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license: cc-by-4.0
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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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---
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[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xHFA2k_ludvae_realplksr_dysample)
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# 4xFFHQLDAT
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Since the 4xFFHQDAT model is not able to handle the noise present in low quality input images, i made a small variant/finetune of this, the 4xFFHQLDAT model. This model might come in handy if your input image is of bad quality/not suited for above model. I basically made this model in a response to an input image posted in upscaling-results channel as a request to this upscale model (since 4xFFHQDAT would not be able to handle noise), see Imgsli1 example below for result.
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Name: 4xFFHQLDAT
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Author: Philip Hofmann
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Release Date: 25.08.2023
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License: CC BY 4.0
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Network: DAT
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Scale: 4
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Purpose: 4x upscaling model for low quality input photos of faces
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Iterations: 44000
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batch_size: 4
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HR_size: 128
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Dataset: FFHQ - full dataset till 50k, then first 10k img multiscaled (resulted in ~260k imgs, 126GB)
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Number of train images: 259990
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OTF Training: Yes
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Pretrained_Model_G: 4xFFHQDAT
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Examples 4xFFHQLDAT:
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[Imgsli1](https://imgsli.com/MjAwNjYx)
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[Imgsli2](https://imgsli.com/MjAwNjYy)
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[Imgsli3](https://imgsli.com/MjAwNjYz)
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