block training-seen checkpoint evaluation

2026-08-09 21:01:12 +02:00
parent 48084799c9
commit fd45f37a38
7 changed files with 362 additions and 3 deletions
@@ -5,6 +5,13 @@ weights on one declared, non-protected `val` split using CUDA. It records exact
 model and dataset hashes, standard Ultralytics detection metrics and a separate
 pure-background detection count. The output claim is validation ranking only;
 the script neither reads protected test data nor promotes a model.
+Governed comparisons must pass every candidate's exact tile-summary with
+`--training-summary` and enable `--require-training-sample-independence`. If
+any validation AOI occurs in any supplied train split, the script writes a
+blocked manifest and exits before importing PyTorch, loading a model or using
+the GPU. A background detection count from a training-seen AOI is only a
+regression check and must never be presented as independent background
+evidence.

 `render_operator_yolo_label_qa_contact_sheets.py` paginates complete visual
 reviews with `--tiles-per-sheet` (default `64`). This keeps large corpora