🛰️ Star Classifier: Predict Stellar Types from Astronomical Data

Star Classifier is an interactive web application built using Flask that allows users to predict the type of a star based on its astronomical properties such as temperature, luminosity, radius, magnitude, color, and spectral class.

The model is trained to classify stars into one of six categories:

• 🌑 Brown Dwarf
• 🔴 Red Dwarf
• ⚪ White Dwarf
• ☀️ Main Sequence
• 🌟 Supergiant
• 💥 Hypergiant

Each prediction is accompanied by an informative description, fun facts, and a dynamically displayed animation-style video to help users visualize the star type!

---

🧠 Machine Learning Model

The backend uses a Voting Classifier composed of several base models (like Decision Trees, KNN, and Random Forests). The model is trained on a balanced dataset with features encoded to match the trained environment.

---

🌌 Preview

---

⚙️ Installation & Setup

🔧 Requirements

• Python 3.7+
• Flask
• NumPy
• Scikit-learn
• Pickle

💻 Clone the Repository

git clone https://github.com/your-username/star-classifier.git
cd star-classifier

📦 Install Dependencies

We recommend using a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

📂 Project Structure

star-classifier/
│
├── static/
│   └── videos/               # MP4 videos named after star types (e.g., Brown_Dwarf.mp4)
│
├── templates/
│   └── index.html            # Frontend form + canvas animation + star info
│
├── voting_classifier_model.pkl  # Trained model
├── app.py                    # Flask backend
├── README.md                 # This file
└── requirements.txt          # Python dependencies

🚀 Run the Application

python app.py

Then visit: http://127.0.0.1:5000 in your browser.

---

🖼️ Video Assets

Place your video files inside the static/videos/ folder, with filenames exactly matching the star prediction labels:

• Brown_Dwarf.mp4
• Red_Dwarf.mp4
• White_Dwarf.mp4
• Main_Sequence.mp4
• Super_Giants.mp4
• Hyper_Giants.mp4

---

💻 Tech Stack

• Frontend: HTML5, JavaScript, CSS (Canvas animations)
• Backend: Python, Flask
• ML Libraries: scikit-learn, NumPy
• Visualization: HTML5 Video & JSON-driven UI updates

---

🤝 Example Usage

Cosmic.Classifier.-.Star.Type.Prediction.-.Google.Chrome.2025-04-13.01-45-03.online-video-cutter.com.mp4

🤝 Contributing

1. Fork this repository
2. Create a new branch (git checkout -b feature-name)
3. Commit your changes (git commit -am 'Add feature')
4. Push to the branch (git push origin feature-name)
5. Create a Pull Request

---

📄 License

This project is licensed under the MIT License.