Seeed Studio Studio Grove Vision AI Module V2 - Arm Cortex-M55 & Ethos-U55
Seeed Studio Studio Grove Vision AI Module V2 - Arm Cortex-M55 & Ethos-U55 - Image 2
Seeed Studio Studio Grove Vision AI Module V2 - Arm Cortex-M55 & Ethos-U55 - Image 3
Seeed Studio Studio Grove Vision AI Module V2 - Arm Cortex-M55 & Ethos-U55 - Image 4
SKU: IOWC-1308
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Seeed Studio Studio Grove Vision AI Module V2 - Arm Cortex-M55 & Ethos-U55

₹1,939.00 (Inclusive of all taxes)
Out of Stock

The Seeed Studio Studio Grove Vision AI Module V2 is an embedded vision AI module powered by a Himax WiseEye2 HX6538 processor with dual-core Arm Cortex-M55 and integrated Ethos-U55 NPU. It supports TensorFlow and PyTorch frameworks and is compatible with Arduino IDE, Raspberry Pi, and ESP-based development boards for deploying AI models via the SenseCraft platform.

Features

  • Powered by Himax WiseEye2 HX6538 with dual-core Arm Cortex-M55 CPU (up to 400MHz) and integrated Arm Ethos-U55 NPU for efficient on-device AI inference.
  • Supports TensorFlow and PyTorch frameworks; deploy pre-trained models like YOLOv5/v8, MobileNet, and EfficientNet-Lite via the SenseCraft AI platform without coding.
  • Standard CSI camera interface and onboard PDM microphone enable multimodal AI applications combining vision and audio sensing.
  • Versatile connectivity via Grove I2C, Type-C, SPI, and UART interfaces, compatible with Seeed Studio XIAO, Arduino, Raspberry Pi, and ESP dev boards.
  • Includes SD card slot for data logging and model storage, powered by a single 5V supply via dual 7-pin connector or USB Type-C.

Out of stock

Description

The Grove Vision AI Module V2 is a dedicated edge AI processor module designed for low-power, high-performance computer vision applications. Its core is the Himax WiseEye2 HX6538 SoC, which pairs a dual-core Arm Cortex-M55 application processor with an integrated Arm Ethos-U55 microNPU, delivering up to 400MHz clock speeds for both CPU and NPU tasks. This architecture enables real-time execution of neural networks directly on the module, eliminating the need for a separate host MCU for basic inference workloads.

The module provides a complete sensor-fusion platform with a Camera Serial Interface (CSI) for connecting MIPI camera sensors and an onboard PDM digital microphone for audio event detection. Power management is streamlined for embedded IoT, operating from a 5V supply with flexible input options via the Grove connector or USB Type-C port. Its peripheral set includes SPI, UART, and I2C buses, making it a flexible co-processor that can interface with a wide range of host controllers and development ecosystems for rapid prototyping and deployment.

Key Features

  • Edge AI Processing: Arm Ethos-U55 microNPU accelerates neural network inference for real-time object detection, classification, and audio event recognition at ultra-low power.
  • Framework & Model Flexibility: Supports TensorFlow Lite for Microcontrollers and PyTorch models; compatible with SenseCraft AI for zero-code deployment of custom or off-the-shelf models.
  • Multimodal Sensing Hub: Integrates a standard CSI-2 interface for high-resolution camera modules and a built-in PDM microphone for concurrent audio-vision AI applications.
  • Expandable Storage & Logging: Onboard SD card slot supports high-capacity microSD cards for storing inference data, training datasets, or multiple AI model files.
  • Developer-Friendly Ecosystem: Fully open-source with provided schematics, libraries, and examples for Arduino IDE, Raspberry Pi, and ESP-IDF, accelerating integration.
  • Low-Power Edge Deployment: Optimized processor and NPU sleep modes enable always-on vision AI in battery-powered IoT devices like smart cameras and wearables.

Applications

  • Industrial Automation: Visual quality inspection, predictive maintenance monitoring, and voice-controlled machinery interfaces.
  • Smart City Infrastructure: Device status monitoring, public space occupancy sensing, and energy management systems.
  • Transportation & Logistics: Vehicle status monitoring, asset location tracking, and package sorting vision systems.
  • Smart Agriculture: Crop health monitoring, pest detection, and environmental parameter logging with visual verification.
  • Mobile & Wearable IoT: Gesture-controlled wearable devices, handheld scanners, and smart appliance with always-on vision AI.

Technical Specifications

Microcontroller / SoCHimax WiseEye2 HX6538 with dual-core Arm Cortex-M55 & integrated Arm Ethos-U55 NPU
CPU FrequencyUp to 400MHz (Big Core), Up to 150MHz (Little Core)
NPU FrequencyUp to 400MHz (Arm Ethos-U55)
System MemoryConfigurable up to 2432KB SRAM, 64KB Boot ROM
AI Framework SupportTensorFlow, PyTorch (via SenseCraft AI platform)
Supply Voltage5V
Power InputDual 7-pin connector, USB Type-C, Grove connector
Onboard PeripheralsPDM Digital Microphone, SD Card Slot
InterfacesCSI (Camera), SPI, UART, I2C (Grove), USB Type-C
Default Baud Rate115200 bps
SD Card SupportSD, SDIO host
Operating TemperatureNot specified
Dimensions (Shipping)14 x 9 x 3 cm

Frequently Asked Questions

How do I power the Grove Vision AI Module V2 and what are the power requirements?

The module requires a 5V DC power supply, which can be provided through its dual 7-pin connector, the USB Type-C port, or the Grove interface. Ensure your power source can deliver sufficient current for the active cores and NPU during inference. For lowest power operation, utilize the processor's sleep modes and power management features when the vision pipeline is idle.

What cameras are compatible with the module's CSI interface and how do I connect one?

The module features a standard MIPI CSI-2 interface compatible with many Raspberry Pi Camera Module variants and other MIPI CSI sensors. You will need a compatible flat flexible cable (FFC) to connect the camera to the module's CSI connector. Ensure the camera's voltage requirements match the module's I/O voltage. Driver support and configuration examples are provided in the Seeed Studio Studio documentation and SenseCraft AI platform.

How do I load and run a custom TensorFlow or PyTorch model on this Vision AI Module?

Deploy models using the SenseCraft Web IDE or offline tools. First, convert your trained TensorFlow Lite or PyTorch model to a compatible format supported by the Ethos-U55 NPU backend. Then, upload the model file to the module via USB or SD card. Use the provided Arduino library or Python SDK on a connected host (like a Raspberry Pi) to send image data from the CSI camera to the module and receive inference results over UART or I2C.

Can I use this module as a standalone device without an external host microcontroller?

Yes, the module can operate standalone for specific applications. Its dual-core Cortex-M55 can run application logic and manage the Ethos-U55 NPU directly. You would need to develop firmware using the provided SDK to handle camera initialization, image capture, inference triggering, and output handling via its GPIOs or serial interfaces. The SD card slot allows for storing application code and models, enabling fully autonomous edge AI devices.

Package Includes

  • 1 x Seeed Studio Studio Grove Vision AI Module V2
  • 1 x Cable

Additional Information

Weight 0.012 kg
Dimensions 9 × 14 × 3 cm

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