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duplicate copies of the training data since doing so uses a lot of RAM for
large datasets.

aliasing violations in user code, even when things get inlined in unfavorable
ways.

opening files in binary mode.  Oops.  This is now fixed.

documented that you couldn't change the padding, cell size, or window size
parameters between calls to load() and detect().

efficiently, even when their window sizes differ.

non-max suppression code that I introduced a few commits ago.

into them.

That is, chain the = operator when using a literal assignment on
matrix objects.

going to be performance critical and is a common user error.