Sign-Language-Detector

Getting Started

Prerequisites

Ensure you have the following installed:

• Python 3.x
• Required Python packages (listed in requirements.txt) such as OpenCV, MediaPipe, NumPy, etc.

Installation

1. Clone the repository:

   git clone https://github.com/1rishu0/Sign-Language-Detector.git
   cd Sign-Language-Detector

2. Install dependencies:

   pip install -r requirements.txt

Usage Workflow

1. Collect Data
   Run collect_imgs.py to capture hand gestures via webcam. Label and save landmark data to build your dataset.

2. Create Dataset
   Use create_dataset.py to preprocess raw data, generating a structured .pickle dataset ready for training.

3. Train the Model
   Execute train_classifier.py to train a classifier (likely using scikit-learn) on the prepared dataset. This script outputs a serialized model.p file.

4. Inference / Real-Time Detection
   Launch inference_classifier.py to perform live gesture recognition using your webcam and the trained model.

Demo

Sign_Language_detector_more_compress.mp4

License

This project is released under the GPL‑3.0 License, so feel free to modify and share as per the license terms. :contentReference[oaicite:0]{index=0}

Contributing

Contributions are welcome! Here’s how you can help:

1. Fork the repository.
2. Create a feature branch (git checkout -b feature/YourFeature).
3. Make your changes.
4. Commit your work and push to your fork.
5. Open a Pull Request with details of your enhancements.