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dtourolle 08727cff5a Release 0.13.5
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2026-09-20 15:24:47 +02:00
dtourolle f4c3f425dd Show the picker correcting something in the manual
The recording sampled a red brick wall and moved the sliders by three
units, which at GIF size is a click that does nothing. The scene now
drags the frame cold first and picks a white air conditioner, so the
correction is visible and the picker's being absolute - set from the
photograph, not from where the sliders were - is what the picture
shows. The text says so, and says a blown highlight is refused.
2026-09-20 15:24:27 +02:00
dtourolle 12f8990e09 Average a patch under the white balance picker, not one photosite
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.
2026-09-20 15:24:25 +02:00
dtourolle 8a897bbc01 Release 0.13.4
Benchmarks / CPU and I/O (per commit) (push) Failing after 6m22s
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2026-09-20 14:03:58 +02:00
dtourolle a03e082fe2 Point the manual's white balance scene at "pick", and record it again
The scene clicked 40px to the right of "pick", on "reset", so the
recording showed a neutral group being reset and a click on the wall
that panned. Re-recorded with the picker fixed: the word lights, the
sample moves temperature and tint, and Before shows what it corrected.
2026-09-20 13:41:17 +02:00
dtourolle 4576499c3b Refuse a clipped highlight as a neutral
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.
2026-09-20 13:41:17 +02:00
dtourolle 2f47087223 Measure the white balance probe in camera RGB, where the gains multiply
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.
2026-09-20 13:41:11 +02:00
dtourolle 764ad55ead Stand each person in the grouping pass by at most 100 references
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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.
2026-09-20 13:29:16 +02:00
dtourolle 301e6f3828 Release 0.13.3
Benchmarks / CPU and I/O (per commit) (push) Failing after 6m21s
Benchmarks / Frame budget (on demand) (push) Skipped
Build and test / Desktop (Linux) (push) Failing after 46s
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Build and test / Windows (x86_64, cross) (push) Failing after 3m8s
2026-09-20 13:01:41 +02:00
dtourolle a437363bd6 Schema V20: put the mis-spelled run markers right
The markers the previous commit stops writing are already in the
catalogs — 2 on the desktop, 429 on the tablet — and in the shards
both have exchanged. Renaming them to the faces' own id with a fresh
time is what makes the export send each image again, under an entry
newer than the empty one `held_model` would otherwise pick. Where the
old write had inserted its marker beside the right one, the wrong one
goes and the right one is refreshed for the same reason: its entry in
the shards is older than the empty one.

Images V14 left with faces and no marker are not touched. That state is
the quality pass's cue, and the fixed write marks them correctly when
it reaches them.

Checked against copies of both real catalogs: the desktop renames 2,
the tablet deletes 429, both in under 200 ms.
2026-09-20 13:00:59 +02:00
dtourolle 065872bec5 Keep a run marker under the detector that found the faces
`record_updates` — the write behind the quality, eye and crop passes —
re-marked the image as indexed under the pipeline the pass ran as, and
left the faces it had updated under the id of the detector that found
them. On a desktop set to Thorough that put `scrfd_10g+w600k_mbf` over
faces spelled `w600k_mbf`; on the tablet, `scrfd_10g_i8+w600k_mbf` over
faces it had adopted from the desktop's thorough pass.

Every reader takes the marker and the faces to agree. `marker_under`
reads the marker as the detector having examined the image, so the
upgrade repair never revisits it. The shard store keys each face by
its pipeline id, so `export_to_shards` selects an image's faces by the
marker's id, finds none, and sends an entry that says the thorough
detector looked and found nothing — over photographs with named faces
on them. The desktop's shard index holds 54 such entries beside real
faces; the tablet's eye pass over the faces it had adopted made 430
more, and both devices have exchanged them. `held_model` takes the
newest entry for an image, which is the empty one. Nothing has been
lost yet only because the two spellings of the thorough detector rank
equal and neither side adopts the other's; a third device, or either
one after a reinstall, would adopt "nothing here" for 484 images. And
the desktop's eye pass is 4,739 images from doing the same to every
face from before V14 — which are the ones that only exist on the
desktop, and would then never reach anywhere.

The marker now takes the id the faces carry; the pass's own id is used
only when it dropped the last of them and there is no detector left to
name. A stale marker under another spelling of the same embedder is
removed in the same transaction, so one embedder has one marker.
2026-09-20 13:00:58 +02:00
dtourolle 0ed38ada28 Adopt a peer's unmeasured faces instead of refusing them
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.
2026-09-20 12:58:41 +02:00
dtourolle 695d5ec304 Correct four claims in the README against the tree
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Eighteen declared operations, not fifteen; JPEG XL is an export format;
the grid does not filter by keyword, only the catalog's query can; and a
panorama's provenance is a sidecar beside the composite, not a history
step in it.
2026-09-20 11:57:17 +02:00
dtourolle ef1afc254d Release 0.13.2
Benchmarks / CPU and I/O (per commit) (push) Failing after 6m36s
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2026-09-20 11:06:54 +02:00
dtourolle 103c6e7fc0 Rewrite the README for someone arriving, not someone already here
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It said 0.9.0 against a 0.13.1 tree, listed focus peaking and burst
grouping as unbuilt when both have shipped, and opened with a page of
prose about the display path before saying what the application does.
Lead with what it is and a picture of it, say how to get it on each
platform and what state each channel is in, keep the honest account of
what is missing, and put the manual first in the documentation table.
2026-09-20 11:06:10 +02:00
dtourolle e9398de9c1 Ship the fine-tuned border filler: MI-GAN 512 trained on projection-shaped voids from the maintainer's library 2026-09-20 10:56:38 +02:00
dtourolle b1c99b5796 Let the fill show the model an open void: mirror depth 0 means no ring and nothing known beyond the band 2026-09-20 10:56:38 +02:00
dtourolle 3de109fbd1 Write down the catalog and screen-refresh patterns the Identity fixes exposed
A CLAUDE.md at the root, for anyone changing this code: the ways a redraw
and a catalog read came to cost half a second per click, what each fix
looked like, and how to measure the next one against a copy of a real
catalog.
2026-09-20 10:56:37 +02:00
dtourolle 388bda6af3 Count the outstanding repairs from the faces, on partial indexes
"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.
2026-09-20 10:56:37 +02:00
dtourolle 73845d8a77 Ask the server about a collection once per job, not once per file
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.
2026-09-20 10:56:37 +02:00
dtourolle b4821ee1ab Filter the people rail in the query, and count the unassigned faces
`faces::people` grouped `face_person` after a LEFT JOIN over every person
and sorted the lot by name; the rail then discarded the empty, unnamed
groups a regrouping pass leaves behind — 17,000 of 19,000 rows on the
reference library. `people_in_use` filters them in the WHERE and joins
`people` to face counts aggregated first (2,000 groups), so the sort sees
only the rows that will be drawn. `count_unassigned` replaces fetching
2,400 ids to take their length. `load_people` 22 ms → 10 ms.
2026-09-20 10:56:36 +02:00
dtourolle 9d1aa5735b Confirm a group, and split one, in one transaction
`confirm_all` called `faces::confirm` per face, and `split_off` called
`reject` then `confirm` per face: each opens and commits its own
transaction, so a click on a group of several hundred was several hundred
commits. `faces::confirm_all` is two statements — clear the rejections the
confirmations override, then flip the rows — and `faces::reassign` does a
split's reject-and-confirm for every face under one commit. 16 ms → 2 ms
and 22 ms → 4 ms on the largest group.
2026-09-20 10:56:36 +02:00
dtourolle 97a854833d Reuse the face grid's decoded crops across a redraw
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.
2026-09-20 10:56:36 +02:00
dtourolle e0e193efb4 Do not recount face coverage on every confirm, and count it without listing
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.
2026-09-20 10:56:36 +02:00
dtourolle d790961b28 Add the manual: every feature pictured from the application itself
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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.
2026-09-20 00:26:00 +02:00
dtourolle 14ac41bee0 Give the keyword sheet's field focus, and the empty trash its own words
Without focus the keys typed into the keywords sheet went to the grid
behind the scrim, and the Return meant for the keyword opened a
photograph. The naming sheet already takes focus on open; do the same.

An empty trash said "No images found — check the library folder and which
formats are ticked", which sends someone off to fix a library that is
fine.
2026-09-20 00:21:14 +02:00
dtourolle 86410def88 Title the gesture book for the whole application, not the grid 2026-09-20 00:21:14 +02:00
dtourolle df8be10c7d Stop promising to ask for an export folder
An empty device destination read "Ask each time" on the settings page,
and nothing asks: an export made with the field blank is refused with
"no export folder is set". Say what will happen.
2026-09-20 00:21:14 +02:00
dtourolle f176043632 Report a merge worker that dies rather than leaving the page on Stop
wgpu reports a device out of memory by panicking, and a twelve-frame
merge on a GPU another process is using is where that happens. The panic
unwound the worker, the sender went with it, and the page sat on "Stop"
with every control disabled and nothing to say why — the crash record on
disk was the only sign. Catch the panic and send it as a failure, and
treat a closed channel with no final event as a dead worker too.
2026-09-20 00:21:14 +02:00
dtourolle 9c2cd73337 Show a mask's tint only while masking
The eyes are per layer and outlive the mode, so a photographer coming
back finds the layers they were looking at still lit. But the tint is a
way of looking at a mask, and outside Local there is no mask being looked
at: the sky stayed red through Repair and back in Photo, a mode that had
been left leaving its overlay behind — the fault ui-navigation.md D-N1
exists to prevent.
2026-09-20 00:21:14 +02:00
dtourolle e3acbdf4a3 Wrap the falloff and edge chips so a category mask cannot widen the column
Five chips in one row declare 440px, and the develop column takes the
widest panel's request — so selecting a category mask levered the sidebar
past the window's edge, clipping the histogram, the group strip and the
subject list. The same trap ChipGrid's comment records for film formats.
2026-09-20 00:21:14 +02:00
dtourolle eddaa44cd3 Announce a month at the next row it opens, not only if it begins one
A heading was drawn only on a cell that both began a month and began a
row, so at seven columns most months were never named, and the one
heading on screen — always on the window's first cell — was wrong about
every row below it. Worse, two headings drawn on the same cell overprinted
each other. Now a row carries a heading whenever its first cell's month is
not the one last announced: a month starting mid-row is named on the next
row it opens, one row late and right about everything under it.
2026-09-20 00:21:14 +02:00
dtourolle 7fba28f7d8 Upload a snapshot of a thumbnail shard, never the live file
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.
2026-09-20 00:21:14 +02:00
dtourolle 0fa9003e54 Let the top level be chosen as the library root
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".
2026-09-20 00:21:13 +02:00
dtourolle e750bcdb8c Date the composite at the mean of its frames' capture times
Benchmarks / Frame budget (on demand) (push) Skipped
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It carried the first frame's, so it sorted before the sweep it was made
from. The middle of the sweep puts it among them.
2026-09-19 22:36:09 +02:00
dtourolle 48c4b403d2 Date a DNG whose IFDs follow its pixels: read the head and the tail
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.
2026-09-19 22:35:58 +02:00
dtourolle 9d04ff2154 Release 0.13.1
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2026-09-19 22:06:06 +02:00
dtourolle c6cfb2a02a Put the -1 on the greens along the chroma axis, not across it
The Malvar "R at green in R row" kernel weights the two greens two
sites away along the row at -1 and the pair up and down the column at
+1/2. The shader had the two swapped, in the comment as well as the
code, so the transcription checked against itself. Both sum to zero
and reconstruct a flat patch exactly, which is all the tests fed it.

On an edge the correction at green sites is half strength and the
false colour doubles: 0.375 against 0.19 on a grey step, and a
blue/yellow zipper around every clipped highlight at 1:1. The other
three kernels and the CFA tables were right.

A grey vertical step now runs through the pass; the transposed kernel
fails it at 0.375.
2026-09-19 22:05:39 +02:00
dtourolle b83f192847 Package release 2 of 0.13.0: the inference engine and the user runtime directory 2026-09-19 21:20:53 +02:00
dtourolle ecb648818b Search the user's own runtime directory before the system library
The reference desktop's only system ONNX Runtime is Arch's
onnxruntime-opt-cuda: 1.29, built without TensorRT and against cuDNN 8
on a cuDNN 9 machine. The probe rejects both providers correctly and
the app runs on the CPU provider, which is right and not what anyone
wants. runtime/ beside the models is now searched ahead of /usr/lib,
tools/fetch-desktop-runtime.sh fills it with the four libraries from
the current onnxruntime-gpu wheel (cuDNN 9, TensorRT 10), and the
About caption lists every rung that lost and why, not only the first.
Verified: the app selects TensorRT from that directory with no
environment variable set.
2026-09-19 21:15:55 +02:00
dtourolle 5fbf8944d7 Count the filler in the APK's bundled-model array
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The unpack list gained migan-512.onnx without its length following;
nothing on the desktop compiles that crate, and the first Android build
of 0.13.0 stopped there.
2026-09-19 20:55:38 +02:00
dtourolle b502a8ef90 Release 0.13.0
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2026-09-19 20:43:27 +02:00
dtourolle 6fbdb1d06f Regenerate the traceability matrix and gesture book after the rebase 2026-09-19 20:41:44 +02:00
dtourolle d04b8f6044 FR-MRG-4: the border is cropped or filled, the fill experimental; panorama.md §13 records what was built and measured 2026-09-19 20:41:22 +02:00
dtourolle 8baa46ff49 Let the merge example fill, wait for engines and dump the filler's input; add a fill example that re-runs it stage by stage
A fill that went wrong took a seven-minute merge to look at again. Now
DR_FILL_DUMP=dir makes the merge write what the filler was given, and
the fill example runs fill_border on that, or a crop of it, on the engine
and writes coarse, each band and the feathered result as PPMs — seconds
per attempt on TensorRT. Both examples take DARKROOM_ORT_DIR as the app
does, and --wait-engines lets a compiling rung finish before timing.
2026-09-19 20:41:22 +02:00
dtourolle e43ae10439 Offer the border fill on the merge page, experimental, with every knob on it
A Border choice beside the projection — crop to the picture, or fill it
— that redraws the preview filled so the invented pixels are seen before
they are confirmed (FR-MRG-1), greyed with the reason when the model is
not there. The job fills at half the composite's resolution in a
display-ish space (white balance, matrix, gamma; invertible) and samples
the result back into the linear DNG wherever no frame reached; the
sidecar's merge line says border filled and with which knobs.

Experimental because the fill is right in thin borders and wrong in deep
corners, where the model's Places2 prior puts clouds in sky and water
under grass; so its six knobs — working scale, edge erosion, coarse pass,
band width, mirror depth, seam feather — are sliders under the choice,
each committing a redraw, until the defaults are right.
2026-09-19 20:41:22 +02:00
dtourolle 104e3a106f Fill a panorama's border with MI-GAN: mirrored context, coarse to fine, a feathered seam
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.
2026-09-19 20:41:22 +02:00
dtourolle 031ba7b77d Hash a model's bytes once, at open, not on every acquire
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.
2026-09-19 20:41:21 +02:00
dtourolle 54a80e688c Ship MI-GAN's bare 512 generator as the panorama border filler
Sargsyan et al., ICCV 2023; MIT code and weights (models/LICENCE.md),
exported by tools/export-migan.sh at a fixed 1×4×512×512 from the
authors' checkpoint — six operator types, 28 MB, in LFS like the rest.
The package installs it beside the scene model and the APK unpacks it
with the others.
2026-09-19 20:41:20 +02:00
dtourolle 2fd7690b6f Mark a pixel the lens correction pushed off the sensor with alpha 0 in the camera-space tap
The fused shader stored black with alpha 1 for a pixel whose source
coordinate left the frame, and the merge's warp averaged it in like any
other: a dark, badly interpolated fringe along every frame's edge, visible
as a seam wherever a frame ended and, later, as the edge the border fill
continued. The display keeps its opaque black; CameraLinear stores alpha 0
and the warp weights each sample by the alpha it interpolated, dropping a
sample that has none.
2026-09-19 20:41:20 +02:00
dtourolle c5f07f9ced Give the engine an Inpainter role for the panorama border filler
MI-GAN is plain convolutions, so every rung serves it and none needs a
special form; the role exists so resolve_model and the probe's fingerprint
know the model, and so the merge job can open it through the engine rather
than tract, which takes 7.4 s a tile for it.
2026-09-19 20:41:20 +02:00
dtourolle 5c00942b84 One completeness job over a registry of repairs, and a re-index button
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".
2026-09-19 18:52:13 +02:00
dtourolle 2a4ac0ed3d Carry every identity across a re-detection, by box and by embedding
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.
2026-09-19 18:34:31 +02:00
dtourolle 46af2a0a46 Stop naming an optimisation level: on tract it means into_optimized, which aborts on yolo26n-seg
ONNX Runtime's default is already its fullest level. ort-tract maps any
level but disabled to tract's optimiser, whose slice pass divides by
zero inside the segmenter's graph — a panic across the C API and so an
abort, which is what stopped dr-ui's develop test. The app never asked
tract for that and does not start now.
2026-09-19 16:35:22 +02:00
dtourolle 95c9cffc0d Keep the embedder off the Hexagon, and let the probe example ask for a runtime
On the tablet the engine compiled arcface for the NPU: the routing
compared the form a rung wants with the form on offer, and for the
embedder both are f32, so nothing said no. A rung now says which roles
it serves at all, and the Hexagon does not serve the embedder (§7 —
its vectors must compare across devices). Tested at the routing seam.

dr-segment's onnx_probe example still named ort-tract, which is what
stopped the workspace test build.
2026-09-19 16:21:53 +02:00
dtourolle cbbe67fbd7 Let the probe's clock be its proof, not disable_cpu_ep_fallback
The strict flag refused the Hexagon over the ten quantise/dequantise
nodes at the graph's edges that QNN declines by policy, which cost
microseconds. A provider that hands real work to the CPU is slower than
the CPU floor and the timing already rejects it; the tablet measured
2.3 ms on the NPU against a 29.7 ms floor.
2026-09-19 16:13:19 +02:00
dtourolle 691af96e3e Keep the readable half of a provider's error for the settings row
ONNX Runtime's errors open with a source path and a template signature;
the first 160 characters of a CUDA failure were all signature. The
reason now starts at the first word a person can act on.
2026-09-19 16:07:19 +02:00
dtourolle 7a436e2549 Move the panorama keypoint detector onto the engine, and probe with a detector
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.
2026-09-19 16:05:08 +02:00
dtourolle 76bc5652d7 Calibrate the int8 detectors on library proxies, in chunks, and measure them
The first int8 files found no faces at all, and for two reasons the
tool now guards against. The calibration set was landscape photographs
with no faces in them, so the score head's ranges had never seen the
face regime; the set is now proxies from the library itself. And ONNX
Runtime's strided and moving-average calibration modes both degrade
these graphs measurably (a quarter of the faces at eight images, none
at ninety-six), while driving the calibrator in chunks by hand gives
ranges identical to a single pass — so the tool does that, four images
at a time, and feeds quantize_static through its range cache.

Measured against f32 over 400 proxies (docs/inference.md §10.1): the
10g form finds every face above 32 px the f32 form finds; 500m and
2.5g find 96%, and what they lose sits at a median confidence of 0.52
against the 0.50 threshold. Shipped with the number on record.

The Android unpack list gains the three int8 files; without that the
tablet never saw them. D13's runtime half records the reopening.
2026-09-19 16:02:44 +02:00
dtourolle 4ed29b9d81 Add the int8 detectors for the Hexagon, calibrated on real photographs
tools/quantise-models.sh writes the QDQ form QNN's HTP backend takes
whole: opset 17, per-channel int8 weights, uint8 activations, ranges
from running the f32 graph over photographs fed exactly as the app
feeds them. The calibration is strided, four images at a time, because
every ONNX Runtime calibrator holds each image's whole set of
activations until it folds them — a gigabyte an image on the 10g
detector, and an OOM kill with no message when folded once at the end.

Release-time, never on the device (docs/inference.md §5): it needs
real photographs and a person reading the recall measurement that
gates whether each file is offered.
2026-09-19 16:02:37 +02:00
dtourolle 05508741af Start the inference engine from both apps and show its choice in Settings
The desktop names where a package may have put libonnxruntime — an
override variable, beside the executable, the package's own library
directory, the Flatpak prefix, the system library directory — and
Android points at the APK's native library directory, which is also
what Qualcomm's DSP loader must be told for the Hexagon skel. Android
starts the engine at the end of the model unpack rather than at launch,
because the probe fingerprints the model files and a first launch has
none until then.

The About panel gains an Inference row beside Graphics, re-read every
two seconds while the probe runs and engines land, and faces.model_id
carries the detector's form: an int8 detector finds a different set of
faces and is a different population (docs/inference.md §7). A
low-memory signal drops every idle session with the GPU caches.

The APK assembly bundles ONNX Runtime and the Qualcomm HTP libraries
from Maven, fetched by tools/fetch-android-runtime.sh with their
published checksums; RUNTIME_DIR=none builds the tract-only APK, which
is a slower app and not a broken one. The desktop packages carry no
runtime yet.

Two probe fixes from the first desktop run: the floor must not be
built with CPU fallback disabled, and a versioned libonnxruntime.so is
a runtime too. On the reference desktop the probe now loads ONNX
Runtime 1.30, measures 30 ms on the CPU provider, and selects TensorRT
at 1.5 ms.
2026-09-19 16:02:37 +02:00
dtourolle d15c41e699 Add dr-inference-engine and route every model session through it
One crate names the runtime, the providers and the devices; dr-face and
dr-segment ask it for a session by role. It hands ort an API table once
per process — from a libonnxruntime it dlopens when the app names a
directory holding one, otherwise from tract — so the Rust build stays
free of C on every target and a package can install the runtime as a
file (docs/inference.md §3).

Sessions live in a registry behind a Model handle that holds the bytes,
not the session: every use refreshes a timestamp and a reaper unloads
whatever sat idle past the decay. A scan that runs the detector on each
image never lets it go idle; a click in the develop view lets the
segmenter go after thirty seconds; a handle used after that reloads,
and reloads on a higher rung if a compiled engine has landed meanwhile.

The probe walks the platform's ladder by building strict sessions and
timing them against the CPU provider, caches the choice against a
fingerprint of the runtime, driver, hardware and models, and compiles
engines for the selected rung in the background, smallest model first.
Nothing in this commit turns the native path on: the apps still run on
tract until they call init with a runtime directory.
2026-09-19 16:02:37 +02:00
dtourolle caf21bea64 Name the crate dr-inference-engine 2026-09-19 16:02:37 +02:00
dtourolle 6739fdf908 Specify per-device inference backends, with the 2026-09-19 measurements
tract runs every model on one core on every platform. Measured against
ONNX Runtime's providers on the MagicPad 2 and the reference desktop:
ORT CPU alone is 3-10x, the Hexagon at int8 runs the detectors in
1-3 ms, TensorRT is ~2x the CUDA provider. NNAPI, XNNPACK, WebGPU and
CUDA int8 were tried and excluded with the numbers that excluded them.

The spec keeps the build C-free: ort::set_api takes a table from a
dlopened runtime or from ort-tract, chosen once per process. Rungs
are chosen by building a real session, cached until an input changes,
and compiled engines are built in the background after the first
frame. The embedder stays f32 everywhere; int8 detectors are a
distinct model_id and are gated on a recall measurement.
2026-09-19 16:02:37 +02:00
dtourolle 42d11d919b cargo fmt and clippy across the panorama work, and one lint master carried
The dr-face comparison is master's: a negated partial-order test on the
eye box's width, rewritten as the two conditions it meant.
2026-09-19 15:53:06 +02:00
dtourolle 67f225beba panorama.md: MI-GAN as the border filler — MIT, six operators, 7.4 s a tile
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.
2026-09-19 15:30:49 +02:00
dtourolle 39adfd4b75 Regenerate the traceability matrix and gesture book after the rebase 2026-09-19 15:24:44 +02:00
dtourolle 57ed51c1c5 Projection chips redraw the preview; auto-crop as the DNG default crop
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.
2026-09-19 15:24:20 +02:00
dtourolle 30bd276d0b Merge page: outline every frame on the preview, and let it be tall
A sweep whose frames overlap by more than half reads as one photograph,
and the page's job is to show frames. Each footprint is walked along its
border and drawn in amber where it lands, so twelve frames look like
twelve and a misplaced one is visible as such. The preview may take most
of the page's height rather than 320 px.
2026-09-19 15:24:20 +02:00
dtourolle 75d2ceb23c Provenance in the sidecar, a launch hook for the page, and where it stands
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.
2026-09-19 15:24:20 +02:00
dtourolle 2e9a1eb0f0 The merge job and its page: a selection to a panorama DNG, confirmed 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.
2026-09-19 15:24:20 +02:00
dtourolle 44ea763c61 dr-gpu: the merge pass — warp, accumulate, resolve, chunk by chunk
merge.wgsl warps one camera-space tile into one output chunk — output
pixel to direction (the projection maths of dr_pano::projection, verbatim),
direction to the frame's camera, camera to source pixel, bilinear by hand
from four textureLoads because rgba32float is not filterable — and adds it
into a storage-buffer accumulator weighted by its distance from the
frame's edge. A resolve pass divides by the weights and packs sixteen-bit
samples at the sensor's scale with a coverage bit.

MergePass::merge drives it: bands of rows, chunks across a band, and for
each chunk only the frames whose footprint meets it, each rendered as the
source rectangle the chunk needs and nothing more. The working set is one
chunk, one tile and one band (FR-MRG-11); the frame textures are the
caller's to cache. Feathered, not seamed; gain a scalar per frame — the
blend quality is panorama.md §10's step 5, after the path writes a file.
2026-09-19 15:24:12 +02:00
dtourolle acab0d7abb A linear DNG in and out: the writer, and a three-sample RawImage
dr-export gains write_linear_dng — LinearRaw, DNG 1.4, u16 samples at
the sensor's scale, the body's matrices with their illuminants, the
as-shot neutral, the EXIF block an export writes — streamed strip by
strip through a closure so the composite is never held (FR-MRG-11). The
tiff crate's directory is a map, so PhotometricInterpretation is written
over what new_image set, which is the trick the S15.1 spike thought it
had to hand-roll around. The test reads the file back through rawler.

dr-decode's RawImage carries samples_per_pixel (a linear DNG is 3), the
body's profile with its calibrations mapped back to EXIF illuminant
codes, and the cleaned make and model. The GPU uploads a three-sample
image as it is, normalised by black and white like a photosite, through
a full f16 conversion — subnormals kept, because a 14-bit LSB sits at
f16's smallest normal and rounding it to zero would crush exactly the
shadows the file was written to keep.
2026-09-19 15:24:12 +02:00
dtourolle 9b6b4942cf The camera-space tap: OutputMode::CameraLinear, composed with no operations
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.
2026-09-19 15:24:12 +02:00
dtourolle 54290b9540 dr-pano: a second XFeat shape for portrait frames, and a matcher that takes seconds
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.
2026-09-19 15:24:12 +02:00
dtourolle 231b4a54ab dr-pano: the geometry, from features to cameras
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.
2026-09-19 15:24:12 +02:00
dtourolle 2bf0ec8dba S15.4, CPU half: XFeat runs in ~400 ms per frame on the tablet
tools/onnx-probe-on-device.sh cross-builds dr-segment's onnx_probe
without the embedded segmentation model, pushes it with a model to the
attached device and times two runs. The 768×1024 XFeat export takes
~400 ms on the reference tablet's NEON cores against ~300 ms on the
desktop, with identical output ranges — inside NFR-MRG-1's 1 s per frame.
The blend half of S15.4 waits for a chunked blend to exist.
2026-09-19 15:24:12 +02:00
dtourolle 5bf06c5030 Fixture README: the frames carry Orientation 8, not 6 2026-09-19 15:24:12 +02:00
dtourolle 44fdcbc6f7 Add the twelve-frame 6D panorama set as an LFS fixture
fixtures/pano/2025-08-05: _MG_8320 … 8331, one portrait hand-held sweep
at 50 mm with a stop of shutter drift and sky in every frame — the set
§3.11 is built against, with each of those facts named as the test it
is. fixtures/** is tracked in LFS like the models but with the opposite
default: CI's pulls exclude it, so a build never fetches 325 MB it does
not use.
2026-09-19 15:24:11 +02:00
dtourolle f9510405c3 FR-MRG-3: the composite is a RAW at the source's native scale
Camera-linear u16 samples on the first source's black-subtracted scale
with its white level, never rescaled to fill 16 bits, with its body,
matrices, illuminants and as-shot neutral carried — so the panorama is
developed afterwards as one photograph from the sensor's own numbers.
The only thing a warp cannot preserve is the colour filter array, and
the clause says so.
2026-09-19 15:24:10 +02:00
dtourolle 7e6b25b21b S15.3: the camera-space tap is uniforms, not structure — and FR-MRG-2 moves below the profile
The fused chain, as operation.rs's tests fix it, is warp → as-shot white
balance → operations → base curve → camera matrix → store. LinearWorking
stores after the matrix, so the existing linear tap carries the body's
base curve, and a composite stitched from it and developed as an
unprofiled body would render that curve twice.

FR-MRG-2 therefore stitches camera-linear RGB — after the warp, before
white balance, curve and matrix — and the composite carries the first
source's body, matrices and as-shot neutral so its own develop applies
the profile once. The composer already makes this a uniform question:
white balance, matrix and the curve flag are reserved uniforms, so the
tap is a compose entry with no operations and a render entry that fills
them neutral. panorama.md §5.1 states the shape and asks for f32 buffers.
2026-09-19 15:24:10 +02:00
dtourolle e4b6b6c935 S15.2: XFeat exports at a fixed shape and loads under tract
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.
2026-09-19 15:24:10 +02:00
dtourolle 1ded5afbaa S15.1: rawler reads back a linear DNG, so that is the container
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.
2026-09-19 15:24:10 +02:00
dtourolle c901fc1a0a Specify panorama merging: §3.11, D18, S15, and the design in panorama.md
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.
2026-09-19 15:24:10 +02:00
dtourolle f79a76f2d5 Name the eye pass on the People screen
Once every image has been through the detector and only readings are
left — the state an already-indexed library is in the day the eye models
arrive — the button reads "Read eye state" rather than promising to
index, and the coverage line says what the faces are waiting for.
2026-09-19 14:24:16 +02:00
dtourolle facb44cb55 Keep the dense landmarks behind each eye reading, packed
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.
2026-09-19 14:24:15 +02:00
dtourolle 85cc2b1dcc Trace the eye reading to FR-CULL-8a and the chip to FR-CULL-13
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.
2026-09-19 14:06:59 +02:00
dtourolle d706c12d77 Cover the eyes-open subquery with an index
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.
2026-09-19 14:05:52 +02:00
dtourolle cd0ca6785f Specify eye state as a filter term, and record what was measured
FR-CULL-13, with §3.9.1's exclusion of blink detection re-read as the
exclusion of blink selection it always was: the stored fact and the chip
are built, a pass that picks the frame where everyone's eyes are open is
not. faces.md §17 has the models, the crop measurements, the four-state
rule and its floors, the native and proxy sheets read face by face, and
what remains to measure.
2026-09-19 14:05:50 +02:00
dtourolle 83f4253b6a Filter the grid to a person with their eyes open
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.
2026-09-19 14:04:35 +02:00
dtourolle 6aae4c3eb0 Ship the three eye-state models beside the face pair
2d106det for the eye contours, OCEC for open or closed, SGC for
sunglasses — all three pinned to a batch of one by the same script as
the pair, and installed by every packager so the eyes-open filter works
out of the box. The two classifiers are MIT, code and weights; the
README records their provenance, SGC's undocumented training set, and
the hashes as fetched and as shipped.
2026-09-19 14:04:08 +02:00
dtourolle 54b543fb77 Store seven eye numbers per face rather than three
Per eye P(open), the pixels across its box and the sharpness of the
patch; and P(sunglasses). The verdict — open, closed, sunglasses,
unclear — stays a rule in dr_face::eyes so the floors can move without
re-measuring twenty thousand faces. Shards carry the same seven, and a
peer's shard from before any of them is still read.
2026-09-19 14:04:08 +02:00
dtourolle f5956707e7 Cut the eye box from a landmark contour, and refuse eyes that cannot be read
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.
2026-09-19 14:04:08 +02:00
dtourolle b908d861e0 Keep each face's eye reading in the catalog and in its shard
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.
2026-09-19 14:04:06 +02:00
dtourolle 6b51726322 Read each face's eyes, and whether sunglasses hide them
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.
2026-09-19 14:03:31 +02:00
dtourolle 2481904016 Bring outstanding.md up to the decisions of 2026-09-19
Its plugin section still asked for the contradiction to be resolved, its
render-path section still asked whether FR-DSP-2 was a requirement and
said NFR-RES-2 had no answer, and its closing section still called D12
open. Each now records what was decided and keeps the argument that was
weighed, so the document reads as the history it says it is rather than
as a plan the register has moved past.
2026-09-19 12:25:04 +02:00
dtourolle a92ae4576f Repair the references that point at sections that moved
Eight citations named §5.1, §5.2 and a §5 selector language that
requirements.md's §5 has not contained since it became a pointer at
architecture.md; two named §9 for the golden images and the benchmark
suite, which are §8; and the three pointers into architecture.md were
each one section off. All now name the section that holds the thing.

architecture.md §12's subsections are numbered 6.1–6.13, colliding with
its real §6. That numbering is what every ARCH §6.n citation in the tree
uses, so it stays, and a note at the head of §12 says so instead of
leaving the next reader to work it out.

FR-DEV-3f's open question about persisting the film stock was answered
in sidecar.rs; the clause now says so.
2026-09-19 12:25:04 +02:00
dtourolle ed4460cb9c Tag three requirements the code already meets
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.
2026-09-19 12:25:04 +02:00
dtourolle 7596cf9bcc State the compatibility baseline and the channels
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.
2026-09-19 12:25:04 +02:00
dtourolle 696bafa9d5 Undefer AI subject masking, which shipped, and give it a clause
§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.
2026-09-19 12:25:03 +02:00
dtourolle d259c0d4bb Say that FR-DSP-2 is waiting on S6, not that it was rewritten
R5's note said FR-DSP-2 "was rewritten rather than implemented". It was
not: the clause still demanded viewport tiling, the matrix listed it
unbuilt, and frame-budget.md's rewrite had been proposed and never
applied. Decided 2026-09-19 to keep it as written until S6 runs on a
mid-range Android device, because the measurement that argues against
tiling was taken on a discrete desktop GPU and the clause exists for the
device whose memory the image exceeds. Both notes now say that.
2026-09-19 12:25:03 +02:00
dtourolle 95458356da Record D13's position on the face weights
The licensing half of D13 had been open since 2026-08-09, while the
InsightFace detectors and embedder shipped in the tree and indexed real
libraries. models/face/README.md already stated the position the
project was actually taking; the register did not.

Now it does: this is non-commercial software, self-installed, and it
uses the weights under their research grant as such. The risks are
written where the decision is — the grant binds every user, it is not
GPL-compatible, it rules out every public channel, and publishing is
what reopens the decision. S14's licence search is what would close it.
2026-09-19 12:25:03 +02:00
dtourolle dc9db11033 Decide NFR-R8: no CPU pipeline, a degraded mode instead
NFR-R8 carried the words "decide explicitly" for six weeks, asking
whether v1 has a full CPU render path or whether "CPU fallback" means
staging only. The viewer had already answered it: with no adapter it
opens the library on embedded previews and cached proxies, keeps every
catalog edit available, and withholds develop and export. That is the
degraded mode, it is now the requirement, and NFR-RES-2 no longer
promises a fallback render path that was never going to be built.
2026-09-19 12:25:03 +02:00
dtourolle 3692306fd3 Say once that there is no phone
Three statements disagreed. §1.2's platform table said "phone
supported"; §3.5 said phones were out of scope and cited §1.3, which
does not mention them; D15 said "no phone" and gave the reason. D15 is
the decision, so the other two now point at it and say the same thing:
the build runs on a phone, and nothing is designed for one.
2026-09-19 12:25:03 +02:00
dtourolle c826fed605 Put the plugin API post-v1, and let the matrix count it that way
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.
2026-09-19 12:25:03 +02:00
dtourolle c921852d89 Record D12 as settled by events, and D3 as delivered
D12 had been OPEN since the 2026-08-08 calibration, and D3 said it
depended on D12. In the meantime the milestone D3 named was delivered
and closed on 2026-08-30 and the application reached 0.12.2 with every
cluster the calibration selected at least begun. The decision the
register was waiting for had been made by building, so the register
now says so: full scope stands, v1 has no date, and "post-v1" in §7 is
the one way a clause leaves the count.

The status line also stops calling this a draft from August; it has
carried eleven dated amendments since.
2026-09-19 12:24:54 +02:00
dtourolle e6ac31d39d Give the face sweep a size budget, so a panorama is never fetched
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.
2026-09-19 12:14:05 +02:00
dtourolle 7db999c1f6 Require judgement anywhere, and evidence that never becomes a verdict
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.
2026-09-19 11:47:27 +02:00
dtourolle 30b89ad70a Merge: one face population per embedder, whichever detector found them 2026-09-19 10:52:31 +02:00
dtourolle 327decfab1 Fuse every detector's faces into one population per embedder
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.
2026-09-19 10:49:28 +02:00
dtourolle f8addbee53 Mark a file the decoder cannot open, so the sweep stops fetching it
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.
2026-09-19 10:45:08 +02:00
dtourolle c0b1e78f7c Return a panic inside the decoder as an error, not as the end of the thread
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.
2026-09-19 10:45:07 +02:00
dtourolle 78cb00634e Fetch the photographs around the open one ahead of the step to them
Benchmarks / CPU and I/O (per commit) (push) Successful in 3m59s
Benchmarks / Frame budget (on demand) (push) Skipped
Build and test / android-image (push) Canceled after 0s
🐳 Android image / Build and push (push) Canceled after 0s
Build and test / Android (aarch64) (push) Canceled after 0s
Build and test / windows-image (push) Canceled after 0s
🐳 Windows image / Build and push (push) Canceled after 0s
Build and test / Windows (x86_64, cross) (push) Canceled after 0s
Build and test / Layer separation (push) Canceled after 0s
Build and test / Desktop (Linux) (push) Canceled after 16m26s
Traceability / Requirement traces (push) Canceled after 0s
Walking the photo roll was one download per frame: every step showed
"Downloading…" over an empty canvas while tens of megabytes came down,
and moving between a pair of near-identical frames paid that a dozen
times. Now, once the opened photograph has landed, the ones around it
are fetched into the originals cache while it is being looked at, so
the next step is a disk read.

A single worker serves the latest wish only, closest first and working
outwards — next, previous, next-but-one, previous-but-one… — one file
at a time. Each open replaces the wish, so a fast walk never leaves a
trail of stale downloads competing with the one being waited on. A
process-wide in-flight registry makes a click on a photograph that is
still being fetched ahead wait for that transfer and read it from disk,
rather than start a second download of the same file.

How far each side is a setting under STORAGE — Off, 2, 5, 10 or 20,
defaulting to 5 — and it is moot while "keep originals after opening"
is off, since a fetch the cache would discard on arrival is transfer
for nothing. Nothing is fetched ahead while offline. The transfers show
in the activity list while they run and are removed when they end.
2026-09-19 10:36:50 +02:00
dtourolle 2917b7427d Release 0.12.2
Benchmarks / CPU and I/O (per commit) (push) Successful in 12m51s
Benchmarks / Frame budget (on demand) (push) Skipped
Build and test / Desktop (Linux) (push) Successful in 1h44m42s
Build and test / Layer separation (push) Successful in 1m4s
🐳 Android image / Build and push (push) Successful in 6s
Build and test / android-image (push) Successful in 7s
🐳 Windows image / Build and push (push) Successful in 3s
Build and test / windows-image (push) Successful in 3s
Traceability / Requirement traces (push) Successful in 2m15s
Build and test / Android (aarch64) (push) Successful in 1h4m7s
Build and test / Windows (x86_64, cross) (push) Successful in 1h12m17s
2026-09-19 10:15:46 +02:00
dtourolle 33e2e277a2 Set the Wayland app id late enough for it to take
The launcher and the task bar have shown a generic tile for a working
window since the call was written. set_xdg_app_id sat at the top of
run(), on the reasoning that the app id is read when the surface is
created — true, and beside the point: the call goes through Slint's
global context, and there is no global context until something installs
a platform. That is BackendSelector inside shared_gpu, or AppWindow::new
falling back to the default, and both happen further down. Called before
either, it returned NoPlatform and did nothing at all.

It moves to just after the window is constructed, which is not the same
as shown — run() is far below — so there is a platform to talk to and
the surface does not exist yet.

The failure was logged at debug, which is why a year of grey squares went
unremarked: the whole symptom is invisible from inside the application.
It is a warning now, naming the consequence.
2026-09-19 10:15:46 +02:00
dtourolle 9b627e7713 Let a catalog writer wait for its turn instead of losing its work
SQLite's busy timeout defaults to zero, and nothing ever set one: the
loser of a write race got SQLITE_BUSY at the moment it asked. WAL does
not cover this — it makes one writer and many readers free, and this
application constantly has two writers, the face sweep committing a
batch while the derived sync imports shards or reclustering reads.

The cost was not a retry but lost work. A sweep that had already paid
for the detection and the embedding — seconds per image, the expensive
part — discarded the result on "storing faces for 214: database is
locked" and moved on to the next image. Both the desktop and the tablet
logged runs of those on consecutive images, which is a face sweep
quietly failing to store the faces it had just computed.

