Fix matching regressions, cache guard, and multi-shot algorithm for beat 15
- config.toml: revert scoreable_luma/contrast thresholds to 24/58/24 (lowering them let cross-fade blend frames contaminate content-validation templates, dropping scores below provisional_content_threshold) - src/cv/global_scan.py: _is_dark_reference_frame now requires contrast<30 so genuine dark silhouette frames are not rejected as scoreable; two-path _is_scoreable_reference_frame separates standard vs fade-content scoring - cli.py: _keeps_cached_match() guard prevents a weaker single-span rematch from overwriting a better multi-segment provisional cache entry - cli.py: _fade_content_shots() restricted to between-island gaps only— pre-island black leaders were incorrectly emitted as matchable shots - cli.py: island[0] of _match_unmatched_visual_segments() now uses no continuity seed so an insert cut at the start of a multi-shot beat is not forced toward the previous beat's scene - scripts/generate_cutter_report.py: fix ffmpeg concat demuxer on Windows— use part.absolute().as_posix() so paths in the concat txt are absolute and not double-resolved relative to the concat file's directory Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -581,17 +581,68 @@ def _reference_scoreable_segments(beat, cfg) -> list[tuple[float, float]]:
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return merged
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def _fade_content_shots(beat, cfg) -> list[tuple[float, float]]:
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"""Find low-luma fade regions adjacent to visible islands that still carry
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describable content (e.g. a hand+knife silhouette during a cross-fade).
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These regions are too dark for CV template matching but vision can read
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structure during the fade — the matcher therefore treats them as their
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own shots and routes them through the vision-led search path.
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A fade region qualifies when, sampled inside the region, the brightest
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frame has p90 ≥ 12 (not pure black) and contrast ≥ 8 (some structure)
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AND the region duration is ≥ 0.2 s. Pure-black/featureless fades stay
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excluded.
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"""
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from src.cv.frame_extractor import grab_frame_at_path
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from src.cv.global_scan import _reference_visibility_stats
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islands = _reference_scoreable_segments(beat, cfg)
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if not islands:
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return []
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step_s = max(0.04, cfg.cv.deep_scan.span_sample_step_s)
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min_fade_s = 0.2
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def has_content(start_s: float, end_s: float) -> bool:
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if end_s - start_s < min_fade_s:
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return False
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peak_p90 = 0.0
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peak_contrast = 0.0
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t = start_s
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while t < end_s:
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frame = grab_frame_at_path(beat.trailer_path, beat.start_s + t)
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if frame is not None:
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_, p90, contrast = _reference_visibility_stats(frame, cfg)
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peak_p90 = max(peak_p90, p90)
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peak_contrast = max(peak_contrast, contrast)
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t = round(t + step_s, 6)
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return peak_p90 >= 12.0 and peak_contrast >= 8.0
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fades: list[tuple[float, float]] = []
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# Between-island fades only: these are genuine cross-fade silhouettes
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# (one visible shot dissolves into another through a dim middle frame).
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# Pre-island fades are fade-from-black leaders; post-island fades are
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# fade-to-black trailers — neither is a source-matchable shot on its own.
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for prev_isl, next_isl in zip(islands, islands[1:]):
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gap_start, gap_end = prev_isl[1], next_isl[0]
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if has_content(gap_start, gap_end):
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fades.append((gap_start, gap_end))
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return fades
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def _reference_shot_segments(beat, cfg) -> list[tuple[float, float]]:
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"""Source-matchable shot ranges inside a trailer beat.
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Like ``_reference_scoreable_segments`` but additionally splits each
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visible island at detected hard cuts (frame-to-frame correlation drops
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below ``cfg.vision.multi_shot_cut_corr_threshold``). A shot is a
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fade-bounded AND cut-bounded sub-range of the trailer beat: this is
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what we want to match against an individual source clip.
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Returns a sorted list of (start_s, end_s) tuples covering:
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* each visible island, further split at internal hard cuts;
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* each fade region adjacent to an island that still carries
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describable content (e.g. a silhouette during a cross-fade) —
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these get matched via the vision-led search path because CV
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templates against the dark frames are unusable.
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Tiny sub-shots (below ``min_shot_s``) are merged into the previous shot
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so noisy cut detection doesn't fragment a real shot into useless slivers.
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Tiny sub-shots are merged so noisy cut detection doesn't fragment a
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real shot into useless slivers.
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"""
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from src.cv.global_scan import _reference_internal_cut_offsets
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@@ -600,7 +651,9 @@ def _reference_shot_segments(beat, cfg) -> list[tuple[float, float]]:
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cut_offsets = sorted(_reference_internal_cut_offsets(beat, cfg))
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except Exception:
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cut_offsets = []
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if not cut_offsets:
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fade_shots = _fade_content_shots(beat, cfg)
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if not cut_offsets and not fade_shots:
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return islands
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min_shot_s = max(0.4, cfg.cv.deep_scan.span_sample_step_s * 4.0)
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@@ -623,6 +676,21 @@ def _reference_shot_segments(beat, cfg) -> list[tuple[float, float]]:
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shots[-1] = (shots[-1][0], seg_end)
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else:
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shots.append((seg_start, seg_end))
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# Add fade-content shots (cross-fade silhouettes / dim shot boundaries)
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# sorted with the visible-island shots so the matcher sees them in
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# trailer-time order.
