From bcaf0417b3aceb48f4bf5abc0c13c964b303ae27 Mon Sep 17 00:00:00 2001 From: Melbar Date: Sat, 9 May 2026 10:38:57 +0200 Subject: [PATCH] Recover short low-light vibe matches --- CUTTER_REPORT.html | 2 +- CUTTER_REPORT.md | 15 ++-- cli.py | 92 ++++++++++++++++++++++++ output/cutter_clips/beat_18_compare.mp4 | Bin 0 -> 50315 bytes output/cutter_clips/beat_18_source.mp4 | Bin 0 -> 25183 bytes output/cutter_stills/beat_18_source.jpg | Bin 5083 -> 8551 bytes 6 files changed, 102 insertions(+), 7 deletions(-) create mode 100644 output/cutter_clips/beat_18_compare.mp4 create mode 100644 output/cutter_clips/beat_18_source.mp4 diff --git a/CUTTER_REPORT.html b/CUTTER_REPORT.html index 55f1593..06eca29 100644 --- a/CUTTER_REPORT.html +++ b/CUTTER_REPORT.html @@ -132,4 +132,4 @@ table.ov tr:hover { background: rgba(255, 255, 255, 0.05); }
-

Cutter & Match Report

Generiert: 2026-05-09 10:09:07Trailer: BehindTheRedDoor_Trailer_REFERENCE.mp4 @ 25.000 fpsSource: BehindTheRedDoor_FTR_1080P_2398_Fixed.mp4 @ 23.976 fps
25 Beats — 23 automatisch (4 bestätigt) — 2 manuell.
Recent Changes:
Improve multi-shot phase retune

Legende

OKBestätigt — direkt in Schnitt-Timeline übernehmen
?Vorläufig — Phase und Aktion im NLE visuell prüfen
MAN.Kein Treffer — manuell suchen oder Schwarzbild einfügen

Übersicht

BeatTrailer TC In–OutDauerSource TC InSceneScoreStatus
0000:00:00:00–00:00:03:003.00s00:00:03:1910.597?
0100:00:03:00–00:00:08:105.40s00:00:04:0910.380?
0200:00:08:10–00:00:16:248.56s00:00:35:0530.761OK
0300:00:16:24–00:00:19:032.16s01:02:19:034360.572?
0400:00:19:03–00:00:20:161.52s01:02:21:094370.728OK
0500:00:20:16–00:00:26:095.72s00:01:33:03100.499?
0600:00:26:09–00:00:29:062.88s00:01:03:0750.396?
0700:00:29:06–00:00:31:172.44s01:20:10:105530.497?
0800:00:31:17–00:00:33:161.96s00:00:51:0750.620?
0900:00:33:16–00:00:36:193.12s01:20:29:035570.674OK
1000:00:36:19–00:00:40:023.32s01:20:35:16558+559+5560.660?
1100:00:40:02–00:00:42:032.04s01:20:40:185590.636?
1200:00:42:03–00:00:50:068.12s01:14:26:06519+130.701OK
1300:00:50:06–00:00:53:213.60s00:43:19:133080.636?
1400:00:53:21–00:00:57:023.24s00:43:24:163090.626?
1500:00:57:02–00:01:01:124.40s00:02:10:0817+3090.708?
1600:01:01:12–00:01:04:123.00s01:05:12:124510.626?
1700:01:04:12–00:01:09:034.64s01:31:18:04623+720.399?
1800:01:09:03–00:01:10:191.64s———MAN.
1900:01:10:19–00:01:12:131.76s00:16:48:131260.403?
2000:01:12:13–00:01:15:143.04s01:27:05:036130.417?
2100:01:15:14–00:01:17:131.96s00:23:55:001750.526?
2200:01:17:13–00:01:19:232.40s01:03:05:114420.544?
2300:01:19:23–00:01:25:145.64s01:04:35:214460.534?
2400:01:25:14–00:01:32:076.72s———MAN.

Beat-Details

Beat 00

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:00:00–00:00:03:00  (3.00s)
Phase logo animation assembling from distorted shapes with motion blur
Bild centered, symmetrical, abstract black void
Source
00:00:03:19–00:00:05:09
Scene 1 · Score 0.597
⚠ Score 0.597 unter 0.65 — visuell prüfen
python cli.py rematch --beat 0

Beat 01

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:03:00–00:00:08:10  (5.40s)
Phase Dynamic motion blur and shifting optical distortions across the text
Bild Centered, symmetrical layout with overlapping circular glass-like distortions, Abstract black void
Source
00:00:04:09–00:00:06:03
Scene 1 · Score 0.380
⚠ Score 0.380 unter 0.65 — visuell prüfen
python cli.py rematch --beat 1

Beat 02

OKBestätigt
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:08:10–00:00:16:24  (8.56s)
Phase drawing a heart shape on a foggy surface
Bild extreme close-up, shifting from profile of a face to a hand interacting with a surface, indoor, obscured glass or foggy surface
Source
00:00:35:05–00:00:43:06
Scene 3 · Score 0.761
python cli.py rematch --beat 2

Beat 03

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:16:24–00:00:19:03  (2.16s)
Phase speaking and smiling slightly
Bild close-up shot, centered face, outdoor rocky environment
Source
01:02:19:03–01:02:20:20
Scene 436 · Score 0.572
⚠ Score 0.572 unter 0.65 — visuell prüfen
python cli.py rematch --beat 3

Beat 04

OKBestätigt
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:19:03–00:00:20:16  (1.52s)
Phase lifting a camera to eye level to take a photo
Bild medium shot, subject centered, shallow depth of field with blurred treeline background, outdoor forest landscape, overcast sky
Source
01:02:21:09–01:02:22:08
Scene 437 · Score 0.728
python cli.py rematch --beat 4

Beat 05

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:20:16–00:00:26:09  (5.72s)
Phase a metallic cylindrical object is brought toward and touches the skin of the forearm
Bild extreme close-up, shallow depth of field, indistinct dark interior
Source
00:01:33:03–00:01:37:09
Scene 10 · Score 0.499
⚠ Score 0.499 unter 0.65 — visuell prüfen
python cli.py rematch --beat 5

Beat 06

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:26:09–00:00:29:06  (2.88s)
Phase hand reaching toward and touching an ornate decorative box
Bild close-up, shallow depth of field, hand entering from left frame, dark interior
Source
00:01:03:07–00:01:05:03
Scene 5 · Score 0.396
⚠ Score 0.396 unter 0.65 — visuell prüfen
python cli.py rematch --beat 6

Beat 07

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:29:06–00:00:31:17  (2.44s)
Phase man appears to be engaged in conversation
Bild man in a light gray sweater and scarf, seated on a white couch, with a window in the background, indoor with a view of the ocean
Source
01:20:10:10–01:20:12:14
Scene 553 · Score 0.497
⚠ Score 0.497 unter 0.65 — visuell prüfen
python cli.py rematch --beat 7

Beat 08

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:31:17–00:00:33:16  (1.96s)
Phase static or slow drifting
Bild close-up, diagonal curve from top-left to bottom-center, dark, indistinct void
Source
00:00:51:07–00:00:53:01
Scene 5 · Score 0.620
⚠ Score 0.620 unter 0.65 — visuell prüfen
python cli.py rematch --beat 8

