Audit and suppress nested detector proposals

scripts/evaluate_belgium_building_candidate.py

@@ -52,6 +52,29 @@ def metrics(tp: int, fp: int, fn: int) -> dict[str, float | int]:
     }
 
 
+def containment_overlap(
+    left: tuple[float, float, float, float], right: tuple[float, float, float, float]
+) -> float:
+    x1, y1 = max(left[0], right[0]), max(left[1], right[1])
+    x2, y2 = min(left[2], right[2]), min(left[3], right[3])
+    intersection = max(0.0, x2 - x1) * max(0.0, y2 - y1)
+    left_area = max(0.0, left[2] - left[0]) * max(0.0, left[3] - left[1])
+    right_area = max(0.0, right[2] - right[0]) * max(0.0, right[3] - right[1])
+    denominator = min(left_area, right_area)
+    return intersection / denominator if denominator > 0 else 0.0
+
+
+def suppress_contained_predictions(
+    predictions: list[tuple[tuple[float, float, float, float], float]], threshold: float
+) -> list[tuple[tuple[float, float, float, float], float]]:
+    kept: list[tuple[tuple[float, float, float, float], float]] = []
+    for candidate in sorted(predictions, key=lambda item: -item[1]):
+        if any(containment_overlap(candidate[0], existing[0]) >= threshold for existing in kept):
+            continue
+        kept.append(candidate)
+    return kept
+
+
 def ensemble_predictions(
     primary: list[tuple[tuple[float, float, float, float], float]],
     secondary: list[tuple[tuple[float, float, float, float], float]],
@@ -128,6 +151,18 @@ def main() -> int:
         default=1000,
         help="Maximum detections retained per tile; dense Belgian urban tiles exceed YOLO's default 300.",
     )
+    parser.add_argument(
+        "--nms-iou",
+        type=float,
+        default=0.7,
+        help="Inference NMS IoU; freeze calibration-selected values before protected test evaluation.",
+    )
+    parser.add_argument(
+        "--containment-nms",
+        type=float,
+        default=1.0,
+        help="Suppress lower-score nested boxes at this intersection-over-minimum-area threshold.",
+    )
     parser.add_argument("--box-scale", type=float, default=1.0)
     parser.add_argument("--box-offset-x", type=float, default=0.0)
     parser.add_argument("--box-offset-y", type=float, default=0.0)
@@ -141,6 +176,10 @@ def main() -> int:
     args = parser.parse_args()
     if args.proposal_classifier_batch < 1:
         parser.error("--proposal-classifier-batch must be positive")
+    if not 0.0 < args.nms_iou < 1.0:
+        parser.error("--nms-iou must be between zero and one")
+    if not 0.0 < args.containment_nms <= 1.0:
+        parser.error("--containment-nms must be above zero and at most one")
 
     from ultralytics import YOLO
     proposal_classifier = None
@@ -173,13 +212,14 @@ def main() -> int:
         augment=args.augment,
         imgsz=args.imgsz,
         max_det=args.max_det,
+        iou=args.nms_iou,
         verbose=False,
     )
     additional_results = None
     if args.additional_model:
         additional_results = YOLO(str(args.additional_model)).predict(
             image_paths, conf=min(args.thresholds), device=args.device, augment=args.augment,
-            imgsz=args.imgsz, max_det=args.max_det, verbose=False,
+            imgsz=args.imgsz, max_det=args.max_det, iou=args.nms_iou, verbose=False,
         )
     observations: list[dict[str, Any]] = []
     for result_index, (tile, result) in enumerate(zip(tiles, results, strict=True)):
@@ -193,6 +233,7 @@ def main() -> int:
             )
             for box, score in zip(result.boxes.xyxy.cpu().tolist(), result.boxes.conf.cpu().tolist(), strict=True)
         ]
+        predictions = suppress_contained_predictions(predictions, args.containment_nms)
         if additional_results is not None:
             secondary = [
                 (
@@ -204,6 +245,7 @@ def main() -> int:
                     additional_results[result_index].boxes.conf.cpu().tolist(), strict=True,
                 )
             ]
+            secondary = suppress_contained_predictions(secondary, args.containment_nms)
             predictions = ensemble_predictions(
                 predictions, secondary, match_iou=args.ensemble_match_iou, mode=args.ensemble_mode
             )
@@ -274,6 +316,8 @@ def main() -> int:
         "test_time_augmentation": args.augment,
         "inference_imgsz": args.imgsz,
         "max_detections_per_tile": args.max_det,
+        "nms_iou": args.nms_iou,
+        "containment_nms": args.containment_nms,
         "box_scale": args.box_scale,
         "box_offset_x": args.box_offset_x,
         "box_offset_y": args.box_offset_y,