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Developed with Vivado 2022.1, these behavioral simulations show how to recover native video timing from an AXI4 Video Stream and how to convert natively timed video to AXI4 Streams using catalog IP blocks including the Video Tiiming Controller, AXI4 Stream to Video Out and Video In to AXI4 Stream IP. AXI4 Stream input video is simulated using a Video Test Pattern Generator and the AXI4 Video Stream Remapper IP to show how to convert from 2 pixels per clock to 1 pixel per clock.

Developed with Vivado 2022.1, these behavioral simulations show how to use the Video Test Pattern Generator and highlight how to control the test pattern generation framerate using a Video Timing Controller and Video In to AXI Stream conversion IP. The simulation simulations a QQVGA (160x120) resolution frame size, showing 4 frames generated as fast as the TPG can generate them at 25MHz bus clock, then shows 4 frames generated with 60fps refresh rate timine (1.944MHz Pixel Clock).

The example design can be used as a reference of how to properly instantiate the Video TPG in a block design and configure a Linux build to generate (and display) test patterns using GStreamer. Four test pattern generator configurations are provided:

(1) Free Running mode (2) Free Running mode with Colorspace Conversion and Scaling using the Video Processing Subsystem IP (3) Rate Controlled mode (4) Rate Controlled mode with Colorspace Conversion and Scaling using the Video Processing Subsystem IP

Yocto meta-layer for MaaXBoard/Mini/Nano

The gitlab will demonstrate the process of creating a meta-user recipe to build custom R5 RPU applications.

This lab descripts the process of running OpenAMP on the Zynq and Zynq Ultrascale+ MPSoC utilizing APUs and RPUs.

Scripted build examples for generating custom ZCU106 Vitis Platforms with Overlay Support, including DPU, SOFTMAX, VVAS HLS Accelerators, etc...)

Jason's collection of custom Vitis Platform recipes. NOTE: The platforms in this repository are for training, debug and integration. WARNING: Makefile stages have been broken up into shell scripts on the back end and MAKE dependencies have been removed. If a MAKE stage fails the build will continue, so be sure to check the console log for errors when using projects from this repository.

Modification of XLX aibox-reid app into face recognition

This article is a complete flow to create a Linux image using Yocto 2021.1.

This lab demos the process of adding applications to a Xilinx Yocto Image.

This lab will focus on applying Linux modifications to a 2021.1 Xilinx Yocto image created with the Xilinx Yocto Manifest.