A scene that makes a parent, nests two collections in it by drag and by
the menu, files frames into a child and opens the parent to see it count
both; stills of the tree and of the menu. The collections recording is
re-made now that the bitmap under the cursor is the photograph.
drive.py grows a multi-leg drag: a diagonal with much vertical in it is
taken by the grid's Flickable as a scroll before the DragArea can claim
it, so a drag to the sidebar goes sideways first.
The bitmap under the cursor was a solid red rectangle. Slint's drag
overlay uploads the image as a texture, draws it and drops the texture in
one call; with the wgpu FemtoVG renderer the drop is immediate and the
draw is deferred to the flush, so the frame binds femtovg's placeholder —
which is red. An image with a cache key survives in the texture cache
until after the flush, and only a path gives one. So the composite goes
to the data directory's scratch as a PNG and comes back through
load_from_path; one file per drag, removed when the drag ends. A
workaround for Slint 1.17.1, written up as one beside the code.
The probe's comment said a 192px render "averages a small neighbourhood
into each of its pixels". It does not: the composed shader fetches the
source at one position per output pixel - nearest for an unrotated
frame, four photosites blended otherwise - so the probe was a point
sample of a noisy sensor, and two painted-white air conditioners on the
same wall answered +37 and -50.
The tap is now narrowed to the patch of the canvas around the click, a
couple of percent of its width and square on screen, and rendered at
64x64 with interpolation forced on, which puts a sample on every sensor
pixel under it at any ordinary zoom. The samples are averaged, with the
void and clipped ones left out rather than allowed to pull the mean, and
fewer than half surviving is refused. compose_camera_probe takes the
patch; the merge's compose_camera_linear keeps its nearest sampling. The
readback shrinks from six megabytes to sixty-four kilobytes.
A frame of alternating warm and cool columns, averaging neutral, moves
the controls by at most two units; a point sample swung them to sixty.
Sampling the overcast sky on a Canon 6D frame set tint to -100 and
temperature to -15 for a patch the canvas showed as pure white. A clipped
photosite is sensor white, not a colour: every channel stopped counting,
so what the tap hands back is the as-shot multipliers themselves, which
are strongly magenta, and the solver dutifully drove green to its stop.
The display shader already fades such a pixel to a neutral of the same
brightness before any operation runs, so the picker was balancing against
something the photographer could not see.
The probe now refuses a sample with any channel at or above the onset the
shader fades from, the way the solver already refuses black. The threshold
is one constant, CLIP_ONSET, formatted into the shader and read by the
probe, so the two cannot drift apart.
Pressing "pick" and clicking a near-neutral wall on a Canon 6D frame set
tint to -77 and turned the whole photograph green. The white balance
operation runs first in the chain, on camera RGB, before the body's base
curve and colour matrix; the probe was read off a display render after
all three, and the solve treated that sRGB triple as if the gains
multiplied it directly. On a JPEG the two spaces coincide, which is why
the existing tests passed while the picker was broken on every raw file.
The probe now reads the camera-space tap a merge stitches from, composed
under the edit's own framing so a fraction of the canvas is a fraction of
the probe, and puts the as-shot balance on itself - exactly the value the
operation's gains are about to multiply. No operations run in the tap, so
nothing has to be stripped and restored, and the display target is left
alone, so a sample that found nothing usable no longer needs a redraw.
A raw-frame test with the 6D's matrix and a typical as-shot balance
samples a warm grey and asserts the rendered pixel comes back neutral; it
fails on the previous probe.
Every face the user has ruled on entered the pass as an anchor, and the
scan is exhaustive by design (`dr_face::neighbours`), so a person with
750 confirmed faces cost 750 comparisons against every other face in
the library — and the cost of a library grew with how well it was
named. Most of those comparisons said nothing new: thirty frames from
one afternoon are one point of view, not thirty, and a face that
matches one of them matches the rest.
Each person now enters through at most 100 of their anchored faces
(`dr_face::references`). Eligible are those whose raw embedding is at
least 15 long — one above the gallery floor, since a reference speaks
for someone rather than merely being admitted — with an unmeasured
length admitted as it is everywhere else. From those, the set spanning
the greatest volume is chosen greedily: the longest vector first, then
at each step the face with the largest component orthogonal to the
chosen so far. That is pivoted Gram–Schmidt, and the product of the
residuals it picks is the Gram determinant, so the greedy step is the
exact greedy on the objective. A near-duplicate of a chosen face has
no residual and is passed over; the one profile shot among two hundred
frontal frames is taken early; faces inside the span of the chosen add
no volume and are not taken to fill the cap.
