VideoScience

Installation

Basic Setup

# Clone the repository
git clone https://github.com/hao-ai-lab/VideoScience.git
cd VideoScience

# Install dependencies
pip install -r requirements.txt

FastVideo Setup

FastVideo is a video generation provider that supports two modes of operation:

Option 1: Remote API Server (Recommended for Production)

If you have a deployed FastVideo API server:

export FASTVIDEO_API_BASE="http://your-fastvideo-server:8000"
export FASTVIDEO_API_KEY="your-api-key"  # Optional, if authentication is required

Option 2: Local Inference Mode

For local GPU inference:

# Install FastVideo package
pip install fastvideo

# Set the model path (will be downloaded on first use)
export FASTVIDEO_MODEL_PATH="FastVideo/FastWan2.1-T2V-1.3B-Diffusers"

Requirements for local inference:

• CUDA-capable GPU with sufficient VRAM
• PyTorch with CUDA support

Usage

launch batched video generation

1. Download csv data file under data/database/data.csv.
2. Launch script:

bash scripts/batched_generation_using_csv.sh

launch single video generation

1. Launch script:

python3 single_generation_frontend.py --provider {provider_name} --model {model_name} --prompt {customized_prompt}

VLM as a judge

bash judge/batched_evaluate_all_models.sh