Yale ASTR 170, Fall 2024

This repository contains the source code for the final project of ASTR 170, Fall 2024.

Authors

• David Chen ([email protected])
• Jonathan Fan ([email protected])
• Bryant Li ([email protected])

Installation

Running the Web Application

To run the web application, you will need to run the following command in the root directory of the project:

yarn install # or npm install

Then, run the following command:

yarn dev

You can then access the web application by navigating to http://localhost:3000 in your web browser.

Running the Model

To run the model, you will need to run the following command in the root directory of the project:

pip install -r requirements.txt

Get the dataset from Kaggle and place it in the model directory.

Then, run the following command:

python create_dataset.py

To run the server, run the following command:

python classify.py

Topic

Our project aims to classify images of galaxies via convolutional neural networks (CNN) by identifying specific visual features and similarities to galaxies of the same type.

Format

The final project will be a web application that takes in image input for galaxy classification. The output will be the type of galaxy identified and a brief explanation of what it is.

Scope Definition

We will train a CNN model to classify whether an uploaded galaxy image is an elliptical, non-barred spiral, barred spiral, or lenticular galaxy.

Technologies Used

• Python
• TensorFlow
• Keras
• Flask
• NumPy
• Next.js
• Tailwind CSS

References

https://astronn.readthedocs.io/en/latest/index.html