Music2Dance Trial
Collection
Dataset and generation model based on StableAnimator • 4 items • Updated
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image, export_to_video
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("dhlee3000/music2dance_cont", dtype=torch.bfloat16, device_map="cuda")
pipe.to("cuda")
prompt = "A man with short gray hair plays a red electric guitar."
image = load_image(
"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png"
)
output = pipe(image=image, prompt=prompt).frames[0]
export_to_video(output, "output.mp4")StableAnimator based checkpoints
If you find StableAnimator useful, please consider giving a star to this github repository and citing it:
@article{tu2024stableanimator,
title={StableAnimator: High-Quality Identity-Preserving Human Image Animation},
author={Shuyuan Tu and Zhen Xing and Xintong Han and Zhi-Qi Cheng and Qi Dai and Chong Luo and Zuxuan Wu},
journal={arXiv preprint arXiv:2411.17697},
year={2024}
}
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