Link to Github Release

4xNomos2_hq_dat2

Scale: 4
Architecture: DAT
Architecture Option: dat2

Author: Philip Hofmann
License: CC-BY-0.4
Purpose: Upscaler
Subject: Photography
Input Type: Images
Release Date: 29.08.2024

Dataset: nomosv2
Dataset Size: 6000
OTF (on the fly augmentations): No
Pretrained Model: DAT_2_x4
Iterations: 140'000
Batch Size: 4
Patch Size: 48

Description:
A dat2 4x upscaling model, similiar to the 4xNomos2_hq_mosr model, trained and for usage on non-degraded input to give good quality output.

I scored 7 validation outputs of each of the 21 checkpoints (10k-210k) of this model training with 68 metrics.
The metric scores can be found in this google sheet.
The corresponding image files for this scoring can be found here
Screenshot of the google sheet:

Release checkpoint has been selected by looking at the scores, manually inspecting, and then getting responses on discord to this quick visual test, A B or C, which denote different checkpoints: https://slow.pics/c/8Akzj6rR

Checkpoint B is the one released here, but you can also try out Checkpoint A or Checkpoint C if you like them better.

Model Showcase:

Slowpics