deepinv.models#
This module contains a collection of models for denoising and reconstruction. Please refer to the user guide for more information.
Base Classes#
User Guide: refer to Introduction for more information.
Base class for denoiser models. |
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Base class for reconstruction models. |
Classical Denoisers#
User Guide: refer to Classical denoisers for more information.
BM3D denoiser. |
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Median filter. |
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Proximal operator of the isotropic Total Variation operator. |
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Proximal operator of (2nd order) Total Generalised Variation operator. |
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Orthogonal Wavelet denoising with the \(\ell_1\) norm. |
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Overcomplete Wavelet denoising with the \(\ell_1\) norm. |
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Expected Patch Log Likelihood denoising method. |
Deep Denoisers#
User Guide: refer to Deep denoisers for more information.
Simple fully connected autoencoder network. |
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U-Net convolutional denoiser. |
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DnCNN convolutional denoiser. |
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DRUNet denoiser network. |
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SCUNet denoising network. |
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Gradient Step Denoiser with DRUNet architecture |
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SwinIR denoising network. |
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Diffusion UNet model. |
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Restormer denoiser network. |
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Convolutional Input Convex Neural Network (ICNN). |
Denoisers Utils#
User Guide: refer to Denoisers Utilities for more information.
Turns the input denoiser into an equivariant denoiser with respect to geometric transforms. |
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Converts a denoiser with real inputs into the one with complex inputs. |
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Time-agnostic network wrapper. |
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Time-averaging network wrapper. |
Artifact Removal#
User Guide: refer to Artifact Removal for more information.
Artifact removal architecture. |
Deep Image Prior#
User Guide: refer to Deep Image Prior for more information.
Deep Image Prior reconstruction. |
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Convolutional decoder network. |
Adversarial Networks#
User Guide: refer to Adversarial Learning for more information.
PatchGAN Discriminator model. |
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ESRGAN Discriminator. |
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DCGAN Generator. |
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DCGAN Discriminator. |
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Adapts a generator model backbone (e.g DCGAN) for CSGM or AmbientGAN. |