M5Stack UnitV2 M12 Version with Cameras
📦 Location of the warehouse: China
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M5Stack UnitV2 M12 Version with Cameras
UnitV2 is a high-efficiency AI recognition module from M5Stack, It adopts Sigmstar SSD202D (integrated dual-core Cortex-A7 1.2GHz processor) control core, integrated 128MB-DDR3 memory, 512MB NAND Flash, 1080P camera. Equipped with 1x regular focal length (FOV: 85°) + 1x wide-angle fisheye lens (FOV: 150°) two M12 general specifications lenses, support manual focus adjustment. Embedded 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!
Features
- Sigmstar SSD202D
- Dual-core Cortex-A7 1.2GHz processor
- 128MB DDR3
- 512MB NAND Flash
- GC2053 1080P Colored Sensor
- Equipped with dual lenses: regular focal length (FOV: 85°) + wide-angle fisheye lens (FOV: 150°)
- 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 recognition
- Support web online preview, UIFlow (used as serial port json format)
- Linux system (OpenCV, SSH, JupyterNotebook)
Include
- 1 x M5Stack UnitV2 M12
- 1 x 16g TF Card
- 1 x USB-C cable (50cm)
- 1 x bracket
- 1 x back clip
- 1x regular focal length lens (FOV: 85°)
- 1x wide-angle fisheye lens (FOV: 150°)
Applications
- 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, the USB-A universal interface, can be connected to various UVC cameras |
| CMOS | GC2145 | GC2053 | / |
Specification
| Specifications | Parameters |
|---|---|
| Sigmstar SSD202D | Dual Cortex-A7 1.2GHz Processor |
| Flash | 512MB NAND |
| RAM | 128MB-DDR3 |
| Camera | GC2053 1080P Colored Sensor |
| Lens | 1x regular focal length (FOV: 85°) + 1x wide-angle fisheye lens (FOV: 150°) |
| 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 |
| Package Size(with lens） | 48 * 24 * 32mm |
Windows
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
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 format through the serial port for convenient use.
JSON
Development Efficiency Improvement
-
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).
Effective Date: March 27, 2025
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