Deep Vacuum Cleaner
Project description
Deep Vacuum Cleaner
Radio telescope deconvolution based using a Conditional Generative Adversarial Deep Network.
Based on pix2pix-tensorflow
Whch is based on pix2pix by Isola et al.
Article about this implemention
preparations
You probably want to download a pretrained model.
download:
http://repo.kernsuite.info/vacuum/model.tar.xz
And extract to share/vacuum/model.
Setup
$ pip install vacuum-cleaner
or if you want to try the GPU accelerated version:
$ pip install "vacuum-cleaner[gpu]"
But the tensorflow-gpu package is not the most portable package available.
Usage
$ vacuum-clean dirty.fits psf.fits
Training
Have a look at vacuum-train --help or at the source. Intended to be trained with
spiel as training data generator.
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