To clarify: I believe that the contrast_remap function is new in OIIO 2.1. On
older versions, or merely if you prefer it, I think you could achieve the same
thing with
ImageBufAlgo::sub(*image, *image, min, roi);
ImageBufAlgo::mul(*image, *image, (max-min), roi);
Note also that this whole business of passing the roi explicitly is to limit
the pixel alterations to just the first 3 channels. You almost surely don't
want to scale the alpha values or any additional channels.
> On Nov 27, 2019, at 5:27 PM, Larry Gritz <[email protected]> wrote:
>
> In what way doesn't it work properly? Does it crash? Appear to do nothing? Do
> something but not what you expect? What kind of image are you trying (I mean,
> what data type and channels)?
>
> I can only speak in generalities without this info, but here's what I spotted
> as likely problems.
>
> * ConstIterator/Iterator<float> is likely to be problematic, because it
> requires the buffer itself to be float. (Is it?) Usually we write a function
> like your normalize as a template and then have a big switch statement that
> selects a specialized variety based on the data type. (This may not really be
> a problem if all of your images are stored as 'float' buffers internally.)
>
> * You initialized 'min' (why are these half?) to 0.0, which means that "if
> (it[c] < min)" will probably never be true (unless you have negative values),
> so it probably is not going to compute the correct minimum. A better way to
> compute min/max would be:
>
> float min = 1e6f;
> float max = -1e6f;
> ...
> for (int c = 0; c < nchannels; ++c) {
> min = std::min(max, it[c]);
> max = std::max(max, it[c]);
> }
>
> * Depending on your image, you may also find that scaling all channels based
> on the biggest min/max may be wrong, particularly if it has any non-color
> chanels like alpha or Z.
>
>
> So OIIO 2.1 (a release candidate now, scheduled to be the official supported
> release in 3 days!) has a function that does everything you want. Assuming
> you're able to use that, here's how I recommend doing this operation robustly
> (this is off the top of my head, I have not tested, so take with a grain of
> salt, but this is the basic idea):
>
> ImageBufAlgo::PixelStats stats = ImageBufAlgo::computePixelStats(*image);
> float min = 1e6f;
> float max = -1e6f;
> int nc = std::min (3, image->nchannels()); // only consider R,G,B
> for (int c = 0; c < nc; ++c) {
> min = std::min(max, stats.min[c]);
> max = std::max(max, stats.max[c]);
> }
> ROI roi = image->roi();
> roi.chend = 3; // only rescale at most the first three channels!
> ImageBufAlgo::contrast_remap(*image, *image, min, max, 0.0f, 1.0f, 1.0,
> 0.5, roi);
>
>
> Using IBA::computePixelStats and contrast_remap has two big advantages over
> writing the loops yourself: (1) it handles every data type that OIIO
> supports, not just float; and (2) will go much faster because internally it's
> multithreaded!
>
>
>
>> On Nov 27, 2019, at 4:31 PM, Chris Dawlud <[email protected]
>> <mailto:[email protected]>> wrote:
>>
>> Hi,
>>
>> I want to normalize exr to make even very bright/dark images visible.
>> The idea is simple but I can't figure out how to do this correctly.
>>
>> I have come up with the following, but it doesn't work properly:
>> void ImageLoader::normalize(OIIO::ImageBuf* image)
>> {
>> using namespace OIIO;
>>
>> auto min = half{ 0.0f };
>> auto max = half{ 0.0f };
>>
>> for (auto it = ImageBuf::ConstIterator<float>{ *image }; !it.done();
>> ++it)
>> for (auto c = 0; c < image->nchannels(); ++c) {
>> if (it[c] < min) min = it[c];
>> if (it[c] > max) max = it[c];
>> }
>>
>> for (auto it = ImageBuf::Iterator<float>{ *image }; !it.done(); ++it)
>> for (auto c = 0; c < image->nchannels(); ++c)
>> it[c] = 0.0f + (it[c] - min) * ( 1.0f - 0.0f ) / (max
>> - min);
>>
>> }
>>
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>
> --
> Larry Gritz
> [email protected] <mailto:[email protected]>
>
>
>
>
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--
Larry Gritz
[email protected]
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