# 视频Caption
通常,大多数视频数据不带有相应的描述性文本,因此需要将视频数据转换为文本描述,以提供必要的训练数据用于文本到视频模型。
## 项目更新
- 🔥🔥 **News**: ```2024/9/19```: CogVideoX 训练过程中用于将视频数据转换为文本描述的 Caption
模型 [CogVLM2-Caption](https://huggingface.co/THUDM/cogvlm2-llama3-caption)
已经开源。欢迎前往下载并使用。
## 通过 CogVLM2-Caption 模型生成视频Caption
🤗 [Hugging Face](https://huggingface.co/THUDM/cogvlm2-llama3-caption) | 🤖 [ModelScope](https://modelscope.cn/models/ZhipuAI/cogvlm2-llama3-caption/)
CogVLM2-Caption是用于生成CogVideoX模型训练数据的视频caption模型。
### 安装依赖
```shell
pip install -r requirements.txt
```
### 运行caption模型
```shell
python video_caption.py
```
示例:
## 通过 CogVLM2-Video 模型生成视频Caption
[Code](https://github.com/THUDM/CogVLM2/tree/main/video_demo) | 🤗 [Hugging Face](https://huggingface.co/THUDM/cogvlm2-video-llama3-chat) | 🤖 [ModelScope](https://modelscope.cn/models/ZhipuAI/cogvlm2-video-llama3-chat) | 📑 [Blog](https://cogvlm2-video.github.io/) | [💬 Online Demo](http://cogvlm2-online.cogviewai.cn:7868/)
CogVLM2-Video 是一个多功能的视频理解模型,具备基于时间戳的问题回答能力。用户可以输入诸如 `Describe this video in detail.` 的提示语给模型,以获得详细的视频Caption:
用户可以使用提供的[代码](https://github.com/THUDM/CogVLM2/tree/main/video_demo)加载模型或配置 RESTful API 来生成视频Caption。
## Citation
🌟 If you find our work helpful, please leave us a star and cite our paper.
CogVLM2-Caption:
```
@article{yang2024cogvideox,
title={CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer},
author={Yang, Zhuoyi and Teng, Jiayan and Zheng, Wendi and Ding, Ming and Huang, Shiyu and Xu, Jiazheng and Yang, Yuanming and Hong, Wenyi and Zhang, Xiaohan and Feng, Guanyu and others},
journal={arXiv preprint arXiv:2408.06072},
year={2024}
}
```
CogVLM2-Video:
```
@article{hong2024cogvlm2,
title={CogVLM2: Visual Language Models for Image and Video Understanding},
author={Hong, Wenyi and Wang, Weihan and Ding, Ming and Yu, Wenmeng and Lv, Qingsong and Wang, Yan and Cheng, Yean and Huang, Shiyu and Ji, Junhui and Xue, Zhao and others},
journal={arXiv preprint arXiv:2408.16500},
year={2024}
}
```