M5Stack UnitV2 USB Version without Camera

Description

UnitV2-USB is an AI recognition module designed for users who want the UnitV2 computing platform without an integrated camera. UnitV2-USB uses the Sigmstar SSD202D dual-core Cortex-A7 processor, 128MB DDR3 memory, and 512MB NAND Flash to run an onboard Linux environment for AI vision development.

The USB AI camera module provides a USB Type-A universal interface for connecting compatible UVC cameras, while Type-C, UART, TF card, microphone, button, active cooling, Wi-Fi, and SR9900 Ethernet support make UnitV2-USB practical for prototypes and embedded deployments. This AI recognition module supports web preview, UIFlow JSON calls, OpenCV, SSH, and Jupyter Notebook workflows.

Features

• UnitV2-USB AI recognition module with Sigmstar SSD202D dual-core Cortex-A7 1.2GHz processor.
• 128MB DDR3 memory and 512MB NAND Flash for onboard Linux and AI processing.
• USB AI camera module with USB-A universal interface for connecting compatible UVC cameras.
• Built-in Wi-Fi 2.4GHz and SR9900 Ethernet card for network workflows.
• Supports 12 common AI image functions including QR code, face detection, line following, motion detection, classification, color tracking, face recognition, object tracking, contour detection, and custom object recognition.
• Development through web online preview, UIFlow, OpenCV, SSH, and Jupyter Notebook.
• UnitV2-USB includes Type-C, UART, TF card, button, microphone, and active cooling fan hardware.

Specifications

Applications

• UnitV2-USB for AI recognition module development with external UVC cameras.
• USB AI camera module projects for industrial vision classification.
• Machine vision learning, AI vision demos, and web preview experiments.
• UnitV2-USB prototypes that need Linux, OpenCV, SSH, and Jupyter Notebook access, with UnitV2-USB local services.

Product List

• 1 x UnitV2-USB
• 1 x 16GB microSD Card
• 1 x USB Type-C Cable (50cm)
• 1 x Stand
• 1 x Back Clip

Other Content

UnitV2-USB can expose online preview and AI function results through its local services. UnitV2-USB also helps developers test external cameras quickly. The AI recognition module is suitable for developers who want to pair the UnitV2 platform with their own UVC camera instead of using a fixed built-in lens.

For driver setup, the USB AI camera module documentation provides SR9900 Ethernet drivers for Windows and macOS, plus guides for UnitV2-USB base functions, model training, configuration, updates, and Jupyter Notebook operation.

Resources

• Documentation
• Base functions guide
• V-Training guide
• Jupyter Notebook guide
• Configuration guide
• Update guide
• UnitV2 Framework
• Windows Ethernet driver
• macOS Ethernet driver

FAQ

What makes UnitV2-USB different from other UnitV2 models?

UnitV2-USB has no built-in lens and instead provides a USB-A interface for compatible UVC cameras, making UnitV2-USB flexible for external camera setups.

What AI functions can the AI recognition module run?

The AI recognition module supports common image functions such as face detection, QR code recognition, classification, tracking, contour detection, and custom object recognition.

Can the USB AI camera module be used for development?

Yes. UnitV2-USB supports UnitV2-USB development tasks, and the USB AI camera module supports web preview, UIFlow JSON calls, Linux tools, OpenCV, SSH, and Jupyter Notebook workflows.