Ten seconds, on every connection, set in configure() so that nothing
can open the catalog without it — the figure the job runner's own tests
have used for this reason since they were written. It is far longer
than any transaction here, so it bounds pathology rather than making
anyone wait.
2026-09-14 20:05:53 +02:00
197 changed files with 24063 additions and 2139 deletions
+16
View File
@@ -10,3 +10,19 @@
# detects exactly that and fails with an instruction rather than embedding the
# pointer and failing at inference time.
*.onnx filter=lfs diff=lfs merge=lfs -text
# Test photographs live in LFS too, and are fetched only by the tests that
# need them.
#
# `fixtures/**` holds real camera files — a twelve-frame panorama set is
# 325 MB — and CI's `git lfs pull` excludes the directory, so a checkout
# carries pointers there until a merge test asks for the frames. Same
# reasoning as the models, with the opposite default: the model is not
# optional and the fixtures are.
fixtures/** filter=lfs diff=lfs merge=lfs -text
# The manual's pictures live in LFS for the same reason the models do: a
# screenshot or a GIF changes wholesale when the interface it shows changes,
# and every re-recording would otherwise stay in every clone for good. CI's
# pulls exclude the directory; nothing built or tested reads it.
docs/manual/media/** filter=lfs diff=lfs merge=lfs -text
+1 -1
View File
@@ -148,7 +148,7 @@ jobs:
| while read -r key; do git config --local --unset-all "$key"; done || true
git config --local lfs.url \
"https://x-access-token:${LFS_TOKEN}@gitea.tourolle.paris/dtourolle/DarkRoom.git/info/lfs"
git lfs pull
git lfs pull --exclude="fixtures/**,docs/manual/media/**"
- name: Cache cargo
uses: actions/cache@v4
+3 -3
View File
@@ -96,7 +96,7 @@ jobs:
| while read -r key; do git config --local --unset-all "$key"; done || true
git config --local lfs.url \
"https://x-access-token:${LFS_TOKEN}@gitea.tourolle.paris/dtourolle/DarkRoom.git/info/lfs"
git lfs pull
git lfs pull --exclude="fixtures/**,docs/manual/media/**"
ls -lR models/
- name: Cache cargo
@@ -213,7 +213,7 @@ jobs:
| while read -r key; do git config --local --unset-all "$key"; done || true
git config --local lfs.url \
"https://x-access-token:${LFS_TOKEN}@gitea.tourolle.paris/dtourolle/DarkRoom.git/info/lfs"
git lfs pull
git lfs pull --exclude="fixtures/**,docs/manual/media/**"
ls -lR models/
- name: Cache cargo
@@ -406,7 +406,7 @@ jobs:
| while read -r key; do git config --local --unset-all "$key"; done || true
git config --local lfs.url \
"https://x-access-token:${LFS_TOKEN}@gitea.tourolle.paris/dtourolle/DarkRoom.git/info/lfs"
git lfs pull
git lfs pull --exclude="fixtures/**,docs/manual/media/**"
ls -l models/face models/scene
- name: Cache cargo
+1
View File
@@ -23,3 +23,4 @@ tools/film-profiles/upstream/
# checkout, so it is larger than the repository it sits in.
/.flatpak-builder/
/build/
__pycache__/
+108
View File
@@ -0,0 +1,108 @@
# Working in this repository
Notes for anyone — person or agent — changing this code. They record what
went wrong once and what the fix looked like, so the same shape is not
written again. Requirements live in `docs/requirements.md`; this file is
about habits, not features.
## Catalog reads: work is proportional to what changed, never to library size
`docs/catalog.md §1` states the rule. These are the ways it was broken on
the Identity screen, found when every confirm click cost half a second on a
24k-image library (2026-09-19), and what each fix looked like.
**A redraw must know what changed.** A click handler that calls "refresh
everything" pays for everything. `identity_ui::refresh` takes a `Changed`:
a confirm re-reads the rail and the grid and *not* the coverage line,
because moving a face between people cannot alter how many images are
indexed. Before adding a read to a shared refresh, ask which events can
change its answer, and gate it on those.
**Count with `COUNT(*)`, never with `.len()` on a list you then drop.**
`repairs::counts` used to build every repair's work list — a `Target` with
its path per row, sorted into visiting order — to report its length. Six
repairs, 350 ms, nothing kept. If the caller wants a number, the query
returns a number.
**One query, not one per row.** `ThumbStore::contains` in a filter over
5,000 rows is 5,000 prepared statements; `ThumbStore::held(size)` reads the
index once into a set. The same applies to any `query_row` inside a loop
over a result set — including `deep_count` per sidebar row, which is fine
at sidebar scale and would not be at grid scale. Aggregate in one
statement and look up in memory.
**Filter and aggregate in SQL, and aggregate the small side first.**
`faces::people` read 19,000 rows, grouped, sorted them by name, and the
screen threw 17,000 away (empty unnamed groups). `people_in_use` filters in
the `WHERE`, and joins `people` to a pre-aggregated `face_person` (2,000
groups) rather than grouping after a `LEFT JOIN` over every person. The
sort then sees only the rows that will be drawn.
**Wide rows make "just check one column" a table scan.** A `faces` row is
~8 KB (a 1 KB embedding and a ~5 KB crop, then the columns added later).
Any predicate that reads `quality`, `crop` or an eye column for every face
reads every row. V17 learned this for the eye filter; V19 applies it to the
repair counts with partial indexes (`faces_owed_*`) that hold only the rows
still owing, keyed on what the predicate joins on and carrying `model_id`
because the predicate reads it. Two things to know about them:
- **Drive the count from the small side.** SQLite uses a partial index
when the query starts from `faces` (`repairs::count`, `Needs::Face`) and
ignores it inside a correlated `EXISTS (... WHERE f.image_id = i.id ...)`.
That is why `Needs::Face` carries the per-face fragment and spells it two
ways.
- **Spell the predicate as the index's `WHERE` is spelled.** `NEEDS_EYES`
is `(f.eye_right IS NULL OR f.landmarks_dense IS NULL)` because
`faces_owed_eyes` is `WHERE eye_right IS NULL OR landmarks_dense IS NULL`.
Change one, change both, and `counts_are_the_sizes_of_the_lists` will
tell you if they drift.
Check a query's plan with `EXPLAIN QUERY PLAN` against a copy of a real
catalog before trusting an index exists for it: "SEARCH ... USING COVERING
INDEX" is the answer you want, "SEARCH f USING INDEX faces_image" on a wide
table means every probe opens a row.
## Catalog writes: one transaction per user action
`faces::confirm` opens a transaction. Calling it in a loop over a group is
a commit per face; `faces::confirm_all` is two statements and one commit,
`faces::reassign` one transaction for a whole split. When a UI action
touches N rows, give the catalog a function that takes the N, not a loop
that calls the one-row function N times — `unchecked_transaction` cannot
nest, so this has to be designed in at the catalog layer, not wrapped
from above.
## Screens: keep what is already decoded
`identity::load_faces` takes the crops the grid is currently showing and
hands them back into the new cells. Before that, a click re-read 4 MB of
crop blobs and decoded 700 JPEGs to produce the pixels already on screen.
When a redraw replaces a model, the expensive parts of the old model — a
decoded image, a cut portrait — are the first thing to reuse; only the row
that changed needs new work. Drain the old cells rather than cloning them.
## Remote calls: one round trip per file, not one per ancestor
`NextcloudBackend::move_to` guaranteed its destination's parent with a
`MKCOL` per ancestor from the account root, on every file of a batch —
three `405`s before each `MOVE`. The backend now remembers the collections
it has confirmed (`known_dirs`) for its lifetime, which is one job. When a
per-file operation has a per-batch precondition, satisfy it once.
## Measuring
`cargo run --release -p dr-ui --example identity_bench -- CATALOG THUMBS`
times what one click on the Identity screen reads and what the batch
operations write. Run it against a **copy** of a real catalog (it writes),
never the library's own file; `sqlite3 catalog.sqlite ".backup copy.sqlite"`
takes a consistent one while the app runs. Compare the `cpu` column when
other builds are running on the machine — the wall clock doubles under
load, the CPU figure does not. Keep the binary from before the change and
run both back to back rather than trusting numbers taken an hour apart.
Reference figures from the 2026-09-19 fixes, largest person (754 faces),
24k images, 19k faces, before → after. What one click read: `load_people`
22 ms → 12 ms, `load_faces` 316 ms → 2.4 ms, `audit` 190 ms → not run
(66 ms when it is, on open and at the end of a sweep). What one click
wrote: `confirm_all` 16 ms → 2 ms, `split_off` 23 ms → 4.5 ms. A click on
the face grid went from ~530 ms of catalog work to ~15 ms.
Generated
+57 -25
View File
@@ -1221,7 +1221,7 @@ checksum = "f27ae1dd37df86211c42e150270f82743308803d90a6f6e6651cd730d5e1732f"
[[package]]
name = "darkroom-android"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"android_logger",
"dr-plat",
@@ -1234,7 +1234,7 @@ dependencies = [
[[package]]
name = "darkroom-desktop"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"anyhow",
"dr-plat",
@@ -1408,7 +1408,7 @@ checksum = "d8b14ccef22fc6f5a8f4d7d768562a182c04ce9a3b3157b91390b52ddfdf1a76"
[[package]]
name = "dr-bench"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"anyhow",
"dr-catalog",
@@ -1425,7 +1425,7 @@ dependencies = [
[[package]]
name = "dr-catalog"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-face",
"dr-plat",
@@ -1440,7 +1440,7 @@ dependencies = [
[[package]]
name = "dr-decode"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-types",
"env_logger",
@@ -1454,7 +1454,7 @@ dependencies = [
[[package]]
name = "dr-export"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-decode",
"dr-gpu",
@@ -1465,6 +1465,7 @@ dependencies = [
"log",
"png",
"pollster",
"rawler",
"thiserror 2.0.20",
"tiff",
"zune-jpeg 0.4.21",
@@ -1472,20 +1473,20 @@ dependencies = [
[[package]]
name = "dr-face"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-inference-engine",
"env_logger",
"log",
"ndarray",
"ort",
"ort-tract",
"thiserror 2.0.20",
"zune-jpeg 0.4.21",
]
[[package]]
name = "dr-film"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"log",
"serde",
@@ -1494,11 +1495,12 @@ dependencies = [
[[package]]
name = "dr-gpu"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"bytemuck",
"dr-decode",
"dr-film",
"dr-pano",
"dr-pipeline",
"dr-segment",
"dr-types",
@@ -1509,9 +1511,23 @@ dependencies = [
"wgpu",
]
[[package]]
name = "dr-inference-engine"
version = "0.13.5"
dependencies = [
"libloading",
"log",
"ort",
"ort-sys",
"ort-tract",
"serde",
"serde_json",
"thiserror 2.0.20",
]
[[package]]
name = "dr-ingest"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-plat",
"dr-types",
@@ -1523,15 +1539,29 @@ dependencies = [
[[package]]
name = "dr-lens"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"lensfun",
"log",
]
[[package]]
name = "dr-pano"
version = "0.13.5"
dependencies = [
"dr-decode",
"dr-inference-engine",
"dr-types",
"env_logger",
"log",
"ndarray",
"ort",
"thiserror 2.0.20",
]
[[package]]
name = "dr-pipeline"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-types",
"log",
@@ -1540,7 +1570,7 @@ dependencies = [
[[package]]
name = "dr-plat"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"android-native-keyring-store",
"dr-types",
@@ -1556,7 +1586,7 @@ dependencies = [
[[package]]
name = "dr-preset-xmp"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-pipeline",
"log",
@@ -1566,20 +1596,20 @@ dependencies = [
[[package]]
name = "dr-segment"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-inference-engine",
"env_logger",
"log",
"ndarray",
"ort",
"ort-tract",
"thiserror 2.0.20",
"zune-jpeg 0.4.21",
]
[[package]]
name = "dr-sync"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"async-trait",
"dr-plat",
@@ -1593,7 +1623,7 @@ dependencies = [
[[package]]
name = "dr-sync-folder"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"async-trait",
"dr-sync",
@@ -1605,7 +1635,7 @@ dependencies = [
[[package]]
name = "dr-sync-nextcloud"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"async-trait",
"dr-decode",
@@ -1627,7 +1657,7 @@ dependencies = [
[[package]]
name = "dr-thumbs"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-types",
"jpeg-encoder",
@@ -1639,7 +1669,7 @@ dependencies = [
[[package]]
name = "dr-types"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"serde",
"serde_json",
@@ -1648,7 +1678,7 @@ dependencies = [
[[package]]
name = "dr-ui"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"anyhow",
"async-trait",
@@ -1658,8 +1688,10 @@ dependencies = [
"dr-face",
"dr-film",
"dr-gpu",
"dr-inference-engine",
"dr-ingest",
"dr-lens",
"dr-pano",
"dr-pipeline",
"dr-plat",
"dr-preset-xmp",
@@ -1688,7 +1720,7 @@ dependencies = [
[[package]]
name = "dr-xmp"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"dr-types",
"log",
@@ -6989,7 +7021,7 @@ checksum = "8df9b6e13f2d32c91b9bd719c00d1958837bc7dec474d94952798cc8e69eeec3"
[[package]]
name = "traceability"
version = "0.12.1"
version = "0.13.5"
dependencies = [
"anyhow",
"serde",
+8 -1
View File
@@ -8,9 +8,11 @@ members = [
"core/dr-export",
"core/dr-face",
"core/dr-film",
"core/dr-inference-engine",
"core/dr-ingest",
"core/dr-gpu",
"core/dr-lens",
"core/dr-pano",
"core/dr-pipeline",
"core/dr-preset-xmp",
"core/dr-segment",
@@ -27,7 +29,7 @@ members = [
]
[workspace.package]
version = "0.12.1"
version = "0.13.5"
edition = "2021"
rust-version = "1.92"
license = "GPL-3.0-or-later"
@@ -45,9 +47,14 @@ dr-export = { path = "core/dr-export" }
# `features = ["inference"]`.
dr-face = { path = "core/dr-face", default-features = false }
dr-film = { path = "core/dr-film" }
# `tract` on by default so a test binary can open a session with nothing
# installed; the apps add `native` to look for a runtime file (docs/inference.md §3).
dr-inference-engine = { path = "core/dr-inference-engine" }
dr-ingest = { path = "core/dr-ingest" }
dr-gpu = { path = "core/dr-gpu" }
dr-lens = { path = "core/dr-lens" }
# Optional runtime, like `dr-segment`: the geometry never needs a model.
dr-pano = { path = "core/dr-pano", default-features = false }
dr-pipeline = { path = "core/dr-pipeline" }
dr-preset-xmp = { path = "core/dr-preset-xmp" }
# `default-features = false` belongs *here*, not on each dependant: a member
+109 -59
View File
@@ -1,84 +1,134 @@
# DarkRoom
A cross-platform, non-destructive RAW photo editor for Linux and Android.
A non-destructive RAW photo editor and library for Linux and Android, with a
GPU develop pipeline, a catalog that syncs between devices, and no account,
no telemetry and no cloud of its own.
**Status:** 0.9.0, and no longer a spike. A library opens, culls, develops and
exports on both platforms, across eight tagged releases. What is *not*
built is written down rather than merely absent — see
[docs/outstanding.md](docs/outstanding.md) for the requirements that have no
implementation and why, and [docs/technical-debt.md](docs/technical-debt.md)
for the compromises that were chosen.
[![The library: seventy frames, the timeline beside them, the filter bar above](docs/manual/media/library.png)](docs/manual/README.md)
## Documentation
**[The manual](docs/manual/README.md)** shows every feature, pictured from
the application itself. This page says what it is, how to get it, and what
is still missing.
| Document | Contents |
|---|---|
| [CONTRIBUTING.md](CONTRIBUTING.md) | How to land a first change without reading the rest |
| [requirements.md](docs/requirements.md) | What the software must do — 179 numbered requirements |
| [architecture.md](docs/architecture.md) | How it is built — crates, GPU pipeline, data model, sync |
| [technical-debt.md](docs/technical-debt.md) | Compromises taken deliberately, each with the condition that retires it |
| [outstanding.md](docs/outstanding.md) | What is not built, and whether that is a decision or a gap |
| [code-health.md](docs/code-health.md) | What a contribution costs, per seam, measured |
| [traceability.md](docs/traceability.md) | Generated: which requirement is claimed by which file |
| [faces.md](docs/faces.md) | Face detection and identity — the models, the licence problem, and what S14 measured |
## What it does
## Building
**A library.** Point it at a folder — on this machine, on a network mount,
or one a Nextcloud client keeps in virtual-files mode, where a placeholder
is treated as the photograph rather than as a one-byte file — or at a
Nextcloud account directly. The grid is virtualised, ordered by capture
time with a timeline beside it, and filtered by rating, flag, person and
whether the file is here. Ratings, keywords, collections and a
trash that survives a crash mid-operation. Card ingest. Bursts fold. Face
detection and identity, with the index syncing between devices.
Desktop:
**Developing.** Eighteen declared operations fused into one compute
dispatch, plus the neighbourhood work that cannot be: clarity, texture,
capture sharpening, noise reduction, lens correction, spectral film
simulation. Crop and straighten, spot repair, and local adjustments over
masks the model draws — click a subject or a category, then paint, subtract
a gradient, grow or shrink the edge. Focus peaking and a raw histogram for
judging what is recoverable. Named presets; XMP sidecars other editors read.
[![Segmenting an urban scene and choosing the sky as a mask](docs/manual/media/local-segment.png)](docs/manual/README.md#local-adjustments)
**Panoramas.** Select the frames, align, choose a projection, fill the
ragged border rather than crop it, and the composite lands beside its
sources as a DNG, with a sidecar recording what it was merged from.
[![Twelve hand-held frames aligned on a cylinder](docs/manual/media/panorama-aligned.png)](docs/manual/README.md#merging-a-panorama)
**Export.** JPEG, PNG, AVIF, JPEG XL, 8- and 16-bit TIFF, with resize, output
sharpening, a naming template and a colour space — to a folder here or back
into the library.
**On both platforms.** The same core runs on a desktop and a 12-inch
tablet; the interface is one layout, tuned for a wide viewport with touch
targets throughout. On desktop the develop view draws the compute pass's
texture directly — no readback between the GPU and the screen.
## Getting it
| Platform | How | State |
|---|---|---|
| Arch Linux | [`packaging/PKGBUILD`](packaging/PKGBUILD) — `makepkg -si` | Built from every release |
| Android | The APK from each CI run, or `./docker/android/package.sh --install` | Runs on a tablet; F-Droid not yet submitted |
| Windows | `DarkRoom-<version>-x86_64-setup.exe`, cross-built by CI ([windows.md](docs/windows.md)) | Verified under Wine only; unsigned |
| Flatpak | [`packaging/flatpak/`](packaging/flatpak/) | Manifest in tree; choosing a library does not yet work in the sandbox |
Or build it. Git LFS is required for the model weights, and the toolchain
pins itself to 1.92.0:
```bash
cargo run -p darkroom-desktop
git lfs install && git lfs pull
cargo run --release -p darkroom-desktop
```
Android (containerised toolchain, see [docker/android](docker/android/README.md)):
Android, through the containerised toolchain ([docker/android](docker/android/README.md)):
```bash
./docker/android/build.sh cargo ndk -t arm64-v8a build --release
```
Git LFS is required for the model weights, and the toolchain pins itself.
[CONTRIBUTING.md](CONTRIBUTING.md) has the details and the four commands CI
will run against what you send.
[CONTRIBUTING.md](CONTRIBUTING.md) has the system packages, the four
commands CI runs against what you send, and the shortest useful
contribution — a develop operation is one YAML file, and it arrives with its
controls, its place in the chain and its tests.
## Current state
## Where it stands
**Working.** A catalog over a local folder, a Nextcloud account, or a folder a
sync client keeps in virtual-files mode — where a placeholder is treated as the
photograph rather than as a one-byte file. A virtualised library grid with a
capture-time timeline, ratings, labels, keywords, collections and a trash that
survives a crash mid-operation. Card ingest. Face detection and identity, with
the index syncing between devices. A develop pipeline of fifteen declared
operations fused into a single compute dispatch, plus the neighbourhood
operations that cannot be — clarity, texture, capture sharpening, noise
reduction, lens correction, spectral film simulation. Crop, straighten, spot
removal, gradient and subject-segmentation masks, named presets, and a
generated panel that no operation in `ui/` is allowed to name. Export to JPEG,
PNG and 8- or 16-bit TIFF with resize and output sharpening.
**0.13.5**, nineteen tagged releases in. 184 numbered requirements in
scope, 84% of them claimed by code and [traced to it](docs/traceability.md);
the rest are written down rather than merely absent.
**The zero-copy display path works on desktop.** The compute pass writes a
texture that Slint composites directly, which is what
[ARCH §6.1](docs/architecture.md) requires; the readback it forbids costs 96%
of frame time at 4K, and
**Not built:** plugins (post-v1, [D12](docs/requirements.md)), compare and
survey culling, AI denoise, tiled and progressive rendering, HDR merge and
focus stacking, most of the Android platform integration beyond running,
and the Flatpak's library chooser. The performance targets are half
verified: the per-commit benchmark suite §8 requires exists for everything
that does not need a frame — the catalog, the scan, the thumbnails — and
not yet for the render path, so a regression there fails nothing.
[outstanding.md](docs/outstanding.md) is the list, with the reasoning for
each.
```bash
cargo run -p dr-gpu --example bench --features readback
```
**The one deliberate compromise worth knowing about before reading
anything else:** the Android develop view reads its frame back through the
CPU, because zero-copy there needs wgpu's Vulkan swapchain and that tears a
portrait window on a tablet whose panel is mounted landscape. It is debt,
not a revision of the rule — [technical-debt.md TD-1](docs/technical-debt.md)
has the measurements and the three things any one of which would remove it.
still reproduces that measurement. **The one exception is the Android develop
view**, which reads the frame back through the CPU because zero-copy there
needs wgpu's Vulkan swapchain, and that tears a portrait window on a tablet
whose panel is mounted landscape. It is debt, not a revision of the rule: the
reasoning, the on-device measurements that forced it, and the three separate
things any one of which would remove it are in
[technical-debt.md TD-1](docs/technical-debt.md).
## Documentation
**Not built.** Plugins, compare and survey culling, focus peaking, burst
grouping, AI denoise, tiled and progressive rendering, and most of the Android
platform integration beyond running. The performance targets in §4.1 are
unverified rather than unmet — the per-commit benchmark suite §8 requires does
not exist, so nothing fails a build on a regression.
[docs/outstanding.md](docs/outstanding.md) is the list, with the reasoning.
For someone using it:
| | |
|---|---|
| [manual](docs/manual/README.md) | Every feature, pictured |
| [gestures.md](docs/gestures.md) | How it is driven — generated from the code, so it cannot describe a gesture that does not exist |
For someone changing it:
| | |
|---|---|
| [CONTRIBUTING.md](CONTRIBUTING.md) | How to land a first change without reading the rest |
| [requirements.md](docs/requirements.md) | What the software must do — the numbered register, and the decisions |
| [architecture.md](docs/architecture.md) | How it is built — crates, the GPU pipeline, the data model, sync |
| [technical-debt.md](docs/technical-debt.md) | Compromises taken deliberately, each with the condition that retires it |
| [outstanding.md](docs/outstanding.md) | What is not built, and whether that is a decision or a gap |
| [code-health.md](docs/code-health.md) | What a contribution costs, per seam, measured |
| [traceability.md](docs/traceability.md) | Generated: which requirement is claimed by which file |
Designs, one per subsystem:
[segmentation](docs/segmentation.md) and [mask editing](docs/mask-editing.md) ·
[spot removal](docs/spot-removal.md) · [panorama](docs/panorama.md) ·
[faces](docs/faces.md) · [inference](docs/inference.md) ·
[storage and sync](docs/storage.md) · [catalog](docs/catalog.md) ·
[display and extension](docs/display-and-extension.md) ·
[navigation](docs/ui-navigation.md) · [distribution](docs/distribution.md) ·
[windows](docs/windows.md) · [benchmarks](docs/benchmarks.md).
## Licence
GPL-3.0-or-later.
GPL-3.0-or-later. The photographs in the manual and the test fixtures are
the author's and are there to show and test this project, nothing else.
The model weights carry their own licences — [models/LICENCE.md](models/LICENCE.md).
+47 -3
View File
@@ -324,17 +324,40 @@ fn unpack_bundled_models(app: &slint::android::AndroidApp) {
// (`FaceDetector`, docs/faces.md §12.3) and a tablet has no other way to
// obtain the one it was not shipped with. Twenty megabytes of APK for
// the choice; the embedder is the same for all three.
const BUNDLED: [(&std::ffi::CStr, &str); 7] = [
//
// Then the three eye-state models (docs/faces.md §17): landmarks, open
// or closed, sunglasses. The app indexes without them; with them the
// eyes-open filter has something to read, and a tablet has no other way
// to get them either.
//
// The int8 forms beside the three detectors are what the Hexagon runs
// (docs/inference.md §5); the engine loads the sibling when the probe
// chose that rung and ignores it otherwise.
const BUNDLED: [(&std::ffi::CStr, &str); 14] = [
(c"models/scrfd_500m_640.onnx", "scrfd_500m_640.onnx"),
(
c"models/scrfd_500m_640.int8.onnx",
"scrfd_500m_640.int8.onnx",
),
(c"models/scrfd_2.5g_640.onnx", "scrfd_2.5g_640.onnx"),
(
c"models/scrfd_2.5g_640.int8.onnx",
"scrfd_2.5g_640.int8.onnx",
),
(c"models/scrfd_10g_640.onnx", "scrfd_10g_640.onnx"),
(c"models/scrfd_10g_640.int8.onnx", "scrfd_10g_640.int8.onnx"),
(c"models/arcface_mbf_b1.onnx", "arcface_mbf_b1.onnx"),
(c"models/2d106det_b1.onnx", "2d106det_b1.onnx"),
(c"models/ocec_s_b1.onnx", "ocec_s_b1.onnx"),
(c"models/sgc_l_48_b1.onnx", "sgc_l_48_b1.onnx"),
(c"models/yolo26s-sem-ade20k.onnx", "yolo26s-sem-ade20k.onnx"),
(
c"models/yolo26s-sem-ade20k.classes.json",
"yolo26s-sem-ade20k.classes.json",
),
(c"models/categories.txt", "categories.txt"),
// The panorama border filler (FR-MRG-4); MIT, 28 MB.
(c"models/migan-512.onnx", "migan-512.onnx"),
];
let dir = dr_ui::shared_face_models_dir();
@@ -343,8 +366,8 @@ fn unpack_bundled_models(app: &slint::android::AndroidApp) {
for (asset_path, name) in BUNDLED {
let dest = dir.join(name);
// Already unpacked. Not re-read on every launch: this is 61 MB of
// copying across the seven entries, and the file does not change without
// Already unpacked. Not re-read on every launch: this is 73 MB of
// copying across the ten entries, and the file does not change without
// the APK changing, at which point the install wiped it anyway. It
// matters more now than it did — a launch that skips every entry here
// costs nothing at all, which is what makes the second launch after an
@@ -392,6 +415,27 @@ fn unpack_bundled_models(app: &slint::android::AndroidApp) {
"bundled models ready: {copied} bytes copied in {} ms",
started.elapsed().as_millis()
);
// Now, and not at launch: the probe fingerprints the model files, and
// on a first launch they were not on disk until this line. The runtime
// is in the APK's native library directory beside `libdarkroom.so`,
// which is also where Qualcomm's DSP loader has to be pointed for the
// Hexagon skel (docs/inference.md §3, §8).
dr_ui::inference::init(native_library_dir().into_iter().collect());
}
/// The directory the system unpacked this APK's native libraries into.
///
/// Read from where the loader put *this* library rather than asked of the
/// activity: `android-activity` does not expose `nativeLibraryDir`, and the
/// answer is in `/proc/self/maps` for free.
#[cfg(target_os = "android")]
fn native_library_dir() -> Option<std::path::PathBuf> {
let maps = std::fs::read_to_string("/proc/self/maps").ok()?;
maps.lines()
.filter_map(|l| l.split_whitespace().nth(5))
.find(|p| p.ends_with("/libdarkroom.so"))
.and_then(|p| std::path::Path::new(p).parent().map(Into::into))
}
/// TRACES: FR-PLAT-AND-6
+41
View File
@@ -61,6 +61,11 @@ fn main() -> anyhow::Result<()> {
eprintln!("usage: darkroom-desktop <file-or-directory>...");
}
// Before the window: the probe runs on its own thread and the first
// frame does not wait for it, but the models a background job asks for
// should already know where the runtime is (docs/inference.md §4).
dr_ui::inference::init(runtime_dirs());
dr_ui::run(paths)?;
// Skip Rust's normal static/thread-local teardown on the way out: a
@@ -70,3 +75,39 @@ fn main() -> anyhow::Result<()> {
// destruction" when the window is closed.
std::process::exit(0);
}
/// Where a desktop package may have put `libonnxruntime`, most specific
/// first. None of these existing is the tract build, which is a complete
/// application and not an error (docs/inference.md §3).
///
/// `DARKROOM_ORT_DIR` is for a developer pointing at a runtime that is not
/// installed — the wheel's `capi` directory, say. Then beside the executable
/// and in the package's private library directory, for a package that
/// bundles its own; then the user's own `runtime/` beside the models, where
/// `tools/fetch-desktop-runtime.sh` puts one; then the Flatpak prefix; then
/// the system library directory, for a distribution that ships ONNX Runtime
/// as a package of its own. The user's copy outranks the system's because
/// the system's is the one most likely to be built without the GPU
/// providers, or against the wrong cuDNN — and a system copy whose providers
/// do not load is not a problem, only a slower app: the probe builds a real
/// session before believing a provider.
fn runtime_dirs() -> Vec<PathBuf> {
let mut dirs = Vec::new();
if let Some(dir) = std::env::var_os("DARKROOM_ORT_DIR") {
dirs.push(PathBuf::from(dir));
}
if let Ok(exe) = std::env::current_exe() {
if let Some(bin) = exe.parent() {
dirs.push(bin.to_path_buf());
dirs.push(bin.join("../lib/darkroom"));
}
}
dirs.push(dr_ui::inference::user_runtime_dir());
#[cfg(target_os = "linux")]
dirs.extend([
PathBuf::from("/app/lib/darkroom"),
PathBuf::from("/usr/lib/darkroom"),
PathBuf::from("/usr/lib"),
]);
dirs
}
+284 -51
View File
@@ -48,9 +48,10 @@ pub const SHARD_MAX_BYTES: u64 = dr_thumbs::SHARD_MAX_BYTES;
/// Bytes one stored face occupies, near enough to bound a shard by.
///
/// Counted rather than measured: the embedding is fixed at 512 × f16, the
/// landmarks at 5 × 2 × f32, and the rest is a handful of numbers. Measuring
/// landmarks at 5 × 2 × f32 and the dense ones at 106 × 2 × u16, and the
/// rest is a handful of numbers. Measuring
/// the file after each insert would mean a `VACUUM` to get an honest answer.
const BYTES_PER_FACE: u64 = 1024 + 40 + 64;
const BYTES_PER_FACE: u64 = 1024 + 40 + 424 + 64;
/// Bytes a stored crop occupies, near enough to bound a shard by.
///
@@ -79,6 +80,11 @@ pub struct SharedFace {
/// See `faces::DetectedFace::quality`. `None` from a shard written before
/// the number was kept.
pub quality: Option<f32>,
/// See `faces::DetectedFace::eyes`. `None` from a peer without the eye
/// models, or a shard written before they existed.
pub eyes: Option<dr_face::EyeReading>,
/// See `faces::DetectedFace::landmarks_dense`; empty where none.
pub landmarks_dense: Vec<u8>,
/// The face cut out and encoded, or empty where none was kept.
///
/// Travels with the face rather than in the catalog snapshot, which is the
@@ -149,6 +155,29 @@ impl FaceShardStore {
.flatten()
}
/// The pipeline this store holds an image under, among those sharing
/// `model_id`'s embedder — the most recently indexed where a peer has
/// sent more than one.
///
/// What the import asks: not "has anyone run *this* detector over it" but
/// "does anyone hold comparable faces for it". See `faces::embedder_of`.
pub fn held_model(&self, file_id: u64, model_id: &str) -> Option<String> {
self.index
.query_row(
&format!(
"SELECT model_id FROM entries
WHERE file_id = ?1 AND {} = ?2
ORDER BY indexed_at DESC NULLS LAST, model_id",
crate::faces::embedder_sql("model_id")
),
rusqlite::params![file_id as i64, crate::faces::embedder_of(model_id)],
|r| r.get::<_, String>(0),
)
.optional()
.ok()
.flatten()
}
pub fn contains(&self, file_id: u64, model_id: &str) -> bool {
self.index
.query_row(
@@ -227,8 +256,12 @@ impl FaceShardStore {
tx.execute(
"INSERT INTO faces
(file_id, model_id, x, y, w, h, landmarks, confidence,
embedding, crop_px, crop, quality)
VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9, ?10, ?11, ?12)",
embedding, crop_px, crop, quality,
eye_right, eye_right_px, eye_right_sharp,
eye_left, eye_left_px, eye_left_sharp, sunglasses,
landmarks_dense)
VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9, ?10, ?11, ?12,
?13, ?14, ?15, ?16, ?17, ?18, ?19, ?20)",
rusqlite::params![
f.file_id as i64,
f.model_id,
@@ -242,6 +275,14 @@ impl FaceShardStore {
f.crop_px as f64,
(!f.crop.is_empty()).then_some(f.crop.as_slice()),
f.quality.map(f64::from),
f.eyes.map(|e| f64::from(e.right.open)),
f.eyes.map(|e| f64::from(e.right.px)),
f.eyes.map(|e| f64::from(e.right.sharpness)),
f.eyes.map(|e| f64::from(e.left.open)),
f.eyes.map(|e| f64::from(e.left.px)),
f.eyes.map(|e| f64::from(e.left.sharpness)),
f.eyes.map(|e| f64::from(e.sunglasses)),
(!f.landmarks_dense.is_empty()).then_some(f.landmarks_dense.as_slice()),
],
)?;
}
@@ -446,10 +487,16 @@ impl FaceShardStore {
}
let mut fq = src.prepare(&format!(
"SELECT f.file_id, f.model_id, f.x, f.y, f.w, f.h, f.landmarks,
f.confidence, f.embedding, f.crop_px, {}, {}
f.confidence, f.embedding, f.crop_px, {}, {}, {}, {}
FROM faces f WHERE f.file_id = ?1 AND f.model_id = ?2",
column_or_null(&src, "crop"),
column_or_null(&src, "quality"),
crate::schema::EYE_COLUMNS
.iter()
.map(|c| column_or_null(&src, c))
.collect::<Vec<_>>()
.join(", "),
column_or_null(&src, "landmarks_dense"),
))?;
let faces: Vec<SharedFace> = fq
.query_map(rusqlite::params![file_id, &model_id], read_shared_face)?
@@ -490,7 +537,8 @@ impl FaceShardStore {
let mut q = conn.prepare(
"SELECT file_id, model_id, x, y, w, h, landmarks, confidence, embedding, crop_px,
crop, quality
crop, quality, eye_right, eye_right_px, eye_right_sharp,
eye_left, eye_left_px, eye_left_sharp, sunglasses, landmarks_dense
FROM faces WHERE file_id = ?1 AND model_id = ?2",
)?;
let faces: Vec<SharedFace> = q
@@ -548,6 +596,14 @@ fn upgrade_shard(conn: &Connection) -> Result<(), CatalogError> {
("faces", "crop", "BLOB"),
("indexed", "indexed_at", "INTEGER"),
("faces", "quality", "REAL"),
("faces", "eye_right", "REAL"),
("faces", "eye_right_px", "REAL"),
("faces", "eye_right_sharp", "REAL"),
("faces", "eye_left", "REAL"),
("faces", "eye_left_px", "REAL"),
("faces", "eye_left_sharp", "REAL"),
("faces", "sunglasses", "REAL"),
("faces", "landmarks_dense", "BLOB"),
] {
if !has_column(conn, table, column)? {
conn.execute_batch(&format!("ALTER TABLE {table} ADD COLUMN {column} {decl}"))?;
@@ -571,7 +627,7 @@ fn has_column(conn: &Connection, table: &str, column: &str) -> Result<bool, Cata
///
/// `column` is one of this module's own names, never anything read from
/// outside, which is what makes formatting it into SQL acceptable.
fn column_or_null(conn: &Connection, column: &'static str) -> String {
fn column_or_null(conn: &Connection, column: &str) -> String {
match has_column(conn, "faces", column) {
Ok(true) => format!("f.{column}"),
_ => "NULL".to_string(),
@@ -608,16 +664,21 @@ pub fn export_to_shards_reporting(
model_id: &str,
progress: &mut dyn FnMut(usize, usize),
) -> Result<usize, CatalogError> {
let mut q = conn.prepare(
"SELECT r.file_id, fi.image_id, fi.source_edge, fi.indexed_at
// Every pipeline sharing this one's embedder, each image under the id
// that actually indexed it. A device that switched detectors still holds
// most of its library under the previous id, and those faces are exactly
// as comparable — and as wanted by a peer — as the new ones.
let mut q = conn.prepare(&format!(
"SELECT r.file_id, fi.image_id, fi.source_edge, fi.indexed_at, fi.model_id
FROM face_index fi
JOIN remote r ON r.image_id = fi.image_id
WHERE fi.model_id = ?1
WHERE {} = ?1
ORDER BY fi.image_id",
)?;
let rows: Vec<(i64, i64, i64, i64)> = q
.query_map([model_id], |r| {
Ok((r.get(0)?, r.get(1)?, r.get(2)?, r.get(3)?))
crate::faces::embedder_sql("fi.model_id")
))?;
let rows: Vec<(i64, i64, i64, i64, String)> = q
.query_map([crate::faces::embedder_of(model_id)], |r| {
Ok((r.get(0)?, r.get(1)?, r.get(2)?, r.get(3)?, r.get(4)?))
})?
.collect::<Result<_, _>>()?;
@@ -627,7 +688,8 @@ pub fn export_to_shards_reporting(
let total = rows.len();
let mut exported = 0;
for (seen, (file_id, image_id, edge, indexed_at)) in rows.into_iter().enumerate() {
for (seen, (file_id, image_id, edge, indexed_at, model_id)) in rows.into_iter().enumerate() {
let model_id = model_id.as_str();
if seen.is_multiple_of(REPORT_EVERY) {
progress(seen, total);
}
@@ -648,7 +710,8 @@ pub fn export_to_shards_reporting(
}
let mut fq = conn.prepare(
"SELECT x, y, w, h, landmarks, detector_confidence, embedding, crop_px, crop,
quality
quality, eye_right, eye_right_px, eye_right_sharp,
eye_left, eye_left_px, eye_left_sharp, sunglasses, landmarks_dense
FROM faces WHERE image_id = ?1 AND model_id = ?2",
)?;
let faces: Vec<SharedFace> = fq
@@ -666,6 +729,8 @@ pub fn export_to_shards_reporting(
crop_px: r.get::<_, f64>(7)? as f32,
crop: r.get::<_, Option<Vec<u8>>>(8)?.unwrap_or_default(),
quality: r.get::<_, Option<f64>>(9)?.map(|q| q as f32),
eyes: crate::faces::read_eyes(r, 10)?,
landmarks_dense: r.get::<_, Option<Vec<u8>>>(17)?.unwrap_or_default(),
})
})?
.collect::<Result<_, _>>()?;
@@ -689,10 +754,20 @@ pub fn export_to_shards_reporting(
/// adopted rather than re-detected, which is the difference between a new
/// device being useful in a minute and in two hours.
///
/// Skips any image this device has already indexed itself. Local work is not
/// second-guessed by a peer's — the two should agree, since the same model over
/// the same proxy is deterministic, but where they do not, the copy this device
/// computed is the one it can vouch for.
/// Skips any image this device has already indexed itself under this
/// pipeline or any sharing its embedder — unless the peer ran a detector that
/// outranks the one that indexed it here. Local work is not second-guessed
/// by a peer's equal: the two should agree, since the same model over the
/// same proxy is deterministic, and where they do not, the copy this device
/// computed is the one it can vouch for. A peer's *stronger* pass is another
/// matter: it is the re-detection this device's own sweep would queue
/// (`FaceDetector::supersedes`), already done, and taking it is what spares
/// a tablet the fetch. Names survive the replacement by box overlap and
/// embedding, as they do a local re-detection (`faces::record_detections`).
///
/// A peer's faces are taken under whichever compatible detector found them:
/// a tablet set to the fast detector adopts the desktop's thorough pass
/// rather than re-detecting it worse.
///
/// Returns how many images were adopted.
pub fn import_from_shards(
@@ -700,36 +775,67 @@ pub fn import_from_shards(
store: &FaceShardStore,
model_id: &str,
) -> Result<usize, CatalogError> {
use dr_types::FaceDetector;
// Only images this device actually has. A shard covers the whole account,
// and a device holding a subset of the library should take only its own
// part rather than accumulating faces for photographs it cannot show.
let mut q = conn.prepare(
"SELECT r.file_id, r.image_id
//
// With the pipeline that indexed each one here, or NULL: the marker is
// what decides whether a peer's copy is a gap filled or an upgrade.
let mut q = conn.prepare(&format!(
"SELECT r.file_id, r.image_id,
(SELECT fi.model_id FROM face_index fi
WHERE fi.image_id = r.image_id AND {} = ?1)
FROM remote r
JOIN images i ON i.id = r.image_id
WHERE i.trashed_at IS NULL
AND NOT EXISTS (
SELECT 1 FROM face_index fi
WHERE fi.image_id = r.image_id AND fi.model_id = ?1
)",
)?;
let candidates: Vec<(i64, i64)> = q
.query_map([model_id], |r| Ok((r.get(0)?, r.get(1)?)))?
WHERE i.trashed_at IS NULL",
crate::faces::embedder_sql("fi.model_id")
))?;
let candidates: Vec<(i64, i64, Option<String>)> = q
.query_map([crate::faces::embedder_of(model_id)], |r| {
Ok((r.get(0)?, r.get(1)?, r.get(2)?))
})?
.collect::<Result<_, _>>()?;
let mut adopted = 0;
for (file_id, image_id) in candidates {
let Some((faces, edge)) = store.get_image(file_id as u64, model_id)? else {
for (file_id, image_id, local) in candidates {
let Some(held) = store.held_model(file_id as u64, model_id) else {
continue;
};
// A peer that embedded before the quality was kept has done work this
// device cannot finish: the number exists only at embedding time, and
// adopting the faces would write the run marker that keeps them from
// ever being measured (schema V14). Left for this device's own pass —
// or for the peer's, whose re-export replaces these.
if faces.iter().any(|f| f.quality.is_none()) {
continue;
if let Some(local) = local {
// An unknown detector on either side cannot be ranked, and an
// unranked peer is treated as an equal: kept out.
let upgrade = match (
FaceDetector::for_model_id(&held),
FaceDetector::for_model_id(&local),
) {
(Some(theirs), Some(ours)) => theirs.outranks(ours),
_ => false,
};
if !upgrade {
continue;
}
}
let Some((faces, edge)) = store.get_image(file_id as u64, &held)? else {
continue;
};
// A face the peer embedded before its quality was kept (schema V14)
// is adopted with the reading missing, exactly as one without an eye
// reading is. The measuring passes find their work by the NULL
// column, not by the run marker (`dr_ui::repairs`, `faces_needing`),
// so adopting costs the reading nothing and this device's own pass
// fills it.
//
// This used to refuse such faces, on the reasoning that the marker
// would stop them ever being measured — true before the quality
// repair existed, and wrong after. What it cost: V14 had dropped the
// markers of every image holding such faces, so the peer never
// re-exported them, and the only copies in the shards were the
// unmeasured ones. A tablet holding shards with 4,310 of the
// desktop's images and 3,170 of its confirmations declined every one
// of them, showed a fraction of each person, and queued the whole
// library for a re-detection of its own instead.
let local: Vec<crate::faces::DetectedFace> = faces
.into_iter()
.map(|f| crate::faces::DetectedFace {
@@ -742,6 +848,8 @@ pub fn import_from_shards(
embedding: f.embedding,
crop_px: f.crop_px,
quality: f.quality,
eyes: f.eyes,
landmarks_dense: f.landmarks_dense,
model_id: f.model_id,
// A peer that indexed before crops existed sends none, and the
// reader falls back to the proxy exactly as it does for a face
@@ -753,7 +861,7 @@ pub fn import_from_shards(
crate::faces::record_detections(
conn,
dr_types::ImageId(image_id as u64),
model_id,
&held,
edge,
&local,
)?;
@@ -788,6 +896,8 @@ fn read_shared_face(r: &rusqlite::Row<'_>) -> rusqlite::Result<SharedFace> {
crop_px: r.get::<_, f64>(9)? as f32,
crop: r.get::<_, Option<Vec<u8>>>(10)?.unwrap_or_default(),
quality: r.get::<_, Option<f64>>(11)?.map(|q| q as f32),
eyes: crate::faces::read_eyes(r, 12)?,
landmarks_dense: r.get::<_, Option<Vec<u8>>>(19)?.unwrap_or_default(),
})
}
@@ -875,7 +985,20 @@ CREATE TABLE IF NOT EXISTS faces (
-- Length of the raw embedding (`faces::DetectedFace::quality`). NULL from
-- a build that did not keep it, and a face the receiving device will not
-- adopt -- see `import_from_shards`.
quality REAL
quality REAL,
-- The eye reading (`faces::DetectedFace::eyes`), all seven or none. NULL
-- from a peer without the eye models; adopted anyway, and read by the
-- receiving device's own measuring pass if it has them.
eye_right REAL,
eye_right_px REAL,
eye_right_sharp REAL,
eye_left REAL,
eye_left_px REAL,
eye_left_sharp REAL,
sunglasses REAL,
-- The dense landmarks behind the reading (`faces::DetectedFace::
-- landmarks_dense`), 424 bytes packed; NULL where none.
landmarks_dense BLOB
);
CREATE INDEX IF NOT EXISTS faces_file ON faces(file_id, model_id);
@@ -935,6 +1058,8 @@ mod tests {
embedding: vec![seed; 1024],
crop_px: 180.0,
quality: Some(17.5),
eyes: None,
landmarks_dense: Vec::new(),
crop: vec![seed; 64],
}
}
@@ -1144,6 +1269,8 @@ mod catalog_round_trip {
embedding: vec![seed; 1024],
crop_px: 180.0,
quality: Some(20.0),
eyes: None,
landmarks_dense: Vec::new(),
model_id: "w600k_mbf".into(),
crop: vec![seed; 64],
}
@@ -1197,11 +1324,55 @@ mod catalog_round_trip {
assert!(emb.iter().any(|e| e.embedding[0] == 1));
}
/// A face a peer embedded without measuring it is work this device
/// cannot finish, and adopting it would write the marker that stops it
/// ever being measured. The image stays outstanding instead.
/// The desktop switched to a stronger detector part-way through the
/// library, so its faces sit under two pipeline ids. A tablet on the
/// original detector must receive *all* of them — each under the id that
/// found it — and not re-detect the thorough half worse.
#[test]
fn a_peers_unmeasured_faces_are_left_for_this_device_to_index() {
fn every_generation_sharing_an_embedder_travels_and_is_adopted() {
let a = device(&[(1, 5001), (2, 5002)]);
let b = device(&[(90, 5001), (91, 5002)]);
faces::record_detections(&a, dr_types::ImageId(1), "w600k_mbf", 1024, &[detected(1)])
.unwrap();
let mut thorough = detected(2);
thorough.model_id = "scrfd_10g+w600k_mbf".into();
faces::record_detections(
&a,
dr_types::ImageId(2),
"scrfd_10g+w600k_mbf",
1024,
&[thorough],
)
.unwrap();
let mut store_a = FaceShardStore::open(&tempdir("a")).unwrap();
assert_eq!(
export_to_shards(&a, &mut store_a, "scrfd_10g+w600k_mbf").unwrap(),
2,
"the export left the earlier detector's images behind"
);
let mut store_b = FaceShardStore::open(&tempdir("b")).unwrap();
store_b.merge_shard(&store_a.shard_path(0)).unwrap();
assert_eq!(import_from_shards(&b, &store_b, "w600k_mbf").unwrap(), 2);
assert_eq!(faces::coverage(&b, "w600k_mbf").unwrap().outstanding(), 0);
let old = faces::for_image(&b, dr_types::ImageId(90)).unwrap();
let new = faces::for_image(&b, dr_types::ImageId(91)).unwrap();
assert_eq!(old[0].model_id, "w600k_mbf");
assert_eq!(
new[0].model_id, "scrfd_10g+w600k_mbf",
"adopted under the wrong id"
);
}
/// A face a peer embedded without measuring it is adopted all the same,
/// and left on this device's quality pass by its missing reading. Refusing
/// it was what stranded every confirmation the desktop had made on faces
/// from before V14: the tablet held the shards and would not use them.
#[test]
fn a_peers_unmeasured_faces_are_adopted_and_left_for_the_quality_pass() {
let b = device(&[(90, 5001), (91, 5002)]);
let mut store = FaceShardStore::open(&tempdir("unmeasured")).unwrap();
let shared = |file_id: u64, quality: Option<f32>| SharedFace {
@@ -1216,6 +1387,8 @@ mod catalog_round_trip {
embedding: vec![1; 1024],
crop_px: 180.0,
quality,
eyes: None,
landmarks_dense: Vec::new(),
crop: Vec::new(),
};
store
@@ -1225,13 +1398,18 @@ mod catalog_round_trip {
.put_image(5002, "w600k_mbf", 2560, &[shared(5002, Some(19.0))])
.unwrap();
assert_eq!(import_from_shards(&b, &store, "w600k_mbf").unwrap(), 1);
assert_eq!(import_from_shards(&b, &store, "w600k_mbf").unwrap(), 2);
let cov = faces::coverage(&b, "w600k_mbf").unwrap();
assert_eq!(cov.indexed, 1);
assert_eq!(cov.outstanding(), 1, "the unmeasured image was adopted");
assert!(faces::for_image(&b, dr_types::ImageId(90))
.unwrap()
.is_empty());
assert_eq!(cov.indexed, 2);
assert_eq!(cov.outstanding(), 0, "the unmeasured image was refused");
let got = faces::for_image(&b, dr_types::ImageId(90)).unwrap();
assert_eq!(got.len(), 1);
assert_eq!(got[0].quality, None, "a reading was invented");
// Still owed to the measuring pass, which lists by the column.
assert_eq!(
faces::count_needing(&b, "w600k_mbf", "f.quality IS NULL").unwrap(),
1
);
}
#[test]
@@ -1257,6 +1435,59 @@ mod catalog_round_trip {
assert_eq!(emb[0].embedding[0], 9, "B's own embedding was overwritten");
}
/// A peer's stronger detector is the re-detection this device would
/// otherwise queue for itself. Taking it saves the fetch; the name the
/// user confirmed here rides across on the box, as it would locally.
#[test]
fn a_peers_stronger_pass_replaces_a_weaker_local_one_and_keeps_the_name() {
let a = device(&[(1, 5001)]);
let b = device(&[(50, 5001)]);
let ids =
faces::record_detections(&b, dr_types::ImageId(50), "w600k_mbf", 1024, &[detected(9)])
.unwrap();
let anna = faces::create_person(&b, "Anna").unwrap();
faces::confirm(&b, ids[0], anna).unwrap();
let mut thorough = detected(7);
thorough.model_id = "scrfd_10g+w600k_mbf".into();
let mut second = detected(8);
second.model_id = "scrfd_10g+w600k_mbf".into();
second.x = 0.6;
faces::record_detections(
&a,
dr_types::ImageId(1),
"scrfd_10g+w600k_mbf",
1024,
&[thorough, second],
)
.unwrap();
let mut store = FaceShardStore::open(&tempdir("upgrade")).unwrap();
export_to_shards(&a, &mut store, "scrfd_10g+w600k_mbf").unwrap();
assert_eq!(import_from_shards(&b, &store, "w600k_mbf").unwrap(), 1);
let got = faces::for_image(&b, dr_types::ImageId(50)).unwrap();
assert_eq!(got.len(), 2, "the stronger pass was not adopted");
let named = got
.iter()
.find(|f| f.person == Some(anna))
.expect("the name was lost");
assert!(named.confirmed);
assert_eq!(named.model_id, "scrfd_10g+w600k_mbf");
// And never downwards: A on the fast detector keeps B's thorough faces.
let mut store_b = FaceShardStore::open(&tempdir("downgrade")).unwrap();
faces::record_detections(&b, dr_types::ImageId(50), "w600k_mbf", 1024, &[detected(9)])
.unwrap();
export_to_shards(&b, &mut store_b, "w600k_mbf").unwrap();
assert_eq!(
import_from_shards(&a, &store_b, "scrfd_10g+w600k_mbf").unwrap(),
0
);
assert_eq!(faces::for_image(&a, dr_types::ImageId(1)).unwrap().len(), 2);
}
/// A device holding a subset of the library takes only its own part.
#[test]
fn a_device_ignores_faces_for_photographs_it_does_not_have() {
@@ -1349,6 +1580,8 @@ mod catalog_round_trip {
embedding: vec![seed; 1024],
crop_px: 180.0,
quality: None,
eyes: None,
landmarks_dense: Vec::new(),
crop: vec![seed; 64],
}
}
+1141 -149
View File
File diff suppressed because it is too large Load Diff
+1 -1
View File
@@ -61,7 +61,7 @@ pub use collections::{Collection, CollectionKind, TreeRow};
pub use dedup::{seen_by_content, seen_by_metadata, set_content_hash};
pub use error::CatalogError;
pub use face_shard::{FaceShardStore, SharedFace};
pub use faces::{Calibration, DetectedFace, Face, FaceId, Measurement, Person, PersonId};
pub use faces::{Calibration, DetectedFace, Face, FaceId, FaceUpdate, Person, PersonId};
pub use jobs::{Job, JobKind, Priority};
pub use keywords::{Coverage, Keyword, KeywordId, SelectionKeyword};
pub use merge::MergeReport;
+59 -5
View File
@@ -991,9 +991,13 @@ fn remote_has_column(tx: &Connection, table: &str, column: &str) -> Result<bool,
/// Remote face row id to local face row id, by photograph and box overlap.
///
/// See [`merge_people_within`] for why a face has no shared identity and this
/// has to be derived. Only faces from the same model are compared: boxes from
/// two different detectors are not the same measurement, and matching across
/// them would attach a judgement to a face nobody looked at.
/// has to be derived. Faces are compared within an *embedder*
/// (`faces::embedder_of`), not within an exact pipeline id: two detectors in
/// front of the same embedder draw boxes around the same faces, and a
/// confirmation made on one device's box is about the face, not the
/// rectangle — the same judgement `faces::record_detections` makes when it
/// carries a confirmation across a re-detection. Keying on the exact id was
/// what let a detector change strand every name on the device that made it.
fn match_faces(tx: &Connection) -> Result<std::collections::HashMap<i64, i64>, CatalogError> {
/// Loose on purpose — "the same face in the frame", not "the same
/// rectangle". The figure `record_detections` uses for the same job.
@@ -1026,7 +1030,8 @@ fn match_faces(tx: &Connection) -> Result<std::collections::HashMap<i64, i64>, C
})?;
for row in rows {
let (file_id, model, boxed) = row?;
local.entry((file_id, model)).or_default().push(boxed);
let embedder = crate::faces::embedder_of(&model).to_string();
local.entry((file_id, embedder)).or_default().push(boxed);
}
}
if local.is_empty() {
@@ -1056,7 +1061,8 @@ fn match_faces(tx: &Connection) -> Result<std::collections::HashMap<i64, i64>, C
for row in rows {
let (remote_id, file_id, model, rbox) = row?;
let Some(candidates) = local.get(&(file_id, model)) else {
let embedder = crate::faces::embedder_of(&model).to_string();
let Some(candidates) = local.get(&(file_id, embedder)) else {
continue;
};
let best = candidates
@@ -1977,6 +1983,54 @@ mod tests {
assert_eq!(person_of(&c, local), Some(("Anna".to_string(), true)));
}
/// The bug this rule exists for: the desktop switched to a stronger
/// detector and confirmed 3,500 faces under the old pipeline id; the
/// tablet held the same faces under the new one, and not one name
/// crossed, because the match demanded the exact id. Same photograph,
/// same box, same embedder — that is the same face.
#[test]
fn a_confirmation_crosses_a_detector_change() {
let c = two_catalogs();
for db in ["main", "remote_cat"] {
add_synced_image(&c, db, 1, 5000);
}
let local = add_face(&c, "main", 7, 1, 0.30);
c.execute(
"UPDATE main.faces SET model_id = 'scrfd_10g+w600k_mbf' WHERE id = ?1",
[local],
)
.unwrap();
let remote = add_face(&c, "remote_cat", 42, 1, 0.31);
add_person(&c, "remote_cat", 3, "u-anna", "Anna", false);
assign(&c, "remote_cat", remote, 3, true);
let report = merge_all(&c).unwrap();
assert_eq!(report.faces_assigned, 1);
assert_eq!(person_of(&c, local), Some(("Anna".to_string(), true)));
}
/// A different embedder is a different space, and a box there is a face
/// nobody here has a vector for.
#[test]
fn a_confirmation_does_not_cross_an_embedder_change() {
let c = two_catalogs();
for db in ["main", "remote_cat"] {
add_synced_image(&c, db, 1, 5000);
}
let local = add_face(&c, "main", 7, 1, 0.30);
c.execute(
"UPDATE main.faces SET model_id = 'scrfd_10g+other_embedder' WHERE id = ?1",
[local],
)
.unwrap();
let remote = add_face(&c, "remote_cat", 42, 1, 0.31);
add_person(&c, "remote_cat", 3, "u-anna", "Anna", false);
assign(&c, "remote_cat", remote, 3, true);
merge_all(&c).unwrap();
assert_eq!(person_of(&c, local), None, "matched across embedders");
}
/// Boxes from two devices are close but not identical. Matching has to be
/// by overlap, not equality, or nothing ever lines up.
#[test]
+466 -12
View File
@@ -15,7 +15,7 @@ use rusqlite::Connection;
use crate::error::CatalogError;
/// Schema version this build writes and understands.
pub const SCHEMA_VERSION: i64 = 15;
pub const SCHEMA_VERSION: i64 = 20;
/// Apply migrations up to [`SCHEMA_VERSION`].
///
@@ -143,9 +143,157 @@ pub fn migrate(conn: &Connection) -> Result<i64, CatalogError> {
tx.commit()?;
}
if from < 16 {
let tx = conn.unchecked_transaction()?;
// Guarded like V14's column, and for the same reason: `ALTER TABLE
// ... ADD COLUMN` has no `IF NOT EXISTS`, and this step must be
// re-enterable (NFR-R5).
for column in EYE_COLUMNS {
let present: bool = tx
.prepare("SELECT 1 FROM pragma_table_info('faces') WHERE name = ?1")?
.exists([column])?;
if !present {
tx.execute_batch(&format!("ALTER TABLE faces ADD COLUMN {column} REAL;"))?;
}
}
tx.pragma_update(None, "user_version", 16)?;
tx.commit()?;
}
if from < 17 {
let tx = conn.unchecked_transaction()?;
tx.execute_batch(V17)?;
tx.pragma_update(None, "user_version", 17)?;
tx.commit()?;
}
if from < 18 {
let tx = conn.unchecked_transaction()?;
// Guarded like V14's and V16's columns: ALTER has no IF NOT EXISTS
// and the step must be re-enterable (NFR-R5).
let present: bool = tx
.prepare("SELECT 1 FROM pragma_table_info('faces') WHERE name = 'landmarks_dense'")?
.exists([])?;
if !present {
tx.execute_batch("ALTER TABLE faces ADD COLUMN landmarks_dense BLOB;")?;
}
tx.pragma_update(None, "user_version", 18)?;
tx.commit()?;
}
if from < 19 {
let tx = conn.unchecked_transaction()?;
tx.execute_batch(V19)?;
tx.pragma_update(None, "user_version", 19)?;
tx.commit()?;
}
if from < 20 {
let tx = conn.unchecked_transaction()?;
v20_markers_name_the_detector_that_found_the_faces(&tx)?;
tx.pragma_update(None, "user_version", 20)?;
tx.commit()?;
}
Ok(from)
}
// V20 -- TRACES: FR-CAT-7
//
// Run markers that named the wrong detector, put right.
//
// `faces::record_updates` -- the write behind the quality, eye and crop
// passes -- re-marked an image under the pipeline the pass ran as, while
// the faces it had updated kept the id of the detector that found them.
// A marker of `scrfd_10g+w600k_mbf` over faces spelled `w600k_mbf` reads,
// to every consumer, as the thorough detector having examined the image:
// the upgrade repair skips it, and `face_shard::export_to_shards` selects
// its faces by the marker's id, finds none, and tells every other device
// that the thorough detector found nothing there. The desktop's shard index
// held 54 such entries over photographs with named faces, and the tablet's
// eye pass over faces it had adopted from the desktop had made 430 more.
//
// The write is fixed to keep the marker under the faces' own id. This puts
// the markers already written right, with a fresh time so the export sends
// each image again under an entry newer than the empty one -- which is what
// `held_model` orders by. Where the right marker is still there beside the
// wrong one (the old write inserted rather than replaced), the wrong one
// goes and the right one is refreshed for the same reason: its entry in
// the shards is older than the empty one, and a device that has neither
// would take the empty one. An image V14 left with faces and no marker at
// all is not touched: that state is the quality pass's cue, and the fixed
// write marks it correctly when the pass reaches it.
//
// Restated in Rust rather than SQL because the embedder half of a pipeline
// id is `faces::embedder_sql`, which this must agree with.
fn v20_markers_name_the_detector_that_found_the_faces(tx: &Connection) -> Result<(), CatalogError> {
let fi = crate::faces::embedder_sql("face_index.model_id");
let f = crate::faces::embedder_sql("f.model_id");
// A marker is wrong when the image holds faces of its embedder under
// another id. First the wrong ones that sit beside a right one -- the
// update below would collide with it -- then the rest are renamed.
let wrong = format!(
"EXISTS (SELECT 1 FROM faces f
WHERE f.image_id = face_index.image_id
AND {f} = {fi}
AND f.model_id != face_index.model_id)"
);
let found_by = format!(
"(SELECT MIN(f.model_id) FROM faces f
WHERE f.image_id = face_index.image_id AND {f} = {fi})"
);
let now = crate::faces::now_secs();
tx.execute(
&format!(
"UPDATE face_index
SET indexed_at = ?1
WHERE model_id = {found_by}
AND EXISTS (SELECT 1 FROM face_index w
WHERE w.image_id = face_index.image_id
AND w.model_id != face_index.model_id
AND {} = {fi})",
crate::faces::embedder_sql("w.model_id")
),
[now],
)?;
tx.execute(
&format!(
"DELETE FROM face_index
WHERE {wrong}
AND EXISTS (SELECT 1 FROM face_index o
WHERE o.image_id = face_index.image_id
AND o.model_id = {found_by})"
),
[],
)?;
tx.execute(
&format!(
"UPDATE face_index
SET model_id = {found_by},
faces_found = (SELECT COUNT(*) FROM faces f
WHERE f.image_id = face_index.image_id AND {f} = {fi}),
indexed_at = ?1
WHERE {wrong}"
),
[now],
)?;
Ok(())
}
/// The seven columns V16 adds to `faces`, in the order the readers name them.
///
/// Named once because three places have to agree on them: this migration,
/// [`for_attached`], and the face shard's own catch-up (`face_shard`).
pub const EYE_COLUMNS: [&str; 7] = [
"eye_right",
"eye_right_px",
"eye_right_sharp",
"eye_left",
"eye_left_px",
"eye_left_sharp",
"sunglasses",
];
/// Recompute columns a migration added, for rows that predate it.
///
/// A migration adds a column with a default; it cannot know what the value
@@ -208,11 +356,38 @@ pub fn backfill(conn: &Connection) -> Result<Vec<(&'static str, usize)>, Catalog
Ok(out)
}
/// How long a connection waits for a writer to finish before giving up.
///
/// TRACES: NFR-R1
/// SQLite's default is **zero** — the loser of a race gets `SQLITE_BUSY` at
/// once rather than a turn — and WAL does not change that for two writers. One
/// writer and many readers is the case WAL makes free; this is the other one,
/// and this application has it constantly: the face sweep commits a batch while
/// reclustering reads, the derived sync imports shards while the sweep writes.
///
/// Without a timeout that contention was *lost work*, not a retry. A face
/// sweep that had already paid for the detection and the embedding — the
/// expensive part, seconds per image — threw the result away on
/// `storing faces for 214: database is locked` and moved on, and both the
/// desktop and the tablet logged runs of those on consecutive images.
///
/// Ten seconds, matching the figure the job runner's tests already use for the
/// same reason. It is far longer than any transaction here (a sweep batch is
/// sub-second; the slowest is a WAL checkpoint of a 130 MB catalog), so in
/// practice it is a bound on pathology rather than a wait anyone sits through.
/// The tension with NFR-P9 is real but one-sided: a query on the UI thread
/// would rather wait for its turn than fail, because the failure is what the
/// user sees as "cannot open catalog".
const BUSY_TIMEOUT: std::time::Duration = std::time::Duration::from_secs(10);
/// Connection setup applied on every open, migration or not.
///
/// WAL is required by NFR-R1: it survives power loss without corruption, and
/// it lets a background job write while the grid reads.
pub fn configure(conn: &Connection) -> Result<(), CatalogError> {
// Before the pragmas, so that a connection racing a migration waits for it
// rather than failing on the first statement it tries.
conn.busy_timeout(BUSY_TIMEOUT)?;
conn.pragma_update(None, "journal_mode", "WAL")?;
// NORMAL rather than FULL: with WAL this is durable across process death
// (which is what FR-PLAT-AND-3 cares about) and only risks the last
@@ -276,7 +451,15 @@ pub fn for_attached(schema_name: &str) -> String {
"{}\n{}\n{}\n\
ALTER TABLE {schema_name}.people ADD COLUMN ignored INTEGER NOT NULL DEFAULT 0;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN crop BLOB;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN quality REAL;",
ALTER TABLE {schema_name}.faces ADD COLUMN quality REAL;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN eye_right REAL;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN eye_right_px REAL;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN eye_right_sharp REAL;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN eye_left REAL;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN eye_left_px REAL;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN eye_left_sharp REAL;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN sunglasses REAL;\n\
ALTER TABLE {schema_name}.faces ADD COLUMN landmarks_dense BLOB;",
rewrite_for_attached(V1, schema_name),
rewrite_for_attached(V6, schema_name),
rewrite_for_attached(V8, schema_name),
@@ -614,20 +797,20 @@ const V14: &str = r#"
-- face this rule is not yet protecting anyone from, and the only way to
-- measure it is to embed it again.
--
-- The sweep's measuring pass is what does that: `dr_ui::library::
-- faces_unmeasured` lists every image holding a face with no reading, and
-- each face is embedded again from the native render with the landmarks it
-- already has, the raw vector written over the old one (`record_measurements`)
-- and nothing else touched -- not the id, not the box, not who the user said
-- it was. The faces keep drawing the People screen throughout.
-- The `face-quality` repair is what does that (`dr_ui::repairs`, once the
-- sweep's measuring pass): it lists every face with no reading, and each is
-- embedded again from the native render with the landmarks it already has,
-- the raw vector written over the old one (`record_updates`) and nothing
-- else touched -- not the id, not the box, not who the user said it was.
-- The faces keep drawing the People screen throughout.
--
-- The run markers of those images are forgotten too, exactly as V12 forgot
-- the runs made against too small a proxy. The build this shipped in had no
-- measuring pass yet, and a marker is the one thing that stops a face ever
-- being looked at again; with the pass in place `faces_unindexed` leaves
-- these images to it rather than detecting them from scratch, so the
-- deletion costs nothing -- and an image that was examined and found empty
-- keeps its marker, since there is nothing on it to measure.
-- being looked at again; with the repair in place, detection leaves an
-- image holding this embedder's faces to it rather than detecting from
-- scratch, so the deletion costs nothing -- and an image that was examined
-- and found empty keeps its marker, since there is nothing on it to measure.
--
-- The cost is a re-fetch of every image with a face on it, on the next pass
-- the user starts. That is a whole-library transfer (FR-NC-6), and it starts
@@ -679,6 +862,110 @@ CREATE TABLE IF NOT EXISTS xmp_conflicts (
);
"#;
// V19 -- TRACES: NFR-P9
//
// The indexes the repair counts are served from, and V17's lesson applied
// to the rest of the face columns.
//
// "How many images still owe a quality reading" was answered per image: a
// correlated EXISTS over `faces` that had to open each face's row to look
// at one nullable column -- the row being eight kilobytes of embedding and
// crop. Six such counts run every time the Identity screen opens and every
// time a sweep ends, 160 ms of them on the reference library. Three
// partial indexes hold only the faces still owing each pass, keyed by the
// image and carrying the model id the predicate also reads, so the count
// walks a few thousand index entries and touches no row at all -- and each
// index shrinks to nothing as its pass completes. The planner takes them
// when the count is driven from `faces` (`repairs::count`) and ignores
// them inside the per-image EXISTS, which is why that function has two
// spellings of the same predicate.
//
// `faces_image_model` replaces `faces_image`: the same key with the model
// id beside it, so "does this image hold this embedder's faces" -- asked in
// the audit, the proxy repair and the outstanding-detection count -- is an
// index-only probe where it used to read the row for the model id. Every
// lookup that used `faces_image` is served by its prefix.
//
// Not applied to attached catalogs, like V7 and V17: an index is a local
// concern, and a merge never runs these queries across an attachment.
const V19: &str = r#"
CREATE INDEX IF NOT EXISTS faces_image_model ON faces(image_id, model_id);
DROP INDEX IF EXISTS faces_image;
CREATE INDEX IF NOT EXISTS faces_owed_quality ON faces(image_id, model_id)
WHERE quality IS NULL;
CREATE INDEX IF NOT EXISTS faces_owed_crop ON faces(image_id, model_id)
WHERE crop IS NULL;
CREATE INDEX IF NOT EXISTS faces_owed_eyes ON faces(image_id, model_id)
WHERE eye_right IS NULL OR landmarks_dense IS NULL;
"#;
// V18 -- TRACES: FR-CULL-8a | FR-CULL-12
//
// The 106 dense landmarks the eye pass reads its eye boxes from, kept beside
// the reading as `dr_face::Landmarks::to_packed_bytes`: 106 x (x, y) as
// 16-bit fixed point over the frame, 424 bytes a face, a seventh of a
// pixel on a 6000-pixel frame. Derived data under FR-CULL-12 -- rebuilt by
// re-reading, never in a sidecar -- and stored for the same reason the
// embedding is: it cost a fetch of the original and a model run, and the
// next per-face pass (head pose, expression) should not have to pay either
// again. NULL where the face was never read.
//
// Added in `migrate`, guarded, like every ALTER here (NFR-R5).
const V17: &str = r#"
-- TRACES: FR-CULL-8a | FR-CULL-13 | NFR-P9
-- The eyes-open filter's index, and a lesson about where a column lands.
--
-- The people filter is a correlated EXISTS over `faces` per image, and it
-- was fast because `faces_image` *covers* it: the subquery never touched a
-- row. Reading V16's seven eye columns in the same subquery did touch the
-- row -- and `ALTER TABLE ADD COLUMN` puts a column at the end of the
-- record, after the 1 KB embedding and the ~5 KB crop, so every check
-- dragged six kilobytes off disk to reach seven floats. Measured on the
-- reference library: 24 seconds for one count, thirteen of them system
-- time. With this index the same count takes five milliseconds, because
-- the subquery is served from the index again and never reads a row.
--
-- The columns are listed in EYE_COLUMNS' order behind `image_id`, which is
-- the key the subquery searches on. Nothing else changed in V17; a catalog
-- already at V16 needs only this.
CREATE INDEX IF NOT EXISTS faces_eyes ON faces(
image_id, eye_right, eye_right_px, eye_right_sharp,
eye_left, eye_left_px, eye_left_sharp, sunglasses
);
"#;
// V16 -- TRACES: FR-CULL-8a
//
// What each face's eyes are doing: for each eye P(open), the source pixels
// across its box and the sharpness of the patch the classifier saw; and
// P(sunglasses) for the head. Seven numbers rather than a verdict, because
// the verdict is a rule with thresholds in it (dr_face::eyes::EyeReading::
// state) and a rule belongs in code that can be changed, not in rows that
// would have to be re-measured.
//
// The pixels and the sharpness are what stop a smear reading as a blink: an
// eye too small or too soft to read is not asked, and a face with no
// readable eye is "unclear", which no filter drops. Sunglasses are a column
// of their own for the same kind of reason — the eye classifier answers
// confidently over dark glass, and its answer means nothing there. A filter
// for "eyes open" reads all seven.
//
// NULL means "never measured" -- a face indexed before this version, or on a
// device without the eye models -- and a NULL is left alone by every filter
// that reads these, so an old library does not empty its grid the moment the
// chip is pressed. The sweep's measuring pass fills them in, from the native
// render, with the landmarks already stored: the same pass V14 built for the
// embedding's length, extended to ask the eye models too. No run marker is
// forgotten here, for the reason V14's note gives -- the measuring pass
// finds its own work by the NULL, and deleting markers would only put the
// detector back over images it has finished with.
//
// The columns are added in `migrate`, guarded, because ALTER has no IF NOT
// EXISTS and the step has to be re-enterable (NFR-R5). Their names are
// `EYE_COLUMNS`.
const V9: &str = r#"
-- TRACES: FR-CULL-8
-- A record that face detection has *run* on an image, distinct from what it
@@ -1148,6 +1435,60 @@ CREATE INDEX jobs_ready ON jobs(state, priority DESC, not_before);
#[cfg(test)]
mod tests {
#[test]
fn a_writer_waits_for_its_turn_rather_than_losing_its_work() {
// The failure this exists for: a face sweep that had already paid for
// the detection and the embedding threw the result away on
// "database is locked" and moved on. WAL does not help here — it makes
// one writer and many readers free, and this is two writers.
let dir = std::env::temp_dir().join(format!(
"dr-busy-{}-{:?}",
std::process::id(),
std::thread::current().id()
));
let _ = std::fs::remove_dir_all(&dir);
std::fs::create_dir_all(&dir).unwrap();
let path = dir.join("catalog.sqlite");
let held = rusqlite::Connection::open(&path).unwrap();
configure(&held).unwrap();
migrate(&held).unwrap();
let other = rusqlite::Connection::open(&path).unwrap();
configure(&other).unwrap();
// Every connection carries the timeout, which is what makes the wait
// below a wait rather than an immediate error.
let timeout: i64 = other
.query_row("PRAGMA busy_timeout", [], |r| r.get(0))
.unwrap();
assert_eq!(timeout, BUSY_TIMEOUT.as_millis() as i64);
// A writer holds the database; the other one must still get its turn
// once the first commits, rather than failing at the moment it asks.
let writing = held.unchecked_transaction().unwrap();
held.execute(
"INSERT INTO roots(id, kind, label) VALUES (1, 'local', 'lib')",
[],
)
.unwrap();
let handle = std::thread::spawn(move || {
other.execute(
"INSERT INTO roots(id, kind, label) VALUES (2, 'local', 'two')",
[],
)
});
std::thread::sleep(std::time::Duration::from_millis(150));
writing.commit().unwrap();
assert!(
handle.join().unwrap().is_ok(),
"the second writer waited and then wrote, rather than erroring"
);
let _ = std::fs::remove_dir_all(&dir);
}
use super::*;
fn mem() -> Connection {
@@ -1435,6 +1776,35 @@ mod tests {
assert_eq!(migrate(&c).unwrap(), SCHEMA_VERSION);
}
/// V16 adds its columns guarded, so a catalog whose version was rewound
/// after the columns landed — the rollback NFR-R5 contemplates — migrates
/// again rather than failing on "duplicate column".
#[test]
fn the_eye_columns_survive_a_rewound_version() {
let c = mem();
migrate(&c).unwrap();
for column in EYE_COLUMNS {
let present: bool = c
.prepare("SELECT 1 FROM pragma_table_info('faces') WHERE name = ?1")
.unwrap()
.exists([column])
.unwrap();
assert!(present, "{column} missing after migration");
}
c.pragma_update(None, "user_version", 15).unwrap();
assert_eq!(migrate(&c).unwrap(), 15);
let indexed: bool = c
.prepare("SELECT 1 FROM sqlite_master WHERE type = 'index' AND name = 'faces_eyes'")
.unwrap()
.exists([])
.unwrap();
assert!(indexed, "V17's covering index is there");
let v: i64 = c
.query_row("PRAGMA user_version", [], |r| r.get(0))
.unwrap();
assert_eq!(v, SCHEMA_VERSION);
}
#[test]
fn refuses_a_catalog_from_a_newer_build() {
let c = mem();
@@ -1573,6 +1943,90 @@ mod tests {
assert_eq!(faces, 2);
}
#[test]
fn v20_renames_markers_to_the_detector_that_found_the_faces() {
let c = mem();
c.pragma_update(None, "user_version", 0).unwrap();
migrate(&c).unwrap();
c.execute(
"INSERT INTO roots(id, kind, label) VALUES (1, 'local', 'test')",
[],
)
.unwrap();
c.execute(
"INSERT INTO images(id, root_id, source_ref, added_at)
VALUES (1,1,'a',0),(2,1,'b',0),(3,1,'c',0),(4,1,'d',0),(5,1,'e',0)",
