File size: 2,343 Bytes
31757cc
 
 
 
 
 
 
 
 
 
 
f2d5ec9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
---
title: Ask-Anything:ChatGPT with Video Understanding
emoji: :movie_camera:
colorFrom: pink
colorTo: green
sdk: gradio
python_version: 3.8.16
app_file: app.py
pinned: false
license: mit
---
# VideoChat

VideoChat is a multifunctional video question answering tool that combines the functions of Action Recognition, Visual Captioning and ChatGPT. Our solution generates dense, descriptive captions for any object and action in a video, offering a range of language styles to suit different user preferences. It supports users to have conversations in different lengths, emotions, authenticity of language.
- Video-Text Generation
- Chat about uploaded video
- Interactive demo

# :fire: Updates

- **2023/04/19**: Code Release

# :speech_balloon: Example

![images](assert/dancing.png)
![images](assert/dancing2.png)

# :running: Usage

```shell
# We recommend using conda to manage the environment and use python3.8.16
conda create -n chatvideo python=3.8.16
conda activate chatvideo

# Clone the repository:
git clone https://github.com/OpenGVLab/Ask-Anything.git
cd ask-anything/video_chat

# Install dependencies:
pip install -r requirements.txt
pip install https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.0.0/en_core_web_sm-3.0.0.tar.gz
python -m pip install 'git+https://github.com/facebookresearch/detectron2.git'

# Download the checkpoints
wget https://huggingface.co/spaces/xinyu1205/Tag2Text/resolve/main/tag2text_swin_14m.pth ./pretrained_models/tag2text_swin_14m.pth
wget https://datarelease.blob.core.windows.net/grit/models/grit_b_densecap_objectdet.pth ./pretrained_models/grit_b_densecap_objectdet.pth
git clone https://huggingface.co/mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback ./pretrained_models/flan-t5-large-finetuned-openai-summarize_from_feedback

# Configure the necessary ChatGPT APIs
export OPENAI_API_KEY={Your_Private_Openai_Key}

# Run the VideoChat gradio demo.
python app.py
```

# Acknowledgement

The project is based on [InternVideo](https://github.com/OpenGVLab/InternVideo), [Tag2Text](https://github.com/xinyu1205/Tag2Text), [GRiT](https://github.com/JialianW/GRiT), [mrm8488](https://huggingface.co/mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback) and [ChatGPT](https://openai.com/blog/chatgpt). Thanks for the authors for their efforts.