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Fix YOLO class normalization
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2026-07-07 01:50:24 +02:00
parent 8f75c89b1c
commit 71c2cd9411
8 changed files with 98 additions and 14 deletions
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scripts/README.md
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@@ -180,9 +180,12 @@ metadata, tiles the raster, selects a mounted local model asset, verifies
read-only YOLO preflight, runs configured YOLO detection, runs detection QA
against persisted `vector_features`, and exports the detection run as GeoJSON.
It does not seed demo data, enable fixture detections, fetch external data or
download model weights. A zero detection count is accepted operationally, but
must be interpreted as model/data quality evidence rather than as a successful
building extraction result.
download model weights. Configured-YOLO model class labels are normalized to
lowercase for filtering and persisted detections, while the original model label
is retained in detection provenance. A zero detection count is accepted
operationally only when the selected model genuinely returns no usable
detections after class filtering; it must be interpreted as model/data quality
evidence rather than as a successful building extraction result.
Docker images install only the GIS runtime by default. To build a local/Tower
image with PyTorch/Ultralytics available for the configured-YOLO preflight and