Zynq UltraScale MPSoC Base TRD 2016.4 - Design Module 7


Zynq UltraScale MPSoC Base TRD 2016.4 - Design Module 7

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Design Overview


This module shows how to add a 2D convolution filter between the capture pipeline and the display. The 2D filter is implemented purely in software using the OpenCV library.





Design Components


This module requires the following components:
  • zcu102_base_trd (SDSoC)
  • pmu_fw
  • petalinux_bsp
    • zynqmp_fsbl
    • bl31
    • u-boot
    • kernel
    • device tree
    • rootfs
  • filter2d (SW)
  • video_lib
  • video_qt2



Build Flow Tutorials


2D Filter Sample


This tutorial shows how to build the OpenCV version of the 2D filter sample based on the Base TRD SDSoC platform.

  • Follow the steps in design module 5 to create a new workspace and to import the video_lib and video_qt2 projects. Otherwise, open the existing XSDK workspace only this time using the SDx tool instead of XSDK.

    % cd $TRD_HOME/apu/video_app
    % sdx -workspace . &&
  • Change the eclipse perspective to 'SDx' instead of 'C/C++' which is the current selection.
  • Create a new SDx Project
  • Enter 'filter2d' as project name
  • Click 'Add Custom Platform', browse to the $TRD_HOME/apu/zcu102_base_trd directory and confirm. Select the newly added 'zcu102_base_trd (custom)' platform from the list and click 'Next'.
  • Check the 'Linux Root File System' box and browse to the $TRD_HOME/apu/petalinux_bsp/build/linux/rootfs/stage directory. This assumes the petalinux-build command has been run in a previous module.
  • Check the 'Shared Library' box and click 'Next'.
  • Select the '2D Filter' template and click 'Finish'.
  • Change the 'Active build configuration' to Release in the SDx Project Settings window.
  • Remove the filter2d_sds HW function by highlighting the function name and clicking the red X symbol.
  • Right-click the filter2d project, select 'C/C++ Build Settings'. Navigate to the 'Build Artifacts' tab and add the output prefix 'lib'. Click OK.
  • Right-click the filter2d project and select 'Build Project'.
  • Copy the content of the generated sd_card folder to the dm7 SD card directory

    % mkdir -p $TRD_HOME/images/dm7/bin
    % cp -rf filter2d/Release/sd_card/* $TRD_HOME/images/dm7/

Video Qt Application


This tutorial shows how to build the video library and the video Qt application.

  • Right-click the video_lib project, select 'C/C++ Build Settings'. Add the symbol 'WITH_SDSOC' and click OK.
  • Source the Qt setup script to re-generate the Qt Makefile reflecting these changes.

    % cd $TRD_HOME/apu/video_app/video_qt2
    % source qmake_set_env.sh
    % qmake video_qt2-dm7.pro -r -spec linux-oe-g++
  • Right-click the video_qt project and click 'Build Project'.
  • Copy the generated video_qt2 executable to the dm7 SD card directory.

    % cp -f video_qt2 run_video.sh video_qt2_wrap.sh $TRD_HOME/images/dm7/bin/



Run Flow Tutorial


  • See here for board setup instructions.
  • Copy all the files from the $TRD_HOME/images/dm7 SD card directory to a FAT formatted SD card.
  • Power on the board to boot the images; make sure INIT_B, done and all power rail LEDs are lit green.
  • After ~30 seconds, the display will turn on and the application will start automatically, targeting the max supported resolution of the monitor (one of 3840x2160 or 1920x1080 or 1280x720).
  • Upon application exit, use the below login and password to log into the framebuffer or serial console:

    root@Xilinx-ZCU102-2016_3 login: root
    password: root
  • The SD card file system is mounted at /media/card
  • To re-start the TRD application type run_video.sh
  • The user can now control the application from the GUI's control bar (bottom) displayed on the monitor.
  • By default, application launches with VIVID as a video-source, user can also select TPG from the "Video-source selection" button present on the GUI's control-bar.
    • Virtual Video Device (VIVID): emulates a USB webcam purely in software
    • USB Webcam (UVC): using the universal video class driver
    • Test Pattern Generator (TPG); implemented in the PL
  • A 2D convolution filter can be turned on and different filter presets can be selected; the following filter modes are available:
    • OFF - accelerator is disabled/bypassed
    • SW - accelerator is run on A53 using OpenCV algorithm
    • HW - accelerator is run on A53 using HLS algorithm
  • The video info panel (top left) shows essential settings/statistics.
  • The CPU utilization graph (top right) shows CPU load for each of the four A53 cores.

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