LinearPhysicsMultiScaler

class deepinv.physics.LinearPhysicsMultiScaler(physics, img_shape, filter='sinc', factors=[2, 4, 8], **kwargs)

Bases: PhysicsMultiScaler, LinearPhysics

Multi-scale wrapper for linear physics operators.

See PhysicsMultiScaler for details.

Examples:

A multiscale BlurFFT operator can be created as follows:

>>> import torch
>>> import deepinv as dinv
>>> physics = dinv.physics.BlurFFT(img_size=(1, 32, 32), filter=dinv.physics.blur.gaussian_blur(.2))
>>> x = torch.rand((1, 1, 8, 8))  # define an image 4 times smaller than the physics input size (scale = 2)
>>> new_physics = dinv.physics.LinearPhysicsMultiScaler(physics, (1, 32, 32), factors=[2, 4, 8])  # define a multiscale physics with base img size (1, 32, 32)
>>> y = new_physics(x, scale=2)  # applying physics at scale 2
>>> print(y.shape)
torch.Size([1, 1, 32, 32])

Parameters:

• physics (deepinv.physics.Physics) – base physics operator.

• img_shape (tuple) – shape of the input image (C, H, W).

• filter (str) – type of filter to use for upsampling, e.g., ‘sinc’, ‘nearest’, ‘bilinear’.

• factors (list[int]) – list of factors to use for upsampling.

• device (torch.device, str) – device to use for the upsampling operator, e.g., ‘cpu’, ‘cuda’.