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Code Issues 6 Releases Activity

script notes, etc.

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@ -68,7 +68,8 @@ The main AI/ML development is being done in Jupyter.
# Jupyter
There Jupyter Lab Notebook files in the `notebooks/` subdirectory.
These are producing usable results.
These are producing usable results. Voila is used to convert
Jupyter notebooks into websites.
* `wut.ipynb` --- Machine learning Python script using Tensorflow and Keras in a Jupyter Notebook.
* `wut-predict.ipynb` --- Make prediction (rating) of observation from pre-existing model.
@ -116,6 +117,8 @@ The following scripts are in the repo.
# Installation
Installation notes...
There's more docs on a few different setups in the `docs/` subdir.
## Setup
The scripts use files that are ignored in the git repo.
So you need to create those directories:
@ -337,48 +340,6 @@ mkdir download
rsync -ultav rsync://ml.spacecruft.org/download/ download/
```
# TODO / Brainstorms
This is a first draft of how to do this. The actual machine learning
process hasn't been looked at at all, except to get it to generate
an answer. It has a long ways to go. There are also many ways to do
this besides using Tensorflow and Keras. Originally, I considered
using OpenCV. Ideas in no particular order below.
## General
General considerations.
* Use Open CV.
* Use something other than Tensorflow / Keras.
* Do mirror of `network.satnogs.org` and do API calls to it for data.
* Issues are now available here:
* https://spacecruft.org/spacecruft/satnogs-wut/issues
## Tensorflow / Keras
At present Tensorflow and Keras are used.
* Learn Keras / Tensorflow...
* What part of image is being evaluated?
* Re-evaluate each step.
* Right now the prediction output is just "good" or "bad", needs
"failed" too.
* Give confidence score in each prediction.
* Visualize what ML is looking at.
* Separate out good/bad/failed by satellite, transmitter, or encoding.
This way "good" isn't considering a "good" vetting to be a totally
different encoding. Right now, it is considering as good observations
that should be bad...
* If it has a low confidence, return "unknown" instead of "good" or "bad".
# Caveats
This is the first artificial intelligence script I've done,
I know little about radio and less about satellites,