Improve multi-shot phase retune

README.md

@@ -36,6 +36,10 @@ Was du bekommst sind zwei Dateien, mit denen du arbeitest:
 5. Bei `MAN.`-Beats selbst die passende Stelle im Spielfilm suchen — die
    Beschreibung im Report sagt dir was du suchst.
 
+Für die visuelle Kontrolle ist zusätzlich **`CUTTER_REPORT.html`** relevant:
+er enthält die frame-locked Compare-Clips. Der alte `match_report.html` ist
+nicht mehr Teil des Workflows.
+
 Alles andere unten ist Hintergrund für den Tool-Verantwortlichen.
 
 ---
@@ -48,7 +52,7 @@ Alles andere unten ist Hintergrund für den Tool-Verantwortlichen.
 | **1** | Schneller Vibe-Check: für jeden Beat die Top-K ähnlichsten Szenen aus dem Spielfilm vorauswählen (Histogramm + pHash). |
 | **2** | Optional: Vision-LLM beschreibt unsichere Szenen mit 3-Frame-Samples; die Beschreibungen liegen gecached vor. |
 | **3** | Frame-genaue Verfeinerung pro Beat (OpenCV-Templatematching, Bewegungsphasen-Vergleich). |
-| **4** | Phasen-Reparatur: bei segmentierten Beats wird die Bewegungsphase im Source mit der sichtbaren Trailerphase abgeglichen. |
+| **4** | Phasen-Reparatur: bei segmentierten Beats wird die Bewegungsphase im Source saliency-gewichtet mit der sichtbaren Trailerphase abgeglichen. |
 | **5** | Recovery: Beats ohne Treffer werden via Vision-Phasensuche in den Top-K Szenen nochmal probiert. |
 | **6** | Export als FCPXML 1.10 oder CMX-3600-EDL plus `CUTTER_REPORT.md`. |
 
@@ -56,6 +60,10 @@ Alles andere unten ist Hintergrund für den Tool-Verantwortlichen.
 Vergleich ausgeblendet, damit Title-Cards, Logos und Letterbox die Treffer
 nicht verfälschen.
 
+**Cutter-Report-Caching:** Vorhandene Compare-Clips werden wiederverwendet.
+Bei gezielten Rematches wird nur der betroffene Beat neu gerendert, damit der
+Report schnell aktuell bleibt und keine unnötigen Videoartefakte neu entstehen.
+
 **Wichtig:** Auch wenn Vision aktiviert ist — der finale Match bleibt
 CV-verifiziert. Das LLM liefert nur zusätzliche Suchanker.
 

cli.py

@@ -131,7 +131,7 @@ def _auto_commit_push_reports(project_root: "Path") -> None:  # type: ignore[nam
         log.warning("Auto-commit/push failed (non-fatal): %s", exc)
 
 
-def _regenerate_cutter_report(cfg: "AppConfig") -> None:  # type: ignore[name-defined]
+def _regenerate_cutter_report(cfg: "AppConfig", force_beats: set[int] | None = None) -> None:  # type: ignore[name-defined]
     """Re-render CUTTER_REPORT.{md,html} with Frame-Locked Compare clips.
 
     Called from every match-style command after the cache is written so all
@@ -141,8 +141,19 @@ def _regenerate_cutter_report(cfg: "AppConfig") -> None:  # type: ignore[name-de
     """
     project_root = cfg.paths.cache_dir.parent
     try:
+        import os
         from scripts.generate_cutter_report import render_report
-        md, html = render_report(project_root, with_stills=True, with_clips=True)
+        old_force = os.environ.get("CUTTER_REPORT_FORCE_BEATS")
+        try:
+            if force_beats:
+                os.environ["CUTTER_REPORT_FORCE_BEATS"] = ",".join(str(b) for b in sorted(force_beats))
+            md, html = render_report(project_root, with_stills=True, with_clips=True)
+        finally:
+            if force_beats:
+                if old_force is None:
+                    os.environ.pop("CUTTER_REPORT_FORCE_BEATS", None)
+                else:
+                    os.environ["CUTTER_REPORT_FORCE_BEATS"] = old_force
         (project_root / "CUTTER_REPORT.md").write_text(md, encoding="utf-8")
         (project_root / "CUTTER_REPORT.html").write_text(html, encoding="utf-8")
 
