clinicadl.transforms.config.SobelGradientsConfig

clinicadl.transforms.config.SobelGradientsConfig

Config class for monai.transforms.SobelGradients.

The keys of the input DataPoint on which the transforms will be applied can be specified via include (only these keys will be transformed) or exclude (all the keys except these ones will be transformed).

copy argument determines if the raw input DataPoint will be returned (False), or a copy (True).

parameter kernel_size: PositiveInt = 3

parameter spatial_axes: Optional[Union[NonNegativeInt, list[NonNegativeInt]]] = None

parameter normalize_kernels: bool = True

parameter normalize_gradients: bool = False

parameter padding_mode: SobelPaddingMode = 'reflect'

parameter dtype: torch.dtype = torch.float32

parameter include: Optional[Sequence[str]] = None

parameter exclude: Optional[Sequence[str]] = None

parameter copy_: bool = False (alias 'copy')