Sign language is a comprehensive language system that employs hand gestures, facial expressions, and body movements to communicate. It serves as a primary means of communication for individuals who are deaf or hard of hearing.

In this project, we aim to bridge the communication gap by developing a system that can recognize and interpret sign language. We leverage the power of Long Short-Term Memory (LSTM) neural networks, a type of Recurrent Neural Network (RNN) well-suited for sequence prediction problems.

• Python 3.8
• opencv-python~=4.9.0.80
• numpy~=1.26.4
• mediapipe~=0.10.9
• scikit-learn~=1.4.1.post1
• tensorflow~=2.15.0

| To use the application, Python 3.8 must be installed on your machine.

1. Fork the repository

2. Clone the repository to your local machine

git clone https://www.github.com/<yourname>/Sign-Language-Recognition.git

3. Install the required packages using pip

pip install -r requirements.txt

4. Run the application

python main.py

The project is licensed under the MIT License. See the LICENSE file for more details.