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Blog Blog 2: Digilent ARTY Z7 with PYNQ-Z1 Embedded Vision
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  • Author Author: anupash.1002
  • Date Created: 6 Oct 2018 7:02 PM Date Created
  • Views 3453 views
  • Likes 9 likes
  • Comments 7 comments
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Blog 2: Digilent ARTY Z7 with PYNQ-Z1 Embedded Vision

anupash.1002
anupash.1002
6 Oct 2018

Here I did some experiments targeted to PYNQ Embedded Vision applications. It includes reading the USB camera in FPGA and projecting the image output via HDMI display on PC, testing the real time edge detection with the USB camera interfaced to the FPGA, and testing the face recognition software code on the HDMI display.

 

  • What is PYNQ?
  • Display image via USB Camera to HDMI display
  • Real time edge detection with the USB camera
  • Testing the Face Recognition Software

What is PYNQ?

 

The Zynq All Programmable device is an SOC based on a dual-core ARM Cortex-A9 processor (Processing System or PS), with FPGA part (referred as Programmable Logic or PL). Overlays or hardware libraries are programmable FPGA designs that extend the user application from the Processing System of the Zynq into the Programmable Logic. PYNQ provides a Python interface to allow overlays in the PL to be controlled from Python running in the PS.

More details are here https://pynq.readthedocs.io/en/latest/pynq_overlays.html

 

As done by other road-testers I also setup my PYNQ-Z1 using the guide from https://pynq.readthedocs.io/en/latest/getting_started/pynq_z1_setup.html#pynqz1-board-setup  I downloaded the .img file into the Micro-SD card which I per-programmed from my PC using Etcher. The planted the Micro-SD card on the Digilent ARTY Z7 Dev Board.

 

image

 

The Jupyter Notebook is already installed in the PYNQ Z1 image file which is in the SD card.

 

I also tried to connect to the router network and it was also successful but my router is located in a hidden place above a large book shelf so I didn't want to leave the FPGA board there as I also had to connect the camera to the fpga.

 

So I created a static ip connection between my PC and the Digilent ARTY Z7 Dev Board. And also connected the USB camera and the HDMI cable to my PC monitor.

 

image

image

Accessing the FPGA board via jupyter Notebook from the SD Card.

 

The Setup is as below

 

image

The USB camera setup and HDMI with the Digilent ARTY Z7 Dev Board

 

image

My PC Setup. The Digilent ARTY Z7 Dev Board is powered from USB cable

 

image

 

Display image via USB Camera to HDMI display

 

Here I used the HDMI and camera code on the SD Card and used it to project the image on the PC

 

image

image

 

The camera is connected to the FPGA board. And it pointing to the picture on the wall held by a friend. All the details on how to run the code are given in the code and commented well.

 

Real time edge detection with the USB camera

 

Here I did real-time edge detection of the video and projected it on the PC display via HDMI cable. There is significant lag in the video output of the HDMI as can been seen below. I tried to change the settings for the video transfer to the HDMI output display to remove the video lag but ended up losing packets and so I dialed it back to the settings

 

image

After playing around with the HDMI resolution of the display and the camera mount on the Digilent ARTY Z7 Dev Board the setup worked somewhat.

 

image

image

 

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Real time edge detection with the USB camera on Digilent ARTY Z7 Dev Board

Testing the Face Recognition Software

 

The test setup for the face recognition software. The image is sent via USB Camera to the HDMI on the PC.

 

image

 

image

 

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In conclusion all tests available for the PYNQ Embedded Vision applications worked very well. Although it may take some time to get a hang of the the PYNQ setup and understand how controls work.

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Top Comments

  • beacon_dave
    beacon_dave over 5 years ago in reply to _andreea_ +2
    These look like the example notebooks. You can view them here: OpenCV Filters Webcam https://nbviewer.jupyter.org/github/Xilinx/PYNQ/blob/v1.4/Pynq-Z1/notebooks/examples/opencv_filters_webcam.ipynb OpenCV…
  • maheredia
    maheredia over 5 years ago +1
    Hi, how are you? Great job done here! I'm looking to build a PYNQ image for my Arty z7. The process to do so is really messy and error prone (Install Ubuntu VM, instal GBs of Xilinx tools on VM, etc) I…
  • embeddedguy
    embeddedguy 9 months ago

    I could not download the PYNQ-Z2 image from the following webpage.

    Does it work for you?

    www.pynq.io/boards.html

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  • maheredia
    maheredia over 5 years ago

    Hi, how are you? Great job done here!

     

    I'm looking to build a PYNQ image for my Arty z7. The process to do so is really messy and error prone (Install Ubuntu VM, instal GBs of Xilinx tools on VM, etc)

     

    I've found that Arty Z7 comes with two versions: Arty Z7-10 and Arty Z7-20. The last one is more suitable for video applications.

     

    Are you using Arty Z7-10 or Arty Z7-20 here in this project? Could you please provide the SD Card image for Arty Z7-10?

     

    Kind regards.

     

    Martin A. Heredia

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  • beacon_dave
    beacon_dave over 5 years ago in reply to _andreea_

    These look like the example notebooks. You can view them here:

     

    OpenCV Filters Webcam

    https://nbviewer.jupyter.org/github/Xilinx/PYNQ/blob/v1.4/Pynq-Z1/notebooks/examples/opencv_filters_webcam.ipynb

     

    OpenCV Face Detection Webcam

    https://nbviewer.jupyter.org/github/Xilinx/PYNQ/blob/v1.4/Pynq-Z1/notebooks/examples/opencv_face_detect_webcam.ipynb

     

    There are more PYNQ examples on GitHub:

    https://github.com/Xilinx/PYNQ/tree/v1.4/Pynq-Z1/notebooks/examples

    which you can preview with the Jupyter Notebook viewer

    https://nbviewer.jupyter.org/

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  • _andreea_
    _andreea_ over 5 years ago

    Hello, is the software you used available?

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  • mihaela03
    mihaela03 over 5 years ago in reply to Fred27

    Oh, ok. Thank you!

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