[Image-SIG] Performance for image processing in Python

Christopher Barker Chris.Barker at noaa.gov
Mon Apr 19 19:08:18 CEST 2010

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. For example, a mosaic of 7 images, each 
> 800x600, the output size is about 8000x2000. Each output pixel is 
> sampled from the source images using bilinear interpolation according to 
> the inverse homography. The running time is nearly 1 hour.
> State-of-the-art commercial mosaicking software (written in C) runs the 
> above examples in less than 10 seconds!!!

Note that "State-of-the-art" image processing software is likely not 
only written in C, but also highly optimized -- taking into account 
cache sizes, using special instructions, etc, so you've not going to get 
close with naively written code. Still a factor of ten or so maybe.

> I wonder how is other Python image processing applications' performance? 
> Do we always need to implement slow functions in C?

in a word, yes -- if you are looping trough pixels in python, it's going 
to be painfully slow - python simply is not designed for that kind of thing.

> E.g., I suppose to 
> reimplement the bilinear interpolation in C, as it is called million 
> times in Python, which is slow.

have you looked at the ndarray package? or PIL's interpolation for that 
matter? both are written in C.

If they don't have the algorithm you need, as a another poster pointed 
out, smart use of numpy will help a lot (essentially,l you are getting 
the inner loop in c via numpy)

If you have not idea how to do that, read up a bit on scipy.org, and 
then post a question to the numpy list.

Option 3 is Cython -- it lets you write C code in an almost-python 
syntax, and it understand numpy arrays, to it's really easy to re-write 
that inner loop in C.


Christopher Barker, Ph.D.

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