A real-time application for detecting and recognizing sign language gestures using a webcam feed.

• Overview
• Features
• Installation
• Usage
• Libraries Used
• Contact

This project leverages Flask for the web interface and TensorFlow/Keras for the machine learning model to recognize sign language gestures in real-time from a webcam feed.

• Real-time sign language gesture detection.
• Web interface for video feed and gesture recognition.
• Utilizes a CNN model for gesture recognition.

1. Clone the repository:

   git clone https://github.com/RiaanSadiq/Sign-Language-Detection.git
   cd Sign-Language-Detection

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install required libraries:

   pip install -r requirements.txt

4. Ensure a webcam is connected to your system.

1. Start the Flask application:

   python app.py

2. Open your web browser and navigate to http://127.0.0.1:5000/.

3. The web interface will display the webcam feed and detected sign language gestures.

• Flask: Web framework
• OpenCV: Video capture and processing
• NumPy: Numerical operations
• TensorFlow/Keras: Machine learning model
• Splitfolders: Dataset splitting
• Logging: Logging messages

For questions or suggestions, please open an issue or contact me at [[email protected]].