INSTALLATION.md

📦 Installation Guide - Sign Language Interpreter

This guide provides detailed installation instructions for the Sign Language Interpreter system.

🔧 System Requirements

• Python: 3.8 - 3.11 (recommended: 3.9 or 3.10)
• Operating System: Windows 10/11, macOS 10.14+, or Linux
• Hardware:
  • Webcam (built-in or external)
  • 4GB RAM minimum (8GB recommended)
  • 2GB free disk space
• Internet: Required for initial setup and package installation

🚀 Quick Installation

Option 1: Automated Setup (Recommended)

1. Download and Extract

   # If using git
   git clone https://github.com/yourusername/sign-language-interpreter.git
   cd sign-language-interpreter
   
   # Or download and extract ZIP file
   

2. Run Setup Script

   python setup.py
   

   This will:

   • Create necessary directories
   • Install required packages
   • Create a sample model
   • Verify installation

Option 2: Manual Installation

1. Create Virtual Environment

   python -m venv venv
   
   # Activate virtual environment
   # Windows:
   venv\Scripts\activate
   # macOS/Linux:
   source venv/bin/activate
   

2. Install Dependencies

   pip install -r requirements.txt
   

3. Create Directories

   mkdir models dataset logs examples
   

4. Create Sample Model

   python create_simple_model.py
   

🔍 Verification

Run the system test to verify everything is working:

python test_system.py

Expected output: ``` 🤟 Sign Language Interpreter - System Test

Dependencies: ✅ All dependencies installed

Camera: ✅ Camera working

MediaPipe: ✅ MediaPipe working

Model Files: ✅ Model files found

Predictor: ✅ Predictor working - Sample prediction: hello (0.85)

================================================== Test Results: 5/5 tests passed 🎉 All tests passed! System is ready to use.

## 🚀 Running the Application

### Web Interface (Recommended)
```bash
streamlit run app.py

Command Line Interface

python examples/basic_usage.py

🛠️ Troubleshooting

Common Issues

1. Python Version Error

   Error: This package requires Python 3.8-3.11
   

   Solution: Install a compatible Python version

2. Camera Access Error

   Error: Camera not accessible
   

   Solutions:

   • Close other applications using the camera
   • Check camera permissions
   • Try a different camera index

3. Package Installation Error

   Error: Could not find a version that satisfies the requirement
   

   Solutions:

   • Update pip: python -m pip install --upgrade pip
   • Try installing packages individually
   • Check Python version compatibility

4. TensorFlow Installation Issues

   Error: No matching distribution found for tensorflow
   

   Solutions:

   • Use Python 3.8-3.11
   • Install TensorFlow separately: pip install tensorflow
   • Use CPU-only version: pip install tensorflow-cpu

Platform-Specific Issues

Windows

• Visual C++ Error: Install Microsoft Visual C++ Redistributable
• Long Path Error: Enable long path support in Windows settings

macOS

• Permission Error: Grant camera access in System Preferences
• Homebrew Issues: Update Homebrew and Python

Linux

• Camera Error: Install v4l-utils: sudo apt install v4l-utils
• Permission Error: Add user to video group: sudo usermod -a -G video $USER

🔄 Updates

To update the system:

1. Update Code

   git pull  # If using git
   

2. Update Dependencies

   pip install -r requirements.txt --upgrade
   

3. Test System

   python test_system.py
   

🆘 Getting Help

If you encounter issues:

1. Check Documentation

   • Read README.md for overview
   • Check QUICKSTART.md for basic usage
   • Review this installation guide

2. Run Diagnostics

   python test_system.py --verbose
   

3. Community Support

   • GitHub Issues: Report bugs and feature requests
   • Discord: Join our community chat
   • Email: support@signlanguage.ai

📋 Next Steps

After successful installation:

1. Try the Demo: streamlit run app.py
2. Collect Data: python data_collection.py
3. Train Model: python train_model.py
4. Read Documentation: Check docs/ folder for guides

🔐 Security Notes

• The application only accesses your camera locally
• No data is sent to external servers
• All processing happens on your device
• You can review the source code for transparency