comet-hunter 0.2.1

Astronomical image ingestion and processing system for Sungrazer project

Comet Hunter

Comet Hunter is an automated astronomical image ingestion and processing system designed to assist in the discovery of sungrazing comets from SOHO LASCO imagery.

About The Project

NASA's Sungrazer Project enables the discovery and reporting of comets visible from the SOHO and STEREO satellites. To date, over five thousand comets have been discovered using the SOHO satellite. On board SOHO is the LASCO coronagraph, which consists of two telescopes — C2 and C3. Images from these telescopes are primarily used for reporting new comets.

Why This Exists?

For comet discovery, users rely on fragmented tools for downloading, processing, and reviewing imagery. There is no unified platform that automates the complete workflow from raw image availability to chronological playback of processed frames. Comet Hunter aims to bridge this gap.

Present Challenges

• RAW images must be processed before becoming usable
• Sungrazer comets are often indistinguishable in single frames
• Chronological playback significantly improves detectability
• Most comets are reported within minutes of data availability.
• Time is critical.

The problem is not merely detection - it is rapid detection.

This requires a robust automation of the complete workflow: from RAW image ingestion to chronological playback of processed frames.

Current Capabilities

• Downlink slot synchronization
• Metadata ingestion from LASCO sources
• Parallel RAW image downloading
• Image processing pipelines for C2/C3
• Time-indexed frame retrieval
• REST API backend
• Scheduler-driven ingestion workflows
• Interactive frontend visualization

User Interface

Getting Started

End User Installation

Install Comet Hunter directly from PyPI:

pip install comet-hunter

End User Commands

Start the application

comet-hunter start

Check application status

comet-hunter status

Stop the application

comet-hunter stop

Note

When started, the application will be available at:

http://localhost:8080

Application data, logs, and database files are stored in:

Windows:
C:\Users\<username>\.comet_hunter

Linux/macOS:
~/.comet_hunter

Development Setup

Clone Repository

git clone https://github.com/AnandKri/comet-hunter.git
cd comet-hunter

Create Virtual Environment

Linux/macOS

python -m venv .venv
source .venv/bin/activate

Windows

python -m venv .venv
.venv\Scripts\activate

Install Dependencies

pip install -r requirements.txt

Run Backend

uvicorn backend.main:app --reload

Run Frontend

python frontend/app.py

Documentation

View full documentation here