Metadata-Version: 2.2
Name: galamo
Version: 0.0.2
Summary: A Python package for classifying galaxy morphologies using deep learning.
Home-page: https://github.com/jdingra11/galamo
Author: Jashanpreet Singh Dingra
Author-email: astrodingra@gmail.com
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Astronomy
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: tensorflow
Requires-Dist: numpy
Requires-Dist: opencv-python
Requires-Dist: joblib
Requires-Dist: matplotlib
Requires-Dist: termcolor
Requires-Dist: requests
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
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Dynamic: requires-dist
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# 🌌 Galamo - Galaxy Morphology Predictor



---

## 🚀 Features

✅ Pre-trained deep learning model for galaxy morphology classification  
✅ Automatic image preprocessing (resizing, normalization, and format conversion)  
✅ Simple and intuitive API requiring only an image file as input  
✅ Supports multiple galaxy morphology types  
✅ Compatible with Python 3.6+

---

## 📥 Installation

### Install from PyPI

To install the package using pip:

```bash
pip install galamo
```

### Install from Source

Alternatively, to install from source:

```bash
git clone https://github.com/jsdingra11/galamo.git
cd galamo
pip install .
```

---

## 📖 Usage Guide

### Import and Initialize the Model

```python
from galamo import galaxy_morph
```

### Predict Galaxy Morphology from an Image

```python
galaxy_morph("galaxy.jpg")
```

### Example Output

```
Predicted Morphology: Spiral Galaxy
```

---

## ⚙️ How It Works

1. Loads a pre-trained deep learning model for galaxy classification.
2. Preprocesses the input image (resizing, RGB conversion, and normalization).
3. Feeds the processed image into the neural network for prediction.
4. Converts the predicted class index to its corresponding galaxy morphology name.

---

## 📋 Requirements

Ensure the following dependencies are installed:

- Python 3.10+
- TensorFlow
- NumPy
- OpenCV
- Joblib
- Matplotlib

---

## 🧠 Model Details

- Trained on a dataset of galaxy images labeled with different morphology types.
- Utilizes a Convolutional Neural Network (CNN) to extract features and classify images.
- Uses a label encoder to map numerical predictions to meaningful class names (e.g., Spiral, Elliptical, Irregular, etc.).

---

## 🤝 Contributing

Galamo welcome contributions! To improve the model or add new features:

1. Fork the repository.
2. Create a feature branch (`git checkout -b feature-name`).
3. Commit your changes (`git commit -m 'Added new feature'`).
4. Push the branch (`git push origin feature-name`).
5. Create a pull request.

---

## 📜 License

This project is licensed under the MIT License – see the LICENSE file for details.

---

## 📬 Contact & Support

👨‍💻 **Author:** Jashanpreet Singh Dingra  
👨‍💻 **Co-Author:** Vikramjeet Singh  
📧 **Email:** [astrodingra@gmail.com](mailto:astrodingra@gmail.com)  
🔗 **GitHub:** [https://github.com/jsdingra11](https://github.com/jsdingra11)

For issues or feature requests, please open an issue on GitHub.

---

🌠 **Galamo - Unveiling the Universe, One Galaxy at a Time!**
