On 16-Sep-08, at 4:50 AM, Stéfan van der Walt wrote:
> Hi Brendan
>
> 2008/9/16 brendan simons <[EMAIL PROTECTED]>:
>> #interpolate the green pixels from the bayer filter image ain
>> g = greenMask * ain
>> gi = g[:-2, 1:-1].astype('uint16')
>> gi += g[2:, 1:-1]
>> gi += g[1:-1, :-2]
>> gi += g[1:-1, 2:]
>> gi /= 4
>> gi += g[1:-1, 1:-1]
>> return gi
>
> I may be completely off base here, but you should be able to do this
> *very* quickly using your GPU, or even just using OpenGL. Otherwise,
> coding it up in ctypes is easy as well (I can send you a code snippet,
> if you need).
I thought so too. I briefly researched using the GPU, but I found
that, surprisingly, neither multitexturing in pyopengl, nor surface
blitting in pygame was any faster than the numpy code I posted above.
That could be because I'm working on a machine with an integrated
graphics chip.
I would love a c-types code snippet. I'm not very handy in c. Since
I gather numpy is row-major, I thought I up and down crops very
quickly by moving the start and end pointers of the array. For
cropping left and right, is there a fast c command for "copy while
skipping every nth hundred bytes"?
>
>
>> I do something similar for red and blue, then stack the
>> interpolated red,
>> green and blue integers into an array of 24 bit integers and blit
>> to the
>> screen.
>>
>> I was hoping that none of the lines would have to iterate over
>> pixels, and
>> would instead do the adds and multiplies as single operations.
>> Perhaps numpy
>> has to iterate when copying a subset of an array? Is there a
>> faster array
>> "crop" ? Any hints as to how I might code this part up using ctypes?
>
> Have you tried formulating this as a convolution, and using
> scipy.signal's 2-d convolve or fftconvolve?
I just read through the scipy tutorial on signal.convolve, and I'm a
bit lost. It's been years since I've last taken a numerical methods
class. Maybe there's something here - but I'm going to have to learn
a bit first.
Thanks for your help,
Brendan
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