2020-01-01 23:12:46 -07:00
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# satnogs-wut
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2020-01-02 16:44:03 -07:00
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The goal of satnogs-wut is to have a script that will take an
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observation ID and return an answer whether the observation is
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"good", "bad", or "failed".
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2020-01-02 16:51:29 -07:00
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![Good Observation](pics/waterfall-good.png)
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![Bad Observation](pics/waterfall-bad.png)
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![Failed Observation](pics/waterfall-failed.png)
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2020-01-02 16:44:03 -07:00
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# Machine Learning
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The system at present is build upon the following:
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* Debian
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2020-01-01 23:18:12 -07:00
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* Tensorflow
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* Keras
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Learning/Testing, results are inaccurate.
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2020-01-02 16:44:03 -07:00
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# wut?
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The following scripts are in the repo:
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* `wut` --- Feed it an observation ID and it returns if it is a "good", "bad", or "failed" observation.
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* `wut-api-test` --- API Tests.
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* `wut-get-obs` --- Download the JSON for an observation ID.
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* `wut-get-staging` --- Download waterfalls to staging for review (deprecated).
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* `wut-get-train-bad` --- Download waterfalls to `data/train/bad` for review (deprecated).
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* `wut-get-train-good` --- Download waterfalls to `data/train/good` for review (deprecated).
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* `wut-get-validation-bad` --- Download waterfalls to `data/validation/bad` for review (deprecated).
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* `wut-get-validation-good` --- Download waterfalls to `data/validation/good` for review (deprecated).
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* `wut-get-waterfall` --- Download waterfall for an observation ID to `download/[ID]`.
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* `wut-get-waterfall-range` --- Download waterfalls for a range of observation IDs to `download/[ID`.
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* `wut-ml` --- Main machine learning Python script using Tensorflow and Keras.
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* `wut-review-staging` --- Review all images in `data/staging`.
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# Source License / Copying
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2020-01-01 23:18:12 -07:00
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GPLv3+
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2020-01-02 16:44:03 -07:00
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Copyright (C) 2019, 2020
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