Decode to CHW format already about wuffs HOT 6 CLOSED

Your terminology is extremely confusing and alien, could you explain in simple terms?

Do you mean planar instead of interleaved?

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@pjanx I am sorry for that. You are right, I mean separated planes.
That's very important in many Deep Learning applications now (for example PyTorch or TensorRT use this format). However, conversation interleaved -> planar is not cheap (for example, with cv::split).

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See usages of wuffs_base__pixel_format__is_planar() and wuffs_base__pixel_buffer__plane()--no, it's not currently supported.

Your best option in the foreseeable future is to do some custom post-processing, which will also give you flexibility with the bit depth, and with the choice of channels. Understand that image formats are wild--the input may be indexed (GIF, PNG), RGB/A interleaved (PNG), or even YCbCr planar with differently sized planes (lossy formats, 4:2:2 and 4:2:0). That's a lot of paths to care about. There are bigger concerns in the image library right now.

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Yeah, custom post-processing is the way to go for now.

I'm surprised that HWC <-> CWH conversion isn't cheap (if HWC and CWH mean what I think it means; I've never seen those terms before today). I'm not very familiar with PyTorch or TensorRT, but it should be very SIMD friendly.

How do existing PyTorch or TensorRT programs load (and convert) PNGs? Do they use libpng? I don't see any PNG_TRANSFORM_FOOBAR definitions in libpng to split into separate R, G, B, A planes, so I'm guessing it'd have to be a post-processing step. Can you just do the same post-processing step?

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I'm not sure what they use, but OpenCV has optimized enough split function for cpu and cuda.
However, copy is still copy. It can be avoided in theory and on big images difference isn't small.
But thanks for answers

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For what it's worth, it's a valid request, but unlikely to be fulfilled, unless someone would step in to work on it themselves.

Another thought: if you don't control the image source, you may want to colour manage the images, which means extra processing anyway. And if you do, you may want to pre-normalize it to whatever format is seen fit.

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