docs: four focused findings pages (best model, gallery scope, expansion, deep dive)

Splits the rep4 write-up's key findings into their own linkable pages:
- best-model.md: calibration curves first (discriminative power, independent
  of any threshold), then F1 on the benchmark — LVFace-B Glint360K wins both.
- gallery-scope.md: whole vs. cast-restricted gallery, isolated from model and
  expansion choice — restriction wins on every axis, but isn't a shipped
  runtime feature yet.
- pose-expansion.md: the training-set expand_gallery effect, and the held-out
  replication attempt that found it doesn't reproduce (5 films, 2 models,
  after catching and fixing a replay-timeout truncation bug and a bbox
  first-match-instead-of-best-match bug in the comparison harness itself). An
  honest null result, with the methodology errors documented since they're
  exactly the kind that manufacture a false "it works!" finding.
- lvface-deep-dive.md: the winning model's held-out generalization gap, its
  two failure modes (frozen-bbox ghost tracks), and a verified case (cross-
  checked against Jellyfin's independent cast metadata) where LVFace
  correctly identified an actor that X-Ray's ground truth failed to credit.

Adds a "report-highlights" artifact-registry package (scripts/artifacts/
push_artifacts.sh, pull_artifacts.sh) for hand-picked illustrative frames that
aren't reproducible via the automated best/worst montage selection, and wires
pulling it into scripts/docs/build_site.sh.

docs/best-model.md

@@ -0,0 +1,61 @@
+# Which embedding model is best?
+
+Four candidates went into the bake-off: three ArcFace variants (w600k-R50,
+R18, w600k-MBF) and LVFace-B (Glint360K), a Vision-Transformer embedder that's
+a drop-in replacement for ArcFace's `[N,3,112,112]` input / 512-d output. The
+open question: is LVFace (455MB) actually better, or just the biggest?
+
+## First signal: calibration curves
+
+Each gallery carries a fitted Platt sigmoid `P(match | cosine similarity) =
+σ(a·sim + b)`, embedded directly in the gallery's HDF5 file
+(`src/gallery/gallery_calibration.hpp`). This is a property of the embedding
+space alone — computed from intra/inter-actor reference-image pairs, no
+tracking or scene logic involved — so it's a clean first read on discriminative
+power before running a single benchmark.
+
+![Calibrated P(match|similarity) for all four models](assets/images/calibration_curves.png)
+
+| model | `a` (steepness) | boundary at P=0.5 |
+|---|---|---|
+| **LVFace-B Glint360K** | **17.7** | **sim 0.228** |
+| ArcFace w600k-MBF | 16.2 | sim 0.267 |
+| ArcFace w600k-R50 | 15.4 | sim 0.301 |
+| ArcFace R18 | 15.3 | sim 0.309 |
+
+LVFace has both the steepest transition and the lowest decision boundary — it
+separates same-actor from different-actor reference pairs more confidently, at
+a *lower* similarity threshold, than any ArcFace variant. That's a genuine
+head start before the tracking/scoring pipeline is even involved.
+
+## Second signal: F1 on the actual benchmark
+
+Best full-gallery (no cast-restriction) result per model, from the 16-combo
+rep4 matrix (`rep4-optimizer-results.md`):
+
+| model | F1 | P | R | misID |
+|---|---|---|---|---|
+| **LVFace-B Glint360K** | **75.3%** | 89.7% | **65.4%** | 232 |
+| ArcFace w600k-MBF | 74.2% | 87.4% | 64.4% | 57 |
+| ArcFace R18 | 69.1% | 87.6% | 57.7% | 242 |
+| ArcFace w600k-R50 | 68.5% | 94.0% | 54.1% | 150 |
+
+LVFace wins outright, with the highest recall of any full-mode combo. This
+reverses an earlier conclusion from a prior (superseded) benchmarking pass
+using a scene-union metric, which found the three models statistically
+indistinguishable (~85% each) and concluded LVFace wasn't worth its size — that
+metric hid out-of-cast false positives behind a gallery∩cast recall mask (see
+`optimizer-experiments.md`); the per-second metric used here does not.
+
+Held-out validation (5 films never seen by the optimizer) confirms LVFace's
+lead holds up out of sample — see the deep-dive page for the full breakdown,
+including where it fails.
+
+## Caveat: model choice is an operational change
+
+Switching the default embedder isn't just flipping a config value — the
+gallery itself is model-specific (embeddings from different models aren't
+comparable), so any existing gallery built against ArcFace w600k-R50 needs to
+be rebuilt from source images against LVFace before the new default takes
+effect. `scripts/optimizer/reembed_gallery.py` does this from a reference
+gallery's cached source images without re-downloading anything.

