Arabic Sign Language Detection

This project uses a YOLO model for Arabic Sign Language detection with a Streamlit interface.

Setup

1. Clone this repository:

   git clone https://github.com/Wanderer0074348/ArsiDet.git
   cd ArsiDet
   

2. Create a virtual environment (optional but recommended):

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

3. Install the requirements:

   pip install -r requirements.txt
   

Running the Application

1. Ensure your webcam is connected and functioning.

2. Run the Streamlit app:

   streamlit run app.py
   

3. Your default web browser should open automatically. If not, navigate to the URL shown in the terminal (usually http://localhost:8501).

4. In the Streamlit interface:

   • Click "Start Camera" to begin the sign language detection.
   • The video feed will appear with real-time detections.
   • Detection results will be displayed below the video feed.
   • Click "Stop Camera" to end the session.

Troubleshooting

• If you encounter any issues with the camera, ensure that your system permissions allow access to the webcam.
• For CUDA-related errors, make sure you have the appropriate CUDA toolkit installed for your GPU.

Requirements

The main requirements for this project are:

• Python 3.7+
• Streamlit
• Ultralytics YOLO
• OpenCV
• PyTorch

For a complete list of dependencies, refer to the requirements.txt file.