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[Karm-Dave]

#536

Star-Galaxy Classification Model

Description

This PR implements a Convolutional Neural Network (CNN) based classification system for distinguishing between stars and galaxies in astronomical images. The system is built using TensorFlow and includes comprehensive metrics visualization and analysis tools.

Changes Made

• Created modular project structure with clear separation of concerns
• Implemented data loading and preprocessing pipeline
• Added CNN model architecture with configurable parameters
• Created comprehensive visualization and metrics generation
• Added environment setup files and documentation
• Organized training pipeline in main.py

Results

The training process will generate the following in the results/ directory:

• Training history plots (accuracy and loss curves)
• Confusion matrix visualization
• ROC curve
• Precision-Recall curve
• Classification report in text format
• Saved model file (model.h5)

Dependencies

• Python 3.8+
• TensorFlow 2.12.0
• scikit-learn 1.2.2
• OpenCV 4.7.0.72
• NumPy 1.23.5
• Matplotlib 3.7.1
• Seaborn 0.12.2
• Pandas 2.0.0

Testing

The code has been tested on:

• Linux Ubuntu 20.04

[github-actions]

👋 Thank you for opening this pull request! We appreciate your contribution to improving this project. Your PR is under review, and we'll get back to you shortly.
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To help move the process along, please tag @UppuluriKalyani, @Neilblaze, and @SaiNivedh26 for a faster review!

[github-actions]

🎉🎉 Thank you for your contribution! Your PR #606 has been merged! 🎉🎉