Added https://github.com/OpenImageIO/oiio/issues/3873
On 6/8/2023 7:12 PM, Larry Gritz wrote:
Yes, I am convinced that IBA::normalize() would be useful to add.
🎣 Mackerel!
(somebody should start by filing an issue so we don't forget about
this potential enhancement)
On Thu, Jun 8, 2023 at 7:08 PM Vladlen Erium <shaam...@icloud.com> wrote:
Thanx Larry!
I definitely will check ImageBuf::Iterator. And do my best.
Common or not, but if you'll check some of 3D format parsers, you
can find that they are by default normalize vertices normals. And
even if most 3D DCC apps do the same with normal maps inputs, and
most normal maps generator output normalized data, it still a good
to have this function in openimageio, well, just in case. :D
Hi, Vlad.
That's probably the simplest approach with the existing set of
IBA functions, yes. Maybe there is some optimizing you can do
around the edges -- like, `mul(img,img)` may be faster than
`pow(img,2.0)`, I'm not sure, and definitely you want to use the
variety of IBA functions that takes a destination image rather
than returning an ImageBuf, in order to minimize needless buffer
copying. But those obvious tricks will only get you so far.
If you're doing this a lot and it's performance critical, a
better way would be to write it as a single function that uses
ImageBuf::Iterator to traverse the image and do all the
operations at once for each pixel, with no extra buffer copies.
Looking at the source code to any of the usual IBA functions that
take one input image and produce one output image will provide
you with a good example to copy and change the guts to make your
new function.
I don't recall anybody asking for this particular thing before,
but if you think it is a commonly needed operation, then by all
means propose a PR to add this new function after you've
implemented it.
On Sun, Jun 4, 2023 at 6:28 PM Vladlen Erium <v...@hdri.xyz> wrote:
What should be most efficient way to implement normalizing
vector data images (normals) using ImageBuffAlgo?
For this moment I only see the way to do this in four steps.
ImageBuffAlgo::madd for [0.0,1.0] -> [-1.0,1.0]
ImageBuffAlgo::pow for power of 2
ImageBuffAlgo::sum_channels for vector magnitude
ImageBuffAlgo::div (sec and magnitude) to normalize vector
length
ImageBuffAlgo::madd for normalize to [0.0, 1.0] range.
This not only required to make so many steps but also
required a lot of temporary buffers, that for huge textures
can required lot of memory. When all steps can be done per
pixel and perfectly parallelized (shaders, cuda).
Maybe I missed some OIIO functions? 🤔
Best regards:
Vlad
PS: btw, looks like Google completely filter out all Larry
messages if Gmail used for subscription to this mailing list.
They even not in spam folder, where mail list messages quite
often can be moved 😒
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