FP-AI-FACEREC1 getting started

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This document is a quick start guide to the Face recognition application.

This article provides an overview on the following topics:

Overview of the required hardware and software,
Setting up the hardware and software components,
Performing the vibration sensor data collection using the provided function pack,
Generating, Installing and testing the NanoEdge™ AI machine learning libraries on the sensor node STM32L562E-DK using the provided function pack, and
Some links to useful online resources, which can help a user to better understand the project and then customize the project for his own needs.

1. Hardware and software overview

1.1. Discovery kit with STM32L562QE MCU hardware description

The STM32L562E-DK is a complete demonstration and development platform, for Arm^® Cortex^®-M33 with Arm^® TrustZone^® and ARMv8-M mainline security extension core-based STM32L562QEI6QU microcontroller. The onboard MCU can run at 110 MHz/165 DMIPS, and has 512 Kbytes of Flash memory and 256 Kbytes of SRAM. The other key specifications of the board are:

1.54" 240 × 240 pixel-262K color TFT LCD module with parallel interface and touch-control pane, which can be used for standalone demos,
iNEMO 3D accelerometer and 3D gyroscope,
MEMS digital microphones, and a low-power stereo audio CODEC with headphone amplifier,
2 user LEDs,
User and reset push-buttons,
512-Mbit Octal-SPI Flash memory.
In terms of board connectors it includes :
- USB Type-C^®,
- Bluetooth^® V4.1 Low Energy module,
- microSD™ card,
- Stereo headset jack including analog microphone input, and
- JTAG debugger.

Information

Note: Arm^® and TrustZone^® are registered trademarks of Arm Limited (or its subsidiaries) in the US and or elsewhere.

For further details readers can have a look at the data brief for STM32L562E-DK.