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if fade_shots:
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all_shots = sorted(list(shots) + list(fade_shots), key=lambda iv: iv[0])
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# Drop overlaps in case a fade region brushes against an island
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# by a few frames; the island wins.
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cleaned: list[tuple[float, float]] = []
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for s, e in all_shots:
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if cleaned and s < cleaned[-1][1]:
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if e > cleaned[-1][1]:
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cleaned.append((cleaned[-1][1], e))
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continue
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cleaned.append((s, e))
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return cleaned
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return shots if shots else islands
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@@ -691,6 +759,23 @@ def _apply_single_island_segments(results: list, trims: dict[int, tuple[float, f
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return expanded
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def _keeps_cached_match(old, new, cfg) -> bool:
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"""Return True when the old cached match is better than the new one and should be kept.
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Specifically protects multi-segment provisional matches from being replaced
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by a weaker single-span result. The old entry wins when it has segments
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(explicitly tuned multi-shot layout) and the new result has none AND is not
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a score improvement.
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"""
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if old is None or new is None:
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return False
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old_segs = getattr(old, "segments", ()) or ()
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new_segs = getattr(new, "segments", ()) or ()
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if old_segs and not new_segs and new.match_score <= old.match_score:
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return True
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return False
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def _merge_best_results(existing: list, candidates: list, cfg) -> list:
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"""Merge matches by beat, preferring confirmed or higher-scoring results."""
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by_id = {r.beat_id: r for r in existing}
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@@ -1347,12 +1432,21 @@ def _match_unmatched_visual_segments(
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continue
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segments: list[MatchSegment] = []
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for start_s, end_s in islands:
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for island_idx, (start_s, end_s) in enumerate(islands):
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segment_beat = replace(
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beat,
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start_s=beat.start_s + start_s,
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end_s=beat.start_s + end_s,
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)
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if island_idx == 0:
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# First island of an unmatched multi-shot beat: search globally
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# without a continuity bias from the previous beat. Continuity
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# assumes the shot follows the previous beat in the source, but
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# the lead shot of a multi-shot beat is often an insert cut from
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# a completely different scene. A wrong seed with score 0.92
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# would push the real match out of the refinement candidate pool.
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continuity = {}
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else:
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continuity = _continuity_seed_in_points(
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beat.beat_id,
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[b if b.beat_id != beat.beat_id else segment_beat for b in beats],
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@@ -1363,6 +1457,28 @@ def _match_unmatched_visual_segments(
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if beat.beat_id not in skip_global_segment_scan_for:
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segment_matches = _run_segment_match(segment_beat, continuity, cfg, allow_fullscan=True)
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if not segment_matches:
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# Fade-content shot fallback: when CV finds no templates
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# inside this shot (typical for cross-fade silhouettes), the
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# vibe-check + vision-action-window recovery path is the only
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# way to get a match. It's slower but works on dark frames
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# because vision can read structure where CV cannot.
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shot_islands = _reference_scoreable_segments(segment_beat, cfg)
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if not shot_islands and cfg.vision.enabled:
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recovered = _recover_unmatched_beats_via_vision([], [segment_beat], cfg)
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if recovered:
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rec = recovered[0]
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seg_dur = min(max(0.0, end_s - start_s), max(0.0, rec.duration_s))
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if seg_dur > 0:
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segments.append(MatchSegment(
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trailer_offset_s=start_s,
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duration_s=seg_dur,
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scene_id=rec.scene_id,
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in_point_s=rec.in_point_s,
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out_point_s=rec.in_point_s + seg_dur,
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match_score=rec.match_score,
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is_confirmed=rec.is_confirmed,
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))
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continue
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local_segment = _local_same_scene_segment_match(
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segment_beat,
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beat,
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@@ -1559,8 +1675,17 @@ def cmd_match(args: argparse.Namespace, cfg) -> list:
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# bit-for-bit identical to what it was before this run.
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if getattr(args, "beat", None) is not None and _results_cache_path(cfg).exists():
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raw_cached = _load_results(cfg)
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old_for_beat = next((r for r in raw_cached if r.beat_id == args.beat), None)
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raw_cached = [r for r in raw_cached if r.beat_id != args.beat]
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for result in results:
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if _keeps_cached_match(old_for_beat, result, cfg):
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print(
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f"ℹ️ Beat {result.beat_id}: keeping existing {len(getattr(old_for_beat, 'segments', ()) or ())}‑segment "
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f"provisional match (score {old_for_beat.match_score:.3f}) over weaker new result "
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f"(score {result.match_score:.3f}, no segments)."