The faces not chosen keep their confirmations and are not touched by
the pass — they stay in the anchor map, so it never releases them —
they are simply not compared. A person none of whose faces is long
enough is still stood for, by their longest, rather than losing their
anchor and having their next face filed as a stranger. Under the cap
nothing changes: every eligible face stands, and the short ones stay
in as the probes they were.
At the reference library's 3,851 confirmations the scan shrinks by
about a fifth; at 15,000 it is a fifth of what it was.
The tablet showed a fraction of each person: 681 of the desktop's 3,851
confirmations, and none of Ian's 746, Catherine's 626 or my own 480.
Every face that existed on both devices agreed on who it was, and the
people rows were identical — the merge was fine. The missing 3,170
confirmations were on faces the tablet did not hold at all: the
desktop's 16,080 faces from the original detector, on 4,310 images,
detected before schema V14 kept the quality reading.
Those faces were in shards the tablet had already downloaded, in
August's export. `import_from_shards` looked at them on every sync pass
and declined each one, because a face without a quality reading was
"work this device cannot finish": adopting it would write the run
marker, and the marker was what stopped an image being looked at again.
That was true when it was written and has not been since the quality
repair existed — that pass lists its work by `f.quality IS NULL`, not by
the marker, exactly as the eye pass does, and faces without an eye
reading were already adopted on that reasoning.
The refusal had no exit. V14 had deleted the markers of every image
holding such faces so the quality pass would find them, and
`export_to_shards` walks the markers, so the desktop never re-exported
them either; the unmeasured August copies were the only ones there
would ever be. The tablet's answer was to queue all 17,727 images for a
re-detection of its own, a fetch of the whole library, while holding
the faces on disk.
Adopt them. The receiving device's quality pass measures them when it
reaches them, and the desktop's confirmations match onto them by box
overlap on the next catalog merge. The test that asserted the refusal
now asserts the adoption and that the image is still owed to the pass.
"How many images still owe a quality reading" was a correlated EXISTS per
image over `faces`, and the face row is 8 KB of embedding and crop before
the column it looks at, so each count opened every row. Six such counts
run on every open of the Identity screen and at the end of every sweep:
160 ms on the reference library.
V19 adds three partial indexes holding only the faces still owing each
pass, keyed on the image and carrying the model id the predicate reads,
and replaces `faces_image` with `(image_id, model_id)` so "does this image
hold this embedder's faces" is answered from the index too. The planner
takes a partial index when the count is driven from `faces` and ignores it
inside the EXISTS, so `Needs::Face` carries the per-face fragment and
`repairs::count` spells the query from the faces' side; the list and the
per-image check keep the EXISTS. A test holds the two spellings to the
same answer for every repair.
Every `move_to` guaranteed its destination's parent with a `MKCOL` for
each ancestor down from the account root, and a trash folder under a
library root several levels deep meant three round trips answering
`405 Method Not Allowed` before the one `MOVE` that did anything — for
every image of a delete, on a connection built for that job.
The backend now records the collections it has confirmed exist and asks
about each once. It lives for one job, so a folder another client removes
mid-batch is the one case this misses, and the `MOVE` then reports the
`409` rather than hiding it.
A confirm or a reject changes one row and redraws the whole grid, and the
redraw re-read every crop blob of the selected person (4 MB for the
largest) and decoded every one — 316 ms per click on the reference
library's 754-face person, to arrive at the pixels already on screen.
`load_faces` now takes the crops the previous load decoded, keyed by face,
and moves each into its new cell; the blob read is skipped when every face
is already in hand. `refresh` drains the old cells into it rather than
cloning them. The redraw is 2.6 ms.
Every click on the Identity screen's face grid — confirm, reject, split,
rename, merge — redrew the whole screen, and the redraw recomputed the
coverage line. That line lists every repair's outstanding images to count
them: six scans of the images table with a correlated EXISTS over the
8 KB face rows, an ORDER BY the job's visiting order, a Target with its
path per row, and a thumbnail-index query per image with faces. On the
reference library (24k images, 19k faces) that was ~200 ms of the
~540 ms each click cost, spent computing a figure a confirm cannot change.
`refresh` now takes what changed: `Changed::Identities` re-reads the rail
and the grid and leaves the coverage line alone; `Changed::Library` — an
open, a sweep ending or stopped, the face data deleted — re-reads it too.
For the times it does run, `repairs::counts` counts instead of building
and dropping the lists, and the thumbnail store is read once
(`ThumbStore::held`) rather than probed once per image in the audit, the
outstanding list and the proxy repair.
