Is there any library to perform robust clustering given two probability distribution with noise?

Given a dataset $X$ consisted with $w|X|$ samples drawn from a mixture of multivariate Gaussian distributions (say in two dimensions) and $(1-w)|X|$ samples of noise, is there any Python, Julia, Matlab, Mathematica library that can perform a robust parameter estimation for the Gaussians?

Above, $|X|$ refers to the total number of elements of the two dimensional $(x,y)$ dataset $X$ and $0\ll w 1$. The idea is to readily use such a library such as to estimate means and covariances in the presence of noise (e.g. by disregarding from the estimation outliers).