✋ Sign Language Interpreter (In Progress)

Welcome to the Sign Language Interpreter project!
This tool uses computer vision and machine learning to recognize sign language gestures in real-time through a webcam and translate them into text and speech.

Note: This project is still a work in progress — more features and improvements are coming soon!

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🚀 Project Goals

• 🎯 Recognize basic American Sign Language (ASL) gestures.
• 🎯 Display the recognized sign as text on screen.
• 🎯 Convert recognized text to speech in real-time to assist communication.
• 🎯 Build a simple, user-friendly interface for live translation.

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📂 Folder Structure

SignLanguageInterpreter/ ├── env/ # Virtual environment (do not edit) ├── test.py # Test script to check OpenCV and MediaPipe ├── (future files) # Main code files will go here ├── README.md # This file

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🛠️ Technologies Used

• Python 3
• OpenCV (computer vision)
• MediaPipe (hand tracking)
• TensorFlow (machine learning model training)
• pyttsx3 (text-to-speech conversion)
• NumPy (numerical operations)

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📋 How to Set Up

1. Clone the repository

   git clone https://github.com/your-username/sign-language-interpreter.git

2. cd sign-language-interpreter
3. python3 -m venv env source env/bin/activate
4. pip install opencv-python mediapipe tensorflow pyttsx3 numpy
5. python test.py

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🔮 Future Plans

• Expand dataset to recognize the full ASL alphabet and common phrases.
• Improve model accuracy with custom-trained TensorFlow models.
• Add a simple GUI for easier interaction.
• Explore deployment options as a web or mobile app.

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🤝 Contributions

Currently, this is a solo project by Anudeep Bonagiri, but collaboration opportunities may open up later!

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📢 Updates

This project is actively being developed.
Check back often for updates and new feature releases!

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