Stuck on an issue?

FWIW, feature/CLF is now rebased on develop in my fork, as of yesterday.

Heya – so, I think I may be able to contribute some stuff here. Over the past few months, on and off, I’ve been messing around with creating additional LUTSequenceOperators, sort of frankensteining together work from Nick’s CLF branch and Thomas’s various lut-related feature branches, and trying my hand at… uh, reimplementing in numpy much of the work contributed by the OCIO2 crew and the AMPAS gang to their respective projects.

Regretfully, I hadn’t anticipated where my experimental operators would take me, so I hadn’t been working in my colour library fork; so I have some stuff to extract and refactor, and certainly some documentation and testing to… document and test, but I’d be happy to share some code and ideas to do with as you please.

For your consideration…

• I’ve put together an ExponentWithLinear Operator, based on an early OCIO2 contribution; need to revisit in light of recent CLF 2.0 VWG discussions…

• I did something similar with the various flavors of Log Operators contributed to OCIO2 – I have separate LogCTF, LogAffine, and LogCamera operators, which should probably be refactored into a single Log Operator. My parametric camera log implementation isn’t quite as fancy as Doug’s proposal – it expects six coefficients in addition to a ‘linSideBreak’ point and a base parameter (which I’ve reduced to five on paper)… but even though my math seems to check out, it might be worth waiting to see where things are going with the CLF implementation, if parity is important.

• I put together a couple of “Shaper” operators – a LG2Shaper Operator (a la aces-dev/OCIO), and a PQShaper Operator, both parameterized the same way (min_exposure_value, max_exposure_value, middle_grey kwargs); as well as, perhaps unnecessarily, an AllocationTransform Operator, parameterized like the OCIO Transform. The PQShaper and LG2Shaper Ops each include ‘shape_cube’ instance methods that sample a function to a LUT3D “wrapped” in reverse and forward shapers as a concatenated 1D +3D LUTSequence. The AllocationTransform Op likewise has a handy class method for computing allocation vars for a given function, for a given range. domain? range, i think. Bonus classmethod factory that does the same thing for an RGB_Colourspace, via its decoding_cctf. Man, it’s gonna be exciting checking my work.

• Somewhere, I put a fair amount of work into wrapping my head around (speedy) HalfDomain LUT inversion, but I kept ending up with an offset that shouldn’t be. I’ll have to give that another go. HalfDomain LUTs kinda blow my mind a little, and having a vectorized implementation is immensely satisfying, I gotta say…

• Oh, I added ‘direction’ and ‘bypass’ kwargs to the AbstractLUTSequenceOperator class… I was a little apprehensive about making the classes particularly ‘stateful’; but I think it’s worth being able to apply each operator in a given direction. Oh, each operator can be applied in reverse via a ‘reverse’ method that does the inverse of whatever the ‘apply’ method is doing, which, itself, is contingent on whether the operator’s direction is set to ‘forward’ or ‘inverse’. (LUT3Ds and HalfDomain operators pending, of course),

• I created a NoOp Operator. Don’t think of me as a hero.

• I actually went through and implemented all the FixedFunctionTransform styles / operations, which ends up being a pretty hefty part of the AMPAS CTL code base. So, there’s that.

• Added a couple of other operators based on various ACES CTL snippets – a CompressHighlights operator (as used by the ACES 1.1 OutputTransform…uh, transform, to prevent simulated whitepoints from clipping), as well as a ‘gamut restrict’ operator…

• An experimental Sympy-based Expression operator that needs more love, and some methods for constructing and ‘lambdifying’ piecewise functions and solving for their inverses [or failing to do so 50% of the time, cuz i’m not great with sympy]

• I definitely screwed up somewhere trying to create an entire OutputTransform operator / Segmented Spline / SSTS operators.

• A couple other odds and ends, like a painfully slow OCIOProcessor Operator, if OCIO is available… various Matrixy convenience operators – “GamutConvert”, “(De)saturation”, “Fit”, and so forth, which really just use Nick’s Matrix Operator under the hood…

…and… perhaps other stuff I’m almost definitely forgetting.

anyway, I’ll start extracting / refactoring these jams if you guys are interested; happy to share gists of where things are now, too, if you’d rather discuss / deliberate / reject stuff before I go too far with refactoring for public consumption. Anyway. More soon. Cheers!