Aupera Facial Recognition Solution is end-to-end commercially deployable solution for facial recognition in the field. Equipped with Aupera proprietary Best-in-Class trained AI model, it has been in field deployment by Tier-1 customers for Smart Building Management, Smart City and Smart Retail Applications. The solution features high accuracy achieved by agile FPGA computing platforms on the edge, ensuring data privacy and sovereignty for end customers. The solution includes full software stack and trained AI model, which can be deployed within minutes after license being activated.
Last Update: February 23, 2021
Size: 1.40 G
Container Version: fr_u30_v2.0.1 _v2.9.3b112
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This application is containerized and can be easily run in a few minutes in the cloud, or on-premises.
Follow the instructions based on your deployment method.
An access key is required to authenticate a user and grant them access to the application based on their entitlements. To obtain your account access key, follow these steps:
Note: The resulting access key will enable all entitlements within your account. If you have not yet obtained entitlements from the "TRY OR BUY" section above, you must do so before following these steps for generating your access key.
The Xilinx Runtime (XRT) host application is supported on Ubuntu 18.04. With sudo access, use the following command to download and run the setup script:
git clone https://github.com/Xilinx/Xilinx_Base_Runtime.git cd Xilinx_Base_Runtime
./host_setup.sh -v 2020.1 --skip-shell-flash
Install Aupera Face Recognition Docker image
a. Prepare essential software and other related packages:
$sudo apt update;sudo apt install make build-essential nfs-kernel-server docker docker-containerd docker.io $sudo service rpcbind restart $sudo service nfs-kernel-server restart
b. Pull Docker image and check:
$docker pull xilinxpartners/aupera_face_recognition:2.0.1 $docker images aupera_face_recognition
c. Copy firmware and driver from Docker image
$docker create --name <CONTAINER_NAME> xilinxpartners/aupera_face_recognition:2.0.1 bash $docker cp <CONTAINER_NAME>:/root/driver <NFS_ABS_PATH> $docker cp <CONTAINER_NAME>:/root/firmware <NFS_ABS_PATH>
Here <CONTAINER_NAME> is a user defined container name, like face, <REPOSITORY>:<TAG> is the repository name, like aupera_face_recognition:2.0.1, <NFS_ABS_PATH> is local directory where firmware and driver will copied to, like /opt/aupera/face-recognition.
a. Source XRT env and check the current XRT version.
Currently XRT version 2.6.655 or 2.6.0 are required for the firmware installation.
$cd /opt/xilinx/xrt/ $source setup.sh $ xbutil --version XCLMGMT: 2.6.655
b. Run lspci command to validate the U30 board seen by the OS
$sudo lspci -d 10ee: 07:00.0 Processing accelerators: Xilinx Corporation Device 503d (rev 02) 07:00.1 Processing accelerators: Xilinx Corporation Device 503c (rev 02) 08:00.0 Processing accelerators: Xilinx Corporation Device 503d (rev 02) 08:00.1 Processing accelerators: Xilinx Corporation Device 503c (rev 02)
Two devices and four functions will be found by the OS if the card is successfully installed.
c. Flash the U30 board using XRT xbmgmt utility:
$sudo /opt/xilinx/xrt/bin/xbmgmt flash --shell --card <card_id> --path <binfile>.bin
Where, <card_id> is the BDF ID read from lspci, like 07:00.1, and <binfile> is the file name of the Aupera firmware QSPI flash dump file in the directory <NFS_ABS_PATH>/firmware/. After completion, flash another one with the second card_id (like 08:00:1) read from lspci and the same flash dump file.
d. After flash, cold reboot server, please do not use ‘sudo poweroff’ or ‘sudo reboot’ command.
$cd <NFS_ABS_PATH>/driver $sudo ./install.sh
a. Setup Environment Variables
$source <(curl -s https://raw.githubusercontent.com/Xilinx/Xilinx_Base_Runtime/master/utilities/xilinx_docker_setup.sh)
b. Docker Run
$docker run -dit --name <CONTAINER_NAME> $XILINX_DOCKER_DEVICES -v <NFS_ABS_PATH>:<NFS_ABS_PATH> -e NFS_ABS_PATH=<NFS_ABS_PATH> -p 56108:56108 <REPOSITORY>:<TAG> bash
An example of the command line:
$docker run -dit --name face $XILINX_DOCKER_DEVICES -v /opt/aupera/face-recognition/:/opt/aupera/face-recognition/ -e NFS_ABS_PATH=/opt/aupera/face-recognition/ -p 56108:56108 aupera_face_recognition:2.0.1 bash
c. Refer to above section 1 to generate a license file (cred.json) and choose a configuration file (conf.json), copy them to <NFS_ABS_PATH>/drm.
d. Start Face Recognition service
$docker container exec -it <CONTAINER_NAME> bash start.sh
An example of the command line:
$docker container exec -it face bash start.sh