Signify - American Sign Language (ASL) Recognition Application

Description

Signify is a Python application that explores the principles of computer vision and machine learning with a practical implementation for sign language recognition. Although currently focused on recognizing American Sign Language (ASL), the application is designed as a foundation for further development in recognizing hand gestures and real-time interactions.

This application uses advanced techniques for hand movement analysis, offering wide possibilities for implementation in various domains such as interactive systems, gesture interfaces, and social interactions.

Key Features

• Real-time sign and gesture recognition: Uses the camera to analyze hand movements and recognize gestures, enabling a broad range of applications beyond ASL.
• Python-based: Developed in Python using popular image processing and machine learning libraries, making it easy to extend the application for new tasks.
• Using MediaPipe: For precise hand detection and key point tracking, ensuring high accuracy in recognizing gestures and movements.
• Machine Learning Model: A trained model that not only recognizes ASL signs but can also be adapted to different types of gestures and hand signals.

Instructions

1. Run imageCollection.py: First, run this script to collect all necessary images for recognizing different classes.
2. Run datasetCreation.py: Then, run this script to create the dataset that will be used for training the classifier.
3. Train the classifier with classifierTraining.py: Using the previously collected data, this script trains a model to recognize signs.
4. Run finalProgram.py: Finally, everything is integrated into one program using finalProgram.py, bringing everything together into a functional application.