From bd2247708ab602ce14fe53741013008074ded6e9 Mon Sep 17 00:00:00 2001 From: cv server Date: Thu, 2 Jan 2020 17:11:16 -0700 Subject: [PATCH] usage stub --- README.md | 37 +++++++++++++++++++++++++++++++++++-- 1 file changed, 35 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index d677668..45882ec 100644 --- a/README.md +++ b/README.md @@ -17,9 +17,7 @@ observation ID and return an answer whether the observation is The system at present is build upon the following: * Debian - * Tensorflow - * Keras @@ -43,8 +41,43 @@ The following scripts are in the repo: * `wut-review-staging` --- Review all images in `data/staging`. +# Usage +The main purpose of the script is to evaluate an observation, +but to do that, it needs to build a corpus of observations to +learn from. So many of the scripts in this repo are just for +downloading and managing observations. + + +The following steps need to be performed: + +1. Download waterfalls and JSON descriptions with `wut-get-waterfall-range`. + These get put in the `downloads/[ID]/` directories. + +1. Organize downloaded waterfalls into categories (e.g. "good", "bad", "failed"). + Note: this needs a script written. + Put them into their respective directories under: +* `data/train/good/` +* `data/train/bad/` +* `data/train/failed/` +* `data/validation/good/` +* `data/validataion/bad/` +* `data/validataion/failed/` + +1. Use machine learning script `wut-ml` to build a model based on + the files in the `data/train` and `data/validation` directories. + +1. Rate an observation using the `wut` script. + + +# Caveats +This is the first machine learning script I've done, +I know little about satellites and less about radio, +and I'm not a programmer. + + # Source License / Copying Main repository is available here: + * https://spacecruft.org/spacecruft/satnogs-wut