Make per-clip sidecar JSONs opt-in (default off)

Previously every video_target_pipeline cut wrote a <uuid>.json provenance
sidecar alongside each <uuid>.mp4. The same provenance is already in the
per-batch plan.json, so the per-clip sidecars are redundant unless a
downstream tool wants each clip self-describing in isolation.

- video_target_pipeline.py cut: new --write-sidecar flag, default off.
- run_video_pipeline.sh: new SIDECAR env var (default "no"), passes
  --write-sidecar when SIDECAR=yes.
- README + docs/analysis/video-target-preprocessing.md updated.

The 1,984 already-emitted sidecars in /mnt/x/src/vd/ct/ct_src_*/ have
been deleted (1.5 MB).

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

README.md

@@ -343,7 +343,7 @@ clean it up over time:
 | `work/consolidate_facesets.py` | Merge duplicate identities (centroid cosine sim ≥ 0.55 with confident ≥ 0.65, **complete-linkage** to defeat single-link chaining). Pulls embeddings from cache, no GPU. See `docs/analysis/identity-consolidation-and-age-extend.md`. |
 | `work/age_extend_001.py` | Slot newly-added PNGs into existing era buckets of `faceset_001` (anchor cosine distance ≤ 0.40 AND `|year_delta|` ≤ 5). Same anchor-fragment rule as `age_split_001.py`. |
 | `work/dedup_optimize.py` (+ Windows `work/multiface_worker.py`) | (a) cross-family SHA256 byte-dedup, (b) within-faceset near-dup at cosine sim ≥ 0.95, (c) multi-face audit (re-detect via insightface, drop PNGs with face_count ≠ 1). Multi-face is the load-bearing roop invariant. See `docs/analysis/dedup-and-roop-optimization.md`. |
-| `work/video_target_pipeline.py` (+ Windows `work/video_face_worker.py` + `work/run_video_pipeline.sh` chain) | Target-side preprocessing: scan a folder of videos → PySceneDetect shot-cuts → 2 fps frame sampling → DML face detection + embedding → IoU+embedding tracking → quality-gated segments (yaw≤75°, face≥80px, det≥0.5, ≥70% pass-rate, 1–120s duration, 2s cross-track merge gap) → ffmpeg stream-copy into UUID-named clips with sidecar JSON. Output organized into per-source subfolders. See `docs/analysis/video-target-preprocessing.md`. |
+| `work/video_target_pipeline.py` (+ Windows `work/video_face_worker.py` + `work/run_video_pipeline.sh` chain) | Target-side preprocessing: scan a folder of videos → PySceneDetect shot-cuts → 2 fps frame sampling → DML face detection + embedding → IoU+embedding tracking → quality-gated segments (yaw≤75°, face≥80px, det≥0.5, ≥70% pass-rate, 1–120s duration, 2s cross-track merge gap) → ffmpeg stream-copy into UUID-named clips. Output organized into per-source subfolders. Provenance sidecars are opt-in (`cut --write-sidecar` or `SIDECAR=yes` env var); the full plan is always retained in the per-batch `plan.json`. See `docs/analysis/video-target-preprocessing.md`. |
 
 All four operate idempotently and reversibly: dropped PNGs go to
 `<faceset>/faces/_dropped/`, quarantined whole facesets go to

docs/analysis/video-target-preprocessing.md

@@ -38,10 +38,11 @@ run_video_pipeline.sh (chain driver)
    └─ report       (HTML preview)
 
