Sign Language Detection

This project aims to detect sign language gestures using a camera, translate them into corresponding text, and display the meaning in real-time. The tool uses machine learning, computer vision, and deep learning techniques to achieve this.

Technologies Used:

• Backend: Python
• Machine Learning: TensorFlow (CNN)
• Video Processing: OpenCV
• Gesture Detection: Mediapipe
• Database: MySQL (optional, for storing data)
• Serialization: Pickle (for storing trained model)

Features:

• Real-time gesture recognition using a camera.
• Gesture-to-text translation of sign language.
• Uses CNN for gesture classification.
• OpenCV for video processing.
• TensorFlow for machine learning model.

Setup:

1. Clone the repository:

   git clone https://github.com/yourusername/sign-language-detection.git
   cd sign-language-detection

Create a virtual environment:

python -m venv venv

Activate the virtual environment:

On Windows:

bash venv\Scripts\activate On macOS/Linux:

On Mac

bash source venv/bin/activate

Install the required dependencies:

bash pip install tensorflow opencv-python mediapipe mysql-connector-python

Run the project:

bash python app.py