---
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/4xHFA2kLUDVAESwinIR_light%264xHFA2kLUDVAESRFormer_light)  

# 4xHFA2kLUDVAESwinIR_light

Name: 4xHFA2kLUDVAESwinIR_light  
Author: Philip Hofmann  
Release Date: 10.06.2023  
License: CC BY 4.0  
Network: SwinIR  
Arch Option: SwinIR-light  
Scale: 4  
Purpose: An lightweight anime 4x upscaling model with realistic degradations, based on musl's HFA2k_LUDVAE dataset  
Iterations: 350,000  
batch_size: 3  
HR_size: 256  
Epoch: 99 (require iter number per epoch: 3424)  
Dataset: HFA2kLUDVAE  
Number of train images: 10270  
OTF Training: No  
Pretrained_Model_G: None  

Description: 4x lightweight anime upscaler with realistic degradations (compression, noise, blur). Visual outputs can be found on https://github.com/Phhofm/models/tree/main/4xHFA2kLUDVAE_results, together with timestamps and metrics to compare inference speed on the val set with other trained models/networks on this dataset.

![image](https://github.com/Phhofm/models/assets/14755670/64941695-7904-4ddf-9fad-d5f2ff04439a)  
![image](https://github.com/Phhofm/models/assets/14755670/095cf1c6-3506-4c3d-a2f3-fa619650915d)  
![image](https://github.com/Phhofm/models/assets/14755670/2dfa9f62-4ec2-4fab-9417-1b18bb4c1315)