Prophesee has announced the launch of the GenX320 Starter Kit for Raspberry Pi 5, making its breakthrough frameless sensing technology available to the Raspberry Pi developer community for the first time.
Built around Prophesee’s ultra-compact, ultra-efficient GenX320 event-based vision sensor, the kit connects directly to the Raspberry Pi 5 camera connector to allow development of real-time applications that leverage the advantages of event-based vision for drones, robotics, industrial automation, surveillance, and more.
The kit enables efficient, cost-effective and easy-to-use access to develop solutions based on Prophesee’s advanced Metavision event-based vision platform, through use of the company’s OpenEB, open-source core of its Metavision SDK. The Raspberry Pi ecosystem is one of the largest and most active hardware communities in the world, with more than 60 million units sold and millions of developers engaged across open-source and maker platforms.
Event-based vision is a paradigm shift from traditional frame-based approaches. It doesn’t capture entire images at once but instead detects changes in brightness, known as ‘events,’ at each pixel. This subsequently makes sensors much faster (responding in microseconds), able to operate with much less data and processing power, and be more power-efficient than traditional sensors.
“This launch makes our pioneering approach available to a highly engaged global developer base that’s already pushing the boundaries of embedded and Edge applications,” said Luca Verre, Co-Founder and CEO of Prophesee. “With the GenX320 Starter Kit for Raspberry Pi 5, we’re making event-based vision more open, easy, and accessible than ever before.”
The kit is purpose-built to enable real-world, real-time applications where traditional frame-based vision struggles:
- Drones & robotics: obstacle avoidance, drone-to-drone tracking, real-time SLAM
- Industrial IoT: 3D scanning, defect detection, and predictive maintenance
- Surveillance & safety: intrusion detection, fall detection, and motion analytics
