A separation — an explicit dismissal, or the implicit one a Split records — was stored as a pair of event_people.id. Those ids do not survive re-derivation: recluster() deletes every person, and a full re-scan replaces a photo's faces outright, so face ids die too. The only thing that survives both is the embedding, so the decision is keyed on the two centroids the pair had when the photographer separated them. It binds while both sides still look like the clusters that were separated, and lapses once they have drifted past recognition.
The constraint is now honoured at assignment time as well as in consolidate(), which is what makes it hold across a re-scan rather than being reformed before any later pass could object.
Six review rounds shaped the matching itself: each candidate must resolve to the OPPOSITE side rather than merely matching something (a split leaves two similar halves, and the loose test fragmented the person the split was not even about); assignment judges both sides at the ordinary match threshold, since a single face — or a cluster of one part-way through a recluster — cannot resemble a settled centroid; separations carry their own model_version; and the projections are hoisted out of the innermost loop, which took a 2000-photo scan from ~15s of dot products to 0.23s.
Lifecycle closed three ways: purgePhotoFaces re-anchors each side onto the live cluster it still describes and drops rows that describe nothing left, deleteEventCascade and the permanent archive delete clear the table (which deliberately has no event FK), and a later manual merge drops the separations it reverses. All of it matched on vectors rather than ids, since a row that has outlived a recluster names people who no longer exist.
Merged with admin privileges: the author cannot self-approve.
Paul Nothaft
c305ad4146