# Flood Risk Monitoring

VIMS instance for flood-monitoring.

## Related Article
[/insights/the-future-of-infrastructure-monitoring/](https://landvex.com/insights/the-future-of-infrastructure-monitoring/)

## Anomaly Classes
- water_level_rise
- drainage_blockage
- levee_damage
- erosion
- debris_accumulation

## 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/flood-monitoring/predict`
- WebSocket: `ws://host/ws/flood-monitoring/alerts`