Repository for Lumos, a code for extracting photometry from astronomical images with neural networks.
The code performs the following steps:
- Creates image cutouts around the positions given externaly
- Evaluates Lumos on the galaxy cutout
A further script named 'lumos_train' allows to train the network from scratch with any data set. This requires a set of N training cutouts of 60x60 pixels and their profiles.
Clone the respository and write
pip install -e .
after entering into the cloned directory.
Examples are available in examples/integration_example_internalDB.ipynb and examples/integration_example_externalDB.ipynb
examples/integration_example_internalDB.ipynb works only for users with access to the PAUS DB examples/integration_example_externalDB.ipynb works for everybody
For the example external to the database, the user needs to download a reduced PAUS image example. This is available at ://www.pausurvey.org/pausurvey/data-processing/
An example of trained model is also available at the examples directory.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 776247 EWC.