Initial public release

backend/tests/test_segmentation_postprocessing_config.py

@@ -0,0 +1,61 @@
+"""Segmentation must honour the same post-processing configuration as detection.
+
+Segmentation reuses the detection suppressor but passed only the IoU threshold,
+so it silently fell back to the hardcoded containment constant while detection
+read a configured one. A deployment tuning containment for a promoted model
+changed detection behaviour and left segmentation on the old value.
+"""
+
+from __future__ import annotations
+
+import pytest
+from shapely.geometry import box
+
+from app.core.config import Settings
+
+
+def test_segmentation_has_its_own_containment_setting() -> None:
+    settings = Settings(_env_file=None)
+
+    assert settings.segmentation_containment_nms_threshold == pytest.approx(0.85)
+
+
+def test_the_setting_is_independent_of_the_detection_one() -> None:
+    """Masks and boxes overlap differently; one value need not fit both."""
+
+    settings = Settings(
+        _env_file=None,
+        yolo_containment_nms_threshold=0.7,
+        segmentation_containment_nms_threshold=0.95,
+    )
+
+    assert settings.yolo_containment_nms_threshold == pytest.approx(0.7)
+    assert settings.segmentation_containment_nms_threshold == pytest.approx(0.95)
+
+
+def test_the_configured_value_reaches_the_suppressor() -> None:
+    from app.services.detection_service import DetectionService
+
+    def candidate(name: str, geometry, confidence: float):
+        return {
+            "class_name": "building",
+            "confidence": confidence,
+            "geometry": geometry,
+            "bbox": [0.0, 0.0, 1.0, 1.0],
+            "source_tile_path": f"/tiles/{name}.tif",
+            "properties": {"name": name},
+        }
+
+    outer = candidate("outer", box(0, 0, 10, 10), 0.9)
+    # Containment 0.9, IoU 0.09: only the containment rule can act on this pair.
+    mostly_nested = candidate("mostly", box(8.2, 1, 10.2, 6), 0.5)
+
+    strict = DetectionService._suppress_duplicate_candidates(
+        [outer, mostly_nested], iou_threshold=0.5, containment_threshold=0.95
+    )
+    loose = DetectionService._suppress_duplicate_candidates(
+        [outer, mostly_nested], iou_threshold=0.5, containment_threshold=0.7
+    )
+
+    assert len(strict) == 2
+    assert len(loose) == 1