Faces are found on the thumbnail, which is cached the right way up --
the grid would lie on its side otherwise. Segmentation runs on a proxy
rendered through a neutral edit graph, which carries no orientation and
is therefore in sensor order. For anything shot in portrait the two
differ by a quarter turn, so a face and the person containing it were
being compared in spaces 90 degrees apart: no match, or worse, a match
against somebody else's region.
The transform goes on the face rather than on the proxy. Instance masks
are defined in the proxy's space and sampled long afterwards, so turning
that space would be a far larger change than naming a region warrants.
Also two things the first screenshot of the running app showed that no
test would have:
110 of 23,528 displayed as "0%", which reads as the feature having done
nothing. One decimal below ten percent, and a floor so real progress
never shows as none.
The rail picked some near-black covers, because the largest face in a
group is often the nearest one in a badly lit frame and a black square
beside a name identifies nobody. It now cuts the best few and takes the
first legible one, falling back to the largest when a person's every
photograph is dark -- which happens, and showing it beats showing
nothing.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The segmenter knows it found a person; the face index knows which person.
Joining them turns "person" in the mask list into "Anna", which is the
difference between a vocabulary of eighty COCO classes and one that
includes the user's family. Selecting a subject in a group photograph
stops being a guessing game between three identical rows.
Containment, not IoU. A face is a small part of the person it belongs to,
so a correct pairing has an IoU near zero and anything IoU-based would
reject every true match.
Confirmed names only. A suggestion is the system's guess, and printing a
guessed name onto a mask region would launder it into a fact.
Writing the tests corrected the design once: a tight head-and-shoulders
portrait, where the face fills most of the person box, is the case where
naming is most certain, not least. An earlier guard rejected exactly that
and has been removed, with the reasoning left as a test because it is
easy to get backwards a second time.
The names hang on the develop session, set when the image opens because
that is the one moment the catalog and the image id are both in reach.
Every segmentation run afterwards picks them up for free, and a library
with no face indexing behaves exactly as it did before.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The rail was drawing an empty square for every person: cover was
hardcoded to a default image. That is the one place a portrait matters
most, because the rail is how the user decides which unnamed group to
open first, and a list of "Unnamed (24 faces)" rows tells them nothing.
The portrait is the person's confirmed face with the largest crop_px --
the most source pixels the face actually occupied, so the one they have
the best chance of recognising -- falling back to a suggestion so a
freshly clustered group still has a face beside it.
Cached in the controller, because every mutating action reloads the whole
screen and cutting a portrait costs a JPEG decode per person. Without the
cache, confirming one face would re-decode a proxy for every person in
the library, and the rail does not change when a suggestion is accepted.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
An image with no faces in it was indistinguishable from one that had
never been looked at, so every landscape, still life and document scan in
the library was re-detected on every pass, for ever. In a real library
that is most of it: on the 23,527-image test library, 64 of the first 110
images indexed contain no face at all.
Schema v9 adds face_index, a run marker per (image, model) carrying the
face count and the proxy edge it read. Keyed on the model, so a model
change puts every image back in the queue by itself.
That makes a coverage figure possible, which is the thing a user actually
wants to see. The audit also splits the outstanding set by whether a
proxy exists, because 23,417 awaiting a proxy and 110 ready to index are
different problems, and telling the user to run indexing again would not
fix the first.
The Identity screen gains Index faces, Stop, and the coverage line.
examples/face_index.rs is the same check and sweep without a window,
which is the right shape for an overnight pass.
Measured on the real library in release: 3.5 images/second, 110 images
and 125 faces in 30 seconds, and a second run correctly finds nothing
left to do.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
A third top-level screen beside the library and develop, because naming a
cluster and pulling a stranger out of it are tasks with their own rhythm
and need the whole window.
The screen is designed around the clustering being wrong, which is
FR-CULL-10 rather than pessimism: grouping over-merges on siblings, on
parents and children, and on the same person a decade apart. So Split off
sits next to Confirm all rather than behind a menu, the confirm/reject
pair is on the face itself, and a group the system found is drawn
differently from a person the user has vouched for.
Splitting rejects before it confirms. Without that the next clustering
pass suggests the face straight back and the user's correction becomes an
argument they keep having.
Face crops come from the proxies the grid already built, one decode per
image rather than per face -- a group photograph holding six faces of one
family is one JPEG.
Where the calibration is not fitted the screen says confidence is
unavailable instead of printing a percentage that looks measured, which
is FR-CULL-9's rule at the point it becomes visible.
The verdict controls use drawn icons, not tick and cross characters:
ui/icons.slint exists because those render as tofu on Android.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
dtourolleandClaude Opus 5