I have trained the model
MobileNetV2 + SSD Lite in PyTorch from ‘https://github.com/qfgaohao/pytorch-ssd/blob/master/vision/ssd/mobilenet_v2_ssd_lite.py’. Now, I want use it in Raspberry Pi3.
I converted ‘.pth’ model into Caffe2 model through
ONNX representation and I got two files: init_net.pb and predict_net.pb for Caffe2 framework.
As far as I know, to accelerate the model on mobile systems such as Rpi3(B/B+) I should use the
QNNPACK lib which allows make the low-precision inference using operators with
int8 data type.
How to perform quantization of this model?
How can I make low-precision inference using
Maybe there are some tutorials about it?