Reconstructor#
- class deepinv.models.Reconstructor(device='cpu')[source]#
Bases:
Module
Base class for reconstruction models.
Provides a template for defining reconstruction models.
Reconstructors provide a signal estimate
x_hat
asx_hat = model(y, physics)
wherey
are the measurements andphysics
is the forward model \(A\) (possibly including information about the noise distribution too).The base class inherits from
torch.nn.Module
.- forward(y, physics, **kwargs)[source]#
Applies reconstruction model \(\inversef{y}{A}\).
- Parameters:
y (torch.Tensor) – measurements.
physics (deepinv.physics.Physics) – forward model \(A\).
- Returns:
(
torch.Tensor
) reconstructed tensor.
Examples using Reconstructor
:#

Reconstructing an image using the deep image prior.

Self-supervised learning with measurement splitting

Self-supervised denoising with the Neighbor2Neighbor loss.

Self-supervised denoising with the Generalized R2R loss.

Self-supervised learning from incomplete measurements of multiple operators.

Imaging inverse problems with adversarial networks