A Smart Camera implemented in PetaLinux 2022.1 on ZCU104

Using a Raspberry Pi camera

A Smart Camera implemented in PetaLinux 2022.1 on ZCU104
In this post we’re going to build a smart camera using a Raspberry Pi camera, the ZCU104 board and PetaLinux. We’re going to do this by leveraging the Smartcam app which was originally designed for the AMD Xilinx Kria SoM. Our version of the Smartcam app can take video inputs from a Raspberry Pi camera, a USB camera or a file, and it can output video to a DisplayPort monitor, a file or via Ethernet over Real-time Transport Protocol. [Read More]

Benchmarking an FPGA based AI Vision application

Docker, Ubuntu and PetaLinux put to the test

Benchmarking an FPGA based AI Vision application
Many smart vision applications need to make fast decisions: autonomous vehicles, drones, surveillance and industrial robotics are only a few examples. When developing these kinds of AI vision systems, understanding performance-affecting factors is critical. In this post, we’ll explore two such factors: the operating system and camera type. We’ll measure and compare the performance of the NLP-SmartVision app on the ZCU104 board. The setups we’ll use are: Operating system: Docker container on Certified Ubuntu 22. [Read More]

NLP-SmartVision in PetaLinux on ZCU104

Using Raspberry Pi cameras

NLP-SmartVision in PetaLinux on ZCU104
In the last post we looked at how to run the Smartcam and NLP-SmartVision apps on the ZCU106 and Certified Ubuntu 22.04 LTS. One reader mentioned that running these apps in a Docker container on Ubuntu probably comes with a performance penalty when compared to running it on a lean PetaLinux build. This piqued my curiosity so in this post, we’re going to get the NLP-Smartvision app running in PetaLinux on the ZCU104 and then in the next post we’ll measure whatever penalty there may be to the throughput (in frames per second) and/or the glass-to-glass latency (in milliseconds). [Read More]

Develop smart vision apps for ZCU106 and RPi Camera FMC

Using Certified Ubuntu 22.04 LTS for Xilinx devices

Develop smart vision apps for ZCU106 and RPi Camera FMC
If you want to develop smart vision applications using Raspberry Pi cameras, the Zynq UltraScale+ MPSoC and Ubuntu 22.04 LTS, we’ve just released some code and the hardware to help you get started. For the launch of our new RPi Camera FMC, we’ve ported the Kria Vitis Platforms and Overlays over to the ZCU106 armed with an RPi Camera FMC. The result is that you can now build and develop the Smartcam and NLP-Smartvision applications in Certified Ubuntu 22. [Read More]

Camera FMC: Connecting MIPI cameras to FPGAs

Camera FMC: Connecting MIPI cameras to FPGAs
FPGAs and MPSoCs are ideally suited for machine vision applications due to their ability to process large amounts of data in parallel and at high speeds. FPGAs can run highly power efficient neural network implementations and benefit from ultra low latency connections to multiple image sensors. Given the inherent strengths of FPGAs for machine vision, it surprises me that GPUs have become the dominant hardware platform for deep learning applications1 in recent years. [Read More]

A peek at the new RPi Camera FMC

A peek at the new RPi Camera FMC
In the coming weeks we’ll be launching a new product called the RPi Camera FMC. This compact little FMC card allows you to connect 4x Raspberry Pi cameras (and variants) to a few Zynq UltraScale+ MPSoC boards listed below. All of the boards will support 4 cameras through the same FMC card. Xilinx ZCU104 Xilinx ZCU102 Xilinx ZCU106 TUL PYNQ-ZU Digilent Genesys-ZU Avnet UltraZed-EV Starter Kit I like Raspberry Pi and especially the impressive camera ecosystem that they and the RPi community have built up. [Read More]

Introducing 96B Quad Ethernet Mezzanine

Introducing 96B Quad Ethernet Mezzanine
Update 2019-06-10: This product is now available to purchase! Read the documentation here, and get it from the order page here. Over the last few months I’ve been really busy working on a new product and I just want to take a step back today and share some of it. Let me start with what it is and then I’ll tell you about how and why I did it. The product A 4-port Gigabit Ethernet mezzanine card designed for Avnet’s Ultra96 Zynq Ultrascale+ single board computer. [Read More]

Board bring-up: MYIR MYD-Y7Z010 Dev board

In this tutorial video, I bring-up the 3x Gigabit Ethernet ports on the MYD-Y7Z010 Development board from MYIR. Firstly, I create a Vivado design for this board, then I export it into the SDK and generate the echo server application for each of the 3 ports (note that the echo server application only supports one port at a time). At the end of the video, I test each of these designs on hardware and ensure that the ports are given an IP address via DHCP and that I can ping the port. [Read More]
lwip  myir  zynq