Welcome to Talking Hands, a real-time sign language detection system built to interpret American Sign Language (ASL) gestures using computer vision and deep learning.
Talking Hands uses webcam video to detect hand gestures and classify them into ASL numbers (0–9). The goal is to bridge communication gaps and make gesture-based interactions more accessible using AI.
- 🔎 Real-time hand gesture recognition
- 🤖 CNN-based model trained on ASL digit images
- 🧠 MediaPipe & OpenCV for hand tracking and image preprocessing
- 💻 Webcam-based live predictions
- 📊 Visual output with gesture overlay and predicted digit
Tool/Library | Purpose |
---|---|
Python | Main programming language |
OpenCV | Video capture and preprocessing |
MediaPipe | Hand tracking and landmarks |
TensorFlow/Keras | Model training and inference |
NumPy/Pandas | Data handling and manipulation |
Matplotlib | Model evaluation and visualization |
- Convolutional Neural Network (CNN) trained on ASL digit dataset (0–9)
- Input: Processed hand images from webcam
- Output: Digit class (0–9)
Talking-Hands/
├── data/ # ASL digit dataset
├── model/ # Trained model files
├── src/ # Python source code
│ ├── hand_tracker.py
│ ├── predict.py
│ └── train_model.py
├── test_images/ # Sample test images
├── README.md # This file
└── requirements.txt # Python dependencies
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Clone the repo
git clone https://github.com/gurpreetgitsingh13/Sign-Language-Detection---Talking-Hands.git cd Sign-Language-Detection---Talking-Hands
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Install dependencies
pip install -r requirements.txt
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Run the detection script
python src/predict.py
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Make hand gestures (0–9) in front of your webcam and see predictions in real-time!
- 🔤 Support for full ASL alphabet
- 🌐 Web interface using Flask or React
- 📱 Mobile deployment (Android/iOS)
- 🗣️ Gesture-to-speech integration
Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.
MIT License © Gurpreet Singh
- ASL Dataset
- MediaPipe by Google
- TensorFlow + Keras community
“Code is poetry. Data is the voice of reality.”