Peter 998fa79f81 Add target-side video preprocessing pipeline ...

Preprocesses a folder of video files into UUID-named clips suitable as
target inputs for roop-unleashed-style face-swap. Counterpart to the
faceset (source-side) tooling.

work/video_target_pipeline.py — orchestration with subcommands
  scan / scenes / stage / merge / track / score / cut / report. Quality
  gates default to face-sets-can-handle-side-profile values (yaw<=75°,
  pitch<=45°, face_short>=80px, det>=0.5). Cross-track segment merge
  fuses adjacent-in-time tracks within the same scene up to 2s gap.
  Output organized into <output_dir>/<source_stem>/<uuid>.mp4 +
  <uuid>.json sidecar with full provenance.

work/video_face_worker.py — Windows DML face detect+embed worker. Uses
  JSONL append-only for results.jsonl: a critical perf fix (re-
  serializing the monolithic 245MB results.json on every flush was the
  dominant cost in the first attempt, dropping throughput to 0.5 fps).
  Append-only got it to 13+ fps, ~7.5 fps cumulative across the first
  6.18h batch. Also uses seek-once-per-video + sequential cap.grab()
  between samples to dodge cv2 per-sample seek pathology on long H.264.
  Legacy results.json is auto-migrated to .jsonl on first load.

work/run_video_pipeline.sh — generic chain driver, parameterized via
  WORK / INPUT_DIR / OUTPUT_DIR / FILTER_FROM / SKIP_PATTERN / MAX_DUR /
  IDENTITY env vars. work/status_video_pipeline.sh — generic status
  helper.

First production batch (ct_src_00050..00062, 13 files, 6.18h input):
600 emitted segments, 239.5min accepted content (64.6% of input), 254
segments built from >=2 tracks (cross-track merge), 1h43m wall clock.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

2026-04-27 21:38:50 +02:00

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