Thanks for the reply.
My current plan is to write an MNIST classifier with GUI as a prototype and try to make it become commercial-grade portable, if possible. I think it would be the best template to try the things you mentioned.
Is this practical by merely using libtorch? Or should I try ONNX or something else? Is pytorch/libtorch suitable for this scenario or should I try other frameworks?
Actually, I have no idea how the industrials deploy deep learning models. But because I can write my own CMakeLists.txt, it’s very simple and convenient to compile with other C++ frameworks (e.g., JUCE, QT, …). And this gives me a strong motivation to try libtorch.