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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


You probably want to download a pretrained model.


And extract to share/vacuum/model.


$ 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.


$ vacuum-clean dirty.fits psf.fits


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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