Pynq FPGA Tutorials

LogicTronix & Digitronix Nepal’s Tutorials on Pynq FPGA:

Are you willing to Learn about the Pynq FPGA Development? Pynq is Python+Zynq Development Environment from which you can get power of FPGA with Python Programming Interface.

Take $9.99 Udemy Course on PYNQ FPGA Development with Python Programming: $9.99 Coupon Code

This course teach you about the PYNQ FPGA development with VIVADO and PYNQ, creating custom overlay, python programming, installing tensorflow, Face Detection and Recognition etc..


PYNQ-Z1 Reference Links for Tutorials: Github Ripositories

Tutorials from LogicTronix and Digitronix Nepal on PYNQ-Z1

1. Install Tensorflow on PYNQ: LogicTronix Tutorial

2. Face and Eye Detection with Python OpenCV & PYNQ FPGA

3. Basic Image Processing with Python OpenCV and PYNQ FPGA, USB Webcam

4.Installing “pip” on PYNQ

  • Connect Pynq Board with USB cable, change Jumper JP5 in to USB power mode, Connect Ethernet cable on pynq and Router for internet access.
  • Open the Serial Terminal Program as TeraTerm, Putty or any other. Set up the serial program in Serial Communication with COM port (shown in Device Manager of your OS) and Baud rate of 115200.
  • Run this command on the terminal:
    $sudo apt-get update
    $sudo apt-get install python-pip
  • If you need to install scipy library then here is command:
    $sudo apt-get install python-scipy
  • If you still not able to configure pip or scipy then : Download the PYNQ-Z1 v2.1 image (released 21 Feb 2018)

5.Simple Neural Net Implementation with PYNQ FPGA

6. Here is our Python Programming Tutorial Playlist (Six Tutorials Playlist on Youtube):

If you have any queries or interest on Project with PYNQ FPGA then do contact us from: or

We can provide service on PYNQ Based Development, Design and Product Design.



This tutorial is as reference tutorial for this project: Binarized Neural Network (BNN) on PYNQ,

Complete Steps from Downloading the PYNQ OS and Booting it on PYNQ Board:

  1. Download latest Version of PYNQ OS from

  2. Visit
    • Open Serial terminal program in the PC, Set up the COM port (see on device manager of your OS), Baud rate of 115200
    • In order to install it your PYNQ, connect to the board, open a terminal and type:
    • sudo pip3.6 install git+ PYNQ v2.0 or later)
    • This will install the BNN package to your board, and create a BNNdirectory in the Jupyter home area. You will find the Jupyter notebooks to test the BNN in this directory.
      3. Connecting to Jupyter Notebooks

In order to build the shared object during installation, the user should copy the        include folder from VIVADO HLS on the PYNQ board (in windows in vivado-path/Vivado_HLS/201x.y/include, /vivado-path/Vidado_HLS/201x.y/include in unix) and set the environment variable VIVADOHLS_INCLUDE_PATH to the location in which the folder has been copied. If the env variable is not set, the precompiled version will be used instead.

To connect to Jupyter Notebooks open a web browser and navigate to:

  1. Accessing Files on The Board

Samba, a file sharing service, is running on the board. This allows you to access the Pynq home area as a network drive, to transfer files to and from the board.

To access the Pynq home area in Windows Explorer type one of the following in the navigation bar.

\\pynq\xilinx                # If connected to a Network/Router with DHCP

\\\xilinx       # If connected to a Computer with a Static IP


  1. Now goto browser and open http://pynq:9090/tree on jupyter. There is installed BNN library on the tree.

      6. Now explore the BNN examples which was available on the Tree.
  3. (least important)
Important Links:
  • Google Search “install pip in pynq”


PYNQ-Z2 Tutorial Series:

1. Unboxing and Demo Session

For more tutorials on PYNQ-Z2, Please visit:

If you have any queries or interest on Project with PYNQ FPGA then do contact us from: or We can provide service on PYNQ Based Development, Design and Product Design.