---
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/4xNomos8kHAT-L_bokeh_jpg)  

# 4xNomos8kHAT-L_bokeh_jpg

Name: 4xNomos8kHAT-L_bokeh_jpg  
Author: Philip Hofmann  
Release: 05.10.2023  
License: CC BY 4.0  
Network: HAT  
Scale: 4  
Purpose: 4x photo upscaler (handles bokeh effect and jpg compression)  
Iterations: 145000  
epoch: 66  
batch_size: 4  
HR_size: 128  
Dataset: nomos8k  
Number of train images: 8492  
OTF Training: No  
Pretrained_Model_G: HAT-L_SRx4_ImageNet-pretrain  

Description:  
4x photo upscaler, made to specifically handle bokeh effect and jpg compression. Basically a HAT-L variant of the already released 4xNomosUniDAT_bokeh_jpg model, but specifically trained for photos on the nomos8k dataset (and hopefully without the smoothing effect).

The three strengths of this model (design purpose):  
Specifically for photos / photography  
Handles bokeh effect  
Handles jpg compression  

This model will not attempt to:  
Denoise  
Deblur