Initial GeoIntel V1 foundation

2026-06-16 23:36:32 +02:00
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+# ADR-005 — AI Model Strategy
+
+## Status
+Accepted for V1.
+
+## Context
+The vacancy emphasizes PyTorch, object detection, segmentation, and GeoAI. A portfolio build should show a real inference pipeline, not only AI text generation.
+
+## Decision
+Use Ultralytics YOLO as the first object detection runtime because it is practical, PyTorch-based, well documented, and fast to integrate. Add segmentation through YOLO-seg or SAM after the detection pipeline is reliable.
+
+Model execution must be wrapped behind `ModelRegistryService` and `DetectionService` interfaces so the UI and API do not depend directly on Ultralytics internals.
+
+## Consequences
+GeoIntel can demonstrate model inference, georeferencing, output conversion, confidence thresholds, and QA/QC against GRB.
+
+## Non-goals
+Do not train a custom model in V1. Fine-tuning becomes V2/V3 after annotation and dataset export exist.