Skip to content

Dinhillel/Friendly-eye

Repository files navigation

logo

Assistive Vision System for Visually Impaired people

Project Overview: This project is an intelligent assistive technology solution designed to help visually impaired people interact with their environment through real-time computer vision and natural language processing. The system combines multiple AI components to provide seamless voice-based interaction with the visual world. Core Functionality The system enables users to ask natural language questions about their surroundings and receive spoken responses.

For example: User: "What is in front of me?" System: "There is a red chair and a table in front of you."

✨ Features

🔍 Computer Vision Real-time Object Detection: Uses YOLOv8 for accurate object recognition Multi-dataset Training: Trained on COCO and Data-image-captioning datasets Live Camera Feed: Processes video stream in real-time Confidence Scoring: Provides detection confidence levels.

🎙️ Audio Processing Speech-to-Text: Whisper-based voice command recognition Text-to-Speech: Natural voice feedback with pyttsx3 Multi-language Support: Configurable language settings Voice Commands: Interactive voice-controlled interface

🧠 Natural Language Processing Question Answering: T5-based contextual understanding Scene Description: Intelligent interpretation of visual context Conversational Interface: Natural language interaction

⚡ Performance Real-time Processing: 30 FPS camera processing GPU Acceleration: CUDA support for faster inference Optimized Models: Lightweight models for efficient processing

Googel cloud Maps- for nevegation

VISION MODEL/ app/ config/
├── main.py
└── pipeline.py
vision/ opencv.py
yolo_detector.py # YOLO object detection ocr.py audio/ stt/ # Speech-to-Text tts/ # Text-to-Speech nlp/ t5/ # T5 model for question answering Dataset/ Data-image-captioning images/ train/ val/ labels/ train/ val/ ── MAPS- # nevegation street │── requirements.txt │── README.md

🗂️ Dataset (https://www.kaggle.com/datasets/aishrules25/automatic-image-captioning-for-visually-impaired) Data-image-captioning for object detection

Object Detection using YOLO

  • Question Answering (NLP) using T5 model
  • Speech-to-Text (STT) using Whisper or another STT module
  • Text-to-Speech (TTS) with Coqui TTS / pyttsx3
  • Real-time camera support with OpenCV

git clone https://github.com/Dinhillel/Friendly-eye.git

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages