On Mon, 19 Apr 2010 14:31:41 Son Hua wrote: > I'm quite new Python here. Recently I wrote an image mosaicking > application in Python (using Numpy library). It turns out that the > performance is quite terrible. [...] > > State-of-the-art commercial mosaicking software (written in C) runs the > above examples in less than 10 seconds!!! > > I wonder how is other Python image processing applications' performance? > Do we always need to implement slow functions in C? E.g., I suppose to > reimplement the bilinear interpolation in C, as it is called million > times in Python, which is slow.
Well, as you stated: You seem to be fairly new to Python. Just *using* NumPy does not guarantee good performance. The trick is to *use it right*. One example in C is for example also to use the right order of iterating over multi dimensional arrays to get the right performance. Otherwise you may be playing against the cache, which is fairly common on huge data structures. So, one thing you ought to look for in your code is that you're for example *not* iterate over the elements of an array (pixelx), but use operations that are to be applied to the whole array at once. You can use these with most basic and more complex operations, e. g. multiply/divide/add/subtract a scalar, apply certain NumPy provided functions (g. g. sin() or log()), apply dot-product multiplication, etc. Doing that, you can probably eliminate orders of magnitude of slowdown already. HTH, Guy -- Guy K. Kloss Institute of Information and Mathematical Sciences Te Kura Pūtaiao o Mōhiohio me Pāngarau Massey University, Albany (North Shore City, Auckland) 473 State Highway 17, Gate 1, Mailroom, Quad B Building voice: +64 9 414-0800 ext. 9266 fax: +64 9 441-8181 g.kl...@massey.ac.nz http://www.massey.ac.nz/~gkloss
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