Sign language detection with Computer Vision

Overview

This project is aimed to detect American Sign Language (ASL) alphabets in real-time using computer vision. The system utilizes OpenCV for image processing, MediaPipe for hand detection, and a Random Forest classifier from scikit-learn for alphabet recognition.
Image Source:(https://takelessons.com/blog/american-sign-language-letters-tips-for-beginners)

Features

• Real-time ASL alphabet detection using a live camera.

• Hand detection using MediaPipe for accurate region of interest extraction.
• Random Forest classifier for predicting ASL alphabet signs.
• Utilizes OpenCV and matplotlib for image processing and visualization.
• Integration with scikit-learn for machine learning tasks.

Dependencies

• Python 3.x
• OpenCV
• Matplotlib
• scikit-learn
• MediaPipe
• NumPy