UnitV2 is a high-efficiency Ai recognition module from M5Stack It uses the 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 GC2145 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) Includes 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 Specification Specifications Parameters Sigmstar SSD202D Dual Cortex-A7 1.2GHz Processor Flash 512MB NAND RAM 128MB-DDR3 Camera GC2145 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 Documentation For quick start guides, schematics, and driver downloads check out the M5Stack doc page