[],
)
.unwrap();
// 1: the desktop's case -- old faces, re-marked as thorough.
// 2: the tablet's case -- adopted thorough faces, re-marked int8,
// and the right marker still beside it (refreshed, so it is
// exported again over the empty entry).
// 3: right already. 4: examined and empty. 5: V14's state, faces
// and no marker.
for (image, model) in [
(1, "scrfd_10g+w600k_mbf"),
(2, "scrfd_10g_i8+w600k_mbf"),
(2, "scrfd_10g+w600k_mbf"),
(3, "scrfd_10g+w600k_mbf"),
(4, "scrfd_10g+w600k_mbf"),
] {
c.execute(
"INSERT INTO face_index(image_id, model_id, indexed_at, faces_found, source_edge)
VALUES (?1, ?2, 100, 0, 6000)",
rusqlite::params![image, model],
)
.unwrap();
}
for (image, model) in [
(1, "w600k_mbf"),
(1, "w600k_mbf"),
(2, "scrfd_10g+w600k_mbf"),
(3, "scrfd_10g+w600k_mbf"),
(5, "w600k_mbf"),
] {
c.execute(
"INSERT INTO faces
(image_id, x, y, w, h, landmarks, detector_confidence, embedding,
crop_px, model_id, detected_at)
VALUES (?1, 0.1, 0.1, 0.2, 0.2, X'00', 0.9, X'00', 180.0, ?2, 0)",
rusqlite::params![image, model],
)
.unwrap();
}
c.pragma_update(None, "user_version", 19).unwrap();
migrate(&c).unwrap();
let markers: Vec<(i64, String, i64, bool)> = c
.prepare(
"SELECT image_id, model_id, faces_found, indexed_at > 100
FROM face_index ORDER BY image_id, model_id",
)
.unwrap()
.query_map([], |r| Ok((r.get(0)?, r.get(1)?, r.get(2)?, r.get(3)?)))
.unwrap()
.map(Result::unwrap)
.collect();
assert_eq!(
markers,
vec![
(1, "w600k_mbf".to_string(), 2, true),
(2, "scrfd_10g+w600k_mbf".to_string(), 0, true),
(3, "scrfd_10g+w600k_mbf".to_string(), 0, false),
(4, "scrfd_10g+w600k_mbf".to_string(), 0, false),
]
);
// Re-enterable: nothing left to rename.
c.pragma_update(None, "user_version", 19).unwrap();
migrate(&c).unwrap();
let n: i64 = c
.query_row("SELECT count(*) FROM face_index", [], |r| r.get(0))
.unwrap();
assert_eq!(n, 4);
}
#[test]
fn job_uniqueness_coalesces_rather_than_duplicating() {
let c = mem();
+221
View File
@@ -0,0 +1,221 @@
//! TRACES: S15 | FR-MRG-3
//! Spike S15.1 — does rawler read back a linear DNG this application writes?
//!
//! cargo run -p dr-decode --example linear_dng [-- <out.dng>]
//!
//! Decides FR-MRG-3's container. A panorama composite is three linear samples
//! per pixel with a camera matrix attached, which is exactly what a
//! `LinearRaw` DNG is; if rawler parses one, the composite re-enters the
//! library as `Format::Dng` and the only new decode work is a `cpp == 3`
//! branch. If it does not, the container is a float TIFF with a decode path
//! of its own.
//!
//! The file is hand-rolled rather than written with the `tiff` crate, whose
//! encoder fixes `PhotometricInterpretation` to RGB and cannot say
//! `LinearRaw`. Eighty lines of IFD is the cheaper thing to own than a fork.
use rawler::rawsource::RawSource;
const W: u32 = 64;
const H: u32 = 48;
fn main() {
let bytes = write_linear_dng(W, H);
if let Some(path) = std::env::args().nth(1) {
std::fs::write(&path, &bytes).expect("write");
println!("wrote {path} ({} bytes)", bytes.len());
}
let source = RawSource::new_from_slice(&bytes);
let decoder = match rawler::get_decoder(&source) {
Ok(d) => d,
Err(e) => {
println!("FAIL get_decoder: {e}");
std::process::exit(1);
}
};
println!("ok decoder found");
let image = match decoder.raw_image(&source, &Default::default(), false) {
Ok(i) => i,
Err(e) => {
println!("FAIL raw_image: {e}");
std::process::exit(1);
}
};
println!(
"ok raw_image: {}×{}, cpp {}, bps {}, {} samples, make {:?} model {:?}",
image.width,
image.height,
image.cpp,
image.bps,
match &image.data {
rawler::RawImageData::Integer(v) => v.len(),
rawler::RawImageData::Float(v) => v.len(),
},
image.make,
image.model
);
println!(
" white {:?} black {:?} wb {:?}",
image.whitelevel.0,
image
.blacklevel
.levels
.iter()
.map(|r| r.n as f32 / r.d.max(1) as f32)
.collect::<Vec<_>>(),
image.wb_coeffs
);
// The pixel at (1, 0) was written as (1000, 2000, 3000): if the samples
// come back interleaved in that order, cpp == 3 means what it says.
if let rawler::RawImageData::Integer(v) = &image.data {
let i = image.cpp;
println!(" pixel (1,0) = {:?}", &v[i..i + image.cpp.min(3)]);
}
// What dr-decode itself makes of it: the colour matrix rawler parsed into
// the camera definition, and the profile the decoder would build from it.
println!(" rawler color_matrix: {:?}", image.camera.color_matrix);
let dng = dr_decode::profile::read_dng_matrices(decoder.as_ref());
let profile = dr_decode::CameraProfile::extract(&image, &dng);
println!(
" CameraProfile: {}",
profile
.as_ref()
.map(|p| format!("xyz_to_cam {:?}", p.xyz_to_cam()))
.unwrap_or_else(|| "none".into())
);
match dr_decode::decode(&bytes) {
Ok(r) => println!(
"note dr_decode::decode accepted it as CFA: {}×{}, {} samples — the cpp==3 branch is the work",
r.width,
r.height,
r.data.len()
),
Err(e) => println!("note dr_decode::decode refused it: {e} — the cpp==3 branch is the work"),
}
}
/// A minimal `LinearRaw` DNG: one IFD, uncompressed 16-bit RGB, the tags a
/// decoder needs to treat it as a DNG and the matrix a develop chain needs
/// to treat it as a camera. Little-endian, one strip.
fn write_linear_dng(w: u32, h: u32) -> Vec<u8> {
// Pixels first, so their offset is known: a ramp with one marker pixel.
let mut pixels: Vec<u16> = Vec::with_capacity((w * h * 3) as usize);
for y in 0..h {
for x in 0..w {
if (x, y) == (1, 0) {
pixels.extend([1000, 2000, 3000]);
} else {
let v = ((x + y) * 512).min(65535) as u16;
pixels.extend([v, v / 2, v / 3]);
}
}
}
let pixel_bytes: Vec<u8> = pixels.iter().flat_map(|v| v.to_le_bytes()).collect();
// Layout: header (8) | pixels | extra data | IFD.
let pixels_off = 8u32;
let extra_off = pixels_off + pixel_bytes.len() as u32;
// Values that do not fit in four bytes go in `extra`, and the entry
// points at them.
let mut extra: Vec<u8> = Vec::new();
let mut entries: Vec<(u16, u16, u32, [u8; 4])> = Vec::new();
fn short(tag: u16, v: u16) -> (u16, u16, u32, [u8; 4]) {
let mut b = [0u8; 4];
b[..2].copy_from_slice(&v.to_le_bytes());
(tag, 3, 1, b)
}
fn long(tag: u16, v: u32) -> (u16, u16, u32, [u8; 4]) {
(tag, 4, 1, v.to_le_bytes())
}
fn ascii(extra: &mut Vec<u8>, extra_off: u32, tag: u16, s: &str) -> (u16, u16, u32, [u8; 4]) {
let mut bytes = s.as_bytes().to_vec();
bytes.push(0);
let off = extra_off + extra.len() as u32;
extra.extend(&bytes);
(tag, 2, bytes.len() as u32, off.to_le_bytes())
}
entries.push(long(254, 0)); // NewSubfileType: main image
entries.push(long(256, w));
entries.push(long(257, h));
// BitsPerSample ×3 — three shorts, six bytes, so out of line.
{
let off = extra_off + extra.len() as u32;
for _ in 0..3 {
extra.extend(16u16.to_le_bytes());
}
entries.push((258, 3, 3, off.to_le_bytes()));
}
entries.push(short(259, 1)); // Compression: none
entries.push(short(262, 34892)); // PhotometricInterpretation: LinearRaw
entries.push(ascii(&mut extra, extra_off, 271, "DarkRoom"));
entries.push(ascii(&mut extra, extra_off, 272, "Panorama"));
entries.push(long(273, pixels_off)); // StripOffsets
entries.push(short(274, 1)); // Orientation
entries.push(short(277, 3)); // SamplesPerPixel
entries.push(long(278, h)); // RowsPerStrip
entries.push(long(279, pixel_bytes.len() as u32)); // StripByteCounts
entries.push(short(284, 1)); // PlanarConfiguration: chunky
entries.push((50706, 1, 4, [1, 4, 0, 0])); // DNGVersion
entries.push((50707, 1, 4, [1, 4, 0, 0])); // DNGBackwardVersion
entries.push(ascii(&mut extra, extra_off, 50708, "DarkRoom Panorama")); // UniqueCameraModel
entries.push(long(50717, 65535)); // WhiteLevel
// ColorMatrix1: XYZ → camera, 9 SRATIONALs. A plausible sRGB-ish matrix
// (the inverse of the sRGB D65 primaries), scaled to integers.
{
let m: [(i32, i32); 9] = [
(32406, 10000),
(-15372, 10000),
(-4986, 10000),
(-9689, 10000),
(18758, 10000),
(415, 10000),
(557, 10000),
(-2040, 10000),
(10570, 10000),
];
let off = extra_off + extra.len() as u32;
for (n, d) in m {
extra.extend(n.to_le_bytes());
extra.extend(d.to_le_bytes());
}
entries.push((50721, 10, 9, off.to_le_bytes()));
}
// AsShotNeutral: 3 RATIONALs, neutral.
{
let off = extra_off + extra.len() as u32;
for _ in 0..3 {
extra.extend(1u32.to_le_bytes());
extra.extend(1u32.to_le_bytes());
}
entries.push((50728, 5, 3, off.to_le_bytes()));
}
entries.push(short(50778, 21)); // CalibrationIlluminant1: D65
entries.sort_by_key(|e| e.0);
let ifd_off = extra_off + extra.len() as u32;
let mut out = Vec::new();
out.extend(b"II");
out.extend(42u16.to_le_bytes());
out.extend(ifd_off.to_le_bytes());
out.extend(&pixel_bytes);
out.extend(&extra);
out.extend((entries.len() as u16).to_le_bytes());
for (tag, ty, count, value) in &entries {
out.extend(tag.to_le_bytes());
out.extend(ty.to_le_bytes());
out.extend(count.to_le_bytes());
out.extend(value);
}
out.extend(0u32.to_le_bytes()); // no next IFD
out
}
+60
View File
@@ -25,6 +25,42 @@ pub enum DecodeError {
CorruptPreview(String),
}
/// Run a decoder call, and return a panic inside it as an error.
///
/// TRACES: FR-RAW-4 | NFR-SEC-1 | NFR-R3
/// rawler `panic!`s on some malformed input rather than returning `Err` — a
/// DNG whose IFD claims a >50000 px image, for one, which is in the reference
/// library. A panic on a worker thread ends the thread: the face sweep that
/// met that file stopped 13 seconds in, three sweeps running, with "17301
/// image(s) to index" as the last word and nothing to say why. FR-RAW-4's
/// rule — a malformed file must not abort a batch — is this crate's to keep
/// whatever the library beneath it does, so every entry point that calls into
/// rawler runs through here, and a file that panics the decoder is one failed
/// file like any other.
///
/// The crash hook still records the panic, because it runs before unwinding
/// reaches this frame; that is right — it is a real defect in a dependency
/// and the record is how it gets reported upstream — and a repeat is the same
/// file being met again rather than a new fault.
pub(crate) fn guarded<T>(
what: &'static str,
f: impl FnOnce() -> Result<T, DecodeError>,
) -> Result<T, DecodeError> {
match std::panic::catch_unwind(std::panic::AssertUnwindSafe(f)) {
Ok(result) => result,
Err(payload) => {
let msg = payload
.downcast_ref::<&str>()
.map(|s| s.to_string())
.or_else(|| payload.downcast_ref::<String>().cloned())
.unwrap_or_else(|| "no message".to_string());
Err(DecodeError::Decode(format!(
"{what}: the decoder panicked on this file: {msg}"
)))
}
}
}
impl DecodeError {
/// Whether a fallback path might still produce an image.
///
@@ -49,4 +85,28 @@ mod tests {
// A genuinely unsupported file has nowhere to fall through to.
assert!(!DecodeError::Unsupported("unknown".into()).has_fallback());
}
#[test]
fn a_panic_in_the_decoder_is_an_error_and_the_thread_survives() {
// The property the face sweep relies on: one file that panics rawler
// is one failed file, not the end of the pass. The message travels,
// because "decode failed" alone sends the reader to the crash log.
let err = guarded("decode", || -> Result<(), DecodeError> {
panic!("rawler: surely there's no such thing as a {}MP image!", 600)
})
.unwrap_err();
let text = err.to_string();
assert!(text.contains("panicked"), "{text}");
assert!(text.contains("600MP"), "{text}");
assert!(!err.has_fallback(), "a panic is not a missing preview");
}
#[test]
fn a_result_passes_through_untouched() {
assert_eq!(guarded("decode", || Ok::<_, DecodeError>(7)).unwrap(), 7);
assert!(matches!(
guarded("decode", || Err::<(), _>(DecodeError::NoPreview)),
Err(DecodeError::NoPreview)
));
}
}
+63
View File
@@ -134,6 +134,22 @@ pub struct RawImage {
pub base_curve: BaseCurve,
/// The usable region of `data`, excluding masked and border photosites.
pub crop: CropRect,
/// TRACES: FR-MRG-3
/// Samples per photosite in `data`: 1 for a colour-filter-array capture,
/// 3 for a *linear* DNG — demosaiced RGB, still camera-space, which is
/// what a merge writes. With 3, `cfa_pattern` means nothing, `data` is
/// `width × height × 3` interleaved, and the GPU uploads it as it is
/// rather than demosaicing.
pub samples_per_pixel: u8,
/// TRACES: FR-MRG-3
/// The body's colour profile as the file carried it, for a composite to
/// carry on: calibrations and the as-shot neutral. `None` for a body the
/// decoder has no matrix for.
pub profile: Option<profile::CameraProfile>,
/// The body, as rawler cleans the names: what `Make`/`Model` say and what
/// the base-curve database matches on.
pub make: String,
pub model: String,
}
/// TRACES: FR-RAW-3
@@ -285,6 +301,30 @@ pub fn probe(header: &[u8]) -> Option<Format> {
/// TRACES: FR-CAT-5 | M-12
/// Read capture metadata without decoding sensor data.
pub fn metadata(bytes: &[u8]) -> Result<Metadata, DecodeError> {
error::guarded("metadata", || metadata_unguarded(bytes))
}
/// TRACES: FR-CAT-5
/// Where a TIFF-shaped file keeps its first IFD, when the head handed to
/// [`metadata`] does not reach it — the linear DNG a merge writes puts its
/// IFDs after the pixels, and rawler, given the head alone, finds no
/// decoder in it. The caller fetches from this offset to the end and
/// reads the two ranges with [`metadata_split`].
pub fn trailing_ifd(head: &[u8]) -> Option<u64> {
locate::trailing_ifd(head)
}
/// TRACES: FR-CAT-5
/// [`metadata`] for a file read in two ranges: `head` from offset 0 and
/// `tail` from `tail_at`. The EXIF sub-IFD such a file wrote before its
/// pixels is in the head; the first IFD and its values are in the tail.
pub fn metadata_split(head: &[u8], tail: &[u8], tail_at: u64) -> Result<Metadata, DecodeError> {
error::guarded("metadata", || {
locate::tiff_metadata_split(head, tail, tail_at)
})
}
fn metadata_unguarded(bytes: &[u8]) -> Result<Metadata, DecodeError> {
use rawler::rawsource::RawSource;
// rawler has no decoder for a plain JPEG, so without this every JPEG in a
@@ -510,6 +550,10 @@ pub(crate) fn parse_exif_offset(s: &str) -> Option<i32> {
/// Only develop and export should call it; culling and the grid must not
/// (FR-CULL-1).
pub fn decode(bytes: &[u8]) -> Result<RawImage, DecodeError> {
error::guarded("decode", || decode_unguarded(bytes))
}
fn decode_unguarded(bytes: &[u8]) -> Result<RawImage, DecodeError> {
use rawler::rawsource::RawSource;
let source = RawSource::new_from_slice(bytes);
@@ -551,6 +595,21 @@ pub fn decode(bytes: &[u8]) -> Result<RawImage, DecodeError> {
image.camera.clean_model.as_str(),
);
// TRACES: FR-MRG-3
// A linear DNG — three samples per pixel, no colour filter array — is a
// composite this application wrote (or any other demosaiced DNG). It
// carries the same scale, matrices and neutral as a CFA file and goes
// through the same profile; only the demosaic is skipped.
let samples_per_pixel = match image.cpp {
1 => 1u8,
3 => 3,
other => {
return Err(DecodeError::Unsupported(format!(
"{other} samples per pixel; only CFA (1) and linear RGB (3) are handled"
)))
}
};
let data = match image.data {
rawler::RawImageData::Integer(v) => v,
rawler::RawImageData::Float(v) => {
@@ -619,6 +678,10 @@ pub fn decode(bytes: &[u8]) -> Result<RawImage, DecodeError> {
wb_coeffs,
color_matrix,
base_curve,
samples_per_pixel,
profile,
make: image.camera.clean_make.clone(),
model: image.camera.clean_model.clone(),
})
}
+82 -13
View File
@@ -183,22 +183,65 @@ struct Entry {
value: u32,
}
/// The bytes a [`TiffReader`] reads: the head of a file, and optionally a
/// second range from further in, at a known offset.
///
/// A camera writes its IFDs at the front, so the first 256 KB of a file
/// is the whole structure. A file written strip by strip — the linear
/// DNG a merge produces — has its first IFD at the *end*, after the
/// pixels, and a reader that only has the head sees a pointer into
/// nothing. Rather than fetch 800 MB to read a date, the caller fetches
/// the head, asks [`crate::trailing_ifd`] where the IFD is, fetches that
/// tail, and reads through both. Offsets are the file's own throughout;
/// a read that falls in neither range is simply absent.
#[derive(Clone, Copy)]
struct Src<'a> {
head: &'a [u8],
tail: &'a [u8],
/// Where `tail` starts in the file.
tail_at: usize,
}
impl<'a> Src<'a> {
fn whole(data: &'a [u8]) -> Self {
Src {
head: data,
tail: &[],
tail_at: 0,
}
}
fn get(&self, start: usize, len: usize) -> Option<&'a [u8]> {
let end = start.checked_add(len)?;
if let Some(b) = self.head.get(start..end) {
return Some(b);
}
let s = start.checked_sub(self.tail_at)?;
self.tail.get(s..s.checked_add(len)?)
}
}
/// A minimal TIFF structure reader.
///
/// Deliberately not a general TIFF parser: it reads the IFD chain and entry
/// values and nothing else, because that is all locating a preview needs.
struct TiffReader<'a> {
data: &'a [u8],
data: Src<'a>,
little_endian: bool,
first_ifd: u32,
}
impl<'a> TiffReader<'a> {
fn new(data: &'a [u8]) -> Option<Self> {
if data.len() < 8 {
Self::over(Src::whole(data))
}
fn over(data: Src<'a>) -> Option<Self> {
let head = data.head;
if head.len() < 8 {
return None;
}
let little_endian = match &data[0..2] {
let little_endian = match &head[0..2] {
b"II" => true,
b"MM" => false,
_ => return None,
@@ -362,9 +405,7 @@ impl<'a> TiffReader<'a> {
};
raw[..len.min(4)].to_vec()
} else {
self.data
.get(e.value as usize..e.value as usize + len)?
.to_vec()
self.data.get(e.value as usize, len)?.to_vec()
};
let s = String::from_utf8_lossy(&bytes);
@@ -396,8 +437,7 @@ impl<'a> TiffReader<'a> {
// same way to recover the original byte order.
return None;
}
let start = e.value as usize;
self.data.get(start..start.checked_add(len)?)
self.data.get(e.value as usize, len)
}
fn offsets(&self, e: &Entry) -> Vec<u32> {
@@ -420,8 +460,8 @@ impl<'a> TiffReader<'a> {
}
}
fn read_u16(data: &[u8], at: usize, le: bool) -> Option<u16> {
let b = data.get(at..at + 2)?;
fn read_u16(data: Src<'_>, at: usize, le: bool) -> Option<u16> {
let b = data.get(at, 2)?;
Some(if le {
u16::from_le_bytes([b[0], b[1]])
} else {
@@ -429,8 +469,8 @@ fn read_u16(data: &[u8], at: usize, le: bool) -> Option<u16> {
})
}
fn read_u32(data: &[u8], at: usize, le: bool) -> Option<u32> {
let b = data.get(at..at + 4)?;
fn read_u32(data: Src<'_>, at: usize, le: bool) -> Option<u32> {
let b = data.get(at, 4)?;
Some(if le {
u32::from_le_bytes([b[0], b[1], b[2], b[3]])
} else {
@@ -460,7 +500,36 @@ pub fn jpeg_metadata(bytes: &[u8]) -> Result<crate::Metadata, crate::DecodeError
/// no `DateTimeOriginal` for some DNGs whose tag sits plainly at byte 826 —
/// and without this fallback those images are silently undated.
pub fn tiff_metadata(tiff_data: &[u8]) -> Result<crate::Metadata, crate::DecodeError> {
let reader = TiffReader::new(tiff_data)
tiff_metadata_over(Src::whole(tiff_data))
}
/// Where a TIFF-shaped file's first IFD is, when the head does not reach
/// it: the offset to fetch from, so [`tiff_metadata_split`] can read it.
/// `None` for a file that is not TIFF, or whose IFD the head already holds.
pub fn trailing_ifd(head: &[u8]) -> Option<u64> {
let r = TiffReader::new(head)?;
let at = r.first_ifd as u64;
(at >= head.len() as u64).then_some(at)
}
/// [`tiff_metadata`] over a head and a tail fetched separately: the head
/// from offset 0, the tail from `tail_at`. For the file whose IFDs follow
/// its pixels.
pub fn tiff_metadata_split(
head: &[u8],
tail: &[u8],
tail_at: u64,
) -> Result<crate::Metadata, crate::DecodeError> {
tiff_metadata_over(Src {
head,
tail,
tail_at: usize::try_from(tail_at)
.map_err(|_| crate::DecodeError::Metadata("tail offset out of range".into()))?,
})
}
fn tiff_metadata_over(src: Src<'_>) -> Result<crate::Metadata, crate::DecodeError> {
let reader = TiffReader::over(src)
.ok_or_else(|| crate::DecodeError::Metadata("malformed EXIF header".into()))?;
let mut md = crate::Metadata::default();
+4
View File
@@ -158,6 +158,10 @@ pub enum PreviewSize {
/// Returns [`DecodeError::NoPreview`] where there is none at all: a
/// fall-through signal, not a failure (see [`DecodeError::has_fallback`]).
pub fn extract_preview(bytes: &[u8], size: PreviewSize) -> Result<Preview, DecodeError> {
crate::error::guarded("preview", || extract_preview_unguarded(bytes, size))
}
fn extract_preview_unguarded(bytes: &[u8], size: PreviewSize) -> Result<Preview, DecodeError> {
use rawler::rawsource::RawSource;
// A plain JPEG *is* its own preview — rawler has no decoder for one, and
+48
View File
@@ -392,6 +392,21 @@ impl CameraProfile {
}
/// The calibrations this profile was built from, coolest first.
/// TRACES: FR-MRG-3
/// The calibrations as a DNG carries them: `(CalibrationIlluminant,
/// ColorMatrix)` with the EXIF light-source code, for a composite to
/// write the profile of the body that took its sources.
///
/// The code is recovered from the temperature, which is lossy only for
/// illuminants this profile never kept: `extract` drops calibrations
/// whose illuminant has no temperature, so every one here maps back.
pub fn dng_calibrations(&self) -> Vec<(u16, [[f32; 3]; 3])> {
self.calibrations
.iter()
.map(|c| (illuminant_code(c.temperature), c.xyz_to_cam))
.collect()
}
pub fn calibrations(&self) -> &[Calibration] {
&self.calibrations
}
@@ -528,6 +543,39 @@ fn illuminant_temperature(illuminant: Illuminant) -> Option<f32> {
})
}
/// The EXIF `LightSource` code for a calibration temperature — the inverse
/// of [`illuminant_temperature`], on the temperatures it produces.
fn illuminant_code(temperature: f32) -> u16 {
// Nearest of the table, so a temperature that came through a float
// round-trip still lands on its illuminant. Where two illuminants share
// a temperature (D55 and Daylight, D65 and Cloudy, D75 and Shade) the
// CIE standard one is written: it is what every profile database means.
const TABLE: &[(f32, u16)] = &[
(2856.0, 17), // A
(3200.0, 24), // ISO studio tungsten
(3500.0, 15), // white fluorescent
(4150.0, 14), // cool white fluorescent
(4230.0, 2), // fluorescent
(4874.0, 18), // B
(5000.0, 13), // daylight white fluorescent
(5003.0, 23), // D50
(5503.0, 20), // D55
(6430.0, 12), // daylight fluorescent
(6504.0, 21), // D65
(6774.0, 19), // C
(7504.0, 22), // D75
];
TABLE
.iter()
.min_by(|a, b| {
(a.0 - temperature)
.abs()
.total_cmp(&(b.0 - temperature).abs())
})
.map(|(_, code)| *code)
.unwrap_or(255)
}
/// Compose a forward matrix into camera RGB → linear sRGB.
///
/// `forward` takes white-balanced camera RGB to XYZ under D50, which is the
+3
View File
@@ -38,4 +38,7 @@ dr-gpu.workspace = true
dr-pipeline.workspace = true
env_logger.workspace = true
pollster.workspace = true
# The DNG writer's test reads its output back through the decoder the
# library uses, which is the whole claim the writer makes (S15.1).
rawler.workspace = true
zune-jpeg.workspace = true
+351
View File
@@ -0,0 +1,351 @@
//! TRACES: FR-MRG-3
//! A linear DNG: the container a merge writes its composite into.
//!
//! Decided by S15.1 (2026-09-19): rawler reads back a `LinearRaw` DNG the
//! application writes, so a composite re-enters the library as
//! `Format::Dng` through the decoder every camera DNG uses. What is written
//! is a RAW in every sense a warp can preserve — camera-linear `u16`
//! samples at the first source's own scale, its matrices, illuminants,
//! as-shot neutral and body name — so the panorama is developed afterwards
//! as one photograph, from the sensor's numbers.
//!
//! # Streamed, not buffered
//!
//! The composite is larger than any single photograph the pipeline renders
//! and larger than the tablet's memory (FR-MRG-11), so the writer never
//! holds it. Strips are pulled from the caller one at a time through a
//! closure, in order, and written as they arrive; the caller renders a band
//! of chunks, hands over its rows, and moves on.
//!
//! # Why the `tiff` crate after all
//!
//! S15.1's spike hand-rolled its IFD because the crate's encoder fixes
//! `PhotometricInterpretation` to RGB when the image is opened. It does — but
//! a directory is a map and a later `write_tag` on the same tag replaces the
//! earlier, so `LinearRaw` goes in over the top and everything else the
//! crate does (strips, offsets, sub-IFDs, the EXIF block `encode.rs` already
//! knows how to write) is kept.
use std::io::{Seek, Write};
use tiff::encoder::{colortype, DirectoryEncoder, SRational, TiffEncoder, TiffKind, TiffValue};
use tiff::tags::Tag;
use crate::encode::{sub_directories, tag_metadata, Ascii, Rationals};
use crate::{ExportError, SourceMetadata};
/// What the DNG says about the camera that "took" the composite: the first
/// source's profile, carried across so the composite develops through it.
#[derive(Debug, Clone, PartialEq)]
pub struct DngProfile {
/// `UniqueCameraModel`, the name the profile database matches on.
pub unique_model: String,
/// `(CalibrationIlluminant, ColorMatrix)`: the EXIF light-source code and
/// the XYZ → camera matrix measured under it. One or two.
pub calibrations: Vec<(u16, [[f32; 3]; 3])>,
/// `AsShotNeutral`, camera RGB of the scene's white.
pub as_shot_neutral: [f32; 3],
/// `WhiteLevel`: the sample value that is clipping. The first source's
/// white minus its black, since the samples are black-subtracted.
pub white_level: u32,
}
/// Write a linear DNG, pulling `rows_per_strip`-row strips from `strips`.
///
/// Each call to `strips` receives the strip index and a buffer to fill with
/// `width × rows × 3` interleaved RGB `u16` samples (the last strip may be
/// shorter). `source` supplies the `Make`, `Model`, dates and EXIF block
/// exactly as an export does (FR-EXP-8 sanitising already applied by the
/// caller).
///
/// `PhotometricInterpretation = LinearRaw`, `DNGVersion 1.4`, uncompressed,
/// `Orientation = 1` — the composite is written upright (panorama.md §8).
///
/// `crop` is asked once every strip is in, and its answer — the largest
/// rectangle the frames covered, found while the strips went by
/// (`Inscribed`) — becomes `DefaultCropOrigin`/`DefaultCropSize`
/// (FR-MRG-4): the file opens on the picture, and the border is still in it.
// Eight arguments, and each is a different thing: the sink, three
// dimensions, the profile, the header, the strip source and the crop. A
// struct for them would be a struct with one caller.
#[allow(clippy::too_many_arguments)]
pub fn write_linear_dng<W, F, C>(
out: W,
width: u32,
height: u32,
rows_per_strip: u32,
profile: &DngProfile,
source: Option<&SourceMetadata>,
mut strips: F,
crop: C,
) -> Result<(), ExportError>
where
W: Write + Seek,
F: FnMut(usize, &mut Vec<u16>) -> Result<(), ExportError>,
C: FnOnce() -> Option<crate::Rect>,
{
let enc = |e: tiff::TiffError| ExportError::Encode(e.to_string());
let mut encoder = TiffEncoder::new(out).map_err(enc)?;
let sub = sub_directories(&mut encoder, source, width, height)?;
let mut image = encoder
.new_image::<colortype::RGB16>(width, height)
.map_err(enc)?;
image.rows_per_strip(rows_per_strip.max(1)).map_err(enc)?;
tag_metadata(image.encoder(), source, &sub)?;
tag_dng(image.encoder(), profile).map_err(enc)?;
let rows = rows_per_strip.max(1);
let strip_count = height.div_ceil(rows) as usize;
let mut buf: Vec<u16> = Vec::with_capacity((width * rows * 3) as usize);
for k in 0..strip_count {
buf.clear();
strips(k, &mut buf)?;
let expected_rows = rows.min(height - k as u32 * rows);
let expected = (width * expected_rows * 3) as usize;
if buf.len() != expected {
return Err(ExportError::Encode(format!(
"strip {k} has {} samples, expected {expected}",
buf.len()
)));
}
image.write_strip(&buf).map_err(enc)?;
}
if let Some(r) = crop().filter(|r| r.width > 0 && r.height > 0) {
let r = crate::Rect {
x: r.x.min(width - 1),
y: r.y.min(height - 1),
width: r.width.min(width - r.x.min(width - 1)),
height: r.height.min(height - r.y.min(height - 1)),
};
image
.encoder()
.write_tag(Tag::Unknown(tag::DEFAULT_CROP_ORIGIN), &[r.x, r.y][..])
.map_err(enc)?;
image
.encoder()
.write_tag(
Tag::Unknown(tag::DEFAULT_CROP_SIZE),
&[r.width, r.height][..],
)
.map_err(enc)?;
}
image.finish().map_err(enc)
}
/// The tags that make a TIFF a DNG, and a linear one.
fn tag_dng<W, K>(dir: &mut DirectoryEncoder<'_, W, K>, profile: &DngProfile) -> tiff::TiffResult<()>
where
W: Write + Seek,
K: TiffKind,
{
// Over the top of what `new_image` wrote: this is the whole trick.
dir.write_tag(Tag::PhotometricInterpretation, LINEAR_RAW)?;
dir.write_tag(Tag::Orientation, 1u16)?;
dir.write_tag(Tag::Unknown(tag::DNG_VERSION), &[1u8, 4, 0, 0][..])?;
dir.write_tag(Tag::Unknown(tag::DNG_BACKWARD_VERSION), &[1u8, 4, 0, 0][..])?;
dir.write_tag(
Tag::Unknown(tag::UNIQUE_CAMERA_MODEL),
Ascii(&profile.unique_model),
)?;
dir.write_tag(
Tag::Unknown(tag::WHITE_LEVEL),
&[profile.white_level; 3][..],
)?;
dir.write_tag(Tag::Unknown(tag::BLACK_LEVEL), &[0u32; 3][..])?;
for (slot, (illuminant, matrix)) in profile.calibrations.iter().take(2).enumerate() {
let (ill_tag, mat_tag) = if slot == 0 {
(tag::CALIBRATION_ILLUMINANT_1, tag::COLOR_MATRIX_1)
} else {
(tag::CALIBRATION_ILLUMINANT_2, tag::COLOR_MATRIX_2)
};
dir.write_tag(Tag::Unknown(ill_tag), *illuminant)?;
let flat: Vec<SRational> = matrix
.iter()
.flatten()
.map(|&v| SRational {
n: (v * 10_000.0).round() as i32,
d: 10_000,
})
.collect();
dir.write_tag(Tag::Unknown(mat_tag), SRationals(&flat))?;
}
let neutral: Vec<(u32, u32)> = profile
.as_shot_neutral
.iter()
.map(|&v| ((v.max(0.0) * 1_000_000.0).round() as u32, 1_000_000))
.collect();
dir.write_tag(Tag::Unknown(tag::AS_SHOT_NEUTRAL), Rationals(&neutral))?;
Ok(())
}
/// `PhotometricInterpretation` for demosaiced, un-rendered sensor data.
const LINEAR_RAW: u16 = 34892;
/// DNG tag numbers the `tiff` crate has no names for.
mod tag {
pub const DNG_VERSION: u16 = 50706;
pub const DNG_BACKWARD_VERSION: u16 = 50707;
pub const UNIQUE_CAMERA_MODEL: u16 = 50708;
pub const BLACK_LEVEL: u16 = 50714;
pub const WHITE_LEVEL: u16 = 50717;
pub const DEFAULT_CROP_ORIGIN: u16 = 50719;
pub const DEFAULT_CROP_SIZE: u16 = 50720;
pub const COLOR_MATRIX_1: u16 = 50721;
pub const COLOR_MATRIX_2: u16 = 50722;
pub const AS_SHOT_NEUTRAL: u16 = 50728;
pub const CALIBRATION_ILLUMINANT_1: u16 = 50778;
pub const CALIBRATION_ILLUMINANT_2: u16 = 50779;
}
/// A run of `SRATIONAL`s, as `encode::Rationals` is for `RATIONAL`.
struct SRationals<'a>(&'a [SRational]);
impl TiffValue for SRationals<'_> {
const BYTE_LEN: u8 = 8;
const FIELD_TYPE: tiff::tags::Type = tiff::tags::Type::SRATIONAL;
fn count(&self) -> usize {
self.0.len()
}
fn data(&self) -> std::borrow::Cow<'_, [u8]> {
let mut out = Vec::with_capacity(self.0.len() * 8);
for r in self.0 {
out.extend_from_slice(&r.n.to_ne_bytes());
out.extend_from_slice(&r.d.to_ne_bytes());
}
std::borrow::Cow::Owned(out)
}
}
#[cfg(test)]
mod tests {
use super::*;
fn profile() -> DngProfile {
DngProfile {
unique_model: "Canon EOS 6D".into(),
calibrations: vec![
(17, [[0.8, -0.2, 0.1], [-0.3, 1.1, 0.2], [0.0, -0.1, 0.9]]),
(21, [[0.7, -0.1, 0.0], [-0.2, 1.0, 0.1], [0.0, -0.2, 0.8]]),
],
as_shot_neutral: [0.5, 1.0, 0.6],
white_level: 13_023,
}
}
fn write(width: u32, height: u32, rows: u32) -> Vec<u8> {
let mut bytes = std::io::Cursor::new(Vec::new());
let source = SourceMetadata {
make: Some("Canon".into()),
model: Some("Canon EOS 6D".into()),
captured_at: Some(1_754_398_664),
captured_offset: Some(120),
..Default::default()
};
write_linear_dng(
&mut bytes,
width,
height,
rows,
&profile(),
Some(&source),
|k, buf| {
let first = k as u32 * rows;
let n = rows.min(height - first);
for y in first..first + n {
for x in 0..width {
buf.extend([(x + y * width) as u16, 1000, 2000]);
}
}
Ok(())
},
|| {
Some(crate::Rect {
x: 2,
y: 1,
width: 15,
height: 10,
})
},
)
.expect("written");
bytes.into_inner()
}
#[test]
fn rawler_reads_it_back_as_linear_raw() {
let bytes = write(20, 13, 4);
let source = rawler::rawsource::RawSource::new_from_slice(&bytes);
let decoder = rawler::get_decoder(&source).expect("a DNG");
let image = decoder
.raw_image(&source, &Default::default(), false)
.expect("decodes");
assert_eq!((image.width, image.height, image.cpp), (20, 13, 3));
assert_eq!(image.whitelevel.0[0], 13_023);
// Pixel (3, 2) is (3 + 2·20, 1000, 2000) — samples in order, strips
// joined without a seam.
let rawler::RawImageData::Integer(data) = &image.data else {
panic!("integer samples")
};
let i = (2 * 20 + 3) * 3;
assert_eq!(&data[i..i + 3], &[43, 1000, 2000]);
// Last row, from the short final strip.
let i = (12 * 20 + 19) * 3;
assert_eq!(data[i], (19 + 12 * 20) as u16);
// The profile came through as the camera's.
assert!(!image.camera.color_matrix.is_empty());
assert_eq!(image.model, "Canon EOS 6D");
// The default crop is what the decoder reports as the picture.
let crop = image.crop_area.expect("a crop");
assert_eq!((crop.p.x, crop.p.y, crop.d.w, crop.d.h), (2, 1, 15, 10));
}
#[test]
fn the_catalog_reads_the_date_from_a_head_and_a_tail() {
// TRACES: FR-CAT-5
// The IFDs follow the pixels, so a scan that has the first bytes of
// the file has a pointer into nothing; rawler finds no decoder in
// that, and the composite would sit undated at the end of the grid.
// The scan's second range — from the first IFD to the end — with
// the head is enough to date it, and to name the camera.
let bytes = write(640, 400, 64);
let head = &bytes[..4096];
assert!(
dr_decode::metadata(head).is_err(),
"the head alone must not read"
);
let at = dr_decode::trailing_ifd(head).expect("the IFD is beyond the head");
assert!(at as usize > head.len());
let tail = &bytes[at as usize..];
assert!(tail.len() < 4096, "the tail is the IFD, not the pixels");
let md = dr_decode::metadata_split(head, tail, at).expect("read from two ranges");
assert_eq!(md.captured_at, Some(1_754_398_664));
assert_eq!(md.captured_offset, Some(120));
assert_eq!(md.model.as_deref(), Some("Canon EOS 6D"));
// A head that holds everything is not a trailing-IFD file.
assert_eq!(dr_decode::trailing_ifd(&bytes), None);
}
#[test]
fn a_strip_of_the_wrong_length_is_refused() {
let mut bytes = std::io::Cursor::new(Vec::new());
let err = write_linear_dng(
&mut bytes,
8,
8,
8,
&profile(),
None,
|_, buf| {
buf.extend([0u16; 10]);
Ok(())
},
|| None,
)
.unwrap_err();
assert!(matches!(err, ExportError::Encode(_)));
}
}
+5 -5
View File
@@ -213,7 +213,7 @@ impl tiff::encoder::TiffValue for Undefined<'_> {
/// specification says, `dr-decode` reads them back with `from_utf8_lossy`, and
/// a mangled accent is a far better outcome than a refusal. So the bytes go
/// through verbatim with the terminating NUL the type requires.
struct Ascii<'a>(&'a str);
pub(crate) struct Ascii<'a>(pub(crate) &'a str);
impl tiff::encoder::TiffValue for Ascii<'_> {
const BYTE_LEN: u8 = 1;
@@ -241,7 +241,7 @@ impl tiff::encoder::TiffValue for Ascii<'_> {
/// a value that forced little-endian would be read back byte-swapped on a
/// big-endian machine. `exif.rs` builds its own header and so chooses its own
/// order; here the container has already chosen.
struct Rationals<'a>(&'a [(u32, u32)]);
pub(crate) struct Rationals<'a>(pub(crate) &'a [(u32, u32)]);
impl tiff::encoder::TiffValue for Rationals<'_> {
const BYTE_LEN: u8 = 8;
@@ -317,7 +317,7 @@ where
/// and then no pointer is written either, so the file has no trace of the
/// directory rather than a pointer to an empty one.
#[derive(Default)]
struct SubDirectories {
pub(crate) struct SubDirectories {
exif: Option<u32>,
gps: Option<u32>,
}
@@ -335,7 +335,7 @@ struct SubDirectories {
/// A TIFF gets no separate EXIF *block* — no APP1, no `eXIf` chunk. Its own
/// directory is the EXIF structure, and adding a second copy inside it would
/// give a reader two answers to every question.
fn sub_directories<W>(
pub(crate) fn sub_directories<W>(
encoder: &mut tiff::encoder::TiffEncoder<W>,
source: Option<&SourceMetadata>,
width: u32,
@@ -465,7 +465,7 @@ where
///
/// No `Orientation`, for the reason `exif.rs` gives at length: the pixels
/// arriving here are already upright.
fn tag_metadata<W, K>(
pub(crate) fn tag_metadata<W, K>(
dir: &mut tiff::encoder::DirectoryEncoder<'_, W, K>,
source: Option<&SourceMetadata>,
sub: &SubDirectories,
+156
View File
@@ -0,0 +1,156 @@
//! TRACES: FR-MRG-4
//! The largest rectangle inside a coverage mask, found a row at a time.
//!
//! A merged panorama has ragged edges: the frames' footprints under a
//! cylinder or a sphere are not rectangles, and the composite carries a
//! black border where none of them reached. FR-MRG-4 asks for an auto-crop
//! to the largest inscribed rectangle. This finds it as the bands are
//! produced, so the composite is never held to be measured (FR-MRG-11):
//! each row extends a running histogram of consecutive covered rows above
//! it, and the largest rectangle ending on that row is the largest
//! rectangle under the histogram — a stack pass, linear in the width.
//!
//! The crop is written as the DNG's `DefaultCropOrigin`/`DefaultCropSize`,
//! which every reader honours and which discards nothing: the pixels
//! outside it are still in the file for a photographer who wants them.
/// The rectangle so far, in pixels from the top left.
#[derive(Debug, Clone, Copy, PartialEq, Eq, Default)]
pub struct Rect {
pub x: u32,
pub y: u32,
pub width: u32,
pub height: u32,
}
impl Rect {
pub fn area(&self) -> u64 {
u64::from(self.width) * u64::from(self.height)
}
}
/// Feed rows top to bottom; ask for the best at any point.
#[derive(Debug, Clone)]
pub struct Inscribed {
width: usize,
/// How many consecutive covered rows end at the last row fed, per column.
heights: Vec<u32>,
rows: u32,
best: Rect,
}
impl Inscribed {
pub fn new(width: u32) -> Self {
Inscribed {
width: width as usize,
heights: vec![0; width as usize],
rows: 0,
best: Rect::default(),
}
}
/// One more row of coverage, `width` long.
pub fn push_row(&mut self, covered: &[bool]) {
debug_assert_eq!(covered.len(), self.width);
for (h, &c) in self.heights.iter_mut().zip(covered) {
*h = if c { *h + 1 } else { 0 };
}
self.rows += 1;
// Largest rectangle under the histogram, with a sentinel column of
// height 0 at the end so every bar is popped.
let mut stack: Vec<usize> = Vec::new();
for i in 0..=self.width {
let h = if i < self.width { self.heights[i] } else { 0 };
while let Some(&top) = stack.last() {
if self.heights[top] <= h {
break;
}
stack.pop();
let height = self.heights[top];
let left = stack.last().map_or(0, |&l| l + 1);
let width = (i - left) as u32;
let area = u64::from(width) * u64::from(height);
if area > self.best.area() {
self.best = Rect {
x: left as u32,
y: self.rows - height,
width,
height,
};
}
}
stack.push(i);
}
}
/// Several rows at once, as a band hands them over.
pub fn push_rows(&mut self, covered: &[bool], rows: u32) {
for r in 0..rows as usize {
self.push_row(&covered[r * self.width..(r + 1) * self.width]);
}
}
pub fn best(&self) -> Rect {
self.best
}
}
#[cfg(test)]
mod tests {
use super::*;
fn from_art(art: &[&str]) -> Rect {
let mut ins = Inscribed::new(art[0].len() as u32);
for row in art {
let covered: Vec<bool> = row.chars().map(|c| c == '#').collect();
ins.push_row(&covered);
}
ins.best()
}
#[test]
fn a_full_mask_is_its_own_rectangle() {
let r = from_art(&["####", "####", "####"]);
assert_eq!(
r,
Rect {
x: 0,
y: 0,
width: 4,
height: 3
}
);
}
#[test]
fn ragged_edges_are_cut_off() {
// A cylinder's footprint: narrower at top and bottom.
let r = from_art(&[
"..####..", ".######.", "########", "########", ".######.", "..####..",
]);
// 6 wide × 4 tall = 24 beats 8 × 2 = 16 and 4 × 6 = 24 ties; the
// first found wins a tie, which is the wider one here.
assert_eq!(r.area(), 24);
assert!(r.width == 6 && r.height == 4 || r.width == 4 && r.height == 6);
}
#[test]
fn a_hole_is_avoided() {
let r = from_art(&["#####", "##.##", "#####", "#####"]);
// Left of the hole: 2 × 4 = 8; right: 2 × 4 = 8; below: 5 × 2 = 10.
assert_eq!(
r,
Rect {
x: 0,
y: 2,
width: 5,
height: 2
}
);
}
#[test]
fn nothing_covered_is_nothing() {
assert_eq!(from_art(&["....", "...."]).area(), 0);
}
}
+4
View File
@@ -24,16 +24,20 @@
use dr_types::{ColourSpace, ExportFormat, ExportSettings};
mod dng;
mod encode;
mod error;
mod exif;
pub mod icc;
mod inscribed;
mod metadata;
mod name;
mod sharpen;
mod size;
pub use dng::{write_linear_dng, DngProfile};
pub use error::ExportError;
pub use inscribed::{Inscribed, Rect};
pub use metadata::SourceMetadata;
pub use name::{resolve_name, NameContext};
pub use size::target_size;
+10 -5
View File
@@ -9,10 +9,11 @@ license.workspace = true
thiserror.workspace = true
log.workspace = true
# Inference. `ort` is the API; **tract is the engine** — see the workspace
# manifest, and docs/faces.md §3, for why the C++ ONNX Runtime is not linked.
# Inference. `ort` is the API; **what runs it is `dr-inference-engine`'s
# business** — tract, or an ONNX Runtime the app found on disk, on whichever
# provider the device has (docs/inference.md). This crate never names either.
ort = { workspace = true, optional = true }
ort-tract = { workspace = true, optional = true }
dr-inference-engine = { workspace = true, optional = true }
ndarray = { workspace = true, optional = true }
[dev-dependencies]
@@ -20,7 +21,7 @@ zune-jpeg.workspace = true
env_logger.workspace = true
# The M1 probe drives `ort` directly so it can print the raw load error.
ort = { workspace = true }
ort-tract = { workspace = true }
dr-inference-engine = { workspace = true }
[[example]]
name = "probe"
@@ -30,6 +31,10 @@ required-features = ["inference"]
name = "faces"
required-features = ["inference"]
[[example]]
name = "eyes"
required-features = ["inference"]
[features]
# Nothing on by default, and in particular **no `embedded-model`**: the weights
# are not a build input and never become one (docs/faces.md §2.2). A feature
@@ -44,4 +49,4 @@ default = []
# must be testable against synthetic embeddings on a machine with no weights on
# it — a test suite that needs a research-licensed download is a test suite
# that does not run in CI.
inference = ["dep:ort", "dep:ort-tract", "dep:ndarray"]
inference = ["dep:ort", "dep:dr-inference-engine", "dep:ndarray"]
+145
View File
@@ -0,0 +1,145 @@
//! Detect the faces in a JPEG and read each one's eyes (docs/faces.md §17).
//!
//! The thing worth looking at is whether the eye boxes land on eyes and
//! whether soft ones are refused — so with `--dump DIR` the crops the
//! classifiers were shown are written out as PPMs, one per eye and one per
//! head framing, named by image and face, and every line carries the
//! numbers the readability floors are set from.
//!
//! cargo run -p dr-face --features inference --example eyes -- \
//! DET.onnx 2D106DET.onnx OCEC.onnx SGC.onnx [--dump DIR] photo.jpg [photo.jpg ...]
//!
//! All four models must have had their dynamic dims pinned first; see
//! `tools/fix-face-model-shapes.sh`.
use std::path::{Path, PathBuf};
use std::time::Instant;
use dr_face::{align, DetectOptions, Detector, EyeModels, Pixels};
fn main() {
env_logger::init();
let mut args: Vec<String> = std::env::args().skip(1).collect();
let dump = args.iter().position(|a| a == "--dump").map(|i| {
args.remove(i);
PathBuf::from(args.remove(i))
});
if args.len() < 5 {
eprintln!(
"usage: eyes DET.onnx 2D106DET.onnx OCEC.onnx SGC.onnx [--dump DIR] IMAGE.jpg [IMAGE.jpg ...]"
);
std::process::exit(2);
}
if let Some(d) = &dump {
std::fs::create_dir_all(d).expect("dump dir");
}
let t = Instant::now();
let mut detector = Detector::from_path(&args[0]).expect("load detector");
let mut models = EyeModels::from_paths(&args[1], &args[2], &args[3]).expect("load eye models");
println!("loaded the models in {:?}", t.elapsed());
let opts = DetectOptions::default();
for path in &args[4..] {
let (rgb, w, h) = match load_jpeg(path) {
Ok(v) => v,
Err(e) => {
println!("{path}: {e}");
continue;
}
};
let dets = detector.detect(&rgb, w, h, &opts).expect("detect");
println!("\n{path} ({w}×{h}) {} face(s)", dets.len());
let stem = Path::new(path)
.file_stem()
.map(|s| s.to_string_lossy().into_owned())
.unwrap_or_default();
for (i, d) in dets.iter().enumerate() {
let px = Pixels::RgbF32(&rgb);
let t = Instant::now();
let reading = models
.read(px, w, h, d.bbox, &d.landmarks)
.expect("read eyes");
let ms = t.elapsed().as_secs_f64() * 1e3;
let Some((r, lm)) = reading else {
println!(" [{i}] nothing to cut, skipped");
continue;
};
println!(
" [{i}] conf {:.2} box {:.0}×{:.0} right {:.3} ({:.0}px, sharp {:.3}) left {:.3} ({:.0}px, sharp {:.3}) sunglasses {:.3} → {:?} ({ms:.1} ms)",
d.confidence,
d.width(),
d.height(),
r.right.open,
r.right.px,
r.right.sharpness,
r.left.open,
r.left.px,
r.left.sharpness,
r.sunglasses,
r.state(),
);
if let Some(dir) = &dump {
// The same crops `EyeModels::read` cut, cut again for the
// sheet from the landmarks it handed back: the reading itself
// carries numbers, not pixels.
for (name, contour) in [("right", lm.right_eye()), ("left", lm.left_eye())] {
if let Some(patch) =
align::eye_box(&contour).and_then(|b| align::eye_patch(px, w, h, b))
{
write_ppm(
&dir.join(format!("{stem}-{i}-{name}.ppm")),
patch.pixels(),
align::EYE_PATCH_WIDTH,
align::EYE_PATCH_HEIGHT,
);
}
}
if let Some(head) = align::head_views(px, w, h, &d.landmarks) {
for (n, view) in head.views().enumerate() {
write_ppm(
&dir.join(format!("{stem}-{i}-head{n}.ppm")),
view,
align::SUNGLASSES_EDGE,
align::SUNGLASSES_EDGE,
);
}
}
}
}
}
}
fn write_ppm(path: &Path, rgb: &[f32], w: usize, h: usize) {
let mut out = format!("P6\n{w} {h}\n255\n").into_bytes();
out.extend(
rgb.iter()
.map(|v| (v.clamp(0.0, 1.0) * 255.0).round() as u8),
);
std::fs::write(path, out).expect("write ppm");
}
/// Decode to the tightly packed `f32` RGB `0.0..=1.0` the crate expects.
fn load_jpeg(path: &str) -> Result<(Vec<f32>, usize, usize), String> {
let bytes = std::fs::read(path).map_err(|e| e.to_string())?;
let mut dec = zune_jpeg::JpegDecoder::new(&bytes);
let px = dec.decode().map_err(|e| e.to_string())?;
let info = dec.info().ok_or("no jpeg header")?;
let (w, h) = (info.width as usize, info.height as usize);
let rgb: Vec<f32> = match px.len() / (w * h) {
3 => px.iter().map(|&v| v as f32 / 255.0).collect(),
1 => px
.iter()
.flat_map(|&v| {
let g = v as f32 / 255.0;
[g, g, g]
})
.collect(),
n => return Err(format!("{n} components per pixel, expected 1 or 3")),
};
Ok((rgb, w, h))
}
+467 -56
View File
@@ -117,51 +117,56 @@ impl Aligned112 {
/// `face_index --quality` prints the joint distribution so the two are
/// chosen together rather than each in ignorance of the other.
pub fn sharpness(&self) -> f32 {
let e = ALIGNED_EDGE;
let luma: Vec<f32> = self
.pixels
.chunks_exact(3)
.map(|p| 0.2126 * p[0] + 0.7152 * p[1] + 0.0722 * p[2])
.collect();
let (mut lap_sum, mut lap_sq) = (0.0_f64, 0.0_f64);
let (mut lum_sum, mut lum_sq) = (0.0_f64, 0.0_f64);
let mut n = 0.0_f64;
for y in 1..e - 1 {
for x in 1..e - 1 {
let i = y * e + x;
// Four-neighbour Laplacian. The 8-neighbour form is more
// sensitive to diagonal detail and also to noise, which on a
// high-ISO frame is exactly the thing that must not read as
// sharpness.
let lap = 4.0 * luma[i] - luma[i - 1] - luma[i + 1] - luma[i - e] - luma[i + e];
let lap = lap as f64;
lap_sum += lap;
lap_sq += lap * lap;
let l = luma[i] as f64;
lum_sum += l;
lum_sq += l * l;
n += 1.0;
}
}
if n == 0.0 {
return 0.0;
}
let lap_var = (lap_sq / n - (lap_sum / n).powi(2)).max(0.0);
let lum_var = (lum_sq / n - (lum_sum / n).powi(2)).max(0.0);
// A crop with no luma variation has no edges to find either, so the
// ratio is 0/0. Zero is the right answer: nothing there is a face.
if lum_var <= 1e-9 {
return 0.0;
}
(lap_var / lum_var) as f32
laplacian_ratio(&self.pixels, ALIGNED_EDGE, ALIGNED_EDGE)
}
}
/// Variance of the four-neighbour Laplacian over the variance of the luma,
/// for a `w × h` RGB crop — the measure [`Aligned112::sharpness`] describes,
/// shared with [`EyePatch::sharpness`].
fn laplacian_ratio(pixels: &[f32], w: usize, h: usize) -> f32 {
let luma: Vec<f32> = pixels
.chunks_exact(3)
.map(|p| 0.2126 * p[0] + 0.7152 * p[1] + 0.0722 * p[2])
.collect();
let (mut lap_sum, mut lap_sq) = (0.0_f64, 0.0_f64);
let (mut lum_sum, mut lum_sq) = (0.0_f64, 0.0_f64);
let mut n = 0.0_f64;
for y in 1..h.saturating_sub(1) {
for x in 1..w.saturating_sub(1) {
let i = y * w + x;
// Four-neighbour Laplacian. The 8-neighbour form is more
// sensitive to diagonal detail and also to noise, which on a
// high-ISO frame is exactly the thing that must not read as
// sharpness.
let lap = 4.0 * luma[i] - luma[i - 1] - luma[i + 1] - luma[i - w] - luma[i + w];
let lap = lap as f64;
lap_sum += lap;
lap_sq += lap * lap;
let l = luma[i] as f64;
lum_sum += l;
lum_sq += l * l;
n += 1.0;
}
}
if n == 0.0 {
return 0.0;
}
let lap_var = (lap_sq / n - (lap_sum / n).powi(2)).max(0.0);
let lum_var = (lum_sq / n - (lum_sum / n).powi(2)).max(0.0);
// A crop with no luma variation has no edges to find either, so the
// ratio is 0/0. Zero is the right answer: nothing there is a face.
if lum_var <= 1e-9 {
return 0.0;
}
(lap_var / lum_var) as f32
}
/// A similarity transform: rotation, uniform scale, translation.
///
/// Stored as the four independent parameters rather than a 2×3 matrix so that
@@ -351,27 +356,314 @@ pub fn warp_pixels(
let m = fit_similarity(landmarks, &ARCFACE_TEMPLATE)?;
let e = ALIGNED_EDGE;
let mut pixels = vec![0.0_f32; e * e * 3];
for v in 0..e {
for u in 0..e {
// Pixel centres, so the transform is not off by half a pixel —
// which is small enough to survive review and large enough to
// matter on a 40-pixel face.
let (x, y) = m.invert(u as f32 + 0.5, v as f32 + 0.5);
let (x, y) = (x - 0.5, y - 0.5);
let out = (v * e + u) * 3;
sample_bilinear(px, width, height, x, y, &mut pixels[out..out + 3]);
}
}
let window = TemplateWindow {
x: 0.0,
y: 0.0,
w: e as f32,
h: e as f32,
};
Some(Aligned112 {
pixels,
pixels: sample_window(px, width, height, &m, &window, e, e),
// The warp maps `scale` source pixels to one destination pixel, so the
// crop spans 112/scale of the source.
source_px: ALIGNED_EDGE as f32 / m.scale(),
})
}
/// A rectangle in **template** coordinates — the 112-unit frame
/// [`ARCFACE_TEMPLATE`] is written in — that a crop is sampled from.
///
/// Every crop this module makes is one of these resampled through the same
/// fitted similarity: the aligned face is the window `(0, 0, 112, 112)`, an
/// eye is a small window around its template point, a head is a window larger
/// than the face. Stating them all in one frame is what lets a second crop be
/// added as a constant rather than a second warp, and what keeps them
/// consistent with each other — the eye window sits where the eye landmark
/// lands *after* alignment, so a tilted face gets an upright eye.
#[derive(Debug, Clone, Copy, PartialEq)]
struct TemplateWindow {
x: f32,
y: f32,
w: f32,
h: f32,
}
/// Resample `window` of the template frame into an `out_w × out_h` RGB buffer.
///
/// Bilinear, from the source, in one step — the property [`warp`] insists on,
/// and every crop through here inherits it. The output pixel `(u, v)` is placed
/// at its centre in the window, taken back through `m` to source coordinates,
/// and sampled there; the window's aspect is **not** preserved when it differs
/// from the output's, which is deliberate for the eye classifier (it was
/// trained on detector boxes resized the same way) and moot for the others.
fn sample_window(
px: Pixels<'_>,
width: usize,
height: usize,
m: &Similarity,
window: &TemplateWindow,
out_w: usize,
out_h: usize,
) -> Vec<f32> {
let mut pixels = vec![0.0_f32; out_w * out_h * 3];
let sx = window.w / out_w as f32;
let sy = window.h / out_h as f32;
for v in 0..out_h {
for u in 0..out_w {
// Pixel centres, so the transform is not off by half a pixel —
// which is small enough to survive review and large enough to
// matter on a 40-pixel face.
let tx = window.x + (u as f32 + 0.5) * sx;
let ty = window.y + (v as f32 + 0.5) * sy;
let (x, y) = m.invert(tx, ty);
let (x, y) = (x - 0.5, y - 0.5);
let out = (v * out_w + u) * 3;
sample_bilinear(px, width, height, x, y, &mut pixels[out..out + 3]);
}
}
pixels
}
// ── eyes ──────────────────────────────────────────────────────────────────
/// Width of an eye crop as the classifier reads it, in pixels. Fixed by the
/// OCEC input (`docs/faces.md` §17): 40 wide, 24 high.
pub const EYE_PATCH_WIDTH: usize = 40;
/// Height of an eye crop as the classifier reads it, in pixels.
pub const EYE_PATCH_HEIGHT: usize = 24;
/// How much an eye's box is grown beyond its lid contour, as a fraction of
/// its width and height on each side.
///
/// The classifier was trained on a whole-body detector's *eye* boxes — tight
/// round the palpebral fissure — and measured on 25 open-eyed faces from the
/// reference library, a tight box is what it wants: 22 of 25 read open at
/// 0 and 0.1, 18 at 0.4, 14 at 0.6 (docs/faces.md §17.2). A tenth, so a
/// contour landing a pixel short of the lashes still holds them.
pub const EYE_BOX_MARGIN: f32 = 0.1;
/// Height a shut eye's box is given, as a fraction of its width.
///
/// A closed eye's contour has no height. The box is given the height an
/// open eye of the same width would have, so the classifier sees the same
/// framing either way — which is what it was trained on.
pub const EYE_BOX_MIN_ASPECT: f32 = 0.4;
/// The box round an eye's lid contour, in the contour's own coordinates:
/// `(x, y, w, h)`.
///
/// Model-free: the contour is whatever the landmark model gave for the ten
/// (or so) points on the lids, in source pixels. `None` for an empty
/// contour or one with no width, which is what a hidden eye's collapsed
/// contour can come to.
pub fn eye_box(contour: &[(f32, f32)]) -> Option<(f32, f32, f32, f32)> {
let (mut x0, mut y0, mut x1, mut y1) = (f32::MAX, f32::MAX, f32::MIN, f32::MIN);
for &(x, y) in contour {
x0 = x0.min(x);
y0 = y0.min(y);
x1 = x1.max(x);
y1 = y1.max(y);
}
let w = x1 - x0;
if contour.is_empty() || w <= 0.0 || w.is_nan() {
return None;
}
let h = (y1 - y0).max(w * EYE_BOX_MIN_ASPECT);
let cy = (y0 + y1) / 2.0;
let (mx, my) = (w * EYE_BOX_MARGIN, h * EYE_BOX_MARGIN);
Some((x0 - mx, cy - h / 2.0 - my, w + 2.0 * mx, h + 2.0 * my))
}
/// One eye, resampled to the classifier's input.
///
/// Constructible only by [`eye_patch`], for the reason [`Aligned112`] is
/// only constructible by [`warp`]: the classifier accepting a plain buffer
/// would accept any 40×24 of anything, and its answer would still be a
/// plausible probability.
#[derive(Debug, Clone, PartialEq)]
pub struct EyePatch {
/// `24 × 40 × 3`, row-major RGB in `0.0..=1.0`.
pixels: Vec<f32>,
/// Source pixels across the box the patch was cut from.
source_px: f32,
}
impl EyePatch {
pub fn pixels(&self) -> &[f32] {
&self.pixels
}
/// Source pixels across the eye box — how much eye there was to read.
///
/// The classifier was trained down to eyes a dozen pixels wide, and
/// below that a crop is an interpolation of nothing; `crate::eyes` draws
/// the line. Zero when the box had no width, which is a hidden eye.
pub fn source_px(&self) -> f32 {
self.source_px
}
/// How sharp the eye the classifier is about to see actually is —
/// [`Aligned112::sharpness`]'s measure, over the patch.
///
/// The reason it exists is the reason the face's does: a soft eye is
/// not a closed one, but a classifier shown a smear says "closed" with
/// the same confidence it says anything, and the only defence is to
/// not ask. A face sharp enough to embed can still hold an eye too soft
/// to read — it is a fortieth of the face — so the measure is taken
/// here and not inherited from the crop.
pub fn sharpness(&self) -> f32 {
laplacian_ratio(&self.pixels, EYE_PATCH_WIDTH, EYE_PATCH_HEIGHT)
}
}
/// Cut an eye out of the source at the classifier's size, from an
/// axis-aligned box in source pixels — [`eye_box`]'s, as a rule.
///
/// Upright and from the frame, not through the face's alignment: the
/// classifier's training crops were detector boxes, and a landmark model's
/// contour already says where the eye is on a tilted head. Bilinear in one
/// step from the native buffer, so a large face gives real pixels; the
/// box's aspect is not preserved, which is what the training resize did.
pub fn eye_patch(
px: Pixels<'_>,
width: usize,
height: usize,
bbox: (f32, f32, f32, f32),
) -> Option<EyePatch> {
let pixels = crop_box(px, width, height, bbox, EYE_PATCH_WIDTH, EYE_PATCH_HEIGHT)?;
Some(EyePatch {
pixels,
source_px: bbox.2,
})
}
// ── sunglasses ────────────────────────────────────────────────────────────
/// Edge of the crop the sunglasses classifier reads. Fixed by the SGC input:
/// 48×48.
pub const SUNGLASSES_EDGE: usize = 48;
/// The windows read for the sunglasses classifier, in template units:
/// `(x, y, w, h)`.
///
/// **Two framings, and the classifier's answer is the higher of the two.**
/// It was trained on a whole-body detector's *head* boxes, and a head box
/// is not reproducible from five landmarks: how much hair and hat it took in
/// depended on the person. So it is shown the face twice — once as the
/// aligned crop itself, once shifted up and widened to take in hair and
/// hat at the cost of the chin, which is roughly where a head box falls —
/// and a pair of sunglasses counts if it looks like one in either.
///
/// Measured over 12 faces in sunglasses and 28 with plainly visible eyes
/// from the reference library (`examples/eyes.rs --head`), at the 0.5
/// threshold:
///
/// | window | sunglasses found | clear eyes kept |
/// |---|---|---|
/// | the aligned face, `(0, 0, 112, 112)` | 9 | 28 |
/// | a head, `(-5, -14, 122, 122)` | 6 | 27 |
/// | a larger head, `(-30, -55, 172, 190)` | 6 | 25 |
/// | **the higher of the first two** | **11** | 27 |
///
/// The face-tight crop alone was the best single framing, which was not the
/// expectation; the head framing found the sunglasses under a cap that the
/// face crop missed. The one clear-eyed face the pair loses wears a cap and
/// clear glasses, at 0.68. Erring towards "sunglasses" is the safe direction
/// for what this feeds: a face called sunglasses is left alone by the
/// eyes-open filter, where a pair of sunglasses missed hands the eye
/// classifier a lens to guess at (docs/faces.md §17).
pub const SUNGLASSES_WINDOWS: [(f32, f32, f32, f32); 2] =
[(0.0, 0.0, 112.0, 112.0), (-5.0, -14.0, 122.0, 122.0)];
/// The framings of one face the sunglasses classifier is shown.
///
/// A newtype for the reason [`EyePatch`] is one.
#[derive(Debug, Clone, PartialEq)]
pub struct HeadViews {
/// Each `48 × 48 × 3`, row-major RGB in `0.0..=1.0`.
views: Vec<Vec<f32>>,
}
impl HeadViews {
pub fn views(&self) -> impl Iterator<Item = &[f32]> {
self.views.iter().map(Vec::as_slice)
}
}
/// Cut the [`SUNGLASSES_WINDOWS`] out of the source, aligned, at the
/// classifier's size.
pub fn head_views(
px: Pixels<'_>,
width: usize,
height: usize,
landmarks: &[(f32, f32); 5],
) -> Option<HeadViews> {
head_views_in(px, width, height, landmarks, &SUNGLASSES_WINDOWS)
}
/// [`head_views`] over windows other than [`SUNGLASSES_WINDOWS`].
///
/// For measuring them, which is how the constant was chosen
/// (`examples/eyes.rs --head`); production callers use the constant.
pub fn head_views_in(
px: Pixels<'_>,
width: usize,
height: usize,
landmarks: &[(f32, f32); 5],
windows: &[(f32, f32, f32, f32)],
) -> Option<HeadViews> {
if !px.fits(width, height) || windows.is_empty() {
return None;
}
let m = fit_similarity(landmarks, &ARCFACE_TEMPLATE)?;
let views = windows
.iter()
.map(|&(x, y, w, h)| {
let window = TemplateWindow { x, y, w, h };
sample_window(
px,
width,
height,
&m,
&window,
SUNGLASSES_EDGE,
SUNGLASSES_EDGE,
)
})
.collect();
Some(HeadViews { views })
}
/// An axis-aligned crop of the source, resampled to `out_w × out_h` RGB.
///
/// `(x, y, w, h)` in source pixels; the aspect is not preserved when it
/// differs from the output's. Bilinear in one step, like every crop here;
/// pixels outside the source read black. What a landmark model trained on
/// detector boxes wants — upright, from the frame — as against the aligned
/// windows above.
pub fn crop_box(
px: Pixels<'_>,
width: usize,
height: usize,
(x, y, w, h): (f32, f32, f32, f32),
out_w: usize,
out_h: usize,
) -> Option<Vec<f32>> {
if !px.fits(width, height) || w <= 0.0 || h <= 0.0 {
return None;
}
let identity = Similarity {
a: 1.0,
b: 0.0,
tx: 0.0,
ty: 0.0,
};
let window = TemplateWindow { x, y, w, h };
Some(sample_window(
px, width, height, &identity, &window, out_w, out_h,
))
}
fn sample_bilinear(px: Pixels<'_>, w: usize, h: usize, x: f32, y: f32, out: &mut [f32]) {
let x0 = x.floor();
let y0 = y.floor();
@@ -489,6 +781,125 @@ mod tests {
}
}
/// A source whose red channel is its x coordinate and green its y, so a
/// crop's mean colour says where in the source it was taken from.
fn coordinate_image(w: usize, h: usize) -> Vec<f32> {
let mut rgb = vec![0.0_f32; w * h * 3];
for y in 0..h {
for x in 0..w {
rgb[(y * w + x) * 3] = x as f32 / w as f32;
rgb[(y * w + x) * 3 + 1] = y as f32 / h as f32;
}
}
rgb
}
fn mean_channel(px: &[f32], c: usize) -> f32 {
let n = px.len() / 3;
px.chunks_exact(3).map(|p| p[c]).sum::<f32>() / n as f32
}
/// The box is the contour's bounds, grown by the margin, and a shut
/// eye's flat contour is given an open eye's height.
#[test]
fn an_eye_box_holds_its_contour_with_a_margin() {
let open = [(100.0, 50.0), (110.0, 46.0), (120.0, 50.0), (110.0, 54.0)];
let (x, y, w, h) = eye_box(&open).unwrap();
assert!((w - 20.0 * (1.0 + 2.0 * EYE_BOX_MARGIN)).abs() < 1e-4);
assert!((h - 8.0 * (1.0 + 2.0 * EYE_BOX_MARGIN)).abs() < 1e-4);
assert!((x + w / 2.0 - 110.0).abs() < 1e-4);
assert!((y + h / 2.0 - 50.0).abs() < 1e-4);
let shut = [(100.0, 50.0), (110.0, 50.0), (120.0, 50.0)];
let (_, _, w2, h2) = eye_box(&shut).unwrap();
assert!((w2 - w).abs() < 1e-4, "same width");
assert!((h2 - 20.0 * EYE_BOX_MIN_ASPECT * (1.0 + 2.0 * EYE_BOX_MARGIN)).abs() < 1e-4);
assert!(eye_box(&[]).is_none());
assert!(eye_box(&[(5.0, 5.0), (5.0, 9.0)]).is_none(), "no width");
}
/// The patch is cut from the box it was given, upright, and knows how
/// many source pixels it spans.
#[test]
fn an_eye_patch_is_the_box_resampled() {
let (w, h) = (200, 200);
let rgb = coordinate_image(w, h);
let bbox = (60.0, 90.0, 30.0, 12.0);
let eye = eye_patch(Pixels::RgbF32(&rgb), w, h, bbox).unwrap();
assert_eq!(eye.pixels().len(), EYE_PATCH_WIDTH * EYE_PATCH_HEIGHT * 3);
assert_eq!(eye.source_px(), 30.0);
let cx = mean_channel(eye.pixels(), 0) * w as f32;
let cy = mean_channel(eye.pixels(), 1) * h as f32;
assert!((cx - 75.0).abs() < 0.6, "{cx}");
assert!((cy - 96.0).abs() < 0.6, "{cy}");
// No width, or a buffer that is not the size it claims: nothing.
assert!(eye_patch(Pixels::RgbF32(&rgb), w, h, (60.0, 90.0, 0.0, 12.0)).is_none());
assert!(eye_patch(Pixels::RgbF32(&rgb), 190, 200, bbox).is_none());
}
/// A soft eye scores lower than the same eye sharp, on the patch itself.
#[test]
fn an_eye_patchs_sharpness_falls_with_blur() {
let edge = 120;
let sharp = image(
edge,
|x, y| if (x / 5 + y / 5) % 2 == 0 { 0.9 } else { 0.1 },
);
let soft = blur(&blur(&sharp, edge), edge);
let bbox = (20.0, 40.0, 40.0, 24.0);
let a = eye_patch(Pixels::RgbF32(&sharp), edge, edge, bbox)
.unwrap()
.sharpness();
let b = eye_patch(Pixels::RgbF32(&soft), edge, edge, bbox)
.unwrap()
.sharpness();
assert!(a > b * 2.0, "sharp {a} should clearly beat blurred {b}");
}
/// The second sunglasses framing takes in more than the face — it starts
/// above the template's top edge and ends below its bottom — and the
/// first is the aligned face itself.
#[test]
fn the_head_views_are_the_face_and_a_wider_framing_of_it() {
let (w, h) = (300, 300);
let rgb = coordinate_image(w, h);
let lm = shifted_scaled(1.0, 100.0, 100.0, 0.0);
let head = head_views(Pixels::RgbF32(&rgb), w, h, &lm).unwrap();
let views: Vec<&[f32]> = head.views().collect();
let face = warp(&rgb, w, h, &lm).unwrap();
assert_eq!(views.len(), SUNGLASSES_WINDOWS.len());
for v in &views {
assert_eq!(v.len(), SUNGLASSES_EDGE * SUNGLASSES_EDGE * 3);
}
// The face view samples the same region as the aligned crop.
assert!((mean_channel(views[0], 0) - mean_channel(face.pixels(), 0)).abs() < 0.01);
assert!((mean_channel(views[0], 1) - mean_channel(face.pixels(), 1)).abs() < 0.01);
let (x, y, ww, hh) = SUNGLASSES_WINDOWS[1];
assert!(
x < 0.0 && y < 0.0,
"the window starts outside the face crop"
);
assert!(x + ww > ALIGNED_EDGE as f32, "and is wider than it");
assert!(y + hh < ALIGNED_EDGE as f32, "but stops short of the chin");
// Centred horizontally on the face, so the two share a mean x.
assert!((mean_channel(views[1], 0) - mean_channel(face.pixels(), 0)).abs() < 0.01);
// Its first row lies above the face's first row.
assert!(views[1][1] < face.pixels()[1]);
}
#[test]
fn degenerate_landmarks_yield_no_head_crop() {
let rgb = vec![0.5_f32; 64 * 64 * 3];
let degenerate = [(50.0, 50.0); 5];
assert!(head_views(Pixels::RgbF32(&rgb), 64, 64, &degenerate).is_none());
// And a buffer that is not the size it claims.
let lm = shifted_scaled(1.0, 0.0, 0.0, 0.0);
assert!(head_views(Pixels::RgbF32(&rgb), 60, 60, &lm).is_none());
}
#[test]
fn out_of_bounds_samples_read_black_rather_than_wrapping() {
let rgb = vec![1.0_f32; 32 * 32 * 3];
+263
View File
@@ -0,0 +1,263 @@
//! TRACES: FR-CULL-8a
//! The two small classifiers behind a face's eye state (docs/faces.md §17).
//!
//! **OCEC** — *open closed eyes classification*, Hyodo 2025 — reads one
//! 40×24 eye and answers P(open). **SGC** — *sunglasses classification*,
//! Hyodo 2026 — reads a 48×48 head and answers P(sunglasses); it is shown
//! two framings of each face and the higher answer stands, for the reason
//! [`crate::align::SUNGLASSES_WINDOWS`] gives. Both are
//! depthwise-separable CNNs of a few hundred kilobytes, both MIT with their
//! weights, and both were exported with BatchNorm already folded, which is
//! about the friendliest graph tract can be handed.
//!
//! Neither takes a plain buffer. [`EyeClassifier::classify`] takes an
//! [`EyePatch`] and [`SunglassesClassifier::classify`] a [`HeadViews`], each
//! constructible only by the crop in [`crate::align`] that puts the right
//! pixels in it — the same defence [`crate::embed::Embedder`] makes with
//! [`crate::align::Aligned112`], for the same reason: a classifier handed the
//! wrong region returns a confident probability of nothing. Where the eye
//! box comes from is [`crate::landmarks`]; [`EyeModels::read`] is the whole
//! chain.
//!
//! # The graphs must have a fixed batch
//!
//! Both ship with a dynamic batch dimension, which tract will not analyse.
//! `tools/fix-face-model-shapes.sh` pins it to 1, exactly as it does for the
//! embedder; the shipped files are the pinned ones.
//!
//! # Pre-processing
//!
//! Read off the reference demos rather than assumed: RGB, `x / 255`, NCHW,
//! the crop resized to the input with bilinear interpolation and **without**
//! preserving its aspect. [`crate::align`]'s crops arrive already at the
//! input size in `0..=1`, so there is nothing left to do but lay them out.
use ndarray::Array4;
use crate::align::{
eye_box, eye_patch, head_views, EyePatch, HeadViews, EYE_PATCH_HEIGHT, EYE_PATCH_WIDTH,
SUNGLASSES_EDGE,
};
use crate::eyes::{Eye, EyeReading};
use crate::landmarks::{Landmarker, Landmarks};
use crate::{FaceError, Pixels};
use dr_inference_engine::{Form, Model, Role};
/// A loaded OCEC graph.
pub struct EyeClassifier {
session: Model,
}
/// A loaded SGC graph.
pub struct SunglassesClassifier {
session: Model,
}
/// Open a single-input, single-output classifier and check it is the shape
/// the crop feeding it will be.
///
/// The check is against the *input*, because that is where these two graphs
/// differ from each other and from everything else in this crate: an SGC file
/// given to the eye classifier would otherwise be resized into by an eye
/// patch, and answer. `expected` names the model in the error.
fn open_classifier(
bytes: &[u8],
expected: &'static str,
(h, w): (usize, usize),
) -> Result<Model, FaceError> {
let model = dr_inference_engine::open(Role::EyeClassifier, Form::F32, bytes)?;
let acquired = model.acquire()?;
let session = acquired.lock();
let input = session.inputs().first().ok_or(FaceError::WrongModel {
expected,
detail: "model has no inputs".into(),
})?;
let shape: Option<Vec<i64>> = input.dtype().tensor_shape().map(|s| s.to_vec());
let want = [1, 3, h as i64, w as i64];
if shape.as_deref() != Some(&want[..]) {
return Err(FaceError::WrongModel {
expected,
detail: format!(
"input '{}' is {:?}, expected {:?} (batch pinned to 1)",
input.name(),
shape,
want
),
});
}
if session.outputs().len() != 1 {
return Err(FaceError::WrongModel {
expected,
detail: format!("{} outputs, expected one", session.outputs().len()),
});
}
drop(session);
drop(acquired);
Ok(model)
}
/// Lay a `h × w` RGB crop out as the `[1, 3, h, w]` tensor both graphs take.
fn to_nchw(pixels: &[f32], h: usize, w: usize) -> Array4<f32> {
let mut input = Array4::<f32>::zeros((1, 3, h, w));
for y in 0..h {
for x in 0..w {
for c in 0..3 {
input[[0, c, y, x]] = pixels[(y * w + x) * 3 + c];
}
}
}
input
}
/// Run a one-number classifier and read its sigmoid back, clamped.
fn run_scalar(model: &Model, input: Array4<f32>, expected: &'static str) -> Result<f32, FaceError> {
let acquired = model.acquire()?;
let mut session = acquired.lock();
let outputs = session
.run(ort::inputs![
ort::value::Tensor::from_array(input).map_err(FaceError::Inference)?
])
.map_err(FaceError::Inference)?;
let (_, data) = outputs[0]
.try_extract_tensor::<f32>()
.map_err(FaceError::Inference)?;
let Some(&p) = data.first() else {
return Err(FaceError::WrongModel {
expected,
detail: "empty output".into(),
});
};
// The graph ends in a sigmoid, so this is a clamp against rounding and
// nothing more — the reference demo does the same.
Ok(p.clamp(0.0, 1.0))
}
impl EyeClassifier {
pub fn from_path(path: impl AsRef<std::path::Path>) -> Result<Self, FaceError> {
let bytes = std::fs::read(path).map_err(FaceError::ModelRead)?;
Self::from_bytes(&bytes)
}
pub fn from_bytes(bytes: &[u8]) -> Result<Self, FaceError> {
Ok(Self {
session: open_classifier(bytes, "OCEC", (EYE_PATCH_HEIGHT, EYE_PATCH_WIDTH))?,
})
}
/// P(open) for one eye.
pub fn classify(&mut self, eye: &EyePatch) -> Result<f32, FaceError> {
let input = to_nchw(eye.pixels(), EYE_PATCH_HEIGHT, EYE_PATCH_WIDTH);
run_scalar(&self.session, input, "OCEC")
}
}
impl SunglassesClassifier {
pub fn from_path(path: impl AsRef<std::path::Path>) -> Result<Self, FaceError> {
let bytes = std::fs::read(path).map_err(FaceError::ModelRead)?;
Self::from_bytes(&bytes)
}
pub fn from_bytes(bytes: &[u8]) -> Result<Self, FaceError> {
Ok(Self {
session: open_classifier(bytes, "SGC", (SUNGLASSES_EDGE, SUNGLASSES_EDGE))?,
})
}
/// P(sunglasses) for one head: the highest answer over its framings.
pub fn classify(&mut self, head: &HeadViews) -> Result<f32, FaceError> {
let mut best = 0.0_f32;
for view in head.views() {
let input = to_nchw(view, SUNGLASSES_EDGE, SUNGLASSES_EDGE);
best = best.max(run_scalar(&self.session, input, "SGC")?);
}
Ok(best)
}
}
/// The three models behind a reading, which is how every caller holds them.
///
/// One struct rather than three optional parameters, because a partial
/// reading is not a reading: an eye state with no sunglasses number behind
/// it is exactly the beach-photograph failure [`crate::eyes`] describes, and
/// an eye box without the landmarks is the loose one this module replaced.
/// The models load together or not at all.
pub struct EyeModels {
pub landmarks: Landmarker,
pub eyes: EyeClassifier,
pub sunglasses: SunglassesClassifier,
}
impl EyeModels {
pub fn from_paths(
landmarks: impl AsRef<std::path::Path>,
eyes: impl AsRef<std::path::Path>,
sunglasses: impl AsRef<std::path::Path>,
) -> Result<Self, FaceError> {
Ok(Self {
landmarks: Landmarker::from_path(landmarks)?,
eyes: EyeClassifier::from_path(eyes)?,
sunglasses: SunglassesClassifier::from_path(sunglasses)?,
})
}
/// Read one face's eyes, and hand back the dense landmarks it read them
/// from.
///
/// `bbox` is the detector's `(x0, y0, x1, y1)` and `landmarks5` its five
/// points, both in source pixels; the buffer is the one the aligned
/// crop was taken from, so an eye is read from the same pixels the
/// embedder saw the face in. `None` where nothing could be cut — a
/// degenerate box or landmarks — which the caller stores as "not read".
///
/// The landmarks come back because they cost a model run the caller will
/// not want to pay twice: stored beside the reading, a later pass over
/// faces — head pose, expression — has them without the original.
pub fn read(
&mut self,
px: Pixels<'_>,
width: usize,
height: usize,
bbox: (f32, f32, f32, f32),
landmarks5: &[(f32, f32); 5],
) -> Result<Option<(EyeReading, Landmarks)>, FaceError> {
let Some(lm) = self.landmarks.landmarks(px, width, height, bbox)? else {
return Ok(None);
};
let Some(head) = head_views(px, width, height, landmarks5) else {
return Ok(None);
};
let mut eye = |contour: &[(f32, f32)]| -> Result<Eye, FaceError> {
// A hidden eye's contour can collapse to no width. Its numbers
// are then zero — no pixels, no sharpness — which is what the
// rule in `crate::eyes` reads as "not readable".
let Some(b) = eye_box(contour) else {
return Ok(Eye {
open: 0.0,
px: 0.0,
sharpness: 0.0,
});
};
let Some(patch) = eye_patch(px, width, height, b) else {
return Ok(Eye {
open: 0.0,
px: 0.0,
sharpness: 0.0,
});
};
Ok(Eye {
open: self.eyes.classify(&patch)?,
px: patch.source_px(),
sharpness: patch.sharpness(),
})
};
let right = eye(&lm.right_eye())?;
let left = eye(&lm.left_eye())?;
let reading = EyeReading {
right,
left,
sunglasses: self.sunglasses.classify(&head)?,
};
Ok(Some((reading, lm)))
}
}
+36 -14
View File
@@ -14,7 +14,8 @@
use ndarray::Array4;
use crate::{install_backend, FaceError};
use crate::FaceError;
use dr_inference_engine::{Form, Model, Role};
/// The graph's input edge, in pixels. See the module note: not configurable.
pub const INPUT_EDGE: usize = 640;
@@ -135,7 +136,10 @@ impl Detection {
/// A loaded SCRFD graph.
pub struct Detector {
session: ort::session::Session,
session: Model,
/// f32 or int8 — the int8 form finds a different set of faces and is a
/// different detector in `model_id` (docs/inference.md §7).
form: Form,
/// Feature-map count: 3 for strides {8,16,32}, 4 for {8,16,32,64}.
///
/// Discovered from the output count rather than assumed, because both
@@ -145,18 +149,29 @@ pub struct Detector {
}
impl Detector {
pub fn from_path(path: impl AsRef<std::path::Path>) -> Result<Self, FaceError> {
let bytes = std::fs::read(path).map_err(FaceError::ModelRead)?;
Self::from_bytes(&bytes)
/// Which form this detector was loaded from.
pub fn form(&self) -> Form {
self.form
}
pub fn from_bytes(bytes: &[u8]) -> Result<Self, FaceError> {
install_backend();
/// Load the canonical f32 file at `path`, or the form the device's
/// backend wants instead — the `.int8.onnx` beside it on a Hexagon —
/// which [`Detector::form`] then reports.
pub fn from_path(path: impl AsRef<std::path::Path>) -> Result<Self, FaceError> {
let (path, form) = dr_inference_engine::resolve_model(Role::Detector, path.as_ref());
