I think i did it.Had an issue with half-float from Imath, but maybe because tried to reimplement template.And
results pretty fast. 1000x iterations on 4K texture: 18.564438 sec so roughly 0.01856 sec for normalizing.Have
one question. What is better for OIIO, single function that will have boolean FullRange option as an input and
x = !fullRange ? 2.0f * x - 1.0f : x; in code or two normalize functions one for 0.0-1.0 range inputs/outputs
and another for -1.0 +1.0 range?Integer normal maps usually 0-1 range, when float exr, if 3D artists have a
brain should use full -1 +1 range, but quite often in studios with "liniar workflow" EXR textures
also can be in 0-1 range.Best regardsVladOn Jun 9, 2023, at 11:13 AM, Larry Gritz <l...@imageworks.com>
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. :DHi, 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 2ImageBuffAlgo::sum_channels for vector
magnitudeImageBuffAlgo::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:VladPS: 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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