Hello,
I have followed the snpe-net-run examples and my understanding is that snpe-net-run is input agnostic, meaning we could define any input we wanted and not just gbr raw files as per the esamples. I have tried successfully with a 1D vector, but would now like to load a 640,320,6 channel deep tensor as an input as well as two other 640,320,1 grey scale images. How would I be able to express these inputs (originally created as Python ndarrays) and write them to files that snpe-net-run could interpret and run the model on? For example, I cannot write the 6 channel deep input as a GBR raw image file, and neither a a txt file which is only 2D, so how would one go about it?
Thanks
Let us talk Snpe expert and give you update.
Thanks
Hi 22imonrea
Yes, you can applied SNPE for non-image inputs, but your model should support your input, For example, if your input is voice, your model should key word detecytion model. make sure model to match your input type.
Thanks
Kevin