4xmssim Realplksr Dysample Pretrain
Scale: 4 Architecture: RealPLKSR with Dysample Architecture Option: realplksr
Source du modèle
- Type
- Other
- Taille du fichier
- 28,3 MB
- Version
- vVersion 1
- Mis à jour
- 14 sept. 2026
- Source
- Hugging Face
Description de la source
4xmssim_realplksr_dysample_pretrain
Scale: 4
Architecture: RealPLKSR with Dysample
Architecture Option: realplksr
Author: Philip Hofmann
License: CC-BY-0.4
Purpose: Pretrained
Subject: Photography
Input Type: Images
Release Date: 27.06.2024
Dataset: nomosv2
Dataset Size: 6000
OTF (on the fly augmentations): No
Pretrained Model: None (=From Scratch)
Iterations: 200'000
Batch Size: 8
GT Size: 192, 512
Description: Dysample had been recently added to RealPLKSR, which from what I had seen can resolve or help avoid the checkerboard / grid pattern on inference outputs. So with the commits from three days ago, the 24.06.24, on neosr, I wanted to create a 4x photo pretrain I can then use to train more realplksr models with dysample specifically to stabilize training at the beginning.
Example1 Example2 Example3 Example4 Example5 Example6 Example7 Example8 Example9 Example10 Example11
Sources
1 source
Sources
1 sourceVérifié 8 août
Artefacts du modèle
2 artefacts
Artefacts du modèle
2 artefacts4xmssim_realplksr_dysample_pretrain.pth
pth · 28,3 MB · SHA-256 0a8706be7239…862f · Hugging Face
Télécharger4xmssim_realplksr_dysample_pretrain.safetensors
safetensors · 28,3 MB · SHA-256 fcf51ad72a97…3cbb · Hugging Face
TéléchargerExtraits de sources
2 extraits
Extraits de sources
2 extraits--- license: cc-by-4.0 pipeline_tag: image-to-image tags: - pytorch - super-resolution - pretrain --- [Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xmssim_realplksr_dysample_pretrain) # 4xmssim_realplksr_dysample_pretrain 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: Pretrained Subject: Photography Input Type: Images Release Date: 27.06.2024 Dataset: [nomosv2](https://github.com/muslll/neosr/?tab=readme-ov-file#-datasets) Dataset Size: 6000 OTF (on the fly augmentations): No Pretrained Model: None (=From Scratch) Iterations: 200'000 Batch Size: 8 GT Size: 192, 512 Description: [Dysample](https://arxiv.org/pdf/2308.15085) had been recently added to RealPLKSR, which from what I had seen can resolve or help avoid the checkerboard / grid pattern on inference outputs. So with the [commits from three days ago, the 24.06.24, on neosr](https://github.com/muslll/neosr/commits/master/?since=2024-06-24&until=2024-06-24), I wanted to create a 4x photo pretrain I can then use to train more realplksr models with dysample specifically to stabilize training at the beginning. Showcase: [Imgsli](https://imgsli.com/Mjc0OTA1) [Slowpics](https://slow.pics/c/I9grkcqM)          