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<h1 id="scene-actor-extraction">scene-actor-extraction<a class="headerlink" href="#scene-actor-extraction" title="Permanent link">&para;</a></h1>
<p>A face-recognition pipeline that finds when each actor appears on screen in a
film or TV episode — built on <a href="https://gitea.tourolle.paris/dtourolle/KPN">KPN++</a>
(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.</p>
<h2 id="start-here-four-questions-this-bake-off-answers">Start here — four questions this bake-off answers<a class="headerlink" href="#start-here-four-questions-this-bake-off-answers" title="Permanent link">&para;</a></h2>
<ul>
<li><strong><a href="best-model/">Which model is best?</a></strong> — calibration curves first
(discriminative power, independent of any threshold), then F1 on the actual
benchmark. LVFace-B Glint360K wins both.</li>
<li><strong><a href="gallery-scope/">Whole gallery vs. limited (cast-restricted) gallery</a></strong> —
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.</li>
<li><strong><a href="pose-expansion/">Does pose expansion help?</a></strong> — 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.</li>
<li><strong><a href="lvface-deep-dive/">Deep dive: LVFace-B Glint360K</a></strong> — 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.</li>
</ul>
<h2 id="the-full-technical-log">The full technical log<a class="headerlink" href="#the-full-technical-log" title="Permanent link">&para;</a></h2>
<ul>
<li><strong><a href="rep4-optimizer-results/">Rep4 model bake-off + threshold re-tune</a></strong> —
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 <code>src/config.hpp</code>
defaults come from.</li>
<li><strong><a href="optimizer-experiments/">Optimizer experiments (prior round)</a></strong> — the
earlier scene-union-metric tuning pass, superseded by the per-second metric
used in rep4 but kept for the ground-truth/architecture background.</li>
<li><strong><a href="service-conversion/">Service conversion (proposal)</a></strong> — design sketch
for an idle-GPU Docker worker, not yet built.</li>
</ul>
<h2 id="reproducing-the-benchmarks">Reproducing the benchmarks<a class="headerlink" href="#reproducing-the-benchmarks" title="Permanent link">&para;</a></h2>
<p>Gallery <code>.h5</code> files, embedding dumps, the X-Ray corpus, montage frame images,
and DE trajectories are not committed to this repository — they're pushed to
the Gitea package registry and pulled on demand:</p>
<div class="language-bash highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a>scripts/artifacts/pull_artifacts.sh<span class="w"> </span>galleries
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a>scripts/artifacts/pull_artifacts.sh<span class="w"> </span>experiment-data
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a>scripts/artifacts/pull_artifacts.sh<span class="w"> </span>montage-frames<span class="w"> </span>&lt;film-slug&gt;
</span></code></pre></div>
<p>See <code>scripts/artifacts/push_artifacts.sh</code> for the upload side (requires a
<code>GITEA_TOKEN</code> with package write scope).</p>
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