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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/4xNomos8k_atd_jpg)
# 4xNomos8k_atd_jpg
Name: 4xNomos8k_atd_jpg
License: CC BY 4.0
Author: Philip Hofmann
Network: [ATD](https://github.com/LabShuHangGU/Adaptive-Token-Dictionary)
Scale: 4
Release Date: 22.03.2024
Purpose: 4x photo upscaler, handles jpg compression
Iterations: 240'000
epoch: 152
batch_size: 6, 3
HR_size: 128, 192
Dataset: nomos8k
Number of train images: 8492
OTF Training: Yes
Pretrained_Model_G: 003_ATD_SRx4_finetune
Description:
4x photo upscaler which handles jpg compression. This model will preserve noise. Trained on the very recently released (~2 weeks ago) Adaptive-Token-Dictionary network.
Training details:
AdamW optimizer with U-Net SN discriminator and BFloat16.
Degraded with otf jpg compression down to 40, re-compression down to 40, together with resizes and the blur kernels.
Losses: PixelLoss using CHC (Clipped Huber with Cosine Similarity Loss), PerceptualLoss using Huber, GANLoss, [LDL](https://github.com/csjliang/LDL) using Huber, YCbCr Color Loss (bt601) and Luma Loss (CIE XYZ) on [neosr](https://github.com/muslll/neosr).
7 Examples:
[Slowpics](https://slow.pics/s/uwnoI435)
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