19 lines
890 B
Markdown
19 lines
890 B
Markdown
# ADR-005 — AI Model Strategy
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## Status
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Accepted for V1.
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## Context
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The vacancy emphasizes PyTorch, object detection, segmentation, and GeoAI. A portfolio build should show a real inference pipeline, not only AI text generation.
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## Decision
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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.
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Model execution must be wrapped behind `ModelRegistryService` and `DetectionService` interfaces so the UI and API do not depend directly on Ultralytics internals.
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## Consequences
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GeoIntel can demonstrate model inference, georeferencing, output conversion, confidence thresholds, and QA/QC against GRB.
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## Non-goals
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Do not train a custom model in V1. Fine-tuning becomes V2/V3 after annotation and dataset export exist.
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