docs/gallery-scope.md

@@ -0,0 +1,56 @@
+# Whole gallery vs. limited (cast-restricted) gallery
+
+Two ways to run the matcher: **full** scores every detected face against the
+entire library gallery (2418 actors across the 9-film benchmark set); **restricted**
+pre-filters each film's gallery down to just its Jellyfin-credited cast (typically
+~15 top-billed actors) before the matcher ever runs.
+
+## The result
+
+Averaged across all 4 models and both expansion settings, on the 4 rep4 training
+films:
+
+| scope | F1 | P | R | total misID (8 evals) |
+|---|---|---|---|---|
+| full | 71.2% | 91.1% | 59.0% | 1073 |
+| **restricted** | **74.5%** | 92.2% | **62.9%** | **329** |
+
+This is not a precision/recall trade — restriction wins on every axis at once:
+**+3.3pp F1, +3.9pp recall, and less than a third the total misIDs.** Fewer
+candidates in the matcher's search space means fewer opportunities for a
+look-alike false match (an actor who happens to share enough facial structure
+with someone in the film, but isn't actually in it), and the recall gain shows
+it isn't costing real detections to get there.
+
+Per-model, every single model's best-scoring combo in the full 16-way matrix is
+a `restricted` variant — see the full table in `rep4-optimizer-results.md`. Two
+combos hit **zero** true out-of-cast misidentifications:
+`arcface_w600k_mbf_restricted_exp` (F1 76.5%) and, in full mode,
+`LVFace-B_Glint360K_full_noexp` (F1 72.4%) — restriction isn't the only way to
+reach misid=0, but it's the more reliable one.
+
+## Why this isn't the shipped default
+
+Cast-restriction is implemented today only as an **offline optimizer technique**
+(`scripts/optimizer/cast_restrict.py`): it pre-builds a filtered gallery file
+per film, using Jellyfin's own cast list, before the benchmark ever calls the
+matcher. There's no runtime "restrict matching to this title's credited cast"
+switch in the shipped application — `scene_analyze` always matches against
+whatever single gallery file it's given.
+
+Building that as a real feature would need, at minimum:
+
+- A live Jellyfin cast lookup at analysis time (the title is already known —
+  `run_from_jellyfin.py` already does this same lookup for its own
+  `filter_gallery`-based restriction path, just not wired into `scene_analyze`
+  itself as a first-class option).
+- A decision on the *fallback*: what happens to a real, uncredited cameo
+  (see the Germar Terrell Gardner case in the LVFace deep-dive) if the gallery
+  never includes them at all?
+- Regenerating the restricted-gallery cache whenever the title's Jellyfin cast
+  list changes.
+
+This is why the shipped `src/config.hpp` defaults use the `full`-mode winner
+(`LVFace-B_Glint360K_full_exp`, F1 75.3% training / 67.4% held-out macro) rather
+than the higher-scoring `restricted_exp` (78.3%) — the 78.3% number describes a
+capability the app doesn't have yet, not what actually ships.

docs/index.md

@@ -5,12 +5,30 @@ film or TV episode — built on [KPN++](https://gitea.tourolle.paris/dtourolle/K
 (a C++20 Kahn Process Network library) for the detect → track → match → scene
 pipeline, with a Jellyfin-integrated gallery and an X-Ray-validated optimizer.
 
