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# Evaluation of TeaCache
## Installation
Prerequisites:
- Python >= 3.10
- PyTorch >= 1.13 (We recommend to use a >2.0 version)
- CUDA >= 11.6
We strongly recommend using Anaconda to create a new environment (Python >= 3.10) to run our examples:
```shell
conda create -n teacache python=3.10 -y
conda activate teacache
```
Install TeaCache:
```shell
git clone https://github.com/LiewFeng/TeaCache
cd TeaCache
pip install -e .
```
## Evaluation of TeaCache
We first generate videos according to VBench's prompts.
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python experiments/latte.py
python experiments/opensora.py
python experiments/open_sora_plan.py
python experiments/cogvideox.py
```
2. Calculate Vbench score
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# generated video is our methods's results
python common_metrics/eval.py --gt_video_dir aa --generated_video_dir bb
```
## Citation
If you find TeaCache is useful in your research or applications, please consider giving us a star 🌟 and citing it by the following BibTeX entry.
```
@article{liu2024timestep,
title={Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model},
author={Liu, Feng and Zhang, Shiwei and Wang, Xiaofeng and Wei, Yujie and Qiu, Haonan and Zhao, Yuzhong and Zhang, Yingya and Ye, Qixiang and Wan, Fang},
journal={arXiv preprint arXiv:2411.19108},
year={2024}
}
```
## Acknowledgements
We would like to thank the contributors to the [Open-Sora](https://github.com/hpcaitech/Open-Sora), [Open-Sora-Plan](https://github.com/PKU-YuanGroup/Open-Sora-Plan), [Latte](https://github.com/Vchitect/Latte), [CogVideoX](https://github.com/THUDM/CogVideo) and [VideoSys](https://github.com/NUS-HPC-AI-Lab/VideoSys).