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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...
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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.
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 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
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1 sourceVerified Aug 8
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2 excerptsExample6
Example7
--- license: cc-by-4.0 pipeline_tag: image-to-image tags: - pytorch - super-resolution --- [Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xFFHQDAT) # 4xFFHQLDAT 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. 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 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)  
Source context: 0 downloads · 1 likes · Pipeline image-to-image · Repo Phips/4xFFHQLDAT
