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Note: pls, use PC chrome/edge browser, if can't connect, refresh the webpage.

1. Click connect button

2. After connected successfully, pick a firmware

3. Click the burn button

4. After burning successfully, Unplug the device and restart.

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UnitV2 USB

SKU:U078-USB

Quick Start

Description

The UnitV2 USB is the latest high efficiency AI recognition module from M5Stack, it adopts Sigmstar SSD202D (integrated dual-core Cortex-A7 1.2GHz processor) control core, 128MB-DDR3 memory and 512MB NAND Flash. It offers USB-A universal interface, which allows you to connect various UVC Cameras, Built-in Linux operating system, integrated with rich hardware and software resources and development tools brings you a simple and efficient AI development experience right out of the box!

Product Features

  • Sigmstar SSD202D
  • Dual-core Cortex-A7 1.2GHz processor
  • 128MB DDR3
  • 512MB NAND Flash
  • USB-A universal interface, can be connected to various UVC cameras
  • Built-in microphone
  • Wi-Fi 2.4GHz
  • Development method:
    • Equipped with 12 ways AI image functions: QR code, face detection, line tracking, movement, shape matching, image streaming, classification, color tracking, face recognition, target tracking, shape detection, custom object detection
    • Support online preview, UIFlow (used as serial port json format)
    • Linux system(OpenCV, SSH, JupyterNotebook)

Include

  • 1 x M5Stack UnitV2 USB
  • 1 x 16g TF Card
  • 1 x USB-C cable (50cm)
  • 1 x bracket
  • 1 x back clip

Application

  • AI recognition function development
  • Industrial visual recognition classification
  • Machine vision learning

UNIT-V2 series comparison

Spec UNIT-V2 UNIT-V2 M12 UNIT-V2 USB
Lens equipment Normal focal length (FOV 68°) Normal focal length (FOV 85°) + wide-angle focal length (FOV: 150°) Without lens, USB-A universal interface, can be connected to various UVC cameras
CMOS GC2145 GC2053 /

Specifications

Specifications Parameters
Sigmstar SSD202D Dual Cortex-A7 1.2GHz Processor
Flash 512MB NAND
RAM 128MB-DDR3
Camera Not equipped with a lens, USB-A universal interface, can be connected to various UVC cameras
Input voltage 5V @ 500mA
Hardware Peripherals TypeC x1, UART x1, TFCard x1, Button x1, Microphone x1, Built-in active cooling fan x1
Indicator light Red, White
Wi-Fi 150Mbps 2.4GHz 802.11 b/g/n
Ethernet network card SR9900

Driver Installation

Download the corresponding SR9900 driver according to the operating system used.

Windows10

Extract the driver compressed package to the desktop path -> Enter the device manager and select the currently unrecognized device (named with SR9900) -> Right-click and select Custom Update -> Select the path where the compressed package is decompressed -> Click OK and wait for the update carry out.

MacOS

Extract the driver package -> double-click to open the SR9900_v1.x.pkg file -> follow the prompts and click Next to install. (The compressed package contains a detailed version of the driver installation tutorial pdf)

  • After the installation is complete, if the network card cannot be enabled normally, you can open the terminal and use the command below to re-enable the network card.
sudo ifconfig en10 down
sudo ifconfig en10 up

Out Of The Box AI Recognition Function

  • UnitV2 integrates not only the basic AI recognition developed by M5Stack, but also has built-in multiple recognition (such as face recognition, object tracking and other common functions), which can quickly help users build AI recognition applications.

  • All features! Plug and play! UnitV2 has a built-in wired network card. When you connect to a PC through the TypeC interface, it will automatically establish a network connection with UnitV2.Flexibly Connectable, it can also be connected and debugged via Wi-Fi.

  • UART serial port output, all identification content is automatically output in JSON format through the serial port for convenient use.

  • Built-in recognition function use tutorial

  • Identify the source code of the service framework

  • Firmware update tutorial

Development Efficiency Improvement

Video

UnitV2 Built-in functions out of the box

UnitV2 Applications