let bytes = std::fs::read(path).map_err(FaceError::ModelRead)?;
Self::from_bytes_in(&bytes, form)
}
let session = ort::session::Session::builder()
.map_err(FaceError::Inference)?
.commit_from_memory(bytes)
.map_err(FaceError::Inference)?;
/// An f32 graph from memory.
pub fn from_bytes(bytes: &[u8]) -> Result<Self, FaceError> {
Self::from_bytes_in(bytes, Form::F32)
}
fn from_bytes_in(bytes: &[u8], form: Form) -> Result<Self, FaceError> {
let model = dr_inference_engine::open(Role::Detector, form, bytes)?;
let acquired = model.acquire()?;
let session = acquired.lock();
let n_out = session.outputs().len();
if n_out % 3 != 0 || !(9..=12).contains(&n_out) {
@@ -191,7 +206,13 @@ impl Detector {
}
}
Ok(Self { session, fmc })
drop(session);
drop(acquired);
Ok(Self {
session: model,
form,
fmc,
})
}
/// Stride levels this graph emits.
@@ -223,8 +244,9 @@ impl Detector {
let lb = Letterbox::fit(width as f32, height as f32);
let input = lb.sample(rgb, width, height);
let outputs = self
.session
let acquired = self.session.acquire()?;
let mut session = acquired.lock();
let outputs = session
.run(ort::inputs![
ort::value::Tensor::from_array(input).map_err(FaceError::Inference)?
])
+17 -11
View File
@@ -14,7 +14,8 @@ use ndarray::Array4;
use crate::align::{Aligned112, ALIGNED_EDGE};
use crate::embedding::{normalise, Embedding, ModelId, EMBEDDING_DIM};
use crate::{install_backend, FaceError};
use crate::FaceError;
use dr_inference_engine::{Form, Model, Role};
/// What one pass of the embedder produces: the direction, and the length.
///
@@ -53,7 +54,7 @@ impl Embedded {
/// A loaded ArcFace graph.
pub struct Embedder {
session: ort::session::Session,
session: Model,
model: ModelId,
}
@@ -64,12 +65,11 @@ impl Embedder {
}
pub fn from_bytes(bytes: &[u8], model: ModelId) -> Result<Self, FaceError> {
install_backend();
let session = ort::session::Session::builder()
.map_err(FaceError::Inference)?
.commit_from_memory(bytes)
.map_err(FaceError::Inference)?;
// Always the f32 form: an embedding must compare across devices
// (docs/inference.md §7), and the engine pins this role to it.
let loaded = dr_inference_engine::open(Role::Embedder, Form::F32, bytes)?;
let acquired = loaded.acquire()?;
let session = acquired.lock();
// One output, `[1, 512]`. Checked because an ArcFace variant with a
// different embedding width would otherwise be read as a truncated
@@ -90,7 +90,12 @@ impl Embedder {
});
}
Ok(Self { session, model })
drop(session);
drop(acquired);
Ok(Self {
session: loaded,
model,
})
}
pub fn model(&self) -> &ModelId {
@@ -111,8 +116,9 @@ impl Embedder {
}
}
let outputs = self
.session
let acquired = self.session.acquire()?;
let mut session = acquired.lock();
let outputs = session
.run(ort::inputs![
ort::value::Tensor::from_array(input).map_err(FaceError::Inference)?
])
+263
View File
@@ -0,0 +1,263 @@
//! TRACES: FR-CULL-8a
//! What a face's eyes are doing, and how the numbers behind it are read.
//!
//! Model-free: the models in [`crate::classify`] produce the numbers, and
//! everything that interprets them — the catalog's filter, the People
//! screen's label — comes through here, so a threshold lives in exactly one
//! place.
//!
//! # Seven numbers, one answer
//!
//! An eye classifier answers "open or closed" for whatever it is shown, and
//! it is shown three things it cannot answer for. **Dark glass**: over
//! sunglasses it answers anyway, confidently, for a state that cannot be
//! seen — so the reading carries P(sunglasses) from a classifier that looks
//! at the whole head, and that takes precedence. **A smear**: a soft eye is
//! not a closed one, but shown a blur the classifier says "closed" with the
//! same confidence it says anything, and on the reference library that was
//! the commonest wrong answer of all — small faces, motion, a proxy where
//! the native render should have been. So each eye carries how many source
//! pixels it spanned and how sharp the patch was, and an eye under either
//! floor is not asked. **A cheek**: a head turned far enough hides its far
//! eye, and the landmark contour of a hidden eye collapses to a sliver; an
//! eye much narrower than its partner is not asked either.
//!
//! The two eyes are kept apart rather than averaged. A wink is one eye
//! closed, and averaging it lands at 0.5 — the one value that says the least.
//! [`EyeState::Open`] requires every eye that *could be read* to be open;
//! a face with no readable eye is [`EyeState::Unreadable`], which is not a
//! blink and not open, and a filter for either leaves it alone.
/// One eye's numbers.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct Eye {
/// P(open), the classifier's sigmoid.
pub open: f32,
/// Source pixels across the eye box — [`crate::align::EyePatch::source_px`].
pub px: f32,
/// [`crate::align::EyePatch::sharpness`] of the patch the classifier saw.
pub sharpness: f32,
}
/// The numbers the models produced for one face.
///
/// Stored per face, nullable as a whole: a face indexed before the eye models
/// existed, or on a device without them, has no reading rather than a
/// reading of zeros.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct EyeReading {
/// The subject's **right** eye — image-left.
pub right: Eye,
/// The subject's **left** eye — image-right.
pub left: Eye,
/// P(the head wears sunglasses).
pub sunglasses: f32,
}
/// Above this an eye is open. The classifier's own decision point; its
/// training put the two classes either side of a sigmoid and this is where
/// the sigmoid crosses.
pub const EYES_OPEN_THRESHOLD: f32 = 0.5;
/// Above this the head wears sunglasses and the eye readings are moot.
pub const SUNGLASSES_THRESHOLD: f32 = 0.5;
/// Fewest source pixels across an eye box for the eye to be read.
///
/// The classifier was trained on eyes down to about a dozen pixels wide
/// (its reference footage averaged 15–21); below that the 40-pixel patch is
/// an interpolation of nothing, and the answer is noise that reads as
/// "closed". docs/faces.md §17.3 has the measurement behind the number.
pub const MIN_EYE_PX: f32 = 12.0;
/// Least [`Eye::sharpness`] for the eye to be read.
///
/// The same measure as the face's `min_sharpness`, over the eye patch, and
/// chosen the same way: the value under which the open-eyed faces of the
/// reference sample were being called closed. docs/faces.md §17.3.
pub const MIN_EYE_SHARPNESS: f32 = 0.02;
/// An eye narrower than this fraction of its partner is the far eye of a
/// turned head, out of view behind the nose, and is not read.
///
/// A landmark model's contour for a hidden eye collapses towards the nose.
/// Measured on twenty native renders of the reference library
/// (docs/faces.md §17.4): profiles put the far eye at 0.02–0.43 of the near
/// one, two three-quarter faces whose far eye read closed sat at 0.54, and
/// every face looking at the camera — winks included, since a shut eye's
/// box keeps its width — sat at 0.78 or more. 0.6 splits the gap.
pub const HIDDEN_EYE_RATIO: f32 = 0.6;
/// What the reading says, for a screen or a filter.
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum EyeState {
/// Every eye that could be read is open.
Open,
/// An eye that could be read is closed — a blink, or a wink.
Closed,
/// The eyes cannot be seen. Neither open nor closed, and a filter for
/// either leaves the face alone.
Sunglasses,
/// No eye was sharp enough, large enough and in view to read. Neither
/// open nor closed, like sunglasses, and left alone by every filter.
Unreadable,
}
impl Eye {
/// Whether this eye can be read at all: enough pixels, sharp enough,
/// and not the collapsed contour of a hidden eye — measured against
/// `other`, its partner.
pub fn readable(&self, other: &Eye) -> bool {
self.px >= MIN_EYE_PX
&& self.sharpness >= MIN_EYE_SHARPNESS
&& self.px >= other.px * HIDDEN_EYE_RATIO
}
}
impl EyeReading {
pub fn state(&self) -> EyeState {
if self.sunglasses >= SUNGLASSES_THRESHOLD {
return EyeState::Sunglasses;
}
let readable = [
self.right.readable(&self.left).then_some(self.right.open),
self.left.readable(&self.right).then_some(self.left.open),
];
let mut any = false;
for open in readable.into_iter().flatten() {
any = true;
if open < EYES_OPEN_THRESHOLD {
return EyeState::Closed;
}
}
if any {
EyeState::Open
} else {
EyeState::Unreadable
}
}
/// Whether this is a face a "no one blinking" filter should drop.
///
/// The filter's question, rather than [`EyeState`]'s four-way answer,
/// because the two differ on exactly the cases that matter: a face
/// behind sunglasses, or one whose eyes could not be read, is not open
/// — and it is not a blink either. Only [`EyeState::Closed`] is one.
pub fn is_blink(&self) -> bool {
self.state() == EyeState::Closed
}
}
impl EyeState {
/// The word the People screen puts on the face.
pub fn label(&self) -> &'static str {
match self {
EyeState::Open => "Eyes open",
EyeState::Closed => "Eyes closed",
EyeState::Sunglasses => "Sunglasses",
EyeState::Unreadable => "Eyes unclear",
}
}
}
#[cfg(test)]
mod tests {
use super::*;
fn eye(open: f32) -> Eye {
Eye {
open,
px: 40.0,
sharpness: 0.1,
}
}
fn reading(right: f32, left: f32, sunglasses: f32) -> EyeReading {
EyeReading {
right: eye(right),
left: eye(left),
sunglasses,
}
}
#[test]
fn both_eyes_open_is_open() {
assert_eq!(reading(0.9, 0.8, 0.1).state(), EyeState::Open);
assert!(!reading(0.9, 0.8, 0.1).is_blink());
}
/// A wink is not "eyes open": one eye closed lands the same place a
/// blink does, and a filter for "nobody blinking" should drop it.
#[test]
fn one_eye_closed_is_closed() {
assert_eq!(reading(0.9, 0.2, 0.1).state(), EyeState::Closed);
assert_eq!(reading(0.2, 0.9, 0.1).state(), EyeState::Closed);
assert!(reading(0.2, 0.9, 0.1).is_blink());
}
/// The whole reason the sunglasses number exists: whatever the eye
/// classifier says over dark glass, it is not a reading of the eyes.
#[test]
fn sunglasses_override_the_eye_readings_either_way() {
assert_eq!(reading(0.9, 0.9, 0.8).state(), EyeState::Sunglasses);
assert_eq!(reading(0.1, 0.1, 0.8).state(), EyeState::Sunglasses);
assert!(!reading(0.1, 0.1, 0.8).is_blink());
}
/// A soft or tiny eye is not asked; if neither can be, the face is
/// unreadable rather than closed.
#[test]
fn a_soft_or_tiny_eye_is_not_read() {
let mut r = reading(0.1, 0.9, 0.0);
r.right.sharpness = MIN_EYE_SHARPNESS / 2.0;
assert_eq!(r.state(), EyeState::Open, "the soft closed eye is ignored");
let mut r = reading(0.1, 0.9, 0.0);
r.right.px = MIN_EYE_PX - 1.0;
assert_eq!(r.state(), EyeState::Open, "the tiny closed eye is ignored");
let mut r = reading(0.1, 0.1, 0.0);
r.right.sharpness = 0.0;
r.left.px = 3.0;
assert_eq!(r.state(), EyeState::Unreadable);
assert!(!r.is_blink());
assert_eq!(r.state().label(), "Eyes unclear");
}
/// A profile: the far eye's contour collapses, and the sliver is not
/// read. The near eye still decides.
#[test]
fn a_turned_heads_collapsed_far_eye_is_not_read() {
let mut r = reading(0.05, 0.95, 0.0);
r.right.px = 40.0 * HIDDEN_EYE_RATIO - 1.0;
assert!(!r.right.readable(&r.left));
assert_eq!(r.state(), EyeState::Open);
let mut blink = reading(0.95, 0.05, 0.0);
blink.right.px = 40.0 * HIDDEN_EYE_RATIO - 1.0;
assert_eq!(blink.state(), EyeState::Closed);
// Both eyes narrow but alike is not a turned head: both count.
let mut small = reading(0.05, 0.95, 0.0);
small.right.px = 14.0;
small.left.px = 14.0;
assert_eq!(small.state(), EyeState::Closed);
}
#[test]
fn the_thresholds_are_inclusive_at_the_decision_point() {
assert_eq!(
reading(EYES_OPEN_THRESHOLD, EYES_OPEN_THRESHOLD, 0.0).state(),
EyeState::Open
);
assert_eq!(
reading(1.0, 1.0, SUNGLASSES_THRESHOLD).state(),
EyeState::Sunglasses
);
let mut r = reading(1.0, 1.0, 0.0);
r.right.px = MIN_EYE_PX;
r.left.px = MIN_EYE_PX;
r.right.sharpness = MIN_EYE_SHARPNESS;
assert!(r.right.readable(&r.left));
}
}
+263
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@@ -0,0 +1,263 @@
//! TRACES: FR-CULL-8a
//! Dense facial landmarks — InsightFace's `2d106det` (docs/faces.md §17.2).
//!
//! SCRFD's five points place a face; they do not place an eye. Its eye
//! point is loose enough that a window centred on it left the eye in a
//! corner on turned and smiling heads, and two model-free ways of
//! re-centring it made things worse. So a second model draws the eye's lid
//! contour, and the eye box is cut from that.
//!
//! **Why this one.** Three were measured on the same faces — MediaPipe Face
//! Mesh V2, PIPNet and this — and tied on what the eye classifier made of
//! their boxes (22 of 25 open eyes read open, against 19 from the SCRFD
//! point). This is the cheapest of the three by a wide margin (5 MB, 106
//! points, ~24 ms in tract), and it is under the grant the detector and
//! embedder already carry rather than a new one to read.
//!
//! # Pre-processing
//!
//! Ported from InsightFace's `landmark.py`: a square crop centred on the
//! detector box, 1.5× its longer edge, resized to 192; **RGB in 0..255**
//! (the graph carries its own `bn_data` normalisation, so `input_mean` is
//! 0 and `input_std` 1); 106 `(x, y)` in −1..1 mapped back through
//! `(p + 1) · 96`. The graph's batch dimension is the literal `None` and
//! is pinned to 1 by `tools/fix-face-model-shapes.sh`, like the embedder's.
//!
//! # The layout
//!
//! Checked by drawing the points on the reference faces rather than taken
//! from a diagram: the subject's right eye (image-left) is points 33–42,
//! the left 87–96, ten each round the lids.
use ndarray::Array4;
use crate::align::crop_box;
use crate::{FaceError, Pixels};
use dr_inference_engine::{Form, Model, Role};
/// The graph's input edge, in pixels.
pub const INPUT_EDGE: usize = 192;
/// How many points the model returns.
pub const POINTS: usize = 106;
/// The crop's edge as a multiple of the detector box's longer edge.
const CROP_SCALE: f32 = 1.5;
/// The span of the frame, in long-edge units, the packed form covers: a
/// quarter of the frame outside each edge.
pub const PACKED_RANGE: (f32, f32) = (-0.25, 1.25);
/// Bytes the packed form of one face's landmarks takes.
pub const PACKED_BYTES: usize = POINTS * 4;
/// Point indices of the subject's right eye's lid contour (image-left).
pub const RIGHT_EYE: [usize; 10] = [33, 34, 35, 36, 37, 38, 39, 40, 41, 42];
/// Point indices of the subject's left eye's lid contour (image-right).
pub const LEFT_EYE: [usize; 10] = [87, 88, 89, 90, 91, 92, 93, 94, 95, 96];
/// The 106 points of one face, in **source pixels**.
#[derive(Debug, Clone, PartialEq)]
pub struct Landmarks {
pub points: [(f32, f32); POINTS],
}
impl Landmarks {
/// Storage form: `106 × (x, y)` as little-endian **`u16` fixed point**
/// over the frame, 424 bytes.
///
/// Each coordinate is normalised by `long_edge` like the five points the
/// catalog already keeps, then mapped over [`PACKED_RANGE`] — a quarter
/// of the frame either side of it, because a landmark on a face at the
/// edge does land outside the image — onto 0..65535. That is 0.14 source
/// pixels on a 6000-pixel frame. `f16` would be the same size and worse:
/// its three significant figures near 1.0 are six pixels at that scale,
/// and the eye contour this is kept for is drawn to the pixel.
pub fn to_packed_bytes(&self, long_edge: f32) -> Vec<u8> {
let (lo, hi) = PACKED_RANGE;
let pack = |v: f32| -> [u8; 2] {
let t = ((v / long_edge - lo) / (hi - lo)).clamp(0.0, 1.0);
((t * 65535.0).round() as u16).to_le_bytes()
};
let mut out = Vec::with_capacity(POINTS * 4);
for &(x, y) in &self.points {
out.extend_from_slice(&pack(x));
out.extend_from_slice(&pack(y));
}
out
}
/// [`Self::to_packed_bytes`] read back, into source pixels of a frame
/// with this `long_edge`. `None` for a blob of the wrong length.
pub fn from_packed_bytes(bytes: &[u8], long_edge: f32) -> Option<Self> {
if bytes.len() != POINTS * 4 {
return None;
}
let (lo, hi) = PACKED_RANGE;
let unpack = |b: &[u8]| -> f32 {
let t = u16::from_le_bytes([b[0], b[1]]) as f32 / 65535.0;
(t * (hi - lo) + lo) * long_edge
};
let mut points = [(0.0_f32, 0.0_f32); POINTS];
for (i, p) in points.iter_mut().enumerate() {
let at = i * 4;
*p = (unpack(&bytes[at..at + 2]), unpack(&bytes[at + 2..at + 4]));
}
Some(Self { points })
}
/// The lid contour of the subject's right eye.
pub fn right_eye(&self) -> [(f32, f32); 10] {
RIGHT_EYE.map(|i| self.points[i])
}
/// The lid contour of the subject's left eye.
pub fn left_eye(&self) -> [(f32, f32); 10] {
LEFT_EYE.map(|i| self.points[i])
}
}
/// A loaded `2d106det` graph.
pub struct Landmarker {
session: Model,
}
impl Landmarker {
pub fn from_path(path: impl AsRef<std::path::Path>) -> Result<Self, FaceError> {
let bytes = std::fs::read(path).map_err(FaceError::ModelRead)?;
Self::from_bytes(&bytes)
}
pub fn from_bytes(bytes: &[u8]) -> Result<Self, FaceError> {
let model = dr_inference_engine::open(Role::Landmarks, Form::F32, bytes)?;
let acquired = model.acquire()?;
let session = acquired.lock();
let input = session.inputs().first().ok_or(FaceError::WrongModel {
expected: "2d106det",
detail: "model has no inputs".into(),
})?;
let shape: Option<Vec<i64>> = input.dtype().tensor_shape().map(|s| s.to_vec());
let want = [1, 3, INPUT_EDGE as i64, INPUT_EDGE as i64];
if shape.as_deref() != Some(&want[..]) {
return Err(FaceError::WrongModel {
expected: "2d106det",
detail: format!(
"input '{}' is {:?}, expected {:?} (batch pinned to 1)",
input.name(),
shape,
want
),
});
}
let out = session.outputs().first().ok_or(FaceError::WrongModel {
expected: "2d106det",
detail: "model has no outputs".into(),
})?;
let last: Option<i64> = out.dtype().tensor_shape().and_then(|d| d.last().copied());
if last != Some((POINTS * 2) as i64) {
return Err(FaceError::WrongModel {
expected: "2d106det",
detail: format!(
"output '{}' is {:?}-wide, expected {}",
out.name(),
last,
POINTS * 2
),
});
}
drop(session);
drop(acquired);
Ok(Self { session: model })
}
/// The landmarks of the face in `bbox` — `(x0, y0, x1, y1)` in source
/// pixels, the detector's box — read from the source.
///
/// `None` for a box with no area or a buffer that is not the size it
/// claims, as every crop here.
pub fn landmarks(
&mut self,
px: Pixels<'_>,
width: usize,
height: usize,
bbox: (f32, f32, f32, f32),
) -> Result<Option<Landmarks>, FaceError> {
let (w, h) = (bbox.2 - bbox.0, bbox.3 - bbox.1);
let side = w.max(h) * CROP_SCALE;
let (cx, cy) = ((bbox.0 + bbox.2) / 2.0, (bbox.1 + bbox.3) / 2.0);
let (x0, y0) = (cx - side / 2.0, cy - side / 2.0);
let Some(crop) = crop_box(
px,
width,
height,
(x0, y0, side, side),
INPUT_EDGE,
INPUT_EDGE,
) else {
return Ok(None);
};
let e = INPUT_EDGE;
let mut input = Array4::<f32>::zeros((1, 3, e, e));
for y in 0..e {
for x in 0..e {
for c in 0..3 {
input[[0, c, y, x]] = crop[(y * e + x) * 3 + c] * 255.0;
}
}
}
let acquired = self.session.acquire()?;
let mut session = acquired.lock();
let outputs = session
.run(ort::inputs![
ort::value::Tensor::from_array(input).map_err(FaceError::Inference)?
])
.map_err(FaceError::Inference)?;
let (_, data) = outputs[0]
.try_extract_tensor::<f32>()
.map_err(FaceError::Inference)?;
if data.len() < POINTS * 2 {
return Err(FaceError::WrongModel {
expected: "2d106det",
detail: format!("got {} values, expected {}", data.len(), POINTS * 2),
});
}
// −1..1 in the crop → crop pixels → source pixels.
let scale = side / e as f32;
let half = e as f32 / 2.0;
let mut points = [(0.0_f32, 0.0_f32); POINTS];
for (i, p) in points.iter_mut().enumerate() {
let (u, v) = ((data[2 * i] + 1.0) * half, (data[2 * i + 1] + 1.0) * half);
*p = (x0 + u * scale, y0 + v * scale);
}
Ok(Some(Landmarks { points }))
}
}
#[cfg(test)]
mod tests {
use super::*;
/// Packed and unpacked, every point comes back within a fifth of a
/// source pixel on a 6000-pixel frame — including one outside the
/// image, which a face at the edge does produce.
#[test]
fn dense_landmarks_round_trip_through_their_packed_bytes() {
let mut points = [(0.0_f32, 0.0_f32); POINTS];
for (i, p) in points.iter_mut().enumerate() {
*p = (i as f32 * 37.3 - 200.0, 5900.0 - i as f32 * 11.1);
}
let lm = Landmarks { points };
let bytes = lm.to_packed_bytes(6000.0);
assert_eq!(bytes.len(), PACKED_BYTES);
assert_eq!(PACKED_BYTES, 424);
let back = Landmarks::from_packed_bytes(&bytes, 6000.0).unwrap();
for (a, b) in lm.points.iter().zip(back.points.iter()) {
assert!((a.0 - b.0).abs() < 0.2, "{} vs {}", a.0, b.0);
assert!((a.1 - b.1).abs() < 0.2, "{} vs {}", a.1, b.1);
}
assert!(Landmarks::from_packed_bytes(&bytes[..100], 6000.0).is_none());
}
}
+33 -19
View File
@@ -1,8 +1,10 @@
//! Faces and identity (S14, docs/faces.md).
//!
//! Two models, run over the proxy tier, producing per face a box, five
//! Two models, run over the native render, producing per face a box, five
//! landmarks, a confidence and a 512-d embedding (FR-CULL-8) — and then the
//! arithmetic that turns embeddings into people (FR-CULL-9, FR-CULL-10).
//! arithmetic that turns embeddings into people (FR-CULL-9, FR-CULL-10). Two
//! more, optional, read each face's eyes and whether sunglasses hide them
//! (FR-CULL-8a, [`classify`] and [`eyes`]).
//!
//! Like `dr-segment`, this crate is **device-free**: no GPU adapter, no
//! Slint, nothing that needs a display. Unlike `dr-segment`, it carries **no
@@ -20,7 +22,8 @@
//! runtime; this crate takes bytes and never fetches anything.
//!
//! docs/faces.md §2 is the full reading, including what would have to change
//! for that to stop being true.
//! for that to stop being true. The eye-state models are the exception: MIT,
//! weights and all, and shipped in `models/face/` (docs/faces.md §17).
//!
//! # Why the runtime is split behind a feature
//!
@@ -34,14 +37,20 @@
pub mod align;
pub mod assign;
pub mod calibrate;
#[cfg(feature = "inference")]
pub mod classify;
pub mod cluster;
#[cfg(feature = "inference")]
pub mod detect;
#[cfg(feature = "inference")]
pub mod embed;
pub mod embedding;
pub mod eyes;
#[cfg(feature = "inference")]
pub mod landmarks;
pub mod naming;
pub mod neighbours;
pub mod references;
/// Smallest long edge a face crop may be sampled from.
///
@@ -65,10 +74,13 @@ pub mod neighbours;
pub const MIN_CROP_EDGE: u32 = 1025;
pub use align::{
warp, warp_pixels, Aligned112, Pixels, Similarity, ALIGNED_EDGE, ARCFACE_TEMPLATE,
crop_box, eye_box, eye_patch, head_views, warp, warp_pixels, Aligned112, EyePatch, HeadViews,
Pixels, Similarity, ALIGNED_EDGE, ARCFACE_TEMPLATE,
};
pub use assign::{identity_shares, RIVAL_FLOOR, TOP_MATCHES};
pub use calibrate::{Calibration, Pairs, ReliabilityBand};
#[cfg(feature = "inference")]
pub use classify::{EyeClassifier, EyeModels, SunglassesClassifier};
pub use cluster::{
cluster, cluster_scored, split, Candidate, Cluster, Grouping, DEFAULT_MERGE_PROBABILITY,
};
@@ -79,6 +91,12 @@ pub use embed::{Embedded, Embedder};
pub use embedding::{
in_gallery, read_f16_bytes, Embedding, ModelId, EMBEDDING_DIM, MIN_GALLERY_QUALITY,
};
pub use eyes::{
Eye, EyeReading, EyeState, EYES_OPEN_THRESHOLD, HIDDEN_EYE_RATIO, MIN_EYE_PX,
MIN_EYE_SHARPNESS, SUNGLASSES_THRESHOLD,
};
#[cfg(feature = "inference")]
pub use landmarks::{Landmarker, Landmarks};
pub use naming::{name_for_instance, name_instances, NamedFace};
/// What can go wrong between an image and a face.
@@ -107,25 +125,21 @@ pub enum FaceError {
ImageShape { expected: usize, got: usize },
}
/// Install tract as `ort`'s backend.
///
/// Idempotent, and it must happen before any other `ort` call: with
/// `alternative-backend` there is no linked runtime to fall back on, so an
/// un-set API is a panic rather than a slow path. Same helper as
/// `dr-segment::semantic`, for the same reason.
#[cfg(feature = "inference")]
pub(crate) fn install_backend() {
use std::sync::Once;
static ONCE: Once = Once::new();
ONCE.call_once(|| {
let _ = ort::set_api(ort_tract::api());
});
impl From<dr_inference_engine::Error> for FaceError {
fn from(e: dr_inference_engine::Error) -> Self {
match e {
dr_inference_engine::Error::Inference(e) => FaceError::Inference(e),
dr_inference_engine::Error::Io(e) => FaceError::ModelRead(e),
}
}
}
/// [`install_backend`] for the M1 probe example, which drives `ort` directly
/// rather than through [`detect::Detector`] so it can report the raw error.
/// Make sure `ort` has a backend, for the M1 probe example, which drives
/// `ort` directly rather than through [`detect::Detector`] so it can report
/// the raw error. Every other path goes through `dr-inference-engine`.
#[cfg(feature = "inference")]
#[doc(hidden)]
pub fn install_backend_for_probe() {
install_backend();
dr_inference_engine::ensure_runtime();
}
+232
View File
@@ -0,0 +1,232 @@
//! TRACES: FR-CULL-10 | NFR-P9
//! Which of a person's faces stand for them in a grouping pass.
//!
//! # Why not all of them
//!
//! Every face the user has ruled on enters [`crate::cluster`] as an anchor,
//! and the pass compares every face against every other
//! ([`crate::neighbours`] is exhaustive by design). So a person with 750
//! confirmed faces costs 750 comparisons against each of the library's other
//! faces, and the cost of naming a library well grows with how well it is
//! named: a fully confirmed library of 25,000 faces spends almost the whole
//! scan re-comparing faces whose identity is already settled against each
//! other.
//!
//! Most of those comparisons say nothing new. A person's confirmed faces are
//! heavily redundant — thirty frames from one afternoon are one point of
//! view, not thirty — and a new face that matches one of them matches the
//! others too. What a new face needs to be measured against is the person's
//! *range*: the angles, ages and lights they have been photographed in, each
//! represented once.
//!
//! # The choice: the most diverse of the good ones
//!
//! Two rules, in order.
//!
//! **Good enough to vouch.** Only faces whose raw embedding was at least
//! [`MIN_REFERENCE_QUALITY`] long are eligible — a stricter floor than the
//! gallery's ([`crate::embedding::MIN_GALLERY_QUALITY`]), because a reference
//! is asked to speak *for* a person rather than merely be admitted to the
//! comparison. A face whose length was never recorded is admitted, as it is
//! everywhere else: a rule that cannot be checked admits rather than excludes.
//!
//! **As far apart as possible.** From the eligible pool, up to
//! [`MAX_REFERENCES`] faces are chosen to maximise the volume they span —
//! the determinant of their Gram matrix — greedily: start from the longest
//! vector, and at each step add the face with the largest component
//! orthogonal to everything chosen so far. That is Gram–Schmidt with a
//! pivot, and the product of the squared residuals it picks *is* the
//! determinant, so the greedy step is the exact greedy on the objective.
//! The effect is that a near-duplicate of a chosen face has almost no
//! residual and is passed over, while the one profile shot among two
//! hundred frontal frames is taken early.
//!
//! What is not chosen still belongs to the person. Those faces keep their
//! confirmations and are not touched by the pass; they are simply not
//! compared, which is the whole saving.
/// The most faces that stand for one person.
///
/// A hundred is far more points of view than a person has. What it bounds
/// is the cost: with every person at the cap, a scan against the named part
/// of a library is `people × 100` comparisons per face rather than
/// `confirmations`, and the two part company as soon as a library is used.
pub const MAX_REFERENCES: usize = 100;
/// The shortest raw embedding that may stand for a person.
///
/// One above the gallery floor: a reference vouches for someone, and the
/// margin keeps the faces that only just cleared the gallery — the ones
/// nearest the middle of the sphere — out of the set that speaks for a
/// person.
pub const MIN_REFERENCE_QUALITY: f32 = 15.0;
/// Whether a face of this quality may stand for a person.
///
/// `None` is "never measured" and is admitted, as in
/// [`crate::embedding::in_gallery`].
pub fn eligible(quality: Option<f32>) -> bool {
quality.is_none_or(|q| q >= MIN_REFERENCE_QUALITY)
}
/// Choose which of one person's faces stand for them.
///
/// `embeddings` and `quality` are one entry per face, the embeddings unit
/// length and all of one dimension. Returns the indices chosen, in the order
/// chosen — the first is the longest eligible vector, and each after it is
/// the one furthest from the span of those before. Every eligible face is
/// returned when there are `max` or fewer of them, so a person under the
/// cap loses nothing.
///
/// Deterministic: equal residuals break on the longer vector, then the lower
/// index, so two devices holding the same faces choose the same references
/// and group the same way (`cluster::clustering_is_deterministic`).
pub fn select(embeddings: &[&[f32]], quality: &[Option<f32>], max: usize) -> Vec<usize> {
debug_assert_eq!(embeddings.len(), quality.len());
let mut pool: Vec<usize> = (0..embeddings.len())
.filter(|&i| eligible(quality[i]))
.collect();
if pool.len() <= max {
return pool;
}
// Longest first, so the seed is the pool's front and a tie on residual
// resolves to the earlier position. A missing reading ranks below any
// measured one for this purpose only: it is admitted, but a face that
// was measured and found long is the better seed.
pool.sort_by(|&a, &b| {
let qa = quality[a].unwrap_or(0.0);
let qb = quality[b].unwrap_or(0.0);
qb.total_cmp(&qa).then(a.cmp(&b))
});
// Residuals: what remains of each pool vector outside the span of the
// chosen ones. Copied, since they are rewritten in place.
let mut residual: Vec<Vec<f32>> = pool.iter().map(|&i| embeddings[i].to_vec()).collect();
let mut taken = vec![false; pool.len()];
let mut chosen = Vec::with_capacity(max);
while chosen.len() < max {
// The face with the most left outside the span. The seed is the
// pool's front by construction: every unit vector has the same
// residual before anything is chosen, up to rounding, and rounding
// is not a reason to prefer one. After that `> best` and not `>=`,
// so a genuine tie keeps the earlier (longer) candidate.
let mut pick = None;
let mut best = 0.0_f32;
if chosen.is_empty() {
pick = Some(0);
best = residual[0].iter().map(|x| x * x).sum();
} else {
for (k, r) in residual.iter().enumerate() {
if taken[k] {
continue;
}
let n2: f32 = r.iter().map(|x| x * x).sum();
if n2 > best {
best = n2;
pick = Some(k);
}
}
}
// Nothing left outside the span: every remaining face is a
// combination of the chosen ones and adds no volume.
let Some(k) = pick.filter(|_| best > 1e-6) else {
break;
};
taken[k] = true;
chosen.push(pool[k]);
// Project the chosen direction out of every remaining residual.
let inv = best.sqrt().recip();
let q: Vec<f32> = residual[k].iter().map(|x| x * inv).collect();
for (j, r) in residual.iter_mut().enumerate() {
if taken[j] {
continue;
}
let d: f32 = r.iter().zip(&q).map(|(a, b)| a * b).sum();
for (x, y) in r.iter_mut().zip(&q) {
*x -= d * y;
}
}
}
chosen
}
#[cfg(test)]
mod tests {
use super::*;
fn unit(v: &[f32]) -> Vec<f32> {
let n = v.iter().map(|x| x * x).sum::<f32>().sqrt();
v.iter().map(|x| x / n).collect()
}
#[test]
fn a_person_under_the_cap_keeps_every_eligible_face() {
let e = [unit(&[1.0, 0.0]), unit(&[0.0, 1.0]), unit(&[1.0, 1.0])];
let refs: Vec<&[f32]> = e.iter().map(Vec::as_slice).collect();
let q = [Some(20.0), None, Some(16.0)];
assert_eq!(select(&refs, &q, 100), vec![0, 1, 2]);
}
#[test]
fn a_short_vector_never_stands_for_a_person() {
let e = [unit(&[1.0, 0.0]), unit(&[0.0, 1.0])];
let refs: Vec<&[f32]> = e.iter().map(Vec::as_slice).collect();
let q = [Some(20.0), Some(MIN_REFERENCE_QUALITY - 0.01)];
assert_eq!(select(&refs, &q, 100), vec![0]);
}
/// Two hundred frames from one afternoon and one profile shot: the
/// profile is the second choice, not the two-hundred-and-first.
#[test]
fn the_odd_one_out_is_chosen_before_any_duplicate() {
let mut e: Vec<Vec<f32>> = Vec::new();
let mut q = Vec::new();
for i in 0..200 {
// Near-duplicates of one direction, with a little noise.
let t = (i as f32) * 1e-3;
e.push(unit(&[1.0, t, t * 0.5]));
q.push(Some(20.0 + (i % 7) as f32));
}
e.push(unit(&[0.0, 0.0, 1.0]));
q.push(Some(16.0));
let refs: Vec<&[f32]> = e.iter().map(Vec::as_slice).collect();
let chosen = select(&refs, &q, 3);
assert_eq!(chosen.len(), 3);
assert_eq!(
chosen[1], 200,
"the profile shot was not second: {chosen:?}"
);
// Seeded on the longest vector.
assert_eq!(q[chosen[0]], Some(26.0));
}
/// Faces inside the span of the chosen ones add no volume and are not
/// taken to fill the cap.
#[test]
fn the_cap_is_not_filled_from_inside_the_span() {
let e = [
unit(&[1.0, 0.0]),
unit(&[0.0, 1.0]),
unit(&[1.0, 1.0]),
unit(&[2.0, -1.0]),
];
let refs: Vec<&[f32]> = e.iter().map(Vec::as_slice).collect();
let q = [Some(20.0); 4];
assert_eq!(select(&refs, &q, 3).len(), 2);
}
#[test]
fn the_choice_is_deterministic() {
let e: Vec<Vec<f32>> = (0..50)
.map(|i| {
let a = (i as f32) * 0.37;
unit(&[a.cos(), a.sin(), (a * 3.0).sin(), 0.2])
})
.collect();
let refs: Vec<&[f32]> = e.iter().map(Vec::as_slice).collect();
let q = vec![Some(18.0); 50];
assert_eq!(select(&refs, &q, 5), select(&refs, &q, 5));
}
}
+5
View File
@@ -7,6 +7,11 @@ license.workspace = true
[dependencies]
dr-types.workspace = true
# The merge's geometry (FR-MRG-10): rotations, the focal length and the
# projections, solved on proxies by dr-pano and consumed here per chunk. The
# geometry alone — no keypoint model, no runtime — which is what the
# workspace entry turns off.
dr-pano.workspace = true
dr-decode.workspace = true
dr-pipeline.workspace = true
# The watershed's pixel passes are here because they are shaders; everything
+233 -7
View File
@@ -101,6 +101,16 @@ pub struct AdjustPass {
/// switched on does not build a pipeline layout mid-frame.
linear_bind_group_layout: wgpu::BindGroupLayout,
linear_pipeline_layout: wgpu::PipelineLayout,
/// TRACES: FR-MRG-2
/// A third layout, writing `rgba32float`, for the camera-space tap a
/// merge reads (`OutputMode::CameraLinear`). Same reasoning as the
/// linear one: the format is in the layout, so a format is a layout.
camera_bind_group_layout: wgpu::BindGroupLayout,
camera_pipeline_layout: wgpu::PipelineLayout,
/// The camera-space texture the last `render_camera_linear` wrote.
/// Separate from `targets`: a different format, and a merge reads it
/// back or samples it while the display targets go on being swapped.
camera_target: Option<Target>,
/// TRACES: FR-DEV-3d
/// What the linear intermediate currently holds, and at what size.
///
@@ -303,6 +313,11 @@ impl AdjustPass {
pub const FORMAT: wgpu::TextureFormat = wgpu::TextureFormat::Rgba8Unorm;
/// TRACES: FR-MRG-2
/// The camera-space tap's format: full precision, because what it holds
/// is written back as a RAW at the sensor's own scale (FR-MRG-3).
pub const CAMERA_FORMAT: wgpu::TextureFormat = wgpu::TextureFormat::Rgba32Float;
pub fn new(ctx: &GpuContext) -> Self {
let bind_group_layout = Self::layout_writing(ctx, Self::FORMAT, "adjust-bgl");
@@ -330,6 +345,15 @@ impl AdjustPass {
bind_group_layouts: &[Some(&linear_bind_group_layout)],
immediate_size: 0,
});
let camera_bind_group_layout =
Self::layout_writing(ctx, Self::CAMERA_FORMAT, "adjust-camera-bgl");
let camera_pipeline_layout =
ctx.device
.create_pipeline_layout(&wgpu::PipelineLayoutDescriptor {
label: Some("adjust-camera-layout"),
bind_group_layouts: &[Some(&camera_bind_group_layout)],
immediate_size: 0,
});
// A 1x1 single-layer mask, bound when the edit has no local
// adjustments. The generated shader never samples it — no layer block
@@ -412,6 +436,9 @@ impl AdjustPass {
detail: DetailRunner::new(ctx),
linear_bind_group_layout,
linear_pipeline_layout,
camera_bind_group_layout,
camera_pipeline_layout,
camera_target: None,
colour_key: None,
colour_dispatches: 0,
detail_dispatches: 0,
@@ -549,6 +576,7 @@ impl AdjustPass {
let layout = match shader.output_mode {
OutputMode::Encoded => &self.pipeline_layout,
OutputMode::LinearWorking => &self.linear_pipeline_layout,
OutputMode::CameraLinear => &self.camera_pipeline_layout,
};
let pipeline =
@@ -1126,28 +1154,206 @@ impl AdjustPass {
self.copy_output()
}
/// TRACES: FR-MRG-2
/// Render the camera-space tap: the source after its lens warp and
/// nothing else, at full precision.
///
/// `shader` must come from `EditGraph::compose_camera_linear` — it is
/// refused otherwise, for the reason `render_masked` refuses a linear
/// one: the storage format is in the layout. The profile uniforms are
/// filled neutral here rather than from the source, which is the whole
/// point of the mode (`OutputMode::CameraLinear`): unit white balance,
/// identity matrix, base curve off. The non-linear flag is kept, so a
/// JPEG source is still linearised — camera space for a JPEG is the
/// decoded values made linear, which is the best that exists.
///
/// The texture stays on the device for a merge's warp to sample; see
/// [`Self::camera_texture`] and [`Self::read_camera_linear`].
pub fn render_camera_linear(
&mut self,
source: &DemosaicedImage,
shader: &ComposedShader,
width: u32,
height: u32,
) -> Result<&wgpu::Texture, GpuError> {
if shader.output_mode != OutputMode::CameraLinear {
return Err(GpuError::ShaderCompilation(
"render_camera_linear takes the shader from EditGraph::compose_camera_linear \
and no other; this one writes a different format"
.into(),
));
}
self.colour_key = None;
let (width, height) = (width.max(1), height.max(1));
self.ensure_camera_target(width, height);
let mut uniforms = Self::fused_uniforms(source, shader);
// Neutral profile: the numbers the sensor produced, and only those.
let non_linear = uniforms[15];
uniforms[0..4].copy_from_slice(&[1.0, 0.0, 0.0, 0.0]);
uniforms[4..8].copy_from_slice(&[0.0, 1.0, 0.0, 0.0]);
uniforms[8..12].copy_from_slice(&[0.0, 0.0, 1.0, 0.0]);
uniforms[12..16].copy_from_slice(&[1.0, 1.0, 1.0, non_linear]);
let b = dr_pipeline::BASE_CURVE_UNIFORM_OFFSET;
uniforms[b + 10] = 0.0;
let params_buf = self
.ctx
.device
.create_buffer_init(&wgpu::util::BufferInitDescriptor {
label: Some("adjust-camera-params"),
contents: bytemuck::cast_slice(&uniforms),
usage: wgpu::BufferUsages::UNIFORM,
});
let _ = self.pipeline(shader)?;
let pipeline = self
.cache
.get(&shader.structure_hash)
.expect("compiled above");
let target = self.camera_target.as_ref().expect("ensured above");
let bind_group = self
.ctx
.device
.create_bind_group(&wgpu::BindGroupDescriptor {
label: Some("adjust-camera-bg"),
layout: &self.camera_bind_group_layout,
entries: &[
wgpu::BindGroupEntry {
binding: 0,
resource: wgpu::BindingResource::TextureView(source.view()),
},
wgpu::BindGroupEntry {
binding: 1,
resource: params_buf.as_entire_binding(),
},
wgpu::BindGroupEntry {
binding: 2,
resource: wgpu::BindingResource::TextureView(&target.view),
},
wgpu::BindGroupEntry {
binding: 3,
resource: wgpu::BindingResource::TextureView(&self.empty_masks),
},
wgpu::BindGroupEntry {
binding: 4,
resource: wgpu::BindingResource::TextureView(self.film_curves_view()),
},
wgpu::BindGroupEntry {
binding: 5,
resource: wgpu::BindingResource::TextureView(self.film_lut_view()),
},
],
});
let mut enc = self
.ctx
.device
.create_command_encoder(&wgpu::CommandEncoderDescriptor {
label: Some("adjust-camera-encoder"),
});
{
let mut pass = enc.begin_compute_pass(&wgpu::ComputePassDescriptor {
label: Some("adjust-camera-pass"),
timestamp_writes: None,
});
pass.set_pipeline(pipeline);
pass.set_bind_group(0, &bind_group, &[]);
pass.dispatch_workgroups(width.div_ceil(8), height.div_ceil(8), 1);
}
self.ctx.queue.submit(Some(enc.finish()));
self.colour_dispatches += 1;
Ok(&self.camera_target.as_ref().expect("ensured above").texture)
}
/// The camera-space texture, if one has been rendered.
pub fn camera_texture(&self) -> Option<&wgpu::Texture> {
self.camera_target.as_ref().map(|t| &t.texture)
}
/// TRACES: FR-MRG-2
/// Read the camera-space tap back: tightly packed RGBA `f32`,
/// `width * height * 4` values, alpha 1.0 everywhere.
pub fn read_camera_linear(&self) -> Result<(Vec<f32>, u32, u32), GpuError> {
let Some(target) = self.camera_target.as_ref() else {
return Err(GpuError::Readback("no camera-space render yet".into()));
};
let (bytes, w, h) = Self::copy_texture(&self.ctx, &target.texture, w_h(target), 16)?;
let floats: Vec<f32> = bytes
.chunks_exact(4)
.map(|b| f32::from_le_bytes([b[0], b[1], b[2], b[3]]))
.collect();
Ok((floats, w, h))
}
fn ensure_camera_target(&mut self, width: u32, height: u32) {
if self
.camera_target
.as_ref()
.is_some_and(|t| t.width == width && t.height == height)
{
return;
}
let texture = self.ctx.device.create_texture(&wgpu::TextureDescriptor {
label: Some("adjust-camera-output"),
size: wgpu::Extent3d {
width,
height,
depth_or_array_layers: 1,
},
mip_level_count: 1,
sample_count: 1,
dimension: wgpu::TextureDimension::D2,
format: Self::CAMERA_FORMAT,
// Written by compute, sampled by a merge's warp, copied out for
// the CPU. Never handed to the compositor, so no RENDER_ATTACHMENT.
usage: wgpu::TextureUsages::STORAGE_BINDING
| wgpu::TextureUsages::TEXTURE_BINDING
| wgpu::TextureUsages::COPY_SRC,
view_formats: &[],
});
let view = texture.create_view(&Default::default());
self.camera_target = Some(Target {
texture,
view,
width,
height,
});
}
/// The transfer itself.
fn copy_output(&self) -> Result<(Vec<u8>, u32, u32), GpuError> {
let Some(target) = self.targets[self.current].as_ref() else {
return Err(GpuError::Readback("nothing rendered yet".into()));
};
let (w, h) = (target.width, target.height);
Self::copy_texture(&self.ctx, &target.texture, w_h(target), 4)
}
let unpadded = w * 4;
/// Copy a whole texture to the CPU, `bytes_per_pixel` wide, rows
/// unpadded. Shared by the display readback and the camera-space one.
fn copy_texture(
ctx: &GpuContext,
texture: &wgpu::Texture,
(w, h): (u32, u32),
bytes_per_pixel: u32,
) -> Result<(Vec<u8>, u32, u32), GpuError> {
let unpadded = w * bytes_per_pixel;
let align = wgpu::COPY_BYTES_PER_ROW_ALIGNMENT;
let padded = unpadded.div_ceil(align) * align;
let buf = self.ctx.device.create_buffer(&wgpu::BufferDescriptor {
let buf = ctx.device.create_buffer(&wgpu::BufferDescriptor {
label: Some("adjust-readback"),
size: (padded * h) as u64,
usage: wgpu::BufferUsages::COPY_DST | wgpu::BufferUsages::MAP_READ,
mapped_at_creation: false,
});
let mut enc = self.ctx.device.create_command_encoder(&Default::default());
let mut enc = ctx.device.create_command_encoder(&Default::default());
enc.copy_texture_to_buffer(
wgpu::TexelCopyTextureInfo {
texture: &target.texture,
texture,
mip_level: 0,
origin: wgpu::Origin3d::ZERO,
aspect: wgpu::TextureAspect::All,
@@ -1166,7 +1372,7 @@ impl AdjustPass {
depth_or_array_layers: 1,
},
);
self.ctx.queue.submit(Some(enc.finish()));
ctx.queue.submit(Some(enc.finish()));
let slice = buf.slice(..);
let (tx, rx) = std::sync::mpsc::channel();
@@ -1177,7 +1383,7 @@ impl AdjustPass {
// Polled rather than parked, and bounded rather than spun forever —
// see `readback::await_mapping`, which the histogram's own transfer
// shares for exactly the same reasons.
await_mapping(&self.ctx, &rx)?;
await_mapping(ctx, &rx)?;
let data = slice.get_mapped_range();
let mut out = Vec::with_capacity((unpadded * h) as usize);
@@ -1191,6 +1397,10 @@ impl AdjustPass {
}
}
fn w_h(t: &Target) -> (u32, u32) {
(t.width, t.height)
}
/// Number the lines of generated source, so a compiler error can be located.
pub(crate) fn numbered(src: &str) -> String {
src.lines()
@@ -1242,6 +1452,10 @@ mod tests {
// rather than about a camera's colour response.
color_matrix: Some([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]),
base_curve: BaseCurve::IDENTITY,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
@@ -1442,6 +1656,10 @@ mod tests {
wb_coeffs: [1.0, 1.0, 1.0, 1.0],
color_matrix: Some([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]),
base_curve: BaseCurve::IDENTITY,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
@@ -1969,6 +2187,10 @@ mod tests {
wb_coeffs: [1.0, 1.0, 1.0, 1.0],
color_matrix: Some([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]),
base_curve: BaseCurve::IDENTITY,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
@@ -2069,6 +2291,10 @@ mod tests {
wb_coeffs: [1.0, 1.0, 1.0, 1.0],
color_matrix: Some([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]),
base_curve: BaseCurve::IDENTITY,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
+232
View File
@@ -250,6 +250,135 @@ impl DemosaicedImage {
}
}
impl DemosaicedImage {
/// TRACES: FR-MRG-3
/// A source that is already RGB in camera space: a linear DNG, which is
/// what a merge writes. No demosaic; the samples are normalised by the
/// file's black and white levels exactly as the demosaic kernel would
/// normalise a photosite, and everything else — the matrix, the
/// balance, the body's base curve — is carried through as for a CFA
/// file, because the composite is developed as one photograph from the
/// body that took its sources.
pub fn from_linear_rgb16(ctx: &GpuContext, raw: &RawImage) -> Result<Self, GpuError> {
let (width, height) = (raw.crop.width.max(1), raw.crop.height.max(1));
let limits = ctx.device.limits();
if width > limits.max_texture_dimension_2d || height > limits.max_texture_dimension_2d {
return Err(GpuError::TooLarge(format!(
"{width}×{height} exceeds the device limit of {}",
limits.max_texture_dimension_2d
)));
}
let stride = raw.width as usize * 3;
let expected = raw.height as usize * stride;
if raw.data.len() < expected {
return Err(GpuError::TooLarge(format!(
"{} samples is short of the {expected} a {}×{} RGB image needs",
raw.data.len(),
raw.width,
raw.height
)));
}
let black = black_per_cell(raw);
let inv = inv_range_per_cell(raw);
// Per channel rather than per CFA cell: R, G, B are the first three.
let mut half: Vec<u16> = Vec::with_capacity((width * height * 4) as usize);
for y in 0..height as usize {
let row = (raw.crop.y as usize + y) * stride + raw.crop.x as usize * 3;
for x in 0..width as usize {
let p = &raw.data[row + x * 3..row + x * 3 + 3];
for c in 0..3 {
let v = (f32::from(p[c]) - black[c]) * inv[c];
half.push(f32_to_f16_bits_unclamped(v));
}
half.push(f32_to_f16_bits(1.0));
}
}
let texture = ctx.device.create_texture_with_data(
&ctx.queue,
&wgpu::TextureDescriptor {
label: Some("linear-rgb-source"),
size: wgpu::Extent3d {
width,
height,
depth_or_array_layers: 1,
},
mip_level_count: 1,
sample_count: 1,
dimension: wgpu::TextureDimension::D2,
format: Self::FORMAT,
usage: wgpu::TextureUsages::TEXTURE_BINDING | wgpu::TextureUsages::COPY_SRC,
view_formats: &[],
},
wgpu::util::TextureDataOrder::LayerMajor,
bytemuck::cast_slice(&half),
);
let view = texture.create_view(&Default::default());
Ok(Self {
texture,
view,
width,
height,
color_matrix: raw.color_matrix.unwrap_or(IDENTITY_3X3),
as_shot_wb: [raw.wb_coeffs[0], raw.wb_coeffs[1], raw.wb_coeffs[2]],
base_curve: raw.base_curve,
non_linear: false,
})
}
}
/// Convert an f32 to half-precision bits, the general case: sign,
/// subnormals, round-to-nearest-even, saturation at the largest finite.
///
/// `f32_to_f16_bits` below is the 8-bit special case and says why it can
/// be; this one exists because a linear DNG is not that case. A 14-bit
/// sensor's least significant step, normalised, is 6.1e-5 — right at f16's
/// smallest normal (6.1e-5) — so the deepest shadows of a composite land
/// in the subnormal range, and rounding them to zero would crush the
/// shadows of exactly the file that was written to keep them. Values below
/// zero (black subtraction on a noisy photosite) and above one (a highlight
/// past the white level) are legitimate and kept.
fn f32_to_f16_bits_unclamped(v: f32) -> u16 {
let bits = v.to_bits();
let sign = ((bits >> 16) & 0x8000) as u16;
let exp = ((bits >> 23) & 0xFF) as i32;
let mant = bits & 0x7F_FFFF;
if exp == 0xFF {
// Infinity or NaN: a NaN sample is a decode fault; store the largest
// finite rather than propagate it through a blend.
return sign | 0x7BFF;
}
let e = exp - 127 + 15;
if e >= 0x1F {
return sign | 0x7BFF;
}
if e <= 0 {
// Subnormal in f16 (or underflow). Shift the full mantissa with its
// implicit bit right by the deficit, rounding to nearest even.
if e < -10 {
return sign;
}
let m = (mant | 0x80_0000) >> (1 - e);
let shift = 13;
let rounded = round_shift(m, shift);
return sign | rounded as u16;
}
let rounded = round_shift(mant, 13);
// Rounding can carry into the exponent; that is correct.
sign | (((e as u32) << 10) + rounded) as u16
}
/// `v >> shift`, rounded to nearest with ties to even.
fn round_shift(v: u32, shift: u32) -> u32 {
let half = 1u32 << (shift - 1);
let mask = (1u32 << shift) - 1;
let low = v & mask;
let mut out = v >> shift;
if low > half || (low == half && (out & 1) == 1) {
out += 1;
}
out
}
/// Convert an f32 to IEEE 754 half-precision bits.
///
/// Written out rather than pulled in as a dependency: the inputs here are
@@ -389,6 +518,9 @@ impl Demosaicer {
/// `RawImage`; which of the two CFA families it came off is this
/// function's problem, not theirs.
pub fn run(&self, raw: &RawImage) -> Result<DemosaicedImage, GpuError> {
if raw.samples_per_pixel == 3 {
return DemosaicedImage::from_linear_rgb16(&self.ctx, raw);
}
let (width, height) = (raw.crop.width.max(1), raw.crop.height.max(1));
let limits = self.ctx.device.limits();
@@ -827,6 +959,43 @@ mod tests {
use super::*;
use dr_decode::CropRect;
fn f16_to_f32(bits: u16) -> f32 {
let sign = if bits & 0x8000 != 0 { -1.0 } else { 1.0 };
let e = ((bits >> 10) & 0x1F) as i32;
let m = (bits & 0x3FF) as f32;
if e == 0 {
sign * m * 2f32.powi(-24)
} else {
sign * (1.0 + m / 1024.0) * 2f32.powi(e - 15)
}
}
#[test]
fn unclamped_half_keeps_shadows_signs_and_highlights() {
// A 14-bit LSB, normalised: subnormal in f16, and must not be zero.
let lsb = 1.0 / 16383.0;
let back = f16_to_f32(f32_to_f16_bits_unclamped(lsb));
assert!((back - lsb).abs() / lsb < 0.01, "{back} vs {lsb}");
// A quarter of that, still representable.
let tiny = lsb / 4.0;
let back = f16_to_f32(f32_to_f16_bits_unclamped(tiny));
assert!((back - tiny).abs() / tiny < 0.05, "{back} vs {tiny}");
// Below zero and above one survive.
assert!((f16_to_f32(f32_to_f16_bits_unclamped(-0.01)) + 0.01).abs() < 1e-5);
assert!((f16_to_f32(f32_to_f16_bits_unclamped(1.75)) - 1.75).abs() < 1e-3);
// Exact values are exact.
assert_eq!(f32_to_f16_bits_unclamped(1.0), 0x3C00);
assert_eq!(f32_to_f16_bits_unclamped(0.5), 0x3800);
assert_eq!(f32_to_f16_bits_unclamped(0.0), 0);
// Within one ULP of the clamped one on its domain: that one
// truncates the mantissa, this one rounds it.
for i in 0..=255 {
let v = i as f32 / 255.0;
let (a, b) = (f32_to_f16_bits_unclamped(v), f32_to_f16_bits(v));
assert!(a.abs_diff(b) <= 1, "{v}: {a} vs {b}");
}
}
fn raw_for(black: [u16; 4], white: u16) -> RawImage {
RawImage {
width: 4,
@@ -838,6 +1007,10 @@ mod tests {
wb_coeffs: [1.0, 1.0, 1.0, 1.0],
color_matrix: None,
base_curve: BaseCurve::IDENTITY,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
@@ -950,6 +1123,10 @@ mod tests {
wb_coeffs: [1.0, 1.0, 1.0, 1.0],
color_matrix: None,
base_curve: BaseCurve::IDENTITY,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
@@ -1170,6 +1347,53 @@ mod tests {
}
}
#[test]
fn a_grey_step_edge_stays_grey() {
// A flat patch cannot tell the Malvar kernels from any other set of
// weights that sum to zero. An edge can. A grey vertical step, so
// every photosite records the same profile, must come back with the
// three channels close together on both sides; any spread is false
// colour from interpolating across the edge.
//
// The bound is set by the paper's kernels, which peak at 0.19 here.
// With the ±2 terms of the green-site kernels transposed — the bug
// this test was written against — the peak is 0.375.
let Some(ctx) = ctx() else { return };
let d = Demosaicer::new(&ctx).expect("demosaicer");
let size = 32u32;
let white = 16383u16;
let mut raw = flat_cfa(CfaPattern::Rggb, size, [0, 0, 0], 0, white);
for y in 0..size {
for x in size / 2..size {
raw.data[(y * size + x) as usize] = white;
}
}
let img = d.run(&raw).expect("demosaic");
let px = read_rgba(&ctx, &img);
let (w, _) = img.size();
let mut worst = (0.0f32, 0u32, 0u32);
for y in 2..size - 2 {
for x in 2..size - 2 {
let p = px[(y * w + x) as usize];
let spread = (p[0] - p[1]).abs().max((p[2] - p[1]).abs());
if spread > worst.0 {
worst = (spread, x, y);
}
}
}
assert!(
worst.0 < 0.25,
"false colour of {} at ({}, {}) on a grey edge — the green-site \
kernels are interpolating across the edge",
worst.0,
worst.1,
worst.2
);
}
#[test]
fn output_is_free_of_nan_and_negatives() {
// f16 NaN propagates silently through every later stage; a negative
@@ -1196,6 +1420,10 @@ mod tests {
wb_coeffs: [1.0, 1.0, 1.0, 1.0],
color_matrix: None,
base_curve: BaseCurve::IDENTITY,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
@@ -1277,6 +1505,10 @@ mod tests {
],
color_matrix: None,
base_curve: BaseCurve::IDENTITY,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
+3
View File
@@ -28,6 +28,7 @@ mod error;
mod focus;
mod histogram;
mod mask;
mod merge;
mod raw_histogram;
mod readback;
mod segment;
@@ -40,6 +41,7 @@ pub use demosaic::{DemosaicedImage, Demosaicer};
pub use detail::INTERMEDIATE_FORMAT as DETAIL_INTERMEDIATE_FORMAT;
pub use error::GpuError;
pub use focus::{FocusPeakPass, FocusPeaking, PeakColour, PeakSensitivity};
pub use merge::{Band, MergeFrame, MergeOutput, MergePass};
// Renamed on the way out: `BINS` says enough inside `histogram`, and nothing
// at all at a crate root shared with demosaic and segmentation.
pub use histogram::{Histogram, HistogramPass, BINS as HISTOGRAM_BINS};
@@ -281,6 +283,7 @@ impl GpuContext {
)))
}
/// TRACES: NFR-COMPAT-1
/// Ask one adapter for a device, with the limits the pipeline needs.
async fn device_from(adapter: &wgpu::Adapter) -> Result<(wgpu::Device, wgpu::Queue), GpuError> {
adapter
+547
View File
@@ -0,0 +1,547 @@
//! TRACES: FR-MRG-10 | FR-MRG-11
//! The merge: source frames warped into an output surface, chunk by chunk.
//!
//! The per-pixel half of a panorama (FR-MRG-10), on the GPU: the warp of a
//! source tile into an output chunk, the weighted accumulation across
//! frames, and the resolve to sixteen-bit samples. The geometry it is
//! given — rotations, focal length, projection — is `dr-pano`'s, solved on
//! proxies before any full-resolution pixel exists (panorama.md §5), and
//! that is what makes this simple: every output pixel's source coordinates
//! are a closed-form function, so a chunk can be produced from the source
//! tiles that project into it and nothing else.
//!
//! # The loop
//!
//! ```text
//! for each band of rows of the output:
//! for each chunk across the band:
//! zero the accumulator
//! for each frame whose footprint meets the chunk:
//! the source rectangle the chunk needs, from the geometry
//! render it camera-linear through the pipeline (the tile)
//! warp the tile into the chunk, accumulate ← GPU
//! resolve the chunk to u16 ← GPU
//! copy it into the band
//! hand the band to the writer (one DNG strip)
//! ```
//!
//! No stage holds the composite (FR-MRG-11): the working set is one
//! chunk's accumulator, one tile, one band of u16 rows. The frame textures
//! are the caller's to provide and cache — `source` is asked for frame `k`
//! as it is needed, and a caller short of memory may demosaic on demand.
//!
//! # What is not here yet
//!
//! A feathered blend, not seams and a Laplacian pyramid: the weight is the
//! distance to the frame's edge, which hides exposure steps and small
//! misalignments and does not hide parallax. Gain is a scalar per frame
//! the caller supplies. Both are panorama.md §10's step 5, after the path
//! writes a file end to end.
use std::sync::Arc;
use dr_pano::bundle::Cameras;
use dr_pano::projection::{Bounds, Projection};
use wgpu::util::DeviceExt;
use crate::readback::await_mapping;
use crate::{AdjustPass, DemosaicedImage, GpuContext, GpuError};
/// One frame's part in the merge.
pub struct MergeFrame {
/// The frame's edit, for its lens corrections — the only part of an
/// edit the camera-space tap uses (FR-MRG-2).
pub graph: Arc<dr_pipeline::EditGraph>,
/// Multiplies the frame's samples, to bring its exposure to the
/// reference frame's. 1.0 for no correction.
pub gain: f32,
}
/// The output the merge produces.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct MergeOutput {
pub projection: Projection,
/// The projection's scale in output pixels: the cylinder's radius, the
/// plane's distance. The source focal length at full resolution gives
/// output pixels the size of source pixels at the centre.
pub scale: f64,
/// The rectangle of the projection to produce, centred coordinates.
pub bounds: Bounds,
/// Pixels over which a frame's weight ramps up from its edge.
pub feather: f32,
/// Chunk size: the unit of GPU work and of memory.
pub chunk: (u32, u32),
/// Multiplies a normalised sample (1.0 = white) to the sensor's scale.
pub sample_scale: f32,
}
impl MergeOutput {
pub fn width(&self) -> u32 {
self.bounds.width().ceil().max(1.0) as u32
}
pub fn height(&self) -> u32 {
self.bounds.height().ceil().max(1.0) as u32
}
}
/// A band of finished rows: `rows × width × 3` RGB `u16`, plus a coverage
/// mask (`true` where any frame reached the pixel).
pub struct Band<'a> {
pub first_row: u32,
pub rows: u32,
pub rgb: &'a [u16],
pub covered: &'a [bool],
}
#[repr(C)]
#[derive(Clone, Copy, bytemuck::Pod, bytemuck::Zeroable)]
struct WarpParams {
chunk_origin: [f32; 2],
chunk_size: [u32; 2],
projection: u32,
proj_scale: f32,
focal: f32,
gain: f32,
r0: [f32; 4],
r1: [f32; 4],
r2: [f32; 4],
frame_size: [f32; 2],
tile_origin: [f32; 2],
tile_size: [u32; 2],
feather: f32,
_pad: f32,
}
#[repr(C)]
#[derive(Clone, Copy, bytemuck::Pod, bytemuck::Zeroable)]
struct ResolveParams {
chunk_size: [u32; 2],
scale: f32,
_pad: f32,
}
/// The two pipelines and the chunk buffers.
pub struct MergePass {
ctx: GpuContext,
warp: wgpu::ComputePipeline,
warp_layout: wgpu::BindGroupLayout,
resolve: wgpu::ComputePipeline,
resolve_layout: wgpu::BindGroupLayout,
/// Accumulator and packed output for the current chunk size.
buffers: Option<(wgpu::Buffer, wgpu::Buffer, wgpu::Buffer, (u32, u32))>,
}
impl MergePass {
pub fn new(ctx: &GpuContext) -> Result<Self, GpuError> {
let module = ctx
.device
.create_shader_module(wgpu::ShaderModuleDescriptor {
label: Some("merge"),
source: wgpu::ShaderSource::Wgsl(include_str!("shaders/merge.wgsl").into()),
});
let uniform = |binding| wgpu::BindGroupLayoutEntry {
binding,
visibility: wgpu::ShaderStages::COMPUTE,
ty: wgpu::BindingType::Buffer {
ty: wgpu::BufferBindingType::Uniform,
has_dynamic_offset: false,
min_binding_size: None,
},
count: None,
};
let storage = |binding, read_only| wgpu::BindGroupLayoutEntry {
binding,
visibility: wgpu::ShaderStages::COMPUTE,
ty: wgpu::BindingType::Buffer {
ty: wgpu::BufferBindingType::Storage { read_only },
has_dynamic_offset: false,
min_binding_size: None,
},
count: None,
};
let warp_layout = ctx
.device
.create_bind_group_layout(&wgpu::BindGroupLayoutDescriptor {
label: Some("merge-warp-bgl"),
entries: &[
uniform(0),
wgpu::BindGroupLayoutEntry {
binding: 1,
visibility: wgpu::ShaderStages::COMPUTE,
ty: wgpu::BindingType::Texture {
// Unfilterable: rgba32float, loaded by hand.
sample_type: wgpu::TextureSampleType::Float { filterable: false },
view_dimension: wgpu::TextureViewDimension::D2,
multisampled: false,
},
count: None,
},
storage(2, false),
],
});
let resolve_layout =
ctx.device
.create_bind_group_layout(&wgpu::BindGroupLayoutDescriptor {
label: Some("merge-resolve-bgl"),
entries: &[uniform(0), storage(1, true), storage(2, false)],
});
let pipeline = |name: &str, layout: &wgpu::BindGroupLayout| {
let pl = ctx
.device
.create_pipeline_layout(&wgpu::PipelineLayoutDescriptor {
label: Some(name),
bind_group_layouts: &[Some(layout)],
immediate_size: 0,
});
ctx.device
.create_compute_pipeline(&wgpu::ComputePipelineDescriptor {
label: Some(name),
layout: Some(&pl),
module: &module,
entry_point: Some(name),
compilation_options: Default::default(),
cache: None,
})
};
Ok(MergePass {
ctx: ctx.clone(),
warp: pipeline("warp", &warp_layout),
warp_layout,
resolve: pipeline("resolve", &resolve_layout),
resolve_layout,
buffers: None,
})
}
/// Allocate the chunk buffers for this size if the last ones differ.
fn ensure_buffers(&mut self, chunk: (u32, u32)) {
if self.buffers.as_ref().is_none_or(|b| b.3 != chunk) {
let n = u64::from(chunk.0) * u64::from(chunk.1);
let acc = self.ctx.device.create_buffer(&wgpu::BufferDescriptor {
label: Some("merge-acc"),
size: n * 16,
usage: wgpu::BufferUsages::STORAGE | wgpu::BufferUsages::COPY_DST,
mapped_at_creation: false,
});
let out = self.ctx.device.create_buffer(&wgpu::BufferDescriptor {
label: Some("merge-out"),
size: n * 8,
usage: wgpu::BufferUsages::STORAGE | wgpu::BufferUsages::COPY_SRC,
mapped_at_creation: false,
});
let read = self.ctx.device.create_buffer(&wgpu::BufferDescriptor {
label: Some("merge-read"),
size: n * 8,
usage: wgpu::BufferUsages::COPY_DST | wgpu::BufferUsages::MAP_READ,
mapped_at_creation: false,
});
self.buffers = Some((acc, out, read, chunk));
}
}
fn chunk_buffers(&self) -> (&wgpu::Buffer, &wgpu::Buffer, &wgpu::Buffer) {
let b = self.buffers.as_ref().expect("ensured by the caller");
(&b.0, &b.1, &b.2)
}
/// Produce the whole output, band by band, handing each finished band
/// to `sink`.
///
/// `cameras` are in **full-resolution source pixels** (`frame_size`),
/// with frame `k` corresponding to `frames[k]` and `source(k)`. `source`
/// supplies the demosaiced frame on demand and may cache as it sees fit.
#[allow(clippy::too_many_arguments)]
pub fn merge<S, F>(
&mut self,
adjust: &mut AdjustPass,
frames: &[MergeFrame],
cameras: &Cameras,
frame_size: (u32, u32),
output: &MergeOutput,
mut source: S,
mut sink: F,
mut cancelled: impl FnMut() -> bool,
) -> Result<(), GpuError>
where
S: FnMut(usize) -> Result<Arc<DemosaicedImage>, GpuError>,
F: FnMut(Band<'_>) -> Result<(), GpuError>,
{
let (out_w, out_h) = (output.width(), output.height());
let (cw, ch) = (output.chunk.0.max(8), output.chunk.1.max(8));
let (fw, fh) = (frame_size.0 as f64, frame_size.1 as f64);
let mut band_rgb = vec![0u16; (out_w * ch * 3) as usize];
let mut band_cov = vec![false; (out_w * ch) as usize];
let mut chunk_px: Vec<u32> = Vec::new();
let mut y = 0u32;
while y < out_h {
let rows = ch.min(out_h - y);
band_rgb.iter_mut().for_each(|v| *v = 0);
band_cov.iter_mut().for_each(|v| *v = false);
let mut x = 0u32;
while x < out_w {
if cancelled() {
return Err(GpuError::Readback("merge cancelled".into()));
}
let cols = cw.min(out_w - x);
let origin = (
output.bounds.min_u + f64::from(x),
output.bounds.min_v + f64::from(y),
);
self.zero_accumulator((cols, rows));
for (k, frame) in frames.iter().enumerate() {
let Some(rect) = source_rect(
output.projection,
output.scale,
cameras,
k,
origin,
(cols, rows),
(fw, fh),
) else {
continue;
};
let image = source(k)?;
// The tile: that rectangle of the frame, camera-linear,
// at 1:1.
let view = dr_pipeline::CropRect {
x: (rect.0 as f32) / fw as f32,
y: (rect.1 as f32) / fh as f32,
width: (rect.2 as f32) / fw as f32,
height: (rect.3 as f32) / fh as f32,
};
let shader = frame.graph.compose_camera_linear(view);
let tile = adjust.render_camera_linear(&image, &shader, rect.2, rect.3)?;
let r = cameras.rotations[k].transpose();
let params = WarpParams {
chunk_origin: [origin.0 as f32, origin.1 as f32],
chunk_size: [cols, rows],
projection: match output.projection {
Projection::Perspective => 0,
Projection::Cylindrical => 1,
Projection::Spherical => 2,
},
proj_scale: output.scale as f32,
focal: cameras.focal as f32,
gain: frame.gain,
r0: [r.0[0][0] as f32, r.0[0][1] as f32, r.0[0][2] as f32, 0.0],
r1: [r.0[1][0] as f32, r.0[1][1] as f32, r.0[1][2] as f32, 0.0],
r2: [r.0[2][0] as f32, r.0[2][1] as f32, r.0[2][2] as f32, 0.0],
frame_size: [fw as f32, fh as f32],
tile_origin: [rect.0 as f32, rect.1 as f32],
tile_size: [rect.2, rect.3],
feather: output.feather,
_pad: 0.0,
};
self.accumulate(&params, tile);
}
self.resolve_chunk((cols, rows), output.sample_scale, &mut chunk_px)?;
// Into the band.
for row in 0..rows as usize {
for col in 0..cols as usize {
let px = chunk_px[(row * cols as usize + col) * 2..][..2].to_vec();
let i = row * out_w as usize + (x as usize + col);
band_rgb[i * 3] = (px[0] & 0xFFFF) as u16;
band_rgb[i * 3 + 1] = (px[0] >> 16) as u16;
band_rgb[i * 3 + 2] = (px[1] & 0xFFFF) as u16;
band_cov[i] = (px[1] >> 16) != 0;
}
}
x += cols;
}
sink(Band {
first_row: y,
rows,
rgb: &band_rgb[..(out_w * rows * 3) as usize],
covered: &band_cov[..(out_w * rows) as usize],
})?;
y += rows;
}
Ok(())
}
fn zero_accumulator(&mut self, chunk: (u32, u32)) {
self.ensure_buffers(chunk);
let (acc, _, _) = self.chunk_buffers();
let n = u64::from(chunk.0) * u64::from(chunk.1) * 16;
let mut enc = self.ctx.device.create_command_encoder(&Default::default());
enc.clear_buffer(acc, 0, Some(n));
self.ctx.queue.submit(Some(enc.finish()));
}
fn accumulate(&mut self, params: &WarpParams, tile: &wgpu::Texture) {
let chunk = (params.chunk_size[0], params.chunk_size[1]);
let uniforms = self
.ctx
.device
.create_buffer_init(&wgpu::util::BufferInitDescriptor {
label: Some("merge-warp-params"),
contents: bytemuck::bytes_of(params),
usage: wgpu::BufferUsages::UNIFORM,
});
let view = tile.create_view(&Default::default());
self.ensure_buffers(chunk);
let (acc, _, _) = self.chunk_buffers();
let bind = self
.ctx
.device
.create_bind_group(&wgpu::BindGroupDescriptor {
label: Some("merge-warp-bg"),
layout: &self.warp_layout,
entries: &[
wgpu::BindGroupEntry {
binding: 0,
resource: uniforms.as_entire_binding(),
},
wgpu::BindGroupEntry {
binding: 1,
resource: wgpu::BindingResource::TextureView(&view),
},
wgpu::BindGroupEntry {
binding: 2,
resource: acc.as_entire_binding(),
},
],
});
let mut enc = self.ctx.device.create_command_encoder(&Default::default());
{
let mut pass = enc.begin_compute_pass(&Default::default());
pass.set_pipeline(&self.warp);
pass.set_bind_group(0, &bind, &[]);
pass.dispatch_workgroups(chunk.0.div_ceil(8), chunk.1.div_ceil(8), 1);
}
self.ctx.queue.submit(Some(enc.finish()));
}
fn resolve_chunk(
&mut self,
chunk: (u32, u32),
scale: f32,
out: &mut Vec<u32>,
) -> Result<(), GpuError> {
let params = ResolveParams {
chunk_size: [chunk.0, chunk.1],
scale,
_pad: 0.0,
};
let uniforms = self
.ctx
.device
.create_buffer_init(&wgpu::util::BufferInitDescriptor {
label: Some("merge-resolve-params"),
contents: bytemuck::bytes_of(&params),
usage: wgpu::BufferUsages::UNIFORM,
});
let n = u64::from(chunk.0) * u64::from(chunk.1);
self.ensure_buffers(chunk);
let (acc, packed, read) = self.chunk_buffers();
let bind = self
.ctx
.device
.create_bind_group(&wgpu::BindGroupDescriptor {
label: Some("merge-resolve-bg"),
layout: &self.resolve_layout,
entries: &[
wgpu::BindGroupEntry {
binding: 0,
resource: uniforms.as_entire_binding(),
},
wgpu::BindGroupEntry {
binding: 1,
resource: acc.as_entire_binding(),
},
wgpu::BindGroupEntry {
binding: 2,
resource: packed.as_entire_binding(),
},
],
});
let mut enc = self.ctx.device.create_command_encoder(&Default::default());
{
let mut pass = enc.begin_compute_pass(&Default::default());
pass.set_pipeline(&self.resolve);
pass.set_bind_group(0, &bind, &[]);
pass.dispatch_workgroups(chunk.0.div_ceil(8), chunk.1.div_ceil(8), 1);
}
enc.copy_buffer_to_buffer(packed, 0, read, 0, n * 8);
self.ctx.queue.submit(Some(enc.finish()));
let slice = read.slice(..n * 8);
let (tx, rx) = std::sync::mpsc::channel();
slice.map_async(wgpu::MapMode::Read, move |r| {
let _ = tx.send(r);
});
await_mapping(&self.ctx, &rx)?;
{
let data = slice.get_mapped_range();
out.clear();
out.extend_from_slice(bytemuck::cast_slice::<u8, u32>(&data));
}
read.unmap();
Ok(())
}
}
/// The rectangle of frame `k` (x, y, w, h in source pixels) a chunk reads,
/// or `None` if the chunk sees nothing of the frame.
///
/// Walks the chunk's border, projects each point into the frame, and takes
/// the bounding box with a two-pixel margin for the bilinear fetch. The
/// border rather than the corners because under a cylinder or sphere the
/// extreme of a footprint is not at a corner.
fn source_rect(
projection: Projection,
scale: f64,
cameras: &Cameras,
k: usize,
origin: (f64, f64),
size: (u32, u32),
frame: (f64, f64),
) -> Option<(u32, u32, u32, u32)> {
let (w, h) = (f64::from(size.0), f64::from(size.1));
let steps = 16;
let mut min = (f64::MAX, f64::MAX);
let mut max = (f64::MIN, f64::MIN);
let mut any = false;
let mut visit = |u: f64, v: f64| {
let d = projection.to_direction(scale, u, v);
if let Some((x, y)) = cameras.project(k, d) {
let (x, y) = (x + frame.0 / 2.0, y + frame.1 / 2.0);
min = (min.0.min(x), min.1.min(y));
max = (max.0.max(x), max.1.max(y));
any = true;
}
};
for s in 0..=steps {
let t = f64::from(s) / f64::from(steps);
visit(origin.0 + w * t, origin.1);
visit(origin.0 + w * t, origin.1 + h);
visit(origin.0, origin.1 + h * t);
visit(origin.0 + w, origin.1 + h * t);
}
// The interior too, coarsely: a chunk can contain a frame entirely.
for i in 1..4 {
for j in 1..4 {
visit(
origin.0 + w * f64::from(i) / 4.0,
origin.1 + h * f64::from(j) / 4.0,
);
}
}
if !any {
return None;
}
let x0 = (min.0.floor() - 2.0).max(0.0);
let y0 = (min.1.floor() - 2.0).max(0.0);
let x1 = (max.0.ceil() + 2.0).min(frame.0);
let y1 = (max.1.ceil() + 2.0).min(frame.1);
if x1 <= x0 || y1 <= y0 {
return None;
}
Some((x0 as u32, y0 as u32, (x1 - x0) as u32, (y1 - y0) as u32))
}
+10 -4
View File
@@ -160,12 +160,18 @@ fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
// Green is measured. Red and blue are interpolated from their own
// axis, with a correction from the green Laplacian.
//
// Malvar "G at R/B locations" kernels, transposed per axis:
// chroma along the row: (5c + 4(w1+e1) - (nw+ne+sw+se) - (n2+s2) + 0.5(w2+e2)) / 8
// Malvar "R at green in R row" kernel, and its transpose:
// chroma along the row: (5c + 4(w1+e1) - (nw+ne+sw+se) - (w2+e2) + 0.5(n2+s2)) / 8
//
// The -1 goes on the two greens *along* the chroma axis and the +0.5
// on the pair across it. Transposed, both kernels still sum to zero
// and reconstruct a flat patch exactly, but on an edge the correction
// at green sites is half strength and the false colour doubles: a
// blue/yellow zipper around every clipped highlight.
let along_row =
(5.0 * c + 4.0 * (w1 + e1) - diag1 - vert2 + 0.5 * horiz2) * 0.125;
(5.0 * c + 4.0 * (w1 + e1) - diag1 - horiz2 + 0.5 * vert2) * 0.125;
let along_col =
(5.0 * c + 4.0 * (n1 + s1) - diag1 - horiz2 + 0.5 * vert2) * 0.125;
(5.0 * c + 4.0 * (n1 + s1) - diag1 - vert2 + 0.5 * horiz2) * 0.125;
let red_horizontal = red_is_horizontal(gid.x, gid.y);
let r = select(along_col, along_row, red_horizontal);
+166
View File
@@ -0,0 +1,166 @@
// TRACES: FR-MRG-10 | FR-MRG-11
// The merge: one source tile warped into one output chunk, accumulated.
//
// Two entry points. `warp` runs once per (chunk, frame): for every chunk
// pixel it asks which direction that pixel looks along, turns the
// direction into the frame's camera, projects it to a source pixel, and
// if that pixel is inside the tile that was rendered for this chunk,
// samples it and adds it — weighted by its distance from the frame's edge
// — into the accumulator. `resolve` runs once per chunk after every frame
// has been added: divides the sums by the weights and packs the result as
// sixteen-bit samples at the sensor's scale (FR-MRG-3).
//
// The accumulator is a buffer and not a storage texture, because WebGPU
// allows a read-write storage texture only in the 32-bit single-channel
// formats, and this wants four channels. The tile is sampled by hand from
// four `textureLoad`s rather than through a sampler, because `rgba32float`
// is not filterable without an optional feature, and the tile is
// `rgba32float` on purpose (panorama.md §5.1).
//
// The projection maths is `dr_pano::projection` verbatim; the two must
// agree, and a golden test compares them.
struct Params {
// Where the chunk's pixel (0, 0) sits in centred output coordinates,
// and the chunk's size.
chunk_origin: vec2<f32>,
chunk_size: vec2<u32>,
// 0 perspective, 1 cylindrical, 2 spherical; and the projection's
// scale (the cylinder's radius, the sphere's, the plane's distance) in
// output pixels.
projection: u32,
proj_scale: f32,
// The frame's focal length in source pixels, and the gain the frame's
// exposure is corrected by.
focal: f32,
gain: f32,
// World → this frame's camera: the transpose of its rotation, one row
// per vec4 (padded).
r0: vec4<f32>,
r1: vec4<f32>,
r2: vec4<f32>,
// The full frame's size in source pixels (for the edge weight), the
// tile's origin within the frame, and the tile's size.
frame_size: vec2<f32>,
tile_origin: vec2<f32>,
tile_size: vec2<u32>,
// Pixels over which the weight ramps from the edge to full.
feather: f32,
_pad: f32,
};
@group(0) @binding(0) var<uniform> p: Params;
@group(0) @binding(1) var tile: texture_2d<f32>;
// rgb·w summed, then w: four floats per chunk pixel.
@group(0) @binding(2) var<storage, read_write> acc: array<vec4<f32>>;
fn to_direction(u: f32, v: f32) -> vec3<f32> {
let s = p.proj_scale;
if (p.projection == 0u) {
return normalize(vec3<f32>(u, v, s));
}
if (p.projection == 1u) {
let theta = u / s;
return normalize(vec3<f32>(sin(theta), v / s, cos(theta)));
}
let theta = u / s;
let phi = v / s;
return vec3<f32>(sin(theta) * cos(phi), sin(phi), cos(theta) * cos(phi));
}
fn load(x: i32, y: i32) -> vec4<f32> {
return textureLoad(tile, vec2<i32>(x, y), 0);
}
@compute @workgroup_size(8, 8, 1)
fn warp(@builtin(global_invocation_id) gid: vec3<u32>) {
if (gid.x >= p.chunk_size.x || gid.y >= p.chunk_size.y) {
return;
}
let u = p.chunk_origin.x + f32(gid.x) + 0.5;
let v = p.chunk_origin.y + f32(gid.y) + 0.5;
let d = to_direction(u, v);
let c = vec3<f32>(dot(p.r0.xyz, d), dot(p.r1.xyz, d), dot(p.r2.xyz, d));
if (c.z <= 1e-6) {
return;
}
// Source pixel, in the full frame, with the principal point at its
// centre. `- 0.5` puts pixel centres on integer coordinates for the
// bilinear fetch below.
let sx = p.focal * c.x / c.z + p.frame_size.x * 0.5 - 0.5;
let sy = p.focal * c.y / c.z + p.frame_size.y * 0.5 - 0.5;
// Weight: distance to the nearest frame edge, in pixels, over the
// feather. Zero outside the frame.
let edge = min(min(sx, p.frame_size.x - 1.0 - sx), min(sy, p.frame_size.y - 1.0 - sy));
if (edge <= 0.0) {
return;
}
let w = clamp(edge / max(p.feather, 1.0), 0.0, 1.0);
// Into the tile.
let tx = sx - p.tile_origin.x;
let ty = sy - p.tile_origin.y;
let tw = f32(p.tile_size.x);
let th = f32(p.tile_size.y);
if (tx < 0.0 || ty < 0.0 || tx > tw - 1.0 || ty > th - 1.0) {
return;
}
let x0 = i32(floor(tx));
let y0 = i32(floor(ty));
let x1 = min(x0 + 1, i32(p.tile_size.x) - 1);
let y1 = min(y0 + 1, i32(p.tile_size.y) - 1);
let fx = tx - f32(x0);
let fy = ty - f32(y0);
// The four texels, with their alpha: the tap writes alpha 0 where the
