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The Grand Budapest Hotel

Film Profile · THE-GRAND-BUDAPEST-HOTEL

The Grand Budapest Hotel

2014Comedy / Drama / AdventureComedy1h 40m
Detections86,484
Night Frames93%
Dialogue WPM86
Dom. Emotionneutral
CharactersCompareDeep Dive

GENOME

Movie DNA

Six core dimensions, each scored against the genre baseline.

Darkness-46% vs genre
38.1/100

Bright

Action Intensity-91% vs genre
5.7/100

Moderate

People Density-97% vs genre
2.0/100

Social

Indoor / Outdoor
91% indoor

Indoor · 90.9% indoors

Object Diversity
72/100

High

Pacing
1.0 cuts/min

Highly Variable · cuts/min

FINGERPRINT

The full shape, vs. genre

Six axes overlaid against the average for this film's primary genre.

DARKNESS93ACTION57DIALOGUE40PEOPLE61VEHICLES2VISUAL100
The Grand Budapest HotelComedy avg · 9 titles

THE ARC

Motion & brightness across the runtime

Hover to scrub. Spikes mark high-action sequences. Dips reveal quiet stretches.

Motion Intensity
Brightness
People
0:00 → 100m
02550751000m25m50m75m100m
See every beat →

STRUCTURE

Scene mix by act

Three-act split — how the visual tone shifts from setup through climax.

ACT 1 · SETUP
●night dominates39%
ACT 2 · CONFRONTATION
●night dominates38%
ACT 3 · CLIMAX
●outdoor dominates39%
Full act breakdown →

PEAKS & VALLEYS

When the film pushes — and breathes

The single most-intense minute and longest stretch of stillness.

MOST INTENSE MINUTE
1:27:43
motion 87/100
BREATHING ROOM
3calm stretches
longest 996.4s at 46:25
All calm sequences · all silences →

CHROMA

Color signature

Frame-sampled palette — temperature, saturation, and how the look shifts across the runtime.

Temperaturewarm
Saturationmuted
Frames sampled4,792
Film color bandhow the palette shifts across the runtime · 60 buckets
0:00¼½¾end
Overall palette6 dominant colors · % of sampled frames
#4C2C25
25.8%
#87402C
17.6%
#A76A5A
16.6%
#BE938B
14.8%
#4F5762
13.9%
#E2CAC7
11.3%
Palette by scene type5 dominant colors per context · sampled within scene class
Empty scenes
#D3B9BC
#C18F8D
#926860
#EDDDDF
#543D40
Indoor scenes
#4E2919
#7C381C
#9F5C3A
#C7846F
#EBBEAE
Intimate scenes
#4F2C21
#754A39
#A5634B
#BF8572
#EBC1AD
Night scenes
#5B2B1F
#8F5342
#B48274
#3C4A59
#DBBCB1
Outdoor scenes
#49302D
#BA8378
#8C4635
#DFC5C3
#5F6772
Vibrant scenes
#7A3E28
#A2553C
#871E0D
#C87555
#22658C

DETECTIONS

What appears on screen most

The four most-present objects — full breakdown with categories in Deep Dive.

Chair10%
Tie13%
Cup6%
Potted plant4%
+ 6 more · person in 81% of frames
Every detected object · by category →

ON SCREEN

Cast at a glance

Top 3 actors by screen time, color-coded by dominant emotion.

RF
Ralph Fiennes
M. Gustave
26.0m · sad
SR
Saoirse Ronan
Agatha
4.4m · neutral
JG
Jeff Goldblum
Deputy Kovacs
4.0m · sad
4 CHARACTERS · EMOTION-CODED ANALYSISSee all characters →

DIALOGUE

Words across the runtime

Volume and pace at a glance. Top vocabulary and per-act WPM in Deep Dive.

40% dialogue60% silence / score
8,620
total words
86
words / min
39 · 0.5%
profanity flagged
Top vocabulary · WPM by act · profanity →