Unconditional Image Generation
Diffusers
TensorBoard
Safetensors
English
DDPMPipeline
diffusion
image generation
unconditional
wsi
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("kaveh/wsi_generator", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]WSI Generation with DDPM
A Diffusion Model for Generating WSI Patches
How to use the model?
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
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