metadata

title: AI-powered ASL text-to-video Generator
emoji: 🐻
colorFrom: blue
colorTo: yellow
sdk: gradio
sdk_version: 5.34.2
app_file: app.py
pinned: false
license: apache-2.0

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

AI-SL API

Convert text documents to American Sign Language (ASL) videos using AI.

Video Output Options

The Gradio interface provides multiple ways for users to receive and download the generated ASL videos:

1. R2 Cloud Storage (Recommended)

Videos are automatically uploaded to Cloudflare R2 storage
Returns a public URL that users can download directly
Videos persist and can be shared via URL
Includes a styled download button in the interface

2. Base64 Encoding (Alternative)

Videos are embedded as base64 data directly in the response
No external storage required
Good for smaller videos or when you want to avoid cloud storage
Can be downloaded directly from the interface

3. Programmatic Access

Users can access the video output programmatically using:

from gradio_client import Client

# Connect to the running interface
client = Client("http://localhost:7860")

# Upload a document and get results
result = client.predict(
    "path/to/document.pdf",
    api_name="/predict"
)

# The result contains: (json_data, video_output, download_html)
json_data, video_url, download_html = result

# Download the video
import requests
response = requests.get(video_url)
with open("asl_video.mp4", "wb") as f:
    f.write(response.content)

4. Direct Download from Interface

The interface includes a styled download button
Users can right-click and "Save As" if automatic download doesn't work
Video files are named asl_video.mp4 by default

Example Usage

See example_usage.py for complete examples of how to:

Download videos from URLs
Process base64 video data
Use the interface programmatically
Perform further video processing

Requirements

Python 3.7+
Required packages listed in requirements.txt
Cloudflare R2 credentials (for cloud storage option)
Supabase credentials for video database

Setup

Install dependencies: pip install -r requirements.txt
Set up environment variables in .env file
Run the interface: python app.py

Video Processing

Once you have the video file, you can:

Upload to YouTube, Google Drive, or other services
Analyze with OpenCV for computer vision tasks
Convert to different formats
Extract frames for further processing
Add subtitles or overlays