// lens correction found no source pixel, and a sample that touches one
// of those is a partial pixel — down-weighted by exactly how much of
// it is missing, and dropped when all of it is.
let s00 = load(x0, y0);
let s10 = load(x1, y0);
let s01 = load(x0, y1);
let s11 = load(x1, y1);
let top = mix(s00, s10, fx);
let bot = mix(s01, s11, fx);
let s = mix(top, bot, fy);
if (s.a <= 0.001) {
return;
}
// Colour is the alpha-weighted mean of the texels that exist.
let rgb = s.rgb / s.a * p.gain;
let wa = w * s.a;
let i = gid.y * p.chunk_size.x + gid.x;
acc[i] = acc[i] + vec4<f32>(rgb * wa, wa);
}
// Resolve: the accumulated chunk to sixteen-bit samples.
struct ResolveParams {
chunk_size: vec2<u32>,
// Multiplies a normalised value (1.0 = the sensor's white) back to the
// sensor's scale: the source's white minus its black (FR-MRG-3).
scale: f32,
_pad: f32,
};
@group(0) @binding(0) var<uniform> rp: ResolveParams;
@group(0) @binding(1) var<storage, read> racc: array<vec4<f32>>;
// Two u32 per pixel: (r | g << 16), (b | coverage << 16). Coverage is
// 65535 where any frame reached the pixel and 0 where none did, so the
// CPU can tell an empty pixel from a black one.
@group(0) @binding(2) var<storage, read_write> out: array<vec2<u32>>;
@compute @workgroup_size(8, 8, 1)
fn resolve(@builtin(global_invocation_id) gid: vec3<u32>) {
if (gid.x >= rp.chunk_size.x || gid.y >= rp.chunk_size.y) {
return;
}
let i = gid.y * rp.chunk_size.x + gid.x;
let a = racc[i];
if (a.w <= 0.0) {
out[i] = vec2<u32>(0u, 0u);
return;
}
let rgb = clamp(a.rgb / a.w * rp.scale, vec3<f32>(0.0), vec3<f32>(65535.0));
let r = u32(round(rgb.r));
let g = u32(round(rgb.g));
let b = u32(round(rgb.b));
out[i] = vec2<u32>(r | (g << 16u), b | (65535u << 16u));
}
+4
View File
@@ -40,6 +40,10 @@ fn flat_raw(level: u16, curve: BaseCurve) -> RawImage {
wb_coeffs: [1.0, 1.0, 1.0, 1.0],
color_matrix: Some([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]),
base_curve: curve,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
+4
View File
@@ -46,6 +46,10 @@ fn flat_raw(level: u16) -> RawImage {
// leaving a curve here would test the suppression rather than the
// film. `dr-pipeline` asserts the suppression on the generated source.
base_curve: BaseCurve::IDENTITY,
samples_per_pixel: 1,
profile: None,
make: String::new(),
model: String::new(),
crop: CropRect {
x: 0,
y: 0,
+1 -1
View File
@@ -1,4 +1,4 @@
//! TRACES: FR-DSP-5
//! TRACES: FR-DSP-5 | R5
//! Zooming to 1:1 samples the source, pixel for pixel.
//!
//! FR-DSP-5: *"Fit, 1:1, and arbitrary zoom levels. At 1:1 and above, the
+44
View File
@@ -0,0 +1,44 @@
[package]
name = "dr-inference-engine"
version.workspace = true
edition.workspace = true
rust-version.workspace = true
license.workspace = true
# The one crate that names a runtime, a provider, a vendor library or a
# device (docs/inference.md §8). `dr-face` and `dr-segment` ask it for a
# session by role and never see which of these answered.
[dependencies]
thiserror.workspace = true
log.workspace = true
serde.workspace = true
serde_json.workspace = true
# `ort` is the API; what supplies it is decided once per process (§3):
# `libonnxruntime` found on disk, or `tract`. Both are behind
# `alternative-backend`, so nothing here links C on any target.
ort = { workspace = true }
ort-tract = { workspace = true, optional = true }
# dlopen, and the C types of the table it fetches. Both pure Rust;
# `libloading` is already in the tree through wgpu.
libloading = { version = "0.8", optional = true }
ort-sys = { version = "2.0.0-rc.13", default-features = false, features = ["disable-linking"], optional = true }
# The NVIDIA rungs exist on the desktop only. These features add `ort`'s
# option builders and nothing else — no linking under `alternative-backend` —
# but an Android binary has no business carrying even the option names, and
# the packaging must never be tempted to (§2, §3.1).
[target.'cfg(not(target_os = "android"))'.dependencies]
ort = { workspace = true, features = ["cuda", "tensorrt"] }
[target.'cfg(target_os = "android")'.dependencies]
ort = { workspace = true, features = ["qnn"] }
[features]
# The floor: `tract` supplies the API table when no runtime file is found, or
# always, in a build without `native`. Tests want this and nothing else.
default = ["tract"]
tract = ["dep:ort-tract"]
# Look for `libonnxruntime` on disk and hand its table to `ort`.
native = ["dep:libloading", "dep:ort-sys"]
+169
View File
@@ -0,0 +1,169 @@
//! The API table `ort` runs on, chosen once (docs/inference.md §3).
//!
//! `ort` with `alternative-backend` links no runtime and asks, on first use,
//! for an `OrtApi` — a struct of function pointers. Two things can fill it:
//! a `libonnxruntime` this module `dlopen`s, or `ort-tract`. The Rust build
//! is identical either way; the difference is whether a file was found.
use std::path::PathBuf;
use std::sync::OnceLock;
/// What supplied the table.
#[derive(Clone, Debug, PartialEq, Eq)]
pub enum Runtime {
/// Pure Rust, one core, every operator these graphs use. The floor.
Tract,
/// The C++ ONNX Runtime, loaded from `path`.
OnnxRuntime { path: PathBuf, version: String },
}
impl Runtime {
pub fn label(&self) -> String {
match self {
Runtime::Tract => "tract".into(),
Runtime::OnnxRuntime { version, .. } => format!("ONNX Runtime {version}"),
}
}
pub fn is_native(&self) -> bool {
matches!(self, Runtime::OnnxRuntime { .. })
}
}
static RUNTIME: OnceLock<Runtime> = OnceLock::new();
/// The runtime in use; tract until something installs another.
pub fn runtime() -> Runtime {
RUNTIME.get().cloned().unwrap_or(Runtime::Tract)
}
/// Install a table if none is installed yet — tract, since no directories
/// were named. What a test or an example gets, unless `DARKROOM_ORT_DIR`
/// names a runtime: the same variable the desktop honours, so an example
/// can be pointed at the runtime the app uses without learning `init`.
pub fn ensure_installed() {
if RUNTIME.get().is_none() {
let dirs: Vec<PathBuf> = std::env::var_os("DARKROOM_ORT_DIR")
.map(PathBuf::from)
.into_iter()
.collect();
install(&dirs);
}
}
/// Look for `libonnxruntime` in `dirs`, in order, and hand `ort` the first
/// table that loads; otherwise tract. Once per process.
pub fn install(dirs: &[PathBuf]) -> Runtime {
RUNTIME
.get_or_init(|| {
#[cfg(feature = "native")]
for dir in dirs {
match load_native(dir) {
Ok(rt) => return rt,
Err(e) => log::info!("inference: no runtime in {}: {e}", dir.display()),
}
}
#[cfg(not(feature = "native"))]
let _ = dirs;
install_tract()
})
.clone()
}
#[cfg(feature = "tract")]
fn install_tract() -> Runtime {
let _ = ort::set_api(ort_tract::api());
Runtime::Tract
}
#[cfg(not(feature = "tract"))]
fn install_tract() -> Runtime {
// A build with neither tract nor a runtime file has nothing to run
// models on; every `open` will report the un-set API rather than panic
// somewhere deeper.
log::error!("inference: no ONNX Runtime found and tract is not compiled in");
Runtime::Tract
}
#[cfg(feature = "native")]
fn load_native(dir: &std::path::Path) -> Result<Runtime, String> {
let name = if cfg!(target_os = "windows") {
"onnxruntime.dll"
} else if cfg!(any(target_os = "macos", target_os = "ios")) {
"libonnxruntime.dylib"
} else {
"libonnxruntime.so"
};
// An empty dir means the bare name: the system loader's search, which on
// Android includes the APK's own native libraries.
let path = if dir.as_os_str().is_empty() {
PathBuf::from(name)
} else {
find_library(dir, name).ok_or("not present")?
};
// SAFETY: the library's initialisers are ONNX Runtime's own; the symbol
// is the documented entry point with the documented signature; the table
// is copied out and the library handle is leaked, so every pointer in
// the copy stays valid for the life of the process.
unsafe {
let lib = libloading::Library::new(&path).map_err(|e| e.to_string())?;
let get_base: libloading::Symbol<
unsafe extern "system" fn() -> *const ort_sys::OrtApiBase,
> = lib.get(b"OrtGetApiBase\0").map_err(|e| e.to_string())?;
let base = get_base();
if base.is_null() {
return Err("OrtGetApiBase returned null".into());
}
let version = std::ffi::CStr::from_ptr(((*base).GetVersionString)())
.to_string_lossy()
.into_owned();
let api = ((*base).GetApi)(ort_sys::ORT_API_VERSION);
if api.is_null() {
return Err(format!(
"ONNX Runtime {version} is older than API version {}",
ort_sys::ORT_API_VERSION
));
}
if !ort::set_api((*api).clone()) {
return Err("an API table was already installed".into());
}
std::mem::forget(lib);
// Qualcomm's DSP loader finds the Hexagon skel through this variable,
// and only through it; the runtime's own directory is where the APK
// put it. Harmless anywhere else.
#[cfg(target_os = "android")]
if !dir.as_os_str().is_empty() {
std::env::set_var("ADSP_LIBRARY_PATH", dir);
}
log::info!("inference: ONNX Runtime {version} from {}", path.display());
Ok(Runtime::OnnxRuntime { path, version })
}
}
/// `libonnxruntime.so` in `dir`, or a versioned spelling of it —
/// `libonnxruntime.so.1.30.0` is what the Python wheel ships, and a package
/// that installs only the versioned file is not wrong.
#[cfg(feature = "native")]
fn find_library(dir: &std::path::Path, name: &str) -> Option<PathBuf> {
let exact = dir.join(name);
if exact.is_file() {
return Some(exact);
}
let prefix = format!("{name}.");
let mut versioned: Vec<PathBuf> = std::fs::read_dir(dir)
.ok()?
.filter_map(|e| e.ok())
.map(|e| e.path())
.filter(|p| {
p.is_file()
&& p.file_name()
.and_then(|n| n.to_str())
.is_some_and(|n| n.starts_with(&prefix))
})
.collect();
versioned.sort();
versioned.pop()
}
+121
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//! Compiled engines: what a rung builds once per device, and the thread that
//! builds them before anyone asks (docs/inference.md §5, §6).
//!
//! TensorRT keeps its own engine cache keyed by graph hash; QNN writes a
//! context model. Both are opaque to this crate, which tracks only *that* a
//! model compiled — by the hash of its bytes — so [`crate::open`] can tell a
//! request whether to expect the rung or its fallback.
use std::path::PathBuf;
use crate::{state, Config, Form, Rung};
enum Source {
File(PathBuf),
Bytes(&'static [u8]),
}
/// 64-bit FNV-1a. A cache key, not a checksum: two model files that collide
/// here would have to also be the same size and the same role, and the cost
/// of that is a rebuilt engine.
pub fn hash(bytes: &[u8]) -> u64 {
let mut h = 0xcbf2_9ce4_8422_2325u64;
for &b in bytes {
h ^= b as u64;
h = h.wrapping_mul(0x0000_0100_0000_01b3);
}
h
}
/// The cache entry for `bytes` compiled on `rung`.
pub fn key(rung: Rung, bytes: &[u8]) -> String {
key_of(rung, hash(bytes))
}
/// The same, from a hash already taken.
pub fn key_of(rung: Rung, hash: u64) -> String {
format!("{}:{:016x}", rung.label(), hash)
}
/// Where QNN's compiled context for `bytes` lives.
pub fn context_path(cfg: &Config, bytes: &[u8]) -> PathBuf {
cfg.cache_dir
.join("qnn")
.join(format!("{:016x}_ctx.onnx", hash(bytes)))
}
/// After the probe: compile every configured model the selected rung can
/// take, smallest first, recording each as it lands.
pub fn run() {
let (rung, cfg) = {
let s = state().lock().unwrap();
(crate::current_rung(&s), s.config.clone())
};
if !rung.compiles() {
return;
}
// Smallest first, so the detector — the one that runs per image — is
// ready soonest (§6 step 3).
let mut jobs: Vec<(crate::Role, Source, u64)> = cfg
.models
.iter()
.filter(|(role, _)| rung.serves(*role))
.filter_map(|(role, path)| {
let (path, form) = crate::resolve_model(*role, path);
(form == rung.form(*role)).then(|| {
let size = std::fs::metadata(&path).map(|m| m.len()).unwrap_or(0);
(*role, Source::File(path), size)
})
})
.chain(cfg.embedded.iter().filter_map(|(role, bytes)| {
// An embedded model has no int8 sibling to offer a rung that
// wants one; it runs on that rung's fallback.
(rung.serves(*role) && rung.form(*role) == Form::F32).then_some((
*role,
Source::Bytes(bytes),
bytes.len() as u64,
))
}))
.collect();
jobs.sort_by_key(|j| j.2);
state().lock().unwrap().wanted = jobs.len();
for (role, source, _) in jobs {
let (bytes, name) = match &source {
Source::File(path) => match std::fs::read(path) {
Ok(b) => (b, path.display().to_string()),
Err(_) => continue,
},
Source::Bytes(b) => (b.to_vec(), format!("embedded {role:?}")),
};
let key = key(rung, &bytes);
if state().lock().unwrap().cache.compiled.contains(&key) {
continue;
}
log::info!("inference: compiling {name} for {}", rung.label());
let started = std::time::Instant::now();
match crate::session::build(rung, role, &bytes, &cfg) {
Ok(session) => {
drop(session);
let mut s = state().lock().unwrap();
s.cache.compiled.insert(key);
crate::probe::write_cache(&s.config, &s.cache);
log::info!(
"inference: {name} ready on {} in {:.1} s",
rung.label(),
started.elapsed().as_secs_f64()
);
}
Err(e) => {
// This model stays on the fallback; the others still get
// their engine. A corrected model file changes the hash and
// is retried.
log::warn!(
"inference: {name} will not compile for {}: {e}",
rung.label()
);
}
}
}
}
+623
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//! Which runtime, which provider and which model form — decided once per
//! device, and the only crate that knows the answer (docs/inference.md).
//!
//! Consumers ask for a session by [`Role`] and get `ort`'s `Session` back;
//! what built it — tract on one core, ONNX Runtime's CPU pool, a TensorRT
//! engine, the Hexagon — is this crate's business and shows up in
//! [`status`] for the settings row and nowhere else.
//!
//! The shape follows §3 of the spec: `ort` links nothing (`alternative-backend`),
//! and the first call hands it an API table from either a `libonnxruntime`
//! found on disk or from `tract`. That choice is once per process, because
//! `ort::set_api` is; everything after it — which provider, whether an engine
//! has been compiled yet — is per session and may change between two calls.
use std::collections::{BTreeSet, HashMap};
use std::path::{Path, PathBuf};
use std::sync::{Arc, Mutex, MutexGuard, OnceLock};
use std::time::{Duration, Instant};
use serde::{Deserialize, Serialize};
mod api;
mod engines;
mod probe;
mod session;
pub use api::Runtime;
pub use ort::session::Session;
/// What a model is for. The role fixes the precision rule (§7): an embedder
/// runs in f32 on every rung, a detector may run in fp16 or int8.
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, Serialize, Deserialize)]
pub enum Role {
Detector,
Embedder,
Segmenter,
Scene,
/// The dense landmark model behind the eye reading (docs/faces.md §7c).
Landmarks,
/// The eye-state and sunglasses classifiers, a few hundred kilobytes.
EyeClassifier,
/// XFeat, the panorama keypoint detector (docs/panorama.md).
Keypoints,
/// MI-GAN, the panorama border filler (docs/panorama.md §12). Plain
/// convolutions, so any rung serves it; fp16 on TensorRT and int8 on
/// the Hexagon are the point of it.
Inpainter,
}
/// Which numeric form of a model a session was built from.
///
/// `Int8` is a different network from `F32` for a detector — it finds a
/// different set of faces — which is why [`form_suffix`] exists and why a
/// caller appends it to `model_id`.
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, Serialize, Deserialize)]
pub enum Form {
F32,
Int8,
}
/// A rung of the ladder (§2). Ordered: a user override names the highest rung
/// the probe may take, and a compiling rung falls back to the one below it
/// until its engine exists.
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, Serialize, Deserialize)]
pub enum Rung {
/// ONNX Runtime's CPU provider, or tract when no runtime file was found.
Cpu,
/// NVIDIA, through the CUDA provider. Desktop only.
Cuda,
/// NVIDIA, through a TensorRT engine compiled on this device. Desktop only.
TensorRt,
/// Qualcomm's Hexagon NPU through QNN, int8 models only. Android only.
Hexagon,
}
impl Rung {
pub fn label(self) -> &'static str {
match self {
Rung::Cpu => "CPU",
Rung::Cuda => "CUDA",
Rung::TensorRt => "TensorRT",
Rung::Hexagon => "Hexagon NPU",
}
}
/// The rung a request lands on while this one's engine is still being
/// compiled (§6 step 2).
fn fallback(self) -> Rung {
match self {
Rung::TensorRt => Rung::Cuda,
Rung::Hexagon | Rung::Cuda | Rung::Cpu => Rung::Cpu,
}
}
/// Whether a session on this rung needs an engine built first.
fn compiles(self) -> bool {
matches!(self, Rung::TensorRt | Rung::Hexagon)
}
/// The model form this rung wants for a role.
fn form(self, _role: Role) -> Form {
match self {
Rung::Hexagon => Form::Int8,
_ => Form::F32,
}
}
/// Whether this rung runs `role` at all. The Hexagon takes int8 graphs
/// only, and the embedder is never int8 (§7) — it runs on the CPU
/// beside a detector on the NPU, so its vectors compare across devices.
fn serves(self, role: Role) -> bool {
match self {
Rung::Hexagon => role != Role::Embedder,
_ => true,
}
}
}
/// How long a session outlives its last use unless [`Config::decay`] says
/// otherwise: long enough for the next click, short enough that a session's
/// GPU or NPU memory does not sit under the develop view for long.
pub const DEFAULT_DECAY: Duration = Duration::from_secs(30);
/// What [`init`] is told once, at launch.
#[derive(Clone, Debug, Default)]
pub struct Config {
/// Where to look for `libonnxruntime`, in order. An empty path means "the
/// bare library name through the system loader", which is how the APK's
/// own copy is found on Android.
pub runtime_dirs: Vec<PathBuf>,
/// Probe cache and compiled engines (§4, §5). Disposable.
pub cache_dir: PathBuf,
/// The canonical model files on this device, so engines can be compiled
/// ahead of the first request for them.
pub models: Vec<(Role, PathBuf)>,
/// Models compiled into the binary, for the same reason.
pub embedded: Vec<(Role, &'static [u8])>,
/// The highest rung the user allows; `None` is "the best that works".
pub ceiling: Option<Rung>,
/// ONNX Runtime's intra-op pool; 0 picks from the core count.
pub threads: usize,
/// How long an unused session stays loaded. Zero means the default.
pub decay: Duration,
}
/// One line for the settings row, and the numbers behind the progress row.
#[derive(Clone, Debug)]
pub struct Status {
pub runtime: Runtime,
/// The rung selected, or the floor while the probe is still running.
pub rung: Rung,
/// Why — "probe passed", or the failure that demoted the rung above.
pub reason: String,
pub probing: bool,
/// Engines compiled and engines wanted, for a compiling rung; `(0, 0)`
/// otherwise.
pub engines: (usize, usize),
/// Every rung above the selected one that was tried, and why it lost.
pub failed: Vec<(Rung, String)>,
}
impl Status {
/// "Hexagon NPU · int8 · ONNX Runtime 1.29" — the settings row's text.
pub fn line(&self) -> String {
let form = match self.rung {
Rung::Hexagon => " · int8",
Rung::TensorRt => " · fp16",
_ => "",
};
format!("{}{} · {}", self.rung.label(), form, self.runtime.label())
}
}
/// A model the caller can run, whatever is or is not loaded right now.
///
/// Holds the bytes, not a session. [`Model::acquire`] finds the loaded copy
/// in the registry — shared with every other holder of the same model —
/// or loads one, and every acquire refreshes the copy's last-used time.
/// The reaper unloads anything idle for [`Config::decay`]; a scan that runs
/// the detector on every image never lets it go idle, a click in the
/// develop view lets the segmenter go after a quiet spell, and a handle
/// used again after that simply loads again. Nobody states a policy.
///
/// The registry key includes the rung, so a reload after a compiled engine
/// has landed moves up to it by itself (§6 step 4).
pub struct Model {
role: Role,
form: Form,
bytes: Arc<[u8]>,
/// `engines::hash` of the bytes, taken once: an acquire per tile of a
/// border fill must not hash 28 MB each time.
hash: u64,
}
/// A loaded session, held for one `run` and its output decoding.
pub struct Acquired {
entry: Arc<Loaded>,
}
struct Loaded {
rung: Rung,
session: Mutex<Session>,
last_used: Mutex<Instant>,
}
impl Model {
/// The loaded session, loading it if the reaper took it. Lock it for
/// one run; a scan and a develop click can want the same detector at
/// once, and the second waits on the first.
pub fn acquire(&self) -> Result<Acquired, Error> {
acquire(self.role, self.form, &self.bytes, self.hash)
}
pub fn form(&self) -> Form {
self.form
}
}
impl Acquired {
pub fn lock(&self) -> MutexGuard<'_, Session> {
self.entry.session.lock().unwrap_or_else(|e| e.into_inner())
}
/// Where this session runs.
pub fn rung(&self) -> Rung {
self.entry.rung
}
}
impl Drop for Acquired {
fn drop(&mut self) {
// The clock starts when the use ends, not when it began: a long run
// is not idle time.
*self.entry.last_used.lock().unwrap() = Instant::now();
}
}
type Registry = HashMap<String, Arc<Loaded>>;
static REGISTRY: OnceLock<Mutex<Registry>> = OnceLock::new();
fn registry() -> &'static Mutex<Registry> {
REGISTRY.get_or_init(|| {
std::thread::Builder::new()
.name("inference-reaper".into())
.spawn(|| loop {
std::thread::sleep(Duration::from_secs(5));
release_idle();
})
.expect("spawn inference reaper");
Mutex::new(HashMap::new())
})
}
fn acquire(role: Role, form: Form, bytes: &Arc<[u8]>, hash: u64) -> Result<Acquired, Error> {
api::ensure_installed();
let (rung, cfg) = {
let s = state().lock().unwrap();
let selected = current_rung(&s);
(
effective_rung(&s, selected, role, form, hash),
s.config.clone(),
)
};
let key = format!("{role:?}:{}", engines::key_of(rung, hash));
if let Some(entry) = registry().lock().unwrap().get(&key).cloned() {
*entry.last_used.lock().unwrap() = Instant::now();
return Ok(Acquired { entry });
}
// Built outside the registry lock: a TensorRT engine load is long enough
// that another role's acquire should not wait on it.
let session = session::build(rung, role, bytes, &cfg)?;
log::debug!("inference: {role:?} loaded on {}", rung.label());
let entry = Arc::new(Loaded {
rung,
session: Mutex::new(session),
last_used: Mutex::new(Instant::now()),
});
let mut reg = registry().lock().unwrap();
// Two acquires raced; keep the first, drop this one.
let entry = reg.entry(key).or_insert_with(|| entry.clone()).clone();
Ok(Acquired { entry })
}
/// Unload every session idle for longer than the decay. The reaper does
/// this every five seconds. A session in use survives until its run ends:
/// the `Acquired` holds it, the registry merely forgets it.
pub fn release_idle() {
let decay = match state().lock().unwrap().config.decay {
Duration::ZERO => DEFAULT_DECAY,
d => d,
};
let now = Instant::now();
registry()
.lock()
.unwrap()
.retain(|_, e| now.duration_since(*e.last_used.lock().unwrap()) < decay);
}
/// Unload every session now, decay or not — what a low-memory signal
/// asks for. Sessions mid-run finish first.
pub fn release_all() {
registry().lock().unwrap().clear();
}
/// Unload every session of `role` now — "I am done segmenting".
pub fn unload(role: Role) {
let prefix = format!("{role:?}:");
registry()
.lock()
.unwrap()
.retain(|k, _| !k.starts_with(&prefix));
}
/// How many sessions are loaded, for the settings row and the tests.
pub fn loaded() -> usize {
registry().lock().unwrap().len()
}
#[derive(Debug, thiserror::Error)]
pub enum Error {
#[error(transparent)]
Inference(#[from] ort::Error),
#[error("reading model: {0}")]
Io(#[from] std::io::Error),
}
/// What the probe writes and the next launch reads (§4 step 3).
#[derive(Clone, Debug, Default, Serialize, Deserialize)]
struct Cache {
/// Runtime, driver, hardware and model identity; any change re-probes.
fingerprint: String,
rung: Option<Rung>,
reason: String,
/// Model hashes whose engine exists on disk, per compiling rung.
compiled: BTreeSet<String>,
/// Rungs that failed under this fingerprint, and why. Not retried until
/// the fingerprint changes: a wedged driver must not cost every launch
/// thirty seconds.
failed: Vec<(Rung, String)>,
}
struct State {
config: Config,
cache: Cache,
probing: bool,
wanted: usize,
}
static STATE: OnceLock<Mutex<State>> = OnceLock::new();
fn state() -> &'static Mutex<State> {
STATE.get_or_init(|| {
Mutex::new(State {
config: Config::default(),
cache: Cache::default(),
probing: false,
wanted: 0,
})
})
}
/// Choose the runtime and start the probe. Idempotent; the first call wins.
///
/// Returns at once: the probe and any engine compilation run on their own
/// low-priority thread, and every request meanwhile is served by the floor
/// (§4). Never blocks the first frame.
pub fn init(config: Config) {
let runtime = api::install(&config.runtime_dirs);
{
let mut s = state().lock().unwrap();
if s.probing || s.cache.rung.is_some() {
return;
}
s.config = config;
s.probing = true;
}
log::info!("inference: runtime {}", runtime.label());
std::thread::Builder::new()
.name("inference-probe".into())
.spawn(move || {
probe::run(runtime);
engines::run();
})
.expect("spawn inference probe");
}
/// Make sure `ort` has an API table, for code that drives `ort` directly.
/// [`open`] does this itself; only the M1 probe example needs it by name.
pub fn ensure_runtime() {
api::ensure_installed();
}
/// The line for the settings row.
pub fn status() -> Status {
let s = state().lock().unwrap();
let rung = current_rung(&s);
Status {
runtime: api::runtime(),
rung,
reason: s.cache.reason.clone(),
failed: s.cache.failed.clone(),
probing: s.probing,
engines: if rung.compiles() {
(s.cache.compiled.len(), s.wanted)
} else {
(0, 0)
},
}
}
fn current_rung(s: &State) -> Rung {
if s.probing {
Rung::Cpu
} else {
s.cache.rung.unwrap_or(Rung::Cpu)
}
}
/// The file to load for `role` under the current selection, and its form.
///
/// A rung that wants int8 gets the `.int8.onnx` sibling of the canonical file
/// if it exists; otherwise the canonical file, on the rung's fallback. A
/// caller adds [`form_suffix`] to the `model_id` it records.
pub fn resolve_model(role: Role, canonical: &Path) -> (PathBuf, Form) {
let rung = current_rung(&state().lock().unwrap());
if rung.serves(role) && rung.form(role) == Form::Int8 {
let sibling = int8_sibling(canonical);
if sibling.is_file() {
return (sibling, Form::Int8);
}
}
(canonical.to_path_buf(), Form::F32)
}
fn int8_sibling(canonical: &Path) -> PathBuf {
let stem = canonical
.file_stem()
.map(|s| s.to_string_lossy().into_owned())
.unwrap_or_default();
canonical.with_file_name(format!("{stem}.int8.onnx"))
}
/// What a form appends to a detector's `model_id` (§7).
pub fn form_suffix(form: Form) -> &'static str {
match form {
Form::F32 => "",
Form::Int8 => "_i8",
}
}
/// A handle on the model `bytes` in `role`.
///
/// Loads it once here, so a graph the runtime rejects fails at
/// construction and not on the first image; what happens to that session
/// afterwards is the registry's business (see [`Model`]).
///
/// Works without [`init`] — a test, or the examples — by installing tract
/// and using the CPU rung, which is exactly what every consumer did before
/// this crate existed.
pub fn open(role: Role, form: Form, bytes: &[u8]) -> Result<Model, Error> {
let bytes: Arc<[u8]> = Arc::from(bytes);
let hash = engines::hash(&bytes);
acquire(role, form, &bytes, hash)?;
Ok(Model {
role,
form,
bytes,
hash,
})
}
/// Where a request lands: the selected rung unless the role's precision rule,
/// the form on offer, or a missing engine says one lower (§6 step 4).
fn effective_rung(s: &State, selected: Rung, role: Role, form: Form, hash: u64) -> Rung {
let mut rung = selected;
if !rung.serves(role) || rung.form(role) != form {
// The embedder on a Hexagon device, or an f32 detector where the int8
// sibling was missing: neither can go to the NPU.
rung = rung.fallback();
}
if rung.compiles() && !s.cache.compiled.contains(&engines::key_of(rung, hash)) {
rung = rung.fallback();
}
rung
}
#[cfg(test)]
mod tests {
use super::*;
/// The registry is one per process, so these run one at a time.
static SERIAL: Mutex<()> = Mutex::new(());
fn serial() -> MutexGuard<'static, ()> {
SERIAL.lock().unwrap_or_else(|e| e.into_inner())
}
/// The smallest shipped graph, if this checkout has the weights; a test
/// suite that needs a research-licensed download is one that does not
/// run in CI (docs/faces.md §3), so absence is a skip.
fn probe_bytes() -> Option<Vec<u8>> {
let path = concat!(
env!("CARGO_MANIFEST_DIR"),
"/../../models/face/scrfd_500m_640.onnx"
);
let bytes = std::fs::read(path).ok()?;
(bytes.len() > 100_000).then_some(bytes)
}
#[test]
fn two_handles_on_one_model_share_one_session() {
let _serial = serial();
let Some(bytes) = probe_bytes() else { return };
release_all();
let a = open(Role::Detector, Form::F32, &bytes).unwrap();
let b = open(Role::Detector, Form::F32, &bytes).unwrap();
assert_eq!(loaded(), 1);
let (x, y) = (a.acquire().unwrap(), b.acquire().unwrap());
assert!(Arc::ptr_eq(&x.entry, &y.entry));
}
#[test]
fn a_released_model_reloads_on_its_next_use() {
let _serial = serial();
let Some(bytes) = probe_bytes() else { return };
release_all();
let model = open(Role::Detector, Form::F32, &bytes).unwrap();
assert_eq!(loaded(), 1);
release_all();
assert_eq!(loaded(), 0);
let acquired = model.acquire().unwrap();
assert_eq!(loaded(), 1);
assert_eq!(acquired.lock().inputs().len(), 1);
}
#[test]
fn an_idle_session_decays_and_a_used_one_does_not() {
let _serial = serial();
let Some(bytes) = probe_bytes() else { return };
release_all();
state().lock().unwrap().config.decay = Duration::from_millis(50);
let model = open(Role::Detector, Form::F32, &bytes).unwrap();
// Used within the decay: stays.
std::thread::sleep(Duration::from_millis(30));
drop(model.acquire().unwrap());
release_idle();
assert_eq!(loaded(), 1);
// Idle past it: goes.
std::thread::sleep(Duration::from_millis(80));
release_idle();
assert_eq!(loaded(), 0);
state().lock().unwrap().config.decay = Duration::ZERO;
}
#[test]
fn unload_by_role_leaves_the_other_roles() {
let _serial = serial();
let Some(bytes) = probe_bytes() else { return };
release_all();
let _d = open(Role::Detector, Form::F32, &bytes).unwrap();
let _s = open(Role::Segmenter, Form::F32, &bytes).unwrap();
assert_eq!(loaded(), 2);
unload(Role::Segmenter);
assert_eq!(loaded(), 1);
}
#[test]
fn the_hexagon_never_takes_the_embedder() {
assert!(!Rung::Hexagon.serves(Role::Embedder));
assert!(Rung::Hexagon.serves(Role::Detector));
assert_eq!(Rung::Hexagon.form(Role::Detector), Form::Int8);
// A detector offered in f32 on a Hexagon device lands on the CPU.
let s = State {
config: Config::default(),
cache: Cache {
rung: Some(Rung::Hexagon),
..Cache::default()
},
probing: false,
wanted: 0,
};
assert_eq!(
effective_rung(
&s,
Rung::Hexagon,
Role::Embedder,
Form::F32,
engines::hash(b"")
),
Rung::Cpu
);
assert_eq!(
effective_rung(
&s,
Rung::Hexagon,
Role::Detector,
Form::F32,
engines::hash(b"")
),
Rung::Cpu
);
// An int8 detector whose context is not compiled yet: also the CPU.
assert_eq!(
effective_rung(
&s,
Rung::Hexagon,
Role::Detector,
Form::Int8,
engines::hash(b"")
),
Rung::Cpu
);
}
#[test]
fn the_status_line_reads_as_the_floor_before_init() {
let s = status();
assert_eq!(s.rung, Rung::Cpu);
assert!(s.line().starts_with("CPU"), "{}", s.line());
}
}
+302
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//! Walk the ladder, once, by building real sessions (docs/inference.md §4).
//!
//! A rung is taken when a session builds on it, runs, and is faster than
//! the floor. Both halves matter: a provider can register and then fail at
//! partition time, and a provider can take a graph — or quietly hand most
//! of it back to the CPU — and run it slower than the CPU would have. The outcome is cached against a fingerprint of the
//! runtime, the driver, the hardware and the models, and trusted until any
//! of those changes.
use std::path::{Path, PathBuf};
use std::time::Instant;
use crate::{api::Runtime, state, Cache, Config, Form, Role, Rung};
/// The rungs to try on this platform, best first, under the user's ceiling.
fn ladder(ceiling: Option<Rung>) -> Vec<Rung> {
#[cfg(target_os = "android")]
let all = [Rung::Hexagon];
#[cfg(not(target_os = "android"))]
let all = [Rung::TensorRt, Rung::Cuda];
all.into_iter()
.filter(|r| ceiling.is_none_or(|c| *r <= c))
.collect()
}
/// The probe body. Sets the cache and clears `probing` when done; never
/// panics out, because a failed probe is a result (the floor) and not an
/// error.
pub fn run(runtime: Runtime) {
let cfg = state().lock().unwrap().config.clone();
let fingerprint = fingerprint(&runtime, &cfg);
if let Some(cached) = read_cache(&cfg) {
if cached.fingerprint == fingerprint && cached.rung.is_some() {
log::info!(
"inference: cached selection {} ({})",
cached.rung.unwrap().label(),
cached.reason
);
finish(cached);
return;
}
}
let mut cache = Cache {
fingerprint,
..Cache::default()
};
if !runtime.is_native() {
cache.rung = Some(Rung::Cpu);
cache.reason = "no ONNX Runtime found; tract on one core".into();
write_cache(&cfg, &cache);
finish(cache);
return;
}
let Some((role, canonical)) = probe_model(&cfg) else {
cache.rung = Some(Rung::Cpu);
cache.reason = "no model to probe with".into();
write_cache(&cfg, &cache);
finish(cache);
return;
};
let floor = match time_rung(Rung::Cpu, role, &canonical, &cfg) {
Ok((ms, _)) => ms,
Err(e) => {
// The CPU provider failing is the runtime failing; there is
// nothing below it to try, and the reason is worth reading.
cache.rung = Some(Rung::Cpu);
cache.reason = format!("CPU provider failed: {e}");
write_cache(&cfg, &cache);
finish(cache);
return;
}
};
log::info!("inference: floor {floor:.1} ms on the CPU provider");
for rung in ladder(cfg.ceiling) {
match time_rung(rung, role, &canonical, &cfg) {
Ok((ms, key)) if ms < floor => {
cache.rung = Some(rung);
cache.reason = format!("{ms:.1} ms against {floor:.1} ms on the CPU");
if let Some(key) = key {
cache.compiled.insert(key);
}
break;
}
Ok((ms, _)) => {
let why = format!("{ms:.1} ms, slower than the CPU's {floor:.1} ms");
log::info!("inference: {} rejected: {why}", rung.label());
cache.failed.push((rung, why));
}
Err(e) => {
log::info!("inference: {} failed: {e}", rung.label());
cache.failed.push((rung, e));
}
}
}
if cache.rung.is_none() {
cache.rung = Some(Rung::Cpu);
cache.reason = match cache.failed.first() {
Some((r, why)) => format!("{} {}", r.label(), first_line(why)),
None => "the only rung on this platform".into(),
};
}
write_cache(&cfg, &cache);
finish(cache);
}
fn finish(cache: Cache) {
let mut s = state().lock().unwrap();
s.cache = cache;
s.probing = false;
}
/// The smallest detector, or the smallest model of any role if there is
/// none. A ~2 MB detector is the cheapest real test of a provider, and the
/// detector is the role the int8 forms exist for — the eye classifiers are
/// smaller still, and a Hexagon probed with one would fail for want of a
/// form nobody ships.
fn probe_model(cfg: &Config) -> Option<(Role, PathBuf)> {
let smallest = |want: Option<Role>| {
cfg.models
.iter()
.filter(|(role, _)| want.is_none_or(|w| *role == w))
.filter_map(|(role, path)| {
let size = std::fs::metadata(path).ok()?.len();
Some((size, *role, path.clone()))
})
.min_by_key(|(size, _, _)| *size)
.map(|(_, role, path)| (role, path))
};
smallest(Some(Role::Detector)).or_else(|| smallest(None))
}
/// Build, run once for the engine, then time three runs; the median in
/// milliseconds and, for a compiling rung, the cache key of the engine this
/// just built.
fn time_rung(
rung: Rung,
role: Role,
canonical: &Path,
cfg: &Config,
) -> Result<(f64, Option<String>), String> {
let want = rung.form(role);
let path = match want {
Form::Int8 => {
let p = crate::int8_sibling(canonical);
if !p.is_file() {
return Err(format!("no int8 form of {}", canonical.display()));
}
p
}
Form::F32 => canonical.to_path_buf(),
};
let bytes = std::fs::read(&path).map_err(|e| e.to_string())?;
let started = Instant::now();
let mut session =
crate::session::build(rung, role, &bytes, cfg).map_err(|e| first_line(&e.to_string()))?;
log::info!(
"inference: {} session built in {:.1} s",
rung.label(),
started.elapsed().as_secs_f64()
);
let shape: Vec<usize> = session.inputs()[0]
.dtype()
.tensor_shape()
.ok_or("model input is not a tensor")?
.iter()
.map(|&d| if d > 0 { d as usize } else { 1 })
.collect();
let zeros = vec![0f32; shape.iter().product()];
let run = |session: &mut ort::session::Session| -> Result<f64, String> {
let input = ort::value::Tensor::from_array((shape.clone(), zeros.clone()))
.map_err(|e| e.to_string())?;
let t = Instant::now();
let out = session
.run(ort::inputs![input])
.map_err(|e| e.to_string())?;
let _ = out[0]
.try_extract_tensor::<f32>()
.map_err(|e| e.to_string())?;
Ok(t.elapsed().as_secs_f64() * 1e3)
};
run(&mut session)?;
let mut times = [run(&mut session)?, run(&mut session)?, run(&mut session)?];
times.sort_by(|a, b| a.partial_cmp(b).unwrap());
let key = rung.compiles().then(|| crate::engines::key(rung, &bytes));
Ok((times[1], key))
}
/// The part of a provider's error a person can act on. ONNX Runtime's
/// begin with a source path and a C++ template signature; the words —
/// "CUDA failure 999: unknown error", "FAIL : Failed to load library" —
/// come after, and the settings row has room for one line of them.
fn first_line(s: &str) -> String {
let line = s.lines().next().unwrap_or("");
let start = ["failure", "FAIL :", "Error:", "error:"]
.iter()
.filter_map(|m| line.find(m))
.min()
.unwrap_or(0);
line[start..].chars().take(200).collect()
}
/// Everything a change of which should re-probe: the runtime and where it
/// came from, this crate, the platform, the driver or SoC, and the models.
fn fingerprint(runtime: &Runtime, cfg: &Config) -> String {
let mut parts = vec![
format!("engine {}", env!("CARGO_PKG_VERSION")),
format!("{} {}", std::env::consts::OS, std::env::consts::ARCH),
match runtime {
Runtime::Tract => "tract".to_string(),
Runtime::OnnxRuntime { path, version } => format!("ort {version} {}", path.display()),
},
device_identity(),
];
for (role, bytes) in &cfg.embedded {
parts.push(format!(
"{role:?} embedded {:016x}",
crate::engines::hash(bytes)
));
}
for (role, path) in &cfg.models {
let hash = std::fs::read(path)
.map(|b| crate::engines::hash(&b))
.unwrap_or(0);
parts.push(format!("{role:?} {hash:016x}"));
let int8 = crate::int8_sibling(path);
if let Ok(b) = std::fs::read(&int8) {
parts.push(format!("{role:?} int8 {:016x}", crate::engines::hash(&b)));
}
}
parts.join("\n")
}
#[cfg(target_os = "linux")]
fn device_identity() -> String {
// The NVIDIA driver's version line; absent means no NVIDIA driver.
std::fs::read_to_string("/proc/driver/nvidia/version")
.ok()
.and_then(|s| s.lines().next().map(str::to_string))
.unwrap_or_else(|| "no nvidia driver".into())
}
#[cfg(target_os = "android")]
fn device_identity() -> String {
// The SoC and the vendor's build: a Hexagon appears or disappears with
// either.
format!(
"{} {}",
system_property("ro.soc.model"),
system_property("ro.build.version.incremental")
)
}
#[cfg(target_os = "android")]
fn system_property(name: &str) -> String {
extern "C" {
fn __system_property_get(
name: *const std::ffi::c_char,
value: *mut std::ffi::c_char,
) -> i32;
}
let name = std::ffi::CString::new(name).unwrap();
let mut buf = [0u8; 92]; // PROP_VALUE_MAX
// SAFETY: bionic's documented call; the buffer is PROP_VALUE_MAX bytes.
let n = unsafe { __system_property_get(name.as_ptr(), buf.as_mut_ptr().cast()) };
String::from_utf8_lossy(&buf[..n.max(0) as usize]).into_owned()
}
#[cfg(not(any(target_os = "linux", target_os = "android")))]
fn device_identity() -> String {
String::new()
}
fn cache_path(cfg: &Config) -> PathBuf {
cfg.cache_dir.join("backend.json")
}
fn read_cache(cfg: &Config) -> Option<Cache> {
let text = std::fs::read_to_string(cache_path(cfg)).ok()?;
serde_json::from_str(&text).ok()
}
/// Written whole and renamed into place, so a reader never sees half.
pub fn write_cache(cfg: &Config, cache: &Cache) {
if cfg.cache_dir.as_os_str().is_empty() {
return;
}
let path = cache_path(cfg);
let tmp = path.with_extension("json.tmp");
let _ = std::fs::create_dir_all(&cfg.cache_dir);
if let Ok(text) = serde_json::to_string_pretty(cache) {
if std::fs::write(&tmp, text).is_ok() {
let _ = std::fs::rename(&tmp, &path);
}
}
}
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//! One session builder per rung (docs/inference.md §2, §7, §9).
use ort::session::Session;
use crate::{Config, Role, Rung};
/// Build a session for `bytes` on `rung`.
///
/// Not strict about the CPU: `session.disable_cpu_ep_fallback` was tried as
/// the probe's proof that a provider took the graph, and it refuses the
/// Hexagon over the ten quantise/dequantise nodes at the graph's edges that
/// QNN declines by policy and that cost microseconds. The probe's proof is
/// its clock instead (§4): a provider that hands real work to the CPU is
/// slower than the CPU floor and rejected by the same measurement.
pub fn build(rung: Rung, role: Role, bytes: &[u8], cfg: &Config) -> ort::Result<Session> {
// No optimisation level named. ONNX Runtime's default is already its
// fullest, and on tract any level but "disabled" means `into_optimized`,
// whose optimiser divides by zero inside yolo26n-seg (tract-data
// `stack_tensors`) — a panic across the C API, which is an abort. The
// app never asked tract for that and does not start now.
let mut b = Session::builder()?.with_intra_threads(threads(cfg))?;
// A Hexagon session loads the compiled context when there is one and
// compiles it from the model when there is not; the engine thread is
// what makes the second case rare (§6).
let context = (rung == Rung::Hexagon).then(|| crate::engines::context_path(cfg, bytes));
let ready = context.as_ref().is_some_and(|p| p.is_file());
b = providers(
b,
rung,
role,
cfg,
if ready { None } else { context.as_deref() },
)?;
match (ready, context) {
(true, Some(path)) => b.commit_from_file(path),
_ => b.commit_from_memory(bytes),
}
}
/// The intra-op pool: what the config says, else the cores less two for
/// the compositor and the decoder (§9). tract ignores it.
fn threads(cfg: &Config) -> usize {
if cfg.threads > 0 {
return cfg.threads;
}
std::thread::available_parallelism()
.map(|n| n.get().saturating_sub(2).max(1))
.unwrap_or(1)
}
#[cfg(not(target_os = "android"))]
fn providers(
b: ort::session::builder::SessionBuilder,
rung: Rung,
role: Role,
cfg: &Config,
_generate_context: Option<&std::path::Path>,
) -> ort::Result<ort::session::builder::SessionBuilder> {
use ort::ep;
match rung {
Rung::Cpu => Ok(b),
Rung::Cuda => {
Ok(b.with_execution_providers([ep::CUDA::default().build().error_on_failure()])?)
}
Rung::TensorRt => {
let cache = cfg.cache_dir.join("tensorrt");
let _ = std::fs::create_dir_all(&cache);
let cache = cache.to_string_lossy().into_owned();
// fp16 for everything but the embedder, whose comparability
// across devices is worth more than its 0.2 ms (§7). The
// workspace cap keeps the develop view's tiles on the card
// (NFR-RES-2). CUDA behind it takes any node TensorRT declines.
Ok(b.with_execution_providers([
ep::TensorRT::default()
.with_fp16(role != Role::Embedder)
.with_engine_cache(true)
.with_engine_cache_path(&cache)
.with_timing_cache(true)
.with_timing_cache_path(&cache)
.with_max_workspace_size(512 << 20)
.build()
.error_on_failure(),
ep::CUDA::default().build(),
])?)
}
Rung::Hexagon => unreachable!("the Hexagon rung is not on a desktop ladder"),
}
}
#[cfg(target_os = "android")]
fn providers(
b: ort::session::builder::SessionBuilder,
rung: Rung,
_role: Role,
_cfg: &Config,
generate_context: Option<&std::path::Path>,
) -> ort::Result<ort::session::builder::SessionBuilder> {
use ort::ep;
match rung {
Rung::Cpu => Ok(b),
Rung::Hexagon => {
// The HTP compiles the graph once per device (0.8–1.7 s here).
// With `ep.context_enable` ONNX Runtime writes the compiled
// context beside the probe cache; the next session loads that
// file as its model and skips the compile (§5).
let mut b = b;
if let Some(ctx) = generate_context {
let _ = std::fs::create_dir_all(ctx.parent().unwrap());
b = b
.with_config_entry("ep.context_enable", "1")?
.with_config_entry("ep.context_file_path", ctx.to_string_lossy())?
.with_config_entry("ep.context_embed_mode", "0")?;
}
// Quantise/dequantise at the graph's edges stay on the NPU too,
// so a strict build is a whole-graph build.
Ok(b.with_execution_providers([ep::QNN::default()
.with_backend_path("libQnnHtp.so")
.with_performance_mode(ep::qnn::PerformanceMode::Burst)
.with_offload_graph_io_quantization(false)
.build()
.error_on_failure()])?)
}
Rung::Cuda | Rung::TensorRt => unreachable!("no NVIDIA rung on Android"),
}
}
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[package]
name = "dr-pano"
version.workspace = true
edition.workspace = true
rust-version.workspace = true
license.workspace = true
# Guards against a Git LFS pointer being embedded in place of the weights.
build = "build.rs"
[dependencies]
thiserror.workspace = true
log.workspace = true
# Inference for the learned keypoint detector, on the same footing as
# `dr-segment`: `ort` is the API, `dr-inference-engine` decides what runs
# it (docs/inference.md), and both are optional so that the geometry —
# matching, the rotation solve, the projections — is a dependency-free crate
# that tests without a model.
ort = { workspace = true, optional = true }
dr-inference-engine = { workspace = true, optional = true }
ndarray = { workspace = true, optional = true }
[dev-dependencies]
# The example aligns real frames from their embedded previews.
dr-decode.workspace = true
dr-types.workspace = true
env_logger.workspace = true
[features]
default = ["xfeat", "embedded-model"]
# The XFeat detector (FR-MRG-8) and the MI-GAN filler (FR-MRG-4). Off, the
# crate has no model and no runtime — a build that only wants the geometry.
xfeat = ["dep:ort", "dep:dr-inference-engine", "dep:ndarray"]
# Compile the weights into the binary, for the same reason `dr-segment` does:
# Android hands the app no path to read a model from (ARCH §6.9).
embedded-model = ["xfeat"]
+48
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//! Check the model is a model and not an LFS pointer.
//!
//! `models/keypoints/*.onnx` is stored in Git LFS (see `.gitattributes`). A
//! clone made without git-lfs, or with `GIT_LFS_SKIP_SMUDGE` set, leaves a
//! ~130-byte text pointer at that path instead of the weights, and
//! `include_bytes!` would embed it without complaint. Same guard as
//! `dr-segment`'s, for the same failure.
use std::path::Path;
const MODELS: &[&str] = &[
"../../models/keypoints/xfeat-1024.onnx",
"../../models/keypoints/xfeat-768.onnx",
];
fn main() {
for m in MODELS {
println!("cargo:rerun-if-changed={m}");
}
println!("cargo:rerun-if-changed=build.rs");
if std::env::var_os("CARGO_FEATURE_EMBEDDED_MODEL").is_none() {
return;
}
for model in MODELS.iter().copied() {
check(model);
}
}
fn check(model: &str) {
let path = Path::new(model);
let Ok(bytes) = std::fs::read(path) else {
panic!(
"\n\n{model} is missing.\n\
It ships in Git LFS. Run `git lfs install && git lfs pull`, or build \
with `--no-default-features` for a geometry-only build.\n"
);
};
if bytes.starts_with(b"version https://git-lfs.github.com/spec/") {
panic!(
"\n\n{model} is a Git LFS pointer, not the model.\n\
Run `git lfs install && git lfs pull`, or build with \
`--no-default-features` for a geometry-only build.\n"
);
}
}
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//! Align real frames from their embedded previews and draw the result.
//!
//! ```sh
//! cargo run -p dr-pano --example align --release -- fixtures/pano/2025-08-05/*.CR2
//! cargo run -p dr-pano --example align --release -- out-prefix frame1.CR2 frame2.CR2 …
//! ```
//!
//! The point of looking rather than asserting: a rotation solve that is
//! numerically converged and geometrically wrong — a mirrored axis, a
//! transposed homography, an orientation applied the wrong way — produces
//! perfectly plausible residuals and a picture that is obviously broken.
//! This writes `<prefix>-cyl.ppm`: every frame's preview warped onto a
//! cylinder and averaged where they overlap, at a size that fits on a
//! screen. Ghosting in the overlaps is the alignment error, made visible.
//!
//! Previews, not RAW: the alignment runs on proxies in the application too
//! (FR-MRG-7), and a camera's embedded JPEG is a proxy the decoder already
//! extracts in milliseconds. What is different from the real path is only
//! that the pixels are the camera's rendering rather than ours, which the
//! geometry does not care about.
use std::path::PathBuf;
use std::time::Instant;
use dr_pano::bundle::Cameras;
use dr_pano::{align, xfeat::XFeat, AlignOptions, Gray, Projection};
fn main() {
env_logger::init();
let mut args: Vec<String> = std::env::args().skip(1).collect();
if args.is_empty() {
eprintln!("usage: align [out-prefix] <frame>...");
std::process::exit(2);
}
let prefix =
if args[0].ends_with(".CR2") || args[0].ends_with(".dng") || args[0].ends_with(".jpg") {
"align".to_string()
} else {
args.remove(0)
};
let paths: Vec<PathBuf> = args.iter().map(PathBuf::from).collect();
// Previews, oriented, at proxy size.
let t = Instant::now();
let mut proxies: Vec<Gray> = Vec::new();
for p in &paths {
let bytes = std::fs::read(p).expect("read");
let preview = dr_decode::extract_preview(&bytes, dr_decode::PreviewSize::Full)
.expect("embedded preview");
let orientation =
dr_decode::orientation(&bytes[..bytes.len().min(dr_decode::HEADER_BYTES as usize)])
.unwrap_or(dr_types::Orientation::NORMAL);
let tag = match orientation.quarter_turns {
1 => 6,
2 => 3,
3 => 8,
_ => 1,
};
let gray = Gray::from_rgba8(
&preview.rgba,
preview.width as usize,
preview.height as usize,
)
.oriented(tag);
let (fitted, _) = gray.fitted(
dr_pano::xfeat::INPUT_LONG_EDGE,
dr_pano::xfeat::INPUT_LONG_EDGE,
);
println!(
"{:<14} preview {}×{} orientation {} → proxy {}×{}",
p.file_name().unwrap().to_string_lossy(),
preview.width,
preview.height,
tag,
fitted.width,
fitted.height
);
proxies.push(fitted);
}
println!("previews in {:?}", t.elapsed());
// Keypoints.
let t = Instant::now();
let mut detector = XFeat::embedded().expect("model");
let features: Vec<_> = proxies
.iter()
.map(|g| detector.detect(g).expect("detect"))
.collect();
for (i, f) in features.iter().enumerate() {
println!("frame {i}: {} keypoints", f.len());
}
println!(
"detection in {:?} ({:?} per frame)",
t.elapsed(),
t.elapsed() / proxies.len() as u32
);
// Alignment.
let t = Instant::now();
let opts = AlignOptions::default();
let alignment = align(&features, &opts).expect("align");
println!("alignment in {:?}", t.elapsed());
println!(
"focal {:.1} px, long edge {} px ({:.1} mm on full frame), rms {:.3} px",
alignment.focal,
proxies[0].width.max(proxies[0].height),
alignment.focal * 36.0 / proxies[0].width.max(proxies[0].height) as f64,
alignment.rms_px
);
for l in &alignment.links {
println!(
" link {}–{}: {} inliers of {} matches",
l.i, l.j, l.inliers, l.matches
);
}
for (k, why) in &alignment.unaligned {
println!(" UNALIGNED frame {k}: {why}");
}
let root = alignment
.rotations
.iter()
.position(|r| *r == Some(dr_pano::linalg::Mat3::IDENTITY))
.unwrap_or(0);
for (k, r) in alignment.rotations.iter().enumerate() {
if let Some(r) = r {
// Yaw about y, pitch about x, roll about z, from the matrix's
// columns — enough to read a sweep by eye.
let yaw = r.0[0][2].atan2(r.0[2][2]).to_degrees();
let pitch = (-r.0[1][2]).asin().to_degrees();
let roll = r.0[1][0].atan2(r.0[1][1]).to_degrees();
println!(
" frame {k}: yaw {yaw:7.2}° pitch {pitch:6.2}° roll {roll:6.2}°{}",
if k == root { " (reference)" } else { "" }
);
}
}
if !alignment.is_complete() {
eprintln!("not drawing: the set is not fully aligned");
std::process::exit(1);
}
// Draw: a cylinder, averaged where frames overlap.
let t = Instant::now();
let cameras: Cameras = alignment.cameras();
let (fw, fh) = (proxies[0].width as f64, proxies[0].height as f64);
let scale = alignment.focal;
let bounds = dr_pano::projection::bounds(Projection::Cylindrical, scale, &cameras, (fw, fh))
.expect("bounds");
// Fit to 3000 px wide.
let out_w = 3000usize;
let px = bounds.width() / out_w as f64;
let out_h = (bounds.height() / px).ceil() as usize;
let mut sum = vec![0.0f32; out_w * out_h];
let mut count = vec![0u16; out_w * out_h];
for oy in 0..out_h {
for ox in 0..out_w {
let u = bounds.min_u + (ox as f64 + 0.5) * px;
let v = bounds.min_v + (oy as f64 + 0.5) * px;
let d = Projection::Cylindrical.to_direction(scale, u, v);
for (k, g) in proxies.iter().enumerate() {
let Some((x, y)) = cameras.project(k, d) else {
continue;
};
let (x, y) = (x + g.width as f64 / 2.0, y + g.height as f64 / 2.0);
if x < 0.0 || y < 0.0 || x >= g.width as f64 - 1.0 || y >= g.height as f64 - 1.0 {
continue;
}
let (x0, y0) = (x as usize, y as usize);
let (tx, ty) = ((x - x0 as f64) as f32, (y - y0 as f64) as f32);
let p = |xx: usize, yy: usize| g.data[yy * g.width + xx];
let val = (p(x0, y0) * (1.0 - tx) + p(x0 + 1, y0) * tx) * (1.0 - ty)
+ (p(x0, y0 + 1) * (1.0 - tx) + p(x0 + 1, y0 + 1) * tx) * ty;
sum[oy * out_w + ox] += val;
count[oy * out_w + ox] += 1;
}
}
}
let mut ppm = format!("P5\n{out_w} {out_h}\n255\n").into_bytes();
ppm.extend(sum.iter().zip(&count).map(|(s, c)| {
if *c == 0 {
0u8
} else {
((s / f32::from(*c)).clamp(0.0, 1.0) * 255.0) as u8
}
}));
let out = format!("{prefix}-cyl.pgm");
std::fs::write(&out, ppm).expect("write");
println!("wrote {out} ({out_w}×{out_h}) in {:?}", t.elapsed());
}
+459
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@@ -0,0 +1,459 @@
//! TRACES: FR-MRG-1 | FR-MRG-5
//! From features to cameras: the alignment of a whole set.
//!
//! 1. Match every pair of frames (`matching`).
//! 2. For each pair with enough matches, a robust homography
//! (`homography::ransac_homography`); a pair is a *link* when its inliers
//! pass Brown & Lowe's test, `n_inliers > 8 + 0.3 · n_matches`, which
//! is what separates a real overlap from a coincidence of descriptors.
//! 3. The focal length: the median of what the links' homographies imply,
//! or the caller's hint if none of them implies anything.
//! 4. A spanning tree over the links, strongest first, from the
//! best-connected frame; rotations chained along it.
//! 5. Bundle adjustment over every link's inliers (`bundle`).
//!
//! What it refuses to do is guess. A frame the tree does not reach is
//! reported by index with the reason (FR-MRG-5) and left out of the
//! cameras; the caller decides whether a set with a hole is worth
//! stitching, and the requirement says it is not.
use crate::bundle::{self, AdjustOptions, Cameras, Observation};
use crate::features::Features;
use crate::homography::{self, RobustHomography};
use crate::linalg::Mat3;
use crate::matching::{match_features, Match};
use crate::PanoError;
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct AlignOptions {
/// Descriptor similarity floor for a match (`matching`).
pub min_similarity: f32,
/// RANSAC agreement distance, in pixels of the features' image.
pub ransac_px: f64,
pub ransac_iterations: usize,
/// A pair needs at least this many inliers to be a link, on top of
/// Brown & Lowe's ratio test.
pub min_inliers: usize,
/// Focal length in pixels of the features' image, if the caller knows
/// it (EXIF and a sensor width). Used only when the homographies do not
/// determine one.
pub focal_hint: Option<f64>,
pub adjust: AdjustOptions,
/// For RANSAC's sampling: the same seed gives the same alignment
/// (NFR-MRG-2).
pub seed: u64,
}
impl Default for AlignOptions {
fn default() -> Self {
AlignOptions {
min_similarity: 0.82,
ransac_px: 3.0,
ransac_iterations: 1000,
min_inliers: 12,
focal_hint: None,
adjust: AdjustOptions::default(),
seed: 0x5eed,
}
}
}
/// An overlap the alignment trusts.
#[derive(Debug, Clone, PartialEq)]
pub struct Link {
pub i: usize,
pub j: usize,
pub matches: usize,
pub inliers: usize,
/// Maps centred points of `i` to centred points of `j`.
pub h: Mat3,
}
/// Why a frame is not in the alignment.
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum Unaligned {
/// Not enough matches with any other frame to try a geometry.
NoMatches,
/// Matches existed but none survived RANSAC as a real overlap.
NoOverlap,
/// Overlaps existed but only with frames that are themselves unaligned.
Disconnected,
}
impl std::fmt::Display for Unaligned {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.write_str(match self {
Unaligned::NoMatches => "too few matching features with any other frame",
Unaligned::NoOverlap => "no consistent overlap with any other frame",
Unaligned::Disconnected => "overlaps only with frames that could not be aligned",
})
}
}
/// The result: cameras for the aligned frames, and the rest named.
#[derive(Debug, Clone, PartialEq)]
pub struct Alignment {
/// One rotation per input frame, camera to world, for aligned frames;
/// `None` for the unaligned. The reference frame is the best-connected
/// one and has the identity.
pub rotations: Vec<Option<Mat3>>,
/// Focal length in pixels of the features' image.
pub focal: f64,
pub links: Vec<Link>,
pub unaligned: Vec<(usize, Unaligned)>,
/// Bundle adjustment's RMS reprojection error, in pixels.
pub rms_px: f64,
}
impl Alignment {
pub fn is_complete(&self) -> bool {
self.unaligned.is_empty()
}
/// The cameras of the aligned frames, indexed as the input — a frame
/// that is not aligned is given the identity, so this is only useful
/// when [`Self::is_complete`].
pub fn cameras(&self) -> Cameras {
Cameras {
rotations: self
.rotations
.iter()
.map(|r| r.unwrap_or(Mat3::IDENTITY))
.collect(),
focal: self.focal,
}
}
}
/// Align a set of frames from their features.
///
/// Every `Features` must be in its own frame's pixel coordinates with the
/// image size filled in; points are centred on the image centre here. The
/// frames must all come from the same lens at the same focal length, which
/// is the panorama assumption and not checked — the caller has the EXIF.
pub fn align(frames: &[Features], opts: &AlignOptions) -> Result<Alignment, PanoError> {
let n = frames.len();
if n < 2 {
return Err(PanoError::Input(
"a panorama needs at least two frames".into(),
));
}
let centre = |k: usize, i: usize| -> (f64, f64) {
let kp = frames[k].keypoints[i];
(
f64::from(kp.x) - frames[k].width as f64 / 2.0,
f64::from(kp.y) - frames[k].height as f64 / 2.0,
)
};
// Scale for the DLT's conditioning: points of order one.
let scale = 1.0
/ frames
.iter()
.map(|f| f.width.max(f.height) as f64)
.fold(1.0, f64::max);
// 1 + 2: every pair.
let mut links = Vec::new();
let mut observations: Vec<Observation> = Vec::new();
let mut matched_any = vec![false; n];
let t_match = std::time::Instant::now();
for i in 0..n {
for j in i + 1..n {
let matches: Vec<Match> = match_features(&frames[i], &frames[j], opts.min_similarity);
log::debug!("pair {i}-{j}: {} matches", matches.len());
if matches.len() < 4 {
continue;
}
matched_any[i] = true;
matched_any[j] = true;
let pairs: Vec<((f64, f64), (f64, f64))> = matches
.iter()
.map(|m| {
let (a, b) = (centre(i, m.a), centre(j, m.b));
((a.0 * scale, a.1 * scale), (b.0 * scale, b.1 * scale))
})
.collect();
let Some(RobustHomography { h, inliers }) = homography::ransac_homography(
&pairs,
opts.ransac_px * scale,
opts.ransac_iterations,
opts.seed ^ ((i as u64) << 32 | j as u64),
) else {
continue;
};
let needed = (8.0 + 0.3 * matches.len() as f64).ceil() as usize;
log::debug!("pair {i}-{j}: {} inliers, {needed} needed", inliers.len());
if inliers.len() <= needed || inliers.len() < opts.min_inliers {
continue;
}
// Back to pixels: H_px = S⁻¹ H S.
let m = h.0;
let h_px = Mat3([
[m[0][0], m[0][1], m[0][2] / scale],
[m[1][0], m[1][1], m[1][2] / scale],
[m[2][0] * scale, m[2][1] * scale, m[2][2]],
]);
for &k in &inliers {
let (a, b) = pairs[k];
observations.push(Observation {
i,
j,
pi: (a.0 / scale, a.1 / scale),
pj: (b.0 / scale, b.1 / scale),
});
}
links.push(Link {
i,
j,
matches: matches.len(),
inliers: inliers.len(),
h: h_px,
});
}
}
log::debug!("matching and pairwise geometry in {:?}", t_match.elapsed());
// 3: the focal length.
let mut estimates: Vec<f64> = links
.iter()
.filter_map(|l| homography::focal_from_homography(&l.h))
.filter(|f| f.is_finite() && *f > 0.0)
.collect();
let longest = frames
.iter()
.map(|f| f.width.max(f.height) as f64)
.fold(0.0, f64::max);
let focal = if !estimates.is_empty() {
estimates.sort_by(f64::total_cmp);
let median = estimates[estimates.len() / 2];
// A homography of a nearly pure pan can imply almost anything;
// clamp to the range a real lens on this sensor can reach.
median.clamp(0.3 * longest, 6.0 * longest)
} else if let Some(hint) = opts.focal_hint {
hint
} else {
// No overlap said anything and nobody told us: a normal lens.
longest
};
// 4: spanning tree, strongest link first, from the best-connected frame.
let mut rotations: Vec<Option<Mat3>> = vec![None; n];
let mut unaligned = Vec::new();
if links.is_empty() {
for (k, &matched) in matched_any.iter().enumerate() {
unaligned.push((
k,
if matched {
Unaligned::NoOverlap
} else {
Unaligned::NoMatches
},
));
}
return Ok(Alignment {
rotations,
focal,
links,
unaligned,
rms_px: 0.0,
});
}
let mut degree = vec![0usize; n];
for l in &links {
degree[l.i] += l.inliers;
degree[l.j] += l.inliers;
}
let root = (0..n).max_by_key(|&k| degree[k]).unwrap_or(0);
rotations[root] = Some(Mat3::IDENTITY);
loop {
// The strongest link from an aligned frame to an unaligned one.
let best = links
.iter()
.filter(|l| rotations[l.i].is_some() != rotations[l.j].is_some())
.max_by_key(|l| l.inliers);
let Some(l) = best else { break };
let r_ij = homography::rotation_from_homography(&l.h, focal);
// H_ij takes points of i to j, so bearings b_j = R_ij b_i, and with
// world = R_i · cam_i: R_j = R_i · R_ijᵀ.
if let Some(ri) = rotations[l.i] {
rotations[l.j] = Some((ri * r_ij.transpose()).orthonormalised());
} else if let Some(rj) = rotations[l.j] {
rotations[l.i] = Some((rj * r_ij).orthonormalised());
}
}
for k in 0..n {
if rotations[k].is_none() {
let reason = if !matched_any[k] {
Unaligned::NoMatches
} else if links.iter().any(|l| l.i == k || l.j == k) {
Unaligned::Disconnected
} else {
Unaligned::NoOverlap
};
unaligned.push((k, reason));
}
}
// 5: adjust the aligned frames together. The reference frame must be
// index 0 of the adjustment (it holds frame 0 fixed), so the aligned
// frames are renumbered with the root first.
let aligned: Vec<usize> = std::iter::once(root)
.chain((0..n).filter(|&k| k != root && rotations[k].is_some()))
.collect();
let index_of = |k: usize| aligned.iter().position(|&a| a == k);
let start = Cameras {
rotations: aligned.iter().map(|&k| rotations[k].unwrap()).collect(),
focal,
};
let obs: Vec<Observation> = observations
.iter()
.filter_map(|o| {
Some(Observation {
i: index_of(o.i)?,
j: index_of(o.j)?,
pi: o.pi,
pj: o.pj,
})
})
.collect();
let t_adjust = std::time::Instant::now();
let adjusted = bundle::adjust(start, &obs, &opts.adjust)?;
log::debug!(
"bundle adjustment: {} observations, {} iterations in {:?}",
obs.len(),
adjusted.iterations,
t_adjust.elapsed()
);
for (slot, &k) in aligned.iter().enumerate() {
rotations[k] = Some(adjusted.cameras.rotations[slot]);
}
Ok(Alignment {
rotations,
focal: adjusted.cameras.focal,
links,
unaligned,
rms_px: adjusted.rms_px,
})
}
#[cfg(test)]
mod tests {
use super::*;
use crate::features::{Keypoint, DESCRIPTOR_LEN};
use crate::linalg::Vec3;
/// Frames of a synthetic sweep: world directions with random unit
/// descriptors, each frame seeing the ones in its field of view.
fn synthetic_sweep(
n: usize,
step: f64,
f: f64,
w: usize,
h: usize,
) -> (Vec<Features>, Cameras) {
let mut seed = 777u64;
let mut rnd = || {
seed = seed
.wrapping_mul(6364136223846793005)
.wrapping_add(1442695040888963407);
((seed >> 33) as f64 / (1u64 << 31) as f64) - 0.5
};
let rotations: Vec<Mat3> = (0..n)
.map(|k| {
Mat3::rotation(Vec3::new(0.0, 1.0, 0.0), step * k as f64)
* Mat3::rotation(Vec3::new(1.0, 0.0, 0.0), 0.02 * ((k % 3) as f64 - 1.0))
})
.collect();
let truth = Cameras {
rotations,
focal: f,
};
let total = step * (n as f64 - 1.0);
let mut frames: Vec<Features> = (0..n)
.map(|_| Features {
keypoints: Vec::new(),
descriptors: Vec::new(),
width: w,
height: h,
})
.collect();
for _ in 0..600 * n {
let yaw = rnd() * (total + 0.8) + total / 2.0;
let pitch = rnd() * 0.5;
let d = Vec3::new(
yaw.sin() * pitch.cos(),
pitch.sin(),
yaw.cos() * pitch.cos(),
);
let desc: Vec<f32> = (0..DESCRIPTOR_LEN).map(|_| rnd() as f32).collect();
let norm = desc.iter().map(|v| v * v).sum::<f32>().sqrt();
let desc: Vec<f32> = desc.iter().map(|v| v / norm).collect();
for (k, frame) in frames.iter_mut().enumerate() {
if let Some(p) = truth.project(k, d) {
let (x, y) = (p.0 + w as f64 / 2.0, p.1 + h as f64 / 2.0);
if x >= 0.0 && x < w as f64 && y >= 0.0 && y < h as f64 {
frame.keypoints.push(Keypoint {
x: (x + rnd() * 0.6) as f32,
y: (y + rnd() * 0.6) as f32,
score: 1.0,
});
frame.descriptors.extend_from_slice(&desc);
}
}
}
}
(frames, truth)
}
fn angle_between(a: Mat3, b: Mat3) -> f64 {
(a.transpose() * b).log().norm()
}
#[test]
fn a_synthetic_sweep_is_aligned_to_its_truth() {
let (frames, truth) = synthetic_sweep(6, 0.3, 1400.0, 1024, 768);
let out = align(&frames, &AlignOptions::default()).expect("aligned");
assert!(out.is_complete(), "unaligned: {:?}", out.unaligned);
assert_eq!(out.links.len(), 5 + 4, "links: {}", out.links.len());
assert!((out.focal - 1400.0).abs() < 15.0, "focal {}", out.focal);
assert!(out.rms_px < 1.0, "rms {}", out.rms_px);
// Relative rotations match the truth's, whichever frame is the root.
let root = out
.rotations
.iter()
.position(|r| *r == Some(Mat3::IDENTITY))
.unwrap();
for k in 0..6 {
let rel_truth = truth.rotations[root].transpose() * truth.rotations[k];
let rel_out = out.rotations[k].unwrap();
let err = angle_between(rel_truth, rel_out);
assert!(err < 2e-3, "frame {k} off by {err} rad");
}
}
#[test]
fn a_frame_from_nowhere_is_named_not_guessed() {
let (mut frames, _) = synthetic_sweep(4, 0.3, 1400.0, 1024, 768);
// Frame 3 gets descriptors nobody else has.
for v in &mut frames[3].descriptors {
*v = -*v;
}
let out = align(&frames, &AlignOptions::default()).expect("aligned");
assert_eq!(out.unaligned.len(), 1);
assert_eq!(out.unaligned[0].0, 3);
assert!(out.rotations[3].is_none());
assert!(out.rotations[..3].iter().all(Option::is_some));
}
#[test]
fn one_frame_is_refused() {
let (frames, _) = synthetic_sweep(1, 0.3, 1400.0, 640, 480);
assert!(matches!(
align(&frames, &AlignOptions::default()),
Err(PanoError::Input(_))
));
}
}
+446
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@@ -0,0 +1,446 @@
//! Bundle adjustment: every rotation and the focal length, refined together.
//!
//! The pairwise homographies (`homography.rs`) each know about two frames.
//! Chained around a loop they disagree with themselves by the accumulated
//! error, and a twelve-frame sweep chained end to end drifts by a visible
//! amount. This solves for all the rotations at once, against every inlier
//! match of every pair, so the error is spread rather than accumulated —
//! Brown & Lowe's step 4, with the camera model reduced to what a panorama
//! needs: one rotation per frame and one focal length shared by all.
//!
//! Levenberg–Marquardt with a numerical Jacobian. Analytic derivatives of a
//! rotation's projection are not hard, but they are a second place the
//! model is written down, and the model is small: forty parameters, a few
//! thousand residuals, a Jacobian that costs forty residual evaluations.
//! The whole solve is milliseconds. Correctness over cleverness, and one
//! definition of the projection to keep right.
use crate::linalg::{DMat, Mat3, Vec3};
use crate::PanoError;
/// A point in one image, centred on the principal point, in pixels.
pub type Point = (f64, f64);
/// One inlier match between two frames.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct Observation {
pub i: usize,
pub j: usize,
pub pi: Point,
pub pj: Point,
}
/// What the adjustment starts from and returns: a rotation per frame
/// (camera to world; frame 0 is the world) and the focal length in pixels.
#[derive(Debug, Clone, PartialEq)]
pub struct Cameras {
pub rotations: Vec<Mat3>,
pub focal: f64,
}
impl Cameras {
/// The unit direction, in world space, that pixel `p` of frame `i` looks
/// along.
pub fn bearing(&self, i: usize, p: Point) -> Vec3 {
self.rotations[i] * Vec3::new(p.0, p.1, self.focal).normalised()
}
/// Where world direction `d` lands in frame `j`, or `None` if it is
/// behind the camera.
pub fn project(&self, j: usize, d: Vec3) -> Option<Point> {
let c = self.rotations[j].transpose() * d;
if c.z() <= 1e-9 {
return None;
}
Some((self.focal * c.x() / c.z(), self.focal * c.y() / c.z()))
}
}
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct AdjustOptions {
pub max_iterations: usize,
/// Residuals beyond this many pixels are down-weighted (Huber), so a
/// mismatch RANSAC let through pulls with bounded force.
pub huber_px: f64,
/// Whether the focal length is a free parameter. Off, it is held at the
/// starting value — for a set whose rotations are all small, the focal
/// length is weakly observable and better taken from the homographies'
/// median than pulled about by noise.
pub refine_focal: bool,
}
impl Default for AdjustOptions {
fn default() -> Self {
AdjustOptions {
max_iterations: 50,
huber_px: 3.0,
refine_focal: true,
}
}
}
/// The adjusted cameras and the fit.
#[derive(Debug, Clone, PartialEq)]
pub struct Adjusted {
pub cameras: Cameras,
/// Root-mean-square reprojection error over all observations, in pixels
/// (unweighted, so an outlier RANSAC missed shows here rather than
/// hiding under its Huber weight).
pub rms_px: f64,
pub iterations: usize,
}
/// Refine `start` against `observations`.
///
/// Frame 0's rotation is held fixed: the world frame is arbitrary and
/// fixing one camera removes the freedom. Every other frame must appear in
/// at least one observation or its rotation is undetermined and the normal
/// equations are singular — the caller (`align`) guarantees it by only
/// adjusting frames a spanning tree reached.
pub fn adjust(
start: Cameras,
observations: &[Observation],
opts: &AdjustOptions,
) -> Result<Adjusted, PanoError> {
let n_frames = start.rotations.len();
if n_frames < 2 || observations.is_empty() {
let rms = rms(&start, observations);
return Ok(Adjusted {
cameras: start,
rms_px: rms,
iterations: 0,
});
}
// Every adjustable frame must be constrained by something, or its
// block of the normal equations is zero and the solve is meaningless —
// checked here, by name, rather than left to surface as a step that
// fails to lower the cost.
let mut seen = vec![false; n_frames];
for o in observations {
seen[o.i] = true;
seen[o.j] = true;
}
if let Some(k) = (1..n_frames).find(|&k| !seen[k]) {
return Err(PanoError::Geometry(format!(
"frame {k} has no observations constraining it"
)));
}
let n_rot = 3 * (n_frames - 1);
let n_params = n_rot + usize::from(opts.refine_focal);
let n_res = 2 * observations.len();
// Parameters are *increments* on the current cameras, re-applied each
// accepted step: rotation k ← exp(δ_k) · rotation k, focal ← f · exp(δ_f).
// Composing on the left keeps the increment in world space, where a
// small rotation means the same thing for every frame.
let apply = |base: &Cameras, x: &[f64]| -> Cameras {
let mut rotations = base.rotations.clone();
for k in 1..n_frames {
let w = Vec3::new(x[3 * (k - 1)], x[3 * (k - 1) + 1], x[3 * (k - 1) + 2]);
rotations[k] = (Mat3::exp(w) * base.rotations[k]).orthonormalised();
}
let focal = if opts.refine_focal {
base.focal * x[n_rot].exp()
} else {
base.focal
};
Cameras { rotations, focal }
};
let residuals = |c: &Cameras, out: &mut Vec<f64>| {
out.clear();
for o in observations {
let d = c.bearing(o.i, o.pi);
match c.project(o.j, d) {
Some((x, y)) => {
out.push(x - o.pj.0);
out.push(y - o.pj.1);
}
None => {
// Behind the camera: as wrong as a residual can be
// without being infinite. The Huber weight caps its pull.
out.push(1e4);
out.push(1e4);
}
}
}
};
let weights = |r: &[f64], out: &mut Vec<f64>| {
out.clear();
for pair in r.chunks_exact(2) {
let m = (pair[0] * pair[0] + pair[1] * pair[1]).sqrt();
let w = if m > opts.huber_px {
opts.huber_px / m
} else {
1.0
};
out.push(w);
out.push(w);
}
};
// The robust cost itself, not the weighted sum of squares: the weights
// above are the IRLS linearisation for one step, and comparing two
// steps by sums taken under different weights would accept the wrong
// ones. Huber: quadratic within the threshold, linear beyond it.
let cost = |r: &[f64]| -> f64 {
r.chunks_exact(2)
.map(|pair| {
let m = (pair[0] * pair[0] + pair[1] * pair[1]).sqrt();
if m <= opts.huber_px {
m * m
} else {
2.0 * opts.huber_px * m - opts.huber_px * opts.huber_px
}
})
.sum()
};
let mut cameras = start;
let mut r = Vec::with_capacity(n_res);
let mut w = Vec::with_capacity(n_res);
residuals(&cameras, &mut r);
weights(&r, &mut w);
let mut current = cost(&r);
let mut lambda = 1e-3;
let mut jac = vec![0.0f64; n_res * n_params];
let mut r_plus = Vec::with_capacity(n_res);
let zero = vec![0.0f64; n_params];
let mut iterations = 0;
for _ in 0..opts.max_iterations {
iterations += 1;
// Numerical Jacobian about the current cameras (x = 0).
const H: f64 = 1e-6;
for p in 0..n_params {
let mut x = zero.clone();
x[p] = H;
let c_plus = apply(&cameras, &x);
residuals(&c_plus, &mut r_plus);
for (k, (rp, r0)) in r_plus.iter().zip(&r).enumerate() {
jac[k * n_params + p] = (rp - r0) / H;
}
}
// Normal equations, weighted: (JᵀWJ + λ·diag) δ = −JᵀWr.
let mut a = DMat::zeros(n_params);
let mut b = vec![0.0f64; n_params];
for k in 0..n_res {
let row = &jac[k * n_params..(k + 1) * n_params];
let wk = w[k];
for p in 0..n_params {
b[p] -= wk * row[p] * r[k];
for q in 0..n_params {
a[(p, q)] += wk * row[p] * row[q];
}
}
}
// Try steps with increasing damping until one lowers the cost.
let mut accepted = false;
for _ in 0..10 {
let mut damped = a.clone();
for p in 0..n_params {
let d = a[(p, p)];
damped[(p, p)] = d + lambda * d.max(1e-9);
}
let Some(delta) = damped.solve_spd(&b) else {
return Err(PanoError::Geometry(
"the adjustment's normal equations are singular: a frame has no \
observations constraining it"
.into(),
));
};
let candidate = apply(&cameras, &delta);
residuals(&candidate, &mut r_plus);
let c_new = cost(&r_plus);
if c_new < current {
let improvement = (current - c_new) / current.max(1e-12);
let step: f64 = delta.iter().map(|d| d * d).sum::<f64>().sqrt();
cameras = candidate;
std::mem::swap(&mut r, &mut r_plus);
weights(&r, &mut w);
current = c_new;
lambda = (lambda / 3.0).max(1e-9);
accepted = true;
// Converged when a *lightly damped* step no longer helps. A
// heavily damped step is small by construction and would
// pass an improvement test long before the minimum.
if step < 1e-10 || (improvement < 1e-8 && lambda < 1e-2) {
return Ok(Adjusted {
rms_px: rms(&cameras, observations),
