base on [CVPR 2024] MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model <!-- # magic-edit.github.io --> <p align="center"> <h2 align="center">MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model</h2> <p align="center"> <a href="https://scholar.google.com/citations?user=-4iADzMAAAAJ&hl=en"><strong>Zhongcong Xu</strong></a> · <a href="http://jeff95.me/"><strong>Jianfeng Zhang</strong></a> · <a href="https://scholar.google.com.sg/citations?user=8gm-CYYAAAAJ&hl=en"><strong>Jun Hao Liew</strong></a> · <a href="https://hanshuyan.github.io/"><strong>Hanshu Yan</strong></a> · <a href="https://scholar.google.com/citations?user=stQQf7wAAAAJ&hl=en"><strong>Jia-Wei Liu</strong></a> · <a href="https://zhangchenxu528.github.io/"><strong>Chenxu Zhang</strong></a> · <a href="https://sites.google.com/site/jshfeng/home"><strong>Jiashi Feng</strong></a> · <a href="https://sites.google.com/view/showlab"><strong>Mike Zheng Shou</strong></a> <br> <br> <a href="https://arxiv.org/abs/2311.16498"><img src='https://img.shields.io/badge/arXiv-MagicAnimate-red' alt='Paper PDF'></a> <a href='https://showlab.github.io/magicanimate'><img src='https://img.shields.io/badge/Project_Page-MagicAnimate-green' alt='Project Page'></a> <a href='https://huggingface.co/spaces/zcxu-eric/magicanimate'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a> <br> <b>National University of Singapore &nbsp; | &nbsp; ByteDance</b> </p> <table align="center"> <tr> <td> <img src="assets/teaser/t4.gif"> </td> <td> <img src="assets/teaser/t2.gif"> </td> </tr> </table> ## 📢 News * **[2023.12.4]** Release inference code and gradio demo. We are working to improve MagicAnimate, stay tuned! * **[2023.11.23]** Release MagicAnimate paper and project page. ## 🏃‍♂️ Getting Started 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). Download our MagicAnimate [checkpoints](https://huggingface.co/zcxu-eric/MagicAnimate). Please follow the huggingface download instructions to download the above models and checkpoints, `git lfs` is recommended. Place the based models and checkpoints as follows: ```bash magic-animate |----pretrained_models |----MagicAnimate |----appearance_encoder |----diffusion_pytorch_model.safetensors |----config.json |----densepose_controlnet |----diffusion_pytorch_model.safetensors |----config.json |----temporal_attention |----temporal_attention.ckpt |----sd-vae-ft-mse |----config.json |----diffusion_pytorch_model.safetensors |----stable-diffusion-v1-5 |----scheduler |----scheduler_config.json |----text_encoder |----config.json |----pytorch_model.bin |----tokenizer (all) |----unet |----diffusion_pytorch_model.bin |----config.json |----v1-5-pruned-emaonly.safetensors |----... ``` ## ⚒️ Installation prerequisites: `python>=3.8`, `CUDA>=11.3`, and `ffmpeg`. Install with `conda`: ```bash conda env create -f environment.yaml conda activate manimate ``` or `pip`: ```bash pip3 install -r requirements.txt ``` ## 💃 Inference Run inference on single GPU: ```bash bash scripts/animate.sh ``` Run inference with multiple GPUs: ```bash bash scripts/animate_dist.sh ``` ## 🎨 Gradio Demo #### Online Gradio Demo: Try our [online gradio demo](https://huggingface.co/spaces/zcxu-eric/magicanimate) quickly. #### Local Gradio Demo: Launch local gradio demo on single GPU: ```bash python3 -m demo.gradio_animate ``` Launch local gradio demo if you have multiple GPUs: ```bash python3 -m demo.gradio_animate_dist ``` Then open gradio demo in local browser. ## 🙏 Acknowledgements We would like to thank [AK(@_akhaliq)](https://twitter.com/_akhaliq?lang=en) and huggingface team for the help of setting up oneline gradio demo. ## 🎓 Citation If you find this codebase useful for your research, please use the following entry. ```BibTeX @inproceedings{xu2023magicanimate, 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}, title = {MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model}, booktitle = {arXiv}, year = {2023} } ``` ", Assign "at most 3 tags" to the expected json: {"id":"5671","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"