feat(ml): cadence-based video frame sampling + min-frame tag aggregation (#747)
CI / lint (push) Successful in 2s
CI / frontend-build (push) Successful in 18s
CI / backend-lint-and-test (push) Successful in 32s
CI / integration (push) Successful in 3m19s

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>
This commit is contained in:
2026-06-16 11:07:00 -04:00
parent 41652db20f
commit 369e3de684
7 changed files with 241 additions and 35 deletions
+30
View File
@@ -56,6 +56,36 @@ async def test_suggestion_threshold_below_store_floor_rejected(client):
assert "tagger_store_floor" in (await resp.get_json())["error"]
@pytest.mark.asyncio
async def test_video_tagging_settings_default_and_patch(client):
"""#747: video cadence/noise knobs are exposed + patchable."""
body = await (await client.get("/api/ml/settings")).get_json()
assert body["video_frame_interval_seconds"] == pytest.approx(4.0)
assert body["video_max_frames"] == 64
assert body["video_min_tag_frames"] == 3
resp = await client.patch(
"/api/ml/settings",
json={"video_frame_interval_seconds": 5, "video_max_frames": 40,
"video_min_tag_frames": 4},
)
assert resp.status_code == 200
out = await resp.get_json()
assert out["video_frame_interval_seconds"] == pytest.approx(5.0)
assert out["video_max_frames"] == 40
assert out["video_min_tag_frames"] == 4
@pytest.mark.asyncio
async def test_video_min_tag_frames_above_max_rejected(client):
resp = await client.patch(
"/api/ml/settings",
json={"video_max_frames": 10, "video_min_tag_frames": 20},
)
assert resp.status_code == 400
assert "video_min_tag_frames" in (await resp.get_json())["error"]
@pytest.mark.asyncio
async def test_backfill_and_recompute_trigger(client):
r1 = await client.post("/api/ml/backfill")