# Waste Management Monitoring

VIMS instance for waste-management.

## Related Article
[/insights/evidence-driven-municipal-maintenance/](https://landvex.com/insights/evidence-driven-municipal-maintenance/)

## Anomaly Classes
- overflowing_bin
- illegal_dumping
- missed_collection
- damaged_container
- hazardous_waste

## Quick Start

1. Add training images to `data/raw/`
2. Annotate using LabelImg (YOLO format)
3. Run preprocessing: `python src/detector.py`
4. Train model: `python src/detector.py --train`
5. Run inference: `python src/detector.py --predict data/test/image.jpg`

## API

Once deployed, access via:
- REST: `POST /api/waste-management/predict`
- WebSocket: `ws://host/ws/waste-management/alerts`