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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/4xArtFaces_realplksr_dysample)
# 4xArtFaces_realplksr_dysample
Scale: 4
Architecture: [RealPLKSR with Dysample](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: Restoration
Subject: Art
Input Type: Images
Release Date: 08.08.2024
Dataset: [ArtFaces](https://github.com/Phhofm/models/releases/tag/dataset_artfaces)
Dataset Size: 5'630
OTF (on the fly augmentations): No
Pretrained Model: [4xNomos2_realplksr_dysample](https://github.com/Phhofm/models/releases/tag/4xNomos2_realplksr_dysample)
Iterations: 139'000
Batch Size: 6
Patch Size: 64
Description:
A Dysample RealPLKSR 4x upscaling model for art / painted faces.
Based on my [ArtFaces Dataset](https://github.com/Phhofm/models/releases/tag/dataset_artfaces) which is a curated version of the [metfaces dataset](https://github.com/NVlabs/metfaces-dataset) for the purpose of training single image super resolution models.
Showcase:
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