HAND SIGN DETECTOR APP

The Hand Sign Language Detector app bridges communication gaps by converting sign language into text using advanced computer vision and machine learning techniques. The app captures, processes, and interprets hand gestures, facilitating seamless interaction between sign language users and non-signers. An integrated interactive tour using Shepherd.js guides users through the app's features, ensuring an intuitive and smooth user experience.

Features

• Image Collection: Capture images for training the sign language detector.It enables the user who know sign language can add new signs to data.
• Dataset Creation: Transform captured images into a structured dataset.
• Model Training: Train a machine learning model using the created dataset.
• Inference: Perform real-time sign language recognition and translation.

Installation

• Clone the Repository:

git clone https://github.com/Shivani-Sharma-23/Hand_Sign_to_Text_converter.git
cd Hand_Sign_to_Text_converter

• Install Dependencies:

pip install -r requirements.txt

npm install sheperd.js

• Run the Flask Application:

python app.py

License

This application is licensed under MIT License.

Built With

• google-cloud
• mediapipe
• opencv-python
• scikit-learn
• sheperd.js
• vertex-ai
• vetex