Harden SAM roof refinement geometry gates

backend/tests/test_sam_roof_label_refinement.py

@@ -13,9 +13,19 @@ SPEC.loader.exec_module(MODULE)
 
 def test_plausible_refinement_is_fail_closed() -> None:
     source = (10.0, 10.0, 30.0, 30.0)
-    assert MODULE.plausible_refinement(source, (8.0, 9.0, 31.0, 32.0), min_iou=0.15, min_area_ratio=0.25, max_area_ratio=4.0)
-    assert not MODULE.plausible_refinement(source, (100.0, 100.0, 120.0, 120.0), min_iou=0.15, min_area_ratio=0.25, max_area_ratio=4.0)
-    assert not MODULE.plausible_refinement(source, (0.0, 0.0, 100.0, 100.0), min_iou=0.15, min_area_ratio=0.25, max_area_ratio=4.0)
+    limits = dict(
+        min_iou=0.15,
+        min_area_ratio=0.25,
+        max_area_ratio=4.0,
+        max_center_shift_ratio=0.75,
+        min_dimension_ratio=0.5,
+        max_dimension_ratio=2.0,
+    )
+    assert MODULE.plausible_refinement(source, (8.0, 9.0, 31.0, 32.0), **limits)
+    assert not MODULE.plausible_refinement(source, (100.0, 100.0, 120.0, 120.0), **limits)
+    assert not MODULE.plausible_refinement(source, (0.0, 0.0, 100.0, 100.0), **limits)
+    assert not MODULE.plausible_refinement(source, (10.0, 10.0, 51.0, 20.0), **limits)
+    assert not MODULE.plausible_refinement(source, (24.0, 24.0, 44.0, 44.0), **limits)
 
 
 def test_yolo_round_trip_shape() -> None:

docs/CODEX_EXECUTION_LOG.md

@@ -3746,6 +3746,34 @@ Validation:
 - `cd backend && python -m alembic heads && python -m alembic upgrade head --sql`
 # Codex Execution Log
 
+## 2026-07-30 - Fail-closed SAM roof-refinement gate hardening
+
+### What changed
+
+- Reproduced the V64 Flemish calibration-candidate export for Aarschot, Beveren and Oostkamp from the immutable temporal-cutoff manifest.
+- Ran the checksummed `/app/sam2_t.pt` model on the server RTX 4080 SUPER and rendered deterministic before/after label contact sheets.
+- Rejected both the legacy refinement settings and a stricter trial because dense or temporally absent footprint prompts still produced visually invalid roof boxes; neither result was promoted into a training corpus.
+- Hardened `scripts/refine_yolo_labels_with_sam.py` with configurable centre-shift and per-dimension ratio gates. The selected values and model checksum are persisted in `sam-refinement.json`.
+
+### What was tested
+
+- `python -m pytest backend/tests/test_sam_roof_label_refinement.py -q` passed (`2 passed`).
+- `python -m py_compile scripts/refine_yolo_labels_with_sam.py` passed.
+- CUDA refinement completed on 706 candidate labels; the strictest trial refined 659 and retained 47 explicit fallbacks. Visual QA still failed, so the run remains evidence only.
+
+### What remains open
+
+- Replace or align the rejected Flemish calibration labels with image-visible, independently validated roof boxes.
+- Rebuild and retrain only after that label gate passes; protected test and pure-background evaluation remain closed.
+
+### Known limitations
+
+- Geometry plausibility alone cannot prove that a SAM mask represents the intended roof in dense scenes.
+
+### Next recommended pass
+
+- Add an auditable image/footprint alignment stage or select lower-parallax independent Flemish AOIs, then repeat visual QA before corpus composition.
+
 ## Post-V1 national coverage completion: Wallonia (2026-07-22)
 