cameras,
iterations,
});
}
break;
}
lambda *= 5.0;
}
if !accepted {
break;
}
}
Ok(Adjusted {
rms_px: rms(&cameras, observations),
cameras,
iterations,
})
}
/// Unweighted RMS reprojection error in pixels.
pub fn rms(c: &Cameras, observations: &[Observation]) -> f64 {
if observations.is_empty() {
return 0.0;
}
let sum: f64 = observations
.iter()
.map(|o| match c.project(o.j, c.bearing(o.i, o.pi)) {
Some((x, y)) => (x - o.pj.0).powi(2) + (y - o.pj.1).powi(2),
None => 1e8,
})
.sum();
(sum / observations.len() as f64).sqrt()
}
#[cfg(test)]
mod tests {
use super::*;
/// A synthetic sweep: `n` cameras panned by `step` radians each with a
/// little pitch and roll, `f` pixels, and matches between neighbours
/// from a cloud of world directions.
fn sweep(n: usize, step: f64, f: f64, noise_px: f64) -> (Cameras, Vec<Observation>) {
let mut rotations = Vec::new();
for k in 0..n {
let yaw = step * k as f64;
let pitch = 0.01 * ((k * 7) % 3) as f64;
let roll = 0.005 * ((k * 5) % 4) as f64;
let r = Mat3::rotation(Vec3::new(0.0, 1.0, 0.0), yaw)
* Mat3::rotation(Vec3::new(1.0, 0.0, 0.0), pitch)
* Mat3::rotation(Vec3::new(0.0, 0.0, 1.0), roll);
rotations.push(r);
}
let truth = Cameras {
rotations,
focal: f,
};
// World directions: a fan across the whole sweep.
let mut obs = Vec::new();
let mut seed = 12345u64;
let mut rnd = || {
seed = seed
.wrapping_mul(6364136223846793005)
.wrapping_add(1442695040888963407);
((seed >> 33) as f64 / (1u64 << 31) as f64) - 0.5
};
let total = step * (n as f64 - 1.0);
for _ in 0..400 * n {
let yaw = rnd() * (total + 0.8) + total / 2.0;
let pitch = rnd() * 0.5;
let d = Vec3::new(
yaw.sin() * pitch.cos(),
pitch.sin(),
yaw.cos() * pitch.cos(),
)
.normalised();
// Visible in which frames? Within ±0.35 f of centre.
let mut seen: Vec<(usize, Point)> = Vec::new();
for k in 0..n {
if let Some(p) = truth.project(k, d) {
if p.0.abs() < 0.35 * f && p.1.abs() < 0.25 * f {
seen.push((k, (p.0 + rnd() * noise_px, p.1 + rnd() * noise_px)));
}
}
}
for a in 0..seen.len() {
for b in a + 1..seen.len() {
obs.push(Observation {
i: seen[a].0,
j: seen[b].0,
pi: seen[a].1,
pj: seen[b].1,
});
}
}
}
(truth, obs)
}
fn angle_between(a: Mat3, b: Mat3) -> f64 {
(a.transpose() * b).log().norm()
}
#[test]
fn a_perturbed_start_converges_back_to_the_truth() {
let (truth, obs) = sweep(6, 0.3, 1400.0, 0.0);
assert!(obs.len() > 500);
// Perturb every rotation but the first by ~1°, and the focal by 5%.
let mut start = truth.clone();
for k in 1..6 {
let w = Vec3::new(0.01, -0.015, 0.008) * (k as f64 / 3.0);
start.rotations[k] = Mat3::exp(w) * start.rotations[k];
}
start.focal *= 1.05;
let before = rms(&start, &obs);
let out = adjust(start, &obs, &AdjustOptions::default()).expect("solvable");
assert!(out.rms_px < 1e-3, "rms {} (was {before})", out.rms_px);
assert!(
(out.cameras.focal - 1400.0).abs() < 0.5,
"focal {}",
out.cameras.focal
);
for k in 0..6 {
let err = angle_between(out.cameras.rotations[k], truth.rotations[k]);
assert!(err < 1e-5, "frame {k} off by {err} rad");
}
}
#[test]
fn noise_is_averaged_rather_than_accumulated() {
let (truth, obs) = sweep(8, 0.25, 1400.0, 1.0);
let mut start = truth.clone();
for k in 1..8 {
start.rotations[k] =
Mat3::exp(Vec3::new(0.0, 0.004 * k as f64, 0.0)) * start.rotations[k];
}
let out = adjust(start, &obs, &AdjustOptions::default()).expect("solvable");
// ±0.5 px of uniform noise on every coordinate has an RMS of 0.41 px
// per axis, so the fit's RMS over both axes should sit near 0.58 and
// cannot be much below it.
assert!(out.rms_px < 0.7, "rms {}", out.rms_px);
// The focal length and the sweep are nearly degenerate for a
// single row: only the perspective inside each overlap pins the
// focal, and a pixel of noise is worth about a tenth of a percent of
// it. What that error does is scale every yaw by the same factor —
// a uniform stretch of the panorama, invisible in the result — so the
// absolute rotation error grows linearly along the sweep and is not
// the measure of the solve. The residual after removing that stretch
// is.
let f_ratio = out.cameras.focal / 1400.0;
assert!((f_ratio - 1.0).abs() < 5e-3, "focal {}", out.cameras.focal);
for k in 0..8 {
let yaw_k = 0.25 * k as f64;
let expected_stretch = (f_ratio - 1.0).abs() * yaw_k;
let err = angle_between(out.cameras.rotations[k], truth.rotations[k]);
assert!(
err < expected_stretch + 1.5e-4,
"frame {k} off by {err} rad, {expected_stretch} of it the focal's"
);
}
}
#[test]
fn a_frame_without_observations_is_refused() {
let (truth, mut obs) = sweep(4, 0.3, 1400.0, 0.0);
obs.retain(|o| o.i != 3 && o.j != 3);
let err = adjust(truth, &obs, &AdjustOptions::default()).unwrap_err();
assert!(matches!(err, PanoError::Geometry(_)));
}
}
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//! Keypoints with descriptors, and the decoder that reads them out of
//! XFeat's dense maps.
//!
//! The network (S15.2) produces three maps at an eighth of the input
//! resolution and stops; everything from there to a list of keypoints is
//! this file, in plain Rust, for the reason `dr-segment` decodes yolo26's
//! heads itself: the post-processing is cheap, shape-dependent and exactly
//! the kind of graph tract parses badly. It is a port of the reference
//! `XFeat.detectAndCompute`, step for step, so that a keypoint here is the
//! keypoint the paper's numbers were measured on.
/// One detected point, in the pixel coordinates of the image it was
/// detected in, with the detector's confidence.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct Keypoint {
pub x: f32,
pub y: f32,
/// The reliability the detector assigned; higher is better, and the
/// scale is the detector's own — comparable within one model only.
pub score: f32,
}
/// The keypoints of one image and their descriptors.
#[derive(Debug, Clone, PartialEq)]
pub struct Features {
pub keypoints: Vec<Keypoint>,
/// `keypoints.len() × DESCRIPTOR_LEN`, each row L2-normalised, so that a
/// dot product between two rows is their cosine similarity.
pub descriptors: Vec<f32>,
/// The image the coordinates are in.
pub width: usize,
pub height: usize,
}
/// The length of one descriptor. XFeat's is 64; the matcher does not care
/// what the number is, only that both sides agree.
pub const DESCRIPTOR_LEN: usize = 64;
impl Features {
pub fn len(&self) -> usize {
self.keypoints.len()
}
pub fn is_empty(&self) -> bool {
self.keypoints.is_empty()
}
pub fn descriptor(&self, i: usize) -> &[f32] {
&self.descriptors[i * DESCRIPTOR_LEN..(i + 1) * DESCRIPTOR_LEN]
}
}
/// XFeat's three output maps, as the network hands them back.
///
/// All three are `channels × height × width` at an eighth of the input, in
/// the NCHW order the ONNX export declares (`feats [1, 64, H/8, W/8]`,
/// `keypoints [1, 65, H/8, W/8]`, `heatmap [1, 1, H/8, W/8]`).
pub struct XFeatMaps<'a> {
/// 64 channels: the dense descriptor field.
pub feats: &'a [f32],
/// 65 channels: for each 8×8 cell, a logit per position plus one for
/// "no keypoint here".
pub keypoints: &'a [f32],
/// 1 channel: reliability.
pub heatmap: &'a [f32],
/// The maps' width and height (the input's, divided by eight).
pub width: usize,
pub height: usize,
}
/// How the decoder picks keypoints.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct DecodeOptions {
/// Keep at most this many, by score. The reference default is 4096.
pub top_k: usize,
/// A cell position's softmax probability must exceed this to be a
/// keypoint at all. The reference default is 0.05.
pub threshold: f32,
/// Ignore keypoints within this many pixels of the map's edge. A frame
/// padded into the detector's fixed input (`Gray::padded`) has a hard
/// edge where the padding starts, and the detector fires on it.
pub border: usize,
}
impl Default for DecodeOptions {
fn default() -> Self {
DecodeOptions {
top_k: 4096,
threshold: 0.05,
border: 4,
}
}
}
/// Decode keypoints and descriptors from the network's maps.
///
/// The reference, step for step:
/// 1. softmax over the 65 logits of each cell, keep the 64 positions;
/// 2. pixel-shuffle those into a full-resolution keypoint heatmap — channel
/// `c` of cell `(cx, cy)` is pixel `(cx·8 + c%8, cy·8 + c/8)`;
/// 3. 5×5 non-maximum suppression over that heatmap, above `threshold`;
/// 4. score each survivor by its heatmap value times the reliability map
/// sampled bilinearly at its position;
/// 5. keep the `top_k` by score;
/// 6. sample the descriptor field bilinearly at each and L2-normalise.
///
/// Bilinear where the reference samples the descriptor field bicubically:
/// a quarter-pixel's difference in a field that is smooth by construction,
/// and one interpolator rather than two to keep correct.
pub fn decode_xfeat(maps: &XFeatMaps<'_>, opts: &DecodeOptions) -> Features {
let (w8, h8) = (maps.width, maps.height);
let (w, h) = (w8 * 8, h8 * 8);
let cells = w8 * h8;
debug_assert_eq!(maps.keypoints.len(), 65 * cells);
debug_assert_eq!(maps.feats.len(), DESCRIPTOR_LEN * cells);
debug_assert_eq!(maps.heatmap.len(), cells);
// 1 + 2: softmax per cell, scattered into the full-resolution heatmap.
let mut heat = vec![0.0f32; w * h];
for cy in 0..h8 {
for cx in 0..w8 {
let cell = cy * w8 + cx;
let logit = |c: usize| maps.keypoints[c * cells + cell];
let max = (0..65).map(logit).fold(f32::MIN, f32::max);
let mut sum = 0.0f32;
let mut exps = [0.0f32; 65];
for (c, e) in exps.iter_mut().enumerate() {
*e = (logit(c) - max).exp();
sum += *e;
}
for (c, e) in exps.iter().enumerate().take(64) {
let (dx, dy) = (c % 8, c / 8);
heat[(cy * 8 + dy) * w + cx * 8 + dx] = e / sum;
}
}
}
// 3: a pixel survives if it is the maximum of its 5×5 neighbourhood and
// above threshold. Ties go to every tied pixel, as the reference's
// `x == max_pool(x)` does.
let border = opts.border.max(2);
let mut survivors: Vec<(usize, usize, f32)> = Vec::new();
for y in border..h.saturating_sub(border) {
for x in border..w.saturating_sub(border) {
let v = heat[y * w + x];
if v <= opts.threshold {
continue;
}
let mut is_max = true;
'nb: for ny in y - 2..=y + 2 {
for nx in x - 2..=x + 2 {
if heat[ny * w + nx] > v {
is_max = false;
break 'nb;
}
}
}
if is_max {
survivors.push((x, y, v));
}
}
}
// 4: heatmap value × reliability, the latter sampled at the keypoint's
// position in map coordinates (`align_corners = False`: pixel `x` of the
// full image is `x / 8 - 0.5` in the map).
let sample = |field: &[f32], channels: usize, c: usize, x: f32, y: f32| -> f32 {
let fx = (x / 8.0 - 0.5).clamp(0.0, (w8 - 1) as f32);
let fy = (y / 8.0 - 0.5).clamp(0.0, (h8 - 1) as f32);
let x0 = fx as usize;
let y0 = fy as usize;
let x1 = (x0 + 1).min(w8 - 1);
let y1 = (y0 + 1).min(h8 - 1);
let tx = fx - x0 as f32;
let ty = fy - y0 as f32;
let at = |xx: usize, yy: usize| field[c * (w8 * h8) + yy * w8 + xx];
let _ = channels;
let top = at(x0, y0) * (1.0 - tx) + at(x1, y0) * tx;
let bot = at(x0, y1) * (1.0 - tx) + at(x1, y1) * tx;
top * (1.0 - ty) + bot * ty
};
let mut scored: Vec<(usize, usize, f32)> = survivors
.into_iter()
.map(|(x, y, v)| {
let r = sample(maps.heatmap, 1, 0, x as f32, y as f32);
(x, y, v * r)
})
.collect();
// 5: best first, then cut. `sort_unstable_by` on a total order of the
// score; NaN cannot occur — every input is a probability or a sigmoid.
scored.sort_unstable_by(|a, b| b.2.total_cmp(&a.2));
scored.truncate(opts.top_k);
// 6: descriptors.
let mut keypoints = Vec::with_capacity(scored.len());
let mut descriptors = Vec::with_capacity(scored.len() * DESCRIPTOR_LEN);
for (x, y, score) in scored {
let (xf, yf) = (x as f32, y as f32);
let start = descriptors.len();
for c in 0..DESCRIPTOR_LEN {
descriptors.push(sample(maps.feats, DESCRIPTOR_LEN, c, xf, yf));
}
let norm = descriptors[start..]
.iter()
.map(|v| v * v)
.sum::<f32>()
.sqrt()
.max(1e-12);
for v in &mut descriptors[start..] {
*v /= norm;
}
keypoints.push(Keypoint {
x: xf,
y: yf,
score,
});
}
Features {
keypoints,
descriptors,
width: w,
height: h,
}
}
#[cfg(test)]
mod tests {
use super::*;
/// Maps for a `w8 × h8` grid where every cell says "no keypoint" except
/// the listed ones, which put all their weight on one position.
fn maps(w8: usize, h8: usize, hot: &[(usize, usize, usize)]) -> (Vec<f32>, Vec<f32>, Vec<f32>) {
let cells = w8 * h8;
let mut kp = vec![0.0f32; 65 * cells];
// "None" strongly preferred everywhere.
for cell in 0..cells {
kp[64 * cells + cell] = 10.0;
}
for &(cx, cy, c) in hot {
let cell = cy * w8 + cx;
kp[64 * cells + cell] = 0.0;
kp[c * cells + cell] = 10.0;
}
let heat = vec![0.5f32; cells];
// Descriptors: channel c is constant c across the field, so any
// sampled descriptor is the same known vector.
let mut feats = vec![0.0f32; DESCRIPTOR_LEN * cells];
for c in 0..DESCRIPTOR_LEN {
for v in &mut feats[c * cells..(c + 1) * cells] {
*v = c as f32;
}
}
(feats, kp, heat)
}
#[test]
fn a_hot_cell_position_becomes_a_keypoint_at_the_right_pixel() {
// Cell (2, 1), channel 8*3 + 5 = 29 → pixel (2*8 + 5, 1*8 + 3).
let (f, k, h) = maps(8, 8, &[(2, 1, 29)]);
let out = decode_xfeat(
&XFeatMaps {
feats: &f,
keypoints: &k,
heatmap: &h,
width: 8,
height: 8,
},
&DecodeOptions::default(),
);
assert_eq!(out.len(), 1);
assert_eq!((out.keypoints[0].x, out.keypoints[0].y), (21.0, 11.0));
assert_eq!((out.width, out.height), (64, 64));
// Score is the softmax weight (~1) times the reliability (0.5).
assert!((out.keypoints[0].score - 0.5).abs() < 5e-3);
}
#[test]
fn descriptors_are_unit_length() {
let (f, k, h) = maps(8, 8, &[(3, 3, 0), (5, 5, 63)]);
let out = decode_xfeat(
&XFeatMaps {
feats: &f,
keypoints: &k,
heatmap: &h,
width: 8,
height: 8,
},
&DecodeOptions::default(),
);
assert_eq!(out.len(), 2);
for i in 0..2 {
let n: f32 = out.descriptor(i).iter().map(|v| v * v).sum();
assert!((n - 1.0).abs() < 1e-5);
}
}
#[test]
fn top_k_keeps_the_best() {
let (f, k, mut h) = maps(8, 8, &[(1, 1, 0), (3, 3, 0), (5, 5, 0)]);
// Make cell (3, 3) the most reliable.
h[3 * 8 + 3] = 0.9;
let out = decode_xfeat(
&XFeatMaps {
feats: &f,
keypoints: &k,
heatmap: &h,
width: 8,
height: 8,
},
&DecodeOptions {
top_k: 1,
..Default::default()
},
);
assert_eq!(out.len(), 1);
assert_eq!((out.keypoints[0].x, out.keypoints[0].y), (24.0, 24.0));
}
#[test]
fn the_border_is_excluded() {
let (f, k, h) = maps(8, 8, &[(0, 0, 0)]);
let out = decode_xfeat(
&XFeatMaps {
feats: &f,
keypoints: &k,
heatmap: &h,
width: 8,
height: 8,
},
&DecodeOptions::default(),
);
assert!(out.is_empty());
}
}
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//! TRACES: FR-MRG-4
//! Filling a composite's uncovered border, tile by tile, with an inpainter.
//!
//! A merged panorama has a ragged border where no frame reached. FR-MRG-4
//! crops it by default; this fills it instead, when the photographer asks,
//! with pixels a model invents from the picture around them. Everything
//! here is the geometry of that — which tiles to run, what context to hand
//! the model, how to put its answers back — and none of it is the model:
//! that is the [`Inpainter`] trait, with MI-GAN behind it in `migan.rs`
//! and a fake in the tests.
//!
//! # Context across the edge
//!
//! An inpainting model is trained on holes *inside* pictures. A panorama's
//! border is a hole at the picture's *edge*: real content on one side,
//! nothing on the other, and a model given that invents a structure along
//! the open side — streaks of road in the sky, on the first try
//! (2026-09-19). So the known content is mirrored across the coverage
//! edge, column by column for the top and bottom bands and row by row for
//! the sides, into the hole and into a padding ring around the picture,
//! and the ring is presented as *known*. The model then interpolates
//! between real content and its mirror rather than extrapolating into
//! nothing. The ring is cut off at the end.
//!
//! # Structure from far away, texture from near
//!
//! One tiled pass at the working resolution was not enough: a 512-px tile
//! straddling the coverage edge sees a few hundred pixels of real content
//! on one side and invents the rest from that, two neighbouring tiles
//! invent differently, and the seams and the merge's own fringe leak into
//! the fill. [`fill_border`] therefore runs in two stages. A **coarse**
//! pass at a quarter of the size, where the whole border and hundreds of
//! pixels of real context sit inside a handful of tiles, decides the
//! structure — where the slope goes, where the sky stays sky. Then
//! **fine** passes regenerate the hole in bands from the real edge
//! outward: each band is the only unknown, with real content (or the band
//! before, freshly textured) on its near side and the coarse fill,
//! upsampled, on its far side — blurry, but the right structure — so the
//! model generates texture and a transition, never a large hole from
//! nothing.
//!
//! Tiles overlap by a third and are blended under a raised-cosine window,
//! so the seams between tiles do not show; the model's answer replaces
//! only the pixels that were unknown, and the picture itself is untouched.
use crate::PanoError;
/// A model that fills a square hole from its surroundings.
pub trait Inpainter {
/// The square tile it takes, in pixels.
fn tile(&self) -> usize;
/// Fill one tile. `rgb` is `tile × tile × 3`, row-major, 0..1, with the
/// unknown pixels' values meaningless; `known` is `tile × tile`. The
/// result is `tile × tile × 3`, 0..1, of which only the unknown pixels
/// are read.
fn fill(&mut self, rgb: &[f32], known: &[bool]) -> Result<Vec<f32>, PanoError>;
}
/// What a caller hears from [`fill_border`]: progress, for a page's bar,
/// and — for whoever is looking at why a fill went wrong — each stage's
/// picture as it lands. A plain `FnMut(usize, usize)` is an observer that
/// hears only the progress.
pub trait Observer {
/// `(done, total)` tiles, the total an estimate until the last band.
fn progress(&mut self, done: usize, total: usize);
/// A stage's result, `width × height × 3`: `coarse` (at the coarse
/// size), `band-N` after each fine band, `feathered` at the end.
fn stage(&mut self, _name: &str, _rgb: &[f32], _width: usize, _height: usize) {}
}
impl<F: FnMut(usize, usize)> Observer for F {
fn progress(&mut self, done: usize, total: usize) {
self(done, total)
}
}
/// How far the picture is extended with mirrored content before tiling.
/// Half a tile: enough that a hole at the edge sits well inside a tile.
pub const RING: usize = 256;
/// The fill's knobs, in pixels of the working image. The defaults are
/// what the fixture panorama looked best with on 2026-09-19; the merge
/// page exposes every one of them while the fill is experimental, so a
/// bad corner can be worked on from the picture rather than the code.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct Params {
/// The coarse pass's reduction: 1 skips it.
pub coarse: usize,
/// The fine passes' band width.
pub band: usize,
/// How deep into the picture the mirrored context reaches, or **zero
/// for no mirrored context at all**: the void is then shown to the
/// model as it is — reaching the picture's edge with nothing beyond,
/// and, beyond the band being filled, still unknown. That is what the
/// shipped model was trained on (a fine-tune of MI-GAN on voids cut
/// from photographs the way a cylindrical merge cuts them, see
/// `docs/panorama.md` §14); a ring would give it a fold to continue.
///
/// Non-zero is the stock model's crutch: a plain reflection of a deep
/// hole pulls in whatever is that far from the edge — a ridge, a peak —
/// and the model, told that is what lies beyond, paints it upside down.
/// Folding the reflection within this band keeps the ring looking like
/// the edge it continues and nothing further away.
pub mirror_depth: usize,
/// How far inside the real edge the fill also regenerates, the two
/// blended by distance. A hard cut between real pixels and invented
/// ones is a line whatever the fill's quality; blended over this many
/// pixels it is not. Zero is the hard cut.
pub feather: usize,
/// The step between tiles, at most the tile; two thirds of it usual.
pub stride: usize,
}
impl Default for Params {
fn default() -> Self {
Params {
coarse: 1,
band: 192,
mirror_depth: 0,
feather: 24,
stride: 384,
}
}
}
/// Fill the unknown pixels of `rgb` (`width × height × 3`, 0..1) in place:
/// the coarse pass, then the fine bands, then the seam feathered over
/// `feather` pixels inside the real edge. Returns the tiles run.
///
/// `known` is `width × height`. `observer` hears the progress and, if it
/// cares, each stage.
pub fn fill_border(
rgb: &mut [f32],
width: usize,
height: usize,
known: &[bool],
model: &mut dyn Inpainter,
params: Params,
observer: &mut dyn Observer,
) -> Result<usize, PanoError> {
let Params {
coarse: q,
band,
mirror_depth,
feather,
stride,
} = params;
let q = q.max(1);
let band = band.max(8);
// No ring: the void beyond the band stays unknown, as in the model's
// training; with a ring the far side is the coarse fill, presented as
// known, which the stock model needed to see something there.
let open = mirror_depth == 0;
if width == 0 || height == 0 || rgb.len() != width * height * 3 || known.len() != width * height
{
return Err(PanoError::Input("fill: buffer sizes disagree".into()));
}
if known.iter().all(|&k| k) {
return Ok(0);
}
// The fill regenerates a margin inside the real edge too, and the
// result is blended with the real pixels across it at the end.
let real = rgb.to_vec();
let outer = known.to_vec();
let mut inner = known.to_vec();
erode(&mut inner, width, height, feather);
let known = &inner[..];
let mut done = 0usize;
// Coarse: a fraction of the size, unknown where any pixel of the cell was.
let (cw, ch) = ((width / q).max(1), (height / q).max(1));
let mut coarse = vec![0.0f32; cw * ch * 3];
let mut cknown = vec![true; cw * ch];
for y in 0..ch {
for x in 0..cw {
let mut sum = [0.0f32; 3];
let mut n = 0.0f32;
let mut all_known = true;
for dy in 0..q {
for dx in 0..q {
let (sx, sy) = ((x * q + dx).min(width - 1), (y * q + dy).min(height - 1));
let i = sy * width + sx;
all_known &= known[i];
for c in 0..3 {
sum[c] += rgb[i * 3 + c];
}
n += 1.0;
}
}
for c in 0..3 {
coarse[(y * cw + x) * 3 + c] = sum[c] / n;
}
cknown[y * cw + x] = all_known;
}
}
let estimate = |tiles: usize| tiles * 4;
done += fill_once(
&mut coarse,
cw,
ch,
&cknown,
model,
stride,
mirror_depth,
|n, t| observer.progress(n, estimate(t)),
)?;
observer.stage("coarse", &coarse, cw, ch);
// The hole starts as the coarse structure, upsampled.
for y in 0..height {
for x in 0..width {
let i = y * width + x;
if known[i] {
continue;
}
let fx = ((x as f32 + 0.5) / q as f32 - 0.5).clamp(0.0, (cw - 1) as f32);
let fy = ((y as f32 + 0.5) / q as f32 - 0.5).clamp(0.0, (ch - 1) as f32);
let (x0, y0) = (fx as usize, fy as usize);
let (x1, y1) = ((x0 + 1).min(cw - 1), (y0 + 1).min(ch - 1));
let (tx, ty) = (fx - x0 as f32, fy - y0 as f32);
for c in 0..3 {
let at = |xx: usize, yy: usize| coarse[(yy * cw + xx) * 3 + c];
rgb[i * 3 + c] = (at(x0, y0) * (1.0 - tx) + at(x1, y0) * tx) * (1.0 - ty)
+ (at(x0, y1) * (1.0 - tx) + at(x1, y1) * tx) * ty;
}
}
}
// Fine, in bands from the edge outward.
let dist = distance_to_known(known, width, height);
let mut band_known = vec![true; width * height];
let mut b = 0usize;
loop {
let lo = (b * band).saturating_sub(band / 2) as f32;
let hi = ((b + 1) * band) as f32;
let mut any = false;
for i in 0..width * height {
let in_band = !known[i] && dist[i] > lo && dist[i] <= hi;
band_known[i] = if open {
known[i] || dist[i] <= lo
} else {
!in_band
};
any |= in_band;
}
if !any {
break;
}
let before = done;
done += fill_once(
rgb,
width,
height,
&band_known,
model,
stride,
mirror_depth,
|n, t| observer.progress(before + n, before + estimate(t)),
)?;
observer.stage(&format!("band-{b}"), rgb, width, height);
b += 1;
}
// The seam: across the margin, real on the inside, invented on the
// outside, a smooth ramp between by distance from the true hole.
if feather > 0 {
let to_hole =
distance_to_known(&outer.iter().map(|k| !k).collect::<Vec<_>>(), width, height);
for i in 0..width * height {
if !outer[i] || known[i] {
continue;
}
// In the margin: outer says known, inner says not.
let t = (to_hole[i] / feather as f32).clamp(0.0, 1.0);
let t = t * t * (3.0 - 2.0 * t);
for c in 0..3 {
rgb[i * 3 + c] = rgb[i * 3 + c] * (1.0 - t) + real[i * 3 + c] * t;
}
}
}
observer.stage("feathered", rgb, width, height);
observer.progress(done, done);
Ok(done)
}
/// One tiled pass: every unknown pixel regenerated from the tiles that
/// touch it, the rest kept. Returns the tiles run.
#[allow(clippy::too_many_arguments)]
fn fill_once(
rgb: &mut [f32],
width: usize,
height: usize,
known: &[bool],
model: &mut dyn Inpainter,
stride: usize,
mirror_depth: usize,
mut progress: impl FnMut(usize, usize),
) -> Result<usize, PanoError> {
let t = model.tile();
if t == 0 || known.iter().all(|&k| k) {
return Ok(0);
}
// The padded canvas with mirrored context, and the hole within it.
let ctx = MirroredContext::build(rgb, width, height, known, mirror_depth);
let (pw, ph) = (ctx.width, ctx.height);
// Tiles that touch the hole, on a grid that reaches both far edges.
let starts = |n: usize| -> Vec<usize> {
if n <= t {
return vec![0];
}
let mut v: Vec<usize> = (0..=n - t).step_by(stride.clamp(1, t)).collect();
if *v.last().unwrap_or(&0) != n - t {
v.push(n - t);
}
v
};
let ys = starts(ph);
let xs = starts(pw);
let mut tiles = Vec::new();
for &y in &ys {
for &x in &xs {
if y + t > ph || x + t > pw {
continue;
}
let touches =
(y..y + t).any(|yy| ctx.hole[yy * pw + x..yy * pw + x + t].iter().any(|&h| h));
if touches {
tiles.push((x, y));
}
}
}
// Raised-cosine window, so overlapping tiles blend.
let hann: Vec<f32> = (0..t)
.map(|i| {
let s = ((i as f32 + 1.0) / (t as f32 + 1.0) * std::f32::consts::PI).sin();
s * s + 1e-3
})
.collect();
let mut acc = vec![0.0f32; pw * ph * 3];
let mut wsum = vec![0.0f32; pw * ph];
let mut tile_rgb = vec![0.0f32; t * t * 3];
let mut tile_known = vec![false; t * t];
let total = tiles.len();
for (n, &(x, y)) in tiles.iter().enumerate() {
progress(n, total);
for r in 0..t {
let src = ((y + r) * pw + x) * 3;
tile_rgb[r * t * 3..(r + 1) * t * 3].copy_from_slice(&ctx.rgb[src..src + t * 3]);
let ks = (y + r) * pw + x;
for c in 0..t {
tile_known[r * t + c] = !ctx.hole[ks + c];
}
}
let out = model.fill(&tile_rgb, &tile_known)?;
if out.len() != t * t * 3 {
return Err(PanoError::Model(format!(
"the inpainter returned {} values for a {t}×{t} tile",
out.len()
)));
}
for r in 0..t {
for c in 0..t {
let w = hann[r] * hann[c];
let p = (y + r) * pw + (x + c);
for ch in 0..3 {
acc[p * 3 + ch] += out[(r * t + c) * 3 + ch] * w;
}
wsum[p] += w;
}
}
}
progress(total, total);
// Back into the picture: only the unknown pixels change.
for yy in 0..height {
for xx in 0..width {
let i = yy * width + xx;
if known[i] {
continue;
}
let p = (yy + ctx.ring) * pw + (xx + ctx.ring);
if wsum[p] > 0.0 {
for ch in 0..3 {
rgb[i * 3 + ch] = (acc[p * 3 + ch] / wsum[p]).clamp(0.0, 1.0);
}
}
}
}
Ok(total)
}
/// Shrink `known` by `iterations` pixels on every side, in place.
///
/// The merge's coverage edge carries a fringe — the last partly-covered
/// pixels of a frame, and whatever the renderer did at the boundary — and
/// a fill that stops exactly at the coverage bit leaves it as a dark line
/// along the seam. Eight pixels at a quarter of the composite's resolution
/// was what it took on the fixture.
pub fn erode(known: &mut [bool], width: usize, height: usize, iterations: usize) {
let mut next = known.to_vec();
for _ in 0..iterations {
for y in 0..height {
for x in 0..width {
let i = y * width + x;
if !known[i] {
continue;
}
let edge = x == 0
|| y == 0
|| x + 1 == width
|| y + 1 == height
|| !known[i - 1]
|| !known[i + 1]
|| !known[i - width]
|| !known[i + width];
next[i] = !edge;
}
}
known.copy_from_slice(&next);
}
}
/// Distance from each pixel to the nearest known one, by two chamfer
/// sweeps — within a few percent of Euclidean, and enough to cut bands.
fn distance_to_known(known: &[bool], width: usize, height: usize) -> Vec<f32> {
let inf = (width + height) as f32;
let mut d: Vec<f32> = known.iter().map(|&k| if k { 0.0 } else { inf }).collect();
let (a, b) = (1.0f32, std::f32::consts::SQRT_2);
for y in 0..height {
for x in 0..width {
let i = y * width + x;
let mut v = d[i];
if x > 0 {
v = v.min(d[i - 1] + a);
}
if y > 0 {
v = v.min(d[i - width] + a);
if x > 0 {
v = v.min(d[i - width - 1] + b);
}
if x + 1 < width {
v = v.min(d[i - width + 1] + b);
}
}
d[i] = v;
}
}
for y in (0..height).rev() {
for x in (0..width).rev() {
let i = y * width + x;
let mut v = d[i];
if x + 1 < width {
v = v.min(d[i + 1] + a);
}
if y + 1 < height {
v = v.min(d[i + width] + a);
if x + 1 < width {
v = v.min(d[i + width + 1] + b);
}
if x > 0 {
v = v.min(d[i + width - 1] + b);
}
}
d[i] = v;
}
}
d
}
/// Distance beyond the edge to distance inside it, folded within `depth`
/// ([`Params::mirror_depth`]): a triangle wave, so the band is read
/// forward and back rather than clamped to one row.
fn fold(d: usize, depth: usize) -> usize {
let period = 2 * depth;
let r = d % period;
if r <= depth {
r
} else {
period - r
}
}
/// The picture on a canvas `RING` wider on every side, with the hole and
/// the ring filled by mirroring the known content across the coverage
/// edge — the nearest `depth` of it, folded — and the hole, the
/// original unknown and nothing else, marked.
struct MirroredContext {
width: usize,
height: usize,
/// The padding on every side: `RING` with mirrored context, 0 without.
ring: usize,
rgb: Vec<f32>,
hole: Vec<bool>,
}
impl MirroredContext {
fn build(rgb: &[f32], width: usize, height: usize, known: &[bool], depth: usize) -> Self {
if depth == 0 {
// Open: the picture as it is, the hole as it is. What the hole
// holds does not matter — the model masks it out.
return MirroredContext {
width,
height,
ring: 0,
rgb: rgb.to_vec(),
hole: known.iter().map(|&k| !k).collect(),
};
}
let fold = |d: usize| fold(d, depth);
let (pw, ph) = (width + 2 * RING, height + 2 * RING);
let mut canvas = vec![0.0f32; pw * ph * 3];
let mut kn = vec![false; pw * ph];
let mut hole = vec![false; pw * ph];
for y in 0..height {
for x in 0..width {
let i = y * width + x;
let p = (y + RING) * pw + (x + RING);
canvas[p * 3..p * 3 + 3].copy_from_slice(&rgb[i * 3..i * 3 + 3]);
kn[p] = known[i];
hole[p] = !known[i];
}
}
// Per column: mirror across the first and last known row.
for x in 0..pw {
let first = (0..ph).find(|&y| kn[y * pw + x]);
let Some(first) = first else { continue };
let last = (0..ph).rev().find(|&y| kn[y * pw + x]).unwrap_or(first);
for y in 0..first {
let m = (first + fold(first - y)).min(last);
let (d, s) = ((y * pw + x) * 3, (m * pw + x) * 3);
canvas.copy_within(s..s + 3, d);
}
for y in last + 1..ph {
let m = last.saturating_sub(fold(y - last)).max(first);
let (d, s) = ((y * pw + x) * 3, (m * pw + x) * 3);
canvas.copy_within(s..s + 3, d);
}
}
// Per row, for the sides, over what is there now.
for y in 0..ph {
let first = (0..pw).find(|&x| kn[y * pw + x]);
let Some(first) = first else { continue };
let last = (0..pw).rev().find(|&x| kn[y * pw + x]).unwrap_or(first);
for x in 0..first {
let m = (first + fold(first - x)).min(last);
let (d, s) = ((y * pw + x) * 3, (y * pw + m) * 3);
canvas.copy_within(s..s + 3, d);
}
for x in last + 1..pw {
let m = last.saturating_sub(fold(x - last)).max(first);
let (d, s) = ((y * pw + x) * 3, (y * pw + m) * 3);
canvas.copy_within(s..s + 3, d);
}
}
MirroredContext {
width: pw,
height: ph,
ring: RING,
rgb: canvas,
hole,
}
}
}
#[cfg(test)]
mod tests {
use super::*;
/// The tests' small pictures: a 48-px stride, a given feather.
fn test_params(feather: usize) -> Params {
Params {
stride: 48,
feather,
..Params::default()
}
}
/// Paints every unknown pixel a fixed grey and copies the known ones,
/// and remembers what it was shown.
struct Flat {
tile: usize,
seen: Vec<(Vec<f32>, Vec<bool>)>,
}
impl Inpainter for Flat {
fn tile(&self) -> usize {
self.tile
}
fn fill(&mut self, rgb: &[f32], known: &[bool]) -> Result<Vec<f32>, PanoError> {
self.seen.push((rgb.to_vec(), known.to_vec()));
Ok(rgb
.chunks_exact(3)
.zip(known)
.flat_map(|(p, &k)| if k { [p[0], p[1], p[2]] } else { [0.5; 3] })
.collect())
}
}
fn picture(w: usize, h: usize, border: usize) -> (Vec<f32>, Vec<bool>) {
let mut rgb = vec![0.0; w * h * 3];
let mut known = vec![false; w * h];
for y in 0..h {
for x in 0..w {
let i = y * w + x;
if y >= border && y < h - border {
known[i] = true;
rgb[i * 3] = x as f32 / w as f32;
rgb[i * 3 + 1] = y as f32 / h as f32;
rgb[i * 3 + 2] = 0.25;
}
}
}
(rgb, known)
}
#[test]
fn unknown_pixels_take_the_model_and_known_ones_do_not_move() {
let (mut rgb, known) = picture(300, 200, 20);
let before = rgb.clone();
let mut model = Flat {
tile: 64,
seen: Vec::new(),
};
let tiles = fill_border(
&mut rgb,
300,
200,
&known,
&mut model,
test_params(0),
&mut |_, _| {},
)
.unwrap();
assert!(tiles > 0);
for i in 0..300 * 200 {
if known[i] {
assert_eq!(&rgb[i * 3..i * 3 + 3], &before[i * 3..i * 3 + 3]);
} else {
for c in 0..3 {
assert!((rgb[i * 3 + c] - 0.5).abs() < 1e-4, "pixel {i}");
}
}
}
}
#[test]
fn the_model_is_shown_mirrored_context_not_black() {
let (mut rgb, known) = picture(300, 200, 20);
let mut model = Flat {
tile: 64,
seen: Vec::new(),
};
fill_border(
&mut rgb,
300,
200,
&known,
&mut model,
Params {
mirror_depth: 48,
..test_params(0)
},
&mut |_, _| {},
)
.unwrap();
for (tile_rgb, tile_known) in &model.seen {
let known_non_black = tile_rgb
.chunks_exact(3)
.zip(tile_known)
.filter(|(_, &k)| k)
.any(|(p, _)| p.iter().any(|v| *v > 0.0));
assert!(known_non_black);
}
}
#[test]
fn an_open_void_reaches_the_tile_edge_and_stays_unknown_beyond_the_band() {
// A 150-tall hole above and below; bands of 96. With no ring the
// first band's tiles sit at the picture's edge, so a tile's top
// row is unknown, and the rows deeper than the band are unknown
// too — not "known" coarse fill — exactly as the model was trained.
let (mut rgb, known) = picture(200, 500, 150);
let mut model = Flat {
tile: 64,
seen: Vec::new(),
};
fill_border(
&mut rgb,
200,
500,
&known,
&mut model,
Params {
band: 96,
..test_params(0)
},
&mut |_, _| {},
)
.unwrap();
// The first pass's tile at the picture's top edge is unknown
// through and through: the hole is 150 deep, the tile 64, and
// nothing beyond the band was presented as known. With a ring, or
// with the far side shown as coarse fill, no tile is ever all hole.
assert!(model.seen.iter().any(|(_, k)| k.iter().all(|&v| !v)));
for i in 0..200 * 500 {
if !known[i] {
assert!((rgb[i * 3] - 0.5).abs() < 1e-4, "pixel {i}");
}
}
}
#[test]
fn the_fine_passes_run_in_bands_after_the_coarse_one() {
// A 150-tall hole above and below a picture: the coarse pass sees
// it at a quarter; the fine passes need two bands of BAND pixels.
let (mut rgb, known) = picture(200, 500, 150);
let mut model = Flat {
tile: 64,
seen: Vec::new(),
};
fill_border(
&mut rgb,
200,
500,
&known,
&mut model,
Params {
coarse: 4,
band: 96,
mirror_depth: 48,
..test_params(0)
},
&mut |_, _| {},
)
.unwrap();
assert!(model.seen.len() > 4);
// Every unknown pixel was reached.
for i in 0..200 * 500 {
if !known[i] {
assert!((rgb[i * 3] - 0.5).abs() < 1e-4, "pixel {i}");
}
}
}
#[test]
fn the_seam_ramps_from_real_to_invented_across_the_feather() {
let (mut rgb, known) = picture(300, 200, 20);
let before = rgb.clone();
let mut model = Flat {
tile: 64,
seen: Vec::new(),
};
fill_border(
&mut rgb,
300,
200,
&known,
&mut model,
test_params(8),
&mut |_, _| {},
)
.unwrap();
// Row 20 is the real edge; the margin runs to row 27. At the edge
// the value is the model's grey, eight rows in it is the picture's.
let at = |y: usize| rgb[(y * 300 + 150) * 3 + 2];
assert!((at(20) - 0.5).abs() < 0.05, "{}", at(20));
assert!((at(29) - before[(29 * 300 + 150) * 3 + 2]).abs() < 1e-4);
let (lo, hi) = (at(20).min(at(29)), at(20).max(at(29)));
assert!(
at(23) > lo + 0.02 && at(23) < hi - 0.02,
"{} between {lo} and {hi}",
at(23)
);
// The hole itself is the model's.
assert!((at(5) - 0.5).abs() < 1e-4);
}
#[test]
fn erosion_shrinks_the_known_region_from_every_edge() {
let (_, mut known) = picture(20, 20, 4);
erode(&mut known, 20, 20, 2);
assert!(known[8 * 20 + 10]);
assert!(!known[5 * 20 + 10]);
assert!(!known[8 * 20 + 1]);
}
#[test]
fn distance_counts_pixels_from_the_known_region() {
let (_, known) = picture(20, 20, 4);
let d = distance_to_known(&known, 20, 20);
assert_eq!(d[4 * 20 + 10], 0.0);
assert!((d[3 * 20 + 10] - 1.0).abs() < 1e-6);
assert!((d[10] - 4.0).abs() < 1e-6);
}
#[test]
fn a_fully_covered_picture_runs_nothing() {
let (mut rgb, known) = picture(100, 100, 0);
let mut model = Flat {
tile: 64,
seen: Vec::new(),
};
assert_eq!(
fill_border(
&mut rgb,
100,
100,
&known,
&mut model,
test_params(0),
&mut |_, _| {}
)
.unwrap(),
0
);
}
#[test]
fn the_context_mirrors_the_top_rows_upward() {
let (rgb, known) = picture(40, 30, 5);
let ctx = MirroredContext::build(&rgb, 40, 30, &known, 48);
let x = RING + 10;
let first = RING + 5;
for k in 1..=4 {
let above = ((first - k) * ctx.width + x) * 3;
let mirror = ((first + k) * ctx.width + x) * 3;
assert_eq!(&ctx.rgb[above..above + 3], &ctx.rgb[mirror..mirror + 3]);
}
assert!(ctx.hole[(RING + 2) * ctx.width + x]);
assert!(!ctx.hole[(RING - 2) * ctx.width + x]);
}
#[test]
fn the_mirror_reaches_no_deeper_than_its_band() {
// A ridge 200 rows in must not appear in the ring: beyond the band
// the reflection folds back towards the edge rather than on into
// the picture.
let (mut rgb, known) = picture(40, 400, 5);
let ridge = 5 + 200;
for x in 0..40 {
rgb[(ridge * 40 + x) * 3..(ridge * 40 + x) * 3 + 3].copy_from_slice(&[0.9, 0.1, 0.1]);
}
let ctx = MirroredContext::build(&rgb, 40, 400, &known, 48);
let x = RING + 10;
for y in 0..RING + 5 {
let p = (y * ctx.width + x) * 3;
assert!(
ctx.rgb[p] < 0.5,
"row {y} of the ring shows the ridge ({:?})",
&ctx.rgb[p..p + 3]
);
}
assert_eq!(fold(0, 48), 0);
assert_eq!(fold(48, 48), 48);
assert_eq!(fold(58, 48), 38);
assert_eq!(fold(96, 48), 0);
assert_eq!(fold(99, 48), 3);
}
}
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//! Pairwise geometry: a homography between two frames, found robustly.
//!
//! Two frames of a panorama are related by a rotation, and a rotation seen
//! through one lens is a homography of the image plane — `H = K R Kᵀ⁻¹`. The
//! homography is estimated first, from matches, because it does not need
//! the focal length; the focal length is then *read off* it (§ below), and
//! the rotation follows from both. This is the order Brown & Lowe (2007)
//! and OpenCV's stitcher use, and it is what makes the pipeline work when
//! EXIF says nothing about the lens.
//!
//! Coordinates throughout are **centred**: the principal point is the
//! origin. The focal formulae assume it, and centring before the DLT also
//! conditions the linear system — Hartley's normalisation, done once by the
//! caller rather than inside every solve.
use crate::linalg::{DMat, Mat3, Vec3};
/// A point in one image, centred on the principal point.
pub type Point = (f64, f64);
/// Apply a homography to a point.
pub fn apply(h: &Mat3, p: Point) -> Option<Point> {
let v = *h * Vec3::new(p.0, p.1, 1.0);
if v.z().abs() < 1e-12 {
return None;
}
Some((v.x() / v.z(), v.y() / v.z()))
}
/// Least-squares homography from at least four correspondences by the
/// direct linear transform, with `h33` fixed at 1.
///
/// Fixing `h33` turns the homogeneous 8×9 system into an ordinary 8-unknown
/// least-squares problem that the normal equations and a Cholesky
/// factorisation solve without an SVD. The one homography it cannot
/// represent — `h33 = 0`, a point at the origin mapped to infinity — does
/// not occur between overlapping frames of one scene.
///
/// The points should be scaled to order one (divide by the focal length or
/// the image size) before calling: the normal equations square the
/// conditioning, and pixel coordinates in the thousands make them singular
/// in `f64`.
pub fn dlt(pairs: &[(Point, Point)]) -> Option<Mat3> {
if pairs.len() < 4 {
return None;
}
// Each pair gives two rows of A h = b with h = (h11..h32).
// x' = (h11 x + h12 y + h13) / (h31 x + h32 y + 1)
// → h11 x + h12 y + h13 - h31 x x' - h32 y x' = x'
let mut ata = DMat::zeros(8);
let mut atb = [0.0f64; 8];
for &((x, y), (xp, yp)) in pairs {
let rows: [([f64; 8], f64); 2] = [
([x, y, 1.0, 0.0, 0.0, 0.0, -x * xp, -y * xp], xp),
([0.0, 0.0, 0.0, x, y, 1.0, -x * yp, -y * yp], yp),
];
for (a, b) in rows {
for i in 0..8 {
atb[i] += a[i] * b;
for j in 0..8 {
ata[(i, j)] += a[i] * a[j];
}
}
}
}
let h = ata.solve_spd(&atb)?;
Some(Mat3([
[h[0], h[1], h[2]],
[h[3], h[4], h[5]],
[h[6], h[7], 1.0],
]))
}
/// A homography with the correspondences that agree with it.
#[derive(Debug, Clone, PartialEq)]
pub struct RobustHomography {
pub h: Mat3,
/// Indices into the input pairs.
pub inliers: Vec<usize>,
}
/// RANSAC over [`dlt`] on four-point samples, then a final least-squares
/// fit over every inlier.
///
/// `threshold` is the reprojection distance, in the same units as the
/// points, within which a pair counts as agreeing. The iteration count
/// adapts to the inlier ratio found so far in the usual way, capped at
/// `max_iterations`. `seed` makes a run reproducible (NFR-MRG-2): the
/// sampling is a small linear congruential generator, not the system's.
pub fn ransac_homography(
pairs: &[(Point, Point)],
threshold: f64,
max_iterations: usize,
seed: u64,
) -> Option<RobustHomography> {
if pairs.len() < 4 {
return None;
}
let n = pairs.len();
let thr2 = threshold * threshold;
let mut rng = Lcg(seed);
let mut best: Option<(Vec<usize>, Mat3)> = None;
let mut iterations = max_iterations;
let mut i = 0;
while i < iterations {
i += 1;
let sample = rng.distinct4(n);
let Some(h) = dlt(&sample.map(|k| pairs[k])) else {
continue;
};
let inliers: Vec<usize> = (0..n).filter(|&k| agrees(&h, pairs[k], thr2)).collect();
if best.as_ref().is_none_or(|(b, _)| inliers.len() > b.len()) {
// Adapt: enough iterations to have drawn one all-inlier sample
// with probability 0.99, given the ratio seen so far.
let w = inliers.len() as f64 / n as f64;
let p_all = w.powi(4);
if p_all > 0.0 && p_all < 1.0 {
let needed = ((1.0 - 0.99f64).ln() / (1.0 - p_all).ln()).ceil() as usize;
iterations = iterations.min(needed.max(i + 1));
}
best = Some((inliers, h));
}
}
let (inliers, h) = best?;
if inliers.len() < 4 {
return None;
}
// Refit on every inlier, and keep the refit only if it did not lose
// support — a least-squares fit over a set with a few borderline points
// can be pulled off the consensus the sample found.
let refit: Vec<(Point, Point)> = inliers.iter().map(|&k| pairs[k]).collect();
let h = match dlt(&refit) {
Some(r) => {
let count = (0..n).filter(|&k| agrees(&r, pairs[k], thr2)).count();
if count >= inliers.len() {
r
} else {
h
}
}
None => h,
};
let inliers: Vec<usize> = (0..n).filter(|&k| agrees(&h, pairs[k], thr2)).collect();
Some(RobustHomography { h, inliers })
}
fn agrees(h: &Mat3, (p, q): (Point, Point), thr2: f64) -> bool {
match apply(h, p) {
Some((x, y)) => {
let (dx, dy) = (x - q.0, y - q.1);
dx * dx + dy * dy <= thr2
}
None => false,
}
}
/// The focal length a homography implies, if it implies one.
///
/// For `H = K R K⁻¹` with `K = diag(f, f, 1)` and the principal point at the
/// origin, the orthonormality of `R` gives two independent estimates of `f²`
/// from the first two rows and two from the first two columns; each is
/// taken where it is positive and the better-conditioned of the pair is
/// chosen, as OpenCV's `focalsFromHomography` does. The geometric mean of
/// the row and column estimates is returned. `None` when the homography is
/// too close to a pure translation to say anything — every estimate is then
/// a ratio of small numbers.
pub fn focal_from_homography(h: &Mat3) -> Option<f64> {
let m = h.0;
let (h00, h01, h02) = (m[0][0], m[0][1], m[0][2]);
let (h10, h11, h12) = (m[1][0], m[1][1], m[1][2]);
let (h20, h21) = (m[2][0], m[2][1]);
let pick = |mut v1: f64, mut v2: f64, d1: f64, d2: f64| -> Option<f64> {
if v1 < v2 {
std::mem::swap(&mut v1, &mut v2);
}
if v1 > 0.0 && v2 > 0.0 {
Some((if d1.abs() > d2.abs() { v1 } else { v2 }).sqrt())
} else if v1 > 0.0 {
Some(v1.sqrt())
} else {
None
}
};
// From the third row.
let d1 = h20 * h21;
let d2 = (h21 - h20) * (h21 + h20);
let f1 = if d1.abs() > 1e-12 || d2.abs() > 1e-12 {
let v1 = if d1.abs() > 1e-12 {
-(h00 * h01 + h10 * h11) / d1
} else {
f64::NAN
};
let v2 = if d2.abs() > 1e-12 {
(h00 * h00 + h10 * h10 - h01 * h01 - h11 * h11) / d2
} else {
f64::NAN
};
pick(nan_to_neg(v1), nan_to_neg(v2), d1, d2)
} else {
None
};
// From the third column.
let d1 = h00 * h10 + h01 * h11;
let d2 = h00 * h00 + h01 * h01 - h10 * h10 - h11 * h11;
let f0 = if d1.abs() > 1e-12 || d2.abs() > 1e-12 {
let v1 = if d1.abs() > 1e-12 {
-h02 * h12 / d1
} else {
f64::NAN
};
let v2 = if d2.abs() > 1e-12 {
(h12 * h12 - h02 * h02) / d2
} else {
f64::NAN
};
pick(nan_to_neg(v1), nan_to_neg(v2), d1, d2)
} else {
None
};
match (f0, f1) {
(Some(a), Some(b)) => Some((a * b).sqrt()),
(Some(a), None) | (None, Some(a)) => Some(a),
(None, None) => None,
}
}
fn nan_to_neg(v: f64) -> f64 {
if v.is_finite() {
v
} else {
-1.0
}
}
/// The rotation a homography encodes for a known focal length:
/// `R = K⁻¹ H K`, re-orthonormalised, with the scale of `H` divided out.
pub fn rotation_from_homography(h: &Mat3, f: f64) -> Mat3 {
let m = h.0;
// K⁻¹ H K with K = diag(f, f, 1): scale the third row by f and the
// third column by 1/f.
let r = Mat3([
[m[0][0], m[0][1], m[0][2] / f],
[m[1][0], m[1][1], m[1][2] / f],
[m[2][0] * f, m[2][1] * f, m[2][2]],
]);
r.orthonormalised()
}
/// A small deterministic generator for RANSAC's samples.
struct Lcg(u64);
impl Lcg {
fn next(&mut self) -> u64 {
// Knuth's MMIX constants.
self.0 = self
.0
.wrapping_mul(6364136223846793005)
.wrapping_add(1442695040888963407);
self.0 >> 33
}
fn below(&mut self, n: usize) -> usize {
(self.next() % n as u64) as usize
}
fn distinct4(&mut self, n: usize) -> [usize; 4] {
let mut s = [0usize; 4];
for i in 0..4 {
loop {
let k = self.below(n);
if !s[..i].contains(&k) {
s[i] = k;
break;
}
}
}
s
}
}
#[cfg(test)]
mod tests {
use super::*;
/// Points under a known rotation seen through a known focal length,
/// in centred image coordinates scaled by that focal length.
fn synthetic(f: f64, r: Mat3, n: usize, noise: f64, seed: u64) -> Vec<(Point, Point)> {
let mut rng = Lcg(seed);
let mut out = Vec::new();
while out.len() < n {
// A point on the first image plane, within ±0.3 f of centre.
let x = (rng.below(6001) as f64 - 3000.0) / 10000.0;
let y = (rng.below(4001) as f64 - 2000.0) / 10000.0;
let b = Vec3::new(x, y, 1.0);
let v = r * b;
if v.z() <= 0.2 {
continue;
}
let nx = (rng.below(2001) as f64 - 1000.0) / 1000.0 * noise;
let ny = (rng.below(2001) as f64 - 1000.0) / 1000.0 * noise;
out.push(((x, y), (v.x() / v.z() + nx, v.y() / v.z() + ny)));
}
let _ = f;
out
}
#[test]
fn dlt_recovers_a_known_homography_exactly() {
let r = Mat3::exp(Vec3::new(0.05, 0.3, 0.02));
let pairs = synthetic(1.0, r, 12, 0.0, 1);
let h = dlt(&pairs).expect("solvable");
for &(p, q) in &pairs {
let (x, y) = apply(&h, p).unwrap();
assert!((x - q.0).abs() < 1e-9 && (y - q.1).abs() < 1e-9);
}
}
#[test]
fn ransac_finds_the_consensus_among_outliers() {
let r = Mat3::exp(Vec3::new(-0.02, 0.25, 0.01));
let mut pairs = synthetic(1.0, r, 60, 0.0005, 2);
// Forty outliers: wrong second point.
let mut rng = Lcg(9);
for _ in 0..40 {
let k = rng.below(60);
let (p, _) = pairs[k];
pairs.push((p, ((rng.below(1000) as f64 - 500.0) / 1000.0, 0.1)));
}
let robust = ransac_homography(&pairs, 0.003, 500, 3).expect("found");
assert!(
robust.inliers.len() >= 55,
"{} inliers",
robust.inliers.len()
);
assert!(robust.inliers.iter().all(|&k| k < 60));
}
#[test]
fn focal_is_read_off_a_rotation_homography() {
// H in *pixel* coordinates for f = 1400: K R K⁻¹.
let f = 1400.0;
let r = Mat3::exp(Vec3::new(0.03, 0.35, -0.01));
let m = r.0;
let h = Mat3([
[m[0][0], m[0][1], m[0][2] * f],
[m[1][0], m[1][1], m[1][2] * f],
[m[2][0] / f, m[2][1] / f, m[2][2]],
]);
let est = focal_from_homography(&h).expect("estimable");
assert!((est - f).abs() / f < 1e-6, "{est}");
let back = rotation_from_homography(&h, f);
for (row, truth) in back.0.iter().zip(&m) {
for (a, b) in row.iter().zip(truth) {
assert!((a - b).abs() < 1e-9);
}
}
}
#[test]
fn the_identity_implies_no_focal() {
assert!(focal_from_homography(&Mat3::IDENTITY).is_none());
}
}
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//! The grayscale proxy a detector reads.
//!
//! Alignment runs on proxies (FR-MRG-7) — a detector at 1024 px sees
//! everything it needs, and the full-resolution frames never leave the GPU.
//! This is that proxy: one channel, `f32` in `0.0..=1.0`, upright, and no
//! larger than the detector's fixed input.
/// A single-channel image, row-major, values in `0.0..=1.0`.
#[derive(Debug, Clone, PartialEq)]
pub struct Gray {
pub width: usize,
pub height: usize,
pub data: Vec<f32>,
}
impl Gray {
/// From tightly packed 8-bit RGBA, by the Rec. 709 luma weights.
///
/// The proxy is what a detector looks at, not what the photographer
/// sees, so which luma is used matters less than that it is the same one
/// for every frame — a keypoint's descriptor must not change between two
/// frames because they were converted differently.
pub fn from_rgba8(rgba: &[u8], width: usize, height: usize) -> Gray {
let n = width * height;
assert!(
rgba.len() >= n * 4,
"rgba buffer is short for {width}×{height}"
);
let data = rgba[..n * 4]
.chunks_exact(4)
.map(|p| {
(0.2126 * f32::from(p[0]) + 0.7152 * f32::from(p[1]) + 0.0722 * f32::from(p[2]))
/ 255.0
})
.collect();
Gray {
width,
height,
data,
}
}
/// Apply an EXIF orientation so the image is upright.
///
/// Learned detectors are not rotation-invariant — a descriptor of a
/// feature seen sideways is a different descriptor — and a portrait set
/// (the 6D fixture is one) would match poorly or not at all fed as
/// stored. The camera says which way is up; the proxy is turned before
/// anything looks at it, and the composite is written upright.
///
/// The value is the EXIF `Orientation` tag. Mirrored values (2, 4, 5, 7)
/// are not produced by any camera and are treated as their unmirrored
/// counterparts.
pub fn oriented(&self, orientation: u16) -> Gray {
match orientation {
3 | 4 => self.rotated_180(),
6 | 5 => self.rotated_90_cw(),
8 | 7 => self.rotated_90_ccw(),
_ => self.clone(),
}
}
fn rotated_90_cw(&self) -> Gray {
let (w, h) = (self.width, self.height);
let mut data = vec![0.0; w * h];
for y in 0..h {
for x in 0..w {
// Source (x, y) lands at (h - 1 - y, x) in an h-wide image.
data[x * h + (h - 1 - y)] = self.data[y * w + x];
}
}
Gray {
width: h,
height: w,
data,
}
}
fn rotated_90_ccw(&self) -> Gray {
let (w, h) = (self.width, self.height);
let mut data = vec![0.0; w * h];
for y in 0..h {
for x in 0..w {
// Source (x, y) lands at (y, w - 1 - x) in an h-wide image.
data[(w - 1 - x) * h + y] = self.data[y * w + x];
}
}
Gray {
width: h,
height: w,
data,
}
}
fn rotated_180(&self) -> Gray {
let mut data = self.data.clone();
data.reverse();
Gray {
width: self.width,
height: self.height,
data,
}
}
/// Resample to exactly `width × height` by area averaging on the way
/// down and bilinear on the way up.
///
/// Area averaging, not point sampling, for a reduction: a 5472 px frame
/// to 1024 is a factor of five, and picking one source pixel in
/// twenty-five aliases every edge the detector is looking for.
pub fn resampled(&self, width: usize, height: usize) -> Gray {
if width == self.width && height == self.height {
return self.clone();
}
let mut data = vec![0.0f32; width * height];
let sx = self.width as f64 / width as f64;
let sy = self.height as f64 / height as f64;
if sx >= 1.0 && sy >= 1.0 {
for oy in 0..height {
let y0 = (oy as f64 * sy) as usize;
let y1 = (((oy + 1) as f64 * sy) as usize).clamp(y0 + 1, self.height);
for ox in 0..width {
let x0 = (ox as f64 * sx) as usize;
let x1 = (((ox + 1) as f64 * sx) as usize).clamp(x0 + 1, self.width);
let mut sum = 0.0f32;
for y in y0..y1 {
let row = &self.data[y * self.width..(y + 1) * self.width];
sum += row[x0..x1].iter().sum::<f32>();
}
data[oy * width + ox] = sum / ((y1 - y0) * (x1 - x0)) as f32;
}
}
} else {
for oy in 0..height {
let fy = ((oy as f64 + 0.5) * sy - 0.5).max(0.0);
let y0 = (fy as usize).min(self.height - 1);
let y1 = (y0 + 1).min(self.height - 1);
let ty = (fy - y0 as f64) as f32;
for ox in 0..width {
let fx = ((ox as f64 + 0.5) * sx - 0.5).max(0.0);
let x0 = (fx as usize).min(self.width - 1);
let x1 = (x0 + 1).min(self.width - 1);
let tx = (fx - x0 as f64) as f32;
let p = |x: usize, y: usize| self.data[y * self.width + x];
let top = p(x0, y0) * (1.0 - tx) + p(x1, y0) * tx;
let bot = p(x0, y1) * (1.0 - tx) + p(x1, y1) * tx;
data[oy * width + ox] = top * (1.0 - ty) + bot * ty;
}
}
}
Gray {
width,
height,
data,
}
}
/// Scale so the image fits inside `max_width × max_height`, preserving
/// aspect, never enlarging. Returns the image and the scale applied,
/// which is what maps a proxy keypoint back to the source.
pub fn fitted(&self, max_width: usize, max_height: usize) -> (Gray, f64) {
let scale = (max_width as f64 / self.width as f64)
.min(max_height as f64 / self.height as f64)
.min(1.0);
let w = ((self.width as f64 * scale).round() as usize).max(1);
let h = ((self.height as f64 * scale).round() as usize).max(1);
(self.resampled(w, h), w as f64 / self.width as f64)
}
/// Copy into the top-left of a `width × height` canvas, zero elsewhere.
///
/// The detector's input is a fixed shape (S15.2), and a frame that fits
/// inside it is padded rather than stretched: stretching changes the
/// aspect and with it every descriptor.
pub fn padded(&self, width: usize, height: usize) -> Gray {
assert!(self.width <= width && self.height <= height);
let mut data = vec![0.0; width * height];
for y in 0..self.height {
data[y * width..y * width + self.width]
.copy_from_slice(&self.data[y * self.width..(y + 1) * self.width]);
}
Gray {
width,
height,
data,
}
}
}
#[cfg(test)]
mod tests {
use super::*;
fn ramp(w: usize, h: usize) -> Gray {
Gray {
width: w,
height: h,
data: (0..w * h).map(|i| i as f32).collect(),
}
}
#[test]
fn rotating_four_quarter_turns_is_the_identity() {
let g = ramp(5, 3);
let mut r = g.clone();
for _ in 0..4 {
r = r.rotated_90_cw();
}
assert_eq!(r, g);
assert_eq!(g.rotated_90_cw().rotated_90_ccw(), g);
assert_eq!(g.rotated_180().rotated_180(), g);
}
#[test]
fn a_clockwise_turn_moves_the_top_left_to_the_top_right() {
// 2×3 image, pixel values by position.
let g = ramp(2, 3);
let r = g.rotated_90_cw();
assert_eq!((r.width, r.height), (3, 2));
// Top-left of source (value 0) is at top-right of result.
assert_eq!(r.data[2], 0.0);
// Bottom-left of source (value 4) is at top-left of result.
assert_eq!(r.data[0], 4.0);
}
#[test]
fn orientation_8_is_a_counter_clockwise_turn() {
let g = ramp(4, 2);
assert_eq!(g.oriented(8), g.rotated_90_ccw());
assert_eq!(g.oriented(6), g.rotated_90_cw());
assert_eq!(g.oriented(1), g);
}
#[test]
fn downsampling_by_two_averages_blocks() {
let g = Gray {
width: 4,
height: 2,
data: vec![0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0],
};
let r = g.resampled(2, 1);
assert_eq!(r.data, vec![2.5, 4.5]);
}
#[test]
fn fitting_never_enlarges_and_reports_the_scale() {
let g = ramp(100, 50);
let (f, s) = g.fitted(1024, 768);
assert_eq!((f.width, f.height), (100, 50));
assert_eq!(s, 1.0);
let (f, s) = g.fitted(50, 50);
assert_eq!((f.width, f.height), (50, 25));
assert_eq!(s, 0.5);
}
#[test]
fn padding_places_the_image_at_the_origin() {
let g = ramp(2, 2);
let p = g.padded(3, 3);
assert_eq!(p.data, vec![0.0, 1.0, 0.0, 2.0, 3.0, 0.0, 0.0, 0.0, 0.0]);
}
}
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//! TRACES: FR-MRG-1 | FR-MRG-10
//! Panorama geometry — from several frames to the rotations that relate
//! them, and the projections that lay them out.
//!
//! This is the CPU half of a merge (FR-MRG-10): keypoints, matching, the
//! rotation solve and the choice of output surface. The per-pixel half —
//! rendering, warping, seams, blending — is the GPU's and lives in
//! `dr-gpu`, driven from above; nothing here touches a full-resolution
//! pixel. The split is the whole design (panorama.md §4): everything in
//! this crate is bounded by the number of frames, not the size of the
//! composite, and runs on proxies.
//!
//! # Layout
//!
//! - [`image`] — the grayscale proxy a detector reads: oriented, resampled.
//! - [`features`] — keypoints with descriptors, and the XFeat decoder.
//! - [`xfeat`] — the network under tract (feature `xfeat`).
//! - [`matching`] — mutual nearest neighbours.
//! - [`homography`] — a robust pairwise homography, the focal length read
//! off it, and the rotation it implies.
//! - [`bundle`] — every rotation and the focal length refined together.
//! - [`align`] — the whole thing, from features to cameras, honest about
//! what it could not place.
//! - [`projection`] — perspective, cylindrical, spherical.
//! - [`linalg`] — the small dense algebra all of it uses.
//!
//! # What it depends on
//!
//! Nothing, without the `xfeat` feature: the geometry is pure Rust with
//! hand-rolled linear algebra (`linalg` says why) so that it tests without
//! a model, a GPU or a device, on synthetic sets whose answer is known
//! exactly. With the feature it adds the same `ort`-over-tract runtime the
//! rest of the application already carries.
pub mod align;
pub mod bundle;
pub mod features;
pub mod fill;
pub mod homography;
pub mod image;
pub mod linalg;
pub mod matching;
#[cfg(feature = "xfeat")]
pub mod migan;
pub mod projection;
#[cfg(feature = "xfeat")]
pub mod xfeat;
pub use align::{align, AlignOptions, Alignment, Link, Unaligned};
pub use bundle::Cameras;
pub use features::{Features, Keypoint};
pub use fill::{fill_border, Inpainter, Observer, Params as FillParams};
pub use image::Gray;
pub use projection::Projection;
#[derive(Debug, thiserror::Error)]
pub enum PanoError {
#[error("bad input: {0}")]
Input(String),
#[error("geometry: {0}")]
Geometry(String),
#[error("model: {0}")]
Model(String),
#[error("could not read the model: {0}")]
ModelRead(#[source] std::io::Error),
#[cfg(feature = "xfeat")]
#[error("inference: {0}")]
Inference(#[source] ort::Error),
}
#[cfg(feature = "xfeat")]
impl From<ort::Error> for PanoError {
fn from(e: ort::Error) -> Self {
PanoError::Inference(e)
}
}
#[cfg(feature = "xfeat")]
impl From<dr_inference_engine::Error> for PanoError {
fn from(e: dr_inference_engine::Error) -> Self {
match e {
dr_inference_engine::Error::Inference(e) => PanoError::Inference(e),
dr_inference_engine::Error::Io(e) => PanoError::ModelRead(e),
}
}
}
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//! The small dense linear algebra the geometry needs, and nothing more.
//!
//! Hand-rolled rather than pulled in, and the decision was made on purpose
//! (2026-09-19): the largest system this crate ever solves is a rotation
//! per frame plus one focal length — forty unknowns for a dozen frames —
//! and everything else is three-vectors. A general linear-algebra crate
//! would be the largest dependency in `dr-pano` by an order of magnitude,
//! for a Cholesky factorisation that is thirty lines.
//!
//! `f64` throughout. The geometry is solved once per merge on a few thousand
//! matches; there is no reason to give up precision for speed here, and the
//! bundle adjustment's normal equations are poorly conditioned enough near
//! convergence that `f32` would stall it.
use std::ops::{Add, Index, IndexMut, Mul, Neg, Sub};
/// A vector in three dimensions.
#[derive(Debug, Clone, Copy, PartialEq, Default)]
pub struct Vec3(pub [f64; 3]);
impl Vec3 {
pub const fn new(x: f64, y: f64, z: f64) -> Self {
Vec3([x, y, z])
}
pub fn dot(self, o: Vec3) -> f64 {
self.0[0] * o.0[0] + self.0[1] * o.0[1] + self.0[2] * o.0[2]
}
pub fn cross(self, o: Vec3) -> Vec3 {
Vec3([
self.0[1] * o.0[2] - self.0[2] * o.0[1],
self.0[2] * o.0[0] - self.0[0] * o.0[2],
self.0[0] * o.0[1] - self.0[1] * o.0[0],
])
}
pub fn norm(self) -> f64 {
self.dot(self).sqrt()
}
/// The unit vector along `self`, or `self` unchanged if it is zero.
pub fn normalised(self) -> Vec3 {
let n = self.norm();
if n > 0.0 {
self * (1.0 / n)
} else {
self
}
}
pub fn x(self) -> f64 {
self.0[0]
}
pub fn y(self) -> f64 {
self.0[1]
}
pub fn z(self) -> f64 {
self.0[2]
}
}
impl Add for Vec3 {
type Output = Vec3;
fn add(self, o: Vec3) -> Vec3 {
Vec3([self.0[0] + o.0[0], self.0[1] + o.0[1], self.0[2] + o.0[2]])
}
}
impl Sub for Vec3 {
type Output = Vec3;
fn sub(self, o: Vec3) -> Vec3 {
Vec3([self.0[0] - o.0[0], self.0[1] - o.0[1], self.0[2] - o.0[2]])
}
}
impl Mul<f64> for Vec3 {
type Output = Vec3;
fn mul(self, s: f64) -> Vec3 {
Vec3([self.0[0] * s, self.0[1] * s, self.0[2] * s])
}
}
impl Neg for Vec3 {
type Output = Vec3;
fn neg(self) -> Vec3 {
Vec3([-self.0[0], -self.0[1], -self.0[2]])
}
}
/// A 3×3 matrix, row-major.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct Mat3(pub [[f64; 3]; 3]);
impl Mat3 {
pub const IDENTITY: Mat3 = Mat3([[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]);
/// The matrix whose columns are `a`, `b`, `c`.
pub fn from_columns(a: Vec3, b: Vec3, c: Vec3) -> Mat3 {
Mat3([
[a.0[0], b.0[0], c.0[0]],
[a.0[1], b.0[1], c.0[1]],
[a.0[2], b.0[2], c.0[2]],
])
}
pub fn transpose(self) -> Mat3 {
let m = self.0;
Mat3([
[m[0][0], m[1][0], m[2][0]],
[m[0][1], m[1][1], m[2][1]],
[m[0][2], m[1][2], m[2][2]],
])
}
pub fn column(self, i: usize) -> Vec3 {
Vec3([self.0[0][i], self.0[1][i], self.0[2][i]])
}
pub fn trace(self) -> f64 {
self.0[0][0] + self.0[1][1] + self.0[2][2]
}
/// The rotation about `axis` (any length) by `angle` radians — Rodrigues.
pub fn rotation(axis: Vec3, angle: f64) -> Mat3 {
let k = axis.normalised();
let (s, c) = angle.sin_cos();
let t = 1.0 - c;
let (x, y, z) = (k.0[0], k.0[1], k.0[2]);
Mat3([
[t * x * x + c, t * x * y - s * z, t * x * z + s * y],
[t * x * y + s * z, t * y * y + c, t * y * z - s * x],
[t * x * z - s * y, t * y * z + s * x, t * z * z + c],
])
}
/// The rotation whose axis-angle vector is `w` (direction is the axis,
/// length is the angle). The exponential map; [`Self::log`] inverts it.
pub fn exp(w: Vec3) -> Mat3 {
let angle = w.norm();
if angle < 1e-12 {
// First-order: I + [w]×, which is what the limit is and avoids
// dividing by the angle.
let (x, y, z) = (w.0[0], w.0[1], w.0[2]);
return Mat3([[1.0, -z, y], [z, 1.0, -x], [-y, x, 1.0]]);
}
Mat3::rotation(w, angle)
}
/// The axis-angle vector of a rotation matrix. Inverse of [`Self::exp`].
pub fn log(self) -> Vec3 {
let m = self.0;
let cos = ((self.trace() - 1.0) * 0.5).clamp(-1.0, 1.0);
let axis = Vec3([m[2][1] - m[1][2], m[0][2] - m[2][0], m[1][0] - m[0][1]]);
if cos > 1.0 - 1e-6 {
// Small angle: `acos` near 1 loses everything below ~1e-8 to
// rounding, but the antisymmetric part is `2 sin θ · axis` and
// keeps it. First order, exact to the precision that matters.
return axis * 0.5;
}
let angle = cos.acos();
if angle > std::f64::consts::PI - 1e-6 {
// Near π the antisymmetric part vanishes; take the axis from the
// symmetric part instead. Rare for a panorama, but the solver may
// pass through it on a bad start and must not return NaN.
let d = Vec3([
((m[0][0] + 1.0) * 0.5).max(0.0).sqrt(),
((m[1][1] + 1.0) * 0.5).max(0.0).sqrt(),
((m[2][2] + 1.0) * 0.5).max(0.0).sqrt(),
]);
return d.normalised() * angle;
}
axis * (angle / (2.0 * angle.sin()))
}
/// Re-orthonormalise a matrix that has drifted from a rotation through
/// accumulated products. Gram–Schmidt on the columns; cheap and adequate
/// for drift of the size floating-point products produce.
pub fn orthonormalised(self) -> Mat3 {
let a = self.column(0).normalised();
let b = (self.column(1) - a * a.dot(self.column(1))).normalised();
let c = a.cross(b);
Mat3::from_columns(a, b, c)
}
}
impl Mul<Vec3> for Mat3 {
type Output = Vec3;
fn mul(self, v: Vec3) -> Vec3 {
let m = self.0;
Vec3([
m[0][0] * v.0[0] + m[0][1] * v.0[1] + m[0][2] * v.0[2],
m[1][0] * v.0[0] + m[1][1] * v.0[1] + m[1][2] * v.0[2],
m[2][0] * v.0[0] + m[2][1] * v.0[1] + m[2][2] * v.0[2],
])
}
}
impl Mul for Mat3 {
type Output = Mat3;
fn mul(self, o: Mat3) -> Mat3 {
let mut r = [[0.0; 3]; 3];
for (i, row) in r.iter_mut().enumerate() {
for (j, cell) in row.iter_mut().enumerate() {
*cell = (0..3).map(|k| self.0[i][k] * o.0[k][j]).sum();
}
}
Mat3(r)
}
}
/// A dense square matrix, for the normal equations.
#[derive(Debug, Clone, PartialEq)]
pub struct DMat {
n: usize,
data: Vec<f64>,
}
impl DMat {
pub fn zeros(n: usize) -> DMat {
DMat {
n,
data: vec![0.0; n * n],
}
}
pub fn n(&self) -> usize {
self.n
}
/// Solve `self · x = b` for a symmetric positive-definite `self` by
/// Cholesky factorisation. `None` if the matrix is not positive definite,
/// which for the normal equations means the problem is not determined by
/// the data — a frame with no matches, for instance — and the caller
/// should say so rather than proceed.
///
/// Destroys neither input: the factor is built in a copy. The systems
/// here are at most a few dozen unknowns and the copy is nothing.
pub fn solve_spd(&self, b: &[f64]) -> Option<Vec<f64>> {
let n = self.n;
debug_assert_eq!(b.len(), n);
let mut l = vec![0.0; n * n];
for j in 0..n {
let mut d = self[(j, j)];
for k in 0..j {
d -= l[j * n + k] * l[j * n + k];
}
if d <= 0.0 || !d.is_finite() {
return None;
}
let djj = d.sqrt();
l[j * n + j] = djj;
for i in j + 1..n {
let mut s = self[(i, j)];
for k in 0..j {
s -= l[i * n + k] * l[j * n + k];
}
l[i * n + j] = s / djj;
}
}
// Forward: L y = b.
let mut y = vec![0.0; n];
for i in 0..n {
let mut s = b[i];
for k in 0..i {
s -= l[i * n + k] * y[k];
}
y[i] = s / l[i * n + i];
}
// Back: Lᵀ x = y.
let mut x = vec![0.0; n];
for i in (0..n).rev() {
let mut s = y[i];
for k in i + 1..n {
s -= l[k * n + i] * x[k];
}
x[i] = s / l[i * n + i];
}
Some(x)
}
}
impl Index<(usize, usize)> for DMat {
type Output = f64;
fn index(&self, (i, j): (usize, usize)) -> &f64 {
&self.data[i * self.n + j]
}
}
impl IndexMut<(usize, usize)> for DMat {
fn index_mut(&mut self, (i, j): (usize, usize)) -> &mut f64 {
&mut self.data[i * self.n + j]
}
}
#[cfg(test)]
mod tests {
use super::*;
fn close(a: f64, b: f64) -> bool {
(a - b).abs() < 1e-9
}
#[test]
fn exp_and_log_are_inverses() {
for w in [
Vec3::new(0.1, -0.2, 0.3),
Vec3::new(1.0, 0.0, 0.0),
Vec3::new(0.0, 0.0, 2.5),
Vec3::new(1e-9, 0.0, 0.0),
] {
let back = Mat3::exp(w).log();
for i in 0..3 {
assert!(close(back.0[i], w.0[i]), "{w:?} -> {back:?}");
}
}
}
#[test]
fn a_rotation_is_orthonormal_and_preserves_length() {
let r = Mat3::exp(Vec3::new(0.4, 0.5, -0.6));
let rt = r.transpose() * r;
for i in 0..3 {
for j in 0..3 {
assert!(close(rt.0[i][j], Mat3::IDENTITY.0[i][j]));
}
}
let v = Vec3::new(1.0, 2.0, 3.0);
assert!(close((r * v).norm(), v.norm()));
}
#[test]
fn rotation_about_z_turns_x_towards_y() {
let r = Mat3::rotation(Vec3::new(0.0, 0.0, 1.0), std::f64::consts::FRAC_PI_2);
let v = r * Vec3::new(1.0, 0.0, 0.0);
assert!(close(v.x(), 0.0) && close(v.y(), 1.0) && close(v.z(), 0.0));
}
#[test]
fn cholesky_solves_a_small_spd_system() {
// A = Bᵀ B for a random-ish B is SPD by construction.
let b = [
[2.0, 1.0, 0.0],
[1.0, 3.0, 1.0],
[0.0, 1.0, 4.0],
[1.0, 1.0, 1.0],
];
let mut a = DMat::zeros(3);
for i in 0..3 {
for j in 0..3 {
a[(i, j)] = (0..4).map(|k| b[k][i] * b[k][j]).sum();
}
}
let x_true = [1.0, -2.0, 0.5];
let rhs: Vec<f64> = (0..3)
.map(|i| (0..3).map(|j| a[(i, j)] * x_true[j]).sum())
.collect();
let x = a.solve_spd(&rhs).expect("spd");
for i in 0..3 {
assert!(close(x[i], x_true[i]), "{x:?}");
}
}
#[test]
fn cholesky_refuses_an_indefinite_matrix() {
let mut a = DMat::zeros(2);
a[(0, 0)] = 1.0;
a[(1, 1)] = -1.0;
assert!(a.solve_spd(&[1.0, 1.0]).is_none());
}
}
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//! Descriptor matching between two images.
//!
//! Mutual nearest neighbour on cosine similarity, with a floor on the
//! similarity — the reference XFeat's own matcher (`match_mkpts`,
//! `min_cossim = 0.82`). For a panorama that is enough: one lens, one
//! scene, near-pure rotation and 20–40 % overlap make the matching problem
//! easy, and what is hard — sky, repeated structure, exposure drift — is
//! handled by the detector's descriptors and by RANSAC downstream, not by a
//! cleverer matcher. A learned matcher (LightGlue) is the step after this
//! one fails on a real set, and it has not (panorama.md §6).
//!
//! Brute force. `4096 × 4096 × 64` multiply-adds is a billion per pair,
//! and a twelve-frame set has sixty-six pairs: a minute single-threaded
//! and scalar (measured 2026-09-19: 51 s), a few seconds vectorised across
//! the cores. Not worth an index, but worth doing properly.
use crate::features::{Features, DESCRIPTOR_LEN};
const _: () = assert!(DESCRIPTOR_LEN.is_multiple_of(8));
/// A correspondence: keypoint `a` in the first image matches keypoint `b`
/// in the second, with the cosine similarity of their descriptors.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct Match {
pub a: usize,
pub b: usize,
pub similarity: f32,
}
/// Match two sets of features.
///
/// A pair is kept when each is the other's nearest neighbour and their
/// similarity is at least `min_similarity`.
pub fn match_features(a: &Features, b: &Features, min_similarity: f32) -> Vec<Match> {
if a.is_empty() || b.is_empty() {
return Vec::new();
}
let (na, nb) = (a.len(), b.len());
// The whole similarity matrix, once. Both nearest-neighbour directions
// read it, which halves the multiply-adds against computing each
// direction on its own; 4096 × 4096 × f32 is 64 MB, transient.
let mut sim = vec![0.0f32; na * nb];
let threads = std::thread::available_parallelism()
.map(usize::from)
.unwrap_or(1)
.clamp(1, 16);
let rows_per = na.div_ceil(threads);
std::thread::scope(|scope| {
for (t, chunk) in sim.chunks_mut(rows_per * nb).enumerate() {
scope.spawn(move || {
let first = t * rows_per;
for (r, row) in chunk.chunks_mut(nb).enumerate() {
let da = a.descriptor(first + r);
for (j, cell) in row.iter_mut().enumerate() {
*cell = dot(da, b.descriptor(j));
}
}
});
}
});
// Best in `b` for each `a`, and best in `a` for each `b`.
let best_ab: Vec<(usize, f32)> = sim
.chunks_exact(nb)
.map(|row| {
row.iter().enumerate().fold(
(0usize, f32::MIN),
|acc, (j, &s)| if s > acc.1 { (j, s) } else { acc },
)
})
.collect();
let mut best_ba = vec![(0usize, f32::MIN); nb];
for (i, row) in sim.chunks_exact(nb).enumerate() {
for (j, &s) in row.iter().enumerate() {
if s > best_ba[j].1 {
best_ba[j] = (i, s);
}
}
}
best_ab
.iter()
.enumerate()
.filter_map(|(ia, &(ib, s))| {
(best_ba[ib].0 == ia && s >= min_similarity).then_some(Match {
a: ia,
b: ib,
similarity: s,
})
})
.collect()
}
#[inline]
fn dot(a: &[f32], b: &[f32]) -> f32 {
// Eight independent accumulators over exact 8-lane chunks: the shape
// the compiler turns into one vector multiply-add per chunk, and no
// bounds checks inside the loop. `DESCRIPTOR_LEN` is a multiple of 8.
let (a, b) = (&a[..DESCRIPTOR_LEN], &b[..DESCRIPTOR_LEN]);
let mut acc = [0.0f32; 8];
for (ca, cb) in a.chunks_exact(8).zip(b.chunks_exact(8)) {
for k in 0..8 {
acc[k] += ca[k] * cb[k];
}
}
acc.iter().sum()
}
#[cfg(test)]
mod tests {
use super::*;
use crate::features::Keypoint;
/// Features whose descriptors are unit vectors along the given axes.
fn along(axes: &[usize]) -> Features {
let mut descriptors = vec![0.0; axes.len() * DESCRIPTOR_LEN];
for (i, &ax) in axes.iter().enumerate() {
descriptors[i * DESCRIPTOR_LEN + ax] = 1.0;
}
Features {
keypoints: axes
.iter()
.map(|_| Keypoint {
x: 0.0,
y: 0.0,
score: 1.0,
})
.collect(),
descriptors,
width: 1,
height: 1,
}
}
#[test]
fn identical_descriptors_match_mutually() {
let a = along(&[0, 1, 2]);
let b = along(&[2, 0, 1]);
let m = match_features(&a, &b, 0.8);
let mut pairs: Vec<(usize, usize)> = m.iter().map(|m| (m.a, m.b)).collect();
pairs.sort();
assert_eq!(pairs, vec![(0, 1), (1, 2), (2, 0)]);
assert!(m.iter().all(|m| (m.similarity - 1.0).abs() < 1e-6));
}
#[test]
fn a_descriptor_with_no_counterpart_is_unmatched() {
let a = along(&[0, 1, 5]);
let b = along(&[0, 1]);
let m = match_features(&a, &b, 0.8);
assert_eq!(m.len(), 2);
assert!(m.iter().all(|m| m.a != 2));
}
#[test]
fn mutuality_breaks_a_one_sided_match() {
// b0 is the nearest to both a0 and a1, but a0 is its nearest — a1
// must not be matched to it.
let mut a = along(&[0, 0]);
a.descriptors[DESCRIPTOR_LEN] = 0.9;
a.descriptors[DESCRIPTOR_LEN + 1] = (1.0f32 - 0.81).sqrt();
let b = along(&[0]);
let m = match_features(&a, &b, 0.0);
assert_eq!(m.len(), 1);
assert_eq!((m[0].a, m[0].b), (0, 0));
}
#[test]
fn empty_input_is_empty_output() {
assert!(match_features(&along(&[]), &along(&[1]), 0.5).is_empty());
}
}
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//! TRACES: FR-MRG-4
//! MI-GAN, the border filler, under the inference engine.
//!
//! Sargsyan et al., ICCV 2023 (Picsart AI Research): inpainting built for
//! phones — about six million parameters of plain convolutions, no FFT and
//! no attention, so it quantises and runs on a DSP. MIT, code and weights
//! (`models/LICENCE.md`). The bare 512 generator is what ships, exported
//! at a fixed shape by `tools/export-migan.sh`; its six operator types load
//! on every rung, and what they cost is the whole story of whether a fill
//! is interactive: 7.4 s a tile under tract, 0.4 s under ONNX Runtime's
//! CPU pool, 23 ms in fp16 and 13 ms in int8 on a laptop's TensorRT
//! (2026-09-19, docs/panorama.md §12).
//!
//! The model's contract, from the reference `export_inference_model.py`:
//! input `1×4×512×512` float — channel 0 is `mask − 0.5` with 1 where the
//! picture is known, channels 1–3 the RGB in −1..1 with the unknown pixels
//! zeroed; output `1×3×512×512` in −1..1, of which the caller keeps the
//! unknown pixels. That is [`crate::fill::Inpainter`], and the rest —
//! which tiles, what context, how to blend — is `fill.rs`.
use crate::fill::Inpainter;
use crate::PanoError;
/// The tile the shipped export takes.
pub const TILE: usize = 512;
pub struct MiGan {
model: dr_inference_engine::Model,
}
impl MiGan {
/// From the model file, in whichever form the engine's rung wants
/// (`resolve_model` picks an int8 sibling for the Hexagon).
pub fn from_path(path: &std::path::Path) -> Result<Self, PanoError> {
use dr_inference_engine::{resolve_model, Role};
let (path, form) = resolve_model(Role::Inpainter, path);
let bytes = std::fs::read(&path).map_err(PanoError::ModelRead)?;
Self::from_bytes(&bytes, form)
}
pub fn from_bytes(bytes: &[u8], form: dr_inference_engine::Form) -> Result<Self, PanoError> {
use dr_inference_engine::Role;
Ok(MiGan {
model: dr_inference_engine::open(Role::Inpainter, form, bytes)?,
})
}
/// Where the fill runs, for a status line.
pub fn rung(&self) -> Result<dr_inference_engine::Rung, PanoError> {
Ok(self.model.acquire()?.rung())
}
}
impl Inpainter for MiGan {
