Text2Sign: Lightweight Diffusion Model for Sign Language Video Generation

This repository contains the pretrained checkpoint and inference code for the Text2Sign model, a lightweight diffusion-based architecture for generating sign language videos from text prompts.

Model Overview

• Architecture: 3D UNet backbone with DiT (Diffusion Transformer) blocks and a custom Transformer-based text encoder.
• Dataset: Trained on How2Sign (ASL) video-text pairs.
• Resolution: 64x64 RGB, 16 frames per clip.
• Checkpoint: Provided at epoch 70.

Files

• checkpoint_epoch_70.pt — Pretrained model weights
• config.py — Model and generation configuration
• inference.py — Example script for generating sign language videos from text

Usage

1. Install dependencies:

   pip install torch torchvision pillow matplotlib
   

2. Run the inference script:

   python inference.py --prompt "Hello world"
   

   This will generate a video for the given prompt and save a filmstrip image.

License

MIT