DFCAN

biapy.models.dfcan.fftshift2d(img, size_psc=128)

class biapy.models.dfcan.RCAB(size_psc=128)

Bases: Module

forward(x, gamma=0.8)

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

class biapy.models.dfcan.ResGroup(n_RCAB=4, size_psc=128)

Bases: Module

forward(x)

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

class biapy.models.dfcan.DFCAN(ndim, input_shape, scale=2, n_ResGroup=4, n_RCAB=4)

Bases: Module

Fourier channel attention network (DFCAN) for super-resolution.

References: Evaluation and development of deep neural networks for image super-resolution in optical microscopy.

forward(x)

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.