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YOLO LLaMa 7B VisNav
This project integrates the YOLO object detection model with the LLaMa 2 7B large language model, aiming to provide navigation assistance for visually impaired individuals in their daily travels.
Downloads 19
Release Time : 7/26/2023
Model Overview
The project combines computer vision and natural language processing technologies, using the YOLO model to detect environmental objects and convert them into structured data, which is then processed by the LLaMa language model to generate navigation instructions, creating a multimodal assisted navigation system.
Model Features
Multimodal Fusion
Combines visual detection with language understanding to achieve environmental perception and natural language interaction
Barrier-free Design
Navigation system specifically optimized for visually impaired individuals, providing spoken environmental descriptions
Real-time Processing
YOLO model enables efficient object detection to meet real-time navigation needs
Model Capabilities
Environmental Object Detection
Spatial Relationship Understanding
Navigation Instruction Generation
Multi-turn Dialogue Interaction
Use Cases
Accessibility Assistance
Indoor Navigation
Identifies key facilities such as doors and elevators and provides directional guidance
Helps visually impaired individuals navigate indoors independently
Obstacle Warning
Detects obstacles in the path and provides voice alerts
Reduces collision risks
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