A real‑time gesture‑to‑music system combining Python-based hand‑gesture recognition with a LabVIEW front end that translates detected signs into dynamic soundscapes.

1. Capture & Preprocess
   • Live video feed from webcam
   • Hand landmark detection via MediaPipe Hands
2. Classification
   • Features extracted → Random Forest model classifies 15 distinct gestures
   • Gesture label exported to gesture_output.txt
3. LabVIEW Integration
   • LabVIEW VI polls the text file
   • Maps each gesture to musical parameters (pitch, tempo, effects)
   • Generates adaptive audio in real time

• Python 3.8+
• mediapipe
• scikit-learn
• opencv-python
• LabVIEW 2021 or later

\\�ash pip install mediapipe scikit-learn opencv-python \\

1. Clone repo
2. Train or load
   andom_forest_gesture.pkl\
3. Open LabVIEW project \GestureMusic.vi\

1. Run: \python gesture_to_file.py\
2. Launch LabVIEW VI
3. Perform hand gestures in front of the camera → listen to responsive music

• Fork the repo & create feature branches
• Submit PRs with clear descriptions
• Report issues in GitHub Issues

MIT © Your Name