Earlier quoted context omitted.
Halide and OpenCV are not comparable. Halide is mainly about decoupling the description of a low-level image processing operation from implementation details regarding tiling, storage of intermediate results, etc. OpenCV is a library implementing high level algorithms like multi-view 3D reconstruction that Halide does not even attempt to address.
My mistake, I phrased my question incorrectly. Why not opencv with a halide backend. The tensorflow whitepaper compares the TF ir to the halide ir. In fact, the work in tensorflow core is around XLA https://www.tensorflow.org/performance/xla/ (which brings compatibility across various architecture) It seems that this is more an attempt at locking the tensors to target custom metal, so that it can't be copied and made…
Also your argument that it’s not about perf makes no sense to me. Sure other phones have HDR, I bet its way slower and more energy intensive than the Pixel 2. Except maybe the iPhone, which may also have custom silicon. If they had custom HDR tech in software they wanted to keep they could just keep the source closed, or patent it.