https://github.com/shehbaz-singh/airwrite
AirWrite is an AI-powered system that converts air-drawn gestures into text using real-time hand tracking and deep learning classification. Built with OpenCV and TensorFlow, it enables touch-free interaction through finger movement, making it ideal for accessible, hygienic, and intuitive digital communication.
https://github.com/shehbaz-singh/airwrite
deep-learning opnecv pygame python tensorflow
Last synced: 2 months ago
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AirWrite is an AI-powered system that converts air-drawn gestures into text using real-time hand tracking and deep learning classification. Built with OpenCV and TensorFlow, it enables touch-free interaction through finger movement, making it ideal for accessible, hygienic, and intuitive digital communication.
- Host: GitHub
- URL: https://github.com/shehbaz-singh/airwrite
- Owner: Shehbaz-Singh
- License: mit
- Created: 2025-04-23T17:52:59.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-23T18:00:38.000Z (about 1 year ago)
- Last Synced: 2025-04-24T00:59:10.147Z (about 1 year ago)
- Topics: deep-learning, opnecv, pygame, python, tensorflow
- Language: Python
- Homepage:
- Size: 7.29 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# AirWrite ✍️
**Character and Numerical Recognition Using OpenCV and Deep Learning**
## 🔍 Abstract
Recent advancements in image processing and pattern recognition have enabled the development of air-writing systems that transform motion into meaningful text. **AirWrite** is a touchless input system that allows users to "write" characters and numbers in the air using just their index finger. Combining real-time hand tracking using **OpenCV** and classification via deep learning, AirWrite provides an efficient, accurate, and hygienic way to interact with digital devices.
This project is particularly useful in settings that demand touchless interactions — such as healthcare or public kiosks — and also provides a new level of accessibility for individuals with physical disabilities.
## 💡 Features
- Real-time hand and fingertip tracking
- Digit and character recognition modes
- Deep learning-based classification
- No need for physical keyboards or touchscreens
- Improves accessibility and hygiene
- Open-source and customizable
## 🛠 Technologies Used
- Python 🐍
- OpenCV 🎥
- NumPy 📊
- TensorFlow/Keras 🧠
- Pygame (for UI) 🎮
## 🚀 Getting Started
### Prerequisites
Make sure you have the following installed:
- Python 3.x
- pip
### Installation
1. Clone the repository:
```bash
git clone https://github.com/yourusername/airwrite.git
cd airwrite