The model, visible
AI Attractiveness Test — With the Cards Face Up
Most AI attractiveness test pages hide the model and invent the score. This one shows you the 478 landmarks it detects, then every metric computed from them — and what AI genuinely cannot decide.
In short: This AI attractiveness test uses machine learning for exactly one job: locating 478 facial landmarks on your photo, on-device. Scoring is transparent geometry — published formulas, versioned weights, no secret model judging beauty. The 'AI' label describes the detection step, and this page proves it by drawing every point on your photo.
By FaceReport Research · Updated October 23, 2026
Honest AI
What AI really does in an AI attractiveness test
The honest division of labor: perception by model, arithmetic by formula, judgment by nobody.
A face landmark model is a genuine piece of machine learning: trained on annotated faces, it predicts point positions — eye corners, brow ridges, jaw curve — in milliseconds. That perception step is what earns the AI in this AI attractiveness test. What the model does not do in this AI attractiveness test is score beauty: it was never trained on attractiveness ratings, and it outputs coordinates, not opinions.
The scoring layer is deliberately old-fashioned: distance, ratio and symmetry arithmetic in published TypeScript functions, with a version stamp and a public weights table. Why not a neural beauty score? Because in an AI attractiveness test an unexplainable score is unanswerable. When your AI attractiveness test result says symmetry 74.2, you can recompute it from the overlay; a black box would ask you to pray.
- 478
- landmark points the AI attractiveness test draws on your photo
- 0
- training on beauty labels — the model detects geometry, never judges it
- 1
- model file, served from this site and cached — no third-party AI API
The pipeline
Inside the AI attractiveness test pipeline
From file to report in five steps you can watch happen.
- 1
Step 1 — the AI attractiveness test loads its model
On first use, your browser downloads the landmark model (about 4 MB) from this site's own hosting. After that it's cached, and every later AI attractiveness test run starts instantly — offline included.
- 2
Steps 2–3 — the AI attractiveness test checks quality
The model maps your photo; the engine then checks roll, yaw, eye closure and resolution. One clear frontal face passes; anything else gets a plain-language retake message.
- 3
Steps 4–5 — geometry and the AI attractiveness report
Landmarks become metrics — symmetry pairs, spacing, ratios, tilt — and the weighted index of the AI attractiveness test lands beside its full breakdown. The overlay drawing the AI attractiveness test result uses the exact same point set.
Every step runs in your browser. There is no server round-trip after the model download — the AI attractiveness test is as private as a calculator.
Skeptic's corner
Why most AI attractiveness test claims are fake
A field guide to the tricks, so you can spot them anywhere.
The invented percentile in fake AI attractiveness tests
'More attractive than 87% of users' requires a database and a comparison that almost no AI attractiveness test site actually runs. If the number arrives with no method section, it is decoration.
The mysterious model behind an AI attractiveness test
Sites that say 'our deep learning model was trained on millions of faces' rarely show a single landmark. Real detection is showable — this page shows all 478 points — and unshown claims are marketing.
The stable-score illusion in AI attractiveness tests
Any honest AI attractiveness test output moves with angle, light and expression. A tool that returns the same number for every photo of you isn't measuring your face; it's hashing your filename.
Our response to this landscape is radical transparency: the detection is visible, the formulas are public, the weights are fixed and versioned, and the disclaimers are honest. The result is an AI attractiveness test you can argue with — which is what a good tool invites.
Privacy
Privacy in the AI attractiveness test
Face photos plus AI is a combination that deserves exact language.
- Your photo is decoded and analyzed in your browser's memory; there is no upload endpoint in the code at all.
- The AI model file itself is self-hosted on this domain — no third-party AI API ever receives a request about your face.
- Landmarks, metrics and overlays exist only for the lifetime of the tab; refresh and they're gone.
- The downloadable annotated PNG is rendered locally and saved only when you click.
This posture isn't a feature bolted on; it shaped the AI attractiveness test architecture. The AI attractiveness test could have been a five-line API call to a cloud vision service — and your face would live on someone else's server forever. It isn't, and it doesn't.
Related
Around this AI attractiveness test
Where to go next, depending on what intrigued you.
If the report's metrics interested you more than the machinery, the attractiveness test page presents the same numbers with the emphasis on interpretation. If the PSL mapping is your context, the PSL score and PSL scale pages explain the 1–8 ladder this index feeds. The symmetry triptych shows the mirror mathematics behind the heaviest-weighted component.
And if you came to see whether AI can judge beauty: it cannot, and any AI attractiveness test claiming otherwise is selling certainty it doesn't have. What it can do — precisely, verifiably, privately — is measure. This page does exactly that, with its whole hand showing.
Frequently asked questions about AI attractiveness test
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