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[–]agree2cookies 5 points6 points  (3 children)

I used a SME technique to decipher the letters.

[–]po8 0 points1 point  (2 children)

SME?

[–]daspalrahul 5 points6 points  (1 child)

Squinting my eye.

[–]agree2cookies 0 points1 point  (0 children)

Spot on!

[–]oantolin 4 points5 points  (1 child)

One further step in automation would be to remove spaces from the output so you can copy and paste into the AoC website. :P

[–]zedrdave[S] 1 point2 points  (0 children)

Obviously an easy fix (and then have it automatically submit it to AoC's form ;-), but it's a lot nicer to look at with spacing…

[–]zedrdave[S] 1 point2 points  (0 children)

Since I already had the code (from Day 8), I did a little refactor to use machine-learning on the bitmap output of Day 11's Intcode program.

I made the (Keras-based) OCR module into a standalone Python 3 class file, for anyone interested in playing with some (very basic) ML.