`identity_bench` is the measurement: the reads a click performs and the
batch writes, timed against a copy of a real catalog.
docs/manual/README.md is a tour for a photographer opening DarkRoom for
the first time — one picture per thing, moving where movement is the
point. tools/manual/ is how the pictures are made: drive.py puppeteers the
desktop build on a private Xvfb (launch, click, drag, type, screenshot,
record), scenes.py is each picture as a script, and record.sh runs them
all over a folder and writes the results into docs/manual/media/.
The media is in LFS, with the CI pulls excluding it as they exclude the
fixtures; a screenshot changes wholesale when the interface does.
Nothing in the pictures shows a person, by design: the demo library is
seventy urban and alpine frames, chosen from the catalog's rows that face
detection found nobody in.
The traceability matrix is regenerated here after the rebase that
brought this branch up to master.
Every shard is in WAL mode and every put opens its own connection, so
while thumbnails are being generated on several threads — which is when
the first sync pass runs — the log is never checkpointed and the main
file holds whatever the last quiet moment left in it. For a shard created
seconds earlier that is nothing: a zero-byte file with the schema still
in the log. The sync read that file and uploaded it, and every other
device merging it failed with "no such table: thumbs" on every pass.
Copy the shard through SQLite's backup API into scratch first, which
serialises against writers and carries the log, and upload that.
Confirming "/" in the folder picker set an empty root, which the launch
model read as no root at all: "Open library" stayed disabled after the
question had plainly been answered, and a folder library — whose folder
is the whole library — could never be opened without first descending
into a subfolder of it. The empty string was carrying two meanings.
Record the choice as its own fact on the account (`root_chosen`, defaulted
so existing configuration loads unchanged), treat a folder endpoint as
chosen by definition, and let the launch screen say so: a folder is shown
as a LIBRARY rather than an ACCOUNT, the second question becomes an
optional "scan only a subfolder", and the library header names the folder
instead of calling it "· whole account".
The scan reads the first 256 KB of a file for its metadata. A camera
writes its IFDs at the front, so that is the whole structure; the linear
DNG a merge writes puts its first IFD after the pixels, and rawler,
given the head alone, finds no decoder in it. The composite was
catalogued without a date and sorted to the very end of the grid, after
every dated photograph — which is where a panorama merged on the tablet
went unfound.
dr-decode's own TIFF reader now reads through a head and a tail at a
known offset; trailing_ifd says where the tail starts and
metadata_split reads the two together. The scan, when the head fails
and points beyond itself, fetches from the IFD to the end — kilobytes —
and dates the file from both. Tested against the writer's own output.
dr_pano::fill owns everything the model does not — which tiles, what
context, how to blend — behind an Inpainter trait, and dr_pano::migan is
that trait over the shipped generator on the inference engine.
The known content is mirrored across the coverage edge into the hole and
a 256-px ring, the nearest 48 px folded, so the model interpolates between
real and mirrored sky rather than extrapolating into nothing. A coarse
pass at a quarter decides the structure with the whole border in a few
tiles; fine passes in 96-px bands from the edge outward texture it; the
seam is blended over a feather inside the real edge. Every knob is a
Params field, and an Observer hears each stage for whoever is looking at
why a fill went wrong.
A border fill acquires the filler once a tile, and each acquire hashed
the 28 MB model twice — 60 ms a tile, a third of the tile's run on a
throttled TensorRT. The Model keeps its hash from open.
A library's records are never all complete at once. A face found before
its quality was kept has no quality; one found before the eye models
existed has no reading; one adopted from a peer's shard has no crop; an
image the fast detector examined on a 1024 px proxy has boxes the current
detector would not have drawn; an image the scan stat'ed has no capture
date. On the reference library that is 17,762 faces under the bare
w600k_mbf id with no quality, no reading and no dense landmarks, 4,144 of
them without a crop, beside 12,217 images the fast detector examined and
found nothing in. Every one of those gaps was its own pass — V14's
measuring pass, §17.5's eye pass, the sweep's proxy repair, the sweep's
detector upgrade — with its own work list, its own count and its own idea
of done, and adding a per-face field meant adding a pass. There was no
pass at all for the case the library is actually in: boxes and landmarks
drawn by a weaker detector on a proxy, which every later per-face pass
would have read from.
dr_ui::repairs replaces them with one job over a registry. A Repair names
one thing a record can lack — the predicate that says which images still
owe it, the input its handler needs (a header, the original, or a native
render), the handler, and what to record for an image that can never be
done. The job unions the predicates into one work list, fetches each
image once at the most any claimant asks for, renders it at most once,
and runs every handler whose predicate that image still matches, checked
again before each because a detection writes every field a per-face
handler would fill. The registry today: face-proxy, face-quality,
face-eyes, face-crop, face-detection, face-upgrade, metadata — the last
there to say that this is not a face job. Adding a field is one entry.
