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

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


[Neosr](https://github.com/muslll/neosr)'s latest update from yesterday included a [new adaptation of the multi-scale ssim loss](https://github.com/muslll/neosr/wiki/Losses#mssim_opt).   
This was an experiment to test out the difference between making a SPAN pretrain with pixel loss with L1 criteria (as often used in research) vs mssim loss as its only loss.   
Models are provided so they can be used for tests or also used as a pretrain for another SPAN model.  

---

## 4xpix_span_pretrain

Scale: 4  
Architecture: SPAN  

Author: Philip Hofmann    
License: CC-BY-4.0  
Purpose: Pretrain  
Subject: Realistic, Anime  
Date: 10.04.2024  

Dataset: [nomos_uni](https://github.com/muslll/neosr)  
Dataset Size: 2989   
OTF (on the fly augmentations): No  
Pretrained Model: None  
Iterations: 80'000  
Batch Size: 12  
GT Size: 128  

Description: 4x SPAN pretrain trained on pixel loss with L1 criteria (as often used in research) on downsampled nomos_uni dataset using kim's [dataset destroyer](https://github.com/Kim2091/helpful-scripts/tree/main/Dataset%20Destroyer) with down_up,linear,cubic_mitchell,lanczos,gauss,box (while down_up used the same and with range = 0.15,1.5).   
The new augmentations except CutBlur have also been used (since CutBlur is meant to be applied to real-world SR and may cause undesired effects if applied to bicubic-only).   
Config and training log provided for more details.  

---

## 4xmssim_span_pretrain

Scale: 4  
Architecture: SPAN  

Author: Philip Hofmann    
License: CC-BY-4.0  
Purpose: Pretrain  
Subject: Realistic, Anime  
Date: 10.04.2024  

Dataset: [nomos_uni](https://github.com/muslll/neosr)  
Dataset Size: 2989   
OTF (on the fly augmentations): No  
Pretrained Model: None  
Iterations: 80'000  
Batch Size: 12  
GT Size: 128  

Description: 4x SPAN pretrain trained on [neosr](https://github.com/muslll/neosr)'s [new adaptation of the multi-scale ssim loss](https://github.com/muslll/neosr/wiki/Losses#mssim_opt) from yesterdays update on downsampled nomos_uni dataset using kim's [dataset destroyer](https://github.com/Kim2091/helpful-scripts/tree/main/Dataset%20Destroyer) with down_up,linear,cubic_mitchell,lanczos,gauss,box (while down_up used the same and with range = 0.15,1.5).   
The new augmentations except CutBlur have also been used (since CutBlur is meant to be applied to real-world SR and may cause undesired effects if applied to bicubic-only).   
Config and training log provided for more details.  

---
 
Showcase:   
[7 Slowpics Examples](https://slow.pics/c/zyilXhKU)  

![Example1](https://github.com/Phhofm/models/assets/14755670/009a554c-e642-40e0-a12d-41e85c3ff618)
![Example2](https://github.com/Phhofm/models/assets/14755670/1e81ca78-6122-4e23-bd25-1b654c09bfce)
![Example3](https://github.com/Phhofm/models/assets/14755670/a654503c-3ce3-46d6-a724-e5c43e5292c5)
![Example4](https://github.com/Phhofm/models/assets/14755670/15be1785-705d-4584-bae3-9ff5fdcbb8a6)
![Example5](https://github.com/Phhofm/models/assets/14755670/7539f74f-8f47-4b05-aed8-7f41b4e8c8f7)
![Example6](https://github.com/Phhofm/models/assets/14755670/05c4c383-b5ac-4403-93c5-1ac5d59b4875)
![Example7](https://github.com/Phhofm/models/assets/14755670/22272b73-c340-471a-9cba-defcddf5b9f7)