A computer vision package for planetary GIS data and using neural networks
Project description
Steren
Steren is an open-source Python package for analyzing planetary surfaces using artificial intelligence. It helps researchers and developers efficiently search, download, slice, and detect features in planetary imagery.
✨ Features
🔎 Search
Discover and scan the web for the latest publicly available planetary datasets.
⬇️ Download
Easily retrieve and manage high-resolution planetary surface imagery.
🧠 Detect
Apply AI-powered object detection to identify features and structures across large planetary images.
🧩 Slice
Divide massive planetary surface images into smaller, manageable tiles for training, testing, and evaluation of AI models.
🌍 Use Cases
- Planetary science research
- Surface feature detection (craters, rocks, anomalies)
- Dataset preparation for machine learning
- Automated analysis of remote sensing imagery
🛠 Installation
PyPI
pip install steren
From Source (with Conda)
conda env create -f environment.yml
conda activate steren
git clone https://github.com/jbr819/steren.git
cd steren
pip install -e .
💻 CLI
Steren comes with a straightforward command-line interface (CLI).
You can quickly explore all available commands by running:
steren
Acknowledgements
Developed during a PhD student internship at the Natural History Museum, London through the BBSRC Professional Internships for PhD Students (PIPS).
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