# satnogs-wut

The goal of satnogs-wut is to have a script that will take an
observation ID and return an answer whether the  observation is
"good", "bad", or "failed".

## Good Observation
![Good Observation](pics/waterfall-good.png)

## Bad Observation
![Bad Observation](pics/waterfall-bad.png)

## Failed Observation
![Failed Observation](pics/waterfall-failed.png)

# Machine Learning
The system at present is build upon the following:

* Debian

* Tensorflow

* Keras


Learning/Testing, results are inaccurate.


# wut?
The following scripts are in the repo:

* `wut` --- Feed it an observation ID and it returns if it is a "good", "bad", or "failed" observation.
* `wut-api-test` --- API Tests.
* `wut-get-obs` --- Download the JSON for an observation ID.
* `wut-get-staging` --- Download waterfalls to staging for review (deprecated).
* `wut-get-train-bad` --- Download waterfalls to `data/train/bad` for review (deprecated).
* `wut-get-train-good` --- Download waterfalls to `data/train/good` for review (deprecated).
* `wut-get-validation-bad` --- Download waterfalls to `data/validation/bad` for review (deprecated).
* `wut-get-validation-good` --- Download waterfalls to `data/validation/good` for review (deprecated).
* `wut-get-waterfall` --- Download waterfall for an observation ID to `download/[ID]`.
* `wut-get-waterfall-range` --- Download waterfalls for a range of observation IDs to `download/[ID`.
* `wut-ml` --- Main machine learning Python script using Tensorflow and Keras.
* `wut-review-staging` --- Review all images in `data/staging`.


# Source License / Copying
GPLv3+


Copyright (C) 2019, 2020