Initial public release

docs/18-ultra-prep/MODEL_ADAPTER_GUIDE.md

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+# 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.