# Model Adapter Guide

## Purpose
Detection and segmentation must be implemented behind stable adapters so V1 can support demo/local model flows while remaining ready for YOLO/SAM integration.

## Detection Adapter Interface
```python
class DetectionAdapter:
    name: str
    supported_classes: list[str]
    def is_available(self) -> bool: ...
    def predict(self, image_tile, parameters) -> list[DetectionResult]: ...
```

## Detection Result
Fields:
- class_name
- confidence
- bbox_pixel
- bbox_geo optional after georeferencing
- source_tile
- metadata

## Segmentation Adapter Interface
```python
class SegmentationAdapter:
    name: str
    supported_classes: list[str]
    def is_available(self) -> bool: ...
    def segment(self, image_tile, parameters) -> list[SegmentationResult]: ...
```

## V1 Rule
If real YOLO weights are not configured, use a demo adapter only when clearly labelled as demo and never present it as production AI.