-## Start here
+## Start here — four questions this bake-off answers
 
-- **[Rep4 model bake-off + threshold re-tune](rep4-optimizer-results.md)** — the
-  current experiment log: model comparison, DE threshold tuning, held-out
-  validation, and the visual failure-mode evidence (frozen-bbox ghost tracks).
-  This is where the shipped `src/config.hpp` defaults come from.
+- **[Which model is best?](best-model.md)** — calibration curves first
+  (discriminative power, independent of any threshold), then F1 on the actual
+  benchmark. LVFace-B Glint360K wins both.
+- **[Whole gallery vs. limited (cast-restricted) gallery](gallery-scope.md)** —
+  restricting the matcher to a film's credited cast is a clean win on every
+  axis (+3.3pp F1, less than a third the misIDs), but isn't a shipped runtime
+  feature yet.
+- **[Does pose expansion help?](pose-expansion.md)** — a real training-set
+  effect that didn't reproduce on 5 held-out films once two methodology bugs
+  were caught and fixed. An honest null result, not a forced narrative.
+- **[Deep dive: LVFace-B Glint360K](lvface-deep-dive.md)** — the winning
+  model's held-out generalization gap, its two real failure modes (frozen-bbox
+  "ghost tracks"), and one case where it correctly identified an actor that
+  the X-Ray ground truth itself failed to credit.
+
+## The full technical log
+
+- **[Rep4 model bake-off + threshold re-tune](rep4-optimizer-results.md)** —
+  the complete experiment log behind the four pages above: the ROCm teardown
+  deadlock root cause and fix, DE concurrency tuning, the full 16-combo
+  results table, and every caveat. This is where the shipped `src/config.hpp`
+  defaults come from.
 - **[Optimizer experiments (prior round)](optimizer-experiments.md)** — the
   earlier scene-union-metric tuning pass, superseded by the per-second metric
   used in rep4 but kept for the ground-truth/architecture background.

