Initial public release

backend/tests/test_sprint134_guided_detection_calibration_runner.py

@@ -0,0 +1,57 @@
+from pathlib import Path
+from tests.frontend_contract import read_feature
+
+
+ROOT = Path(__file__).resolve().parents[2]
+
+
+def test_detection_lab_has_guided_threshold_calibration_runner() -> None:
+    hook = ROOT / "frontend" / "src" / "hooks" / "useDetectionWorkflow.ts"
+    lab = ROOT / "frontend" / "src" / "components" / "detection" / "DetectionLab.tsx"
+    todo = ROOT / "docs" / "TODO.md"
+
+    hook_source = hook.read_text(encoding="utf-8")
+    lab_source = lab.read_text(encoding="utf-8")
+    app_source = read_feature("shell")
+    todo_source = todo.read_text(encoding="utf-8")
+
+    assert "interface DetectionCalibrationRunRow" in hook_source
+    assert "parseCalibrationThresholds" in hook_source
+    assert "calibrationThresholdText" in hook_source
+    assert "runningDetectionCalibration" in hook_source
+    assert "detectionCalibrationRows" in hook_source
+    assert "detectionCalibrationError" in hook_source
+    assert "runDetectionCalibration" in hook_source
+    assert "executeDetection(" in hook_source
+    # Every requested threshold is reported, but from one inference pass at the
+    # lowest cut: detections above a higher cut are a subset of it, and
+    # suppression walks candidates in descending confidence, so the kept set
+    # above a cut does not depend on the threshold the run used. Asserting the
+    # old per-threshold loop pinned N GPU passes that produced identical numbers.
+    assert "lowestThreshold," in hook_source
+    assert "calibration_thresholds: thresholds" in hook_source
+    assert "calibration_sweep" in hook_source
+    assert "{ calibration: true, calibration_thresholds: thresholds }," in hook_source
+    assert "detectionApi.compareWithReference(result.analysis_run_id" in hook_source
+    assert "reference_dataset_id: referenceDatasetId" in hook_source
+    assert "Kies eerst een referentiebron om te kalibreren" in hook_source
+    assert "Geef minstens één geldige drempel tussen 0 en 1 op" in hook_source
+    assert "Kalibratie met YOLO vereist een beeldtegelmanifest" in hook_source
+    assert "Kies eerst een lokaal modelbestand om te kalibreren" in hook_source
+
+    assert "Modelkalibratie voor beheerders" in lab_source
+    assert "Voert het lokale model en een kwaliteitscontrole uit" in lab_source
+    assert "Zekerheidsdrempels" in lab_source
+    assert "Drempels vergelijken" in lab_source
+    assert "Voortgang modelkalibratie" in lab_source
+    assert "detectionCalibrationRows.map" in lab_source
+    assert "runningDetectionCalibration" in lab_source
+    assert "detectionCalibrationError" in lab_source
+    assert "onRunCalibration" in lab_source
+    assert "onSetCalibrationThresholdText" in lab_source
+
+    assert "calibrationThresholdText={calibrationThresholdText}" in app_source
+    assert "runningDetectionCalibration={runningDetectionCalibration}" in app_source
+    assert "detectionCalibrationRows={detectionCalibrationRows}" in app_source
+    assert "onRunCalibration={runDetectionCalibration}" in app_source
+    assert "[x] Add guided in-app detection calibration runner" in todo_source