Grove Vision AI Module is a thumb-sized board based on Himax HX6537-A processor and equips with an OV2640 camera, a digital microphone and a 6-axis Inertial Measurement Unit (IMU). It's fully supported by Edge Impulse which allows you seamlessly sample raw data, build models and deploy the trained ML models to the module without any programming. It is compatible with the ecology of XIAO series and Arduino, ideal for a wide range of object detection applications.

Note

Check out the upgraded version Grove Vision AI Module v2, which is based on Himax WiseEye2 HX6538 processor featuring a dual-core Arm Cortex-M55 and integrated Arm Ethos-U55.

Update

We're excited to have Edge Impulse officially support our Grove-Vision AI Module. Now, you can follow our Wiki or go to the Edge Impulse website to get started training and deploying your ML models!

The module features a compact AI-powered OV 2640 camera sensor embedded with Edge Machine Learning algorithms and can be easily deployed with simple clicks. It is a small and great assistant for various object detection projects and can be customized based on different needs. Just imagine endowing devices with vision through a tiny sensor.

Artificial Intelligence camera (AI camera) is the enhanced camera powered by a built-in Edge Machine Learning algorithm, smartly processing with computational photography to perform enhanced object detection in real-time. It has been widely used in smartphones for face recognition, edge devices for wildlife detection, and other Edge Intelligence applications.

This compact camera sensor will be the perfect module for you to get started with the AI-powered camera. It is installed with one pre-trained model that allows you to detect human faces. Furthermore, it has been installed with three ML classification algorithms for model recognition, which allows you to freely develop the models for detecting different objects and directly apply them to your projects.

Launched by Seeed Studio, the IoT hardware enabler, the sensor includes two typical IoT modules: a digital microphone and a 6-axis Inertial Measurement Unit (IMU), for your further usage of edge AI. Edge Impulse has annouced the IMU and Microphone Support for Grove - Vision AI, to get you started, here are two tutorials focused on the Microphone and IMU Sensors:

Use YOLOv5 to Build Detect Models of Your Own

YOLO is an abbreviation for the term 'You Only Look Once'. It is an algorithm that detects and recognizes various objects in an image in real-time. Ultralytics YOLOv5 is the version of YOLO based on the PyTorch framework. Based on its repository, Seeed Studio has published a more suitable version that fits in Seeed Studio AIoT hardware/devices. You can use this repository to build detect models of your own. They can not only be implemented on the Grove vision AI module but also on the industrial-level SenseCAP A1101 - LoRaWAN Vision AI Sensor.

Meanwhile, we have provided a specific tutorial to show you how to train the AI model for specific applications and then deploy it onto the devices.

Transmit Your Data to the SenseCAP Cloud

Same as the SenseCAP industrial-level sensors, the base-level Grove Vision AI Module can be connected to the SenseCAP cloud for data transmission. We are proud to introduce the SenseCAP K1100 - The Sensor Prototype Kit with LoRa® and AI that combines Wio Terminal and other classic IoT sensors to achieve this function.

The kit enables you to rapidly digitize the world using LoRa and AI technology to tackle real-world challenges. With this plug-and-play toolkit, anyone can add AI to their edge devices and unlock the potential of AIoT. After walking through the plain and easy tutorials, you can connect the sensors with the SenseCAP cloud by LoRaWAN or Wi-Fi within 10 minutes.

Build the Project with a Smaller MCU Board: Seeed Studio XIAO

Around the ports of the Grove Vision AI, there are dual 7-pin headers built to connect the Seeed Studio XIAO series. Seeed Studio XIAO series are all designed as thumb-sized development boards, empowered by popular and powerful chips: SAMD21, nRF52840, RP2040, and ESP32C3. In addition, it is so compact that all SMD components are placed on the same side of the board, so designers can easily integrate XIAO into the boards for rapid production.

Attention

Please be cautious of the connection method and be careful when you soldered the slot.

Key Features:

Fully supported by Edge Impulse : Seamlessly sample raw data from the camera, build models and deploy trained ML models to the module from the studio without any programming
Compact AI camera sensor: Equipped with OV2640 SOC sensor that supports auto-exposure and auto-white balance to offer good images
Customizable model: Support the import of up to 3 customized models to realize mainstream ML functions like object detection
Simple development & deployment: Support Arduino IDE programming and drag-and-drop model implementation
High compatibility: Perfectly match with XIAO series interface, supports Arduino ecology through Grove connector

Specifications:

Characteristic Value
Operating Voltage 5
Rate 115200
I2C Interface Seeed Studio XIAO & Arduino
Power Supply dual 7-pin connector & Type-C
Downloading & Firmware Burn Interface Type-C
Dimensions 40 * 20 * 13

Applications:

People Detection
Customized Object Detection
Smart Doorkeeper
Fall Detection & Alarm
Face Recognition

Hardware Layout:

Connector	Grove (Grove base for Arduino)	5V Charge and Data Transmission
	Double row 7pin socket (Seeed Studio XIAO)	5V Charge and Data Transmission
	USB Type-C	5V Charge and Firmware Burn
Communication Mode	IIC
Processor	Himax HX6537-A	400Mhz DSP (ultra-low power consumption)
Camera Sensor	OV2640	Resolution Ratio up to 1600 1200