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.
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Fork the repository
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Clone the repository to your local machine
git clone https://www.github.com/<yourname>/Sign-Language-Recognition.git
- Install the required packages using pip
pip install -r requirements.txt
- Run the application
python main.py
The project is licensed under the MIT License. See the LICENSE file for more details.