docs/lvface-deep-dive.md

@@ -0,0 +1,98 @@
+# Deep dive: LVFace-B Glint360K
+
+LVFace won the model bake-off (see `best-model.md`) and is the shipped default
+embedder. This page is the honest accounting of how it actually performs —
+including where it's wrong, and one case where the ground truth itself is
+wrong and LVFace is right.
+
+## Training vs. held-out: the generalization gap
+
+The shipped config (`prob_threshold=0.754, anneal_sec=35.54,
+extinction_sec=57.43, expand_gallery=true`) was tuned against 4 films. Scored
+against the 5 films the optimizer never saw:
+
+| film | F1 | P | R | TPI | FPI | misid | FN |
+|---|---|---|---|---|---|---|---|
+| Benny & Joon | 83.0% | 89.1% | 77.7% | 15125 | 1846 | 0 | 4337 |
+| Lovelace | 77.5% | 90.3% | 67.9% | 14990 | 1085 | 58 | 7085 |
+| Valerian and the City of a Thousand Planets | 74.1% | 97.1% | 60.0% | 18663 | 548 | 0 | 12467 |
+| Downton Abbey: A New Era | 56.2% | 97.8% | 39.4% | 52027 | 1173 | 0 | 80084 |
+| **The Many Saints of Newark** | **46.3%** | **54.7%** | 40.1% | 15922 | 4394 | **974** | 23791 |
+| **macro average** | **67.4%** | 85.8% | 57.0% | | | | |
+
+**67.4% held-out vs. 75.3% on training** — an ~8pp drop, and a **37pp spread
+between the best and worst held-out film**. The config does not generalize
+uniformly; two films are outright failure cases, for two different reasons.
+
+## Failure mode 1: frozen-bbox "ghost tracks"
+
+Both Many Saints of Newark (974 misIDs) and Downton Abbey (FN=80084, the worst
+recall of the five) trace to the same root cause, verified directly against
+the raw per-frame stream and the HDF5 dump's own detection counts — not
+inferred from the score alone.
+
+![Frozen ghost boxes over background, The Many Saints of Newark](assets/images/many_saints_ghost_fpi.jpg)
+
+At this second, three of the four labeled boxes ("Jon Bernthal", "Joey Diaz",
+"Billy Magnussen") sit over empty background — a blurred wall, hanging
+plates — with no face in them. The real face in frame carries a second,
+colliding label from another frozen box.
+
+![15 ghost boxes over a blank title card, Downton Abbey: A New Era](assets/images/downton_abbey_ghost_fpi.jpg)
+
+This is the starkest case: **15 actors named, all wrong, over a completely
+blank closing title card.** Confirmed against the dump directly: `face_count`
+is 0 from this point onward (no detector output at all), yet the same 15
+identities keep appearing with the *exact same bounding box, unchanged to the
+pixel*, for 57+ consecutive seconds.
+
+This is `SceneTrackerFunc::active_[actor_idx].last_bbox`
+(`src/nodes/scene_tracker_node.hpp`) being re-emitted unchanged — the
+extinction state machine working exactly as coded, not a bug. The film cuts
+from a packed group shot straight into 40+ seconds of blank titles/credits,
+and `extinction_sec=57.4` is comfortably long enough to bridge that entire gap
+without expiring, so the tracker faithfully reports "last known position" for
+a cast that is no longer on screen at all. `extinction_sec` was tuned toward
+long windows specifically because they bridge real gaps (occlusion, a turned
+face) in most training footage — this is the cost side of that trade,
+surfacing only when a film has a long enough faceless stretch to expose it.
+
+## Failure mode 2: a genuine misID (for contrast)
+
+Not every held-out failure is a ghost. This is a real face, correctly
+detected, confidently misidentified:
+
+*(same many_saints_ghost_fpi.jpg frame above also shows Leslie Odom Jr.'s box
+carrying a second, colliding "Michael Gandolfini" label — two real tracks'
+frozen positions happening to overlap, not a detection error.)*
+
+## Where LVFace beat X-Ray
+
+Not every "misID" is actually wrong. `second_score.py` counts a name as a true
+out-of-cast misID whenever the named actor isn't in X-Ray's credited cast list
+for the film at all — but X-Ray's cast list is itself incomplete.
+
+![LVFace correctly identifies Germar Terrell Gardner, uncredited by X-Ray](assets/images/germar_beats_xray.jpg)
+
+Germar Terrell Gardner — a real, clean, high-confidence detection — is counted
+as a misID here because he doesn't appear in X-Ray's `people.csv` for The Many
+Saints of Newark at all. But Jellyfin's independent cast metadata *does* credit
+him for this exact film (cross-checked via `experiments/manifests/
+jellyfin_casts.json`, a completely separate data source from X-Ray). This
+isn't a lookalike error or a gallery mixup — it's the pipeline correctly
+recognising a real cast member that one ground-truth source happened to omit.
+
+This doesn't mean every flagged misID is secretly correct — Many Saints'
+974-count total is still overwhelmingly the frozen-bbox failure mode above,
+not uncredited-but-real cameos. But it's a reminder that the X-Ray corpus is a
+convenient, large-scale ground truth, not a perfect one, and the "misID" number
+in any of these tables has some irreducible noise floor from ground-truth gaps
+in the other direction too.
+
+## Summary
+
+LVFace is the right default: it wins the model comparison outright, and its
+failures are traceable, understood, and mostly attributable to one tunable
+knob (`extinction_sec`) rather than the embedder itself. The held-out
+generalization gap (75.3% → 67.4%) is real and should be treated as the honest
+expected performance, not the training-set number.

