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1/ PSA/rant: If your'e a developer trying to port a deep learning model from Onnx to Core ML and are finding that Apple's onnx-coreml conversion script isn't working out of the box- you aren't alone. While iOS13 has brought about great improvements to what you can do in Core ML,
/7 Also also.... Just put all your image normalization/denormalization code in additional layers sandwiching your model before converting it to Onnx. It's easier to reason about and do correctly where as Apple's code again is strange and not quite right.
Hey there, I’m planning to follow a similar path but wondering if it’s possible to just rebuild the model entirely in swift, so as to fully utilize all of apple’s hardware magic?
You mean like train it and everything else? Honestly I haven’t bothered digging into that because I’m very happy with FastAI and haven’t seen any compelling reason to move off it. I (superficially) think you may be able to but not sure if it would be worth it....
I agree that it's not seamless but:
1/ it's way better than it used to be.
2/ the onnx conversion itself is not seamless either, in my experience
3/ You get amazing perf on device in the end, which for me makes all of this worth it
1b/ @bhushan23s lead on onnx-coreml is v helpful
PS: this thread really makes me want to try DeOldify on an iOS device!! Do you already have a CoreML app out?
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