This project is a machine learning-based system to detect hand signs using computer vision and deep learning techniques. It is built using Python, OpenCV, and TensorFlow/Keras, and is designed for educational and assistive technology purposes.
- Real-time hand sign recognition
- Trained on a custom dataset of hand gestures
- Uses Convolutional Neural Networks (CNN)
- Interactive interface using OpenCV
The model uses a CNN trained on labeled hand gesture images to classify gestures into predefined categories. It is designed to recognize hand signs corresponding to alphabets or control signals.
- Clone the repository:
git clone https://github.com/Anmol659/handsign.git cd handsign
pip install -r requirements.txt