62 lines
2.9 KiB
Python
62 lines
2.9 KiB
Python
from pathlib import Path
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ROOT = Path(__file__).resolve().parents[2]
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def test_detection_operator_profiles_define_explicit_yolo_candidates_and_promoted_profile() -> 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: true" in source
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assert "promotionRecommendation: 'promote_candidate'" in source
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assert "positiveSampleCount: 7" in source
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assert "precision: 0.6140895327792112" in source
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assert "recall: 0.6062221049337548" in source
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assert "f1: 0.6068607646002744" in source
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assert "f1: 0.5432865390636915" in source
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assert "maxBackgroundDetections: 0" in source
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assert "lege-achtergrondtest is geslaagd" in source
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assert "Postel blijft met 47,5% F1" 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 "Gevalideerde YOLO-profielen" 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 "kandidaat, extra controle vereist" in lab
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assert "standaardprofiel" 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 = (ROOT / "frontend" / "src" / "App.tsx").read_text(encoding="utf-8")
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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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