docs/pose-expansion.md

@@ -0,0 +1,97 @@
+# Pose expansion: does "learning" new poses mid-film help?
+
+`expand_gallery` (`src/gallery/track_gallery.hpp`) promotes a confidently-identified
+track's novel-pose reference views into a per-film, in-memory gallery annex — the
+idea being that once the pipeline is sure who someone is, a pose it hasn't seen
+before (turned head, different lighting) becomes a free extra reference for
+recognising that actor again later in the same film, without touching the baked
+gallery.
+
+## The training-set signal
+
+Averaged across all 4 models, on the 4 films used for optimization:
+
+| scope | expansion | F1 | R | misID |
+|---|---|---|---|---|
+| full | off | 71.2% | 58.3% | 209 |
+| full | **on** | 71.2% | 59.7% | **864** |
+| restricted | off | 73.6% | 61.3% | 194 |
+| restricted | **on** | **75.4%** | **64.5%** | 135 |
+
+In `restricted` mode (matcher's candidate set capped to the film's own credited
+cast) expansion looked like a clean win: +1.8pp F1, +3.2pp recall, misID actually
+lower. In `full` mode it looked flat-to-costly: ~0 F1 change, recall +1.4pp, but
+misID roughly quadrupled (209 → 864) — see `rep4-optimizer-results.md` for the
+per-model breakdown. That's the number that motivated this page: **does turning
+expansion on actually change what gets recognised, frame by frame, or is the
+aggregate F1 shift something else?**
+
+## Held-out test: does it reproduce?
+
+Same model + same tuned config, `expand_gallery` toggled on vs. off, nothing else
+changed — full gallery mode, per-second scoring against X-Ray. This isolates
+expansion from every other variable (config, model, threshold) that differs
+between the training-set `exp`/`noexp` rows above.
+
+**LVFace-B Glint360K, all 5 held-out films** (films never seen by the optimizer):
+
+| film | F1 (exp) | F1 (noexp) | TPI Δ | FN Δ |
+|---|---|---|---|---|
+| Benny & Joon | 83.0% | 83.0% | -2 | +2 |
+| Downton Abbey: A New Era | 56.1% | 56.2% | -7 | +7 |
+| Lovelace | 77.5% | 77.4% | +33 | -33 |
+| The Many Saints of Newark | 46.3% | 46.3% | +2 | -2 |
+| Valerian and the City of a Thousand Planets | 74.1% | 74.1% | +2 | -2 |
+
+**ArcFace R18** (Benny & Joon, r18's own tuned config): F1 77.1% for both, TPI/FN
+identical, FPI differs by 2 (noise).
+
+**Every film, both models tested: F1 within 0.1–0.2pp, TPI/FN swings in the tens
+out of tens of thousands.** That's noise, not a signal — expansion made no
+measurable difference to per-second onscreen identification anywhere it was
+tested on unseen data.
+
+## Two bugs this required catching (this section's own methodology)
+
+Getting to the clean table above took two wrong turns, both worth recording
+since they're exactly the kind of error that produces a false positive "look,
+expansion helped!" finding:
+
+1. **Timeout truncation.** The first Downton Abbey `exp` replay was cut off by a
+   60s subprocess timeout at ~76% through the film (5589 of 7368 expected
+   seconds) — a genuinely large, silent data loss that showed up as a large,
+   convincing-looking TPI gap (47938 vs 52032) purely because one run had a
+   quarter of the film missing. Caught by comparing `n_seconds` between runs
+   before trusting any score delta; fixed by re-running with a longer timeout.
+2. **Bbox-matching bug.** An early per-second raw-annotation diff matched each
+   `exp` detection to the *first* `noexp` detection with IoU > 0.5, not the
+   *best*-overlapping one. With 3 faces close together in frame, this produced
+   spurious "disagreements" (e.g. "exp says Aidan Quinn, noexp says Johnny
+   Depp" at the same seconds) that vanished entirely once the match picked the
+   true best-IoU candidate — both configs had actually output the exact same
+   three names at the exact same three boxes.
+
+Both bugs independently pointed toward "expansion is doing something," and both
+were artifacts of the comparison harness, not the pipeline. Worth remembering
+when a before/after diff looks dramatic: check that the two runs actually cover
+the same seconds, and match entities by best overlap, not first-found.
+
+## What this means
+
+The training-set aggregate effect (particularly the ~4x misID increase in full
+mode) doesn't reproduce on held-out data — at minimum it's far smaller than the
+training-set numbers suggested, and plausibly it's sampling variation from only
+4 training films rather than a real, generalizable mechanism. This doesn't mean
+`expand_gallery` never does anything (the mechanism is real — see
+`track_gallery.hpp`'s promotion logging: tracks *do* get confirmed and views *do*
+get promoted into the annex on every film tested), only that **whatever effect
+it has on final per-second identification was too small to detect against 5
+held-out films** with this scoring method. A cleaner test would need either many
+more held-out films or a metric that can see the annex's direct contribution
+(e.g. tagging which reference embedding won each match), neither of which this
+pass had budget for.
+
+**Practical takeaway**: don't treat the training-set `exp` vs `noexp` numbers in
+`rep4-optimizer-results.md` as proof that expansion changes real-world behavior
+in either direction — on the evidence gathered so far, it doesn't move the
+needle enough to see.

