a  d.@sddlmZddlZddlmZddlmZddlmZddlm Z eeeeefddd Z deee ed ed ddZ deee ed ed ddZ dS))TupleN)Tensor)Literal)universal_image_quality_index)reduce)predstargetreturncCs|j|jkr&td|jd|jdt|jdkrNtd|jd|jd|jdd|jddkrtd |jd|jd||fS) zUpdate and returns variables required to compute Spectral Distortion Index. Args: preds: Low resolution multispectral image target: High resolution fused image z>Expected `ms` and `fused` to have the same data type. Got ms: z and fused: .z@Expected `preds` and `target` to have BxCxHxW shape. Got preds: z and target: NzNExpected `preds` and `target` to have same batch and channel sizes.Got preds: )Zdtype TypeErrorlenshape ValueErrorrrro/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/torchmetrics/functional/image/d_lambda.py!_spectral_distortion_index_updates" relementwise_mean)rsumnone)rrp reductionr csjd}tj||fjd}tj||fjd}t|D]F}||d}|dkrVq:dd||dddddf|ddd} tjfddt|d|Ddd} ddt| | d d jdD} t | d|||ddf<dd||dddddf|ddd} tjfd dt|d|Ddd} d dt| | d d jdD} t | d|||ddf<q:||j }||j }t t |||} |dkrt | d |} n&t d ||dt | d |} t| |S)aCompute Spectral Distortion Index (SpectralDistortionIndex_). Args: preds: Low resolution multispectral image target: High resolution fused image p: a parameter to emphasize large spectral difference reduction: a method to reduce metric score over labels. - ``'elementwise_mean'``: takes the mean (default) - ``'sum'``: takes the sum - ``'none'``: no reduction will be applied Example: >>> _ = torch.manual_seed(42) >>> preds = torch.rand([16, 3, 16, 16]) >>> target = torch.rand([16, 3, 16, 16]) >>> preds, target = _spectral_distortion_index_update(preds, target) >>> _spectral_distortion_index_compute(preds, target) tensor(0.0234) r)devicerNcs0g|](}dd||dddddfqSNrr.0r)rrr Vz6_spectral_distortion_index_compute..)ZdimcSsg|] }|qSrmeanrsrrrr Wsr)rcs0g|](}dd||dddddfqSrrr)rrrr ]r!cSsg|] }|qSrr"r$rrrr ^sg?)rtorchzerosrrangerepeatcatrsplitstackTpowabsrr)rrrrlengthm1m2knumZstack1Zstack2Zscorediffoutputrrr"_spectral_distortion_index_compute1s4  0&0&   &r7cCs>t|tr|dkr"td|dt||\}}t||||S)aCalculate `Spectral Distortion Index`_ (SpectralDistortionIndex_) also known as D_lambda. Metric is used to compare the spectral distortion between two images. Args: preds: Low resolution multispectral image target: High resolution fused image p: Large spectral differences reduction: a method to reduce metric score over labels. - ``'elementwise_mean'``: takes the mean (default) - ``'sum'``: takes the sum - ``'none'``: no reduction will be applied Return: Tensor with SpectralDistortionIndex score Raises: TypeError: If ``preds`` and ``target`` don't have the same data type. ValueError: If ``preds`` and ``target`` don't have ``BxCxHxW shape``. ValueError: If ``p`` is not a positive integer. Example: >>> from torchmetrics.functional.image 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) rz.Expected `p` to be a positive integer. Got p: r ) isinstanceintrrr7)rrrrrrrspectral_distortion_indexns(r:)rr)rr)typingrr&rZtyping_extensionsrZ!torchmetrics.functional.image.uqirZ"torchmetrics.utilities.distributedrrr9r7r:rrrrs0      @