 - Located and live-validated the stable official WALOUS 2018 GeoTIFF

docs/TODO.md

@@ -8,6 +8,8 @@ Uitvoeringsbord: `docs/PYTORCH_TRAINING_ROADMAP_BELGIUM.md`.
 - [x] Generaliseer de single-class tile-export op klasse, referentiebron en referentielaag.
 - [x] Laat productietraining fail-closed stoppen wanneer vereiste CUDA ontbreekt.
 - [ ] Materialiseer geografisch gescheiden GRB/PICC/URBIS-gebouwcorpora met temporeel passende orthofoto's.
+  - [x] Verwerp de drie V64 Vlaamse kalibratiekandidaten fail-closed na gereproduceerde ruwe en SAM2-contact-sheets; verscherp de geometrische SAM2-gates.
+  - [ ] Lever onafhankelijke Vlaamse kalibratie-AOI's met aantoonbaar beeldzichtbare daklabels vóór een volgende training.
 - [ ] Train en evalueer een Belgische gebouwchallenger onafhankelijk; promoveer alleen zonder achtergrondregressie.
 - [ ] Houd zonnepanelen en segmentatie `not_configured` tot gereviewde taaklabels en hold-outs bestaan.
 

scripts/refine_yolo_labels_with_sam.py

@@ -7,6 +7,7 @@ import argparse
 import gc
 import hashlib
 import json
+import math
 import os
 import shutil
 from pathlib import Path
@@ -38,11 +39,29 @@ def plausible_refinement(
     min_iou: float,
     min_area_ratio: float,
     max_area_ratio: float,
+    max_center_shift_ratio: float,
+    min_dimension_ratio: float,
+    max_dimension_ratio: float,
 ) -> bool:
-    source_area = (source[2] - source[0]) * (source[3] - source[1])
-    refined_area = (refined[2] - refined[0]) * (refined[3] - refined[1])
+    source_width, source_height = source[2] - source[0], source[3] - source[1]
+    refined_width, refined_height = refined[2] - refined[0], refined[3] - refined[1]
+    source_area = source_width * source_height
+    refined_area = refined_width * refined_height
     ratio = refined_area / source_area if source_area > 0 else 0.0
-    return min_area_ratio <= ratio <= max_area_ratio and iou(source, refined) >= min_iou
+    if source_width <= 0 or source_height <= 0:
+        return False
+    width_ratio = refined_width / source_width
+    height_ratio = refined_height / source_height
+    source_centre = ((source[0] + source[2]) / 2, (source[1] + source[3]) / 2)
+    refined_centre = ((refined[0] + refined[2]) / 2, (refined[1] + refined[3]) / 2)
+    centre_shift_ratio = math.dist(source_centre, refined_centre) / math.hypot(source_width, source_height)
+    return (
+        min_area_ratio <= ratio <= max_area_ratio
+        and min_dimension_ratio <= width_ratio <= max_dimension_ratio
+        and min_dimension_ratio <= height_ratio <= max_dimension_ratio
+        and centre_shift_ratio <= max_center_shift_ratio
+        and iou(source, refined) >= min_iou
+    )
 
 
 def read_boxes(path: Path, width: int, height: int) -> list[tuple[float, float, float, float]]:
@@ -85,6 +104,9 @@ def main() -> int:
     parser.add_argument("--min-source-iou", type=float, default=0.15)
     parser.add_argument("--min-area-ratio", type=float, default=0.25)
     parser.add_argument("--max-area-ratio", type=float, default=4.0)
+    parser.add_argument("--max-center-shift-ratio", type=float, default=0.75)
+    parser.add_argument("--min-dimension-ratio", type=float, default=0.5)
+    parser.add_argument("--max-dimension-ratio", type=float, default=2.0)
     parser.add_argument("--max-prompts-per-pass", type=int, default=96)
     parser.add_argument("--force", action="store_true")
     args = parser.parse_args()
@@ -139,6 +161,9 @@ def main() -> int:
                         min_iou=args.min_source_iou,
                         min_area_ratio=args.min_area_ratio,
                         max_area_ratio=args.max_area_ratio,
+                        max_center_shift_ratio=args.max_center_shift_ratio,
+                        min_dimension_ratio=args.min_dimension_ratio,
+                        max_dimension_ratio=args.max_dimension_ratio,
                     ):
                         output_boxes[start + local_index] = candidate
                         unmatched.remove(candidate_index)
@@ -184,6 +209,9 @@ def main() -> int:
         "min_source_iou": args.min_source_iou,
         "min_area_ratio": args.min_area_ratio,
         "max_area_ratio": args.max_area_ratio,
+        "max_center_shift_ratio": args.max_center_shift_ratio,
+        "min_dimension_ratio": args.min_dimension_ratio,
+        "max_dimension_ratio": args.max_dimension_ratio,
         "max_prompts_per_pass": args.max_prompts_per_pass,
         "refined_label_count": refined_count,
         "fallback_label_count": fallback_count,