| license: gpl-3.0 | |
| language: | |
| - en | |
| metrics: | |
| - mse | |
| pipeline_tag: unconditional-image-generation | |
| tags: | |
| - diffusion | |
| - image generation | |
| - unconditional | |
| - wsi | |
| # WSI Generation with DDPM | |
|  | |
| A Diffusion Model for Generating WSI Patches | |
| How to use the model? | |
| ```py | |
| from diffusers import DiffusionPipeline | |
| wsi_generator = DiffusionPipeline.from_pretrained("kaveh/wsi_generator") | |
| device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') | |
| wsi_generator.to(device) | |
| generated_image = wsi_generator().images[0] | |
| generated_image.save("wsi_generated.png") | |
| ``` | |
| there is also a docker image available for this model in the following link: | |
| [https://hub.docker.com/r/kaveh8/wsi-ddpm](https://hub.docker.com/r/kaveh8/wsi-ddpm) |