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Key Features: Real-time Object Detection with CNN, OpenCV & Caffe Voice Command Processing for hands-free interaction; Text-to-Speech & Speech Recognition for user engagement; Live Video Stream Analysis from a smartphone/ Laptopcamera

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NEHAKIRANNAYAK/Navigation-Assist

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AR4VI: Assistive Navigation for the Visually Impaired

Project Overview

AR4VI (Augmented Reality for Visually Impaired) is a Flask-based web application designed to assist visually impaired individuals with navigation and object recognition. The project utilizes computer vision techniques for object detection and face recognition to provide real-time feedback to users.

Features

  1. Object Detection: Identifies and locates objects in the user's environment.
  2. Face Recognition: Detects and recognizes faces, with the ability to add new faces to the system.
  3. Real-time Video Streaming: Provides live video feed with object and face detection overlays.
  4. User-friendly Web Interface: Easy-to-use web pages for accessing different functionalities.

Installation

  1. Clone the repository;
  2. Install required dependencies;
  3. Ensure you have the necessary models and data files for object detection and face recognition.

Usage

  1. Run the Flask application:

    python app.py
    
  2. Open a web browser and navigate to http://localhost:5000

  3. Use the web interface to access object detection and face recognition features.

File Structure

  • app.py: Main Flask application file
  • object_camera.py: Contains VideoCamera class for object detection
  • facecam.py: Contains Facecamera class for face recognition
  • templates/: HTML templates for the web interface
    • object_index.html: Main page for object detection
    • object_index2.html: Page displayed after closing object detection
    • face_index.html: Main page for face recognition
    • face_index2.html: Page displayed after closing face recognition

Future Development

  • Mobile application development is pending for increased portability and accessibility.
  • Further optimization for real-time performance on mobile devices.
  • Integration with additional assistive technologies for comprehensive support.

About

Key Features: Real-time Object Detection with CNN, OpenCV & Caffe Voice Command Processing for hands-free interaction; Text-to-Speech & Speech Recognition for user engagement; Live Video Stream Analysis from a smartphone/ Laptopcamera

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