A repair's predicate is the only definition of its work: the count the
settings page shows, the list the job fetches and the check before its
handler run are one predicate, so the job converges. That is why the
registry is cut to what the device can do rather than listing what it
skips — an entry is a count and a set of originals to fetch — and why an
eye reading that cannot be cut is not a criterion.
The catalog side is generic to match: record_updates writes whichever
fields a FaceUpdate carries and re-marks the image so the shards export
it; faces_needing and count_needing answer a predicate the caller
supplies, replacing the measuring pass's three special cases.
Two buttons on the settings page run the job and differ in one
predicate. "Index faces" converges on coverage: has anything examined
this image. "Re-index every face" converges on provenance: face-detection
claims every image with no marker under the chosen detector, in either
of its forms (FaceDetector::model_ids, so a desktop in f32 and a tablet
on the Hexagon do not re-index each other's work), and a marker saying a
weaker one looked is not that. An original over the fetch budget is left
exactly as it was under the re-index, where the sweep marks it examined:
a re-detection with nothing found would delete the faces, and "cannot
fetch" is not "no faces".
record_detections replaces an image's faces and carried only the user's
confirmations onto the new ones, by box overlap above 0.5 IoU. Everything
else on the old faces was dropped: the suggestions the last grouping pass
made, and the people the user had said a face was not. On the reference
library that is 13,011 suggestions and 77 rejections beside 3,778
confirmations — a re-detection of it would have been correct by
FR-CULL-12's letter, since suggestions are derived data, and would have
handed back a People screen of strangers.
Now every old face is read before the delete — box, vector, assignment,
rejections — and matched to the new faces one-to-one, best pair first. A
pair qualifies when the boxes overlap at all and either the overlap alone
says so (IoU above 0.5, the old rule) or the embeddings do (cosine above
SAME_FACE_COSINE, 0.45, the reference library's P≈0.95 line). The
embedding route claims the box a low-resolution pass drew badly enough
that overlap alone would not; the vector is also what breaks the tie in a
group photograph, where two neighbouring faces overlap both new boxes.
Overlap is required on both routes, because the same vector elsewhere in
the frame — a mirror, a print on the wall — is not the same face and must
not take its name. Onto the matched face go the assignment as it was,
confirmed or suggested with its probability, and every rejection.
The merge's match_faces still matches by overlap alone across devices; it
is the same question and is not changed here.
XFeat's two exports are a Keypoints role now; the crate no longer names
tract, and the app compiles TensorRT engines for both ahead of the
first merge. The probe picks the smallest *detector* rather than the
smallest file: the tablet's first run chose the 112 KB eye classifier,
which has no int8 form, and reported the Hexagon as failed for want of
one.
Read and measured, not built. The bare 512 generator exports at a fixed
shape and loads under tract with nothing unsupported; at f32 on the
desktop CPU it takes 7.4 s per 512×512 tile, which puts a full-resolution
fill of the fixture's border at ten minutes. The three routes that would
make it viable are recorded, with the quarter-resolution fill the cheapest
and Hexagon int8 the one the model was designed for.
Picking a chip stored the choice for the merge and changed nothing on
screen — the chip did not even highlight, since the selected property
was never written back. Now the pick is reflected, and the job, waiting
for its decision, takes a Preview request, draws the alignment on the
chosen surface at proxy cost and reports again; the drain puts the new
picture and its size up. Auto is the surface the field of view suggests.
Also:
The largest rectangle inside the frames' coverage is found a row at a
time — a histogram of consecutive covered rows and a stack pass per row —
so the composite is never held to be measured (FR-MRG-11). It is written
as DefaultCropOrigin/DefaultCropSize (FR-MRG-4): the file opens on the
picture, the border is still in it, and resetting the crop shows it.
rawler reports the crop as the picture, which the test checks.
FR-MRG-4 records the question raised the same day — fill the border
rather than crop it — as open: a non-generative fill through the heal,
or a generative inpainter with its licence and weights. Neither decided.
derived_from and merge are top-level sidecar fields (FR-MRG-6): one line
per source in order, and how the composite was made. A build that
predates them keeps the lines as unknown and writes them back. The job
writes the sidecar beside the composite and stages it with its own
record when the composite goes through the outbox.
