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  1. cc-by-nc-sa/Alsa/4x_realistic_misc_alsa.pth +3 -0
  2. cc-by-nc-sa/EzoGaming/2x_KemonoScale_v2.pth +3 -0
  3. cc-by-nc-sa/Foolhardy/4x_foolhardy_Remacri.pth +3 -0
  4. cc-by-nc-sa/Kim2091/4x-UltraSharp.pth +3 -0
  5. cc-by-nc-sa/Kim2091/4x-UniScale-Balanced [72000g].pth +3 -0
  6. cc-by-nc-sa/Kim2091/4x-UniScale-Interp.pth +3 -0
  7. cc-by-nc-sa/Kim2091/4x-UniScale-Strong [42400g].pth +3 -0
  8. cc-by-nc-sa/Kim2091/4x-UniScaleNR-Balanced [34400g].pth +3 -0
  9. cc-by-nc-sa/Kim2091/4x-UniScaleNR-Strong [62400g].pth +3 -0
  10. cc-by-nc-sa/Kim2091/4x-UniScaleV2_Mod.Shapr.Soft.INFO.txt +31 -0
  11. cc-by-nc-sa/Kim2091/4x-UniScaleV2_Moderate.pth +3 -0
  12. cc-by-nc-sa/Kim2091/4x-UniScaleV2_Sharp.pth +3 -0
  13. cc-by-nc-sa/Kim2091/4x-UniScaleV2_Soft.pth +3 -0
  14. cc-by-nc-sa/Kim2091/4x-UniScale_Restore.pth +3 -0
  15. cc-by-nc-sa/Kim2091/4x-UniScale_Restore_INFO.txt +1 -0
  16. cc-by-nc-sa/Kim2091/LICENSE.txt +1 -0
  17. cc-by-nc-sa/LyonHrt/atrib.txt +1 -0
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cc-by-nc-sa/Kim2091/4x-UniScaleV2_Mod.Shapr.Soft.INFO.txt ADDED
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+ @News @Wiki Editor
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+ **Name:** 4x-UniScaleV2_Soft/Moderate/Sharp
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+ **Author:** Kim2091
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+ **License:** CC BY-NC-SA 4.0
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+ **Link:** <https://mega.nz/folder/zZhA1KoD#ds2nmgDNV4hfFpNSfEqN6Q>
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+ **Model Architecture:** ESRGAN
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+ **Scale:** 4
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+ **Purpose:** Effectively a UniScale successor. It does nearly everything better, other than dealing with noise or compression. Use UniScale_Restore or UniScale_Iterp for that.
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+
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+ **Iterations:** 111k
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+ **batch_size:** 4
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+ **HR_size:** 112
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+ **Epoch:** 8
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+ **Dataset:** Custom Dataset consisting of lossless 4k frames from Metal Arms: Glitch in the System, Just Cause 3, Dirt 3, Forza Horizon 3, Sleeping Dogs, and self-edited photos from SignatureEdits + ATLA DVD images
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+ **Dataset_size:** 18,909 tiles + 288 ATLA Frames
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+ **OTF Training** Yes (JPEG artifacts, base_blur, bsrgan_resize)
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+ **Pretrained_Model_G:** 4xESRGAN
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+
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+ **Description:** I really don't have a great description for this model set. It just works well on nearly everything (other than Anime sadly). They work best with realistic images. I hope you guys like it :stuck_out_tongue:
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+
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+ The Moderate and Soft models are interpolations between UniScaleV2_Sharp, UniScale-Strong, and UniScaleNR-Balanced.
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+
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+ If your image has compression, the Soft model will work the best. Moderate and Sharp will work on images with compression, but they won't be as clean.
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+
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+ UniScale_Restore or UniScale_Interp (available in the main UniScale folder) will likely work better for images with heavy compression.
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+
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+ Comparisons:
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+ https://cdn.discordapp.com/attachments/884239326471393331/884296266857713704/unknown.png
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+ https://cdn.discordapp.com/attachments/884239326471393331/884294468709257216/unknown.png
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+ https://cdn.discordapp.com/attachments/884239326471393331/884298572894441512/unknown.png
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+ https://cdn.discordapp.com/attachments/884239326471393331/884302370136289323/unknown.png
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cc-by-nc-sa/Kim2091/4x-UniScale_Restore_INFO.txt ADDED
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+ This model has strong compression removal that helps with restoring heavily compressed or noisy images. It is intended to compete with BSRGAN.
cc-by-nc-sa/Kim2091/LICENSE.txt ADDED
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+ These models are licensed under CC BY-SA 4.0
cc-by-nc-sa/LyonHrt/atrib.txt ADDED
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+ https://upscale.wiki/wiki/User:LyonHrt