Spectral Distortion Index¶
Module Interface¶
- class torchmetrics.SpectralDistortionIndex(p=1, reduction='elementwise_mean', **kwargs)[source]
Computes Spectral Distortion Index (SpectralDistortionIndex) also now as D_lambda is used to compare the spectral distortion between two images.
- Parameters
reduction¶ (
Literal
[‘elementwise_mean’, ‘sum’, ‘none’]) –a method to reduce metric score over labels.
'elementwise_mean'
: takes the mean (default)'sum'
: takes the sum'none'
: no reduction will be applied
kwargs¶ (
Any
) – Additional keyword arguments, see Advanced metric settings for more info.
Example
>>> import torch >>> _ = torch.manual_seed(42) >>> from torchmetrics import SpectralDistortionIndex >>> preds = torch.rand([16, 3, 16, 16]) >>> target = torch.rand([16, 3, 16, 16]) >>> sdi = SpectralDistortionIndex() >>> sdi(preds, target) tensor(0.0234)
References
[1] Alparone, Luciano & Aiazzi, Bruno & Baronti, Stefano & Garzelli, Andrea & Nencini, Filippo & Selva, Massimo. (2008). Multispectral and Panchromatic Data Fusion Assessment Without Reference. ASPRS Journal of Photogrammetric Engineering and Remote Sensing. 74. 193-200. 10.14358/PERS.74.2.193.
Initializes internal Module state, shared by both nn.Module and ScriptModule.
Functional Interface¶
- torchmetrics.functional.spectral_distortion_index(preds, target, p=1, reduction='elementwise_mean')[source]¶
Spectral Distortion Index (SpectralDistortionIndex) also now as D_lambda is used to compare the spectral distortion between two images.
- Parameters
- Return type
- Returns
Tensor with SpectralDistortionIndex score
- Raises
TypeError – If
preds
andtarget
don’t have the same data type.ValueError – If
preds
andtarget
don’t haveBxCxHxW shape
.ValueError – If
p
is not a positive integer.
Example
>>> from torchmetrics.functional import spectral_distortion_index >>> _ = torch.manual_seed(42) >>> preds = torch.rand([16, 3, 16, 16]) >>> target = torch.rand([16, 3, 16, 16]) >>> spectral_distortion_index(preds, target) tensor(0.0234)