Film Profile · GET-OUT
Get Out
Detections70,667
Night Frames68%
Dialogue WPM56
Dom. Emotionneutral
GENOME
Movie DNA
Six core dimensions, each scored against the genre baseline.
Darkness-79% vs genre
12/100
Very Bright
Action Intensity+6% vs genre
52/100
Moderate
People Density-6% vs genre
46/100
Intimate
Indoor / Outdoor
84% indoor
Indoor · 84.0% indoors
Object Diversity
70/100
High
Pacing
1.0 cuts/min
Dynamic · cuts/min
FINGERPRINT
The full shape, vs. genre
Six axes overlaid against the average for this film's primary genre.
Get OutHorror avg · 8 titles
THE ARC
Motion & brightness across the runtime
Hover to scrub. Spikes mark high-action sequences. Dips reveal quiet stretches.
Motion Intensity
Brightness
People
STRUCTURE
Scene mix by act
Three-act split — how the visual tone shifts from setup through climax.
PEAKS & VALLEYS
When the film pushes — and breathes
The single most-intense minute and longest stretch of stillness.
CHROMA
Color signature
Frame-sampled palette — temperature, saturation, and how the look shifts across the runtime.
Temperaturewarm
Saturationmuted
Frames sampled4,992
Film color bandhow the palette shifts across the runtime · 60 buckets
0:00¼½¾end
Overall palette6 dominant colors · % of sampled frames
#4C3721
24.6%
#6E5D3F
21.0%
#817C68
19.3%
#3A4850
14.7%
#A5A08F
13.5%
#D2CEC8
6.8%
Palette by scene type5 dominant colors per context · sampled within scene class
General scenes
#4B3A29
#6C6247
#928664
#ADA68E
#DAD4C9
Intimate scenes
#4D3721
#786140
#89897A
#465552
#CAC7BA
Night scenes
#4E3520
#6A5C45
#2B3F4F
#838576
#BFBEB3
Outdoor scenes
#503A24
#766A4F
#979381
#3E4A4F
#C9C6BF
Romantic scenes
#463E31
#695F43
#857F69
#ACA697
#DDD8D4
Vibrant scenes
#7E6032
#6F4322
#9E8042
#2B4F74
#3E8399
DETECTIONS
What appears on screen most
The four most-present objects — full breakdown with categories in Deep Dive.
ON SCREEN
Cast at a glance
Top 3 actors by screen time, color-coded by dominant emotion.
DK
Daniel Kaluuya
Chris Washington
37.3m · sad
AW
Allison Williams
Rose Armitage
13.5m · happy
LR
Lil Rel Howery
Rod Williams
6.5m · neutral
AI-DISCOVERED FACTS
AI-Discovered Facts — Get Out (2017)
Insights surfaced by machine analysis of every frame, audio track, and object.
- Get Out boasts dialogue that's a whopping 72.7% faster than the average Horror film, outpacing 7 out of 7 of its genre companions with a mind-bending 56.10 words per minute.
- 1,864 unique people spotted (88% of frames)
- "chris" is said 35 times — once every 3.0 minutes.
- Daniel Kaluuya is on screen for 37 of 104 minutes — 36% of the runtime.
- The longest stretch of silence runs 13 min 39 sec — no dialogue at all.
- 71 profanity instances across the runtime — roughly one every 88 seconds.
- Only 18.1% of all detected faces are smiling across the entire film.
- The 5 most intense moments all happen within 4 seconds of each other.
- At 125 BPM, the soundtrack rarely lets up — one of the faster-paced scores in the database.
- 1,632 unique words spoken out of 5,842 total — a vocabulary richness of 27.9%.
- AI detected 70 unique object types across 70,667 frame-by-frame detections.
- 550 unique chairs spotted (15% of frames)
- 226 unique wine glasses spotted (3% of frames)
- 110 unique potted plants spotted (5% of frames)
- 103 unique cars spotted (5% of frames)
- 142 unique couchs spotted (4% of frames)
- 124 unique cups spotted (2% of frames)
- 160 unique ties spotted (3% of frames)
- 91 unique dining tables spotted (3% of frames)
- 95 unique bottles spotted (2% of frames)
- Features 279 dog appearances
- Contains 71 profanities (0.7 per minute)
- Longest silence: 14 minutes of unbroken quiet
- 31% of frames are close-ups
- The film's emotional journey ends on a neutral note
- Shot predominantly with warm tones
DIALOGUE
Words across the runtime
Volume and pace at a glance. Top vocabulary and per-act WPM in Deep Dive.
34% dialogue66% silence / score
5,842
total words
56
words / min
71 · 1.2%
profanity flagged
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