Beat 09

OKBestätigt
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:33:16–00:00:36:19  (3.12s)
Phase speaking, transitioning from closed eyes to open mouth and focused gaze
Bild medium close-up, subject positioned right of center, profile/three-quarter view, indoor room next to a large window overlooking a blue horizon/sea
Source
01:20:29:03–01:20:32:06
Scene 557 · Score 0.674
python cli.py rematch --beat 9

Beat 10

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:36:19–00:00:40:02  (3.32s)
Phase conversation
Bild alternating close-ups and a medium two-shot, indoor living room with large windows showing a blue exterior landscape
Source
01:20:35:16  (multi-shot)
Scene Scenes 558, 559, 556 · 3 Segmente
  • Seg 1: 01:20:35:16  dur 0.88s  @ off 0.00s  sc 558  score 0.674
  • Seg 2: 01:20:36:14  dur 1.76s  @ off 0.88s  sc 559  score 0.649
  • Seg 3: 01:20:22:14  dur 0.68s  @ off 2.64s  sc 556  score 0.672
python cli.py rematch --beat 10

Beat 11

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:40:02–00:00:42:03  (2.04s)
Phase static talking head with slight facial expression changes
Bild medium close-up, subject positioned right of center, profile/three-quarter view facing left, indoor room with a large window showing a blue sea/horizon background
Source
01:20:40:18–01:20:42:18
Scene 559 · Score 0.636
⚠ Score 0.636 unter 0.65 — visuell prüfen
python cli.py rematch --beat 11

Beat 12

OKBestätigt
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:42:03–00:00:50:06  (8.12s)
Phase static profile shot transitioning to black/darkness
Bild medium close-up, profile view, subject positioned on the right side of the frame, dark outdoor environment, blurred trees in background
Source
01:14:26:06  (multi-shot)
Scene Scenes 519, 13 · 2 Segmente
  • Seg 1: 01:14:26:06  dur 3.52s  @ off 0.16s  sc 519  score 0.721
  • Seg 2: 00:01:47:14  dur 2.88s  @ off 4.88s  sc 13  score 0.676
python cli.py rematch --beat 12

Beat 13

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:50:06–00:00:53:21  (3.60s)
Phase static conversation; woman on right is standing and holding a cup
Bild wide shot, two figures positioned on opposite sides of a round dining table, modern glass-walled sunroom or conservatory overlooking a snowy landscape
Source
00:43:19:13–00:43:23:04
Scene 308 · Score 0.636
⚠ Score 0.636 unter 0.65 — visuell prüfen
python cli.py rematch --beat 13

Beat 14

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:53:21–00:00:57:02  (3.24s)
Phase static conversation, subject holding a white cup
Bild medium shot, subject positioned on the left, vertical window frame dividing the right third of the frame, interior room with a large window overlooking a snowy pine forest
Source
00:43:24:16–00:43:27:19
Scene 309 · Score 0.626
⚠ Score 0.626 unter 0.65 — visuell prüfen
python cli.py rematch --beat 14

Beat 15

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:57:02–00:01:01:12  (4.40s)
Phase static conversation
Bild medium shot, profile view of two characters facing each other, indoor room with a large window overlooking a snowy forest
Source
00:02:10:08  (multi-shot)
Scene Scenes 17, 309 · 2 Segmente
  • Seg 1: 00:02:10:08  dur 2.80s  @ off 0.24s  sc 17  score 0.720
  • Seg 2: 00:43:27:13  dur 1.28s  @ off 3.04s  sc 309  score 0.682
python cli.py rematch --beat 15

Beat 16

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:01:12–00:01:04:12  (3.00s)
Phase man reaches out and touches the red door with a small object
Bild medium side profile shot, subject on left, door on right, indoor dim environment, adjacent to a red wooden door
Source
01:05:12:12–01:05:15:07
Scene 451 · Score 0.626
⚠ Score 0.626 unter 0.65 — visuell prüfen
python cli.py rematch --beat 16

Beat 17

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:04:12–00:01:09:03  (4.64s)
Phase Static intimacy transitioning to a spatial arrangement of figures
Bild Medium shot, eye-level. First two frames: static shot of couple in bed. Third frame: wide shot of women among white blocks, Bedroom with bedside table and lamp; transition to a white minimalist interior with pedestals
Source
01:31:18:04  (multi-shot)
Scene Scenes 623, 72 · 3 Segmente
  • Seg 1: 01:31:18:04  dur 1.92s  @ off 0.24s  sc 623  score 0.384
  • Seg 2: 00:09:06:13  dur 1.04s  @ off 2.80s  sc 72  score 0.434
  • Seg 3: 00:09:07:18  dur 0.50s  @ off 4.00s  sc 72  score 0.384
⚠ Score 0.399 unter 0.65 — visuell prüfen
python cli.py rematch --beat 17

Beat 18

MAN.Kein Treffer
Trailer 18
— manuell setzen —
Trailer
00:01:09:03–00:01:10:19  (1.64s)
Phase Woman in foreground turns her head from profile to face the camera while speaking
Bild Medium shot, three-quarter profile of woman in foreground left, two women positioned behind her to the right, Indoors, minimalist dark background
— kein automatischer Treffer —
python cli.py rematch --beat 18

Beat 19

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:10:19–00:01:12:13  (1.76s)
Phase static conversation, subtle facial expression change
Bild medium close-up, over-the-shoulder shot with a blurred figure in the foreground right, outdoor dark forest or wooded area
Source
00:16:48:13–00:16:49:10
Scene 126 · Score 0.403
⚠ Score 0.403 unter 0.65 — visuell prüfen
python cli.py rematch --beat 19

Beat 20

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:12:13–00:01:15:14  (3.04s)
Phase man kisses woman's forehead, then they pull back slightly to face each other
Bild extreme close-up, profile view, faces facing each other, indoor, blurred background
Source
01:27:05:03–01:27:06:00
Scene 613 · Score 0.417
⚠ Score 0.417 unter 0.65 — visuell prüfen
python cli.py rematch --beat 20

Beat 21

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:15:14–00:01:17:13  (1.96s)
Phase hand raised to mouth, slight facial movement
Bild extreme close-up, face partially obscured by shadow, dark interior
Source
00:23:55:00–00:23:56:23
Scene 175 · Score 0.526
⚠ Score 0.526 unter 0.65 — visuell prüfen
python cli.py rematch --beat 21

Beat 22

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:17:13–00:01:19:23  (2.40s)
Phase man looks up and speaks, transitioning from downward gaze to forward gaze
Bild close-up, profile to three-quarter view, outdoor rocky environment, blurred background
Source
01:03:05:11–01:03:07:07
Scene 442 · Score 0.544
⚠ Score 0.544 unter 0.65 — visuell prüfen
python cli.py rematch --beat 22

Beat 23

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:19:23–00:01:25:14  (5.64s)
Phase static posture, head tilted upwards looking at the sky
Bild medium shot, subject positioned on the left third, facing away from camera towards the water, rocky shoreline next to a body of water under an overcast sky
Source
01:04:35:21–01:04:41:02
Scene 446 · Score 0.534
⚠ Score 0.534 unter 0.65 — visuell prüfen
python cli.py rematch --beat 23

Beat 24

MAN.Kein Treffer
Trailer 24
— manuell setzen —
Trailer
00:01:25:14–00:01:32:07  (6.72s)
— kein automatischer Treffer —
python cli.py rematch --beat 24
+

