Hello,
I’m working on a project on implementation of Face Recognition model on PYNQ Z2 FPGA, recognize trained persons and other as unknown. And want to get a comparison report on performance between FPGA and CPU/GPU.
Can I get to know about how to implement it on PYNQ, use any library in jupyter notebook or create any overlay for this. How to go about in this implementation?
Thank you.
with regards
Hello,
Maybe these projects are interesting for you, check it out:
Quantized Neural Networks (QNNs) on PYNQ
GitHub - Xilinx/BNN-PYNQ: Quantized Neural Networks (QNNs) on PYNQ
Object detection on the PYNQ-Z1 and Movidius Neural Compute Stick
GitHub - fpgadeveloper/pynq-ncs-yolo: YOLO object detector for Movidius Neural Compute Stick (NCS)
PYNQ Classification - Python on Zynq FPGA for Convolutional Neural Networks
GitHub - awai54st/PYNQ-Classification: Python on Zynq FPGA for Convolutional Neural Networks
Regards