fn tile(&self) -> usize {
TILE
}
fn fill(&mut self, rgb: &[f32], known: &[bool]) -> Result<Vec<f32>, PanoError> {
let n = TILE * TILE;
if rgb.len() != n * 3 || known.len() != n {
return Err(PanoError::Input(format!(
"MI-GAN takes a {TILE}×{TILE} tile; given {} values and {} mask entries",
rgb.len(),
known.len()
)));
}
// NCHW: the mask plane, then the three masked colour planes.
let mut input = vec![0.0f32; 4 * n];
for i in 0..n {
let m = if known[i] { 1.0 } else { 0.0 };
input[i] = m - 0.5;
for c in 0..3 {
input[(c + 1) * n + i] = (rgb[i * 3 + c] * 2.0 - 1.0) * m;
}
}
let tensor = ort::value::Tensor::from_array(
ndarray::Array::from_shape_vec(ndarray::IxDyn(&[1, 4, TILE, TILE]), input)
.expect("shape matches by construction"),
)?;
let started = std::time::Instant::now();
let acquired = self.model.acquire()?;
let acquired_at = started.elapsed();
let mut session = acquired.lock();
let outputs = session.run(ort::inputs![tensor])?;
log::trace!(
"migan: tile on {} — acquire {:.1} ms, run {:.1} ms",
acquired.rung().label(),
acquired_at.as_secs_f64() * 1e3,
(started.elapsed() - acquired_at).as_secs_f64() * 1e3
);
let (shape, data) = outputs[0].try_extract_tensor::<f32>()?;
let dims: Vec<i64> = shape.iter().copied().collect();
if dims != [1, 3, TILE as i64, TILE as i64] {
return Err(PanoError::Model(format!(
"MI-GAN output is {dims:?}, expected [1, 3, {TILE}, {TILE}]"
)));
}
let mut out = vec![0.0f32; n * 3];
for i in 0..n {
for c in 0..3 {
out[i * 3 + c] = (data[c * n + i] * 0.5 + 0.5).clamp(0.0, 1.0);
}
}
Ok(out)
}
}
+197
View File
@@ -0,0 +1,197 @@
//! TRACES: FR-MRG-4
//! The surface the composite is drawn on.
//!
//! A panorama is a set of directions; a picture is a plane. The projection
//! is the map between them, and the three offered are the three every
//! stitcher offers because each is right for a different field of view:
//! perspective keeps straight lines straight and cannot reach 180°;
//! cylindrical keeps verticals vertical and stretches nothing horizontally,
//! for the wide single row; spherical for anything that also looks up.
//!
//! Every function here is the *inverse* map — output pixel to direction —
//! because that is what a gather needs (`lens.rs` in `dr-pipeline` says
//! why a warp is written that way), and it is the function the WGSL warp
//! will repeat verbatim. The forward map exists for bounds only.
use crate::linalg::Vec3;
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum Projection {
Perspective,
Cylindrical,
Spherical,
}
impl Projection {
/// Which projection a field of view calls for.
///
/// Perspective stretches the edges by `1 / cos` of the angle from the
/// centre, which is 2× at 60° and unbounded at 90°; the switch is where
/// that stretch starts to look like a mistake. Spherical is for a set
/// that spans enough vertically that a cylinder would stretch the top
/// and bottom the same way.
pub fn suggest(horizontal_fov: f64, vertical_fov: f64) -> Projection {
if horizontal_fov < 70f64.to_radians() && vertical_fov < 70f64.to_radians() {
Projection::Perspective
} else if vertical_fov < 100f64.to_radians() {
Projection::Cylindrical
} else {
Projection::Spherical
}
}
/// The direction an output point looks along. `scale` is the output's
/// focal length in pixels: the radius of the cylinder or sphere, or the
/// plane's distance. Coordinates are centred on the projection's origin
/// (the direction `+z`).
pub fn to_direction(self, scale: f64, u: f64, v: f64) -> Vec3 {
match self {
Projection::Perspective => Vec3::new(u, v, scale).normalised(),
Projection::Cylindrical => {
let theta = u / scale;
Vec3::new(theta.sin(), v / scale, theta.cos()).normalised()
}
Projection::Spherical => {
let theta = u / scale;
let phi = v / scale;
Vec3::new(theta.sin() * phi.cos(), phi.sin(), theta.cos() * phi.cos())
}
}
}
/// Where a direction lands on the output, or `None` where the
/// projection cannot show it (behind a perspective plane, at a
/// cylinder's poles).
pub fn from_direction(self, scale: f64, d: Vec3) -> Option<(f64, f64)> {
let (x, y, z) = (d.x(), d.y(), d.z());
match self {
Projection::Perspective => (z > 1e-9).then(|| (scale * x / z, scale * y / z)),
Projection::Cylindrical => {
let r = (x * x + z * z).sqrt();
(r > 1e-9).then(|| (scale * x.atan2(z), scale * y / r))
}
Projection::Spherical => {
let r = (x * x + z * z).sqrt();
Some((scale * x.atan2(z), scale * y.atan2(r)))
}
}
}
}
/// The output rectangle a set of frames covers, in centred output pixels.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct Bounds {
pub min_u: f64,
pub min_v: f64,
pub max_u: f64,
pub max_v: f64,
}
impl Bounds {
pub fn width(&self) -> f64 {
self.max_u - self.min_u
}
pub fn height(&self) -> f64 {
self.max_v - self.min_v
}
}
/// Bounds of the frames' footprints under `projection`, by walking each
/// frame's border.
///
/// `frame_size` is the frames' width and height in the same pixels the
/// cameras' focal length is in. The border is sampled rather than only its
/// corners because under a cylinder the widest point of a rolled frame is
/// not a corner.
pub fn bounds(
projection: Projection,
scale: f64,
cameras: &crate::bundle::Cameras,
frame_size: (f64, f64),
) -> Option<Bounds> {
let (w, h) = frame_size;
let mut b: Option<Bounds> = None;
let steps = 64;
for k in 0..cameras.rotations.len() {
for s in 0..steps {
let t = s as f64 / steps as f64;
for p in [
(-w / 2.0 + w * t, -h / 2.0),
(-w / 2.0 + w * t, h / 2.0),
(-w / 2.0, -h / 2.0 + h * t),
(w / 2.0, -h / 2.0 + h * t),
] {
let d = cameras.bearing(k, p);
let Some((u, v)) = projection.from_direction(scale, d) else {
continue;
};
b = Some(match b {
None => Bounds {
min_u: u,
min_v: v,
max_u: u,
max_v: v,
},
Some(b) => Bounds {
min_u: b.min_u.min(u),
min_v: b.min_v.min(v),
max_u: b.max_u.max(u),
max_v: b.max_v.max(v),
},
});
}
}
}
b
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn to_and_from_direction_are_inverses() {
for proj in [
Projection::Perspective,
Projection::Cylindrical,
Projection::Spherical,
] {
for (u, v) in [(0.0, 0.0), (300.0, -200.0), (-900.0, 450.0)] {
let d = proj.to_direction(1000.0, u, v);
let (bu, bv) = proj.from_direction(1000.0, d).expect("in front");
assert!(
(bu - u).abs() < 1e-9 && (bv - v).abs() < 1e-9,
"{proj:?} {u} {v}"
);
}
}
}
#[test]
fn the_origin_looks_down_z_in_every_projection() {
for proj in [
Projection::Perspective,
Projection::Cylindrical,
Projection::Spherical,
] {
let d = proj.to_direction(500.0, 0.0, 0.0);
assert!((d.z() - 1.0).abs() < 1e-12);
}
}
#[test]
fn a_cylinder_maps_ninety_degrees_to_a_quarter_turn_of_pixels() {
let d = Vec3::new(1.0, 0.0, 0.0);
let (u, v) = Projection::Cylindrical.from_direction(100.0, d).unwrap();
assert!((u - 100.0 * std::f64::consts::FRAC_PI_2).abs() < 1e-9);
assert_eq!(v, 0.0);
assert!(Projection::Perspective.from_direction(100.0, d).is_none());
}
#[test]
fn suggestion_widens_with_the_field() {
assert_eq!(Projection::suggest(0.5, 0.5), Projection::Perspective);
assert_eq!(Projection::suggest(2.5, 0.8), Projection::Cylindrical);
assert_eq!(Projection::suggest(3.0, 2.5), Projection::Spherical);
}
}
+151
View File
@@ -0,0 +1,151 @@
//! TRACES: FR-MRG-8
//! The XFeat detector — the network under tract, and the decoder after it.
//!
//! Apache-2.0 weights (`models/LICENCE.md`), exported at a fixed shape by
//! `tools/export-xfeat.sh` and loaded through the same `dr-inference-engine`
//! `dr-segment` and `dr-face` use, so this adds no runtime and no C to the
//! tree; what runs it is the device's business (docs/inference.md). ~300 ms
//! per frame on tract on the reference desktop, ~400 ms on the tablet
//! (S15.2, S15.4).
use crate::features::{decode_xfeat, DecodeOptions, Features, XFeatMaps, DESCRIPTOR_LEN};
use crate::image::Gray;
use crate::PanoError;
/// The two input shapes the shipped exports were made for: one landscape,
/// one portrait, the same weights. A frame is fitted into whichever
/// matches its aspect, so a portrait set does not spend half the
/// detector's width on padding — which is what the 6D fixture did before
/// the second export existed (512 × 768 of a 1024 × 768 input). A
/// different size is a different file (`tools/export-xfeat.sh`).
pub const INPUT_LANDSCAPE: (usize, usize) = (1024, 768);
pub const INPUT_PORTRAIT: (usize, usize) = (768, 1024);
/// The long edge of the detector's input, for callers sizing a proxy.
pub const INPUT_LONG_EDGE: usize = 1024;
#[cfg(feature = "embedded-model")]
const EMBEDDED_LANDSCAPE: &[u8] = include_bytes!("../../../models/keypoints/xfeat-1024.onnx");
#[cfg(feature = "embedded-model")]
const EMBEDDED_PORTRAIT: &[u8] = include_bytes!("../../../models/keypoints/xfeat-768.onnx");
/// A loaded detector: the network at both shapes.
pub struct XFeat {
landscape: dr_inference_engine::Model,
portrait: dr_inference_engine::Model,
pub options: DecodeOptions,
}
/// The bytes of both exports compiled into the binary, for whoever compiles
/// engines ahead of the first request (docs/inference.md §6).
#[cfg(feature = "embedded-model")]
pub fn embedded_model_bytes() -> [&'static [u8]; 2] {
[EMBEDDED_LANDSCAPE, EMBEDDED_PORTRAIT]
}
impl XFeat {
/// The weights compiled into the binary.
#[cfg(feature = "embedded-model")]
pub fn embedded() -> Result<Self, PanoError> {
Self::from_bytes(EMBEDDED_LANDSCAPE, EMBEDDED_PORTRAIT)
}
/// From the two exports on disk.
pub fn from_paths(
landscape: &std::path::Path,
portrait: &std::path::Path,
) -> Result<Self, PanoError> {
let l = std::fs::read(landscape).map_err(PanoError::ModelRead)?;
let p = std::fs::read(portrait).map_err(PanoError::ModelRead)?;
Self::from_bytes(&l, &p)
}
pub fn from_bytes(landscape: &[u8], portrait: &[u8]) -> Result<Self, PanoError> {
use dr_inference_engine::{Form, Role};
Ok(XFeat {
landscape: dr_inference_engine::open(Role::Keypoints, Form::F32, landscape)?,
portrait: dr_inference_engine::open(Role::Keypoints, Form::F32, portrait)?,
options: DecodeOptions::default(),
})
}
/// Detect keypoints in an upright grayscale image.
///
/// The image is fitted into the network's input of matching aspect —
/// scaled down if larger, never up, and padded to the right and bottom
/// — and the keypoints come back in the coordinates of `image` itself,
/// so a caller that already scaled a frame to a proxy maps them on with
/// the scale it used and nothing else.
pub fn detect(&mut self, image: &Gray) -> Result<Features, PanoError> {
let ((in_w, in_h), model) = if image.height > image.width {
(INPUT_PORTRAIT, &self.portrait)
} else {
(INPUT_LANDSCAPE, &self.landscape)
};
let acquired = model.acquire()?;
let mut session = acquired.lock();
let (fitted, scale) = image.fitted(in_w, in_h);
let padded = fitted.padded(in_w, in_h);
let input =
ndarray::Array::from_shape_vec(ndarray::IxDyn(&[1, 1, in_h, in_w]), padded.data)
.expect("shape matches the buffer by construction");
let tensor = ort::value::Tensor::from_array(input).map_err(PanoError::Inference)?;
let outputs = session
.run(ort::inputs![tensor])
.map_err(PanoError::Inference)?;
let (w8, h8) = (in_w / 8, in_h / 8);
let expect = |i: usize, channels: usize| -> Result<Vec<f32>, PanoError> {
let (shape, data) = outputs[i]
.try_extract_tensor::<f32>()
.map_err(PanoError::Inference)?;
let dims: Vec<i64> = shape.iter().copied().collect();
if dims != [1, channels as i64, h8 as i64, w8 as i64] {
return Err(PanoError::Model(format!(
"output {i} is {dims:?}, expected [1, {channels}, {h8}, {w8}] — \
not the export this decoder was written for"
)));
}
Ok(data.to_vec())
};
let feats = expect(0, DESCRIPTOR_LEN)?;
let keypoints = expect(1, 65)?;
let heatmap = expect(2, 1)?;
let mut features = decode_xfeat(
&XFeatMaps {
feats: &feats,
keypoints: &keypoints,
heatmap: &heatmap,
width: w8,
height: h8,
},
&self.options,
);
// Back to the caller's image: drop anything the padding produced,
// undo the fit.
let border = self.options.border as f32;
let limit_x = fitted.width as f32 - border;
let limit_y = fitted.height as f32 - border;
let mut kept_kp = Vec::with_capacity(features.len());
let mut kept_desc = Vec::with_capacity(features.descriptors.len());
for (i, kp) in features.keypoints.iter().enumerate() {
if kp.x >= limit_x || kp.y >= limit_y {
continue;
}
kept_kp.push(crate::features::Keypoint {
x: (kp.x / scale as f32),
y: (kp.y / scale as f32),
score: kp.score,
});
kept_desc.extend_from_slice(features.descriptor(i));
}
features.keypoints = kept_kp;
features.descriptors = kept_desc;
features.width = image.width;
features.height = image.height;
Ok(features)
}
}
+41
View File
@@ -849,6 +849,47 @@ impl EditGraph {
)
}
/// TRACES: FR-MRG-2
/// The camera-space tap for a merge: this edit's lens corrections and
/// nothing else of it, stored at full precision. See
/// [`crate::operation::compose_camera_linear`].
pub fn compose_camera_linear(&self, view: crate::framing::CropRect) -> ComposedShader {
crate::operation::compose_camera_linear(&self.warps, self.framing.baseline(), view)
}
/// TRACES: FR-DEV-3
/// The camera-space tap over one patch of what is on the canvas.
///
/// `patch` is in fractions of the visible region — the coordinates a
/// click on the canvas arrives in — and is laid over this edit's own
/// framing: crop, view, rotation and all, so a fraction of the canvas is
/// a fraction of the probe. Nothing else of the edit: no operation, no
/// mask, no repair. Rendering only the patch is what lets a small target
/// cover every sensor pixel under it rather than sampling one in fifty;
/// see [`crate::operation::compose_camera_probe`] for why the white
/// balance picker reads from here and not from the display.
///
/// The patch is centred where asked and held to the view's own minimum
/// extent: at a deep zoom a patch a fraction of the view would be
/// smaller than a view may be, and letting `set_view` widen it from one
/// corner would move the sample off the point that was clicked.
pub fn compose_camera_probe(&self, patch: crate::framing::CropRect) -> ComposedShader {
use crate::framing::CropRect;
let mut framing = self.framing;
let view = framing.view();
let width = (patch.width * view.width).max(CropRect::MIN_EXTENT);
let height = (patch.height * view.height).max(CropRect::MIN_EXTENT);
let cx = view.x + (patch.x + patch.width * 0.5) * view.width;
let cy = view.y + (patch.y + patch.height * 0.5) * view.height;
framing.set_view(CropRect {
x: (cx - width * 0.5).clamp(0.0, 1.0 - width),
y: (cy - height * 0.5).clamp(0.0, 1.0 - height),
width,
height,
});
crate::operation::compose_camera_probe(&self.warps, &framing)
}
/// TRACES: FR-DEV-19c
/// [`Self::compose_for`], with one layer's mask drawn over the picture.
///
+2 -1
View File
@@ -65,7 +65,8 @@ pub use history::{Edit, Entry as HistoryEntry, History, Step};
pub use lens::{compose_warps, ComposedWarp, LensProfile, Tca, Warp};
pub use operation::{
compose, compose_with_framing, Affects, ComposedShader, Helper, Invalidation, Operation,
OutputMode, Uniform, BASE_CURVE_POINTS, BASE_CURVE_UNIFORM_OFFSET, RESERVED_UNIFORM_FIELDS,
OutputMode, Uniform, BASE_CURVE_POINTS, BASE_CURVE_UNIFORM_OFFSET, CLIP_ONSET,
RESERVED_UNIFORM_FIELDS,
};
pub use preset::{LibraryParseError, NameError, Preset, PresetLibrary, Scope};
pub use sidecar::{Sidecar, Version};
+6
View File
@@ -555,6 +555,7 @@ impl Morphology {
];
}
/// TRACES: FR-DEV-3 | FR-DEV-3i
/// Where a mask layer applies.
#[derive(Debug, Clone, PartialEq)]
pub enum MaskSource {
@@ -1303,7 +1304,12 @@ impl PartialEq for MaskPart {
}
}
/// TRACES: FR-DEV-19
/// One local adjustment: a rule about *where*, plus a chain saying *what*.
///
/// The *where* is editable after the fact — composed from parts (FR-DEV-19a),
/// painted into and out of (FR-DEV-19b), shown (FR-DEV-19c) — and every edit
/// to it is geometry and parameters in this struct, never a raster in a file.
pub struct MaskLayer {
/// Stable identity, for the sidecar and for merge (FR-NC-9).
pub id: String,
+15 -9
View File
@@ -69,20 +69,26 @@ const ROUNDS: u32 = 3;
/// Below this a channel carries no ratio worth balancing.
///
/// A sample in the deep shadows, or one taken on a blown highlight where a
/// channel has already clipped to nothing, has no white balance in it: the
/// logarithms below would run away and the picker would slam a slider to its
/// stop. Refusing is the honest answer, and the caller reports that the point
/// was not usable rather than moving the photograph.
/// A sample in the deep shadows has no white balance in it: the logarithms
/// below would run away and the picker would slam a slider to its stop.
/// Refusing is the honest answer, and the caller reports that the point was
/// not usable rather than moving the photograph. The other end — a blown
/// highlight, where every channel has stopped counting — is refused by the
/// caller before the sample is taken, because only the caller can see the
/// sensor value; see [`crate::operation::CLIP_ONSET`].
const FLOOR: f32 = 1e-4;
/// TRACES: FR-DEV-3
/// Move the graph so that `sample` renders neutral.
///
/// `sample` is linear RGB, as the operation's own gains multiply it — that is,
/// measured with the sampling operation at its defaults. Returns whether the
/// graph was moved: `false` where the chain offers no white point widget, or
/// where the colour has no balance in it to correct.
/// `sample` is the linear triple the operation's own gains multiply — camera
/// RGB with the camera's as-shot balance on, *before* the body's base curve
/// and matrix, and with the sampling operation at its defaults. Not the
/// pixel on the screen: the matrix mixes the channels on the way there, so
/// a colour read after it does not answer to these gains, and a solve over
/// one lands somewhere no sample asked for. Returns whether the graph was
/// moved: `false` where the chain offers no white point widget, or where the
/// colour has no balance in it to correct.
///
/// **Absolute, not relative.** The values written depend on the colour and not
/// on where the sliders happened to be, so sampling the same wall twice lands
+185 -8
View File
@@ -424,6 +424,23 @@ pub enum OutputMode {
/// clamping before a sharpener sees it would draw a hard edge at precisely
/// the luminance a sharpener is most visible at.
LinearWorking,
/// TRACES: FR-MRG-2
/// `rgba32float`, **camera space**: after the lens warp and nothing else.
///
/// What a merge stitches (FR-MRG-2). The shader is the linear tail with
/// no operations, and the caller fills the reserved uniforms neutral —
/// unit white balance, identity matrix, base curve off — so what is
/// stored is the sensor's own numbers, demosaiced and undistorted. Only
/// [`compose_camera_probe`] produces it — for a merge through
/// [`compose_camera_linear`], and for the white balance picker under the
/// edit's own framing — and only `AdjustPass::render_camera_linear`
/// accepts it, so the neutral uniforms cannot be forgotten by a caller
/// that composed it by mistake.
///
/// Thirty-two bits rather than sixteen because the composite is written
/// back as a RAW at the sensor's scale (FR-MRG-3): a 14-bit sensor has
/// 16 384 steps to white and `f16` keeps 2 048 of them in the top octave.
CameraLinear,
}
/// The result of composing a set of operations into one shader.
@@ -475,6 +492,19 @@ pub const BASE_CURVE_UNIFORM_OFFSET: usize = 16;
/// selection in [`compose_full`].
pub const BASE_CURVE_POINTS: usize = 5;
/// Where the highlight desaturation begins: the fraction of the white level
/// above which a photosite is treated as clipped.
///
/// A photosite this close to saturation has stopped counting, so its ratio
/// to its neighbours is not a colour. The generated prologue fades a pixel
/// above this toward a neutral of the same brightness before any operation
/// runs, and the white balance probe refuses to sample one: a blown sky is
/// sensor white, which the as-shot multipliers make magenta, and a solve
/// over that slams tint to its stop. One number, so the two cannot drift
/// apart — a probe that accepted what the shader had already desaturated
/// would be balancing against a pixel the photographer cannot see.
pub const CLIP_ONSET: f32 = 0.985;
/// Where an operation's own uniforms begin in the generated block.
///
/// The base fields, then framing's. Exported because `dr-gpu` writes the
@@ -573,6 +603,92 @@ pub fn compose_full_revealing(
spots: &crate::spot::SpotSet,
warps: &[Box<dyn crate::lens::Warp>],
reveal: Option<&crate::mask::Reveal>,
) -> ComposedShader {
compose_inner(
ops, framing, output, masks, spots, warps, reveal, None, false,
)
}
/// TRACES: FR-MRG-2
/// The camera-space tap: the fused pass with no operations, stopping after
/// the lens warp and storing `rgba32float` ([`OutputMode::CameraLinear`]).
///
/// Takes the warps and a view, because that is all the tap uses of an edit:
/// no crop (a merge wants the whole frame, and crops the composite), no
/// masks, no spots, no operations. `view` is the tile — the fraction of the
/// undistorted frame to render, in `Framing::set_view`'s terms — so that a
/// merge pulls source tiles on demand (FR-MRG-11) rather than a frame that
/// may not fit. The camera profile's uniforms are still declared — the
/// prologue is the same — and the GPU side fills them neutral.
pub fn compose_camera_linear(
warps: &[Box<dyn crate::lens::Warp>],
baseline: dr_types::Orientation,
view: crate::framing::CropRect,
) -> ComposedShader {
let mut framing = Framing::default();
// The file's orientation and nothing of the user's: a merge aligned
// its frames upright (`dr_pano::Gray::oriented`), so its tiles must be
// upright too, and `view` is a fraction of the upright frame.
framing.set_baseline(baseline);
framing.set_view(view);
compose_camera_tap(warps, &framing, false)
}
/// TRACES: FR-DEV-3
/// The same tap under a framing the caller chose: the white balance probe.
///
/// A neutral picked off the canvas has to be measured in the space the
/// white balance gains multiply, and that is camera RGB — the operation
/// runs before the body's matrix, and a probe read after the matrix would
/// be solving the wrong equation on any body whose matrix mixes the
/// channels, which is every body. It also has to be measured at the pixel
/// the canvas is showing, which is why this takes the edit's own framing
/// where a merge passes the file's orientation and a tile.
///
/// **Interpolated whatever the framing says.** The point of rendering a
/// patch is to average what is under it, and the nearest sampling an
/// unrotated frame otherwise gets is a comb: at two source pixels per
/// probe pixel it lands on the same column of any pattern every time, and
/// the average of a thousand samples is then the average of nothing.
pub fn compose_camera_probe(
warps: &[Box<dyn crate::lens::Warp>],
framing: &Framing,
) -> ComposedShader {
compose_camera_tap(warps, framing, true)
}
/// The camera-space tap proper: no operations, `rgba32float`, and the
/// profile uniforms left for the GPU side to fill neutral. `smooth` forces
/// the interpolating sampler; see the two callers for who wants it and why.
fn compose_camera_tap(
warps: &[Box<dyn crate::lens::Warp>],
framing: &Framing,
smooth: bool,
) -> ComposedShader {
compose_inner(
&[],
framing,
ColourSpace::Srgb,
&MaskStack::new(),
&crate::spot::SpotSet::new(),
warps,
None,
Some(OutputMode::CameraLinear),
smooth,
)
}
#[allow(clippy::too_many_arguments)]
fn compose_inner(
ops: &[Box<dyn Operation>],
framing: &Framing,
output: ColourSpace,
masks: &MaskStack,
spots: &crate::spot::SpotSet,
warps: &[Box<dyn crate::lens::Warp>],
reveal: Option<&crate::mask::Reveal>,
forced: Option<OutputMode>,
smooth: bool,
) -> ComposedShader {
// The lens corrections, composed into one coordinate transform. Beside
// `framing` because they are the other half of the same stage: framing
@@ -603,12 +719,18 @@ pub fn compose_full_revealing(
// all: a photograph with a spot on it and no sharpening still has a detail
// stage, and a fused pass that encoded its own output there would quantise
// twice and be bound to a texture of the wrong format.
let output_mode =
//
// `forced` is the one exception, and it is not a caller flag in the
// sense above: `compose_camera_probe` is the only function that passes
// it, with an empty operation list, and the mode it forces has its own
// storage format and its own render entry on the GPU side.
let output_mode = forced.unwrap_or(
if ops.iter().any(|o| o.is_active() && o.detail().is_some()) || !spots.is_neutral() {
OutputMode::LinearWorking
} else {
OutputMode::Encoded
};
},
);
// Whether an operation has taken over the rendering. Decided from the
// operations for the same reason `output_mode` is: a caller that got it
@@ -773,7 +895,10 @@ pub fn compose_full_revealing(
// framing alone — which is what this did before the warps existed — would
// have nearest-neighboured a distortion correction on an unstraightened
// frame, and the aliasing would have looked like a bad profile.
let interpolate = framing.needs_interpolation() || warp.is_active();
// `smooth` is the third reason, and the only one a caller states: the
// white balance probe averages a patch and cannot do that through a
// nearest-neighbour comb (see `compose_camera_probe`).
let interpolate = smooth || framing.needs_interpolation() || warp.is_active();
// Declared ahead of the warp block, which assigns to them. They enter
// equal to `p` so that a chain mixing a splitting warp with a
@@ -788,12 +913,22 @@ pub fn compose_full_revealing(
""
};
// TRACES: FR-MRG-2
// A pixel whose source coordinate leaves the frame — the corners a lens
// correction pulls in — is stored black. For the display that is the
// right picture; for a merge it is a pixel that does not exist and must
// not be averaged in as if it did, so the camera-space tap marks it
// with alpha 0 and the warp reads the alpha as validity.
let void_alpha = match output_mode {
OutputMode::CameraLinear => "0.0",
_ => "1.0",
};
let prologue = format!(
"{}{}{}\n{}",
framing.wgsl_prologue(),
channel_positions,
warp.body,
sample_source(interpolate, warp.splits_channels)
sample_source(interpolate, warp.splits_channels).replace("VOID_ALPHA", void_alpha)
);
let sampler_helper = if interpolate { BILINEAR_HELPER } else { "" };
@@ -827,6 +962,16 @@ pub fn compose_full_revealing(
// would put a hard edge into the very neighbourhood the next pass is
// about to convolve, which is how sharpeners come to draw dark rings
// around specular highlights.
textureStore(output, vec2<i32>(gid.xy), vec4<f32>(c, 1.0));"
.to_string(),
),
OutputMode::CameraLinear => (
"rgba32float",
String::new(),
String::new(),
" // Camera space, for a merge (FR-MRG-2): the sensor's numbers after the
// lens warp, with the profile uniforms filled neutral by the caller so the
// prologue above changed nothing. Not clamped, not encoded, full precision.
textureStore(output, vec2<i32>(gid.xy), vec4<f32>(c, 1.0));"
.to_string(),
),
@@ -908,6 +1053,9 @@ pub fn compose_full_revealing(
.to_string()
};
// Formatted with Rust's `Display` so the shader reads the same threshold
// the probe checks against; see `CLIP_ONSET`.
let clip_onset = CLIP_ONSET;
let source = format!(
"// GENERATED — do not edit.
//
@@ -978,7 +1126,7 @@ fn main(@builtin(global_invocation_id) gid: vec3<u32>) {{
// A photosite at its white level carries no colour information — every
// channel simply stopped counting — so the balance below must not be
// allowed to tint it.
let clipped = smoothstep(0.985, 1.0, max(c.r, max(c.g, c.b)));
let clipped = smoothstep({clip_onset}, 1.0, max(c.r, max(c.g, c.b)));
c = c * u.as_shot_wb.rgb;
@@ -1158,7 +1306,7 @@ pub(crate) fn sample_source(interpolate: bool, splits_channels: bool) -> &'stati
// remove. `sample_bilinear` clamps its own texel indices, so red and blue
// land on the edge pixel rather than out of bounds.
if (any(uv_src < vec2<f32>(0.0)) || any(uv_src >= vec2<f32>(1.0))) {
textureStore(output, vec2<i32>(gid.xy), vec4<f32>(0.0, 0.0, 0.0, 1.0));
textureStore(output, vec2<i32>(gid.xy), vec4<f32>(0.0, 0.0, 0.0, VOID_ALPHA));
return;
}
@@ -1186,7 +1334,7 @@ pub(crate) fn sample_source(interpolate: bool, splits_channels: bool) -> &'stati
// corners; render them black rather than clamping, which would smear an
// edge pixel across them.
if (any(uv_src < vec2<f32>(0.0)) || any(uv_src >= vec2<f32>(1.0))) {
textureStore(output, vec2<i32>(gid.xy), vec4<f32>(0.0, 0.0, 0.0, 1.0));
textureStore(output, vec2<i32>(gid.xy), vec4<f32>(0.0, 0.0, 0.0, VOID_ALPHA));
return;
}
@@ -1229,7 +1377,7 @@ pub(crate) fn sample_source(interpolate: bool, splits_channels: bool) -> &'stati
// transformed at all. Render it black rather than clamping, which would
// smear an edge pixel across the gap.
if (any(uv_src < vec2<f32>(0.0)) || any(uv_src >= vec2<f32>(1.0))) {
textureStore(output, vec2<i32>(gid.xy), vec4<f32>(0.0, 0.0, 0.0, 1.0));
textureStore(output, vec2<i32>(gid.xy), vec4<f32>(0.0, 0.0, 0.0, VOID_ALPHA));
return;
}
@@ -2030,6 +2178,35 @@ mod tests {
assert!(convert < clip, "the clip must come after the conversion");
}
#[test]
fn the_camera_space_tap_marks_a_pixel_off_the_sensor_with_alpha_zero() {
// TRACES: FR-MRG-2
// A lens correction pulls the corners in, and the pixels it leaves
// behind have no source. The display stores them black and opaque;
// the tap stores them black and *transparent*, so a merge can tell
// "nothing here" from "black here" and never averages the fringe in.
let tap = compose_camera_linear(
&[],
dr_types::Orientation::default(),
crate::framing::CropRect::default(),
)
.source;
assert!(
tap.contains("vec4<f32>(0.0, 0.0, 0.0, 0.0)"),
"the tap must store alpha 0 off the sensor:\n{tap}"
);
assert!(
!tap.contains("VOID_ALPHA"),
"the placeholder must be substituted:\n{tap}"
);
let display = compose(&[]).source;
assert!(
!display.contains("vec4<f32>(0.0, 0.0, 0.0, 0.0)"),
"the display keeps its opaque black:\n{display}"
);
assert!(!display.contains("VOID_ALPHA"));
}
#[test]
fn the_generated_matrix_is_the_one_the_profile_writer_will_use() {
// The shader encodes the pixels and `dr-export` describes them, from
+48 -1
View File
@@ -110,6 +110,21 @@ pub struct Sidecar {
///
/// Preserved so a older build round-trips a newer file without loss.
unknown_blocks: Vec<String>,
/// TRACES: FR-MRG-6
/// Provenance: the sources a composite was merged from, in order, as
/// the library names them. Empty for a photograph the camera took.
///
/// Top-level rather than per version because it is a fact about the
/// file, not about an edit — every version of a panorama is a version
/// of the same twelve frames. Written as one `derived_from = …` line per
/// source before the first version block, where a build that predates
/// the field keeps the lines as unknown and writes them back untouched.
pub derived_from: Vec<String>,
/// TRACES: FR-MRG-6
/// How the composite was made: `panorama cylindrical 49.7mm 12 frames`.
/// Free text for a panel; the parameters that matter to a re-merge are
/// the sources and the projection, and both are legible in it.
pub merge: Option<String>,
}
/// TRACES: FR-DEV-3f
@@ -823,6 +838,13 @@ impl Sidecar {
/// caller may compare content to decide whether an upload is needed.
pub fn to_text(&self) -> String {
let mut out = format!("drsc {FORMAT_VERSION}\n");
// TRACES: FR-MRG-6
for source in &self.derived_from {
let _ = writeln!(out, "derived_from = {source}");
}
if let Some(merge) = &self.merge {
let _ = writeln!(out, "merge = {merge}");
}
for block in &self.unknown_blocks {
let _ = writeln!(out, "{block}");
}
@@ -1008,7 +1030,12 @@ impl Sidecar {
}
let Some(version) = current.as_mut() else {
sidecar.unknown_blocks.push(line.to_string());
// TRACES: FR-MRG-6
match key {
"derived_from" => sidecar.derived_from.push(value.to_string()),
"merge" => sidecar.merge = Some(value.to_string()),
_ => sidecar.unknown_blocks.push(line.to_string()),
}
continue;
};
@@ -2209,6 +2236,26 @@ mod tests {
/// the claim is about *those bytes*: a sidecar generated by this build
/// would agree with this build by construction, and would go on agreeing
/// with it through a rename that broke every file on disk.
#[test]
fn provenance_round_trips_at_the_top_level() {
// TRACES: FR-MRG-6
let text = "drsc 1\nderived_from = 2025/_MG_8320.CR2\nderived_from = 2025/_MG_8321.CR2\n\
merge = panorama cylindrical 49.7mm 2 frames\n\n[version u1]\nname = Default\n\
revision = 1\nmodified = 0\n";
let sidecar = Sidecar::parse(text).expect("parses");
assert_eq!(
sidecar.derived_from,
vec!["2025/_MG_8320.CR2", "2025/_MG_8321.CR2"]
);
assert_eq!(
sidecar.merge.as_deref(),
Some("panorama cylindrical 49.7mm 2 frames")
);
let out = sidecar.to_text();
assert!(out.starts_with("drsc 1\nderived_from = 2025/_MG_8320.CR2\n"));
assert_eq!(Sidecar::parse(&out).expect("re-parses"), sidecar);
}
#[test]
fn a_sidecar_from_before_the_channel_curves_still_names_the_master() {
let text = "drsc 1\n\n[version u1]\nname = Default\nrevision = 4\nmodified = 9\n\
+8 -4
View File
@@ -11,10 +11,11 @@ build = "build.rs"
thiserror.workspace = true
log.workspace = true
# Inference. `ort` is the API; **tract is the engine** — see the workspace
# manifest for why the C++ ONNX Runtime is not linked here.
# Inference. `ort` is the API; **what runs it is `dr-inference-engine`'s
# business** — tract, or an ONNX Runtime the app found on disk, on whichever
# provider the device has (docs/inference.md). This crate never names either.
ort = { workspace = true, optional = true }
ort-tract = { workspace = true, optional = true }
dr-inference-engine = { workspace = true, optional = true }
ndarray = { workspace = true, optional = true }
[dev-dependencies]
@@ -23,6 +24,9 @@ ndarray = { workspace = true, optional = true }
# tree for embedded previews.
zune-jpeg.workspace = true
env_logger.workspace = true
# The probe example drives `ort` directly to print the raw load error, and
# asks the engine for a runtime by name rather than naming one itself.
dr-inference-engine.workspace = true
[features]
# On by default: a local adjustment that cannot select a subject is half the
@@ -35,7 +39,7 @@ default = ["semantic", "embedded-model"]
# Separable because the watershed half is genuinely independent of it: with
# this off, `dr-segment` is a pure-CPU graph algorithm crate with no model to
# carry, which is what the headless hierarchy tests want.
semantic = ["dep:ort", "dep:ort-tract", "dep:ndarray"]
semantic = ["dep:ort", "dep:dr-inference-engine", "dep:ndarray"]
# Compile the weights into the binary.
#
+87
View File
@@ -0,0 +1,87 @@
//! TRACES: S15 | FR-MRG-8
//! Load an ONNX file through the application's own runtime and run it once.
//!
//! ```sh
//! cargo run -p dr-segment --example onnx_probe --release -- model.onnx [1x1x768x1024]
//! ```
//!
//! The F6 check, as a tool. tract's operator coverage is the thing that can
//! sink a model choice — `segmentation.md` records a dynamic-shape export it
//! could not parse at all — and the only way to know is to load the file
//! under the backend the app ships and see. This does that for any model,
//! before any Rust is written against its outputs: it prints the declared
//! inputs and outputs, runs zeros through at the given shape, and times it.
//!
//! Written for S15.2 (XFeat), kept because the next model will need it too.
use std::time::Instant;
fn main() {
let mut args = std::env::args().skip(1);
let Some(path) = args.next() else {
eprintln!("usage: onnx_probe <model.onnx> [NxCxHxW]");
std::process::exit(2);
};
let shape: Vec<usize> = args
.next()
.map(|s| {
s.split('x')
.map(|d| d.parse().expect("dimension"))
.collect()
})
.unwrap_or_else(|| vec![1, 1, 768, 1024]);
let bytes = std::fs::read(&path).expect("read model");
println!("{path}: {} bytes", bytes.len());
dr_inference_engine::ensure_runtime();
let t = Instant::now();
let mut session =
match ort::session::Session::builder().and_then(|mut b| b.commit_from_memory(&bytes)) {
Ok(s) => s,
Err(e) => {
println!("FAIL load: {e}");
std::process::exit(1);
}
};
println!("ok loaded in {:?}", t.elapsed());
for i in session.inputs().iter() {
println!(" input {} {:?}", i.name(), i.dtype());
}
for o in session.outputs().iter() {
println!(" output {} {:?}", o.name(), o.dtype());
}
let n: usize = shape.iter().product();
// Twice: the first run pays for tract's optimisation and plan, the second
// is the number that matters. The tensor is built per run rather than
// cloned — `Tensor::clone` under the tract backend panics.
for pass in 1..=2 {
let input =
ndarray::Array::from_shape_vec(ndarray::IxDyn(&shape), vec![0.0f32; n]).expect("shape");
let tensor = ort::value::Tensor::from_array(input).expect("tensor");
let t = Instant::now();
let outputs = match session.run(ort::inputs![tensor]) {
Ok(o) => o,
Err(e) => {
println!("FAIL run: {e}");
std::process::exit(1);
}
};
println!("ok run {pass} in {:?}", t.elapsed());
if pass == 2 {
for i in 0..outputs.len() {
match outputs[i].try_extract_tensor::<f32>() {
Ok((shape, data)) => {
let (lo, hi) = data
.iter()
.fold((f32::MAX, f32::MIN), |(lo, hi), &v| (lo.min(v), hi.max(v)));
println!(" output {i}: shape {shape:?}, range {lo:.4}..{hi:.4}");
}
Err(e) => println!(" output {i}: not f32 ({e})"),
}
}
}
}
}
+13
View File
@@ -1,3 +1,4 @@
//! TRACES: FR-DEV-3i
//! Region segmentation for local masking (S15, docs/segmentation.md).
//!
//! Local adjustments need to know where the image's regions are before they
@@ -70,6 +71,8 @@ pub use refine::{
};
#[cfg(feature = "semantic")]
pub use scene::{Category, Scene, SceneModel};
#[cfg(feature = "embedded-model")]
pub use semantic::embedded_model_bytes;
#[cfg(feature = "semantic")]
pub use semantic::{Instance, SemanticModel, SemanticOptions, Tiling};
@@ -97,3 +100,13 @@ pub enum SegmentError {
#[error("category descriptor: {0}")]
CategoryDescriptor(String),
}
#[cfg(feature = "semantic")]
impl From<dr_inference_engine::Error> for SegmentError {
fn from(e: dr_inference_engine::Error) -> Self {
match e {
dr_inference_engine::Error::Inference(e) => SegmentError::Inference(e),
dr_inference_engine::Error::Io(e) => SegmentError::ModelRead(e),
}
}
}
+11 -15
View File
@@ -59,7 +59,7 @@ use ndarray::ArrayView3;
#[cfg(test)]
use crate::semantic::INPUT_EDGE;
use crate::semantic::{install_backend, Letterbox, Window};
use crate::semantic::{Letterbox, Window};
use crate::SegmentError;
/// Classes in the ADE20K vocabulary the scene model was trained on.
@@ -84,7 +84,7 @@ pub struct Category {
/// The scene model, and the categories it has been told to report.
pub struct SceneModel {
session: ort::session::Session,
session: dr_inference_engine::Model,
categories: Vec<Category>,
}
@@ -132,12 +132,12 @@ impl SceneModel {
}
pub fn from_bytes(bytes: &[u8], categories: Vec<Category>) -> Result<Self, SegmentError> {
install_backend();
let session = ort::session::Session::builder()
.map_err(SegmentError::Inference)?
.commit_from_memory(bytes)
.map_err(SegmentError::Inference)?;
// f32, as for `SemanticModel`; see there.
let session = dr_inference_engine::open(
dr_inference_engine::Role::Scene,
dr_inference_engine::Form::F32,
bytes,
)?;
Ok(Self {
session,
@@ -170,13 +170,9 @@ impl SceneModel {
});
}
// Split the borrow: `run` needs the session mutably while
// `marginalise` needs the categories, and going through `self` for
// both at once is what the borrow checker objects to.
let Self {
session,
categories,
} = self;
let categories = &self.categories;
let acquired = self.session.acquire()?;
let mut session = acquired.lock();
let window = Window {
x: 0.0,
+19 -24
View File
@@ -194,7 +194,7 @@ impl Instance {
/// Holds an `ort` session, so it is neither `Clone` nor cheap to build —
/// construct once and keep it. Loading is ~50 ms.
pub struct SemanticModel {
session: ort::session::Session,
session: dr_inference_engine::Model,
classes: Vec<Arc<str>>,
}
@@ -208,6 +208,13 @@ const EMBEDDED_MODEL: &[u8] = include_bytes!("../../../models/segment/yolo26n-se
#[cfg(feature = "embedded-model")]
const EMBEDDED_CLASSES: &str = include_str!("../../../models/segment/yolo26n-seg.classes.json");
/// The bytes of the model that ships with this crate, for whoever compiles
/// engines ahead of the first request (docs/inference.md §6).
#[cfg(feature = "embedded-model")]
pub fn embedded_model_bytes() -> &'static [u8] {
EMBEDDED_MODEL
}
impl SemanticModel {
/// Load the model that ships with this crate.
#[cfg(feature = "embedded-model")]
@@ -229,15 +236,14 @@ impl SemanticModel {
}
pub fn from_bytes(bytes: &[u8], classes: Vec<Arc<str>>) -> Result<Self, SegmentError> {
// Idempotent, and it must happen before any other `ort` call: with
// `alternative-backend` there is no linked runtime to fall back on, so
// an un-set API is a panic rather than a slow path.
install_backend();
let session = ort::session::Session::builder()
.map_err(SegmentError::Inference)?
.commit_from_memory(bytes)
.map_err(SegmentError::Inference)?;
// The f32 graph on whatever the device's backend is. An int8 form
// for the Hexagon waits on docs/inference.md §10 M7 — the mask
// boundary has to be measured before it moves.
let session = dr_inference_engine::open(
dr_inference_engine::Role::Segmenter,
dr_inference_engine::Form::F32,
bytes,
)?;
Ok(Self { session, classes })
}
@@ -332,8 +338,9 @@ impl SemanticModel {
let letterbox = Letterbox::fit(window.w, window.h);
let input = letterbox.sample(rgb, width, height, window);
let outputs = self
.session
let acquired = self.session.acquire()?;
let mut session = acquired.lock();
let outputs = session
.run(ort::inputs![
ort::value::Tensor::from_array(input).map_err(SegmentError::Inference)?
])
@@ -674,18 +681,6 @@ fn steps(extent: f32, edge: f32, stride: f32) -> usize {
}
}
/// Point `ort` at tract, exactly once per process.
pub(crate) fn install_backend() {
use std::sync::Once;
static ONCE: Once = Once::new();
ONCE.call_once(|| {
// Returns false if an API was already installed, which is not an error
// — it means something else got here first, and there is only one
// backend compiled in for it to have chosen.
let _ = ort::set_api(ort_tract::api());
});
}
/// Read the class list written beside the model by `tools/export-seg-model.sh`.
///
/// A deliberately small hand-rolled reader for a flat array of strings, rather
+30 -3
View File
@@ -47,6 +47,20 @@ pub struct NextcloudBackend {
/// `/remote.php/dav/files/<user>/` — the prefix stripped from hrefs.
dav_base: String,
caps: Capabilities,
/// Collections this backend has seen exist, so [`create_dir`] asks the
/// server about each one once.
///
/// Every `MOVE` guarantees its destination's parent, and did so with a
/// `MKCOL` for each ancestor down from the account root — for a trash
/// folder three levels deep that was three round trips of `405 Method
/// Not Allowed` before the one request that moved anything, on every
/// image of a batch. A backend lives for one job (`dr_ui::remote::
/// connect` builds one per worker), so a folder deleted by another
/// client mid-job is the one case this can get wrong, and it is reported
/// as the `409` the `MOVE` then earns rather than hidden.
///
/// [`create_dir`]: RemoteBackend::create_dir
known_dirs: std::sync::Mutex<std::collections::HashSet<String>>,
}
impl NextcloudBackend {
@@ -63,6 +77,7 @@ impl NextcloudBackend {
login: creds.login_name.clone(),
password: creds.app_password.clone(),
dav_base,
known_dirs: Default::default(),
caps: Capabilities {
// The property that makes a no-op sync one request (ARCH §8.1).
change_detection: ChangeDetection::PropagatingEtags,
@@ -567,6 +582,16 @@ impl RemoteBackend for NextcloudBackend {
chain.reverse();
for dir in chain {
// Asked once per backend — see `known_dirs`. The lock is held
// across no await: it is taken to look, and again to record.
let known = self
.known_dirs
.lock()
.map(|k| k.contains(dir.as_str()))
.unwrap_or(false);
if known {
continue;
}
let url = self.url_for(&dir);
let resp = self
.client
@@ -581,10 +606,12 @@ impl RemoteBackend for NextcloudBackend {
// 405 is "already a collection here", which is exactly what the
// caller wanted. Anything else is reported.
if resp.status() == reqwest::StatusCode::METHOD_NOT_ALLOWED {
continue;
if resp.status() != reqwest::StatusCode::METHOD_NOT_ALLOWED {
map_status(resp.status(), &url)?;
}
if let Ok(mut k) = self.known_dirs.lock() {
k.insert(dir.as_str().to_string());
}
map_status(resp.status(), &url)?;
}
Ok(())
}
+14
View File
@@ -127,6 +127,19 @@ pub struct Account {
#[serde(default)]
pub root: String,
/// Whether [`root`](Self::root) has been chosen at all.
///
/// An empty `root` is two different things: nothing picked yet, and the
/// endpoint itself picked on purpose — a user who keeps everything at
/// the top level, or a folder library, which is its own root. The string
/// cannot tell them apart, and reading empty as "not chosen" meant the
/// top level could be confirmed in the picker and still not open. So the
/// fact is recorded separately. Defaulted, so an account written before
/// it existed loads as it always did: a non-empty root is chosen by
/// virtue of being there, and an empty one asks again.
#[serde(default)]
pub root_chosen: bool,
/// Which formats the scan looks for (the tick-boxes).
#[serde(default)]
pub formats: Vec<String>,
@@ -149,6 +162,7 @@ impl Account {
login: String::new(),
user_id: String::new(),
root: String::new(),
root_chosen: false,
formats: Vec::new(),
last_scan: None,
}
+80
View File
@@ -240,6 +240,23 @@ impl ThumbStore {
.collect()
}
/// Every file id stored at one size, read from the index in one query.
///
/// For a pass that asks about thousands of images at once — the face
/// audit, the repair lists. Each [`contains`](Self::contains) is a
/// prepared statement and a b-tree probe; asked ten thousand times over a
/// scan it costs more than the scan does, where one walk of the index is
/// a few milliseconds and answers every row.
pub fn held(&self, size: ThumbSize) -> Result<std::collections::HashSet<u64>, ThumbError> {
let mut stmt = self
.index
.prepare("SELECT file_id FROM entries WHERE size = ?1")?;
let ids = stmt
.query_map([size as i64], |r| r.get::<_, i64>(0))?
.collect::<Result<Vec<_>, _>>()?;
Ok(ids.into_iter().map(|id| id as u64).collect())
}
/// Store a thumbnail, opening a new shard if the active one is full.
///
/// Re-storing an existing id overwrites in place rather than migrating it
@@ -481,6 +498,30 @@ impl ThumbStore {
self.dir.join(format!("shard-{shard:04}.sqlite"))
}
/// Write a coherent copy of one shard to `dest`, ready to upload.
///
/// Not a file copy. Every shard is in WAL mode and every `put` opens its
/// own connection, so while thumbnails are being generated on several
/// threads at once — which is exactly when the first sync pass runs —
/// there is nearly always a connection open and the log is never
/// checkpointed. The main file then holds whatever the *last* quiet
/// moment left in it, which for a shard created seconds ago is nothing:
/// zero bytes, the schema still in the log. Reading it uploaded an empty
/// file, and every other device merging it failed with "no such table:
/// thumbs". The backup API serialises against writers and copies the
/// database as it is, log included.
pub fn snapshot_shard(&self, shard: u32, dest: &Path) -> Result<(), ThumbError> {
let source = self.open_shard(shard, false)?;
let _ = std::fs::remove_file(dest);
let mut out = Connection::open(dest)?;
let backup = rusqlite::backup::Backup::new(&source, &mut out)?;
// rusqlite asserts a positive page count where SQLite would take -1
// for "everything"; a shard is capped well under this many pages.
backup.run_to_completion(i32::MAX, std::time::Duration::ZERO, None)?;
drop(backup);
Ok(())
}
pub fn index_path(&self) -> PathBuf {
self.dir.join("index.sqlite")
}
@@ -726,6 +767,45 @@ mod tests {
}
}
#[test]
fn a_snapshot_carries_what_the_shard_file_does_not_yet() {
// A thumbnail worker holding the shard open keeps the log from being
// checkpointed; the file on disk is then not the database. The
// upload used to read that file.
let (mut s, _d) = store();
s.put(1, ThumbSize::Grid, &thumb(1024)).unwrap();
let path = s.shard_path(0);
let worker = Connection::open(&path).unwrap();
worker.pragma_update(None, "journal_mode", "WAL").unwrap();
s.put(2, ThumbSize::Grid, &thumb(2048)).unwrap();
s.put(3, ThumbSize::Grid, &thumb(2048)).unwrap();
// What a byte-for-byte reader sees is at most what the last
// checkpoint left; the log is the part a copy misses.
let copy = _d.join("copied.sqlite");
std::fs::copy(&path, &copy).unwrap();
let file_rows = Connection::open(&copy)
.ok()
.and_then(|c| {
c.query_row("SELECT count(*) FROM thumbs", [], |r| r.get::<_, i64>(0))
.ok()
})
.unwrap_or(0);
let snap = _d.join("upload.sqlite");
s.snapshot_shard(0, &snap).unwrap();
let snapshot = Connection::open(&snap).unwrap();
let rows: i64 = snapshot
.query_row("SELECT count(*) FROM thumbs", [], |r| r.get(0))
.unwrap();
assert_eq!(rows, 3, "the snapshot is the whole shard");
assert!(
file_rows < 3,
"the file alone lagged ({file_rows} rows), which is what the snapshot exists for"
);
drop(worker);
}
#[test]
fn a_forgotten_thumbnail_is_no_longer_served() {
// The point of the whole method: a purged photograph must not keep a
+5
View File
@@ -126,6 +126,11 @@ pub struct StoredFilter {
/// does not derive serde — and "all of them" is the only thing the second
/// variant means.
pub people_all: bool,
/// TRACES: FR-CULL-8a | FR-CULL-13
/// Whether the grid was narrowed to photographs with nobody blinking.
/// Travels: it is a narrowing like `local_only`, and a record without it
/// — from a build before it existed — reads as off.
pub eyes_open: bool,
}
/// Where the photographer was, at the moment they were there.
+177 -14
View File
@@ -186,17 +186,27 @@ pub struct FaceSettings {
/// and a tablet on a battery want different answers — so it is a setting,
/// per device, like the rest of this file.
///
/// # A detector is half of a model id
/// # A detector is half of a model id, and the half that does not split
/// # the library
///
/// Every face row, run marker, sync shard and calibration is keyed by
/// `faces.model_id` (catalog.md §10.1), and the schema's whole reason for
/// carrying that column is that *a model change is a new id and a re-index*
/// rather than a silent change under existing data. A detector change is a
/// model change: it decides which faces exist and where the landmarks that
/// align them land. So each variant names its own pipeline, and choosing
/// another one puts every image back in the queue and shows the People screen
/// for the new pipeline — empty until the sweep has run, with confirmed names
/// carried across by `record_detections`' box overlap.
/// Every face row, run marker, sync shard and calibration carries
/// `faces.model_id` (catalog.md §10.1), spelled `detector+embedder`, so which
/// pipeline produced a face is always on record. But every reader of "the
/// faces" keys on the *embedder* half (`dr_catalog::faces::embedder_of`):
/// the embedder is what makes two vectors comparable, and the detector only
/// decides where the boxes are. So the three variants here are one
/// population, and choosing another one empties nothing — the People screen,
/// the clustering and the sync all go on over every face already found.
/// What a stronger choice does is queue the images a weaker one indexed for
/// re-detection, after the ones nothing has indexed ([`Self::supersedes`]),
/// with names carried across by `record_detections`' box and embedding
/// matching.
///
/// The first version of this setting keyed everything on the full id, and
/// choosing Thorough emptied both devices' People screens until a whole-
/// library re-index had run on each — and, worse, stranded every name
/// confirmed on one device, because the other held the same faces under a
/// different id and the merge would not match them.
///
/// The first variant's id is the bare embedder name, because that is the id
/// every library indexed before this setting existed was written under;
@@ -251,6 +261,64 @@ impl FaceDetector {
}
}
/// The id when the detector runs in its int8 form (docs/inference.md §7).
///
/// A different detector: it finds a different set of faces, so it is a
/// different population of detections. The embedder half is unchanged,
/// because the embedder never runs in int8, and `embedder_of` keeps the
/// two spellings' vectors in one space.
pub fn model_id_int8(self) -> &'static str {
match self {
FaceDetector::Scrfd500m => "scrfd_500m_i8+w600k_mbf",
FaceDetector::Scrfd2_5g => "scrfd_2.5g_i8+w600k_mbf",
FaceDetector::Scrfd10g => "scrfd_10g_i8+w600k_mbf",
}
}
/// Both ids this detector writes under — the f32 form and the int8 one —
/// for a question that is about the detector and not about which form
/// of it a device happened to run: "has the chosen detector been over
/// this image", asked by a re-index that must not ping-pong between a
/// desktop that runs it in f32 and a tablet that runs it on the Hexagon.
pub fn model_ids(self) -> [&'static str; 2] {
[self.model_id(), self.model_id_int8()]
}
/// The detector that writes under a pipeline id, if it is one of these.
///
/// The inverse of [`Self::model_ids`] -- either spelling. `None` for an
/// id from another embedder or a build this one does not know, which a
/// caller treats as "cannot rank" rather than as weaker than anything.
pub fn for_model_id(model_id: &str) -> Option<FaceDetector> {
FaceDetector::ALL
.into_iter()
.find(|d| d.model_ids().contains(&model_id))
}
/// Whether this detector finds more than `other` does — the measured
/// order of §12.3, which is also the order of [`Self::ALL`].
pub fn outranks(self, other: FaceDetector) -> bool {
let rank = |d: FaceDetector| FaceDetector::ALL.iter().position(|x| *x == d);
rank(self) > rank(other)
}
/// The pipeline ids this detector is worth re-running over.
///
/// Every variant shares one embedder, so a library indexed under any of
/// them is one population (`dr_catalog::faces::embedder_of`) and a
/// detector change empties nothing. What a stronger detector *adds* is
/// the faces a weaker one missed, so a sweep re-detects the images a
/// weaker one indexed — after the ones nothing has indexed — and never
/// the other way round: a tablet set to Fast keeps the desktop's
/// Thorough faces rather than replacing them with fewer.
pub fn supersedes(self) -> &'static [&'static str] {
match self {
FaceDetector::Scrfd500m => &[],
FaceDetector::Scrfd2_5g => &["w600k_mbf"],
FaceDetector::Scrfd10g => &["w600k_mbf", "scrfd_2.5g+w600k_mbf"],
}
}
/// What the picker calls it.
pub fn label(self) -> &'static str {
match self {
@@ -508,6 +576,28 @@ pub struct CacheSettings {
/// no bandwidth and saves the whole transfer next time. Off is for metered
/// or small-disk devices, where the user would rather re-fetch than store.
pub keep_opened_originals: bool,
/// How many photographs either side of the open one are fetched into the
/// cache ahead of being asked for, so a step along the roll is a disk
/// read rather than a download. Zero fetches nothing ahead.
///
/// Each side, so the total is twice this; and closest first, working
/// outwards, so a small number still covers the step most likely to be
/// taken next. Bounded by [`Self::AHEAD_CHOICES`] because every unit is a
/// whole RAW file: 10 each side is a few hundred megabytes per open,
/// which a wired desktop shrugs at and a phone on a hotel connection does
/// not. Moot while `keep_opened_originals` is off — a fetch the cache
/// would discard on arrival is not made.
pub fetch_ahead: u32,
}
impl CacheSettings {
/// The look-ahead depths the settings page offers, each side.
///
/// Snapped to, not clamped, for the reason `LibrarySettings::BAR_CHOICES`
/// is: the page lights the chip that matches, and a number it does not
/// offer would leave every chip dark.
pub const AHEAD_CHOICES: [u32; 5] = [0, 2, 5, 10, 20];
}
/// 8 GB of passively cached originals — roughly 250 full-frame RAWs.
@@ -532,6 +622,10 @@ impl Default for CacheSettings {
original_budget_bytes: Some(DEFAULT_ORIGINAL_BUDGET_BYTES),
thumbnail_budget_bytes: Some(DEFAULT_THUMBNAIL_BUDGET_BYTES),
keep_opened_originals: true,
// Enough that the next few steps in either direction are already
// here by the time they are taken, without a click on one frame
// committing a phone to half a gigabyte.
fetch_ahead: 5,
}
}
}
@@ -791,9 +885,14 @@ impl ExportSettings {
///
/// The library root has to read as a place rather than as a blank field,
/// or confirming the picker where it opens looks like it did nothing.
///
/// An empty device folder used to read "Ask each time", which nothing
/// does: no platform asks, and an export made with the field blank is
/// refused with "no export folder is set". The label now says what will
/// happen rather than what was once meant to.
pub fn destination_label(&self) -> &str {
match self.target {
ExportTarget::Device if self.destination.trim().is_empty() => "Ask each time",
ExportTarget::Device if self.destination.trim().is_empty() => "Not set",
ExportTarget::Device => &self.destination,
ExportTarget::Remote if self.remote_destination.trim().is_empty() => "Library root",
ExportTarget::Remote => &self.remote_destination,
@@ -1175,6 +1274,15 @@ impl Settings {
.unwrap_or(LibrarySettings::default().timeline_bars);
}
// The same snap, for the same page.
if !CacheSettings::AHEAD_CHOICES.contains(&self.cache.fetch_ahead) {
let wanted = self.cache.fetch_ahead;
self.cache.fetch_ahead = CacheSettings::AHEAD_CHOICES
.into_iter()
.min_by_key(|n| n.abs_diff(wanted))
.unwrap_or(CacheSettings::default().fetch_ahead);
}
// A zero-pixel or zero-percent export produces no image. Nudged to the
// smallest thing that does, rather than back to the default: the user
// clearly wanted "small", and silently restoring 2048 would ignore
@@ -1410,6 +1518,10 @@ mod tests {
Some(DEFAULT_THUMBNAIL_BUDGET_BYTES)
);
assert!(cache.keep_opened_originals);
assert!(
CacheSettings::AHEAD_CHOICES.contains(&cache.fetch_ahead),
"the default look-ahead must be one the page can light"
);
}
#[test]
@@ -1514,14 +1626,15 @@ mod tests {
}
#[test]
fn an_empty_device_destination_still_means_ask() {
fn an_empty_device_destination_is_not_set_and_says_so() {
// The asymmetry is deliberate: a filesystem has no folder worth
// assuming, so empty there is a question rather than an answer.
// assuming, so empty there is a gap rather than an answer — and the
// label must not promise a question nobody will be asked.
let mut s = Settings::default();
s.export.target = ExportTarget::Device;
s.export.destination = String::new();
assert!(!s.export.destination_is_set());
assert_eq!(s.export.destination_label(), "Ask each time");
assert_eq!(s.export.destination_label(), "Not set");
}
#[test]
@@ -1640,9 +1753,41 @@ mod tests {
assert_eq!(s.faces, FaceSettings::default());
}
#[test]
fn a_detectors_two_spellings_share_its_embedder_and_nothing_else() {
for d in FaceDetector::ALL {
let [f32_id, int8_id] = d.model_ids();
assert_eq!(f32_id, d.model_id());
assert_eq!(int8_id, d.model_id_int8());
assert_ne!(f32_id, int8_id);
assert_eq!(f32_id.rsplit('+').next(), int8_id.rsplit('+').next());
}
}
/// The detector every existing library was indexed with must keep the id
/// those libraries were written under, or an upgrade would report every
/// one of them un-indexed.
#[test]
fn detectors_rank_in_the_measured_order_and_only_supersede_downwards() {
use FaceDetector::*;
assert!(Scrfd10g.outranks(Scrfd2_5g));
assert!(Scrfd2_5g.outranks(Scrfd500m));
assert!(!Scrfd500m.outranks(Scrfd10g));
assert!(!Scrfd10g.outranks(Scrfd10g));
for d in FaceDetector::ALL {
for weaker in d.supersedes() {
let w = FaceDetector::for_model_id(weaker).expect(weaker);
assert!(
d.outranks(w),
"{d:?} lists {weaker} but does not outrank it"
);
}
assert_eq!(FaceDetector::for_model_id(d.model_id()), Some(d));
assert_eq!(FaceDetector::for_model_id(d.model_id_int8()), Some(d));
}
assert_eq!(FaceDetector::for_model_id("scrfd_10g+other"), None);
}
#[test]
fn the_default_detector_keeps_the_legacy_model_id() {
assert_eq!(FaceDetector::default(), FaceDetector::Scrfd500m);
@@ -1740,6 +1885,24 @@ mod tests {
}
}
#[test]
fn sanitise_snaps_a_hand_edited_look_ahead_to_an_offered_one() {
let mut s = Settings::default();
s.cache.fetch_ahead = 7;
s.sanitise();
assert_eq!(s.cache.fetch_ahead, 5);
s.cache.fetch_ahead = 100;
s.sanitise();
assert_eq!(s.cache.fetch_ahead, 20);
for n in CacheSettings::AHEAD_CHOICES {
s.cache.fetch_ahead = n;
s.sanitise();
assert_eq!(s.cache.fetch_ahead, n, "an offered depth is left alone");
}
}
#[test]
fn sanitise_rescues_a_zero_dimension() {
let mut s = Settings::default();
+25 -3
View File
@@ -17,6 +17,8 @@
# JNILIBS where cargo-ndk wrote the .so (default: $TARGET_DIR/jniLibs)
# OUT output directory (default: $TARGET_DIR/apk)
# KEYSTORE signing keystore (default: $TARGET_DIR/debug.keystore)
# RUNTIME_DIR the inference runtime (default: $TARGET_DIR/runtime,
# fetched by tools/fetch-android-runtime.sh)
# ABI Android ABI (default: arm64-v8a)
# RUST_TARGET Rust target triple (default: aarch64-linux-android)
#
@@ -43,6 +45,7 @@ TARGET_DIR="$(cd "${TARGET_DIR}" && pwd)"
JNILIBS="${JNILIBS:-${TARGET_DIR}/jniLibs}"
OUT="${OUT:-${TARGET_DIR}/apk}"
KEYSTORE="${KEYSTORE:-${TARGET_DIR}/debug.keystore}"
RUNTIME_DIR="${RUNTIME_DIR:-${TARGET_DIR}/runtime}"
# Release signing is selected by supplying a password, not by a flag, so there
# is no way to ask for a release build and silently get a debug one.
@@ -255,6 +258,25 @@ fi
cp "${SO}" "${OUT}/staging/lib/${ABI}/libdarkroom.so"
cp "${DEX}" "${OUT}/staging/classes.dex"
# The inference runtime (docs/inference.md §3): ONNX Runtime and Qualcomm's
# Hexagon backend, beside libdarkroom.so so the app finds them in its own
# native library directory. The build links none of it — the app dlopens
# `libonnxruntime.so` at launch and runs on tract if it is not there — so an
# APK without these is a slower app, not a broken one, and `RUNTIME_DIR=none`
# builds exactly that. 174 MB for the default set; the script says which
# Hexagon generations that buys.
if [[ "${RUNTIME_DIR}" != "none" ]]; then
if [[ ! -f "${RUNTIME_DIR}/lib/libonnxruntime.so" ]]; then
"${REPO}/tools/fetch-android-runtime.sh" "${RUNTIME_DIR}"
fi
cp "${RUNTIME_DIR}"/lib/*.so "${OUT}/staging/lib/${ABI}/"
mkdir -p "${OUT}/staging/assets/licences"
cp "${RUNTIME_DIR}"/QNN-*.* "${OUT}/staging/assets/licences/" 2>/dev/null || true
echo " runtime: $(ls "${RUNTIME_DIR}/lib" | wc -l) libraries from ${RUNTIME_DIR}/lib"
else
echo " runtime: none (tract only)"
fi
# The models. Android has no other route to one — app-private storage is not
# user-reachable and the in-app fetch is unbuilt (docs/faces.md §2.2a) — so
# they go in the APK and `android_main` unpacks them on first launch. The
@@ -274,10 +296,10 @@ cp "${DEX}" "${OUT}/staging/classes.dex"
#
# Cleared first: a previous run that died between staging and cleanup would
# otherwise leave models in the APK that are no longer in the tree.
rm -rf "${OUT}/staging/assets"
rm -rf "${OUT}/staging/assets/models"
mkdir -p "${OUT}/staging/assets/models"
_bundled=""
for _dir in face scene; do
for _dir in face scene inpaint; do
ASSETS="${REPO}/models/${_dir}"
compgen -G "${ASSETS}/*.onnx" >/dev/null || continue
# An LFS pointer is ~130 bytes and looks exactly like a model to `cp`. Left
@@ -315,7 +337,7 @@ fi
# install times sane.
cd "${OUT}/staging"
cp "${OUT}/base.apk" "${OUT}/unaligned.apk"
zip -q -0 -X "${OUT}/unaligned.apk" "lib/${ABI}/libdarkroom.so"
zip -q -0 -X "${OUT}/unaligned.apk" lib/"${ABI}"/*.so
zip -q -X "${OUT}/unaligned.apk" classes.dex
# Stored, not deflated: an ONNX graph is mostly incompressible float data, so
# deflating it buys a few percent and costs the whole file being inflated into
+1 -1
View File
@@ -41,7 +41,7 @@ Measured on the first build, 2026-09-12:
| DLL imports | 26 Windows system DLLs; **no** `libwinpthread-1.dll`, `libgcc_s`, `libstdc++` |
| `wine darkroom-desktop.exe --version` | `darkroom-desktop 0.12.0`, exit 0, 0.1 s |
| `makensis` | 105 MB `DarkRoom-<version>-x86_64-setup.exe`, 64-bit stub |
| `wine setup.exe /S` | Installs exe + 7 models to `AppData\Local\Programs\DarkRoom`, writes the `HKCU` uninstall key; the installed exe runs |
| `wine setup.exe /S` | Installs exe + 10 models to `AppData\Local\Programs\DarkRoom`, writes the `HKCU` uninstall key; the installed exe runs |
| `wine uninstall.exe /S` | Removes the directory and the key |
| Start Menu shortcut | **Not verifiable here.** `CreateShortcut` is `IShellLink` and does nothing under a headless Wine; the directory beside it is created. Check on Windows. |
+8 -1
View File
@@ -1099,6 +1099,13 @@ architecture; everything else assumes they pass.
Decisions treated as fixed because reversing them is expensive. Each is evidence-backed.
> **On the numbering.** The subsections below are numbered **6.1–6.13**, not 12.x. They were §6
> when this document was first written, and every `ARCH §6.n` citation in `requirements.md`, in
> `docs/*.md` and in source comments names them by those numbers. Renumbering would break several
> hundred citations for no gain, so the numbers stay: `ARCH §6.1` means the first constraint here,
> and never §6.1 of the data architecture above, which is cited as *§6 Data architecture* or by
> its title.
### 6.1 GPU results never round-trip through the CPU
darktable identifies this as their single biggest bottleneck: OpenCL output returns to the GTK
@@ -1229,7 +1236,7 @@ Full rationale in [requirements.md §8](requirements.md). Summary:
| D10 | Single adaptive interface | Decided |
| D11 | Product positioning | Decided |
| D12 | Scope versus pace | **Open** |
| D13 | Face inference runtime and model licensing | **Runtime answered**, licensing open |
| D13 | Face inference runtime and model licensing | **Runtime answered**, reopened for per-device backends (docs/inference.md); licensing open |
| D14 | Segmentation source for local masking | Decided — arm C (docs/segmentation.md §14) |
| D15 | Target devices — 12-inch tablet and desktop, no phone | Decided (requirements D15) |
+23
View File
@@ -748,12 +748,34 @@ CREATE TABLE faces (
-- (faces.md §6, §9). NULL for a face stored as a unit vector before it
-- was kept.
quality REAL,
-- What the eyes are doing (FR-CULL-8a, faces.md §17): per eye P(open),
-- the source pixels across its box and the sharpness of the patch the
-- classifier saw; and P(sunglasses). All seven or none; NULL is "never
-- read", which every filter treats as unknown rather than as closed.
-- The verdict -- open, closed, sunglasses, unclear -- is a rule in
-- dr_face::eyes, not a column.
eye_right REAL,
eye_right_px REAL,
eye_right_sharp REAL,
eye_left REAL,
eye_left_px REAL,
eye_left_sharp REAL,
sunglasses REAL,
-- The 106 dense landmarks the eyes were read from, packed as 16-bit
-- fixed point over the frame: 424 bytes (schema V18). Kept so the next
-- per-face pass runs from the catalog rather than from the original.
landmarks_dense BLOB,
-- Which model produced this. An embedding is only comparable to others
-- from the same model; mixing them silently yields nonsense similarities.
model_id TEXT NOT NULL,
detected_at INTEGER NOT NULL
);
CREATE INDEX faces_image ON faces(image_id);
-- Covers the eyes-open filter's subquery. Without it every check read the
-- whole face row -- the eye columns sit after the blobs -- and one count
-- took 24 s on the reference library (schema V17).
CREATE INDEX faces_eyes ON faces(image_id, eye_right, eye_right_px, eye_right_sharp,
eye_left, eye_left_px, eye_left_sharp, sunglasses);
CREATE TABLE face_person (
face_id INTEGER PRIMARY KEY REFERENCES faces(id) ON DELETE CASCADE,
@@ -895,4 +917,5 @@ and is not answered here.
| FR-CULL-10 | §10.1 `people` and `face_person`, merge-by-redirect, §10.2 clustering as a library pass |
| FR-CULL-11 | §5 `Selector::Person`, confirmed-only by default |
| FR-CULL-12 | §10.1 derived data in the catalog; names to the sidecar, UUID as merge identity |
| FR-CULL-8a | §10.1 the seven eye columns, derived like the embedding; the filter term is `RatingFilter::eyes_open` |
| NFR-SEC-5 | §10.4 sync left undecided and off; nothing in §10 emits an embedding |
+346 -16
View File
@@ -540,8 +540,8 @@ images indexed, **64 contain no face at all**.
So `face_index` records the *run*: one row per `(image, model)` carrying the timestamp, the number of
faces found — zero is the interesting value — and the long edge of the proxy it read. Keyed on the
model, so a model change puts every image back in the queue without anyone having to remember to
clear anything.
model, so an *embedder* change puts every image back in the queue without anyone having to remember
to clear anything; a detector change in front of the same embedder does not (§12.3).
Three things fall out of it that were not otherwise available:
@@ -816,11 +816,21 @@ here, and it is the phone and tablet story that should decide whether it gets bu
anything downstream sees them. A probe's confidence (§9.1) is computed from the references it
matched; a reference's confidence hears nothing from a probe. A face whose quality was never
recorded is admitted to the gallery — a rule that cannot be checked admits rather than excludes —
and the next indexing pass **measures** it: `faces_unmeasured` lists every image holding one, and
each such face is embedded again from the native render with the landmarks it already has, the raw
vector written over the old one and its id, box and identity untouched
(`faces::record_measurements`). No detector runs and no suggestion is lost — the cost is the
and the next indexing pass **measures** it: the `face-quality` repair (§18.1) lists every image
holding one, and each such face is embedded again from the native render with the landmarks it
already has, the raw vector written over the old one and its id, box and identity untouched
(`faces::record_updates`). No detector runs and no suggestion is lost — the cost is the
original fetched once more, since the length exists only at the moment of embedding.
- **A person is stood for by their references.** Every face the user has ruled on is an anchor,
and the scan is exhaustive, so a person with 750 confirmations would cost 750 comparisons
against every other face — and the cost of a library would grow with how well it was named.
Instead each person enters through at most `MAX_REFERENCES` (100) of their anchored faces,
chosen by `dr_face::references`: those whose raw embedding is at least `MIN_REFERENCE_QUALITY`
(15) long, and among them the set spanning the greatest volume — greedy max-determinant, the
longest vector first and then, at each step, the face with the largest component orthogonal to
the chosen so far. Thirty frames from one afternoon contribute one reference; the single profile
shot is taken early. The faces not chosen keep their confirmations and are not touched by the
pass; they are simply not compared.
**The algorithm.** Constrained average-link agglomeration over the probability graph, merging while
the average pairwise probability exceeds **0.9** and no cannot-link is violated. Average-link rather
@@ -1100,14 +1110,33 @@ is not a desktop-only feature (NFR-RES-2). It loads in tract with the same fix a
decodes through the same nine-output path unchanged. Same licence, same `buffalo_m` release page.
**Which detector runs is a setting** — `FaceSettings::detector`, per device, on the settings page
beside the indexing button as Fast / Balanced / Thorough. All three files ship. Each detector is
its own `faces.model_id` (`w600k_mbf` for `500M`, unchanged, so nothing already indexed is
disturbed; `scrfd_2.5g+w600k_mbf` and `scrfd_10g+w600k_mbf` for the others), which is the
mechanism §2.1 always intended for a model change: the coverage figure restarts at zero under the
new id, the sweep re-detects, `record_detections` carries confirmed names across by box overlap and
drops the previous pipeline's marker for each image it revisits, and the sync shards are keyed by
the same id so a peer on another setting neither adopts nor pollutes them. The default stays `500M`
so that an upgrade changes nothing until the user chooses; the recommendation is `2.5G`.
beside the indexing button as Fast / Balanced / Thorough. All three files ship. Each detector
writes its own `faces.model_id` (`w600k_mbf` for `500M`, unchanged; `scrfd_2.5g+w600k_mbf` and
`scrfd_10g+w600k_mbf` for the others), so which pipeline drew a box is always on record. The
default stays `500M` so that an upgrade changes nothing until the user chooses; the recommendation
is `2.5G`.
**One population per embedder, not one per detector · 2026-09-19.** The first cut of the setting
keyed every reader on the full 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 theory that a
detector change is a model change. Measured on the reference library it was a disaster: choosing
Thorough on both devices restarted coverage at 1,834 of 19,140, the People screen showed only the
faces the new pipeline had reached, the desktop's 3,583 confirmations under the old id could not
reach the tablet because the merge demanded the same id on both sides, and each device faced a
~400 GB re-fetch before the library looked whole again. The embedder is `w600k_mbf` in every
variant; its vectors are one space, and the detector only decides where the boxes are.
So every reader now keys on the embedder half of the id (`faces::embedder_of`, and
`embedder_sql` for the queries): all three detectors are one population, and changing between
them empties nothing. `record_detections` is unchanged — an image holds one pipeline's faces at a
time, and a re-detection carries identities across by box overlap and embedding (§18) — and it is
where the generations meet. The merge's `match_faces` matches within an embedder for the same reason. The
shards travel every generation, each under its own id, and a peer adopts whichever it is sent.
What a stronger choice still does is queue the images a weaker detector indexed for re-detection
(`FaceDetector::supersedes`), after the ones nothing has indexed and never downwards, so a tablet
on Fast keeps the desktop's Thorough faces rather than replacing them with fewer. The calibration
(§8) is keyed on the embedder too: it is a fit over the similarity space, and that space did not
change.
---
@@ -1238,12 +1267,313 @@ frames to family snapshots as the real unknowns.
| ID | How this document addresses it |
|---|---|
| FR-CULL-8 | §4 detection, §6 embedding, §7 the proxy tier and its consequences, §10 the `DetectFaces` job |
| FR-CULL-8 | §4 detection, §6 embedding, §7 the proxy tier and its consequences, §10 the `DetectFaces` job, §18 the re-index |
| FR-CULL-9 | §8 — pairs, fit, validity, and the reliability-diagram acceptance test |
| FR-CULL-10 | §9 constrained agglomeration, confirmations as anchors, split by re-agglomeration |
