The recommended detection profile showed operators precision 0.614, recall 0.606 and F1 0.607. Those three numbers appear nowhere in this repository except the file that publishes them and a test that pinned them as literal strings. The only recorded evaluation of that model at that operating point — tile 512, overlap 64, threshold 0.15, the exact key its promotion report recommended — reported 0.590, 0.577 and 0.582. The published figures were about two and a half points more flattering than anything that was measured, on the profile labelled "aanbevolen", and the test made sure nobody would correct them. They now carry the measured values. Worse in kind: the conservative profile reported "gemeten achtergrondfouten 0". Its nine-sample hard-negative matrix at threshold 0.35 recorded 198 background detections with 55 in the worst sample. The one number that tells an operator whether a high-precision model invents buildings on empty terrain said zero where the evidence said 55. Those zeros are not simply wrong everywhere, which is why the fix is not just a number. The other two profiles genuinely produced zero — against a strict pure-empty gate of three samples, a different and much weaker test than the nine-sample hard-negative matrix. Printing 0, 0 and 55 side by side invites a comparison the evidence does not support, so each profile now states its gate, its background sample count and the evaluation behind its figures, and the panel shows them. A test refuses any published figure that does not appear in the evidence record, with a negative control so it cannot pass by matching nothing. Pinning the numbers as literal strings is what let an unsourced precision survive; that assertion is gone. Also ignoring .codex-artifacts/ — ~300 MB of the rejected SAM2 and edge-alignment trials plus a deploy bundle. Kept on disk, out of the repository. No credentials in it; the two token scripts generate from settings. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
82 lines
1.9 KiB
Plaintext
82 lines
1.9 KiB
Plaintext
# Python
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__pycache__/
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*.py[cod]
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.venv/
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venv/
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.env
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*.egg-info/
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.pytest_cache/
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.ruff_cache/
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# Node
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node_modules/
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dist/
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build/
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*.tsbuildinfo
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# Local source-transfer archives; preserve them outside version control.
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/frontend-src.tar.gz
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# Large local data
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/artifacts/*
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!/artifacts/evidence/
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/artifacts/evidence/*
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!/artifacts/evidence/accuracy/
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/artifacts/evidence/accuracy/*
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!/artifacts/evidence/accuracy/P1/
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!/artifacts/evidence/accuracy/P1/**
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!/artifacts/evidence/accuracy/P3/
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!/artifacts/evidence/accuracy/P3/**
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!/artifacts/evidence/accuracy/P4/
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/artifacts/evidence/accuracy/P4/*
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!/artifacts/evidence/accuracy/P4/runs/
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/artifacts/evidence/accuracy/P4/runs/*
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!/artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/
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!/artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/**
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!/artifacts/evidence/accuracy/P2/
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!/artifacts/evidence/accuracy/P2/**
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/.cache/
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/datasets/raw/*
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/datasets/processed/*
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/datasets/cache/*
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/storage/uploads/*
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/storage/tiles/*
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/storage/masks/*
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/storage/reports/*
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/storage/exports/*
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/storage/rasters/*
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/storage/models/*
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/storage/operator-data/*
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/storage/operator-evidence/*
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/storage/release-evidence/*
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/storage/previews/*
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/storage/training/*
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/storage/ultralytics/*
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/exports/*
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/models/*
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/backend/storage/uploads/*
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/backend/storage/tiles/*
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/backend/storage/masks/*
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/backend/storage/reports/*
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/backend/storage/exports/*
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/backups/*
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/postgres-data/*
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# Keep folder placeholders
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!**/.gitkeep
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!**/README.md
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# Runtime-generated operator documentation is not repository documentation.
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/storage/operator-data/README.md
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# OS/editor
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.DS_Store
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.vscode/
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.idea/
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# Local investigation scratch: the SAM2 and edge-alignment trials the README
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# records as rejected, plus their imagery and a deploy bundle (~300 MB). Kept
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# on disk because the rejections are worth being able to re-check, out of the
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# repository because none of it is an input to the product.
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/.codex-artifacts/
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