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4xNomosUniDAT_bokeh_jpg

4xDATby Helaman

4x Multipurpose DAT upscaler

Trained on DAT with Adan, U-Net SN, huber pixel loss, huber perceptial loss, vanilla gan loss, huber ldl loss and huber focal-frequency loss, on paired nomos_uni (universal dataset containing photographs, anime, text, maps, music sheets, paintings ..) with added jpg compression 40-100 and down_up, bicubic, bilinear, box, nearest and lanczos scales. No blur degradation had been introduced in the training dataset to keep the model from trying to sharpen blurry backgrounds.

The three strengths of this model (design purpose):

  1. Multipurpose
  2. Handles bokeh effect
  3. Handles jpg compression

This model will not:

  • Denoise
  • Deblur
Training details (7)
Date
2023-09-14
Dataset
nomos_uni
Dataset size
2989
Training iterations
185000
Training epochs
9
Training batch size
4
Training HR size
128

Model

Architecture
DAT
Scale
4x
Color Mode

Rights

CC-BY-4.0
Private use
Commercial use
Distribution
Modifications
Credit required
State Changes
No Liability & Warranty
Disclaimer

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