geointel/docs/reviews/2026-07-15-small-building-model-review.md

Small-building model review - 2026-07-15

Scope

This review uses persisted configured-YOLO detections, persisted GRB building features and the exact orthophoto inference tiles from Geel, Herentals and Turnhout. It does not infer labels from QA status alone and does not alter the active model.

• Model asset: geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt
• SHA256: a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1
• Canonical QA method: candidate polygon versus GRB footprint IoU 0.25
• False-positive cards reviewed: 48
• False-negative cards reviewed: 48
• False negatives outside persisted inference-tile coverage: 731, excluded

Every card was checked against its orthophoto and the persisted candidate and reference overlays. Geometric overlap diagnostics were used to distinguish a model error from box/footprint or one-to-one matching effects. Ambiguous cards remain excluded from training.

Decisions

Evidence	Confirmed model error	QA alignment	Reference gap/change	Uncertain/obscured
False positive	5	34	5	4
False negative	10	25	5	8
Total	15	59	10	12

The dominant finding is not a model error. In 59 of 96 reviewed cards, a real candidate and reference overlap but the canonical box-versus-footprint or one-to-one assignment does not count that pair as a match. Those records must not become positive or negative training labels.

Training-readiness audit

The active tile corpus already uses Geel and Herentals as training sources and keeps Turnhout excluded as an operation-level holdout.

Confirmed evidence	Geel	Herentals	Turnhout holdout
False positive	3	1	1
False negative	0	4	6

• The four confirmed false negatives in Herentals already exist as GRB labels in the current training source. Re-adding them would not add new ground truth; it would only change sample weighting.
• Confirmed false-positive detections in Geel and Herentals occur on urban source tiles that also contain valid GRB buildings. Treating those complete tiles as empty hard negatives would create false negative labels.
• The seven confirmed errors in Turnhout remain holdout evidence and cannot be used for training without invalidating the independent benchmark.

Result: 0 novel, leakage-free training labels are available from this review bundle. A new fine-tuning run is therefore rejected. The active model and confidence 0.15 remain unchanged.

Required next evidence before training

1. Collect new training-only orthophoto AOIs outside all Mol/Turnhout/Retie/ Westerlo operational holdouts.
2. Label the complete contents of each selected tile from an authoritative reference snapshot; never label only the reviewed detection box.
3. Add enough independent confirmed small-building and true empty-background examples to justify a separate candidate.
4. Keep the candidate inactive until it passes the same positive-AOI, pure-empty-background and Mol holdout gates.

The review CSVs, contact sheets and validator outputs remain under the persistent operator-data mount and are intentionally not committed as generated repository artifacts.