[−][src]Struct nnnoiseless::RnnModel
An RnnModel contains all the model parameters for the denoising algorithm.
nnnoiseless has a built-in model that should work for most purposes, but if you have
specific needs then you might benefit from training a custom model. Scripts for model
training are available as part of RNNoise; once the model is trained, you can load it
here.
Implementations
impl RnnModel[src]
pub fn from_read<R: Read>(r: R) -> Result<RnnModel, ReadModelError>[src]
Reads an RnnModel from a std::io::Read.
The file format of an RnnModel is not specified anywhere; it should have been generated
from the dump_rnn.py script in the [RNNoise repository].
Trait Implementations
Auto Trait Implementations
impl RefUnwindSafe for RnnModel[src]
impl Send for RnnModel[src]
impl Sync for RnnModel[src]
impl Unpin for RnnModel[src]
impl UnwindSafe for RnnModel[src]
Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized, [src]
T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized, [src]
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized, [src]
T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T[src]
impl<S, T> Duplex<S> for T where
T: FromSample<S> + ToSample<S>,
T: FromSample<S> + ToSample<S>,
impl<T> From<T> for T[src]
impl<S> FromSample<S> for S
pub fn from_sample_(s: S) -> S
impl<T, U> Into<U> for T where
U: From<T>, [src]
U: From<T>,
impl<T> ToOwned for T where
T: Clone, [src]
T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T[src]
pub fn clone_into(&self, target: &mut T)[src]
impl<T, U> ToSample<U> for T where
U: FromSample<T>,
U: FromSample<T>,
pub fn to_sample_(self) -> U
impl<T, U> TryFrom<U> for T where
U: Into<T>, [src]
U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>[src]
impl<T, U> TryInto<U> for T where
U: TryFrom<T>, [src]
U: TryFrom<T>,