Running the Pipeline
Import data sources:
This by default uses the SWIRE catalogue. For using the WISE catalogue:
crowdastro import_data --ir wise
Process the consensuses:
Generate the training data:
The training data contains
labels. Note that image features have not been processed — these are raw pixels.
Generate the training and testing sets:
Generate a model:
Train the CNN:
Generate the CNN outputs:
This adds the
features dataset to the training HDF5 file.
The experiments in
crowdastro.experiment can now be run as command-line scripts:
python3 -m crowdastro.experiment.experiment_name
The files generated by the pipeline can also be used directly to train and test
classifiers. See the files in the
crowdastro.experiment module for examples.