The Lattice sensAI Edge Vision Engine is a versatile tool that empowers developers with advanced AI and machine learning capabilities, featuring sophisticated computer vision functionalities. It includes a camera Viewer designed to facilitate the effective visualization of these capabilities.
Designed for Windows PCs, Raspberry Pi, and visualizing experiences running on Lattice FPGAs. This tool accelerates the deployment of intuitive, touchless, and intelligent interfaces across industrial, automotive, consumer, and client computing segments.
The models in this tool are designed to operate at extremely low power in Lattice FPGAs, but they are also optimized for devices with more resources, such as CPUs on Windows and Raspberry Pi.
All computer vision AI models in the SDK have an F1 score of 0.95 or higher, making them production-ready for real-world applications and significantly accelerating implementation speed and time to market.
Key Capabilities
- Body Detection & Tracking –Accurately identifies and tracks human bodies for interactive applications.
- Face Detection & Tracking – Enables facial recognition, user authentication, and analysis of facial expressions.
- Face Identification – Recognizes and verifies individuals for security and personalization.
- Speaker Identification –Identifies individuals based on voice patterns for secure and hands-free authentication.
- Gesture Detection & Tracking –Supports touchless interactions using hand and body gestures.
- Gaze Tracking – Detects user focus for adaptive UI/UX, accessibility enhancements, and safety applications.
- Object Detection –Recognizes and tracks objects in real-time for enhanced situational awareness.
Quick Start Your FPGA Experience
To quickly evaluate and trial our solution on FPGA hardware, we recommend starting with the human to machine interface demonstration and the Crosslink-NX-33 Voice and Machine Learning Board listed below. This setup provides a ready-to-use environment, allowing you to explore the capabilities of our solution with minimal setup time.
Click the link below to access the recommended demo and hardware platform, and get started today.