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---
license: cc-by-4.0
pipeline_tag: image-to-image
tags:
- pytorch
- restoration
---
[Link to Github Release](https://github.com/Phhofm/models/releases/tag/1xDeJPG_realplksr_otf)
# 1xDeJPG_realplksr_otf
Scale: 1
Architecture: [RealPLKSR](https://github.com/muslll/neosr/?tab=readme-ov-file#supported-archs)
Architecture Option: [realplksr](https://github.com/muslll/neosr/blob/master/neosr/archs/realplksr_arch.py)
Author: Philip Hofmann
License: CC-BY-0.4
Purpose: JPEG, Restoration
Subject: Photography
Input Type: Images
Release Date: 09.07.2024
Dataset: [nomosv2](https://github.com/muslll/neosr/?tab=readme-ov-file#-datasets)
Dataset Size: 6000
OTF (on the fly augmentations): Yes
Pretrained Model: This one used the 60 model as pretrain, while I used [4xNomos2_realplksr_dysample](https://github.com/Phhofm/models/releases/tag/4xNomos2_realplksr_dysample) as a pretrain for the 60 model.
Iterations: 196'000
Batch Size: 24
GT Size: 64
Description:
A 1x dejpg model, trained with otf down to jpg 40 in both degradation processes, see the yml config file for details.
I also release the 1xDeJPG_realplksr_otf_60 model additionally, which had been trained with less jpg compression in comparison, down to 60 in both cases, where the hope was that it could give a bit higher quality on less compressed inputs.
The 40 model is released as default since it will be able to handle more compressed inputs in general.
Since these are trained with otf will slightly deblur. Examples here are compressed, and then recompressed, with jpg 40.
Showcase:
[Slowpics](https://slow.pics/c/c0Wft9H4)
[Imgsli](https://imgsli.com/Mjc3NzMw)
(Click on image for better view)
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