Name: 4x Valar
Author: musl

Nice to release a model again! This one is intended for realistic imagery, and works especially well on faces, hair, and nature shots. It should only be used on somewhat clear shots, without a lot of grain. I trained this model on SPAN, which as of the time of release, you'll need chaiNNer-nightly for. I aimed for a softer, more natural look for this model with as few artifacts as possible.

In addition to the Normal model, I've included a "soft" model. The Soft model is... softer. Basically it was an earlier version of the model with a more limited dataset. It produces more natural output on games or rendered content, but suffers a bit more with realistic stuff.

Note: In shots with DOF (depth of field) or bokeh, unfortunately there will be artifacts. 

Compatibility: You'll have to use the latest chaiNNer-nightly to use this model

ClearRealityV1

Rybu

Meant as an experiment to test latest techniques implemented on traiNNer, including: AdaTarget, KernelGAN, UNet discriminator, nESRGAN+ arch, noise patches, camera noise, isotropic/anisotropic/sinc blur, frequency separation, contextual loss, mixup, clipL1 pixel loss, AdamP optimizer, etc. The config file is provided on the download link above. I encourage everybody to mirror the model, distribute and modify it in anywway you want.

Valar

## RealPLKSR GAN pretrain

**Scale:** 4x  
**Architecture:** RealPLKSR  
**Download:** [GDrive](https://drive.google.com/file/d/1iQmsnMhWXsHLYuYEwwRhdj9fMg71h-IU/view) | Training files: [GDrive](https://drive.google.com/drive/folders/1OWLGBce6oe8W6kARINFCWG7o0O5LeC_h?usp=sharing)  

**Author:** musl  
**License:** [CC0](https://creativecommons.org/public-domain/cc0/)  
**Purpose:** Pretrain  
**Subject:** Multipurpose  
**Date:** 15 May 2024  

**Size:** default Real-PLKSR  
**I/O Channels:** 3(RGB)->3(RGB)  

**Dataset:** Nomos-v2  
**Dataset Size:** 6000  
**OTF (on the fly augmentations):** No  
**Pretrained Model:** 4x_realplksr_mssim_pretrain  
**Iterations:** ~450k  
**Batch Size:** 2-6  
**GT Size:** 128-416  

**Description:** Pretrained GAN models for RealPLKSR network. Trained on downsampling-only (nearest, bilinear, bicubic, lanczos and mitchell).

4x_realplksr_gan_pretrain

## RealPLKSR mssim pretrains

**Scale:** 2x and 4x  
**Architecture:** RealPLKSR  
**Links:**  

**`4x_realplksr_mssim_pretrain.pth`** | [GDrive](https://drive.google.com/file/d/12ek1vitEporWc5qqaYo6AMy0-RYlRqu8/view?usp=drive_link)  
**`2x_realplksr_mssim_pretrain.pth`** | [GDrive](https://drive.google.com/file/d/1GAdf5VOqYa5ntswT9sYsKKZ2Z7OQp7gO/view?usp=drive_link)  

**Author:** musl  
**License:** [CC0](https://creativecommons.org/public-domain/cc0/)  
**Purpose:** Pretrain  
**Subject:** Multipurpose  
**Date:** 08 May 2024  

**Size:** default Real-PLKSR  
**I/O Channels:** 3(RGB)->3(RGB)  

**Dataset:** Nomos-v2  
**Dataset Size:** 6000  
**OTF (on the fly augmentations):** No  
**Pretrained Model:** scratch  
**Iterations:** ~260k  
**Batch Size:** 2-6  
**GT Size:** 128-256  

**Description:** Pretrained models for RealPLKSR network. Trained on downsampling-only (nearest, bilinear, bicubic and lanczos).

Valar

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