DARKROOM_START_MERGE=a.CR2,b.CR2 lands on the merge page at startup with
the job running on local files, on the model of DARKROOM_START_IDENTITY,
for looking at the page where synthetic clicks do not reach it. The fetch
and the start are shared with the grid's button.
panorama.md §11 records what exists, the fixture's figures, and the six
things still open, auto-crop first.
dr_ui::merge is the orchestration with no interface in it: decode each
frame to sensor data and build its graph as a session would (orientation,
lens profile); render each through the camera-space tap at proxy size and
detect keypoints there, so the alignment is measured in the undistorted
frame the tiles are rendered in; align; solve one gain per frame from the
proxies' overlaps; draw the aligned set in colour for the page; then wait.
Nothing is written until a Decision arrives (FR-MRG-1). The merge writes
a linear DNG through the outbox with a destination record, so the drain
puts it beside its sources on a folder library and a server alike, and
the library rescans (FR-MRG-3).
merge.slint is the page, on the import page's model: the alignment
table with a failed frame named on its row and the button held off
(FR-MRG-5), the preview, the projection choice, Stop and Back. A
"Merge to panorama" button joins the grid's selection bar at two frames.
Headless, the example produces the fixture's 22 993 x 5 980 DNG in 45 s
on the reference desktop, exposures balanced across the stop of drift.
compose_camera_linear composes the fused pass with an empty operation
list, the file's orientation as the baseline, a view rect for the tile,
and a store of rgba32float. On the GPU, render_camera_linear is the only
entry that accepts it: it fills the profile uniforms neutral — unit white
balance, identity matrix, curve off — so what lands in the texture is the
sensor's numbers after the lens warp and nothing else (FR-MRG-2). A third
bind-group layout carries the format, as the linear one does, and the
readback is generalised to any pixel width for the f32 copy.
Thirty-two bits because the composite is written back at the sensor's
scale: a 14-bit sensor has 16 384 steps to white and f16 keeps 2 048 of
them in the top octave.
Twelve real frames from the fixture set now align in 4.5 s — 4.4 s of
matching, 118 ms of bundle adjustment — where the first run took 51 s and
left the first two frames out.
The matcher computes each pair's similarity matrix once, across the
cores, with a dot product written to vectorise; both nearest-neighbour
directions read it. The frames that failed were portrait: fitted into the
landscape input they used 512 of 1024 px, and their thin overlap did not
survive at half resolution. The same weights are now exported at 768×1024
as well and the detector picks the shape by aspect. The example aligns
from embedded previews and draws the set on a cylinder; on the fixture the
sweep is 152° at a fitted 47.9 mm against the EXIF's 50, RMS 1.5 px, and
the overlaps show no ghosting.
A new crate holding the CPU half of a merge (FR-MRG-10): the grayscale
proxy with orientation, the XFeat decoder ported step for step from the
reference detectAndCompute, mutual-nearest-neighbour matching, a robust
pairwise homography with the focal length read off it, a hand-rolled
Levenberg–Marquardt bundle adjustment over every rotation and the focal,
the three output projections, and align(), which chains it all and names
the frames it could not place rather than guessing (FR-MRG-5).
Dependency-free without the xfeat feature — linalg.rs says why the dense
algebra is hand-rolled — and tested on synthetic sweeps whose answer is
known exactly. The noise test records the single-row degeneracy: one
pixel of noise is a tenth of a percent of focal, which is a uniform
stretch of the sweep, not a misalignment.
tools/export-xfeat.sh exports the convolutional network alone at 768×1024
grayscale, on the pattern of export-seg-model.sh: thirteen standard
operator types, no dynamic axes, the keypoint decoding left to Rust.
examples/onnx_probe loads it through the ort-over-tract backend the app
ships with nothing unsupported and runs it in ~300 ms on the desktop CPU.
The weights are Apache-2.0, read from the repository's LICENSE, with no
grant on the checkpoint — recorded in models/LICENCE.md before they land,
as FR-MRG-8 asks. The probe stays: the next model will need the same
check.
A hand-rolled 64×48 LinearRaw DNG — one IFD, 16-bit RGB, DNGVersion,
ColorMatrix1, AsShotNeutral — comes back through rawler 0.7 with cpp 3,
the samples in the order written and the matrix parsed into the camera
definition; CameraProfile::extract builds a profile from it. ImageMagick
reads the same bytes.
dr_decode::decode currently accepts the file as CFA and passes three
times the samples on, so the cpp == 3 branch is the decode work FR-MRG-3
needs, and the only decode work. panorama.md §8 records the result.