    Output: <output_dir>/<source_video_stem>/<uuid>.mp4
-                                           /<uuid>.json (sidecar)
+                                           /<uuid>.json (sidecar; opt-in via
+                                                          --write-sidecar)
 ```
 
-`run_video_pipeline.sh` is parameterized via env vars (`WORK`, `INPUT_DIR`, `OUTPUT_DIR`, `FILTER_FROM`, `SKIP_PATTERN`, `MAX_DUR`, `IDENTITY`) so you can pin a particular batch without editing the script.
+`run_video_pipeline.sh` is parameterized via env vars (`WORK`, `INPUT_DIR`, `OUTPUT_DIR`, `FILTER_FROM`, `SKIP_PATTERN`, `MAX_DUR`, `IDENTITY`, `SIDECAR`) so you can pin a particular batch without editing the script. Sidecars are off by default — the per-batch `plan.json` always carries the full provenance for every clip; the `<uuid>.json` files alongside the clips are redundant and only useful if you need each clip to be self-describing in isolation.
 
 ## 3. Quality signals (matched to inswapper_128's working envelope)
 

work/run_video_pipeline.sh

@@ -15,6 +15,7 @@
 #   SKIP_PATTERN regex of basenames to exclude (Python `re` syntax). Applied AFTER FILTER_FROM.
 #   MAX_DUR      score --max-dur (default 120)
 #   IDENTITY     "yes" to enable identity tagging; default "no"
+#   SIDECAR      "yes" to emit <uuid>.json provenance sidecars; default "no"
 
 set -e
 
@@ -23,6 +24,7 @@ set -e
 : ${OUTPUT_DIR:=/mnt/x/src/vd/ct}
 : ${MAX_DUR:=120}
 : ${IDENTITY:=no}
+: ${SIDECAR:=no}
 
 mkdir -p "$WORK" "$WORK/scenes"
 
@@ -37,7 +39,7 @@ log() { echo "[$(ts)] [$PHASE] $*"; }
 
 PHASE="setup"
 log "STARTED — host=$(hostname) pid=$$ work=$WORK"
-log "config: input=$INPUT_DIR output=$OUTPUT_DIR filter_from=${FILTER_FROM:-<none>} skip_pattern=${SKIP_PATTERN:-<none>} max_dur=$MAX_DUR identity=$IDENTITY"
+log "config: input=$INPUT_DIR output=$OUTPUT_DIR filter_from=${FILTER_FROM:-<none>} skip_pattern=${SKIP_PATTERN:-<none>} max_dur=$MAX_DUR identity=$IDENTITY sidecar=$SIDECAR"
 
 PHASE="inventory"
 log "building subset inventory"
@@ -110,7 +112,9 @@ log "done in $(($(date +%s)-T0))s"
 PHASE="cut"
 log "ffmpeg stream-copy into per-source subfolders (no --clean)"
 T0=$(date +%s)
-$PY_WSL $PIPELINE cut --plan "$WORK/plan.json" --output-dir "$OUTPUT_DIR"
+SIDECAR_FLAG=""
+if [ "$SIDECAR" = "yes" ]; then SIDECAR_FLAG="--write-sidecar"; fi
+$PY_WSL $PIPELINE cut --plan "$WORK/plan.json" --output-dir "$OUTPUT_DIR" $SIDECAR_FLAG
 log "done in $(($(date +%s)-T0))s"
 
 PHASE="report"

work/video_target_pipeline.py

@@ -722,7 +722,7 @@ def cmd_cut(args):
             if out_video.exists() and out_video.stat().st_size < 1024:
                 out_video.unlink()
             continue
-        # sidecar (alongside the clip in the source-named subfolder)
+        if args.write_sidecar:
             sidecar = seg_dir / f"{seg['uuid']}.json"
             sidecar.write_text(json.dumps({
                 "uuid": seg["uuid"],
@@ -901,6 +901,8 @@ def main():
     cu.add_argument("--force", action="store_true")
     cu.add_argument("--clean", action="store_true",
                     help="remove prior UUID-named clips before cutting (preserves non-UUID files)")
+    cu.add_argument("--write-sidecar", action="store_true",
+                    help="emit <uuid>.json provenance sidecar alongside each clip (default off)")
     cu.set_defaults(func=cmd_cut)
 
     rp = sub.add_parser("report")