DEEP DIVE · WHIPLASH
The full breakdown
Detection, audio and scene analysis across every frame of Whiplash — derived from object recognition, transcript alignment and shot segmentation.
2014Drama, Music, Thriller106.8 min● analyzed May 26, 2026
Total Detections
79,372
objects + faces
Unique Objects
127
distinct types
Detections / min
743.5
avg rate
Night Scenes
92.2%
low-light frames
Words Spoken
5,607
transcribed
Named Actors
13
face-id matched
SIX-AXIS GENOME
Movie DNA radar
Darkness Index35.2%
Darkness RatingBright
Action Intensity5.3
Action RatingModerate
People Density1.89 people/min
Social RatingIntimate
Vehicle Density0.02 vehicles/min
Chase PotentialLow
Indoor %89.5%
SettingIndoor
Object Diversity127 types
Visual ComplexityHigh
Pacing SignatureDynamic
FUN FACTS
Things the model surfaced
Whiplash uses 25% close-ups, surpassing the average of its Drama peers by a substantial 9 percentage points, outpacing 8 out of 8 other Drama films.
3,209
unique people spotted (87% of frames)
"fucking" is said 39 times — once every 2.7 minutes.
Miles Teller is on screen for 41 of 107 minutes — 38% of the runtime.
The longest stretch of silence runs 18 min 2 sec — no dialogue at all.
79
profanity instances across the runtime — roughly one every 81 seconds.
Only 4.8% of all detected faces are smiling across the entire film.
At 144 BPM, the soundtrack rarely lets up — one of the faster-paced scores in the database.
1,535
unique words spoken out of 5,607 total — a vocabulary richness of 27.4%.
AI detected 127 unique object types across 79,372 frame-by-frame detections.
385
unique chairs spotted (8% of frames)
257
unique ties spotted (4% of frames)
104
unique cups spotted (3% of frames)
125
unique bottles spotted (3% of frames)
46
unique clocks spotted (2% of frames)
74
unique wine glasses spotted (2% of frames)
92.2%
of the movie takes place at night
119
weapon appearances (1 per minute)
Shot predominantly with warm tones
High color saturation — vivid visual style