A merge writes a new source file beside its sources (D18) rather than a
multi-source Version, which answers the schema question §7 had been holding
open for panorama, HDR merge and focus stacking together. The panorama is
undeferred as FR-MRG-1 … 11; the other two stay in §7 with their data model
decided.
FR-MRG-10 and 11 fix where the work runs — every per-pixel stage on the GPU,
the composite never held as one texture — because the output exceeds
max_texture_dimension_2d before it exceeds memory. panorama.md carries the
stage table, the chunked output driver, the model licences and the porting
sources. S15 gates all of it.
Coverage falls from 83.0% to 77.2%: thirteen requirements entered with no
code, and outstanding.md §11 says so.
The 106 points the eye boxes were cut from, stored beside the reading as
16-bit fixed point over the frame: 424 bytes a face, a seventh of a pixel
on a 6000-pixel frame, where f16 at the same size would have been six.
Derived data like the embedding, kept for the same reason — it cost a
fetch and a model run, and the next per-face pass should run from the
catalog. Shards carry it; a peer's shard from before it is still read.
The register grew both clauses the same day this was built: FR-CULL-8a is
the per-face state the reading is, and FR-CULL-13 is the rule that a
signal is shown and filtered and never writes a judgement. The tags,
faces.md §17 and catalog.md now say which is which; FR-CULL-8a records
what of it is built, and that its third model is under the InsightFace
grant by the same decision as the pair.
The people filter was served from faces_image without touching a row;
reading the eye columns in the same subquery touched every one, and
ALTER TABLE had put those seven floats after the embedding and the crop
blob. One count took 24 seconds on the reference library, thirteen of
them system time. faces_eyes covers the subquery again: five
milliseconds.
An "Eyes open" chip beside the people chips, offered only while someone
is chosen and dropped when the last person goes, so no term narrows the
grid with nothing on the bar to say so. It compiles the rule in
dr_face::eyes into the person's face subquery — Anna, eyes open, whoever
else is blinking beside her — and drops a frame only on a closed eye that
could be read: sunglasses, eyes too small or soft to read, and faces never
read all pass, so an old library shows everything under the chip until
the measuring pass has run. A test drives the same readings through the
SQL and through the rule and requires them to agree.
The People screen badges a face "Eyes closed", "Sunglasses" or "Eyes
unclear" so the reason a frame is or is not in the grid can be read off
the face; the sweep loads the three models when they are beside the pair
and reads eyes on the indexing and measuring passes from the native
render; the coverage line counts unread faces as work to measure so an
already-indexed library keeps its Index button. The term travels with the
place.
SCRFD's eye point places a face, not an eye: on turned and smiling heads
the classifier's window had the eye in a corner, and two model-free ways
of re-centring it — the darkest blob, the most contrasty window — both
lost open eyes (19 → 15 and 19 → 9 of 25). Three landmark models were
then run over the same faces; Face Mesh V2 and InsightFace's 2d106det
tied at 22 of 25 and 2d106det ships, being the cheapest by far and under
the grant the detector and embedder already carry. The eye box is the
tight bounding box of its ten lid points, cut upright from the native
render, which is what the classifier was trained on.
The larger change is that the reading now carries, per eye, the source
pixels across the box and the sharpness of the patch — because the
commonest wrong answer on the reference library was a soft eye read as
closed, and a classifier shown a smear will always say something. An eye
under either floor, or narrower than six tenths of its partner (the far
eye of a turned head, whose contour collapses), is not asked; a face with
no readable eye is a fourth state, Unreadable, that no filter drops. On
twenty native renders the one real blink is caught, the laughing faces
are closed, the profiles are judged on the near eye, and the one thing
left beyond any floor is a face with a pot held over it.
Three nullable columns beside quality — P(open) for each eye and
P(sunglasses) — because the verdict is a rule with thresholds in it and a
rule belongs in code, not in rows that would have to be re-measured. NULL
is "never read": a face from before the models, or from a device without
them, and every reader treats it as unknown rather than as closed.
The measuring pass V14 built for the embedding's length is what fills
them, so the sweep's work list now also names faces with no eye reading
— but only on a device that has the models, or it would fetch every
original to do nothing to it. A peer's shard without the reading is still
adopted, unlike one without the quality: the pass finds this work by the
NULL rather than by the run marker, so adoption costs it nothing.
