amitdedhia:

I am still interested in knowing (in case of static quantization for qnnpack config) why the output value for all pixels is positive for background channel and negative for foreground channel.


Some models are more sensitive to quantization than others, and you can try selectively quantizing a part of the model, e.g. keep first conv unquantized, to mitigate the problem for post training static quantization. and typically qat will help in these cases as well.