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Add fail-closed source class and SAM fallback filters
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This commit is contained in:
Jens
2026-07-30 04:24:35 +02:00
parent 29378bba42
commit 08422ca50c
6 changed files with 74 additions and 4 deletions
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scripts/refine_yolo_labels_with_sam.py
+24 -4
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@@ -108,6 +108,7 @@ def main() -> int:
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("--fallback-policy", choices=("retain", "drop"), default="retain")
parser.add_argument("--force", action="store_true")
args = parser.parse_args()
if args.output_dir.exists():
@@ -134,7 +135,7 @@ def main() -> int:
with Image.open(source_image) as image:
width, height = image.size
source_boxes = read_boxes(source_label, width, height)
output_boxes = list(source_boxes)
output_boxes: list[tuple[float, float, float, float] | None] = list(source_boxes)
if source_boxes:
for start in range(0, len(source_boxes), args.max_prompts_per_pass):
source_chunk = source_boxes[start : start + args.max_prompts_per_pass]
@@ -153,6 +154,8 @@ def main() -> int:
if candidate_index < 0 or overlap < args.min_source_iou:
reason_counts["unmatched_mask"] = reason_counts.get("unmatched_mask", 0) + 1
fallback_count += 1
if args.fallback_policy == "drop":
output_boxes[start + local_index] = None
continue
candidate = candidates[candidate_index]
if plausible_refinement(
@@ -171,14 +174,22 @@ def main() -> int:
else:
reason_counts["geometry_gate"] = reason_counts.get("geometry_gate", 0) + 1
fallback_count += 1
if args.fallback_policy == "drop":
output_boxes[start + local_index] = None
del result, masks
if model.predictor is not None:
model.predictor.reset_image()
gc.collect()
torch.cuda.empty_cache()
target_label.write_text("\n".join(yolo_line(box, width, height) for box in output_boxes) + ("\n" if output_boxes else ""), encoding="utf-8")
retained_boxes = [box for box in output_boxes if box is not None]
target_label.write_text("\n".join(yolo_line(box, width, height) for box in retained_boxes) + ("\n" if retained_boxes else ""), encoding="utf-8")
output_tile = dict(tile)
output_tile.update({"image_path": str(target_image), "label_path": str(target_label)})
output_tile.update({
"image_path": str(target_image),
"label_path": str(target_label),
"label_count": len(retained_boxes),
"is_negative": not retained_boxes,
})
output_tiles.append(output_tile)
print(f"{index}/{len(summary['tiles'])} {tile['sample_slug']}: {len(source_boxes)}", flush=True)
@@ -188,7 +199,14 @@ def main() -> int:
"output_dir": str(args.output_dir),
"dataset_yaml": str(args.output_dir / "dataset.yaml"),
"tiles": output_tiles,
"label_semantics": "sam_visible_roof_with_official_footprint_fallback",
"label_semantics": (
"sam_visible_roof_only"
if args.fallback_policy == "drop"
else "sam_visible_roof_with_official_footprint_fallback"
),
"label_count": refined_count if args.fallback_policy == "drop" else summary["label_count"],
"positive_tile_count": sum(not tile["is_negative"] for tile in output_tiles),
"negative_tile_count": sum(tile["is_negative"] for tile in output_tiles),
}
)
summary_path = args.output_dir / "yolo_tile_dataset_summary.json"
@@ -213,8 +231,10 @@ def main() -> int:
"min_dimension_ratio": args.min_dimension_ratio,
"max_dimension_ratio": args.max_dimension_ratio,
"max_prompts_per_pass": args.max_prompts_per_pass,
"fallback_policy": args.fallback_policy,
"refined_label_count": refined_count,
"fallback_label_count": fallback_count,
"dropped_fallback_label_count": fallback_count if args.fallback_policy == "drop" else 0,
"fallback_reason_counts": reason_counts,
}
(args.output_dir / "sam-refinement.json").write_text(json.dumps(evidence, indent=2), encoding="utf-8")