Sign Language Detector

This is a Python based sign language detector that uses computer vision and machine learning to recognize and classify sign language gestures in real-time.

Features

• Real-time gesture recognition: The application uses your webcam to detect and classify sign language gestures in real-time.
• 26-letter alphabet support: The model is trained to recognize all 26 letters of the American Sign Language (ASL) alphabet.
• Easy to use: The application is easy to set up and use. Simply run the inference_classifier.py script to start detecting gestures.
• Customizable: You can easily retrain the model on your own custom gestures by following the data collection and training instructions below.

Requirements

• Python 3.10
• OpenCV
• MediaPipe
• Scikit-learn

Installation

1. Clone the repository:

   git clone https://github.com/88448844/sign-language-detector.git
   cd sign-language-detector

2. Create a virtual environment:

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

3. Install the requirements:

   pip install -r requirements.txt

Usage

1. Collect Image Data

This is the most important step for creating an accurate model. You will need to collect a few hundred images for each sign language gesture you want to recognize.

Run the collect_imgs.py script to start the data collection process.

python collect_imgs.py

The script will open your webcam and guide you through the process. For each letter of the alphabet (A-Z), you will be prompted to press 'Q' to start collecting images. Make sure to move your hand around and show the gesture from different angles to create a robust dataset. The script will collect 200 images for each letter.

2. Create the Dataset

Once you have collected the images, run the create_dataset.py script to process them and create a dataset file (data.pickle). This script will extract the hand landmarks from the images and save them in a format that can be used for training the model.

python create_dataset.py

3. Train the Model

Run the train_classifier.py script to train a machine learning model on the dataset you created. This script will create a model.p file, which contains the trained model.

python train_classifier.py

4. Run the Sign Language Detector

Finally, run the inference_classifier.py script to see the sign language detector in action! The script will use your webcam to recognize and classify the gestures you trained it on.

python inference_classifier.py

5. Like the Repo :)

License

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