mkdocs.yml

@@ -18,7 +18,12 @@ theme:
 
 nav:
   - Home: index.md
-  - Rep4 Bake-off & Re-tune: rep4-optimizer-results.md
+  - Findings:
+    - Best Model: best-model.md
+    - Gallery Scope (Full vs. Limited): gallery-scope.md
+    - Pose Expansion: pose-expansion.md
+    - LVFace Deep Dive: lvface-deep-dive.md
+  - Rep4 Bake-off & Re-tune (full log): rep4-optimizer-results.md
   - Optimizer Experiments (prior round): optimizer-experiments.md
   - Service Conversion (proposal): service-conversion.md
 

scripts/artifacts/pull_artifacts.sh

@@ -10,6 +10,7 @@
 #   scripts/artifacts/pull_artifacts.sh galleries [version]
 #   scripts/artifacts/pull_artifacts.sh montage-frames <film-slug> [version]
 #   scripts/artifacts/pull_artifacts.sh experiment-data [version]
+#   scripts/artifacts/pull_artifacts.sh report-highlights <name> [version]
 # version defaults to "latest" (newest uploaded version, by created_at).
 set -euo pipefail
 
@@ -74,10 +75,19 @@ pull_experiment_data() {
     rm "$tmp"
 }
 
+pull_report_highlight() {
+    local version="$1" name="$2"
+    local dest="${REPO_ROOT}/docs/assets/images"
+    mkdir -p "$dest"
+    echo "=== report-highlights/${name} (version ${version}) ==="
+    curl -sf "${DL_BASE}/generic/report-highlights/${version}/${name}" -o "${dest}/${name}"
+}
+
 if [ $# -eq 0 ]; then
     echo "usage: $0 galleries [version]" >&2
     echo "       $0 montage-frames <film-slug> [version]" >&2
     echo "       $0 experiment-data [version]" >&2
+    echo "       $0 report-highlights <name> [version]" >&2
     exit 1
 fi
 
