Astrophilia 🌌

Astrophilia - A cutting-edge web application for classifying celestial objects using machine learning.

📖 About

Astrophilia, derived from "astro" (cosmos) and "philia" (deep love or affinity), is a revolutionary website that enables users to identify celestial objects through an innovative coordinate-based classification system. By inputting celestial coordinates and photometric data, users can instantly determine whether a celestial entity is a Galaxy, Star, or Quasar (QSO).

The application leverages advanced machine learning algorithms and astronomical databases to categorize celestial objects with precision, offering astronomers and space enthusiasts a streamlined approach to exploring the cosmos.

✨ Features

• Celestial Object Classification: Classify astronomical objects using Right Ascension (RA), Declination (Dec), and photometric magnitudes (u, g, r, i, z filters)
• Educational Content:
  • Astronomical vocabulary section explaining key concepts
  • Detailed information about stars, galaxies, quasars, and black holes
  • Classification methodology explanation
• Interactive User Interface: Modern, user-friendly web interface
• Machine Learning Backend: Decision tree model for accurate celestial object classification
• Real-time Predictions: Instant classification results

🛠️ Technology Stack

• Frontend: HTML5, CSS3
• Backend: Python Flask
• Machine Learning: scikit-learn (Decision Tree Classifier)
• Model Persistence: joblib

📁 Project Structure

mon site web/
├── index.html              # Main landing page
├── About_Us.html           # About Astrophilia
├── astro_vocab.html        # Astronomical vocabulary
├── how_classify!.html      # Classification methodology
├── contact.html            # Contact page
├── FH.html                 # Additional page
├── GO1.html                # Classification interface
├── main.py                 # Flask application backend
├── decisionTree.joblib     # Trained ML model
├── style.css               # Main stylesheet
├── style1.css - style7.css # Additional stylesheets
├── static/                 # Static assets
│   ├── image/              # Images for the website
│   └── style*.css          # CSS files
└── image/                  # Additional images

🚀 Getting Started

Prerequisites

• Python 3.x
• pip (Python package manager)

Installation

1. Clone or download the project

   cd "mon site web"

2. Install required Python packages

   pip install flask joblib scikit-learn

3. Ensure the ML model file exists

   • Make sure decisionTree.joblib is present in the project directory

Running the Application

1. Start the Flask server

   python main.py

2. Access the application

   • Open index.html in your web browser to view the landing page
   • Click the "GO" button to access the classification tool at http://127.0.0.1:5000

📊 Classification Parameters

The classification system uses the following astronomical parameters:

• RA (Right Ascension): Celestial longitude coordinate
• Dec (Declination): Celestial latitude coordinate
• u, g, r, i, z: Photometric magnitudes measured through different color filters
  • u: Ultraviolet
  • g: Green
  • r: Red
  • i: Near-infrared
  • z: Infrared

🌟 Celestial Object Types

Galaxy

Massive collections of stars, gas, dust, and dark matter held together by gravity. Extended objects with faint overall brightness and minimal variation across color filters.

Star

Luminous spheres of plasma sustained by gravity. Point-like sources with significant brightness across most filters.

QSO (Quasar)

Quasi-stellar objects - extremely luminous active galactic nuclei powered by supermassive black holes. Objects with extremely high redshifts and unusual spectral features.

🎓 Educational Resources

The website includes:

• AstroVocab: Comprehensive astronomical terminology and definitions
• How We Classify: Detailed explanation of the classification methodology
• About Us: Background information about the Astrophilia project

📝 Usage Example

1. Navigate to the main page (index.html)
2. Click on "GO" to access the classification tool
3. Enter the celestial coordinates and magnitude values:
   • RA (Right Ascension)
   • Dec (Declination)
   • u, g, r, i, z filter magnitudes
4. Submit the form to receive the classification result

🔧 Development Notes

• The Flask application runs on http://127.0.0.1:5000 by default
• The application uses a pre-trained Decision Tree model stored in decisionTree.joblib
• Multiple CSS files are used for different page styling
• Static assets are organized in the static/ directory

🤝 Contributing

This is an educational and research-oriented project. Contributions to improve the classification model, user interface, or educational content are welcome.

📧 Contact

For inquiries or feedback, please use the Contact Us page on the website.

🌠 Acknowledgments

This project combines the power of machine learning with the wonder of astronomy to make celestial object classification accessible to everyone passionate about exploring the cosmos.

---

Astrophilia - Embark on a journey of discovery and awe-inspiring exploration of the cosmos! 🚀✨