https://github.com/hsymal/sign-language-detection-with-python-and-scikit-learn-main
This project focuses on detecting sign language gestures using Python and Scikit-Learn, aimed at providing a tool for real-time communication assistance for the hearing impaired. The core of the system is based on computer vision techniques to identify hand gestures and map them to their corresponding sign language alphabet or words.
https://github.com/hsymal/sign-language-detection-with-python-and-scikit-learn-main
machine-learning mediapipe opencv pickle python sign-language
Last synced: 2 months ago
JSON representation
This project focuses on detecting sign language gestures using Python and Scikit-Learn, aimed at providing a tool for real-time communication assistance for the hearing impaired. The core of the system is based on computer vision techniques to identify hand gestures and map them to their corresponding sign language alphabet or words.
- Host: GitHub
- URL: https://github.com/hsymal/sign-language-detection-with-python-and-scikit-learn-main
- Owner: hsymal
- Created: 2025-01-21T03:19:52.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-22T00:06:57.000Z (over 1 year ago)
- Last Synced: 2025-03-17T12:47:01.849Z (over 1 year ago)
- Topics: machine-learning, mediapipe, opencv, pickle, python, sign-language
- Language: Python
- Homepage:
- Size: 640 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
Sign Language Detection with Python and Scikit-Learn
Overview
This project aims to develop a system for detecting sign language using a webcam. It utilizes the MediaPipe library for hand landmark detection and Scikit-Learn's RandomForestClassifier for sign classification. The system is capable of recognizing different signs and displaying the corresponding character on the screen.
Features
Real-time hand landmark detection using MediaPipe
Sign language classification using RandomForestClassifier
Easy to extend and add new sign classes
Simple and user-friendly interface
Prerequisites
Python 3.6 or higher,
OpenCV,
MediaPipe ,
Scikit-Learn ,
Numpy