Sign Language Detection

This project is a real-time American Sign Language (ASL) alphabet detection system using Convolutional Neural Networks (CNNs).
It allows recognition of hand gestures captured via webcam and maps them to the corresponding alphabet.

Features

• Real-time sign language alphabet detection
• Pre-trained deep learning model (Keras/TensorFlow)
• Simple and clean interface
• Extendable for word/phrase detection

Installation

Clone the repository:

git clone https://github.com/HetShingala/sign-language-detection.git
cd sign-language-detection

Install dependencies:

pip install -r requirements.txt

Usage

Run the detection script:

python sign_language_detection.py

Project Structure

• sign_language_detection.py – main detection script
• requirements.txt – dependencies
• README.md – project documentation
• Model files (.h5) and dictionary (words_alpha.txt) should be placed in the project directory.

Future Scope

• Add word-level and sentence-level detection
• Improve model accuracy with larger datasets
• Develop a web or mobile app interface

Author

Het Shingala