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Xilinx / BNN-PYNQ

Quantized Neural Networks (QNNs) on PYNQ
https://xilinx.github.io/finn/
BSD 3-Clause "New" or "Revised" License
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Implement Cifar-10 in real time on PYNQ-Z2 #158

Open mohitajais opened 3 years ago

mohitajais commented 3 years ago

Hello, I am trying to implement Cifar-10 in real-time on hardware(PYNQ-Z2) after capturing a frame from a USB webcam and pass it to HDMI out (monitor). For this, I have used the base overlay of pynq (having HDMI-in and HDMI-out) and manually add the CNV IP core i.e BlackBoxJam_0 with it. So that, I can generate my own overlay with CNV and HDMI using VIVADO IP integrator.

The block design has successfully generated a bitstream file. The .bit, tcl and hwh file has uploaded to the jupyter notebook environment. Also, the hardware .so file is successfully generated. I have tried to capture images from USB camera and classify each frame using the bnn.CnvClassifier. But always the jupyter notebook kernel dies whenever I apply bnn.CnvClassifier on the frame.

Is this a correct way to manually add BlackBoxJam_0 IP?? Please give suggestions

IP block design given : AcroRd32_4A9DeK6wdg

mohitajais commented 3 years ago

Is it possible to do real-time image recognition using the BNN project? Please reply