This repository contains the install scripts needed to add PYNQ to your Kria KV260 Vision AI Starter Kit's official Ubuntu SDCard Image. From that installation, a complete Python and Jupyter environment is installed on the Kria SOM along with multiple programmable logic overlays all ready to use.
Follow the steps to Get Started with Kria KV260 Vision AI Starter Kit until you complete the Booting your Starter Kit section
Then install PYNQ on your Kria KV260 Vision AI Starter Kit. Simply clone this repository from the KV260 and run the install.sh script.
git clone https://github.com/Xilinx/Kria-PYNQ.git
cd Kria-PYNQ/
sudo bash install.shThis script will install the required debian packages, create Python virtual environment and configure a Jupyter portal. This process takes around 25 minutes.
JupyterLab can now be accessed via a web browser <ip_address>:9090/lab or kria:9090/lab. The password is xilinx
Base Overlay [GitHub]
This overlay includes support for the KV260's Raspberry Pi camera and PMOD interfaces. A Digilent Pcam 5C camera can be attached to the KV260 and controlled from Jupyter notebooks. Additionally, a variety of Grove and PMOD devices are supported on the PMOD interface - all controllable from a Xilinx Microblaze processor in programmable logic.
This overlay contains a Vitis-AI 1.4.0 Deep Learning Processor Unit (DPU) and comes with a variety of notebook examples with pre-trained ML models.
Composable Pipeline [GitHub]
The Composable pipeline is an overlay with a novel and clever architecture that allow us to adapt how the data flows between a series of IP cores.
One of PYNQ's first overlays, the PYNQ-Helloworld overlay includes an image resizer block in programmable logic. This overlay demonstrates a simple but powerful use of programmable logic HLS blocks to do image processing.
Copyright (C) 2021 Xilinx, Inc
SPDX-License-Identifier: BSD-3 License