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·
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<a href="https://scholar.google.com.sg/citations?user=8gm-CYYAAAAJ&hl=en"><strong>Jun Hao Liew</strong></a>
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·
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<a href="https://hanshuyan.github.io/"><strong>Hanshu Yan</strong></a>
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·
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<a href="https://scholar.google.com/citations?user=stQQf7wAAAAJ&hl=en"><strong>Jia-Wei Liu</strong></a>
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·
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<a href="https://zhangchenxu528.github.io/"><strong>Chenxu Zhang</strong></a>
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·
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<a href="https://sites.google.com/site/jshfeng/home"><strong>Jiashi Feng</strong></a>
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·
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<a href="https://sites.google.com/view/showlab"><strong>Mike Zheng Shou</strong></a>
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<br>
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<br>
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<a href="https://arxiv.org/abs/2311.16498"><img src='https://img.shields.io/badge/arXiv-MagicAnimate-red' alt='Paper PDF'></a>
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<a href='https://showlab.github.io/magicanimate'><img src='https://img.shields.io/badge/Project_Page-MagicAnimate-green' alt='Project Page'></a>
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<a href=''><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a>
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<br>
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<b>National University of Singapore | ByteDance</b>
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</p>
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<table align="center">
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<tr>
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<td>
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<img src="assets/teaser/t1.gif">
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</td>
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<td>
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<img src="assets/teaser/t4.gif">
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</td>
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</tr>
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<tr>
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<td>
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<img src="assets/teaser/t3.gif">
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</td>
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<td>
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<img src="assets/teaser/t2.gif">
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</td>
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</tr>
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</table>
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## 📢 News
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* **[2023.12.4]** Release inference code and gradio demo. We are working to improve MagicAnimate, stay tuned!
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* **[2023.11.23]** Release MagicAnimate paper and project page.
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## 🏃♂️ Getting Started
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Please download the pretrained base models for [StableDiffusion V1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5) and [MSE-finetuned VAE](https://huggingface.co/stabilityai/sd-vae-ft-mse).
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Download our MagicAnimate [checkpints](https://huggingface.co/zcxu-eric/MagicAnimate).
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**Place them as following:**
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```bash
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magic-animate
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|----pretrained_models
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|----MagicAnimate
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|----appearance_encoder
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|----diffusion_pytorch_model.safetensors
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|----config.json
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|----densepose_controlnet
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|----diffusion_pytorch_model.safetensors
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|----config.json
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|----temporal_attention
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|----temporal_attention.ckpt
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|----sd-vae-ft-mse
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|----...
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|----stable-diffusion-v1-5
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|----...
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|----...
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```
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## ⚒️ Installation
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prerequisites: `python>=3.8`, `CUDA>=11.3`, and `ffmpeg`.
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Install with `conda`:
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```bash
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conda env create -f environment.yml
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conda activate manimate
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```
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or `pip`:
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```bash
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pip3 install -r requirements.txt
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```
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## 💃 Inference
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Run inference on single GPU:
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```bash
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bash scripts/animate.sh
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```
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Run inference with multiple GPUs:
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```bash
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bash scripts/animate_dist.sh
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```
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## 🎨 Gradio Demo
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#### Online Gradio Demo:
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Try our [online gradio demo]() quickly.
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#### Local Gradio Demo:
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Launch local gradio demo on single GPU:
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```bash
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python3 -m demo.gradio_animate
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```
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Launch local gradio demo if you have multiple GPUs:
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```bash
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python3 -m demo.gradio_animate_dist
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```
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Then open gradio demo in local browser.
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## 🎓 Citation
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If you find this codebase useful for your research, please use the following entry.
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```BibTeX
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@inproceedings{xu2023magicanimate,
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author = {Xu, Zhongcong and Zhang, Jianfeng and Liew, Jun Hao and Yan, Hanshu and Liu, Jia-Wei and Zhang, Chenxu and Feng, Jiashi and Shou, Mike Zheng},
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title = {MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model},
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booktitle = {arXiv},
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year = {2023}
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}
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```
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title: MagicAnimate
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emoji: 💃
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colorFrom: purple
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colorTo: purple
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sdk: gradio
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sdk_version: 4.4.0
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python_version: 3.8
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app_file: app.py
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pinned: false
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