o .wiC!@sLddlmZddlmZmZmZddlmZddlm Z ddl m Z ddl m Z ddlmZddlmZdd lmZdd lmZmZdd lmZdd lmZdd lmZGddde ZGdddeZGddde ZGdddeZ GdddeZ!GdddeZ"Gddde Z#GdddeZ$GdddeZ%Gd d!d!eZ&d"S)#)Sequence)AnyOptionalUnion)Literal)SpectralDistortionIndex))ErrorRelativeGlobalDimensionlessSynthesis)PeakSignalNoiseRatio)RelativeAverageSpectralError)&RootMeanSquaredErrorUsingSlidingWindow)SpectralAngleMapper)*MultiScaleStructuralSimilarityIndexMeasure StructuralSimilarityIndexMeasure)TotalVariation)UniversalImageQualityIndex)_deprecated_root_import_classc s<eZdZdZ  d dededdedd ffd d ZZS) *_ErrorRelativeGlobalDimensionlessSynthesiszWrapper for deprecated import. >>> from torch import rand >>> preds = rand([16, 1, 16, 16]) >>> target = preds * 0.75 >>> ergas = _ErrorRelativeGlobalDimensionlessSynthesis() >>> ergas(preds, target).round() tensor(10.) elementwise_meanratio reductionrsumnoneNkwargsreturnNc &tddtjd||d|dS)Nrimage)rrrsuper__init__)selfrrr __class__r[/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/torchmetrics/image/_deprecated.pyr!s z3_ErrorRelativeGlobalDimensionlessSynthesis.__init__)rr) __name__ __module__ __qualname____doc__floatrrr! __classcell__rrr#r%rs rcseZdZdZ        dd ed eeeefd eeeefde dde eee eeffdedede edfde dde ddffdd Z ZS)+_MultiScaleStructuralSimilarityIndexMeasurea Wrapper for deprecated import. >>> from torch import rand >>> preds = rand([3, 3, 256, 256]) >>> target = preds * 0.75 >>> ms_ssim = _MultiScaleStructuralSimilarityIndexMeasure(data_range=1.0) >>> ms_ssim(preds, target) tensor(0.9628) T ?rN{Gz?Q?gǺ?g48EG?ga4?g??g9EGr?relugaussian_kernel kernel_sizesigmarr data_rangek1k2betas. normalize)r2simpleNrrc 4tddtjd||||||||| d | dS)Nr r) r3r4r5rr6r7r8r9r:rr) r"r3r4r5rr6r7r8r9r:rr#rr%r!4  z4_MultiScaleStructuralSimilarityIndexMeasure.__init__) Tr-r.rNr/r0r1r2)r&r'r(r)boolrintrr*rrtuplerr!r+rrr#r%r,(sD     r,cspeZdZdZ    ddeeeeeeffdededd eee ee d ffd e d df fd d Z Z S)_PeakSignalNoiseRatiozWrapper for deprecated import. >>> from torch import tensor >>> psnr = _PeakSignalNoiseRatio() >>> preds = tensor([[0.0, 1.0], [2.0, 3.0]]) >>> target = tensor([[3.0, 2.0], [1.0, 0.0]]) >>> psnr(preds, target) tensor(2.5527) N$@rr6baserrdim.rrc s*tddtjd||||d|dS)Nr r)r6rCrrDrr)r"r6rCrrDrr#rr%r!\s  z_PeakSignalNoiseRatio.__init__)NrBrN) r&r'r(r)rrr*r@rr?rr!r+rrr#r%rAPs& rAc:eZdZdZ d dedeeefddffdd ZZ S) _RelativeAverageSpectralErrorzWrapper for deprecated import. >>> from torch import rand >>> preds = rand(4, 3, 16, 16) >>> target = rand(4, 3, 16, 16) >>> rase = _RelativeAverageSpectralError() >>> rase(preds, target) tensor(5326.40...)  window_sizerrNc $tddtjdd|i|dS)Nr rrHrrr"rHrr#rr%r!t z&_RelativeAverageSpectralError.