Hello all,
I have a piece of code I could use some help optimizing. What I'm
attempting to do is periodically grab a screenshot, and search for 2D
patterns of black pixels in it. I don't care about any color other
than black. Here's some simple code that simulates my worst-case
scenario, scanning the whole screen for a sequence that does not
exist:
import ImageGrab # From the PIL library
def removeColor(rgb):
r, g, b = rgb
return (r == 0 and g == 0 and b == 0)
BMP = ImageGrab.grab.getdata()
x = map(removeColor, BMP)
The idea is to search for sequences of black pixels on a background
that can change colors. To that end, I transform the screengrab into
a sequence of either black or nonblack pixels as I search them. Note
that in my actual code, I use imap so I only transform pixels as I
search them, and I'm using the KnuthMorrisPratt algorithm from
http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/117214 to do
the actual searching.
>From some testing using the timeit module:
map(None, BMP) takes about 0.6 seconds on a 1600x1200 screengrab.
map(removeColor, BMP) takes about 1.5 seconds.
I'd love to speed things up, if possible. It seems like what I'm
doing would probably be a fairly well defined problem, but I don't
know enough about the field to even know where to start my research,
so even a list of keywords that would point me to discussion of
similar topics would be welcome.
This is being done in Python 2.5c2 using PIL 1.1.5
--
Jerry
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