Hi, Sorry for the repost. I sent this to the development list yesterday, but posting over here as well to cast a broader net.
Has anyone dug around the "target input alpha" option in the DeepRecolor node, and has some insight on how it is retargetting each sample internally? Long story short, I'm trying to implement a procedure to re-target opacity of each sample in a deep pixel, akin to what's happening in a DeepRecolor node when "target input alpha" is checked. I've got this to a point where it's working ok, but I think I might be missing something, as my results differ from those you'd get in a DeepRecolor. My re-targetting algorithm is based on the assumption that the relative opacity between samples should be preserved, but DeepRecolor clearly uses a different approach. Example: Say you have a deep pixel with 2 samples, and the following opacities: Samp1 : 0.4 Samp2 : 0.2 The accumulated opacity is 0.52 (Samp1 over Samp2). Note that Samp1 deliberately has an opacity of 2 times Samp2. Now, let's say we want to re-target those samples to an accumulated opacity of 0.9. What I am doing is trying to calculate new opacities for Samp1 and Samp2 in such a way that both of these conditions are met. a) Samp1 == 2 * Samp2 b) Samp1 over Samp2 == 0.9 This gives me the following re-targeted values: Samp1 : 0.829284 Samp2 : 0.414642 I'm happy with those, but it bugs me that DeepRecolor throws different results: Samp1 : 0.798617 Samp2 : 0.503434 Which meets the second condition (Samp1 over Samp2 == 0.9), but does not preserve the relative opacities of the original samples. It seems to me like DeepRecolor is applying some sort of non-linear function to apply a different weight to each of the original samples, but I haven't been able to figure out the logic of that weighting, or a reason why it's done that way. Does anyone have any insight/ideas on what DeepRecolor might be doing internally? Or a reason why you might want to distribute the target alpha in a non-linear way? Thanks in advance, Ivan
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