AyaeMichelle/Zimbabwe-Sign-Language-System

Sign Language Detection System # 🇿🇼 Zimbabwe Sign Language Detection System ## 📌 Overview The Zimbabwe Sign Language Detection System is a computer vision and machine learning project designed to bridge the communication gap between individuals with hearing impairments and the wider community. This system detects and interprets hand gestures in real time, converting them into meaningful outputs. It demonstrates how technology can be used to create inclusive and impactful solutions in society. --- ## 🎯 Problem Statement Communication barriers remain a major challenge for people with hearing impairments, especially in environments where sign language is not widely understood. This project aims to: * Improve accessibility through technology * Promote inclusivity * Provide a foundation for assistive communication tools --- ## 🚀 Features * ✋ Real-time hand gesture detection * 🤖 Machine learning-based sign recognition * 📷 Computer vision using webcam input * ⚡ Fast and responsive processing * 🧠 Scalable model for adding more gestures --- ## 🛠️ Technologies Used * Python * OpenCV * TensorFlow / Keras * NumPy --- ## 🧩 System Architecture The system works in the following stages: 1. Capture hand gestures via webcam 2. Preprocess the image frames 3. Extract key features 4. Classify gestures using a trained model 5. Output the detected sign --- ## ▶️ How to Run the Project ### 1. Clone the Repository ```bash git clone github.com cd Zimbabwe-Sign-Language-System ``` ### 2. Install Dependencies ```bash pip install -r requirements.txt ``` ### 3. Add the Model Download the trained model and place it inside the `model/` folder. ### 4. Run the Application ```bash python main.py ``` --- ## 📊 Future Improvements * Add more Zimbabwe Sign Language gestures * Improve model accuracy * Deploy as a web or mobile application * Integrate text-to-speech functionality --- ## 🌍 Impact This project highlights the potential of artificial i …