M5Stack UnitV2 is a high-efficiency AI recognition module launched by M5Stack, using Sigmstar SSD202D (integrated dual-core Cortex-A7 1.2GHz processor) control core, integrated 128MB-DDR3 memory, 512MB NAND Flash, and 1080P camera. With embedded Linux operating system and rich software and hardware resources and development tools integrated, UnitV2 is committed to bringing users a simple and efficient AI development experience out of the box.

Note:
Best to use the original M5 data cable to connect to the computer, otherwise it may cause a crash, and the loose data cable may also cause a crash.
Edge and Chrome browsers are recommended, Firefox has a certain chance of causing it to cause a crash or the screen is not smooth.

Features

Sigmstar SSD202D
Dual Cortex-A7 1.2GHz Processor
128MB DDR3
512MB NAND Flash
GC2145 1080P Colored Sensor
Microphone
Wi-Fi 2.4GHz

Applications

AI recognition function development
Industrial visual identification sorting
Machine vision learning

Video

Learn

Quick Start

Driver Installation

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

Driver Name	Download Link
SR9900_Windows	Download
SR9900_MacOS	Download

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

Unzip 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

Specification

Resources	Parameter
Sigmstar SSD202D	Dual Cortex-A7 1.2GHz Processor
Flash	512MB NAND
RAM	128MB-DDR3
Camera	GC2145 1080P Colored Sensor
Lens	FOV 68° , DOF= 60cm- ∞
Power Input	5V @ 500mA
Peripherals	TypeC x1, UART x1, TFCard x1, Button x1, Microphone x1, Fan x1
Indicator light	Red, White
Wi-Fi	150Mbps 2.4GHz 802.11 b/g/n
Operating Temperature	0°C to 60°C
Net weight	18g
Product Size	4818.524mm
Package Size	1573838mm
Case Material	Plastic ( PC )

Hardware Overview

Include

1 x M5Stack UnitV2
1 x 16g TF Card
1 x USB-C Cable (50cm)
1 x Stand
1 x Back Brick

Documents

Out Of The Box AI Recognition Function

UnitV2 integrates not only the basic AI recognition service developed by M5Stack, but also has built-in multiple recognition functions (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. With highly free connectable style, 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, which is convenient to call.
Built-in recognition function use tutorial
Identify the source code of the service framework
Firmware update tutorial

Development Efficiency Improvement

UnitV2’s factory Linux image integrates a variety of basic peripherals and development tools (such as Jupyter Notebook etc.)
Through SSH access, you can fully control the hardware resources of this camera
Easily build a custom recognition model through M5Stack’s V-Training (AI model training service).
V-Training online AI model training service
Jupyter Notebook Development Tutorial/Example
SSH connection & WIFI configuration

Schematic

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