Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction
Paper β’ 2409.18124 β’ Published β’ 33
How to use jingheya/lotus-normal-g-v1-1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("jingheya/lotus-normal-g-v1-1", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]This model belongs to the family of official Lotus models.
Some training normals in the Hypersim dataset are not properly oriented towards the camera. This models was re-trained using aligned surface normals, referred to GeoWizard, and achieves significantly improved results.
Developed by: Jing Heβ±, Haodong Liβ±, Wei Yin, Yixun Liang, Leheng Li, Kaiqiang Zhou, Hongbo Zhang, Bingbing Liu, Ying-Cong Chenβ
Please refer to this page.