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.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file vacuum-cleaner-0.3.tar.gz.
File metadata
- Download URL: vacuum-cleaner-0.3.tar.gz
- Upload date:
- Size: 14.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.1.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | e1d5f0edef6a5585ed81c18e4faa432205e85df687e7a85a53179774fcdf2b62 |
|
| MD5 | 8cfa56510dac93d49f5b7cbcd8fdf846 |
|
| BLAKE2b-256 | aa5af3993e386c3806ed792303004e750d45950f37f6284b65d02b3424a9d7a6 |
File details
Details for the file vacuum_cleaner-0.3-py2.py3-none-any.whl.
File metadata
- Download URL: vacuum_cleaner-0.3-py2.py3-none-any.whl
- Upload date:
- Size: 31.5 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.1.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | e03c8b1d661073469aaf795c871ecc150a346859149355759ef664a8af98f2f9 |
|
| MD5 | ea251c49f8310747db34f4d40b1f6482 |
|
| BLAKE2b-256 | 5efdf0c13ab30d162ebb9dee304c2f7a285b915ca7767327de4fd178d9f14235 |
