---
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_VCISR_GRLGAN_ep200)

# 4xHFA2k_VCISR_GRLGAN_ep200 

Name: 4xHFA2k_VCISR_GRLGAN_ep200    
Release Date: 04.01.2024    
Author: Philip Hofmann    
License: CC BY 4.0    
Network: GRL    
Scale: 4    
Purpose: 4x anime upscaler handling video compression artifacts, trained for 200 epochs    
Iterations: 85959    
epoch: 200    
batch_size: 6    
HR_size: 128    
Dataset: hfa2k    
Number of train images: 2568    
OTF Training: Yes    
Pretrained_Model_G: None    

Description:
4x anime upscaler handling video compression artifacts since trained with otf degradations for "mpeg2video", "libxvid", "libx264", "libx265" with crf 20-32, mpeg bitrate 3800-5800 (together with the standard Real-ESRGAN otf pipeline). A faster arch using this otf degradation pipeline would be great for handling video compression artifacts. Since this one is a GRL model and therefore slow, [as noted by the dev](https://github.com/Kiteretsu77/VCISR-official/issues/3) maybe more for research purposes (or more for single images/screenshots). Trained using [VCISR](https://github.com/Kiteretsu77/VCISR-official) for 200 epochs.  

"This is epoch 200 and the start iteration is 85959 with learning rate 2.5e-05"  

Slow Pics examples:  
[h264_crf28](https://slow.pics/c/fqOnxXep)  
[ludvae1](https://slow.pics/c/OcukRy7d)  
[ludvae2](https://slow.pics/c/FI33mX4F)

![Example1](https://github.com/Phhofm/models/assets/14755670/8baeac11-72a2-4955-8a65-e67b88dd1f55)
![Example2](https://github.com/Phhofm/models/assets/14755670/5a940e22-10be-4043-a5ad-c8bed1fbbb80)
![Example3](https://github.com/Phhofm/models/assets/14755670/1ccc8b71-227e-438a-9df8-c8541b961a23)