Alag-Labs/project-yaR

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
• Key Features
• Repository Structure
• Getting Started
  • Server Setup
  • Raspberry Pi Client Setup
• License

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.