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README.md
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license: cc-by-4.0
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tags:
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- super-resolution
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Scale: 4x
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Network type: DAT2
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Author: Philip Hofmann
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Training iterations: 240000
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Description: 4x dat2 upscaling model for web and realistic images. It handles realistic noise, some realistic blur, and webp and jpg (re)compression. Trained on my BHI dataset (390'035 training tiles) with degraded LR subset.
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Have a look at the applied_degradations files in the attachement to know what degradations in what order were applied to the BHI dataset to create the corresponding LR set for training.
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Visual Examples:
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[slow.pics](https://slow.pics/c/WekJvaLo?image-fit=cover)
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[imgsli](https://imgsli.com/MzI3MzI2)
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---
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license: cc-by-4.0
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pipeline_tag: image-to-image
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tags:
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- pytorch
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- super-resolution
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[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xBHI_dat2_real)
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Scale: 4x
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Network type: DAT2
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Author: Philip Hofmann
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Training iterations: 240000
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Description: 4x dat2 upscaling model for web and realistic images. It handles realistic noise, some realistic blur, and webp and jpg (re)compression. Trained on my BHI dataset (390'035 training tiles) with degraded LR subset.
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Visual Examples:
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[slow.pics](https://slow.pics/c/WekJvaLo?image-fit=cover)
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[imgsli](https://imgsli.com/MzI3MzI2)
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