This repository contains an updated version of Brut (https://github.com/ChrisBeaumont/brut) used in the paper

Assessing the Performance of a Machine Learning Algorithm in Identifying Bubbles in Dust Emission, ApJ in press (arXiv link)*

We make slight changes on the modules that Brut import. The current version Brut can be successfully run with the following libraries

• astropy '2.0.2'
• h5py '2.7.0'
• matplotlib '2.0.2'
• numpy '1.13.3'
• scipy '1.0.0'
• skimage '0.13.0'
• sklearn '0.19.1'
• cloud '2.8.5'

We update the retrained model in models/ directory.

Contains the original training model and the model retrained on synthetic images and the orignial traning set. The synthetic bubble images can be found here (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/OSMNDG).