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Sign Language Detection can interpret sign language gestures and facilitate communication between sign language users and non-signers. The project utilizes computer vision techniques and deep learning algorithms to accurately recognize

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Sign Language Detection

This repository contains code and resources for a Sign Language Detection project. The goal of this project is to develop a system that can recognize and interpret sign language gestures using computer vision techniques and machine learning algorithms.

Features

  • Real-time detection of hand gestures and signs.
  • Training and evaluation of machine learning models for sign recognition.
  • User-friendly interface for interacting with the system.
  • Support for multiple sign languages.

Installation

  1. Clone the repository:

    git clone https://github.com/Thilagavijayan/Sign_Language_Detection.git
  2. Install the required dependencies:

    pip install -r requirements.txt

Usage

  1. Open the project in your preferred IDE or text editor.

  2. Run the main application file:

    python testing.py
  3. Follow the instructions in the terminal or GUI to interact with the system.

Contributing

Contributions to this project are welcome! If you find any bugs or have suggestions for improvements, please open an issue or submit a pull request.

License

This project is licensed under the MIT License.

Contact

For any questions or inquiries, please reach out to [thilagavathivijayan850@gmail.com].

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Sign Language Detection can interpret sign language gestures and facilitate communication between sign language users and non-signers. The project utilizes computer vision techniques and deep learning algorithms to accurately recognize

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