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Nicla Vision projects and builds

Compact machine-vision board with a 2 MP camera, dual-core STM32H7, microphone, IMU and time-of-flight distance sensor.

Official page ↗Buying-link policy
Nicla Vision product photograph
Image: Arduino product photography ↗ · Original image asset ↗Manufacturer product photograph copied locally at reduced WebP resolution solely to identify the device in independent editorial coverage. The image is attributed and linked to its original product page, is not used as a brand asset or endorsement, and should be removed if the rights holder objects.

Why it belongs on the bench

Arduino Nicla Vision is a compact machine-vision board built around a dual-core STM32H747, two-megapixel camera, microphone, six-axis motion sensor, time-of-flight distance sensor, Wi-Fi and Bluetooth LE. Its OpenMV and MicroPython support suits the catalogue’s camera getting-started workflow and custom Edge Impulse image-classification project. Firmware choice matters: uploading an Arduino sketch replaces the shipped OpenMV environment, and returning to OpenMV requires a DFU recovery and firmware reinstall. Models also need to fit the board’s internal flash; Arduino’s classification guide recommends a small MobileNetV2 configuration and warns that larger ROM footprints are unlikely to fit.

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Sources

Sources and further reading

Original project pages, manufacturer documentation and repositories used while preparing this page. Last reviewed .

  1. Nicla Vision official pageArduino
  2. Getting Starteddocs.arduino.cc
  3. Image Classificationdocs.arduino.cc

Nicla Vision projects and open-source builds

Guides for Nicla Vision

learn

Start an edge-AI camera project: XIAO Sense vs Nicla Vision vs Watcher

Choose XIAO ESP32S3 Sense for the lowest-cost camera prototype, Nicla Vision for a compact OpenMV/TinyML development board with richer onboard sensing, and SenseCAP Watcher for a packaged event-detection appliance that integrates with automation systems. Prove capture and lighting first, then measure an inference model on examples from the real deployment rather than trusting a demo score.

3 devices

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