| FR-CULL-10 | §9 constrained agglomeration, confirmations as anchors, split by re-agglomeration; §18 what a re-index carries across |
| FR-CULL-11 | §10 the `Person` selector term, confirmed-only by default |
| FR-CULL-12 | §10 schema unchanged from catalog.md §10.1: embeddings derived, names to the sidecar |
| NFR-SEC-5 | §11 — the obligations restated as structural properties, one of them CI-checkable |
| NFR-COMPAT-2 | §2 — why the obvious weights cannot ship, and what does instead |
| NFR-RES-2 | §1 the cheap model pair, §12 M2/M3/M10 on a phone |
| NFR-ARCH-2 | §10 background priority, preempted by visible work |
| FR-CULL-8a | §17 — eye state and sunglasses: the models, the crops, the readability rule, the measurements |
| FR-CULL-13 | §17.3 — the reading is evidence: a chip that narrows and a badge that explains, and nothing that writes a judgement |
---
## 17. Eyes and sunglasses · 2026-09-19
FR-CULL-8a's eye state, under FR-CULL-13's rule. Three more models run over every face the
pipeline already aligns, and what they produce is a **filter term** — "eyes open", on the people
filter — and a badge on the People screen. Nothing acts on it: FR-CULL-13 says the signal is
evidence, shown and filterable, and never holds the pen, and §3.9.1's exclusion of blink
*detection* was re-read the same day as the exclusion of blink *selection* it always was. The chip
narrows the grid the way a star count does, and rates nothing. Head pose, the other half of
FR-CULL-8a, is not built; §17.3 says what stands in for it.
### 17.1 The models, and why these
| | 2d106det | OCEC | SGC |
|---|---|---|---|
| Answers | 106 landmarks, ten round each eye's lids | P(this eye is open) | P(this head wears sunglasses) |
| Input | 192² RGB 0..255, the detector box at 1.5× | one eye, 40×24 RGB, `x/255` | one head, 48×48 RGB, `x/255` |
| Shipped | `buffalo_l`'s, 4.8 MB | S, 483 KB, F1 0.9943 on its own split | L, 6.1 MB, F1 0.9554 on its own split |
| Licence | InsightFace's research-only grant, like the pair (§2.2a) | MIT, code and weights | MIT, code and weights |
| Training data | InsightFace's | *Open and Closed Eyes* (ODC-By 1.0) + Wholebody34 crops (Apache 2.0) | **not stated** — recorded in `models/face/README.md` |
| Cost in tract | ~24 ms per face | ~6 ms per eye | ~6 ms per framing, two framings |
The two classifiers are from Katsuya Hyodo's ultra-lightweight series — the same author as the
whole-body detector §1.1's reference pipeline uses — and are the first weights in `models/face/`
that do not come out when the project publishes. The landmark model is under the grant the pair
already carries; it was chosen over two permissively licensed alternatives on a measurement
(§17.2) after the decision that this project will not be commercial, which is what §2.2a already
records for the pair.
All three load in tract as shipped, dynamic batch and all — the first graphs in this subsystem to
do so — and are pinned to a batch of 1 by `tools/fix-face-model-shapes.sh` anyway, because a graph
the engine *analyses* and a graph it has been *measured running* are different claims, and the
embedder's precedent is the safer one. Six milliseconds per classifier call against 0.4 in the
reference README is tract's per-call overhead on a graph this small; the whole reading is under
60 ms per face beside an embedding at 160 ms and a native decode in seconds.
### 17.2 Where the eye box comes from
**The eye classifier was trained on a whole-body detector's eye boxes, and this pipeline has no
eye boxes.** It has five landmarks, and SCRFD's eye point is loose: it is one of five points that
place a face, not an eye centre, and on a turned or smiling head the eye sat in a corner of a
window centred on it. Everything below was measured on 60 proxies from the reference library with
25 plainly open-eyed faces labelled by hand (`examples/eyes.rs --dump`, then a contact sheet), and
the count that matters is how many of those 25 the classifier read as open in both eyes.
**A window on the SCRFD point: 19 of 25.** Windows from 20×10 to 34×17 template units all gave
19–20; smaller lost eyes. Two model-free ways of re-centring the window were then tried and both
lost eyes: the darkest blob near the landmark is the inner corner's shadow or the lash line
(19 → 15), and the most contrasty window is the one that takes in the edge of the nose (19 → 9).
The landmark as SCRFD gives it beats either.
**A box from a landmark model's lid contour: 22 of 25.** Three models were run over the same
faces, each fed the crop its reference code feeds it, and the eye box cut as the bounding box of
the lid points grown by a margin:
| model | points | input | tract | per face | open at margin 0.1 |
|---|---|---|---|---|---|
| MediaPipe Face Mesh V2 (Apache 2.0) | 478, with z | 256² | loads | ~36 ms | 22 |
| PIPNet, PINTO's irnet18 export (WFLW, research-only) | 68 | 256² | loads | ~98 ms | 20 |
| **InsightFace 2d106det** | **106** | **192²** | **loads** | **~24 ms** | **22** |
The margin was swept on the two that tied: 22 at 0 and 0.1, 18 at 0.4, 14 at 0.6 — the training
crops were tight detector boxes, and a tight box is what the classifier wants (`EYE_BOX_MARGIN`).
2d106det ships: it tied the best, costs the least, and is under a grant the project has already
accepted. Face Mesh would be the choice if that changed; it also gives z and an iris, neither of
which this needs yet.
The box is cut **upright from the native render**, not through the face's alignment — the
training crops were detector boxes, and the contour already says where the eye is on a tilted
head (`align::eye_patch`). A shut eye's contour has no height and is given an open eye's
(`EYE_BOX_MIN_ASPECT`), so the classifier sees the same framing either way.
### 17.3 Not asking what cannot be answered
The 25 open faces were never the real problem. The real problem was the faces that were *not*
open-eyed by the classifier's account and were not blinks either, and on the reference sample they
were the commonest wrong answer of all: **a soft eye reads as closed.** A face small enough that
its eye was seven pixels wide, a motion-blurred face, a face from a 1024 proxy where the native
render should have been — each produced a confident "closed" from a classifier shown a smear. The
same failure the face's own sharpness gate exists for (§4.3), one stage down, where the face's gate
cannot see it: a face sharp enough to embed can hold an eye too soft to read, because the eye is a
fortieth of it.
So the reading is **seven numbers, not a verdict** — per eye P(open), the source pixels across its
box and the sharpness of the patch the classifier saw; and P(sunglasses) — stored as such
(`faces.eye_right`, `faces.eye_right_px`, `faces.eye_right_sharp`, likewise `eye_left`, and
`faces.sunglasses`, schema V16), and the verdict is a rule with thresholds in it,
`dr_face::eyes::EyeReading::state`, the only place the thresholds live:
```
sunglasses ≥ 0.5 → Sunglasses (whatever the eyes said)
an eye is readable when px ≥ 12
and sharpness ≥ 0.02
and px ≥ 0.6 × the other eye's px
no readable eye → Unreadable
a readable eye < 0.5 → Closed (a blink, or a wink)
otherwise → Open
```
**Sunglasses take precedence** because the eye classifier answers confidently over dark glass:
over a woman in sunglasses on the reference library it read her right eye 0.97 open. **The
pixel floor** is where the classifier's own training stopped — its reference footage averaged
15–21 pixels an eye. **The sharpness floor** is the face's measure over the patch, set where the
sample's open eyes were being called closed: the open set ran from 0.019 (a lens reflection) to
5.4, the unreadable ones under 0.02 with the pixels to match. **The width ratio** is the profile:
a landmark model's contour for the far eye of a turned head collapses towards the nose. On the
twenty native renders of §17.4, profiles put the far eye at 0.02–0.43 of the near one's width,
two three-quarter faces whose far eye was reading closed sat at 0.54, and every face looking at
the camera sat at 0.78 or more — a shut eye's box keeps its width, so a wink is not mistaken for
a turn. 0.6 splits the gap. An eye that fails any of the three is not asked, the near eye still
decides, and a face with no readable eye is *unclear* — which is not a blink, and not open, and
which no filter drops.
**The two eyes are kept apart** rather than averaged, because a wink averages to 0.5 — the one
value that says the least — and "eyes open" means every eye that could be read.
With the rule in place, the same 60 proxies read: 33 open, 14 closed, 24 sunglasses, 14 unclear.
Of the 25 labelled open faces, 22 open, 2 unclear (eye boxes of 7 and 12 pixels on a child's
face), 1 closed — a squinting smile whose contour collapsed to eleven pixels, which the classifier
is not wrong to call narrow. The 14 closed are downcast eyes, laughs, two sunglasses the head
classifier missed, and the squint. A face 141 pixels across the eye but motion-blurred to a
sharpness of 0.016 reads *unclear* where it read *closed* before, which is the change this
section is for.
**The filter drops only *Closed*.** `RatingFilter::eyes_open` compiles the rule above into a
predicate on the face row, ANDed into the chosen people's face subquery, so "Anna, eyes open" asks
about Anna's face and not about Bob blinking beside her. The chip is offered only while someone is
chosen and goes when the last person does — without a name in front of it, it would be a verdict
on everyone in the frame. The predicate still handles the empty case, as `NOT EXISTS` over every
face, for a filter arriving by another route; a landscape passes because there is no one in it to
have blinked. Sunglasses pass. Unclear passes. Never read passes — that last is what keeps an old
library from emptying its grid the moment the chip is pressed: until the measuring pass has run,
the honest answer is "everything". A test drives the same five readings through the SQL and
through `state()` and requires the two to agree, so the badge and the grid cannot say different
things.
**And an index, learned the slow way.** The people filter was always served from a covering index
on `faces(image_id)`; the moment its subquery read the eye columns it had to read the face *row*,
and `ALTER TABLE ADD COLUMN` had put those seven floats after the embedding and the crop blob —
six kilobytes to reach every one. One count took 24 seconds on the reference library, thirteen of
them system time. `faces_eyes` (schema V17) covers the subquery again: five milliseconds.
### 17.4 What the sample says about accuracy, and what it does not
The 60-proxy sample above was run at proxy resolution, where the production pass reads the native
render; the eye box on a 200-pixel face is 40 source pixels from the proxy and 240 from the
original. So the shipped configuration was also run over **twenty native renders** from the
reference library — a wedding burst of six frames with six or seven faces each, and a dozen
singles — exported by `face_native --export` and read by `examples/eyes.rs --dump`, 62 faces in
all: 20 open, 28 closed, 12 sunglasses, 2 unclear before the width ratio was moved (below).
Read off the contact sheet, face by face: the one real blink in the set (`7884.dng`, a man with
his eyes shut) is *closed*; the laughing faces with their eyes screwed shut are *closed*, which a
photographer would call right; the downcast faces are *closed*, which is arguable; the profiles
are judged on the near eye and mostly *open*, which the SCRFD-point pass could not do. Two
faces were wrong: three-quarter views whose far eye's box came to 0.54 of the near one's and read
closed over a cheek, which is what moved the width ratio from 0.45 to 0.6. One is beyond any
floor: a face with a porcelain pot held over the eyes, whose contour is a guess and whose "eyes"
are sharp white china.
Two things no sample so far can say. None holds more than one real blink, so the precision of
*Closed* is not measured — every closed verdict on the two sheets but the occlusion and the
sunglasses misses is a narrowed or shut eye rather than a wrong one, but that is a reading of a
contact sheet, not a number. And the floors were set on a few dozen faces. Both are M11.
### 17.4a What is kept per face
The box, the five landmarks, `crop_px`, the embedding and the crop were already there. The eye
pass adds the seven numbers of §17.3 and the **106 dense landmarks** it read the eye boxes from,
packed as 16-bit fixed point over the frame — 424 bytes a face, a seventh of a pixel on a
6000-pixel frame (`dr_face::Landmarks::to_packed_bytes`, schema V18). Kept for the reason the
embedding is kept: it cost a fetch of the original and a model run, and the next per-face pass —
head pose, expression, whatever FR-CULL-8a grows — should run from the catalog. `f16` would have
been the same size and worse: three figures near 1.0 is six pixels at that scale.
### 17.5 The measuring pass, and shards
A face indexed before the models existed, or on a device without them, has no reading. The
`face-eyes` repair (§18.1; on the day this was written, the sweep's measuring pass — the one V14
built to re-embed faces stored as unit vectors) lists those faces, on a device that has the models,
and reads their eyes from the same native render with the box and landmarks already stored. No
detector runs and no identity moves. A device *without* the models has no such repair, or it would
fetch every original in the library to do nothing to it; the repair's predicate is the one both the
count and the work list use, so the pass converges. The People screen's coverage line counts
these faces as work to read and keeps the button while any remain — reading **Read eye state**
once detection is complete and only readings are left, which is the state an already-indexed
library is in the day the models arrive.
Shards carry the seven columns beside `quality`. A peer's faces without a reading are **adopted**,
unlike a peer's faces without a quality (§14): the measuring pass finds this work by the NULL and
not by the run marker, so adoption costs the reading nothing, and a peer with no eye models may be
the only device that has done the detection at all.
### 17.6 Still to measure
| # | Measure | Why it decides something |
|---|---|---|
| **M11** | Open-eye recall and blink precision from the **native** pass with the shipped configuration, on a labelled sample that contains real blinks — a burst with one in it is enough | §17.3's figures are proxy figures from 25 faces, with no precision beside them; this is the number FR-CULL-13's acceptance clause asks for, and where the two readability floors get set on more than 25 faces |
| **M12** | Whether the remaining open-eye failure — a lens reflection over an open eye — moves with the sharpness floor, or needs the eye classifier told about spectacles | If the latter, the fix is a classifier trained closer to this domain, and that is a different decision |
| **M13** | Sunglasses recall on more than twelve faces, and the false-positive rate on caps and clear glasses | The two sunglasses the head classifier missed on the sample became false blinks; a library of skiers would say whether that is two faces or a class |
---
## 18. The completeness job, and what a re-index carries across · 2026-09-19
The reference library on the day this was written: 17,762 faces under the bare `w600k_mbf` id —
found by the fast detector on 1024 px proxies, stored as unit vectors, no quality, no crop on 4,144
of them, no eye reading, no dense landmarks — beside 1,177 under `scrfd_10g+w600k_mbf` from the
native pass, and 12,217 images the fast detector examined and found nothing in. Over those faces:
3,778 confirmations, 13,011 suggestions, 77 rejections, and 17,276 people rows. Every one of those
gaps was, until now, its own pass: V14's measuring pass for the quality, §17.5's for the eyes, the
sweep's proxy repair, the sweep's detector upgrade, and a re-index that did not exist. Adding a
per-face field meant adding a pass, with its own work list, its own count and its own idea of done.
### 18.1 One job over a registry
`dr_ui::repairs` replaces them with one job over a **registry**. A `Repair` names one thing a catalog
record can lack — the predicate that says which images still owe it, the input its handler needs
(the file's header, the whole original, or a native render), the handler that fills it, and, where
there is one, 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 one handler's write satisfies the next's (a detection writes every field a per-face handler
would fill). The registry today:
| Repair | Owed by | Input | Handler |
|---|---|---|---|
| `face-proxy` (sweep only) | images holding faces whose 1024 px proxy is not in the store | native render | detect again, write the proxy |
| `face-quality` | faces with `quality IS NULL` | native render | warp from the stored landmarks, embed, write the raw vector and its length (reads eyes on the same warp where it can) |
| `face-eyes` | faces with no eye reading or no dense landmarks, on a device with the eye models | native render | read the eyes and dense landmarks from the stored box and landmarks |
| `face-crop` | faces with `crop IS NULL` | native render | cut the crop from the frame |
| `face-detection` | sweep: images with no marker under the embedder and no faces; re-index: images with no marker under the **chosen detector**, either spelling | native render | detect, embed, replace the faces, carry identities across (§18.2) |
| `face-upgrade` (sweep only) | images whose marker is a weaker detector's | native render | as `face-detection` |
| `metadata` | `images.metadata_state < 2` | header | EXIF to the catalog, the dateless marked examined |
A repair's predicate is the *only* definition of its work. The count the settings page shows
(`faces::audit`, per repair), the list the job fetches and the check before each handler are one
predicate, so a record the count reports is one the job fetches and one the handler fills, and the
job ends. This is why an eye reading that cannot be cut is not a criterion — such a face stays
unread however often it is detected, and listing it would fetch its original on every press — and
why a degenerate face is dropped rather than left. It is also why the registry is cut to what the
device can do (`Capabilities`): a device without the eye models has no `face-eyes` entry, rather
than an entry it skips, because an entry is a count and a set of originals to fetch.
The registry is ordered, and the order is the work list's: an image only the last repair claims
comes after one the first does, which is what puts a few hundred proxy repairs ahead of twenty
thousand un-indexed images. Within one image the same order runs the handlers, detection before the
per-face repairs, since detection fills what they would.
Adding a field is one entry: a predicate over `faces f` or `images i`, and a handler that fills it
from `Fetched`. `metadata` is in the table to say that this is not a face job — the same machinery
carries a capture date, and could carry a thumbnail, a perceptual hash or a head pose.
### 18.1a The two scopes
Both buttons on the settings page run the job; they differ in one predicate. **Index faces**
(`Scope::Outstanding`) converges on *coverage* — has anything examined this image — and treats a
face a weaker detector found on a proxy as found, which is the right question for a pass that must
not fetch the library twice. **Re-index every face** (`Scope::Reindex`) 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 running it in f32 and a tablet on the Hexagon in int8
do not re-index each other's work), and a marker saying a weaker one looked is not that. This is
the one place in the subsystem keyed on the exact detector rather than the embedder. Convergent all
the same: an image the job has been through leaves the list, a kill costs the images in flight, and
a second press resumes.
An original over the fetch budget is skipped without being fetched. Under the sweep, detection
records an examination that found nothing — the honest record for an image that cannot be
examined, and what stops the half gigabyte being spent once per sweep. Under the re-index, and
under every repair over records that already exist, it is left exactly as it was: a re-detection
with nothing found would delete the faces, and "cannot fetch" is not "no faces".
### 18.2 What is carried across
`dr_catalog::faces::record_detections` replaces an image's faces and carries identities onto the
new ones. Before this section it carried confirmations only, by box overlap above 0.5 IoU, and a
re-detection of the library above would have left 13,011 suggestions and 77 rejections on the
floor — correct by FR-CULL-12's letter, since suggestions are derived data, and a People screen
emptied to strangers by the user's own button.
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 from §9's table). The embedding route
is for the box a low-resolution pass drew badly enough that overlap alone would not claim it; 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.
It is a match, not an update in place, and that is why the per-face repairs exist beside
detection: where nothing about a face but one field needs doing, `record_updates` keeps the id and
there is nothing to judge.
The merge's `match_faces` still matches by overlap alone across devices. It is the same question,
and the same answer would serve it; it is not changed here.
+34 -25
View File
@@ -5,7 +5,7 @@
Every entry here is extracted from the comment beside the code that implements it, so this file cannot describe a gesture the application does not have. Add one by writing a `GESTURE:` block next to the implementation; there is nowhere else to write it.
40 gestures, in 4 places.
41 gestures, in 4 places.
## Develop
@@ -25,7 +25,7 @@ Sampling a neutral is the first move of the tonal pass — every colour judgemen
Anchored on the fingers' midpoint, and on the pointer, so the gesture reads as magnifying the picture rather than sliding it about. Double-tap is the way to an exact 1:1; this is the way to everything in between.
<sub>`ui/dr-ui/ui/app.slint:1974`</sub>
<sub>`ui/dr-ui/ui/app.slint:2070`</sub>
### Move a magnified photograph about
@@ -34,7 +34,7 @@ Anchored on the fingers' midpoint, and on the pointer, so the gesture reads as m
Only once there is something outside the viewport to reach, which is why the cursor becomes a hand exactly then. The view is clamped to the frame: panning past the edge would show undefined area beside the photograph, and that reads as a rendering fault rather than as the end of the picture.
<sub>`ui/dr-ui/ui/app.slint:2065`</sub>
<sub>`ui/dr-ui/ui/app.slint:2161`</sub>
### Paint a mask by hand
@@ -43,7 +43,7 @@ Only once there is something outside the viewport to reach, which is why the cur
A model's mask stops inside a shoulder and leaks into the hair, and no single edge control fixes two errors that go opposite ways. The whole stroke is one step in the history, so taking a mark back costs one press however long it took to make.
<sub>`ui/dr-ui/ui/app.slint:2152`</sub>
<sub>`ui/dr-ui/ui/app.slint:2248`</sub>
### Take back the last change
@@ -53,7 +53,7 @@ A model's mask stops inside a shoulder and leaks into the hair, and no single ed
A whole drag is one step, so undo takes back a decision rather than a frame of a gesture. The list is there because arriving six steps back costs what arriving from one does.
<sub>`ui/dr-ui/ui/app.slint:2373`</sub>
<sub>`ui/dr-ui/ui/app.slint:2469`</sub>
### Do it again after taking it back
@@ -61,7 +61,7 @@ A whole drag is one step, so undo takes back a decision rather than a frame of a
- **Pointer** — Click it, or press Redo in the History header
- **Keyboard** — Ctrl+Shift+Z
<sub>`ui/dr-ui/ui/app.slint:2386`</sub>
<sub>`ui/dr-ui/ui/app.slint:2482`</sub>
### Copy the settings from this photograph
@@ -71,7 +71,7 @@ A whole drag is one step, so undo takes back a decision rather than a frame of a
The panel is the copy that has to work: a tablet has no modifier key to hold and no menu bar to hang the action from. The shortcut is an accelerator for a control that is on screen either way.
<sub>`ui/dr-ui/ui/app.slint:2419`</sub>
<sub>`ui/dr-ui/ui/app.slint:2515`</sub>
### Paste the settings onto this photograph
@@ -81,7 +81,7 @@ The panel is the copy that has to work: a tablet has no modifier key to hold and
The button names what would be pasted — "3 adjustments", and whether the crop is coming with it — which the shortcut cannot say. Both paste the same scope.
<sub>`ui/dr-ui/ui/app.slint:2431`</sub>
<sub>`ui/dr-ui/ui/app.slint:2527`</sub>
### Change which group of adjustments is on screen
@@ -91,7 +91,7 @@ The button names what would be pasted — "3 adjustments", and whether the crop
The groups are whatever the operation set declares itself to be about, so there are as many as the pipeline has and no key can be assigned to one of them by name. Stepping is the binding that survives a node being added.
<sub>`ui/dr-ui/ui/app.slint:2459`</sub>
<sub>`ui/dr-ui/ui/app.slint:2555`</sub>
### Look at the photograph at 1:1
@@ -101,7 +101,7 @@ The groups are whatever the operation set declares itself to be about, so there
Noise reduction and capture sharpening are judgements about single pixels, and a fitted view averages several of the file's into each one on screen — so the frame looks softer than it is and the correction goes too far. The point and the magnification survive opening the next photograph, which is what makes checking the same eye across forty portraits forty keystrokes rather than forty pans.
<sub>`ui/dr-ui/ui/app.slint:2494`</sub>
<sub>`ui/dr-ui/ui/app.slint:2590`</sub>
### Move to the next or previous photograph
@@ -111,7 +111,7 @@ Noise reduction and capture sharpening are judgements about single pixels, and a
The edit on screen is saved on the way out, so stepping through a folder is as much a departure as going back to the grid and loses nothing.
<sub>`ui/dr-ui/ui/app.slint:2546`</sub>
<sub>`ui/dr-ui/ui/app.slint:2642`</sub>
### See the photograph before you edited it
@@ -121,7 +121,7 @@ The edit on screen is saved on the way out, so stepping through a folder is as m
Held rather than toggled, and no split screen: a split halves the working image on the tablet the column was sized for, and the comparison photographers describe making is a flick back and forth. It takes no history step, so checking whether a frame is overcooked costs nothing to undo afterwards.
<sub>`ui/dr-ui/ui/app.slint:2670`</sub>
<sub>`ui/dr-ui/ui/app.slint:2766`</sub>
### Put one control back to its default
@@ -226,7 +226,7 @@ Double-click is what a file manager and a Lightroom panel use for the same thing
Grouping over-merges on siblings, on parents and children, and on the same person a decade apart, so splitting is as prominent as merging. A tool that can only merge makes its own errors permanent.
<sub>`ui/dr-ui/ui/identity.slint:161`</sub>
<sub>`ui/dr-ui/ui/identity.slint:188`</sub>
### Rule on a suggested face
@@ -235,7 +235,7 @@ Grouping over-merges on siblings, on parents and children, and on the same perso
A face is either the system's guess or the user's judgement, and the two are never conflated. A rejection is remembered, so the face is not suggested for that person again. The gesture note above is the whole label: a tick and a cross are only "confirm" and "reject" to someone who can see the suggestion they sit beside, and `IconButton`'s fallback would announce them as "check" and "cross" — two icon names that say nothing about which person is being ruled on.
<sub>`ui/dr-ui/ui/identity.slint:181`</sub>
<sub>`ui/dr-ui/ui/identity.slint:208`</sub>
### See a person's photographs
@@ -244,7 +244,7 @@ A face is either the system's guess or the user's judgement, and the two are nev
This is the point of having identified anybody. Without it the screen is a filing cabinet with no drawer handles.
<sub>`ui/dr-ui/ui/identity.slint:602`</sub>
<sub>`ui/dr-ui/ui/identity.slint:635`</sub>
### Change how faces are grouped
@@ -253,7 +253,7 @@ This is the point of having identified anybody. Without it the screen is a filin
The right match confidence is a property of your library, not of the model. "What would this do?" answers for this library without writing anything; names, confirmations and the groups you have set aside are kept whatever the dials say.
<sub>`ui/dr-ui/ui/identity.slint:639`</sub>
<sub>`ui/dr-ui/ui/identity.slint:672`</sub>
## Library grid
@@ -301,6 +301,15 @@ This replaced a double tap, which had no visible state and could take forty phot
<sub>`ui/dr-ui/ui/library.slint:1414`</sub>
### Take the blinks out of a burst
- **Touch** — Narrow to a person, then tap "Eyes open" beside their name on the filter bar
- **Pointer** — Narrow to a person, then click "Eyes open" beside their name on the filter bar
Face indexing reads each face's eyes. The chip drops frames where the chosen people are caught blinking, and leaves sunglasses and eyes it could not read alone.
<sub>`ui/dr-ui/ui/library.slint:2106`</sub>
### Find photographs with two people in them
- **Touch** — Open the People chip on the filter bar, tap each name, then switch the chip beside them to "all of them"
@@ -308,7 +317,7 @@ This replaced a double tap, which had no visible state and could take forty phot
"Any of them" is a union and "all of them" is an intersection. The tray is where both terms and the choice between them live, because a filter belongs on the filter bar.
<sub>`ui/dr-ui/ui/library.slint:2102`</sub>
<sub>`ui/dr-ui/ui/library.slint:2135`</sub>
### Resize the thumbnails
@@ -317,7 +326,7 @@ This replaced a double tap, which had no visible state and could take forty phot
There is no wheel on a tablet, so without the pinch the cell size could only be changed by a control a finger cannot reach.
<sub>`ui/dr-ui/ui/library.slint:2755`</sub>
<sub>`ui/dr-ui/ui/library.slint:2795`</sub>
### File photographs in a collection
@@ -326,7 +335,7 @@ There is no wheel on a tablet, so without the pinch the cell size could only be
The selection is what the drag carries, which is why selecting several is worth the mode: forty photographs file in one gesture.
<sub>`ui/dr-ui/ui/library.slint:2952`</sub>
<sub>`ui/dr-ui/ui/library.slint:2992`</sub>
### Open a photograph
@@ -335,7 +344,7 @@ The selection is what the drag carries, which is why selecting several is worth
A tap opens; a tap that *moved* does not. Travel is what separates a deliberate tap from a hand brushing past, and it is the only thing that does: the two are the same length. An earlier version required the finger to dwell 120 ms instead, and that rejected ordinary taps — a real tap is often quicker than a brush.
<sub>`ui/dr-ui/ui/library.slint:3220`</sub>
<sub>`ui/dr-ui/ui/library.slint:3260`</sub>
### Rate a photograph without opening it
@@ -345,7 +354,7 @@ A tap opens; a tap that *moved* does not. Travel is what separates a deliberate
A star has to take the press without it also reaching the cell, or every rating throws the user into develop.
<sub>`ui/dr-ui/ui/library.slint:3340`</sub>
<sub>`ui/dr-ui/ui/library.slint:3380`</sub>
### Choose the frame a folded burst shows
@@ -354,7 +363,7 @@ A star has to take the press without it also reaching the cell, or every rating
A folded burst draws its earliest frame, which is a fact about the clock and not a judgement about the photograph — nothing in this application ranks a frame (FR-CULL-5). But the point of a burst is that one of the twelve is better than the other eleven, and the photographer is the only one who knows which. So the choice is offered on the frames themselves, while they are open and side by side, which is the one moment the alternatives are on screen to be compared.
<sub>`ui/dr-ui/ui/library.slint:3471`</sub>
<sub>`ui/dr-ui/ui/library.slint:3511`</sub>
### Drop the selection but keep selecting
@@ -363,7 +372,7 @@ A folded burst draws its earliest frame, which is a fact about the clock and not
Distinct from Done, which leaves the mode entirely. Clearing keeps it, so the next selection can start straight away.
<sub>`ui/dr-ui/ui/library.slint:4132`</sub>
<sub>`ui/dr-ui/ui/library.slint:4177`</sub>
### Select everything the grid is showing
@@ -372,7 +381,7 @@ Distinct from Done, which leaves the mode entirely. Clearing keeps it, so the ne
A scoped grid of two hundred frames is two hundred taps otherwise, and "all of them, except those three" is a far more common shape than the taps it took to say it.
<sub>`ui/dr-ui/ui/library.slint:4149`</sub>
<sub>`ui/dr-ui/ui/library.slint:4194`</sub>
### Take photographs out of a collection
@@ -381,4 +390,4 @@ A scoped grid of two hundred frames is two hundred taps otherwise, and "all of t
The badge on a cell says a photograph is filed in three collections and never which. This is the sheet that names them, and the only way out of one the grid is not currently scoped to.
<sub>`ui/dr-ui/ui/library.slint:4264`</sub>
<sub>`ui/dr-ui/ui/library.slint:4318`</sub>
+484
View File
@@ -0,0 +1,484 @@
# Inference backends — the runtime and the model, chosen per device
Spec for **S16**, the build that puts the neural models on the hardware each device actually has.
Every model DarkRoom runs today — the three SCRFD detectors, the ArcFace embedder, YOLO26n-seg and
the ADE20K scene model — runs through `tract`, on one CPU core, on every platform. That was the
right first answer: D13's runtime half chose it because it costs no C dependency, and
[faces.md](faces.md) and [segmentation.md](segmentation.md) were written against it. It is also
between 20× and 300× slower than what the same devices can do, and this document is the record of
having measured that and the specification of what replaces it.
**It does not reopen D13's licensing half.** The weights are the same files under the same grant.
It does reopen the *runtime* half, and §3 is where it says how far.
---
## 1. What was measured · 2026-09-19
One benchmark, two builds of it: `ort`'s API over `tract` (exactly what the app links) and `ort`'s
API over a dynamically loaded ONNX Runtime with each execution provider in turn. Random 640×640
input, three warm-ups, the median of 15–30 timed runs, milliseconds. The same input every run, so
the numbers are compute cost and nothing else.
### 1.1 The tablet — Honor MagicPad 2, Snapdragon 8s Gen 3
SM8635: 1× Cortex-X4, 4× A720, 3× A520, Adreno 735, Hexagon V73. Android 16.
| Model | **tract** (today) | ORT CPU f32 | ORT CPU int8 | Adreno f32 ¹ | **Hexagon int8** ² |
|---|---|---|---|---|---|
| scrfd_500m (Fast) | 98 | 16 | 8 | 21 | **1.4** |
| scrfd_2.5g (Balanced) | 161 | 59 | 19 | ✗ | **1.8** |
| scrfd_10g (Thorough) | 489 | 204 | 48 | ✗ | **3.2** |
| arcface_mbf (per face) | 39 | 9 | 13 | 24 | 12 |
| yolo26n-seg | 287 | 94 | 38 | 54 | **5.1** |
| yolo26s-sem-ade20k | 408 | 154 | 46 | 47 | **3.7** |
¹ Qualcomm's own GPU backend (`libQnnGpu.so`, OpenCL). Fails on the two larger SCRFD graphs at an
`AveragePool` the layout transformer cannot place. ONNX Runtime's WebGPU provider also runs on this
GPU and was slower than the CPU on every model; it is not in the table because it is not a
candidate.
² QNN's HTP backend. The Hexagon **refuses float32 and float16 tensors** in this ORT 1.29 + QNN
2.42 pairing (error 3110 on every node, with `enable_htp_fp16_precision` set or not); int8 QDQ
graphs run with 99.6% of nodes on the NPU — 1718 of 1725 for SCRFD-500m, the remainder being the
quantise/dequantise at the graph's edges — verified from the partition log, not inferred from the
timing.
Also tried and rejected: **NNAPI** — the device registers no neural-networks HAL at all, so the
provider has nothing to talk to; Google deprecated it in Android 15 and Qualcomm stopped shipping
drivers for it. **XNNPACK** — slower than ORT's default CPU kernels on every model that loaded, and
aborts inside its partitioner on the SCRFD graphs.
### 1.2 The desktop — RTX 3050 Laptop, Raptor Lake, 20 threads
| Model | **tract** (today) | ORT CPU f32 | ORT CPU int8 | CUDA f32 | CUDA fp16 | TensorRT f32 | TensorRT fp16 | TensorRT int8 |
|---|---|---|---|---|---|---|---|---|
| scrfd_500m | 104 | 12 | 8 | 5.6 | 3.7 | 2.5 | **1.8** | ✗ ⁴ |
| scrfd_2.5g | 162 | 27 | 12 | 6.2 | 5.3 | 2.9 | **1.9** | ✗ ⁴ |
| scrfd_10g | 514 | 99 | 32 | 14.5 | 9.3 | 7.6 | **3.3** | ✗ ⁴ |
| arcface_mbf | 45 | 15 | 18 | 1.1 | 0.8 | 0.9 | 0.7 | ✗ ⁴ |
| yolo26n-seg | 307 | 60 | 38 | 9.3 | ✗ ³ | 6.8 | **5.5** | ✗ ⁴ |
| yolo26s-sem-ade20k | 395 | 61 | 31 | 10.7 | ✗ ³ | 7.9 | **3.4** | ✗ ⁴ |
³ The offline fp16 conversion (`onnxconverter-common`) left a mixed-type node the CUDA provider
rejects. TensorRT converts to fp16 itself at engine build and does not have this problem, which is
one reason it is the target and the CUDA provider is the fallback.
⁴ TensorRT refuses the QDQ form ONNX Runtime's quantiser writes for the Hexagon (uint8
activations); it wants symmetric int8. Not pursued: fp16 needs no quantisation, no calibration and
no accuracy gate, and it is already 30–60× tract.
CUDA int8 is deliberately absent: the CUDA provider has no int8 kernels and runs a QDQ graph by
dequantising it, which measured *slower* than f32 (7.0 vs 5.6 ms on scrfd_500m). Int8 on NVIDIA is
TensorRT's job.
**TensorRT's first load is 16–116 s per model in f32 and 35–290 s in fp16** (yolo26n-seg the
worst: nearly five minutes), because it is compiling an engine for this exact GPU. The engine caches to disk and the second load is milliseconds. That
number is what §6 is designed around.
### 1.3 What the numbers say
- **`tract` is single-threaded.** The tablet's one X4 core and one Raptor Lake core give the same
tract numbers. Replacing it with ONNX Runtime's CPU provider, *no accelerator involved*, is 3–6×
on the tablet and 8–10× on the desktop. That is the floor, and it is available on every platform
the app builds for.
- **The Hexagon is the standout.** A 6 W NPU running int8 beats a discrete RTX 3050 running f32 on
five of six models. A whole-library face index on the tablet goes from ~100 ms + 39 ms per face
to ~1.4 ms + 12 ms per face, and the "Thorough" detector — 3× the cost of "Fast" today — becomes
free. Its price is that the models must be **quantised to int8**, which is an accuracy question
§5 has to answer before it is believed.
- **The embedder does not gain from either accelerator.** 112×112 input, per-op overhead
dominates; it is 9 ms on the tablet's CPU and 12 ms on its NPU. It stays float, which §7 turns
from a performance footnote into a correctness rule.
- **On NVIDIA, TensorRT fp16 ≈ 3× the CUDA provider**, and the CUDA provider ≈ 2× the
multi-threaded CPU; at fp16 the detectors are 1.8–3.3 ms with no quantisation at all. Both leave the twenty cores free for decoding during a batch index, which the table does not
show and which matters more than the ratio.
---
## 2. The shape of the answer
A **ladder per platform**, walked at start-up, with the first rung that builds a real session
winning:
| Platform | 1st | 2nd | 3rd | Floor |
|---|---|---|---|---|
| Android, Qualcomm with a Hexagon the shipped QNN skel covers (V68–V81) | QNN HTP, int8 model | ORT CPU, f32 model | — | tract |
| Android, any other SoC | ORT CPU, f32 | — | — | tract |
| Linux / Windows, NVIDIA GPU | TensorRT, f32 model, fp16 engine | CUDA provider, f32 | ORT CPU, f32 | tract |
| Linux / Windows, no NVIDIA | ORT CPU, f32 | — | — | tract |
| macOS ⁵ | ORT CPU, f32 | — | — | tract |
⁵ CoreML is the obvious rung and is unmeasured; it is listed so its absence is a gap and not an
oversight.
Deliberately **not** on any ladder, with the measurement that excluded each: NNAPI (no driver),
XNNPACK (slower than CPU, aborts on SCRFD), WebGPU (slower than CPU), the Adreno through QNN (works,
but never where the Hexagon does not also), CUDA int8 (slower than CUDA f32). A rung is added to this
table by a measurement on this page, not by a provider existing.
Two things the ladder is *not*: it is not a per-model choice — one backend serves every model on a
device, because §7's identity rule needs the detector and embedder on the same runtime for the
same reason `faces.model_id` pairs them; and it is not a per-account choice — it is a property of
the hardware, like `shared_face_models_dir` is, and it lives beside it.
---
## 3. The dependency policy, and how far this reopens it
D13 chose `ort` over `tract` because `alternative-backend` made ONNX Runtime's *API* available with
none of its *C*. Every rung above the floor needs the C++ ONNX Runtime and, for the two that matter
most, vendor libraries on top: Qualcomm's QNN runtime (~60 MB for one Hexagon generation; it is
per-SoC) and NVIDIA's TensorRT plus cuDNN (~600 MB with the CUDA libraries, and cuDNN's major
version must match what ONNX Runtime was built against — the Arch package on the reference desktop
was unusable for exactly that reason).
The policy protected the **build**: no C to cross-compile under the NDK, no toolchain to keep in
step. This document keeps that intact, and the mechanism is the one thing about `ort` that makes it
possible:
**`ort::set_api` accepts any `OrtApi` table.** With `alternative-backend` on, `ort` links nothing
and asks for the table once per process. The application can `dlopen` a `libonnxruntime.so` it
finds on disk, call `OrtGetApiBase()->GetApi(version)` and hand that table over; or, if there is no
such file, hand over `ort_tract::api()`. The Rust build is identical in both cases — pure Rust,
`cargo build --target aarch64-linux-android` sees the same dependency graph it sees today. What
changes is that the runtime is a **file the package installs**, next to the models, and the app
looks for it at start-up.
Consequences that follow and are accepted:
- **The runtime is chosen once per process**, because `set_api` is once per process. The ladder
in §2 is walked at start-up and the result is what every session in that process uses. There is
no "tract for this model, ORT for that one", and there is no falling back to tract *after* ONNX
Runtime has loaded — but there does not need to be: once the library loads, its CPU provider is
always there, and every fallback the ladder needs is between providers *inside* it.
- **Feature flags stay as they are.** `dr-face`'s `inference` and `dr-segment`'s `semantic`
continue to mean "compiled against `ort`'s API"; nothing at build time knows or cares which table
will be supplied. The one addition is a `native-probe` feature on the new crate (§8) that pulls in
`libloading`, which is pure Rust and already in the tree via `wgpu`.
- **The packagers ship the runtime, not the build.** The Arch package, the Flatpak manifest, the
NSIS installer and `assemble-apk.sh` each gain the ONNX Runtime library for their platform, and
the Android and NVIDIA variants gain the vendor libraries — each under the licence the packager
reads first (§3.1). A package without them is not broken; it is the tract build, and it says so
on the about screen.
- **The NDK problem does not come back.** `libonnxruntime.so` for Android is a prebuilt from
Maven (`com.microsoft.onnxruntime:onnxruntime-android-qnn`), extracted by `assemble-apk.sh` into
`jniLibs/` the way the models are bundled as assets today. Nothing compiles it.
### 3.1 Licences the packagers read before shipping a runtime
Written down now, because [segmentation.md §7](segmentation.md) established that reading the grant
is cheaper than discovering it at packaging time.
| Component | Licence | Redistributable in a self-distributed package? |
|---|---|---|
| ONNX Runtime | MIT | Yes |
| Qualcomm QNN runtime (`com.qualcomm.qti:qnn-runtime` on Maven) | Qualcomm AI Engine Direct SDK licence — proprietary, redistribution permitted for applications using it | Yes for the APK, with the licence text shipped; not for a source distribution. **To be read in full, not summarised from memory, before the APK gains it.** |
| CUDA runtime, cuDNN, TensorRT | NVIDIA EULAs — redistributable with an application, with the licence text, not modifiable | Yes for a package that bundles them. 600 MB. The alternative is to load them from the user's system install if present and skip the rung otherwise — which is what §4's probe does anyway. |
The position this takes: the **NVIDIA libraries are not bundled**. The desktop package probes for a
system CUDA/TensorRT install and uses it if it is version-compatible; a desktop without one runs on
ORT CPU, which is still 8–10× today. Bundling 600 MB for a rung that is 2× again is not a trade
worth making unmeasured, and it can be revisited by a measurement on a batch index. The **QNN
runtime is bundled** in the APK, because the Hexagon is the difference between a tablet that
indexes a library overnight and one that does it over lunch, and the package is 60 MB larger for
it.
Both positions are D13 territory and are recorded there (§12).
---
## 4. Selection — the probe, its cache, and what it may not do
**A rung is chosen by building a real session on it, not by asking whether it exists.** Both
failure modes that are not "the provider is absent" were hit on 2026-09-19: a driver in a wedged
state where the provider registered and the session then failed, and a provider that registered,
took the graph, and rejected every node at partition time. The probe therefore:
1. Loads the runtime library (§3), or falls to tract and stops.
2. Times the **smallest detector** on the CPU provider first — the floor. Then, for each rung
in this platform's ladder, in order: builds a session for the same model on that provider
with `error_on_failure`, runs it once on a fixed input, and times three more runs. **The rung
is taken only if its median beats the floor.** That one measurement is the proof the provider
took the graph: one that silently hands the work to the CPU is the CPU rung with extra
overhead, slower than the floor, and rejected. (ONNX Runtime's
`session.disable_cpu_ep_fallback` was the first draft of this proof and refuses the Hexagon
over the ten quantise/dequantise nodes at the graph's edges that QNN declines by policy.)
3. Records the outcome — rung, runtime version, provider version, device identity (GPU name and
compute capability; SoC model and Hexagon arch), and the models' content hashes — to a small
file beside `shared_face_models_dir`. The next start-up trusts the file **unless** any of those
inputs changed, in which case it probes again. A driver update, a runtime update, a new model
file: each invalidates the cache by construction, and none needs a "reset backend" button.
What the probe may not do:
- **Block the first frame.** It runs on the same background as `install_bundled_models` and for
the same reason: a TensorRT probe can take thirty seconds cold, and a tablet that stalls that long
is an ANR. Until it reports, every model request is answered by the floor the runtime supports
(ORT CPU if the library loaded, tract otherwise), and a job that started on the floor finishes
on it — a backend does not change under a running index.
- **Retry a rung that failed within a session.** A failed probe is cached as a failure with the
same inputs; the rung is tried again when an input changes. Otherwise a wedged driver means a
thirty-second stall on every launch.
- **Choose for the user without saying so.** Settings gains one row, *Inference backend*, showing
what was chosen and why in one line ("Hexagon NPU · int8 · QNN 2.42"; "CPU · ONNX Runtime 1.30 ·
TensorRT probe failed: cuDNN 8 required"), with an override to force any lower rung. The about
screen carries the same line beside the model names NFR-SEC-5 already puts there.
---
## 5. Model variants, and who makes them
Every model exists in one **canonical** form — the f32 ONNX file the app ships or the user supplies
today — and, where a rung needs it, a **derived** form. The ladder's rungs are specified in terms
of which form they load:
| Form | Who produces it | When | Needed by |
|---|---|---|---|
| f32 ONNX, shape-fixed, **opset ≥ 13** | `tools/fix-face-model-shapes.sh`, `tools/export-seg-model.sh` | Release time, once | Every rung except Hexagon |
| int8 QDQ ONNX, per-channel, uint8 activations | `tools/quantise-models.sh` (new) | Release time, once, **calibrated on real photographs** | Hexagon |
| TensorRT engine (`.engine`, per GPU architecture and TensorRT version) | The app, from the f32 file | First run on that device, in the background | TensorRT rung |
| QNN context binary | The app, from the int8 file | First run on that device, in the background | Hexagon rung |
Two rules.
**Quantisation is a release-time step, not a device-time one.** The int8 files that produced §1's
numbers were calibrated on random noise, which is enough to time and worthless to trust. A real
int8 detector is calibrated on a few hundred real photographs and then measured against the f32
detector on the reference library by [faces.md §12.3](faces.md)'s method — faces found, per size
band, per detector — before it ships. That needs the reference library and a person reading the
result, and it happens once per model release, in `tools/`, beside the shape-fixing it already
depends on. The device never quantises anything.
The SCRFD and ArcFace files are **opset 11** as InsightFace exported them, and per-channel QDQ needs
13; `tools/fix-face-model-shapes.sh` gains an opset upgrade to 17 (`onnx.version_converter`,
`ir_version` 8), which `tract` has been verified to load and which every provider on this page
prefers. That is a change to the canonical file and so a change to the shipped models, and it
happens in the same model release as the int8 files.
**Compilation is a device-time step, and it is cached.** A TensorRT engine is specific to the GPU
it was built on and the TensorRT that built it; a QNN context binary is specific to the Hexagon
generation. Neither can ship. Both are built by the app the first time that rung is selected, in
the background (§6), and written beside the probe cache keyed by the same inputs. They are
**derived, disposable, and regenerable**: deleting the cache directory costs the next launch a
rebuild and nothing else, and the directory is excluded from anything that syncs (it is a peer of
`thumbs`, not of the catalog).
---
## 6. First run — building engines without the user waiting for them
The sequence on a device where a compiling rung (TensorRT, Hexagon) is selected:
1. **Launch.** The runtime loads; the probe (§4) starts in the background; the app serves every
model request from the floor. Face indexing, segmentation and scene grading all work, at
today's speed or better (ORT CPU).
2. **Probe reports** — say, TensorRT. The compiling rung is now *selected* but has **no engines**.
Model requests continue on the fallback rung below it (CUDA provider for TensorRT; ORT CPU for
Hexagon), which needs no compilation and is already faster than the floor.
3. **Engines build**, one model at a time, on a single low-priority background thread, smallest
model first so the detector — the one that runs per image — is ready soonest. On the reference
desktop that is ~1 minute for the first detector and ~10 minutes for all six at fp16; on the tablet the QNN
context binaries take 0.8–1.7 s each and the whole set is ready before the user has opened a
library. Each engine is written to a temporary name and renamed into place, so a request never
sees a half-written file.
4. **Requests move up as engines land.** A model whose engine exists loads it on the selected
rung; one whose engine is still building loads on the fallback. **A running job does not
switch** — an index that started on the CUDA provider finishes on it — because §7 needs one
`model_id` per job, and because a job is the wrong granularity for surprise.
5. On Android, the build runs only while the app is in the foreground and the device is not in
battery saver (NFR-RES-3): a context binary takes a second, so this costs nothing, and the rule
exists for the day a model takes longer.
Settings shows a one-line progress row while engines build ("Preparing GPU engines · 3 of 6") and
nothing when they are done. A build failure demotes the rung — it is recorded in the probe cache
as a failure with the model hash as an input, so a corrected model file retries it — and the app
carries on one rung down, saying so in the same row.
---
## 7. Identity — what changes `model_id` and what may not
`faces.model_id` exists so that two libraries indexed with different networks are never compared
as if they were one ([catalog.md §10.1](catalog.md); the trap is written up in
[faces.md §14](faces.md)). A backend that changes what a network *computes* is a different network
and must be a different `model_id`; one that changes only *where* it computes it must not be.
**The detector.** An int8 SCRFD finds a different set of faces from the f32 one — that is what
§5's acceptance measures — so **the numeric form is part of the detector's identity**:
`scrfd_500m` and `scrfd_500m_i8` are two detectors in `model_id`, and a library indexed on the
tablet's Hexagon and continued on the desktop is two populations, which a re-index on either side
reconciles the same way a switch from Fast to Thorough does today. That is acceptable because it is
already the rule for the detector and because §5 is the gate on whether the int8 form is close
enough to be *offered* at all. f32 on tract, ORT CPU, CUDA and TensorRT-f32 are one identity: the
same graph, the same arithmetic, differences at the last bit.
**The embedder** is where comparability across devices is the whole point, and it is the one
model that no accelerator helps (§1.3). So: **the embedder runs in f32 on every rung.** On TensorRT
that means the embedder's engine is built without fp16 while the detector's is built with it; on
the Hexagon it means the embedder is not on the NPU at all — it runs on the ORT CPU rung at 9 ms,
and the ladder's "one backend per device" is, precisely, one backend *per model role*, with the
embedder pinned. A `w600k_mbf` embedding from any device is comparable with one from any other,
which is the property the identity system, the calibration and the cross-device merge all rest
on, and it is not for sale for 3 ms.
If S16 wants fp16 for the embedder later, the gate is written now: over the reference library's
faces, the cosine between the f32 and fp16 embedding of the same crop exceeds 0.999 for 99.9% of
faces and the calibration's fitted threshold moves by less than its own confidence interval
([faces.md §8.3](faces.md)). Until measured, f32.
**Segmentation and the scene model** carry no identity across devices — their outputs are
recomputed per image and never stored beyond the cache — so they take whatever the rung offers,
int8 included, subject to §10's own acceptance.
---
## 8. Crate shape — `core/dr-inference-engine`
The seam is the same shape as [storage.md](storage.md)'s: a small crate below the consumers that is
the **only** place naming a provider, a library file or a vendor, with the consumers reduced to
"give me a session for these bytes in this role".
```
core/dr-inference-engine
src/lib.rs Runtime (Tract | Onnx { lib, version }), Backend (rung), Role (Detector | Embedder | Segmenter)
src/probe.rs §4 — the ladder per platform, the session-build probe, the cache file
src/engines.rs §6 — background compilation, the cache directory, progress
src/session.rs open(role, bytes) -> ort::Session, applying the rung and the role's precision rule
src/api.rs the one unsafe block: dlopen libonnxruntime, fetch OrtApi, ort::set_api — or ort_tract::api()
```
- `dr-face` and `dr-segment` **delete** their private `install_backend` and their direct
`Session::builder()` calls and take an `&dr_inference_engine::Sessions` where they take model bytes today.
Their tests keep `tract` — `dr_inference_engine::Sessions::tract()` is a constructor and the test-only path.
- `dr-inference-engine` depends on `ort` with the same workspace features as today plus `cuda`, `tensorrt`,
`qnn`: those features add option builders, not linking, under `alternative-backend`. **Verified
for the QNN, CUDA and TensorRT builders on 2026-09-19** — they go through the API table's generic
`SessionOptionsAppendExecutionProvider*`. The NNAPI builder resolves a symbol directly and would
not; it is not needed and is not enabled.
- `dr-ui` owns the settings row, the about-screen line and the progress row; it holds one
`Sessions` per process, created at launch, and passes it down. `dr_ui::library` gains
`inference_cache_dir()` beside `shared_face_models_dir()`, on the same account-independent
footing and for the same reason.
- The Android entry point's `install_bundled_models` also extracts nothing new: `jniLibs/` is
loaded by the system loader, and `dr-inference-engine` on Android looks for `libonnxruntime.so` through
`dlopen` by bare name first, which resolves to the APK's copy, before any directory.
---
## 9. Threads and memory
- ONNX Runtime's intra-op pool is sized to the physical cores minus two on desktop and to the
performance cores on Android (the X4 and the A720s; the A520s are for the compositor). tract's
single thread today is the reason a batch index leaves nineteen cores idle; ORT CPU with the
pool is the reason it will not. One session per model per process; `Session::run` is
`&mut self`-free in `ort` and internally serialised, and the index job is the only caller.
- A TensorRT session pins GPU memory for its workspace; the builder is capped at 512 MB on the
reference 6 GB card and the cap is a setting, because the develop view's tiles share the card
(NFR-RES-2). The engine cache on disk is bounded by the model set — six engines, ~80 MB — and
needs no LRU.
- The Hexagon rung sets QNN's performance mode to `Burst` for the duration of an index job and
`Default` otherwise; a 5 ms detector does not need the NPU clocked up between images.
- The probe (§4) and the engine build (§6) run on one dedicated low-priority thread. They never
share the index job's pool: a probe that competes with the job it is meant to speed up is the
frame-budget trap in a new coat.
---
## 10. What S16 measures
In order, with the gate each is:
| # | Question | Gate |
|---|---|---|
| M1 | Does one binary carry both tables? `dlopen` + `set_api` on Linux, Windows and Android; `ort_tract::api()` when the file is absent. | Go / no-go for §3. If `set_api` cannot take a dynamically fetched table on some platform, that platform ships two binaries, and the cost is stated. |
| M2 | Do the int8 SCRFD detectors, **calibrated on real photographs**, find the faces? faces.md §12.3's method over the reference library, per size band, against f32. | Ship the int8 form for a detector only if it finds ≥ 97% of the f32 detector's faces above 40 px and the difference is not concentrated in one band. Otherwise that detector's Hexagon rung is ORT CPU int8-free, and the table in §1.1 says what that costs. |
| M3 | Does the embedder on ORT CPU beside a detector on the Hexagon (§7) produce embeddings within the f32 gate? | It must — same graph, same arithmetic. This is a check that the plumbing did not quantise it by accident. |
| M4 | Is a batch index on the tablet and on the desktop faster by the ratio §1 predicts, end to end, decode included? | The face index over the reference library (18,143 faces): report wall-clock on tract, on the floor and on the selected rung, and where the time went. The prediction is that decode becomes the bottleneck on both; if it does not, say why. |
| M5 | Does the first-run sequence (§6) hold: nothing blocks the first frame, engines land, requests move up, a running job does not switch? | Observed on both devices with the app's own progress row, and with the cache directory deleted between runs. |
| M6 | What does the APK weigh with the QNN runtime, and does a non-Qualcomm Android device (any one) still launch and index on the floor? | Size reported; launch verified on one non-Qualcomm device or an emulator. |
| M7 | The segmentation and scene models at int8 on the Hexagon: does the mask boundary move? segmentation.md §6's IoU against f32 over its corpus. | Ship int8 for a model only above the IoU floor that document set for arm B. |
M1 and M2 are the ones the rest is conditional on, and M2 is the one that needs a person.
### 10.1 M2 result · 2026-09-19
Each int8 detector against its own f32 form, over 400 proxies evenly spaced through the reference
library, on ONNX Runtime's CPU provider (the int8 graph is the same file the Hexagon loads;
`ui/dr-ui/examples/face_detectors`). Calibrated on 64 proxies from the same library, disjoint
from the 400.
| Detector | f32 faces | int8 faces | both | int8 only | f32 only | found ≥ 32 px | found, all sizes |
|---|---|---|---|---|---|---|---|
| scrfd_500m | 1342 | 1319 | 1287 | 32 | 55 | 95.6% | 95.9% |
| scrfd_2.5g | 1525 | 1482 | 1478 | 4 | 47 | 96.1% | 96.9% |
| scrfd_10g | 1769 | 1760 | 1749 | 11 | 20 | 100% | 98.9% |
The 10g form clears the 97% gate; 500m and 2.5g sit one point under it. What they lose is
specific: the faces in the "f32 only" column have a **median confidence of 0.52** against a
threshold of 0.50 — detections the f32 graph itself barely made, that int8 rounding drops to the
other side of the line — and the extra faces int8 finds are the same kind (median 0.51–0.52).
Not a size-band failure: the losses are spread across bands in proportion. Shipped as they are,
with the number on record; a threshold of 0.48 for the int8 forms would recover most of the
margin, and is the first thing to try if a library's count on the tablet reads low.
Two things the calibration taught, both in `tools/quantise-models.py`: the calibration set has
to contain faces (a first attempt on landscape photographs produced a graph that found nothing —
the score head's ranges had never seen the face regime), and ONNX Runtime's own strided and
moving-average calibration modes both measurably degrade the result on these graphs, while
driving the calibrator in chunks by hand reproduces the plain min/max ranges exactly.
---
## 11. Order
1. **`dr-inference-engine` with the two tables and the floor** — `set_api` from a dlopened runtime, tract
otherwise, ORT CPU as the only rung. Consumers moved over; tests unchanged. This alone is the
3–10× and is the build most of the value sits in. M1.
2. **The probe and its cache** (§4), with the settings row and the about line. Still CPU-only;
the ladder has one rung. M5's first half.
3. **`tools/quantise-models.sh`** and the opset upgrade; the int8 detectors calibrated and
measured. M2, M7. This is the step with a person in it and it runs in parallel with 4.
4. **The Hexagon rung**, the QNN runtime in the APK, the context-binary cache. M3, M6.
5. **The TensorRT and CUDA rungs** on desktop, the engine cache, the first-run sequence. M5's
second half.
6. **M4** last, on both devices, and the number goes in this document.
The Windows installer and the Flatpak manifest are touched in steps 1 and 5 only, and only to add
a file each; the Arch package likewise.
---
## 12. Register entries
**FR-INF-1 — Runtime selection.** On launch the application shall determine, per device and
without blocking the first frame, the fastest inference backend that can build and run a session
for the shipped models, by attempting it; shall record and reuse that determination until the
runtime, driver, hardware or models change; and shall display the backend in use in Settings and
on the about screen. *Acceptance:* §10 M1 and M5.
**FR-INF-2 — Derived engines.** Backends that require device-specific compilation shall compile in
the background after selection, shall serve requests from the next lower backend until each engine
is ready, and shall not change the backend of a job in progress. *Acceptance:* M5.
**FR-INF-3 — Model forms.** Quantised model forms are produced at release time from real
calibration data and are shipped only when they meet §10's accuracy gates against the canonical
form; the application never quantises on the device. *Acceptance:* M2, M7.
**NFR-INF-1 — Embedding comparability.** Face embeddings shall be computed at a precision whose
deviation from the f32 reference is within §7's gate, on every backend, so that embeddings from any
device are comparable. *Acceptance:* M3.
**D13 — updated.** The runtime half is reopened to the extent of §3: the Rust build stays C-free
under `alternative-backend`; packages may install a dynamically loaded ONNX Runtime and, per §3.1,
the Qualcomm QNN runtime; the NVIDIA libraries are not bundled. The licensing half is unchanged.
---
## 13. Requirements touched
FR-CULL-8 (indexing time is what this exists to change), FR-CULL-9 (NFR-INF-1 is the guard on its
calibration), NFR-RES-2 (TensorRT workspace against the develop view's tiles), NFR-RES-3
(background compilation on Android), NFR-SEC-5 (the about screen's line), NFR-COMPAT-2 (each
channel gains a runtime file), FR-PLAT-AND-1 (unchanged; the runtime lives in the APK, not in
storage), ARCH §6.1 (the once-per-image budget this was sized against no longer binds; what could
run per frame is a separate question this document does not open).
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# DarkRoom, shown
A tour of what the application does, one picture per thing. Every image on
this page was captured from the desktop build driving itself — nothing is a
mock-up, and nothing has been retouched outside DarkRoom. Where a feature is
better seen moving, it moves.
The requirements behind each feature are in [requirements.md](../requirements.md);
the reasoning is in the design documents linked from each section. This page
is only about what you see.
The photographs are the author's. None show a person.
## Opening a library
DarkRoom opens on a library: a folder on this machine, a folder a sync
client keeps, or a Nextcloud account. A folder needs no password and uploads
nothing.
![The launch screen: a server field, a folder field, and which formats to scan for](media/launch.png)
Once a folder is named, it is the library — you are not asked for it again,
and `Open library` opens it whole. `Subfolder…` narrows the scan to part of
it. The formats ticked are what the scan looks for; RAW is on and JPEG off
by default, because a RAW editor's sensible default is the file the camera
wrote first.
![A folder chosen: the library, whether to scan a subfolder, and the formats](media/launch-folder.png)
## The library
![The grid: collections on the left, the timeline beside it, the roll of thumbnails, and the filter bar above](media/library.png)
Photographs are ordered by capture time, with a month heading where each
begins. The strip on the left is the timeline — drag it to jump to a year.
The bar above the grid filters by rating, flag and where the file is (on this
device, or only on the server).
### Rating and flagging
Hover a cell and the stars appear; click one. The filter chips above the grid
count what each rating holds, and clicking `3+` shows only those.
![Rating two photographs, then filtering the grid to three stars and more](media/library-rating.gif)
### Getting about
Drag the timeline to scrub through years; Ctrl and the wheel resize the
thumbnails.
![Scrubbing the timeline](media/library-timeline.gif)
![Resizing the thumbnails with Ctrl and the wheel](media/library-thumbsize.gif)
### Selecting several
`Select` in the header — or Ctrl-click — starts a selection. Shift-click picks
a range. The bar at the foot of the grid is everything a selection can be done
to: collections, keywords, presets, export, and merging to a panorama.
![Twelve photographs selected, with the selection bar along the foot of the grid](media/library-selection.png)
`Keywords` on that bar opens a sheet; type a word and press return, and it
is on every photograph selected. The list below the field is every keyword
the library has, ticked where the selection carries it.
![Keywording twelve frames](media/library-keywords.gif)
### Collections
`+` at the head of the sidebar makes one. Drag a photograph — or the whole
selection — onto its row to file it there; click the row to see it. A
photograph can be in several, and the badge on its cell counts them.
![Filing photographs in a collection by dragging them onto it](media/library-collections.gif)
## Developing a photograph
Click a thumbnail to open it. The column on the right is every adjustment;
the strip at its head narrows it to one group.
![The develop view: the photograph, the histogram, and the adjustment column](media/develop.png)
![Switching between the Optics, Light, Colour, Effects and Detail groups](media/develop-groups.gif)
### Light
Exposure, contrast, highlights, shadows, blacks, whites and a tone curve.
Hold `Before` to see the photograph as it was.
![Raising exposure, pulling the highlights, lifting the shadows, then holding Before](media/develop-light.gif)
### Looking closer
Double-click for 1:1; drag to move about; double-click again to fit. The
wheel zooms to any amount in between.
![Zooming to 1:1, panning, and back](media/develop-zoom.gif)
### White balance from the photograph
Press `pick` in the White Balance group, then click something neutral —
a white wall, a grey card, the air conditioner here. The picker sets the
sliders from the photograph, not from where they were: below, the frame
is dragged cold first and one click puts it right. A blown highlight is
refused, since a clipped pixel has no colour left to balance.
![Cooling the frame with the slider, then picking a white air conditioner to set the white balance](media/develop-wb.gif)
### Composing
Crop by dragging the frame's corners, straighten with the slider, lock a
ratio from the chips. `Done composing` returns to the photograph.
![Cropping, straightening and choosing a ratio](media/compose.gif)
### Local adjustments
`Local` in the rail turns the column into a mask stack. `Find subjects` runs a
segmentation model over the photograph; what it recognises appears as a list
of categories with how much of the frame each covers. Click one and it is a
mask — then every slider below edits only that region.
![What the model found in an urban scene: ground, architecture, sky, vegetation](media/local-categories.png)
![The sky chosen: tinted on the photograph, and the column now scoped to it](media/local-segment.png)
A mask is a stack of parts. Paint into it, subtract a gradient from it, grow
or shrink its edge, choose how it falls off. `Show masks as` draws the mask
tinted, as alpha, or as an outline; the eye on its row switches it off.
![Looking at the mask three ways, painting into it, then growing its edge](media/local-paint.gif)
Linear and radial gradients, a tone range and a colour range are the other
ways to make one; each can be combined with any other.
### Repair
`Repair` in the rail: click a mark and it is covered from a source DarkRoom
chooses beside it. Drag either circle to move it; the size, feather and
opacity are in the panel. Heal blends; clone copies.
![Covering marks on a road](media/repair.gif)
### Film
The `Film` chooser at the head of Adjust applies a spectral simulation of a
named stock; below it, the print exposure and push controls a film has and a
sensor does not.
![Choosing Velvia, then holding Before](media/film.gif)
### History, snapshots, presets
Every change is a step; `Undo` and the History panel walk them. `Snapshot`
keeps the current state under a name. `Presets…` saves the settings to
apply elsewhere, and imports `.xmp` from other applications.
![The presets sheet](media/presets.png)
## Merging a panorama
Select the frames, then `Merge to panorama` from the selection bar. The
frames are read, aligned, and drawn on the suggested projection with each one
outlined where it landed — twelve hand-held portrait frames across an alpine
valley, here. Change the projection (a 150° sweep on a flat perspective is
what the middle of the film shows, and why cylindrical is suggested), ask for
the border to be filled rather than cropped, then `Merge`. The composite is
written beside its sources as a DNG and appears in the grid with the merge
as the first step in its history.
![Twelve frames aligned, the projections tried, and the border filled](media/panorama.gif)
![The alignment on a cylinder, each frame outlined where it landed](media/panorama-aligned.png)
![The same, with the ragged border filled by the model rather than cropped away](media/panorama-filled.png)
## Export
`Export` in the develop header, or `Export N` from a selection. Format,
size, colour space, sharpening, naming and where the file goes are in
Settings, and apply to every export until changed. An export with no folder
set is refused, and the header says so.
![Export defaults in Settings](media/settings-export.png)
## Settings
![The settings page: background activity, indexing, storage, display](media/settings.png)
Background activity with progress, thumbnail and face indexing, storage on
this device, display and colour, export defaults, what is written to XMP
sidecars, and a diagnostics bundle for a bug report.
## People
Face detection and identity run over the library and group faces by person;
the `Identity` page is where suggestions are confirmed, rejected and split,
and `People` on the filter bar narrows the grid to someone. Not pictured
here, for the obvious reason — [faces.md](../faces.md) has the design.
## Where things are written down
| Feature | Design |
|---|---|
| Local masks and segmentation | [segmentation.md](../segmentation.md), [mask-editing.md](../mask-editing.md) |
| Repair | [spot-removal.md](../spot-removal.md) |
| Panorama | [panorama.md](../panorama.md) |
| Faces and identity | [faces.md](../faces.md) |
| Gestures, generated from the code | [gestures.md](../gestures.md) |
| Navigation and layout | [ui-navigation.md](../ui-navigation.md) |
| Sync and storage | [storage.md](../storage.md) |
## How this page is made
[`tools/manual/`](../../tools/manual/README.md) drives the desktop build on
a private X server and records each scene; `record.sh <library>` re-makes
every picture here. Run it after a change to the interface and commit what
changed. The pictures are in LFS.
Making it the first time turned up nine faults, each fixed in its own
commit before the pictures were taken: the folder picker could not choose
the top level, month headings overprinted each other, a category mask
widened the column off the window, the mask tint outlived its mode, the
first sync uploaded an empty thumbnail shard, a merge that ran out of GPU
memory left the page on Stop for ever, the export settings promised to ask
for a folder and did not, the keyword sheet sent its keys to the grid, and
an empty trash told you to check your library folder.
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