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| license: cc-by-4.0 |
| pipeline_tag: image-to-image |
| tags: |
| - pytorch |
| - super-resolution |
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| [Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xFFHQDAT) |
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| # 4xFFHQDAT |
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| Name: 4xFFHQDAT |
| Author: Philip Hofmann |
| Release Date: 25.08.2023 |
| License: CC BY 4.0 |
| Network: DAT |
| Scale: 4 |
| Purpose: 4x upscaling model for faces |
| Iterations: 122000 |
| epoch: 2 |
| batch_size: 4 |
| HR_size: 128 |
| Dataset: FFHQ - full dataset till 50k, then first 10k img multiscaled (resulted in ~260k imgs, 126GB) |
| Number of train images: 259990 |
| OTF Training: Yes |
| Pretrained_Model_G: DAT_x4.pth |
| |
| 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: |
| [Imgsli1](https://imgsli.com/MjAwNjUz) |
| [Imgsli2](https://imgsli.com/MjAwNjU0) |
| [Imgsli3](https://imgsli.com/MjAwNjU2) |
| [Imgsli4](https://imgsli.com/MjAwNjU3) |
| [Imgsli5](https://imgsli.com/MjAwNjU4) |
| [Imgsli6](https://imgsli.com/MjAwNjU5) |
| [Imgsli7](https://imgsli.com/MjAwNzk0) |
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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. |
| |
| Name: 4xFFHQLDAT |
| Author: Philip Hofmann |
| Release Date: 25.08.2023 |
| License: CC BY 4.0 |
| Network: DAT |
| Scale: 4 |
| Purpose: 4x upscaling model for low quality input photos of faces |
| Iterations: 44000 |
| epoch: 0 |
| batch_size: 4 |
| HR_size: 128 |
| Dataset: FFHQ - full dataset till 50k, then first 10k img multiscaled (resulted in ~260k imgs, 126GB) |
| Number of train images: 259990 |
| OTF Training: Yes |
| Pretrained_Model_G: 4xFFHQDAT |
| |
| Examples 4xFFHQLDAT: |
| [Imgsli1](https://imgsli.com/MjAwNjYx) |
| [Imgsli2](https://imgsli.com/MjAwNjYy) |
| [Imgsli3](https://imgsli.com/MjAwNjYz) |
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