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)
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raw_cached.append(old_for_beat)
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else:
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raw_cached = _update_result(result, raw_cached)
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results_to_save = sorted(raw_cached, key=lambda r: r.beat_id)
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else:
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+3
-3
@@ -72,12 +72,12 @@ match_threshold = 0.65
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# Store/report lower-confidence automatic candidates for visual review instead
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# of dropping them as "NO MATCH". Confirmed exports can still use match_threshold.
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provisional_match_threshold = 0.43
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provisional_match_threshold = 0.35
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# Lower gate for entering temporal multi-frame refinement. The final decision
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# still uses sequence/span scoring; this only avoids rejecting real matches
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# because one midpoint frame is weak.
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coarse_candidate_threshold = 0.50
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coarse_candidate_threshold = 0.40
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# Candidate ranking weights. Duration coverage matters when the same visual
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# shot appears multiple times: prefer the occurrence that can cover the beat.
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@@ -103,7 +103,7 @@ refine_step_seconds = 0.04 # ≈ 1 frame at 25 fps
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content_align_window_seconds = 0.48
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content_align_sample_step_s = 0.28
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content_validation_weight = 0.35
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provisional_content_threshold = 0.42
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provisional_content_threshold = 0.30
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# When several adjacent frame offsets score almost the same, prefer the earlier
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# one. This avoids matches that are visually correct but start a few frames late.
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@@ -219,7 +219,7 @@ def extract_concat_clip(
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# encoder settings).
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list_file = out.with_name(f"{out.stem}_concat.txt")
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list_file.write_text(
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"\n".join(f"file '{part.as_posix()}'" for part in parts) + "\n",
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"\n".join(f"file '{part.absolute().as_posix()}'" for part in parts) + "\n",
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encoding="utf-8",
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)
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cmd = [
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+41
-6
@@ -580,13 +580,24 @@ def _prepare_motion_templates(
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def _is_dark_reference_frame(frame: np.ndarray, cfg: AppConfig) -> bool:
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"""Truly dark / pure-black frame: no usable structure for matching.
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A cross-fade silhouette (low overall luma but visible contrast) is NOT
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a dark frame for our purposes — it carries content (a hand, a knife,
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a face peeking through the fade) and should still be matchable.
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"""
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cropped = text_safe_crop(
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frame,
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cfg.cv.vibe_check.crop_top_fraction,
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cfg.cv.vibe_check.crop_bottom_fraction,
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)
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gray = cv2.cvtColor(cropped, cv2.COLOR_BGR2GRAY)
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return float(np.mean(gray)) < 28.0 and float(np.percentile(gray, 90)) < 58.0
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mean = float(np.mean(gray))
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p90 = float(np.percentile(gray, 90))
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p10 = float(np.percentile(gray, 10))
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contrast = p90 - p10
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# Real darkness: low luma AND low contrast (no structure visible)
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return mean < 28.0 and p90 < 58.0 and contrast < 30.0
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def _reference_visibility_stats(frame: np.ndarray, cfg: AppConfig) -> tuple[float, float, float]:
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@@ -602,16 +613,40 @@ def _reference_visibility_stats(frame: np.ndarray, cfg: AppConfig) -> tuple[floa
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def _is_scoreable_reference_frame(frame: np.ndarray, cfg: AppConfig) -> bool:
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"""Exclude black, fade, and low-visibility reference frames from scoring."""
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"""Decide whether a reference frame can carry a usable match template.
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Two acceptance paths:
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* Standard: regular daylight / interior shot — luma at or above the
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configured thresholds AND enough contrast to be distinct.
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* Fade-content: low overall luma BUT with strong local contrast,
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i.e. a cross-fade silhouette where you can clearly see structure
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(hand+knife against dark, face emerging from black, etc.). Without
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this path the matcher would silently drop content-bearing fades and
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mis-match the visible portion alone.
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"""
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if _is_dark_reference_frame(frame, cfg):
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return False
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mean_luma, p90_luma, contrast = _reference_visibility_stats(frame, cfg)
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low_visibility = (
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mean_luma < cfg.cv.deep_scan.scoreable_luma_mean_min
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and p90_luma < cfg.cv.deep_scan.scoreable_luma_p90_min
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# Standard daylight / interior shot
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enough_luma = (
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mean_luma >= cfg.cv.deep_scan.scoreable_luma_mean_min
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or p90_luma >= cfg.cv.deep_scan.scoreable_luma_p90_min
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)
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return not low_visibility and contrast >= cfg.cv.deep_scan.scoreable_contrast_min
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if enough_luma and contrast >= cfg.cv.deep_scan.scoreable_contrast_min:
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return True
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# Fade-content: dim but with structure. The local contrast must be
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# well above what a uniform dim frame would have, and at least a few
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# bright pixels must exist (p90 above pure-black), so we don't accept
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# a featureless dark wash. These thresholds are deliberately tighter
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# than the standard path so we don't pollute scoring with smooth fades.
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if contrast >= 40.0 and p90_luma >= 30.0:
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return True
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return False
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def estimate_matchable_reference_duration(
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