Cutter & Match Report

Generiert: 2026-05-09 10:33:46Trailer: BehindTheRedDoor_Trailer_REFERENCE.mp4 @ 25.000 fpsSource: BehindTheRedDoor_FTR_1080P_2398_Fixed.mp4 @ 23.976 fps
25 Beats — 24 automatisch (4 bestätigt) — 1 manuell.
Recent Changes:
Handle fade-led segment phase ties

Legende

OKBestätigt — direkt in Schnitt-Timeline übernehmen
?Vorläufig — Phase und Aktion im NLE visuell prüfen
MAN.Kein Treffer — manuell suchen oder Schwarzbild einfügen

Übersicht

BeatTrailer TC In–OutDauerSource TC InSceneScoreStatus
0000:00:00:00–00:00:03:003.00s00:00:03:1910.597?
0100:00:03:00–00:00:08:105.40s00:00:04:0910.380?
0200:00:08:10–00:00:16:248.56s00:00:35:0530.761OK
0300:00:16:24–00:00:19:032.16s01:02:19:034360.572?
0400:00:19:03–00:00:20:161.52s01:02:21:094370.728OK
0500:00:20:16–00:00:26:095.72s00:01:33:03100.499?
0600:00:26:09–00:00:29:062.88s00:01:03:0750.396?
0700:00:29:06–00:00:31:172.44s01:20:10:105530.497?
0800:00:31:17–00:00:33:161.96s00:00:51:0750.620?
0900:00:33:16–00:00:36:193.12s01:20:29:035570.674OK
1000:00:36:19–00:00:40:023.32s01:20:35:16558+559+5560.660?
1100:00:40:02–00:00:42:032.04s01:20:40:185590.636?
1200:00:42:03–00:00:50:068.12s01:14:26:06519+130.701OK
1300:00:50:06–00:00:53:213.60s00:43:19:133080.636?
1400:00:53:21–00:00:57:023.24s00:43:24:163090.626?
1500:00:57:02–00:01:01:124.40s00:02:10:0817+3090.708?
1600:01:01:12–00:01:04:123.00s01:05:12:124510.626?
1700:01:04:12–00:01:09:034.64s01:31:18:04623+720.399?
1800:01:09:03–00:01:10:191.64s00:09:13:13750.542?
1900:01:10:19–00:01:12:131.76s00:16:48:131260.403?
2000:01:12:13–00:01:15:143.04s01:27:05:036130.417?
2100:01:15:14–00:01:17:131.96s00:23:55:001750.526?
2200:01:17:13–00:01:19:232.40s01:03:05:114420.544?
2300:01:19:23–00:01:25:145.64s01:04:35:214460.534?
2400:01:25:14–00:01:32:076.72s———MAN.

Beat-Details

Beat 00

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:00:00–00:00:03:00  (3.00s)
Phase logo animation assembling from distorted shapes with motion blur
Bild centered, symmetrical, abstract black void
Source
00:00:03:19–00:00:05:09
Scene 1 · Score 0.597
⚠ Score 0.597 unter 0.65 — visuell prüfen
python cli.py rematch --beat 0

Beat 01

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:03:00–00:00:08:10  (5.40s)
Phase Dynamic motion blur and shifting optical distortions across the text
Bild Centered, symmetrical layout with overlapping circular glass-like distortions, Abstract black void
Source
00:00:04:09–00:00:06:03
Scene 1 · Score 0.380
⚠ Score 0.380 unter 0.65 — visuell prüfen
python cli.py rematch --beat 1

Beat 02

OKBestätigt
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:08:10–00:00:16:24  (8.56s)
Phase drawing a heart shape on a foggy surface
Bild extreme close-up, shifting from profile of a face to a hand interacting with a surface, indoor, obscured glass or foggy surface
Source
00:00:35:05–00:00:43:06
Scene 3 · Score 0.761
python cli.py rematch --beat 2

Beat 03

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:16:24–00:00:19:03  (2.16s)
Phase speaking and smiling slightly
Bild close-up shot, centered face, outdoor rocky environment
Source
01:02:19:03–01:02:20:20
Scene 436 · Score 0.572
⚠ Score 0.572 unter 0.65 — visuell prüfen
python cli.py rematch --beat 3

Beat 04

OKBestätigt
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:19:03–00:00:20:16  (1.52s)
Phase lifting a camera to eye level to take a photo
Bild medium shot, subject centered, shallow depth of field with blurred treeline background, outdoor forest landscape, overcast sky
Source
01:02:21:09–01:02:22:08
Scene 437 · Score 0.728
python cli.py rematch --beat 4

Beat 05

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:20:16–00:00:26:09  (5.72s)
Phase a metallic cylindrical object is brought toward and touches the skin of the forearm
Bild extreme close-up, shallow depth of field, indistinct dark interior
Source
00:01:33:03–00:01:37:09
Scene 10 · Score 0.499
⚠ Score 0.499 unter 0.65 — visuell prüfen
python cli.py rematch --beat 5

Beat 06

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:26:09–00:00:29:06  (2.88s)
Phase hand reaching toward and touching an ornate decorative box
Bild close-up, shallow depth of field, hand entering from left frame, dark interior
Source
00:01:03:07–00:01:05:03
Scene 5 · Score 0.396
⚠ Score 0.396 unter 0.65 — visuell prüfen
python cli.py rematch --beat 6

Beat 07

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:29:06–00:00:31:17  (2.44s)
Phase man appears to be engaged in conversation
Bild man in a light gray sweater and scarf, seated on a white couch, with a window in the background, indoor with a view of the ocean
Source
01:20:10:10–01:20:12:14
Scene 553 · Score 0.497
⚠ Score 0.497 unter 0.65 — visuell prüfen
python cli.py rematch --beat 7

Beat 08

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:31:17–00:00:33:16  (1.96s)
Phase static or slow drifting
Bild close-up, diagonal curve from top-left to bottom-center, dark, indistinct void
Source
00:00:51:07–00:00:53:01
Scene 5 · Score 0.620
⚠ Score 0.620 unter 0.65 — visuell prüfen
python cli.py rematch --beat 8

Beat 09

OKBestätigt
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:33:16–00:00:36:19  (3.12s)
Phase speaking, transitioning from closed eyes to open mouth and focused gaze
Bild medium close-up, subject positioned right of center, profile/three-quarter view, indoor room next to a large window overlooking a blue horizon/sea
Source
01:20:29:03–01:20:32:06
Scene 557 · Score 0.674
python cli.py rematch --beat 9

Beat 10

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:36:19–00:00:40:02  (3.32s)
Phase conversation
Bild alternating close-ups and a medium two-shot, indoor living room with large windows showing a blue exterior landscape
Source
01:20:35:16  (multi-shot)
Scene Scenes 558, 559, 556 · 3 Segmente
  • Seg 1: 01:20:35:16  dur 0.88s  @ off 0.00s  sc 558  score 0.674
  • Seg 2: 01:20:36:14  dur 1.76s  @ off 0.88s  sc 559  score 0.649
  • Seg 3: 01:20:22:14  dur 0.68s  @ off 2.64s  sc 556  score 0.672
python cli.py rematch --beat 10

Beat 11

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:40:02–00:00:42:03  (2.04s)
Phase static talking head with slight facial expression changes
Bild medium close-up, subject positioned right of center, profile/three-quarter view facing left, indoor room with a large window showing a blue sea/horizon background
Source
01:20:40:18–01:20:42:18
Scene 559 · Score 0.636
⚠ Score 0.636 unter 0.65 — visuell prüfen
python cli.py rematch --beat 11

