Sign Language Detection using MediaPipe and SVM

📥 Installation:

Install uv for linux:

curl -LsSf https://astral.sh/uv/install.sh | sh

Clone the repository:

git clone https://github.com/ashuguptahere/sign-language-detection.git
cd sign-language-detection

Download dataset from kaggle using cURL and unzip it:

curl -L -o archive.zip https://www.kaggle.com/api/v1/datasets/download/grassknoted/asl-alphabet
unzip archive.zip

Install all uv dependencies:

uv sync

To extract keypoints from data:

uv run scripts/extract_keypoints.py

To train the SVM model:

uv run scripts/train.py

To test the SVM model on a video:

uv run scripts/test.py

📊 Results:

🤝 Contributing:

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the project
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License:

This project is licensed under the MIT License - see the LICENSE file for details.

🎥 Video Source [LINK]:

The model was tested on a video sourced from YouTube to evaluate its performance. The video is included for demonstration purposes and that its ownership belongs to the original creator

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Made with ❤️ by Aashish Gupta