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
- Main PYNQ Repository
- Xilinx’ PYNQ Networking
- Xilinx’ PYNQ Quantized Neural Networks
- Xilinx’ PYNQ Binary Neural Networks
- Xilinx’ PYNQ Computer Vision
- Xilinx’ PYNQ Deep Learning
- Xilinx’ PYNQ BOT
- Hillhao’s PYNQ Neural Networks
- Awai54st’s PYNQ Convolutional Neural Networks
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: email@example.com or firstname.lastname@example.org
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, https://github.com/Xilinx/BNN-PYNQ/
Complete Steps from Downloading the PYNQ OS and Booting it on PYNQ Board:
Download latest Version of PYNQ OS from
- Download the PYNQ-Z1 v2.1 image (released 21 Feb 2018)
- Unzip the image
- Write the image to a blank Micro SD card (minimum 8GB recommended)
- Insert SD card into PYNQ Board
- Boot the Board with following setting, shown in the figure
- 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+https://github.com/Xilinx/BNN-PYNQ.git(on 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:
- http://pynq:9090if your PYNQ-Z1 board is connected to a router or network
- http://192.168.2.99:9090If your PYNQ-Z1 board is connected to a computer
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 \\192.168.2.99\xilinx # If connected to a Computer with a Static IP
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.
- http://pynq.readthedocs.io/en/latest/python_environment.html (least important)
- Google Search “install pip in pynq”
1. Unboxing and Demo Session
For more tutorials on PYNQ-Z2, Please visit: https://logictronix.com/tutorials/pynq-fpga-tutorials/pynq-z2-tutorials/
If you have any queries or interest on Project with PYNQ FPGA then do contact us from: email@example.com or firstname.lastname@example.org. We can provide service on PYNQ Based Development, Design and Product Design.