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SnoreStopper_v2/requirements.txt
spencer 28012e70e0 feat: add storage and training modules for snore detection
- Implemented `storage.py` for managing metadata storage, including sample addition, retrieval, and review state management.
- Created `training.py` for training a local model using Random Forest, including functions for training and predicting samples.
- Developed a web interface in `app.js` for capturing audio samples, managing labels, and training the model.
- Added HTML structure in `index.html` for the SnoreStopper control room with sections for sample capture, overnight gathering, training, and status display.
- Styled the application with `styles.css` to enhance user experience and interface aesthetics.
2026-03-12 13:35:17 -04:00

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fastapi>=0.115,<1.0
uvicorn[standard]>=0.30,<1.0
numpy>=2.0,<3.0
sounddevice>=0.5,<1.0
soundfile>=0.12,<1.0
scipy>=1.13,<2.0
matplotlib>=3.9,<4.0
scikit-learn>=1.5,<2.0
joblib>=1.4,<2.0
python-multipart>=0.0.9,<1.0