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.
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.
|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
|Dual Cortex-A7 1.2GHz Processor
|GC2145 1080P Colored Sensor
|FOV 68° , DOF= 60cm- ∞
|5V @ 500mA
|TypeC x1, UART x1, TFCard x1, Button x1, Microphone x1, Fan x1
|150Mbps 2.4GHz 802.11 b/g/n
|0°C to 60°C
|Plastic ( PC )
Download the corresponding SR9900 driver according to the operating system used.
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.
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)
sudo ifconfig en10 down
sudo ifconfig en10 up
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.
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).
UnitV2 Built-in functions out of the box