caching, downloads ...

README.md

@@ -119,6 +119,16 @@ The following steps need to be performed:
 
 1. Rate an observation using the `wut` script.
 
+# Data Caching Downloads
+The scripts are designed to not download a waterfall or make a JSON request
+for an observation it has already requested. The first time an observation
+is requested, it is downloaded from the SatNOGS network to the `download`
+directory. That `download` directory is the download cache. 
+
+
+The `data` directory is just temporary files,mostly linked from the
+`downloads` directory. Files in the `data` directory are deleted by many
+scripts, so don't put anything you want to keep in there.
 
 # Caveats
 This is the first machine learning script I've done,

wut-dl-sort

@@ -21,9 +21,9 @@ OBSIDMIN="$1"
 OBSIDMAX="$2"
 OBSID=$OBSIDMIN
 
-# First make sure we have the range all downloaded:
-echo "Downloading Waterfalls"
-./wut-water-range $OBSIDMIN $OBSIDMAX
+# Enable the following if you want to download waterfalls in this range:
+#echo "Downloading Waterfalls"
+#./wut-water-range $OBSIDMIN $OBSIDMAX
 
 # XXX remove data/train and data/val directories XXX
 echo "Removing data/ subdirectories"

wut-ml

@@ -1,5 +1,17 @@
 #!/usr/bin/python3
 # wut-ml
+#
+# Vet a SatNOGS image using machine learning (guessing).
+# It will vet the image located at test/unvetted/waterfall.png.
+#
+# Note, there is an issue to fix where it will vet everything
+# under the data/test directory, so fix that. For now, just deleted
+# everything else. :)
+#
+# Usage:
+# wut-ml
+# Example:
+# wut-ml
 
 import os
 import numpy as np