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@News @Wiki Editor **Name:** 4x-UniScaleV2_Soft/Moderate/Sharp **Author:** Kim2091 **License:** CC BY-NC-SA 4.0 **Link:** <https://mega.nz/folder/zZhA1KoD#ds2nmgDNV4hfFpNSfEqN6Q> **Model Architecture:** ESRGAN **Scale:** 4 **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. **Iterations:** 111k **batch_size:** 4 **HR_size:** 112 **Epoch:** 8 **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 **Dataset_size:** 18,909 tiles + 288 ATLA Frames **OTF Training** Yes (JPEG artifacts, base_blur, bsrgan_resize) **Pretrained_Model_G:** 4xESRGAN **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: The Moderate and Soft models are interpolations between UniScaleV2_Sharp, UniScale-Strong, and UniScaleNR-Balanced. 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. UniScale_Restore or UniScale_Interp (available in the main UniScale folder) will likely work better for images with heavy compression. Comparisons: https://cdn.discordapp.com/attachments/884239326471393331/884296266857713704/unknown.png https://cdn.discordapp.com/attachments/884239326471393331/884294468709257216/unknown.png https://cdn.discordapp.com/attachments/884239326471393331/884298572894441512/unknown.png https://cdn.discordapp.com/attachments/884239326471393331/884302370136289323/unknown.png |