import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Pensioner/LightShift", dtype=torch.bfloat16, device_map="cuda")
prompt = "Turn this cat into a dog"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
image = pipe(image=input_image, prompt=prompt).images[0]LightShift
LightShift: Controllable Indoor Relighting via Video Diffusion Priors
This repository contains the fine-tuned UNet checkpoint for LightShift, a controllable indoor relighting method that repurposes Stable Video Diffusion for image-based relighting.
Usage
This checkpoint is compatible with the Diffusers library. See the code and inference scripts at Pensioner-11/LightShift.
from diffusers import StableVideoDiffusionPipeline
pipe = StableVideoDiffusionPipeline.from_pretrained(
"Pensioner/LightShift",
torch_dtype=torch.float16,
).to("cuda")
Model Description
- Base model: stabilityai/stable-video-diffusion-img2vid-xt
- Fine-tuned component: UNet
- Training steps: 200,000
Citation
Citation information will be updated after publication.
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