README.md

# TimeChat: Docker Environment Setup (CUDA 12.1, Ubuntu 22.04, Python 3.10, PyTorch 2.1.2)

## 📖 Overview

This project provides a Dockerized environment to run the Python-based TimeChat application with GPU acceleration, using:

- CUDA 12.1  
- Ubuntu 22.04  
- Python 3.10  
- PyTorch 2.1.2

Original repository:  
[https://github.com/RenShuhuai-Andy/TimeChat](https://github.com/RenShuhuai-Andy/TimeChat)

## 🧱 Prerequisites

- Docker and NVIDIA Container Toolkit must be installed
- A Linux machine with a compatible NVIDIA GPU and drivers
- `TimeChat` and `ckpt` directories must be present in the current working directory

## 📥 Clone the Repository

Clone the required repository and initialize Git LFS:

```
git lfs install
git clone https://huggingface.co/Bio-sensing/video_captioning_ubicomp_student_challenge
```

Make sure the TimeChat directory is properly set up.


## 🔨 Build the Docker Image

Build the Docker image using the following command:

```
docker build -t cuda121_ubuntu2204_python310_torch212 -f Dockerfile_cuda121_ubuntu2204_python310_torch212 .
```


## 🚀 Run the Docker Container

Run the container with GPU access and volume mounting:

```
docker run -it --name "timechat" --gpus all \
    -v $(pwd)/TimeChat:/home/TimeChat \
    -v $(pwd)/ckpt:/home/ckpt/ \
    -p 12354:12354 -p 12355:12355 \
    cuda121_ubuntu2204_python310_torch212 bash

```


## 💻 Launch Jupyter Lab

Inside the container, execute the following:

```
cd /home/
jupyter-lab --ip 0.0.0.0 --port=12354 --allow-root --no-browser --ContentsManager.allow_hidden=True &


```


Then, open the following URL in your browser on the host machine:


```
http://localhost:12354
```


You can verify the environment and functionality by opening and running ` demo.ipynb ` .