Pravin Barapatre
Pin dependencies for Hugging Face Spaces compatibility and remove submodule issue
db8251f
#!/usr/bin/env python3
"""
Demo script for text-to-video generation
This script demonstrates how to use the text-to-video generator with a simple example.
"""
import os
import sys
from simple_generator import generate_video_from_text
def main():
print("Text-to-Video Generation Demo")
print("=" * 40)
# Demo prompt
demo_prompt = "A beautiful butterfly flying through a colorful garden with flowers"
print(f"Generating video for prompt: '{demo_prompt}'")
print("This may take a few minutes depending on your hardware...")
print()
try:
# Generate video with default settings
output_path = generate_video_from_text(
prompt=demo_prompt,
model_id="damo-vilab/text-to-video-ms-1.7b", # Fast model for demo
num_frames=16,
fps=8,
num_inference_steps=20, # Reduced for faster demo
guidance_scale=7.5,
seed=42, # Fixed seed for reproducible demo
output_path="demo_video.mp4"
)
print("=" * 40)
print("Demo completed successfully!")
print(f"Video saved as: {output_path}")
print()
print("You can now:")
print("1. Open the video file to view the result")
print("2. Run 'python text_to_video.py' for the web interface")
print("3. Try different prompts with 'python simple_generator.py'")
except Exception as e:
print(f"Error during demo: {str(e)}")
print()
print("Troubleshooting tips:")
print("- Make sure all dependencies are installed: pip install -r requirements.txt")
print("- Check if you have sufficient disk space")
print("- Ensure you have a stable internet connection for model download")
print("- Try running with CPU if GPU memory is insufficient")
return 1
return 0
if __name__ == "__main__":
exit(main())