feat(ml): cadence-based video frame sampling + min-frame tag aggregation (#747)

Video tag noise root cause: frames were a FIXED count (6) max-pooled — a tag
firing on one frame survived at peak confidence, and a fixed count under-samples
long multi-scene videos so real scene-local tags looked like noise.

Redesign (operator-steered):
- Sample at a fixed CADENCE — one frame every `video_frame_interval_seconds`
  (default 4) across the 5–95% window — so a tag's frame-presence reflects real
  screen time independent of video length. Capped at `video_max_frames` (default
  64): a long video stretches the spacing instead of exploding into hundreds of
  inferences, bounding per-video cost on the single ml-worker (per-frame ffmpeg
  timeout also cut 60s→30s).
- Aggregate with `_aggregate_video_predictions`: keep a tag only if it appears in
  >= `video_min_tag_frames` sampled frames (≈ that many × interval seconds on
  screen — duration-independent noise rejection), with confidence = MEAN over the
  frames it appears in (not max). Clamps the threshold to the sample count so a
  1–2-frame short video still tags.
- All three knobs are DB-backed ml_settings (migration 0053), patchable via
  /api/ml/settings + sliders in the ML settings card — replaces the
  VIDEO_ML_FRAMES env var (product-not-project).

Tests: aggregation drops one-frame noise + means corroborated tags + clamps on
short videos; settings round-trip + min>max validation. Replaced the
_maxpool_predictions unit test.

NOTE: this is the QUALITY half of #747. The perf half — the ml-worker runs
CPU-only — is GPU enablement, tracked separately in #872.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

backend/app/models/ml_settings.py

@@ -40,6 +40,21 @@ class MLSettings(Base):
     min_reference_images: Mapped[int] = mapped_column(
         Integer, nullable=False, default=5
     )
+    # Video tagging (#747). Sample one frame every N seconds (fixed CADENCE, not a
+    # fixed count) so a tag's frame-presence reflects real screen time regardless
+    # of video length; cap the total so a long video can't explode into hundreds
+    # of inferences (the cadence stretches past the cap). A tag is kept only if it
+    # appears in >= video_min_tag_frames sampled frames (≈ that many × interval
+    # seconds on screen) — duration-independent noise rejection. Operator-tunable.
+    video_frame_interval_seconds: Mapped[float] = mapped_column(
+        Float, nullable=False, default=4.0
+    )
+    video_max_frames: Mapped[int] = mapped_column(
+        Integer, nullable=False, default=64
+    )
+    video_min_tag_frames: Mapped[int] = mapped_column(
+        Integer, nullable=False, default=3
+    )
     tagger_model_version: Mapped[str] = mapped_column(
         String(128), nullable=False, default="camie-tagger-v2"
     )