Pathology fine-tuned AEs
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https://histodiffusion.github.io/docs/projects/pathae/ • 4 items • Updated • 1
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("StonyBrook-CVLab/sd-vae-ft-ema-path", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
StabilityAI KL-f8-c8 (SD1.5 VAE) autoencoder finetuned on digital histopathology images.
The original autoencoder is taken from StabilityAI.
We fine-tune the decoder on histopathology images using an L1 reconstruction loss, a PatchGAN adversarial loss and a pathology-specific perceptual loss (UNI).
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