Beat 12

OKBestätigt
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:42:03–00:00:50:06  (8.12s)
Phase static profile shot transitioning to black/darkness
Bild medium close-up, profile view, subject positioned on the right side of the frame, dark outdoor environment, blurred trees in background
Source
01:14:26:06  (multi-shot)
Scene Scenes 519, 13 · 2 Segmente
  • Seg 1: 01:14:26:06  dur 3.52s  @ off 0.16s  sc 519  score 0.721
  • Seg 2: 00:01:47:14  dur 2.88s  @ off 4.88s  sc 13  score 0.676
python cli.py rematch --beat 12

Beat 13

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:50:06–00:00:53:21  (3.60s)
Phase static conversation; woman on right is standing and holding a cup
Bild wide shot, two figures positioned on opposite sides of a round dining table, modern glass-walled sunroom or conservatory overlooking a snowy landscape
Source
00:43:19:13–00:43:23:04
Scene 308 · Score 0.636
⚠ Score 0.636 unter 0.65 — visuell prüfen
python cli.py rematch --beat 13

Beat 14

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:53:21–00:00:57:02  (3.24s)
Phase static conversation, subject holding a white cup
Bild medium shot, subject positioned on the left, vertical window frame dividing the right third of the frame, interior room with a large window overlooking a snowy pine forest
Source
00:43:24:16–00:43:27:19
Scene 309 · Score 0.626
⚠ Score 0.626 unter 0.65 — visuell prüfen
python cli.py rematch --beat 14

Beat 15

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:00:57:02–00:01:01:12  (4.40s)
Phase static conversation
Bild medium shot, profile view of two characters facing each other, indoor room with a large window overlooking a snowy forest
Source
00:02:10:08  (multi-shot)
Scene Scenes 17, 309 · 2 Segmente
  • Seg 1: 00:02:10:08  dur 2.80s  @ off 0.24s  sc 17  score 0.720
  • Seg 2: 00:43:27:13  dur 1.28s  @ off 3.04s  sc 309  score 0.682
python cli.py rematch --beat 15

Beat 16

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:01:12–00:01:04:12  (3.00s)
Phase man reaches out and touches the red door with a small object
Bild medium side profile shot, subject on left, door on right, indoor dim environment, adjacent to a red wooden door
Source
01:05:12:12–01:05:15:07
Scene 451 · Score 0.626
⚠ Score 0.626 unter 0.65 — visuell prüfen
python cli.py rematch --beat 16

Beat 17

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:04:12–00:01:09:03  (4.64s)
Phase Static intimacy transitioning to a spatial arrangement of figures
Bild Medium shot, eye-level. First two frames: static shot of couple in bed. Third frame: wide shot of women among white blocks, Bedroom with bedside table and lamp; transition to a white minimalist interior with pedestals
Source
01:31:18:04  (multi-shot)
Scene Scenes 623, 72 · 3 Segmente
  • Seg 1: 01:31:18:04  dur 1.92s  @ off 0.24s  sc 623  score 0.384
  • Seg 2: 00:09:06:13  dur 1.04s  @ off 2.80s  sc 72  score 0.434
  • Seg 3: 00:09:07:18  dur 0.50s  @ off 4.00s  sc 72  score 0.384
⚠ Score 0.399 unter 0.65 — visuell prüfen
python cli.py rematch --beat 17

Beat 18

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:09:03–00:01:10:19  (1.64s)
Phase Woman in foreground turns her head from profile to face the camera while speaking
Bild Medium shot, three-quarter profile of woman in foreground left, two women positioned behind her to the right, Indoors, minimalist dark background
Source
00:09:13:13–00:09:15:05
Scene 75 · Score 0.542
⚠ Score 0.542 unter 0.65 — visuell prüfen
python cli.py rematch --beat 18

Beat 19

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:10:19–00:01:12:13  (1.76s)
Phase static conversation, subtle facial expression change
Bild medium close-up, over-the-shoulder shot with a blurred figure in the foreground right, outdoor dark forest or wooded area
Source
00:16:48:13–00:16:49:10
Scene 126 · Score 0.403
⚠ Score 0.403 unter 0.65 — visuell prüfen
python cli.py rematch --beat 19

Beat 20

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:12:13–00:01:15:14  (3.04s)
Phase man kisses woman's forehead, then they pull back slightly to face each other
Bild extreme close-up, profile view, faces facing each other, indoor, blurred background
Source
01:27:05:03–01:27:06:00
Scene 613 · Score 0.417
⚠ Score 0.417 unter 0.65 — visuell prüfen
python cli.py rematch --beat 20

Beat 21

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:15:14–00:01:17:13  (1.96s)
Phase hand raised to mouth, slight facial movement
Bild extreme close-up, face partially obscured by shadow, dark interior
Source
00:23:55:00–00:23:56:23
Scene 175 · Score 0.526
⚠ Score 0.526 unter 0.65 — visuell prüfen
python cli.py rematch --beat 21

Beat 22

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:17:13–00:01:19:23  (2.40s)
Phase man looks up and speaks, transitioning from downward gaze to forward gaze
Bild close-up, profile to three-quarter view, outdoor rocky environment, blurred background
Source
01:03:05:11–01:03:07:07
Scene 442 · Score 0.544
⚠ Score 0.544 unter 0.65 — visuell prüfen
python cli.py rematch --beat 22

Beat 23

?Vorläufig
▶ Trailer  /  ▶ Source (Frame-Locked Compare)
Trailer
00:01:19:23–00:01:25:14  (5.64s)
Phase static posture, head tilted upwards looking at the sky
Bild medium shot, subject positioned on the left third, facing away from camera towards the water, rocky shoreline next to a body of water under an overcast sky
Source
01:04:35:21–01:04:41:02
Scene 446 · Score 0.534
⚠ Score 0.534 unter 0.65 — visuell prüfen
python cli.py rematch --beat 23