@@ -293,6 +304,8 @@ def _normalize_cached_results(beats: list, results: list, cfg) -> list:
                                 segment,
                                 in_point_s=in_point_s,
                                 out_point_s=in_point_s + float(segment.duration_s),
+                                match_score=max(float(segment.match_score), float(_phase_score)),
+                                is_confirmed=float(_phase_score) >= cfg.cv.deep_scan.match_threshold,
                             )
                 repaired_segments.append(segment)
 
@@ -1430,6 +1443,8 @@ def _attach_visual_segments(results: list, beats: list, cfg) -> list:
                         seg,
                         in_point_s=in_point_s,
                         out_point_s=in_point_s + seg.duration_s,
+                        match_score=max(seg.match_score, _phase_score),
+                        is_confirmed=_phase_score >= cfg.cv.deep_scan.match_threshold,
                     )
                 else:
                     seg = repaired
@@ -1693,27 +1708,34 @@ def _local_same_scene_segment_match(segment_beat, beat, segment_offset_s: float,
 
 
 def _phase_probe_segment_in_scene(segment_beat, scene: dict, original_in_s: float, cfg):
-    """Retune a weak multi-shot segment inside its own scene using cheap frame features."""
+    """Retune a weak multi-shot segment inside its own scene using saliency-weighted frames."""
     import cv2
     import numpy as np
 
-    offsets = [0.0, 0.28, 0.56, 0.84, 1.12]
+    offsets = [0.0, 0.16, 0.32, 0.48, 0.64, 0.80, 0.96, 1.12]
     size = (160, 90)
 
-    def feature(frame):
+    def prepared_gray(frame):
         if frame is None:
             return None
         h, w = frame.shape[:2]
         frame = frame.copy()
-        frame[: int(h * 0.16), : int(w * 0.28)] = 0
+        # Timecode overlays and letterbox edges are trailer/source-specific and
+        # should not pull the phase toward the wrong moment.
+        frame[: int(h * 0.16), : int(w * 0.32)] = 0
         gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
         gray = cv2.resize(gray, size)
-        edges = cv2.Canny(gray, 40, 120)
-        vec = np.concatenate([
-            gray.reshape(-1).astype("float32") / 255.0,
-            edges.reshape(-1).astype("float32") / 255.0,
-        ])
-        return (vec - vec.mean()) / (vec.std() + 1e-6)
+        return cv2.equalizeHist(gray).astype("float32") / 255.0
+
+    def edge(gray):
+        return cv2.Canny((gray * 255).astype("uint8"), 45, 130).astype("float32") / 255.0
+
+    def pair_score(ref_gray, src_gray, mask):
+        if ref_gray is None or src_gray is None:
+            return None
+        pixel = 1.0 - float((np.abs(ref_gray - src_gray) * mask).sum())
+        edge_score = 1.0 - float((np.abs(edge(ref_gray) - edge(src_gray)) * mask).sum())
+        return 0.65 * pixel + 0.35 * edge_score
 
     def frame_at(cap, t_s):
         cap.set(cv2.CAP_PROP_POS_MSEC, t_s * 1000.0)
@@ -1722,39 +1744,69 @@ def _phase_probe_segment_in_scene(segment_beat, scene: dict, original_in_s: floa
 
     trailer_cap = cv2.VideoCapture(str(cfg.paths.reference_trailer))
     refs = [
-        feature(frame_at(trailer_cap, segment_beat.start_s + offset))
+        prepared_gray(frame_at(trailer_cap, segment_beat.start_s + offset))
         for offset in offsets
         if offset <= segment_beat.duration_s + 0.04
     ]
     refs = [ref for ref in refs if ref is not None]
-    if len(refs) < 3:
+    if len(refs) < 4:
         return None
 
