I should have seen this sooner, but it appears that set_pixels in python is
hard-coded to expect TypeDesc::TypeFloat, where as get_pixels lets me get
the values using any type I specify. Do you think it's a good idea to be
symmetric here?
(py_imagebuf.cpp line 362)
My particular use case is 16-bit int data. It's probably OK to promote to
float given the processing I'm doing, but wasn't going to do that without a
need.
The current get_pixels/set_pixels interface return a python array
(array.array), which I'm converting to a numpy.ndarray without trouble. I
think I'm copying the data. There may be some way to get numpy and array to
share memory, I'm still figuring that out. I imagine most will want them as
numpy ndarrays, but it is nice to not have OIIO dependent on NumPy.
(For the python-ites:
numpyPixels = numpy.asarray(arrayPixels).reshape((spec.width, spec.height))
and
arrayPixels = array.array('H', numpyPixels.flatten())
)
--jono
PS: Either Google or Apply insist of changing "numpy" into "bumpy" every
single time. Bumpy is a much better name for the library.
On Mon, Jun 15, 2015 at 2:54 PM Larry Gritz <[email protected]> wrote:
> Jono, see this: https://github.com/OpenImageIO/oiio/pull/1167
>
> This adds a set_pixels (and in the Python binding, it takes either a tuple
> or a Python array). It's probably not super efficient (ick, there's an
> intermediate copy to a std::vector involved), but it's a start.
>
> I'm not experienced enough with numpy to know; how would you want the
> Python API to look to be most efficient for your purposes?
>
> -- lg
>
>
> On Jun 4, 2015, at 4:24 PM, Jonathan Gibbs <[email protected]> wrote:
>
> Does anyone have a good/simple example of working with OIIO in python. I
> can get at the raw pixels nicely enough with ImageBuf.get_pixels(), but
> it's not clear the best way to get those pixels back into an ImageBuf for
> writing. (There is no set_pixels.)
>
> As a side note, get_pixels returns a Python array, which I can convert
> easily enough to a numpy.ndarray. Is there a better way to get from a
> ImageBuf to a numpy.ndarray and back again in a reasonably efficient manner?
>
> --jono
>
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>
>
> --
> Larry Gritz
> [email protected]
>
>
>
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