Beat 24

MAN.Kein Treffer
Trailer 24
— manuell setzen —
Trailer
00:01:25:14–00:01:32:07  (6.72s)
— kein automatischer Treffer —
python cli.py rematch --beat 24
diff --git a/CUTTER_REPORT.md b/CUTTER_REPORT.md index 4a64e21..8146743 100644 --- a/CUTTER_REPORT.md +++ b/CUTTER_REPORT.md @@ -1,6 +1,6 @@ # Cutter-Report — manuelles Nachschneiden -Generiert: **2026-05-09 10:09:07** +Generiert: **2026-05-09 10:33:46** - **Trailer**: `BehindTheRedDoor_Trailer_REFERENCE.mp4` @ 25.000 fps - **Source** : `BehindTheRedDoor_FTR_1080P_2398_Fixed.mp4` @ 23.976 fps @@ -15,7 +15,7 @@ Trailer-TC in Trailer-Framerate, Source-TC in Source-Framerate. | `?` | Vorläufig — korrekte Szene, Phase im NLE prüfen | | `MAN.` | Kein automatischer Treffer — manuell setzen | -**25** Beats gesamt · **23** automatisch (**4** bestätigt) · **2** manuell. +**25** Beats gesamt · **24** automatisch (**4** bestätigt) · **1** manuell. ## Beat-Tabelle @@ -39,7 +39,7 @@ Trailer-TC in Trailer-Framerate, Source-TC in Source-Framerate. | 15 | 00:00:57:02 – 00:01:01:12 | 00:02:10:08 – 00:02:13:03 | 17 (+1) | 0.708 | ? | | 16 | 00:01:01:12 – 00:01:04:12 | 01:05:12:12 – 01:05:15:07 | 451 | 0.626 | ? | | 17 | 00:01:04:12 – 00:01:09:03 | 01:31:18:04 – 01:31:20:02 | 623 (+2) | 0.399 | ? | -| 18 | 00:01:09:03 – 00:01:10:19 | — – — | — | — | MAN. | +| 18 | 00:01:09:03 – 00:01:10:19 | 00:09:13:13 – 00:09:15:05 | 75 | 0.542 | ? | | 19 | 00:01:10:19 – 00:01:12:13 | 00:16:48:13 – 00:16:49:10 | 126 | 0.403 | ? | | 20 | 00:01:12:13 – 00:01:15:14 | 01:27:05:03 – 01:27:06:00 | 613 | 0.417 | ? | | 21 | 00:01:15:14 – 00:01:17:13 | 00:23:55:00 – 00:23:56:23 | 175 | 0.526 | ? | @@ -323,17 +323,20 @@ Trailer-TC in Trailer-Framerate, Source-TC in Source-Framerate. |:---:|:---:| | ![Trailer 17](data:image/jpeg;base64,/9j/4AAQSkZJRgABAgAAAwAEAAD//gAQTGF2YzYyLjI4LjEwMQD/2wBDAAgICAkICQsLCwsLCw0MDQ0NDQ0NDQ0NDQ0ODg4REREODg4NDQ4OEBARERITEhERERETExQUFBgYFxccHB0iIin/xACXAAACAwEBAQEAAAAAAAAAAAACAwEABAUGBwgBAQEBAQEBAAAAAAAAAAAAAAABAgMEBRAAAgECAwQHBQQIBgMBAQEAAQACEQMhEgQxUUEFE2GRcTIi0YEUobFSwUJicoLhBjOSFfAjc0MkNFOi8YNjk9JEEQEBAQEAAQQCAgMBAQAAAAAAARECEiEDQTFRIhNhcTIEkRT/wAARCAEOAeADASIAAhEAAxEA/9oADAMBAAIRAxEAPwD4CAwWdjLlj1Ayy2jNPVDWaNo09RWxmK7JHcrteL2OhasLyQ3MZI7k2FpqDCO5fas2yMYhVxdVnYVpooaa1KVMq2WjtAeALdOP7nsL0MoLNNcI6e2PuhRLTx4YPoTbieDmnZizV1wTZpxU4PTnGhefcGWXe3VA1uDIoW6BasyNys0LanlblWoBqeUNyhuqBhZlDcobphbVmVjKzU9QNWZW5VplAwnlZyhaZS2rMrcrdMpbVuVuUM0KatytyhaFNW5QxlC0LatyhtAtCmrsoZoNwWmUhq/KNzOULTKzsujLFuWK0yszLpyxblitMZmukRizljuWjKzR05ItyRWjMx2OvLFkQitVjqzXudmSG5no4blqYygM5ep99Dl9oAVMP4Fw0dgfdgf0Xjfdz4dZ7O/LyvJuS/zQ6q5dvjSaXRWen1N8wldMYmYhCFu3EgzuXJyEYisRtJIetH9kJ6y9y7+XauGp0vMJX4R1F21LTy08tLHPfGotZrmXo7f9wGMpCQ2YvqeU39FprWu0mpgYWNdZhblctQE5W52rguW55CY541FJCoNDg9bTc45dyv3DT6eE9Rp9PPVz1EzAWZXDrLXQzFmBlLLkt7DI+aW2jZ7kS+1ny+a6vkOkPLr+v5br5a61pLtq3qo3NNLS3LYvEi3ehE3LgnalKJjtjOJpWOKGh/Zq/cnrjr5nl1nl1u1c1U52zduxN+QjZt27UZRz3LhOFZRiBUkvvLl7lWh5brNHo5T1EtdOx0k7lgWI27NiRnGOXpJmdyUqVOEQBgp0dzlmntcx0Fy5M6bWxsZdTbseeF2xPPGUrMpgyhUyjIZq8Q3z/pP4/wC3jdX+zps+4XdFqI63T8y6SOmuziNLKNy1LLdtX43ZmFqUCQc3SGBiags88/Z88l/l/wDqbOrOt03T5tP5rUT0s7eSFz/Mxj4wACdlRi+o5tc0V3Q6Dl+klO5a0Z1FyV65bFs3buolEyy2808sIxhECpqcSaKea3NPrdLyi1CRB0ejOnu1hgJG/cn5ccRlkG+SeLz+j/Z2chr7nMLh5dY5d0UdSTaN690t80tWbdmMo5pyoSazEYxFSU9VyPQ6K5o713XXJ8v11m5d0+qs6Uyu5rU8k7VzTzvQyThLCVLkhShFavotGeW2tLzLll7UXTp9VPTXbWrhp/NC7pzKhnYlcBMJCcomkqjAhHmE+Xai3ynQW7l6Wj0GcXb0rQhcunUXxcvTjaEpZQIjLAZqmlS3UxxObfs9oNFy7R6qxrtReva6f+m0t3RixduWa5feDTUXctuUvLbqKzNaYCrj5dyXVajWXNHclZ0c7MgL8tVdjajZ8wjjU5pyqcIWxKR3Pa57ct845rqNTnMLMpiFiOT9zprfktQEK4ZbYHlHGrzfcrFjVxlC8btu3djKNzo8hlGMga5CSYkjhVamD1nKrug53qOWWzLU3LN+WnhkgRK7KoAywBkak8Kl6/OeRz5LDRGd+3elqrVy5IWsYWpW7htyt5wSJmJBBkMKg0qMXdd53Zsc/wCbcysWLepjrZXRbN7pbdy1buHzG3K1chOE5R8pINctQNqPPOcaHmHLuWafT6S3YnpbVyMzE3iLVb05dFb6S5IShIESMpVkDgDRI8wqmuGxRNyOfqPE8q9jJ6l6tcXnXYAYulZwkMEsGnglTmDahioZwSrUNqGatqxEVDODLcEqKhtQzgxghFQ2obg3BotQ2obg3AsFqG1DaBuDRahtQ3BmgYIzBuYM0DcGojMG1DNAwlWobUM0DaBCG1CWDcEIq2rODcELVmrcG4IVrFEsEJbUNwbghODcG1DahgluDahtQ0XBnBuDahInBte9tRuZqNyH0GIwCVGIbAm+Xr7r1z6LyjcGMo3BNgowkxG4ImI3LCgWsUqg3IkBMotc6WQEaBMol3GAEBigSKLqICgQoFiLpmllVMLyrkEjl6gPOuCoL1r48peZJNRh4slk+ItLVA1gs0aiapY0B3o0osqTAR4A1Pew1DcUGRtWKnFmhSaWKHFijNGtRFGWnYigWLNCgygVC2hRYQPKW5Sg1Jo6FtEEkoqNa2iEMbG0SohDasYoo0yrKtlJo20wqiAu8NvJ9UhKXs2BKGhYoWWoRRmjCQohaNSwYQraFLDc3BoijaM4NwSPpEdNqogVsTpv2sGJD9Gt2M1qB6h8nz/M+XUrdgNniH2vzr7u9Xfy93HXNjzFGCHWYUVmLvyb8WUhB0GKsxdSufUZyguIVkO449QooFaVbqOdCgmiXcQDCTWs0sq5LVcky59/wl5c3rXvCXkza1GQ+ItOxp8Ra1QUWQtmYlSnljmQdenH7z/DKTCRb34pUWlAs1cZyzEJFoaoqNonRpYFtoyQ0ILIbRYQwkBRoSYaLSrFEg2mKAUZosoxRICjaJJUShSbRlAWQy0MEGNUDE8VxGDSMD3/AGNTGdbCBkJEfdFUaOiwKxv/AJB80ExgeJ7E6JURKVaM0aE0EkMhktohWs0ZQijUmoQyzSrNGo/SNivRx7h8mLgBBBFd7ns3BGA6gOyiUrox7PR+T3P2v+Xo55rzOu0nQXMMYyxj1dReZKL6rURF6BjL2dR3vmrsTGRB2h3zXq5+mSQUyDokok9Iz1CSFMlxVF6Rx6JKsrSrLuOVAiUii7jAUUmC6jNAqktKqSZYr3hk8qT1b3hk8qSWMcvEWGZeIsOmw8XXYP7z/DLmo6bAxuf4ckgigU67EC5UksjaykGgmSWUChDQ0MoVFIoITRiiQ2IkoXYiSjKaAGZrJmduJLMYhdAEHDaUmhFvfgmIJC2TWROA470hhsSh6OiOVdUsZ+5GkZTuaAtNwHBFGhLBOHt+xko7+/7GLoHTp/Bf/JH5ud02fBf/ACx+aAlBMoIEEmGoUhgJFFolhKjaJEMtokEqA1JEofcbd/AY7Y07E+nwHYXixvGkfZ8k+moSN74Ouf2r6HOY6hv+n63naoZ/MNvFUbxQN1eK7jDIqSVtzAucydyMWhJUkpkqiXcceqElWSyUCXUcrUItYJdxiqiWaoF0zUFUVqqTUY7vhk8qT1buwvKkxYxy8RYbLxlgYumhL7J80x/85KAuseOX+HJKLgGG8B3NcqBIIptBoELFZLBWGWEylWUypJaJJVmTBLcppVuIgCrpAFsAnGuxCERlqtqCRxADQEayk6Kxhj1bd7Fi2JiRKycQaMRmMjMgE0iOG91DEUDbdgHalOM4YxFUqRZrtPsH2uiFmBwo5o3icaUPdtd9uQkK7EMtzSR4YOIgwuAdr2ZF5espmjTbX4IJltV8P0vsX5cFEsO37EIdFjwX/wAsPm5wvs/u7/dD5sVBRDLAQJKjCR2IQ0MNCDGGKloKFZAayGqlWUyjSqR9IhPyjuTzvNjqLeUeYJe8W/rD5+ufX6eqd+jodIwZuD3m19Qb7zb+oM8annPy1SNXNI0QOptfUpnfty44t8Wb3BmSsyV5qomTqcud60ZKJKFWKupGLREo1YYdIlFrDWbUVVyTVyKRku+GTypPVu7JPJkU1GOfiLCVzxIDa2KYF1j94fySVBbZ/eH8kkouA7mG8B3MVYqCkNiLUptQrLNUSxE1RaVZk1lMipJqyTVF1ImjApiUzMcaq61KzJUltVMfNicBsw4lZSmAQpXIN1VgFCGA41t7MM210CNQ5bsqZeqtXXblmAYGQDpBFFEjlVi9EnKcOpKKeUnBs7vRAU/ooxBhI08w4dSc4xlE5qb0YEajNEk073BOfSSJ4OeU+EcI8P1trwamtfSVVSPzUZjVZ4mImq+0fJe6xCnsLlAPf1LRKUdkT7UpjVPSyP3VkTLiEumMsJVYBKBlRIlXJDRaMLoOOUj2ii0WJfdMT8HmxmbU68Dt63p2pCezDc6xncLlbnHbE/Nge3sezarlpJd0carDzcCoaHunS2T90KjorP0ntKw84+sWOWctyRPulgmg+7+t0jlvLR//AJNP/AHPau+SPcFovPze+uvK+t+3untzBnl/LyP9rY//ADi47vJeX3P8iEfy4OvpUDdc+XX5rU4k+HBvcgsiuTDveTd5XO1919jK5g45yq9efc6Tr2+b8PGS05jwUStkPqrtqMuAeZd072nua4de1+HEysULtnZooMXpK43mxnxYWEI0ds4BrLCQCuSxXJIyXdh7nkSevc2HueVJLGW5tVjasntVDa2NGgrbPj/RKmqy0fP+iUo+ARLHAdzFWKirGZEokrE04zoqMyg11jNqalhrW4ita1uIrINGGpTbcvNi6qOB02JwifNWvDd7WWK0G1miVMTK0XpWoiUa7WJ2oy2hyqbU4XApvWgevdvHtUXLduzjnNeA4qPeJnafYl1r6SNmOMvZxc92/wBKOKHknia161B24GrUtRxaW7WkUbjKuiIz93AKIipdkZZKADN3JYOMKcFwishGJFSaFASiTQEuW05Adoc9y1KOMCSOI4+x3iNMdqMkMELsZYHtWSFFF0ATzDYfEnURptynb3dSZ+lNEBEz8IMvygn5PX03LoT80o1HDMa/DY9iFqFoUAA7mzlm9PF3oShhKMondIULOnkRN6vOwOktHjkNfYXk6b97H2/JuG69DbuVjEuqM6vLEnZbk1mt4SVQKxMvcwunKO4LOlebCflCfSPzup+1fW5vo6HSsdK8/pGOkc403m6pldcZuKpXG4y0SvB5mp5potPMwu3hCQxMcsice4FmU3xn7Qf76v1WofMvT25Orjn7nXjzrv3ubaW9Ax013PcGJ8khSA8R8wAUS5ty87Lsj/6p+jydBbgRMgYmAif0nSNDapTo4dsn1T248l9zTZc10XCVw/8ArkpPNNN/9P4CkdFZG2EB/F6sjR2T92Hx9XXgzeiTzPT7rv8AB+tA81sfRd/hHq6zobWUkRt1H4a/a8K8AYggAbRg3xTXoIyE4xkNkgCPaiUNJjpbP5AOzBYXFGS5sLyJvYu7C8eYSxlntVcU57VbWjSzb8fsKJZt+LtQjOQB3PQtaONyIkZnECoA2dTzZcHswOSMDwlGNezaktAdJZj9R7z6KjbtDZAfN0XJOWtS1AyjD6R2OW4BHg7OtxXDWRSlta10wrWtQrWtaK1rWKZC7O34ZEJ+83fq+AUNZhopSMjUmqLWrEESS2uCLUqta1qJFXdppZcARSla7ieDjhU4B1wy29oqNrlqN480TmAB6th6xuUC2Aa0B70oXIT2YdTpjHBNlxJjw+NWapEhDMhjmRmO5uFMtP1huSVThtJVnNGiYr1Ghn0unhL9HswdRcPKpA6b9KT0SK8C6jnXl+bmuoA+mA+JeTaJ6SNN4e7zq2AITAxJyk7xR4mnGa9Dv+WLGp9OqQ6bAlXHZvU0XwJSNwKwFzQ2LQWo9NC5glnccJYJ53xWetfR5vo05253NnYzMxdPM1cpKjJAyZhqTJ8rz4f6i0d9qnYX0Rk+e55jPTH8NwfJ37f+zn7t/UXLBUS7ovUnIWomctgDy+WGlok/VT4OzUGF2Jjm2YkPtjxOVK/qNUa1yRGwcP1lGPTxNayI+XsWAZ5ihyDYBwdlqsJyzRrEfeDRo0t6ROWWNRgfV4N4UqN1yXzL1tJ5r0pkGA4De83VYXLw3T+aT5dLl3+0t9RmP+xdBcfLJf6eQ+m7IdtHYXj19umMtzi8i5xexPi8m4NqWME9qtZJXVqmNh4u1iobA+ZCJbA9kCtmA/BH5PGlwezGYFuP5R8ms1nNdh4NAaTmnglOkWWrCZ/AOAmpK+9cJw2D5udshVa1rplWtagyNuU9gXe7da+zsA6nSBVmrjFHS75LRpYdZdeVkMGb3S1uPaW+52+vtdjUMPulvr7WfdLfX2u6jOC0xy56eAnbiB4ia9wdPQ2o/cilqMMlwY5Dj+U7SkZwpXMO1KCNiEsckexGVm19EWPeoxwqD3KemzGuxGC6G2K4fFOMKDy4Bi3IVxXVFMEuLs207GelUZ8aSqO9OkTsKUZkSqMqMmchtj7QlEgitK9RShFzZuU3LoMgN23qUXITzE+EE7K7GIRoDXimbXdN/wBz0FqMJUuXakHcCakj7HDC7OWJuTP6R9XHO5O9IZ/uxEYjgANyVidJZTtTMjoTHTwEZykRtGOw78XDCxOxqI1xBrlI2HB6UcpGxKUahurhNVsZcHKZUNExMKMVsE0ukcokzmamO2OZ6SIH90dh9GP5to/+T/rL0fGVkOMe1uY749rP4eL811