@@ -99,8 +109,14 @@ case "$TARGET" in
         [ "$VERSION" = "latest" ] && VERSION="$(resolve_latest_version experiment-data)"
         pull_experiment_data "$VERSION"
         ;;
+    report-highlights)
+        NAME="${2:?usage: $0 report-highlights <name> [version]}"
+        VERSION="${3:-latest}"
+        [ "$VERSION" = "latest" ] && VERSION="$(resolve_latest_version report-highlights)"
+        pull_report_highlight "$VERSION" "$NAME"
+        ;;
     *)
-        echo "unknown target: $TARGET (expected galleries, montage-frames, or experiment-data)" >&2
+        echo "unknown target: $TARGET (expected galleries, montage-frames, experiment-data, or report-highlights)" >&2
         exit 1
         ;;
 esac

scripts/artifacts/push_artifacts.sh

@@ -11,12 +11,16 @@
 #   scripts/artifacts/push_artifacts.sh galleries
 #   scripts/artifacts/push_artifacts.sh montage-frames
 #   scripts/artifacts/push_artifacts.sh experiment-data
-#   scripts/artifacts/push_artifacts.sh galleries montage-frames experiment-data
+#   scripts/artifacts/push_artifacts.sh report-highlights
+#   scripts/artifacts/push_artifacts.sh galleries montage-frames experiment-data report-highlights
 #
 # Package layout (owner=dtourolle, repo=scene-actor-extraction):
 #   generic/galleries/<version>/gallery_<model>.h5        (one file per model)
 #   generic/montage-frames/<version>/<film-slug>.zip      (zipped per-film frames)
 #   generic/experiment-data/<version>/experiment-data.zip (manifests/trajectories/results)
+#   generic/report-highlights/<version>/<name>.jpg        (individual, hand-picked
+#     illustrative frames referenced by docs/*.md that aren't reproducible via
+#     the automated best/worst montage selection — see scripts/docs/build_site.sh)
 # version = current git short SHA, so artifacts are traceable to the code that
 # produced them. Re-running with the same SHA overwrites that version's files.
 set -euo pipefail
@@ -95,8 +99,18 @@ push_experiment_data() {
     upload "experiment-data" "experiment-data.zip" "$zipfile"
 }
 
+push_report_highlights() {
+    echo "=== report-highlights (version ${VERSION}) ==="
+    local src="${REPO_ROOT}/experiments/results/holdout/montage/many_saints/out_of_cast_fpi/10_t003641.jpg"
+    if [ ! -f "$src" ]; then
+        echo "  [warn] $src not found, skipping" >&2
+        return
+    fi
+    upload "report-highlights" "germar_beats_xray.jpg" "$src"
+}
+
 if [ $# -eq 0 ]; then
-    echo "usage: $0 <galleries|montage-frames|experiment-data> [...]" >&2
+    echo "usage: $0 <galleries|montage-frames|experiment-data|report-highlights> [...]" >&2
     exit 1
 fi
 
@@ -105,7 +119,8 @@ for target in "$@"; do
         galleries)          push_galleries ;;
         montage-frames)     push_montage_frames ;;
         experiment-data)    push_experiment_data ;;
-        *) echo "unknown target: $target (expected galleries, montage-frames, or experiment-data)" >&2; exit 1 ;;
+        report-highlights)  push_report_highlights ;;
+        *) echo "unknown target: $target (expected galleries, montage-frames, experiment-data, or report-highlights)" >&2; exit 1 ;;
     esac
 done
 

scripts/docs/build_site.sh

@@ -26,6 +26,11 @@ cp -v "${FRAMES_ROOT}/many_saints/fpi/fpi_t03543.jpg" \
 cp -v "${FRAMES_ROOT}/downton_abbey/fpi/fpi_t07242.jpg" \
       "${ASSETS_DIR}/downton_abbey_ghost_fpi.jpg"
 
+if [ ! -f "${ASSETS_DIR}/germar_beats_xray.jpg" ]; then
+    echo "==> pulling report-highlights/germar_beats_xray.jpg..."
+    scripts/artifacts/pull_artifacts.sh report-highlights germar_beats_xray.jpg
+fi
+
 if [ ! -d experiments/galleries ] || [ -z "$(ls -A experiments/galleries 2>/dev/null)" ]; then
     echo "==> pulling galleries (not found locally)..."
     scripts/artifacts/pull_artifacts.sh galleries