This is interesting. I have always done RGB imaging with numpy using arrays of shape (height, width, 3). In fact, this is the form that PIL gives when calling np.asarray() on a PIL image.
It does seem more efficient to be able to do a[0],a[1],a[2] to get the R, G, and B channels respectively. This, obviously is not currently the case. Would it be better for me to switch to this way of doing things and/or work a patch for PIL so that the array is built in the form (3, height, width)? Chris On Tue, May 12, 2009 at 4:14 PM, David Warde-Farley <d...@cs.toronto.edu>wrote: > > On 12-May-09, at 3:55 PM, Ryan May wrote: > > > > It's going to be faster to do it without the transpose. Besides, > > for numpy, > > that imshow becomes: > > > > imshow(b[0]) > > > > Which, IMHO, looks better than Matlab. > > You're right, that is better, odd how I never thought of doing it like > that. I've been stuck in my Matlab-esque world with dstack() as my > default mental model of how images/matrices ought to be stacked. > > Am I right in thinking that b[0] is stored in a big contiguous block > of memory, thus making the read marginally faster than slicing on the > third? > > David > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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