__init__rG r&r'r(r)r?dictstrrr!r+rrr#r%rFh  rFcrE) '_RootMeanSquaredErrorUsingSlidingWindowzWrapper for deprecated import. >>> from torch import rand >>> preds = rand(4, 3, 16, 16) >>> target = rand(4, 3, 16, 16) >>> rmse_sw = RootMeanSquaredErrorUsingSlidingWindow() >>> rmse_sw(preds, target) tensor(0.4158) rGrHrrNc rI)Nr rrHrrrJr#rr%r!rKz0_RootMeanSquaredErrorUsingSlidingWindow.__init__rLrMrrr#r%rQ}rPrQcs6eZdZdZ d deddeddffdd ZZS) _SpectralAngleMapperzWrapper for deprecated import. >>> from torch import rand >>> preds = rand([16, 3, 16, 16]) >>> target = rand([16, 3, 16, 16]) >>> sam = _SpectralAngleMapper() >>> sam(preds, target) tensor(0.5914) rrrrrrrNc rI)Nr rrrrr"rrr#rr%r!rKz_SpectralAngleMapper.__init__)rr&r'r(r)rrr!r+rrr#r%rRs rRc s:eZdZdZ d dededdedd ffd d ZZS) _SpectralDistortionIndexzWrapper for deprecated import. >>> from torch import rand >>> preds = rand([16, 3, 16, 16]) >>> target = rand([16, 3, 16, 16]) >>> sdi = _SpectralDistortionIndex() >>> sdi(preds, target) tensor(0.0234) rprrSrrNc r)Nrr)rXrrr)r"rXrrr#rr%r!s z!_SpectralDistortionIndex.__init__)rWr) r&r'r(r)r?rrr!r+rrr#r%rVs rVcseZdZdZ        dd ed eeeefd eeeefd e dde eee eeffdedededede ddffdd Z ZS)!_StructuralSimilarityIndexMeasurezWrapper for deprecated import. >>> import torch >>> preds = torch.rand([3, 3, 256, 256]) >>> target = preds * 0.75 >>> ssim = _StructuralSimilarityIndexMeasure(data_range=1.0) >>> ssim(preds, target) tensor(0.9219) Tr.r-rNr/r0Fr3r5r4rrr6r7r8return_full_imagereturn_contrast_sensitivityrrc r<)Nrr) r3r5r4rr6r7r8rZr[rr) r"r3r5r4rr6r7r8rZr[rr#rr%r!r=z*_StructuralSimilarityIndexMeasure.__init__) Tr.r-rNr/r0FF)r&r'r(r)r>rr*rr?rrr@rr!r+rrr#r%rYsD     rYcs4eZdZdZd deddeddffdd ZZS) _TotalVariationzWrapper for deprecated import. >>> from torch import rand >>> tv = _TotalVariation() >>> img = rand(5, 3, 28, 28) >>> tv(img) tensor(7546.8018) rr)meanrrNrrNc rI)NrrrrrrTr#rr%r!s z_TotalVariation.__init__)rrUrrr#r%r\s( r\c sJeZdZdZ   ddeedeededd ed d f fd d Z Z S)_UniversalImageQualityIndexzWrapper for deprecated import. >>> import torch >>> preds = torch.rand([16, 1, 16, 16]) >>> target = preds * 0.75 >>> uqi = _UniversalImageQualityIndex() >>> uqi(preds, target) tensor(0.9216) r-r-r.r.rr4r5rrrrNc s(tddtjd|||d|dS)Nrr)r4r5rrr)r"r4r5rrr#rr%r!s z$_UniversalImageQualityIndex.__init__)r_r`r) r&r'r(r)rr?r*rrr!r+rrr#r%r^s  r^N)'collections.abcrtypingrrrtyping_extensionsrtorchmetrics.image.d_lambdartorchmetrics.image.ergasrtorchmetrics.image.psnrr torchmetrics.image.raser torchmetrics.image.rmse_swr torchmetrics.image.samr torchmetrics.image.ssimr rtorchmetrics.image.tvrtorchmetrics.image.uqirtorchmetrics.utilities.printsrrr,rArFrQrRrVrYr\r^rrrr%s.           ((