and standard deviation of array elements . The calculated standard deviation is only the diagonal of the complete normalized covariance matrix . If the full matrix is needed you can reshape the multi - channel array M x N to the single - channel array M \ * N x mtx . channels () ( only possible when the matrix is continuous ) and then pass the matrix to calcCovarMatrix .
pub fn mean_std_dev(src: &dyn core::ToInputArray, mean: &mut dyn core::ToOutputArray, stddev: &mut dyn core::ToOutputArray, mask: &dyn core::ToInputArray) -> Result<()> {
	input_array_arg!(src);
	output_array_arg!(mean);
	output_array_arg!(stddev);
	input_array_arg!(mask);
	unsafe { sys::cv_meanStdDev_const__InputArrayX_const__OutputArrayX_const__OutputArrayX_const__InputArrayX(src.as_raw__InputArray(), mean.as_raw__OutputArray(), stddev.as_raw__OutputArray(), mask.as_raw__InputArray()) }.into_result()
}
pub fn mean_std_dev ( src : & dyn core :: ToInputArray , mean : & mut dyn core :: ToOutputArray , stddev : & mut dyn core :: ToOutputArray , mask : & dyn core :: ToInputArray ) -> Result < ( ) > { input_array_arg ! ( src ) ; output_array_arg ! ( mean ) ; output_array_arg ! ( stddev ) ; input_array_arg ! ( mask ) ; unsafe { sys :: cv_meanStdDev_const__InputArrayX_const__OutputArrayX_const__OutputArrayX_const__InputArrayX ( src . as_raw__InputArray ( ) , mean . as_raw__OutputArray ( ) , stddev . as_raw__OutputArray ( ) , mask . as_raw__InputArray ( ) ) } . into_result ( ) }
Calculates a mean and standard deviation of array elements.
Calculates a mean and standard deviation of array elements .
src
&dyn core::ToInputArray
mean
&mut dyn core::ToOutputArray
stddev
&mut dyn core::ToOutputArray
mask
&dyn core::ToInputArray
see also
countNonZero, mean, norm, minMaxLoc, calcCovarMatrix
countNonZero mean norm minMaxLoc calcCovarMatrix
c++ default parameters
None