+    ref_stack = np.stack(refs, axis=0)
+    edge_stack = np.stack([edge(ref) for ref in refs], axis=0)
+    saliency = ref_stack.std(axis=0) * 1.25 + edge_stack.mean(axis=0) * 0.75
+    saliency[:, : int(size[0] * 0.12)] *= 0.15
+    saliency[: int(size[1] * 0.16), : int(size[0] * 0.32)] = 0.0
+    threshold = np.quantile(saliency, 0.72)
+    mask = (saliency >= threshold).astype("float32")
+    mask /= mask.sum() + 1e-6
+
     scene_start = float(scene["start_s"])
     scene_end = float(scene["end_s"])
     scan_end = max(scene_start, scene_end - max(0.04, segment_beat.duration_s))
-    max_points = 96
+    max_points = 400
     step_s = max(0.08, (scan_end - scene_start) / max_points)
 
     source_cap = cv2.VideoCapture(str(cfg.paths.source_movie))
+    source_fps = source_cap.get(cv2.CAP_PROP_FPS) or _scene_fps_light(scene, cfg)
+    stride = max(1, int(round(step_s * source_fps)))
+    start_frame = max(0, int(round(scene_start * source_fps)))
+    end_frame = max(start_frame, int(round(scene_end * source_fps)))
+    times: list[float] = []
+    source_frames: list = []
+    frame_idx = start_frame
+    while frame_idx <= end_frame:
+        source_cap.set(cv2.CAP_PROP_POS_FRAMES, frame_idx)
+        ok, frame = source_cap.read()
+        if not ok:
+            break
+        times.append(frame_idx / source_fps)
+        source_frames.append(prepared_gray(frame))
+        frame_idx += stride
+
     candidates: list[tuple[float, float, float]] = []
-    t = scene_start
-    while t <= scan_end:
+    for i, t in enumerate(times):
+        if t > scan_end:
+            break
         vals = []
         for offset, ref in zip(offsets, refs):
-            src = feature(frame_at(source_cap, t + offset))
-            if src is not None:
-                vals.append(float(np.dot(ref, src) / len(ref)))
-        if len(vals) >= 3:
-            candidates.append((sum(vals) / len(vals), min(vals), t))
-        t = round(t + step_s, 6)
+            j = int(round((t + offset - scene_start) / step_s))
+            if 0 <= j < len(source_frames):
+                score = pair_score(ref, source_frames[j], mask)
+            else:
+                score = None
+            if score is not None:
+                vals.append(score)
+        if len(vals) >= 4:
+            avg_score = sum(vals) / len(vals)
+            candidates.append((0.55 * avg_score + 0.45 * min(vals), min(vals), t))
 
     if not candidates:
         return None
 
     candidates.sort(reverse=True)
     best_score = candidates[0][0]
-    near_tie = [c for c in candidates if c[0] >= best_score - 0.01]
+    near_tie = [c for c in candidates if c[0] >= best_score - 0.002]
     chosen = min(near_tie, key=lambda c: abs(c[2] - original_in_s))
     return chosen[2], chosen[0]
 
@@ -1858,7 +1910,8 @@ def cmd_match(args: argparse.Namespace, cfg) -> list:
         results_to_save = results
 
     _save_results(results_to_save, cfg)
-    _regenerate_cutter_report(cfg)
+    force_report_beats = {int(args.beat)} if getattr(args, "beat", None) is not None else None
+    _regenerate_cutter_report(cfg, force_beats=force_report_beats)
 
     print(f"\n✅  {len(results)} / {len(beats)} beats matched.")
     for r in results:

docs/ALGORITHM.md

@@ -148,8 +148,17 @@ Phasenfehler nicht durch Schwarz verdeckt werden.
 Für Multi-Shot-Beats gilt zusätzlich eine Segment-Schwelle pro sichtbarer
 Einstellung. Ein gutes erstes Segment darf kein zweites Segment mit schwachem
 Score mitziehen. Segmente unter `multi_shot_segment_threshold` werden nicht als
-Source-Material ausgegeben; der entsprechende Beat-Bereich bleibt im
-Cutter-Report offen, bis ein eigenständig belastbarer Treffer gefunden wird.
+stabile Wahrheit behandelt, sondern innerhalb derselben plausiblen Source-Scene
+nachjustiert. Die Nachjustierung nutzt eine saliency-gewichtete Mehrframe-Prüfung:
+Timecodes und statische Randbereiche werden entwertet, kontrastreiche und über
+mehrere Trailerframes unterscheidbare Bildbereiche zählen stärker. Dadurch kann
+eine schwache zweite Einstellung phasengenauer repariert werden, ohne den Fehler
+durch Schwarzbild zu verdecken oder einen Beat manuell zu kuratieren.
+
+Der Cutter-Report verwendet Clip-Caching. Bereits vorhandene Compare-Clips werden
+wiederverwendet; bei gezielten Rematches wird nur der betroffene Beat neu gerendert
+(`CUTTER_REPORT_FORCE_BEATS`). So bleibt der Report aktuell, ohne alle Beats jedes
+Mal neu zu kodieren.
 
