Tim created another superb solution. The highlights are an elegant center of square's determination using ndgrid. The crux of his method is a convolution for each square not using "same" with an interesting centroid kernel. The comparison between all square convolutions for all rotations utilizes a concise norm metric function. The method should work on non-binary images. The best six matches from the 180x180 upper triangle error array are handily converted into the output format. Thank You Tim for this elegant solution.
pressure to dB?
What digit is it?
Insert zeros into vector
Max index of 3D array
ICFP2021 Hole-In-Wall: Figure Validation
Vine Contest 1-D Case Optimization: Board 78
Script file size
GJam: 2013 China Event: Name Sorting
GJam 2017 Kickstart: Parentheses (Large)
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