Two MIT classifiers from the same author as the reference pipeline's
whole-body detector: OCEC answers P(open) for one 40×24 eye, SGC
P(sunglasses) for a 48×48 head. Both load in tract once their batch
dimension is pinned by tools/fix-face-model-shapes.sh, like the embedder.
The crops come through the same fitted similarity the aligned face does,
so an eye window is a constant in template units rather than a second
warp, and a tilted head yields an upright eye. Measured on 60 proxies
from the reference library: the eye window plateaus at 22×11, the S
variant beats M and L (which overfit their own domain), and for
sunglasses the aligned face beats a head framing but the higher of the
two catches 11 of 12 pairs against 9 for either alone.
The reading keeps both eyes and the sunglasses number apart, because a
wink averages to the least informative value and a lens of dark glass
draws a confident answer from the eye classifier — over a woman in
sunglasses it read the right eye 0.97 open. Sunglasses take precedence,
and a face behind them is neither open nor a blink.
R5 says in its own note that zoom_resolution.rs establishes it as a
pixel equality; that file was tagged FR-DSP-5 alone. FR-DEV-19's three
sub-clauses carry eighty-three tags between them while the parent had
none; MaskLayer, which is the thing they edit, now carries it. And
NFR-R3 — a crash in decode does not take down the application, the
image is marked failed — is exactly what the decoder's panic guard and
the face sweep's unreadable mark do, tagged FR-RAW-4 and NFR-SEC-1 and
not the clause that asked for them.
NFR-COMPAT-1 and NFR-COMPAT-2 were instructions to write a requirement,
not requirements: "state the API level", "state the channels". Both
are now stated from what the build enforces and what exists.
The baseline is minSdk 28 / targetSdk 36 from the Android Dockerfile,
a Vulkan adapter at wgpu's default limits because compute needs storage
textures — device_from already called that the floor and is tagged for
it — with no optional feature required, since the f16 in FR-DEV-2 is a
texture format and not shader arithmetic. The reference device is the
HONOR ROD2-W09 the figures are taken on, and the second-vendor clause is
recorded as unmet rather than quietly dropped: there is no Mali or
PowerVR device, so an Android figure here is an Adreno figure.
The channels are all self-distribution — Arch package, local Flatpak,
sideloaded APK, NSIS installer — because D13's face weights rule out
every store, and the two consequences are written down: SAF stays
although a sideloaded build need not have it, and S11 becomes a
pre-publication step.
§7 still listed "AI subject masking — deferred per D11" while
MaskSource::Subject and MaskSource::Category, backed by dr-segment's
instance and semantic models, had been the primary way a local
adjustment is made for weeks. The code was tagged FR-DEV-3, which
names gradients and brushes and says nothing about a model.
FR-DEV-3i now states what exists: a subject or a category found by a
local model, stored as identity with the run's signature so that it
merges per field and reads as stale rather than wrong, then treated as
any other layer by the edge, stroke, composition and reveal clauses.
The one place it departs from FR-DEV-19 — coverage written run-length
coded beside the layer, so a stored subject renders without a model —
is recorded in the clause instead of left for the next audit to find.
The segmentation crate and the UI's selection module are tagged to it.
The register said two things about plugins. §7 had listed "Plugin API"
as deferred since the first draft, in a bare row; §3.10 then specified
it in 23 clauses that counted against coverage. Twenty-one of them had
no implementation of any kind, and could not have: no crate loads
anything at runtime. The coverage figure was measuring the contradiction.
Decided 2026-09-19: §7 is right. §3.10 stays as the design of record,
each of its clauses is marked "(post-v1)" on its defining line, and
NFR-SEC-6 — which exists only for plugins — goes with them, as does D16.
The traceability tool learns the marker. A deferred requirement is still
defined, so a tag naming it is not an orphan, but it leaves the
denominator and is listed in its own table rather than under "not yet
tagged". The marker must sit on the definition line; a mention of
"post-v1" in prose changes nothing, and where an ID is defined twice the
deferral on either line wins. Both are tested. Coverage moves from 72.2%
of 194 to 80.6% of 170 without a line of application code changing,
which is the honest figure: it now measures what v1 owes.
The sweep fetches the whole original before it can learn anything
about it, and the one file in the reference library the decoder
refuses on sight is a 521 MB stitched panorama — so every pass on the
tablet spent half a gigabyte of Wi-Fi to find that out again. The
catalog already knows the byte count, and that is enough to decide
before the fetch: originals over 256 MB are marked examined with
nothing found and a zero edge, counted as failed, and named in the
log. Below the line is every camera RAW the library holds; above it,
four files, all panoramas.