 ## Vision-Seeds vs. Vollscan
 

scripts/generate_cutter_report.py

@@ -22,6 +22,7 @@ from __future__ import annotations
 import argparse
 import base64
 import json
+import os
 import re
 import subprocess
 import sys
@@ -134,6 +135,19 @@ def _run(cmd: list[str], timeout: int = 120) -> bool:
         return False
 
 
+def _forced_beats() -> set[int]:
+    raw = os.environ.get("CUTTER_REPORT_FORCE_BEATS", "")
+    forced: set[int] = set()
+    for part in re.split(r"[,;\s]+", raw):
+        if not part:
+            continue
+        try:
+            forced.add(int(part))
+        except ValueError:
+            continue
+    return forced
+
+
 def extract_still(video_path: Path, t_s: float, out: Path) -> bool:
     """Always render fresh."""
     if not video_path.exists():
@@ -410,6 +424,7 @@ def collect_rows(
         stills_dir.mkdir(parents=True, exist_ok=True)
     if with_clips:
         clips_dir.mkdir(parents=True, exist_ok=True)
+    force_beats = _forced_beats()
 
     rows: list[BeatRow] = []
     for beat in beats:
@@ -454,13 +469,17 @@ def collect_rows(
         if with_stills:
             t_still = beat_still_time(beat["start_s"], beat["end_s"])
             tjpg = stills_dir / f"beat_{bid:02d}_trailer.jpg"
-            if extract_still(trailer_path, t_still, tjpg):
+            if tjpg.exists() and bid not in force_beats:
+                trailer_still = tjpg
+            elif extract_still(trailer_path, t_still, tjpg):
                 trailer_still = tjpg
             if rec is not None:
                 src_dur = max(0.04, rec["out_point_s"] - rec["in_point_s"])
                 s_still = rec["in_point_s"] + min(0.4, src_dur * 0.3)
                 sjpg = stills_dir / f"beat_{bid:02d}_source.jpg"
-                if extract_still(source_path, s_still, sjpg):
+                if sjpg.exists() and bid not in force_beats:
+                    source_still = sjpg
+                elif extract_still(source_path, s_still, sjpg):
                     source_still = sjpg
 
         if with_clips:
@@ -468,12 +487,16 @@ def collect_rows(
 
             # Trailer clip (cutter-side, simple)
             tmp4 = clips_dir / f"beat_{bid:02d}_trailer.mp4"
-            if extract_clip(trailer_path, beat["start_s"], beat_dur, tmp4):
+            if tmp4.exists() and bid not in force_beats:
+                trailer_clip = tmp4
+            elif extract_clip(trailer_path, beat["start_s"], beat_dur, tmp4):
                 trailer_clip = tmp4
 
             if rec is not None:
                 smp4 = clips_dir / f"beat_{bid:02d}_source.mp4"
-                if num_segs >= 2:
+                if smp4.exists() and bid not in force_beats:
+                    source_clip = smp4
+                elif num_segs >= 2:
                     seg_specs = [
                         (float(s["in_point_s"]),
                          max(0.04, float(s["out_point_s"]) - float(s["in_point_s"])))
@@ -502,7 +525,9 @@ def collect_rows(
                         "match_score": rec.get("match_score", 0.0),
                         "is_confirmed": rec.get("is_confirmed", False),
                     }]
-                if build_compare_clip(
+                if cmp4.exists() and bid not in force_beats:
+                    compare_clip = cmp4
+                elif build_compare_clip(
                     trailer_path, beat["start_s"], beat_dur,
                     source_path, compare_segs,
                     cmp4,