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#!/usr/bin/env python3
"""
Script to deploy the Watermark Leaderboard to Hugging Face Spaces
"""
import os
import shutil
import json
from pathlib import Path
def copy_files_to_hf_directory():
"""Copy necessary files to the Hugging Face deployment directory"""
# Files to copy from the main project
source_dir = Path("../")
hf_dir = Path(".")
# Essential files for Hugging Face deployment
files_to_copy = [
"app.py",
"requirements.txt",
"README.md",
"leaderboard.json"
]
# Copy Reproducibility folder if it exists
reproducibility_source = source_dir / "Reproducibility"
if reproducibility_source.exists():
reproducibility_dest = hf_dir / "Reproducibility"
if reproducibility_dest.exists():
shutil.rmtree(reproducibility_dest)
shutil.copytree(reproducibility_source, reproducibility_dest)
print("✅ Copied Reproducibility folder")
# Copy individual files
for file_name in files_to_copy:
source_file = source_dir / file_name
dest_file = hf_dir / file_name
if source_file.exists():
shutil.copy2(source_file, dest_file)
print(f"✅ Copied {file_name}")
else:
print(f"⚠️ {file_name} not found in source directory")
print("\n🎉 Files copied successfully!")
print("\nNext steps:")
print("1. Create a new Hugging Face Space")
print("2. Upload all files in this directory")
print("3. Set the Space to use Gradio SDK")
print("4. Your leaderboard will be live!")
def create_hf_readme():
"""Create a Hugging Face specific README"""
readme_content = """---
title: Watermark Leaderboard
emoji: 🏆
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: "4.44.0"
app_file: app.py
pinned: false
license: mit
short_description: Interactive leaderboard for watermark performance evaluation
---
# Watermark Leaderboard 🏆
An interactive leaderboard for comparing watermark performance across different models and evaluation settings.
## Features
- **Interactive Scatter Plot**: Visualize watermark performance with Plotly charts
- **Performance Table**: Detailed metrics with sorting and filtering
- **Multiple Evaluation Settings**: Attack-free, Watermark Removal, and Stealing Attack
- **Model Support**: LLaMA3 and DeepSeek models
- **Dynamic Filtering**: Real-time updates based on model and metric selection
- **Flexible Submissions**: Submit data for any combination of attack types
- **Pending Approval System**: All submissions reviewed before appearing on leaderboard
- **Complete Field Visibility**: Administrators see all submission details for review
- **Professional UI**: Clean, modern interface with accordion sections
- **Reproducibility**: Access to all evaluation codes and guidelines
## How to Use
1. **Select Model**: Choose between LLaMA3 or DeepSeek
2. **Choose Setting**: Pick from Attack-free, Watermark Removal, or Stealing Attack
3. **View Results**: Explore the scatter plot and detailed table
4. **Submit Data**: Click "Add Your Data" to submit new results
- Submit any combination of attack types (Attack-free, Watermark Removal, Stealing Attack)
- All submissions go through approval process before appearing on leaderboard
5. **Administrator Review**: Administrators can review pending submissions with full field visibility
## Metrics Explained
- **Normalized Utility ↑**: Higher values indicate better text quality
- **Detection Rate (%) ↑**: Higher values indicate better watermark detection
- **Absolute Utility Degradation ↑**: Higher values indicate better resistance to removal attacks
- **Adversary BERT Score ↑**: Higher values indicate better performance under adversarial conditions
## Contributing
We encourage researchers to contribute their evaluation results. Please follow the guidelines in the "Guidelines" section for submission requirements.
## License
MIT License
---
*Last updated: December 2024*
"""
with open("README.md", "w", encoding="utf-8") as f:
f.write(readme_content)
print("✅ Created Hugging Face README.md")
def main():
"""Main deployment function"""
print("🚀 Preparing Watermark Leaderboard for Hugging Face deployment...")
# Create HF README
create_hf_readme()
# Copy files
copy_files_to_hf_directory()
print("\n📋 Deployment Checklist:")
print("✅ All files prepared")
print("✅ Requirements.txt updated")
print("✅ README.md created for Hugging Face")
print("✅ Reproducibility codes included")
print("\n🌐 Ready for Hugging Face Spaces deployment!")
if __name__ == "__main__":
main()
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