Hi Folks,
I have been trying to perform static quantization of a model for scene text detection and reduce the precision of the model from float32 to integer8.
I followed the steps mentioned in the official tutorial - fused the conv,batch norm and relu layers ;  converted to int ; replaced concat with nn.quantized.Floattensor().
The original model works well, but the prediction from quantized model is really bad -
Prediction from FP32 model -

Prediction from INT8 model -

Not sure where I’m going wrong 
Would appreciate on any suggestions where I’m going wrong during quantization.
The code is available here -  https://github.com/raghavgurbaxani/experiments/blob/master/try_static_quant.py 3