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---
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/2xLexicaRRDBNet)
# 2xLexicaRRDBNet_Sharp
Name: 2xLexicaRRDBNet_Sharp
Author: Philip Hofmann
Release Date: 01.06.2023
License: CC BY 4.0
Network: RRDBNet
Scale: 2
Purpose: Upscaling AI generated images - a bit sharper then above model
Iterations: 220'000
batch_size: 4
HR_size: 128
Epoch: 18 (require iter number per epoch: 10964)
Dataset: lexica-aperture-v3-small
Number of train images: 43856
OTF Training: No
Pretrained_Model_G: None
Description: Its like the above model, but trained for some more with l1_gt_usm and percep_gt_usm set to true, resulting in sharper outputs. I provide both so they can be chosen based on preferrence of the user.
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