---
license: cc-by-4.0
pipeline_tag: image-to-image
tags:
- pytorch
- super-resolution
---

[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xNomos2_hq_mosr) 


# 4xNomos2_hq_mosr  
Scale: 4  
Architecture: [MoSR](https://github.com/umzi2/MoSR)  
Architecture Option: [mosr](https://github.com/umzi2/MoSR/blob/95c5bf73cca014493fe952c2fbc0bdbe593da08f/neosr/archs/mosr_arch.py#L117)  

Author: Philip Hofmann  
License: CC-BY-0.4  
Purpose: Upscaler  
Subject: Photography  
Input Type: Images  
Release Date: 25.08.2024  

Dataset: [nomosv2](https://github.com/muslll/neosr/?tab=readme-ov-file#-datasets)  
Dataset Size: 6000  
OTF (on the fly augmentations): No  
Pretrained Model: [4xmssim_mosr_pretrain](https://github.com/Phhofm/models/releases/tag/4xmssim_mosr_pretrain)  
Iterations: 190'000  
Batch Size: 6  
Patch Size: 64  

Description:   
A 4x [MoSR](https://github.com/umzi2/MoSR) upscaling model, meant for non-degraded input, since this model was trained on non-degraded input to give good quality output.   

If your input is degraded, use a 1x degrade model first. So for example if your input is a .jpg file, you could use a 1x dejpg model first.  

PS I also provide an onnx conversion in the Attachements, I verified correct output with chainner:  

<img src="https://github.com/user-attachments/assets/7f2be678-9d63-43e3-bfb6-59c94827a828" width=25% height=25%>  

## Model Showcase:
[Slowpics](https://slow.pics/c/cqGJb0gT)

(Click on image for better view)
![Example1](https://github.com/user-attachments/assets/f7af4d9c-c40f-45bf-a2b5-7d11fea31ee8)
![Example2](https://github.com/user-attachments/assets/4796cd41-fa12-493b-abb0-c4a62c6baa0c)
![Example3](https://github.com/user-attachments/assets/d069d258-3151-4b28-9328-caace08a3390)
![Example4](https://github.com/user-attachments/assets/8826faa6-d52c-468a-ab6a-7c60d30410f8)
![Example5](https://github.com/user-attachments/assets/350d9810-715e-424e-911e-2d4818ddaa31)
![Example6](https://github.com/user-attachments/assets/803997bc-c640-4bac-ab0f-76fc8e1d594b)
![Example7](https://github.com/user-attachments/assets/dd81d313-b07a-426c-ad4d-376f48631f05)
![Example8](https://github.com/user-attachments/assets/932617fc-a5c4-46b6-95a5-553bc302d027)
![Example9](https://github.com/user-attachments/assets/2e205c4d-5da2-47ca-b9f4-c5218be7d74d)