65 lines
3.0 KiB
Python
65 lines
3.0 KiB
Python
from pathlib import Path
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from tests.frontend_contract import read_feature
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ROOT = Path(__file__).resolve().parents[2]
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def test_detection_operator_profiles_define_explicit_historical_yolo_controls_without_promotion_claim() -> None:
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profiles = ROOT / "frontend" / "src" / "components" / "detection" / "detectionProfiles.ts"
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source = profiles.read_text(encoding="utf-8")
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assert "DETECTION_OPERATOR_PROFILES" in source
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assert "geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt" in source
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assert "geointel-building-yolov8s-aoi1024expandedminpx4vis035e50-pt" in source
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assert "geointel-building-yolov8s-aoi1024bg512r3e50-pt" in source
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assert "small-building-balanced-review" in source
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assert "expanded-balanced-review" in source
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assert "conservative-review" in source
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assert "confidenceThreshold: 0.15" in source
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assert "confidenceThreshold: 0.35" in source
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assert "defaultApproved" not in source
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assert "promotionRecommendation" not in source
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assert "independentTestProven: false" in source
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assert "positiveSampleCount: 7" in source
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# The figures themselves are checked against the evidence record in
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# tests/test_detection_profile_metrics_are_traceable.py. Pinning them as
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# literals here is what kept an unsourced precision in the product.
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assert "maxBackgroundDetections: 0" in source
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assert "maxBackgroundDetections: 55" in source
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assert "backgroundGate:" in source
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assert "Slechts drie pure-achtergrondbeelden" in source
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assert "ruimtelijke onafhankelijkheid niet bewezen" in source
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assert "controlekandidaat en niet als grondwaarheid" in source
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def test_detection_lab_surfaces_profiles_as_deliberate_operator_actions() -> None:
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lab = "\n".join(
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(
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(ROOT / "frontend" / "src" / "components" / "detection" / "DetectionLab.tsx").read_text(encoding="utf-8"),
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(ROOT / "frontend" / "src" / "components" / "detection" / "DetectionModelManagement.tsx").read_text(encoding="utf-8"),
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)
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)
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assert "DETECTION_OPERATOR_PROFILES" in lab
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assert "Historische YOLO-controleprofielen" in lab
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assert "profile.displayName" in lab
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assert "profile.confidenceThreshold" in lab
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assert "historisch, geen releasebewijs" in lab
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assert "historische F1" in lab
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assert "Profiel gebruiken" in lab
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assert "onApplyOperatorProfile(profile)" in lab
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assert "Recommended starting threshold: 0.25" not in lab
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def test_detection_workflow_applies_profiles_without_selecting_the_first_arbitrary_asset() -> None:
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hook = (ROOT / "frontend" / "src" / "hooks" / "useDetectionWorkflow.ts").read_text(encoding="utf-8")
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app = read_feature("shell")
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assert "applyDetectionOperatorProfile" in hook
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assert "setSelectedDetectionModelId('yolo-configured')" in hook
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assert "setSelectedModelAssetId(profile.modelAssetId)" in hook
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assert "setDetectionConfidenceThreshold(profile.confidenceThreshold)" in hook
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assert "setSelectedModelAssetId(assetResponse.items[0]" not in hook
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assert "onApplyOperatorProfile={applyDetectionOperatorProfile}" in app
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