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MobileNet-V1 Implemetation on FPGA

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This implementation is based on the upstream repo but with C++ wrapper (using xcl2.hpp and xcl2.cpp) to avoid "Not Releasing object" errors which is tuned for stanford40 dataset with 40 action classes.

  • Used Techniques : Transfer Learning and Folding Batch Normalization
  • Network : MobileNet v1
  • Dataset : Stanford40 (Action recognition)
  • Target FPGA: AWS f1 (VU9P chip)
  • Frameworks : Keras and tflite
  • Software for FPGA : SDAccel v2018.3 in Centos 7.6
  • Data Precision : Floating Point
  • Input image format : Numpy Arrays extracted using Netron and Reading using CNPY