---
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/4xHFA2k_ludvae_realplksr_dysample)  

# 4xLSDIRCompactR

Name: 4xLSDIRCompactR  
Author: Philip Hofmann  
Release Date: 17.03.2023  
License: CC BY 4.0  
Network: SRVGGNetCompact  
Scale: 4  
Purpose: 4x photo uspcaler that handles jpg compression, noise and slight  

Iterations: 130000  
batch_size: Variable(1-5)  
HR_size: 256  
Dataset: LSDIR  
Dataset_size: 84991  
OTF Training No  
Pretrained_Model_G: 4xLSDIRCompact.pth  

Description: Extending my last 4xLSDIRCompact model to Real-ESRGAN, meaning trained on synthetic data instead to handle more kinds of degradations, it should be able to handle compression, noise, and slight blur.

---

Here is a comparison to show that 4xLSDIRCompact cannot handle compression artifacts, and that these two models will produce better output for that specific scenario. These models are not ‘better’ than the previous one, they are just meant to handle a different use case: https://imgsli.com/MTYyODY3 


![Example1](https://github.com/Phhofm/models/assets/14755670/68be7b9e-472a-4eab-b0ec-a19346f6ac0d)
![Example2](https://github.com/Phhofm/models/assets/14755670/b3f59497-82e5-48d1-a15e-842ebfbcbf8a)
![Example3](https://github.com/Phhofm/models/assets/14755670/c0ddd288-52fe-4786-841a-264fe5098904)
![Example4](https://github.com/Phhofm/models/assets/14755670/292e2c49-5b99-4255-9068-bb1ed33f58cd)
![Example5](https://github.com/Phhofm/models/assets/14755670/bba3fb8c-d3f8-438a-9e9c-a3517a88ab5b)