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- ---
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- license: cc-by-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: cc-by-4.0
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+ ---
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+
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+ [Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xFFHQDAT)
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+ Name: 4xFFHQDAT
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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 faces
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+ Iterations: 122000
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+ epoch: 2
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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: DAT_x4.pth
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+ Description: 4x photo upscaler for faces with otf jpg compression, blur and resize, trained on FFHQ dataset. This has been trained on and for faces, but i guess can also be used for other photos, might be able to retain skin detail. This is not face restoration, but simply a 4x upscaler trained on faces, therefore input images need to be of good quality if good output quality is desired.
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+ Examples 4xFFHQDAT:
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+ [Imgsli1](https://imgsli.com/MjAwNjUz)
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+ [Imgsli2](https://imgsli.com/MjAwNjU0)
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+ [Imgsli3](https://imgsli.com/MjAwNjU2)
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+ [Imgsli4](https://imgsli.com/MjAwNjU3)
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+ [Imgsli5](https://imgsli.com/MjAwNjU4)
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+ [Imgsli6](https://imgsli.com/MjAwNjU5)
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+ [Imgsli7](https://imgsli.com/MjAwNzk0)
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+
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+ ![Example1](https://github.com/Phhofm/models/assets/14755670/3b69c1cb-3c94-4f26-8547-d8745a7165af)
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+ ![Example2](https://github.com/Phhofm/models/assets/14755670/57d92f97-0b62-44bc-ae6a-a15891d0d8a8)
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+ ![Example3](https://github.com/Phhofm/models/assets/14755670/968460e4-f94d-4c67-a657-4c634e1b03ff)
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+ ![Example4](https://github.com/Phhofm/models/assets/14755670/25261c31-a13c-43b3-96be-1116b4b12319)
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+ ![Example5](https://github.com/Phhofm/models/assets/14755670/b87b3226-24a5-4d17-a550-2c6894037e95)
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+
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+
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+ ---
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+
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+ Since the above 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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+ epoch: 0
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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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+
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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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+ ![Example6](https://github.com/Phhofm/models/assets/14755670/61b3cff7-117b-4510-bdcf-cd49a1494227)
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+ ![Example7](https://github.com/Phhofm/models/assets/14755670/de8e63a4-3b7b-4583-b638-720bb6423b2d)