A project to detect and translate sign language gestures into text using machine learning and computer vision techniques.
This repository contains code for a Sign Language Detection system that uses Convolutional Neural Networks (CNN) to recognize hand gestures and translate them into corresponding text.
The project aims to help bridge the communication gap for people with hearing and speech disabilities by translating sign language gestures into text.
- Real-time sign language gesture recognition.
- Detects individual letters of the sign language alphabet.
- Provides a simple interface to display detected gestures.
- Python: Programming language used for this project.
- TensorFlow: Deep learning framework used for training models.
- OpenCV: Computer vision library to process video streams and capture gestures.
- Keras: Neural network API for building the detection model.
- NumPy: Library for handling arrays and matrices in Python.
- Project Overview: A brief explanation of what the project does.
- Features: Highlights key features of the project.
- Technologies Used: Lists the main technologies and libraries used.
- Installation: Describes how to install and set up the project.
- Usage: Explains how to use the project once it is set up.
- Project Structure: Shows the structure of the project’s directory.
- Contributing: Provides instructions on how to contribute to the project.
- License: Includes licensing information for the project.
- Acknowledgements: Credits the tools and libraries used.
- Contact: Information on how to reach the project author for queries.
- requirements.txt should include the dependencies you’re using, like
tensorflow,opencv-python,numpy, etc. - If your project has specific instructions or more complex usage, be sure to adapt the README accordingly.
To get started with this project, clone the repository and install the necessary dependencies.
git clone https://github.com/Pramod3245/Sign-Language-Detection.git
cd Sign-Language-Detection