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# Video Caption | |
Typically, most video data does not come with corresponding descriptive text, so it is necessary to convert the video | |
data into textual descriptions to provide the essential training data for text-to-video models. | |
## Update and News | |
- π₯π₯ **News**: ```2024/9/19```: The caption model used in the CogVideoX training process to convert video data into text | |
descriptions, [CogVLM2-Caption](https://huggingface.co/THUDM/cogvlm2-llama3-caption), is now open-source. Feel | |
free to download and use it. | |
## Video Caption via CogVLM2-Caption | |
π€ [Hugging Face](https://huggingface.co/THUDM/cogvlm2-llama3-caption) | π€ [ModelScope](https://modelscope.cn/models/ZhipuAI/cogvlm2-llama3-caption/) | |
CogVLM2-Caption is a video captioning model used to generate training data for the CogVideoX model. | |
### Install | |
```shell | |
pip install -r requirements.txt | |
``` | |
### Usage | |
```shell | |
python video_caption.py | |
``` | |
Example: | |
<div align="center"> | |
<img width="600px" height="auto" src="./assests/CogVLM2-Caption-example.png"> | |
</div> | |
## Video Caption via CogVLM2-Video | |
[Code](https://github.com/THUDM/CogVLM2/tree/main/video_demo) | π€ [Hugging Face](https://huggingface.co/THUDM/cogvlm2-video-llama3-chat) | π€ [ModelScope](https://modelscope.cn/models/ZhipuAI/cogvlm2-video-llama3-chat) | π [Blog](https://cogvlm2-video.github.io/) ο½ [π¬ Online Demo](http://cogvlm2-online.cogviewai.cn:7868/) | |
CogVLM2-Video is a versatile video understanding model equipped with timestamp-based question answering capabilities. | |
Users can input prompts such as `Please describe this video in detail.` to the model to obtain a detailed video caption: | |
<div align="center"> | |
<a href="https://cogvlm2-video.github.io/"><img width="600px" height="auto" src="./assests/cogvlm2-video-example.png"></a> | |
</div> | |
Users can use the provided [code](https://github.com/THUDM/CogVLM2/tree/main/video_demo) to load the model or configure a RESTful API to generate video captions. | |
## Citation | |
π 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} | |
} | |
``` |