/l6n4ez/m2j/5f+svRP+Z6M/50fbUfY+KzdYZBHFv/AM3N/J/N1/T2o12nl4bts/pOiB6bC2M5/D5vk+BzgcHo8tuXIGUomUBSnlJGPW47/wCfx+W571vw9l7jqz/lS+Hq8bnPL9ZOFoixcOSRrQVoC5JcxMD5blyUt1uUie0GiUf2r5lZjK2JZonCl4CdO7CoPteXPFl1b3OoxRz2dHGoMZG9LAihoOoswniZVNS8/Ucx1WpNblyvVQUHwZjOVBV9Eed07UM8uvg9CFsQwqDjiP1PnLl+UDHIadayF6WEsxqePq6Ho60J8vtHEPD1f72710Lss60XPLOleB4Fy6wUuy64BIby2VIXR+MHtDulN5WgNJXR1RPzd0i8evt0BOVXBd8J9rrk5rvhl3Fg5Ujiiyw9IlqshhkAk4NRD0c9AO4OeNoDbiVlHNUQJBrVg1lxYqygmVqe0Enqc70QjO1GfUd7pGBqUoGBxRaita1Do2JwyDHFf0gDx2uca12emCPTR3jteQ1mGuqdTEfeCHvcevsea1uGt51p4BUdXcO4OVKMZSNIgk9SxNHK9cltkVT07XLLk8ZyEOraXpW+WaaPiJkd5P2Nw1xLEujhKRjXhV3gZwPDR6vQacRyk1jurh2IdHpIimUMw8nM6G3vRNuI2SegTpQcLcT2uW8bZ2QFdmFXLUtpVDHCoPexkidgx6kujNDUk7glDNE4YUGBZrRcZiG/2qZXtvB0zhOccTi55W4zFCMpHxWnqSK3BUlHKVot3YjAVA4cUM28EO5Y53Q0LMAfE2UhlNFkRQYOvRDoTmBt7VpvSO4OVESNVhtaJTJ20Ks0ZqEsFhoKTGwpZriQVynlOLmymufgyDHcxgz5abHvzzPzBSWKlkDMaBMRjHxGv5fVddePz/4YGIMt70rVuU4RgZCg2WwaDH6qYkl5/SU8OA3JWr0rExOFMOEhUPK29NT0eoscsuSjjK1bHAREpE+yI+1wa7k1yEs1nPOuMjIZQO5K1+0OrAoZCA4ZI/YSxPnmrkfLeBHXERPxFHj+8rp+mfLn29Bqa/us3XjT0dh0V4YyAj30Ru801Ett6cu4j7A45arpD/cMpDdmI7S63pzvit6MIyruFKH6juotBsRAjW4cOAiXOB5vMYjdQ1y9ykRoanHq3uojb01sf8le6LFy+JmpzE0pU0+xxyy8I09tWDk4CrdMbNJMRumvGH2u0XoTOUSqXl2bMpyww69z0LdmFrZid7i+rUGVM/DLuKwqp+E9xcK5LWtesYqQKumMREdau3GmPYsqquCYqjVtWKKqVVVW1QdVkSV5kwkHgcCKqJ2OMexczV0jnkEbWHoTtiY6+BcBBiaFIhrIBOwErrWnuXZZaEbyRQAb2hUISuHLGJkdwFS7Ry2/96ke84/B63L5W7UpRiBTf96VN5+x0xn0kpMHFHL4x8cz7B6pjT2I/cr3k/qd15yFgdDTWJfciV8bNi1sAj3Fz278bcSDjuVzvx/8LT1aZ3rcPD8VHvv4Oxy+a4cVma3b3VZ5NTky5flxwqroSaknqUkm5sB21ruosEZUodlajePa5trc5igmFaeIlZbApWoqwQCakYtGWPEkbtzloQlRuYqzU4hmMZHiWB2ZmpVG3LexS4NxQcKbm5YGvWqFwjaCsFyJCCTpRLxebcdlFE4Ss4bRwPq9CoPFpNB5tm9s7sZs1yxi2julZAxABCmVsgVjjTaPR6zuVjwIqsBV4FmlHbJtUT5mAW8UjntayNrlU0IFWASK9bJKLRISoEGsVJpwYa1IrNe5hqB4hGpYZYqQFkCKIBoODGnagBCIAYJV5sB3ImThUkq5eE9zSVc5eU9yGBrXpW9AeiN24TE0rGNMT37ne4yzHAIVZKLFE0mgaISPV3rOhB8Rq1ExjEjezlA4JRgI7EyG4moFEwjRMCjcRNKsGISYQjK6NP0Wak7cJHfIV9jnq0odY34Wj4Mo/CBQLeljPEGMgXkC9XCWLMr1u3jUd3FI6tIROYRjXqwedK5luSpscU9d9MT7S23qOkP9yP6QZRvzZxtc047j2oTqBWJqPi45XAeNUuHSluNUaqwkZUctwyspdQTjEcMXIZyLotSxZVaAJM5TvK2EqpFikGPeiYjeV5UEsBi3EjaUsoGwlVmwZiSg8kdbc3UiCnwSrXqZyRlwDFExRBM7eXGKcThjiuRy7sHIVE0O/qZMRLYadSOQZ827giYSEqxIA60rBcErUsRUE7fsaJh2XrfTRGyo3OOWjux+nte3PTnYnOE82Dn93udXanCxdwwwrji62MYyta1Cta1qq1rUK1rWIrWtQrWtTSWsNZg6gOHsRqrBwHcwS5URkquHylmvB32bMbQzXKZtoHCP62CNLo+jj0kwDOlYxOwdZ6/kvuyvGJzAY/iQnqxwxcU7sp7SsvS/RWTesAAYqy7nLGpZCNWusQbNVdW1QZVmqkliqD8zFauY3NwqkBM4mvsSn1COZkV+lKnU48jGMxlORxojIQGw4uwxq5jYmTwXkuFRAri642TXMP4XOYmHB0WpkrVw4ShMUOxxzsCuBo6jbrjsqrNsjizQrJLqWxtjvQnglZrtLFDOJCqJoXpUEtrlnZxwSn2Z1o6S5Lccm1dVgspKJ13F0CiYYaxCqwYO3KDuR6OO4IZgSsjVb0Q4JdGhATo3IyIlghpDLNWBVQcEJZsppwV3yRILrchIY9zVZhcHBZnMtzhNYyosjOjQ/J1sEUWA1YISOK1rXs5q1rUK1rot6a5PhlHWkZ1kLNyfhiT/AF1vShp7drE+Y9aw3NyVzxo7vUPa33Se+Pb+p2mZRq5vSyMvukvqj8WfdRxl2OglrPKrjN7tH6iwdNul8HSlVeVMZ8k4jZVAiXEUddQiaLTCbZ6M1GMt54dzMrkpbTVIwB2K8shwdTE9VqxmblluYySLUTmZq0W95WCMQzyMLGOxMRJWVYMmXpfFGQJZQji2rNrWQygbQIYpM0wYoOAZqhiywGzlYZqgBiWKEMkpAlDPIV4MRjldW1XKIaBqhKSJqGBiwXLmXAUY2IGSDqsVCnMSnGBKBElZEb2Y25HguFgoLSW9CUTbkODBQVgCuiQkwM4tqyizVTVNUsDFScUK0TKMg0Iu28+KiIMSvJlFLCYxUqs8owl4u1X7uD4ZdroNkbQe1ohIOkKETHangty1GLmNQaJHHa1ZC1K5sHtezmWvt2J3Oodbrt6eEMTiVpnTY0DCzC1wqUjc3KzJAlxauDMiUCUatcbrWCqwS1hC1ZxYqiZUQYypzLMyB0YVGaUZINALNEM7ekQOiNETKrQJFAqMiKQiygOUNoGktQmgbRtGoVlFIBCWUhFtEAq2quR4LrcEJjCq7KAl4UDJmriT3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| ![Source 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) | -### Beat 18 — MAN. / Kein Treffer +### Beat 18 — ? / Vorläufig - **Trailer**: 00:01:09:03 – 00:01:10:19 (1.64 s) -- **Source** : — (manuell setzen) +- **Source** : 00:09:13:13 – 00:09:15:05 (scene 75, score 0.542) +- ⚠ Score 0.542 unter 0.65 — visuell prüfen - **Rematch**: `python cli.py rematch --beat 18` - **Phase**: Woman in foreground turns her head from profile to face the camera while speaking - **Bild**: Medium shot, three-quarter profile of woman in foreground left, two women positioned behind her to the right, Indoors, minimalist dark background +**[▶️ Frame-Locked Compare Video ansehen](output/cutter_clips/beat_18_compare.mp4)** + | Trailer | Source | |:---:|:---:| -| ![Trailer 18](data:image/jpeg;base64,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) | _(MAN.)