A budget and not a verdict on panoramas. The right treatment for one
is a tiled pass — read it in strips, detect in each, stitch the boxes
back — and the zero edge is what that pass would select on. Until it
exists, this is what keeps a background sweep on a phone from paying
for the decision the decoder cannot make.
Rating and flagging were reachable from the grid alone, so a photograph
opened in develop could not be judged without leaving it; FR-UI-5 said
"rating" without qualifying the view and was built as though it had.
And FR-UI-1's expanded row has said "filmstrip" since it was written
while the roll stayed on demand in both classes. Both are amended to
say what they meant: judgement follows the photograph, without
auto-advance outside the culling mode, and the roll is open by default
where there is room for it.
The larger change is a rule. Per-face signals — eye state from a
classifier, head pose from the five landmarks the detector already
yields — are worth having for culling, and §3.9.1 excluded detecting a
blink outright. The exclusion was always of judgement, not of knowing:
a blink is a fact about a frame of the same kind as a clipped
highlight. FR-CULL-8a specifies the two signals; FR-CULL-13 says what
any signal may do (be shown, filtered, sorted, propose a burst
representative) and what none may (write a rating or flag without a
user action between). R7 states the same thing as a user need.
Licensing was read before either was written. OCEC's eye-state weights
are MIT with a clean data chain; every open gaze model is trained on
Gaze360 or its peers, whose licences restrict derived models by name,
so gaze is deferred in §7 and head pose stands in for it. D13 records
both so they are not re-searched.
Replacing a closed-eyed face from a neighbouring frame was raised and
is written down as D17 rather than built: it is the multi-source schema
question §7 already defers for panorama and HDR, with its non-goals —
never automatic, provenance declared — fixed now.
Traceability regenerated: three new IDs, none yet tagged.
Choosing "Thorough" made the library look empty. The detector setting
writes under its own faces.model_id, and every reader of "the faces"
keyed on that exact id: the clustering pass, the coverage figure, the
sweep's work list, the shard export and import, and the sync merge's
face matching. On the reference library that restarted coverage at
1,834 of 19,140, drew a People rail of 36 faces for a person with 520,
queued a ~400 GB re-fetch on each device, and stranded the desktop's
3,583 confirmations under the old id: the tablet held the same faces
under the new one and the merge refused to match them. Same photograph,
same box, same embedder, two ids — that is one face, not two libraries.
The embedder half of the id is now the key. embedder_of and embedder_sql
give it to every query; writes keep the full id, so which detector drew
a box stays on record. record_detections is unchanged and is where the
generations meet: an image holds one pipeline's faces at a time, and a
re-detection carries confirmations across by box overlap. The merge's
match_faces applies the same rule within an embedder. The calibration
is keyed on the embedder too, since the similarity space did not change.
Shards travel every generation, each under its own id, and a peer adopts
whichever it is sent — including a stronger detector's pass over an
image it indexed itself with a weaker one, which is the re-detection its
own sweep would otherwise queue, already done. Never downwards: a tablet
on Fast keeps the desktop's Thorough faces. The sweep gains the same
tail — images a weaker detector indexed, after the ones nothing has —
driven by FaceDetector::supersedes, so choosing a stronger detector still
improves the library over time without first making it disappear.
A decode failure in the face sweep was counted, logged at debug where
nobody saw it, and left unmarked — so the next pass fetched the same
file and failed the same way. For the 521 MB panorama behind rawler's
panic that was half a gigabyte per sweep, on a tablet. It is now marked
examined with nothing found and a zero edge, which is what a later "try
again with a better decoder" pass would select on, and the warning
names the file. The failure count is unchanged: it did fail.
rawler panics on some input rather than returning Err — a DNG whose IFD
claims a >50000 px image, which the reference library has: a 521 MB
stitched panorama, IMG_4181-Pano.dng. On a worker thread a panic is the
end of the thread, so the face sweep that met it stopped thirteen
seconds in, three sweeps running on the tablet and three on the
desktop, with "17301 image(s) to index" as the last word. FR-RAW-4
says a malformed file must not abort a batch, and that is this crate's
promise whatever the library beneath it does: every entry point that
calls into rawler now runs under catch_unwind, and a file that panics
the decoder is one failed file with the panic's message in the error.
Verified on the panorama itself: metadata reads, decode returns the
error, the thread survives. The crash hook still records the panic,
which is right — it is a defect in a dependency and the record is how
it gets reported.
dtourolle