Current Product Don't Have Test Firmware
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.
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!
|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|
|Sigmstar SSD202D||Dual Cortex-A7 1.2GHz Processor|
|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|
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.
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)
sudo ifconfig en10 down sudo ifconfig en10 up
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.
UnitV2's factory setting 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