LEGO Brick Identifier

A real-time LEGO brick detection app designed for accessibility, featuring advanced computer vision and user-friendly functionalities.

📚 Table of Contents

• Overview
• Features
• Installation
• Usage
• Project Architecture
• Testing
• Contributing
• License
• Credits

📝 Overview

The LEGO Brick Identifier is an innovative application leveraging deep learning and computer vision to detect and identify LEGO bricks in real-time. It is built with accessibility in mind, ensuring usability for individuals with color blindness or coordination challenges.

Key Highlights

• Real-time identification of LEGO pieces
• Color detection for improved accessibility
• Text-to-speech functionality for auditory feedback

✨ Features

• Real-Time Detection: Utilizes DenseNet to identify LEGO pieces from live camera input
• Color Identification: Distinguishes LEGO piece colors with enhanced precision
• Text-to-Speech Feedback: Provides auditory outputs for detected bricks
• User-Friendly Interface: Accessible design with clear navigation and error recovery
• Cross-Platform Compatibility: Runs seamlessly on Android and iOS devices

⚙️ Installation

Prerequisites

• Python 3.8+
• Node.js 14+
• npm or yarn package manager

Steps

1. Clone the repository:

git clone https://github.com/yourusername/lego-brick-identifier.git
cd lego-brick-identifier

2. Install backend dependencies:

cd backend
pip install -r requirements.txt

3. Install frontend dependencies:

cd frontend
npm install

4. Set up and start the backend:

cd backend
uvicorn main:app --reload

5. Start the frontend:

cd frontend
npm start

🚀 Usage

1. Launch the backend server with FastAPI:

uvicorn main:app --reload

2. Start the frontend:

npx expo start --tunnel

3. Open your browser and navigate to http://localhost:3000

4. Point your camera feed to LEGO pieces for real-time detection and text-to-speech feedback

🛠 Project Architecture

The LEGO Brick Identifier app consists of the following key components:

• Frontend: Built with React for a responsive user interface
• Backend: Powered by FastAPI for real-time WebSocket communication
• Model: Utilizes DenseNet for robust and accurate LEGO detection

🧪 Testing

Types of Testing

• Performance Testing: Evaluated under load for real-time detection with up to 100 concurrent users
• Usability Testing: Assessed for ease of use, navigation, and error recovery
• Compatibility Testing: Verified across Android and iOS devices

Key Results

• Successfully detects most LEGO pieces with an 80% accuracy rate
• Passed tests for cross-platform compatibility and stability

🤝 Contributing

We welcome contributions to improve the app! Here's how you can get started:

1. Fork the repository
2. Create a new branch for your feature or fix
3. Commit and push your changes
4. Submit a pull request with a detailed explanation of your work

📄 License

This project is licensed under the MIT License. See the LICENSE file for more details.

💡 Credits

This project was developed by a team of dedicated students to provide a meaningful solution for LEGO enthusiasts and users with accessibility needs. Special thanks to everyone who contributed to its success!

🤝 The Dream Team