_ | +| ![Trailer 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) 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| ### Beat 19 — ? / Vorläufig diff --git a/cli.py b/cli.py index 892e8d3..7296db1 100644 --- a/cli.py +++ b/cli.py @@ -1038,6 +1038,97 @@ def _recover_unmatched_beats_via_vision(results: list, beats: list, cfg) -> list return sorted(new_results, key=lambda r: r.beat_id) +def _recover_short_lowlight_vibe_matches(results: list, beats: list, cfg) -> list: + """Keep obvious short low-light scene hits as provisional instead of no-match. + + Short blue/dark dialogue shots can be correctly ranked by scene-level + histogram/pHash but then rejected by the stricter content aligner because + the shot contains little texture, motion blur, or trailer timecode overlay. + This fallback only accepts the top vibe scene when it has a clear margin and + the local content scan still finds a usable in-point. + """ + from src.core.models import MatchResult, Scene + from src.cv.global_scan import _content_alignment_score, _content_alignment_templates + from src.cv.vibe_check import run_vibe_check + from src.cv.frame_extractor import open_video + + matched_ids = {r.beat_id for r in results} + targets = [b for b in beats if b.beat_id not in matched_ids and b.duration_s <= 2.25] + if not targets: + return results + + raw_scenes = _load_scene_cache_light(cfg) + scenes = [ + Scene( + scene_id=int(s["scene_id"]), + source_path=cfg.paths.source_movie, + start_s=float(s["start_s"]), + end_s=float(s["end_s"]), + start_frame=int(s["start_frame"]), + end_frame=int(s["end_frame"]), + luma_hist=bytes.fromhex(s["luma_hist"]) if s.get("luma_hist") else None, + sat_hist=bytes.fromhex(s["sat_hist"]) if s.get("sat_hist") else None, + phash=s.get("phash"), + ) + for s in raw_scenes + ] + scenes_by_id = {s.scene_id: s for s in scenes} + recovered = list(results) + + with open_video(cfg.paths.source_movie) as cap: + for beat in targets: + templates = _content_alignment_templates(beat, cfg) + if not templates: + continue + hits = run_vibe_check( + beat, + scenes, + top_k=6, + hist_method=cfg.cv.vibe_check.hist_compare_method, + phash_max_distance=64, + ) + if len(hits) < 2: + continue + top, second = hits[0], hits[1] + if top.combined_score < 0.74 or top.combined_score - second.combined_score < 0.03: + continue + scene = scenes_by_id.get(top.scene_id) + if scene is None or scene.duration_s < max(0.5, beat.duration_s): + continue + + best: tuple[float, float] | None = None + scan_end = max(scene.start_s, scene.end_s - beat.duration_s) + step_s = 0.12 + t = scene.start_s + while t <= scan_end: + score = _content_alignment_score(cap, t, templates, cfg) + if best is None or score > best[0]: + best = (score, t) + t = round(t + step_s, 6) + if best is None or best[0] < 0.15: + continue + + content_score, in_point_s = best + final_score = max( + cfg.cv.deep_scan.provisional_match_threshold, + min(0.64, top.combined_score * 0.55 + content_score * 0.45), + ) + recovered.append(MatchResult( + beat_id=beat.beat_id, + scene_id=scene.scene_id, + source_path=scene.source_path, + in_point_s=in_point_s, + out_point_s=in_point_s + beat.duration_s, + in_point_frame=int(in_point_s * cfg.export.edl_frame_rate), + match_score=final_score, + match_location=(0, 0), + is_confirmed=False, + segments=tuple(), + )) + + return sorted(recovered, key=lambda r: r.beat_id) + + def _filter_semantically_invalid_vision_matches(results: list, beats: list, cfg) -> list: """Drop vision-enabled matches whose final action phase contradicts the beat.""" if not cfg.vision.enabled or not results: @@ -1929,6 +2020,7 @@ def cmd_match(args: argparse.Namespace, cfg) -> list: results = _attach_visual_segments(results, beats, cfg) results = _filter_semantically_invalid_vision_matches(results, beats, cfg) results = _recover_unmatched_beats_via_vision(results, beats, cfg) + results = _recover_short_lowlight_vibe_matches(results, beats, cfg) # A targeted one-beat match must NEVER delete or modify any other beat's # cache entry. 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