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yaR: AI-Powered Pendant for the Visually Impaired

yaR is an open-source AI wearable device designed to assist visually impaired individuals in navigating the world with greater confidence and independence.

Table of Contents

Project Overview

yaR started as a hackathon project and has evolved into a sophisticated AI-powered pendant. It uses a Raspberry Pi to capture visual input and process it to provide audio feedback to the user.

Key Features

  • Visual input processing using AI
  • Audio feedback for users
  • Lightweight and wearable design
  • Open-source for community contributions

Repository Structure

The repository is organized into two main folders:

  1. Client: Contains the Python code for the Raspberry Pi
  2. Server: Contains the Django Python code for the server

Client Files

  • main.py: The main script for the Raspberry Pi
  • audio_utils.py: Utilities for audio processing
  • request_handler.py: Handles requests to the server
  • Logger.py: Logging utilities
  • yaRException.py: Custom exception handling
  • requirements.txt: Required Python packages for the client

Server Files

  • manage.py: Django management script
  • video_processing/: Django app for video processing
    • views.py: Contains the view functions
    • urls.py: URL configurations
    • utils/: Utility functions for various tasks
  • server/: Django project settings
  • requirements.txt: Required Python packages for the server

Getting Started

Server Setup

  1. Create a virtual environment and install the required Python packages:

    python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt

  2. Set up environment variables:

    • OPENAI_API_KEY: OpenAI API key
    • ANTHROPIC_API_KEY: Anthropic API key

  3. Firebase Credentials Setup:

    • Create a new Firebase project in the Firebase Console
    • Generate a new private key:
      • Go to Project Settings > Service Accounts
      • Click "Generate new private key"
    • Rename the downloaded JSON file to yar-v2.json
    • Move yar-v2.json to the video_processing folder

    Important: Keep yar-v2.json secure and never expose it publicly.

  4. Configure Django:

    • Add the server's IP address/domain to ALLOWED_HOSTS in Server/server/settings.py

  5. Run the Django server:

    python manage.py runserver 0.0.0.0:8000

Raspberry Pi Client Setup

  1. Set up the Raspberry Pi hardware (Hardware Guide coming soon)

  2. Install required Python packages:

    pip3 install -r requirements.txt

  3. Set up environment variables:

    • VIDEO_PROCESSING_URL: URL/IP address of the server
    • API_TOKEN: API token for the server (e.g., "1234")

  4. Run the client:

    python main.py

License

This project is licensed under the MIT License.