This ai face shape detector is a text-based decision worksheet for people who want to create a transparent face-proportion classification without implying biometric AI is running. Its starting material is user-entered ratios, visible contour notes, confidence ratings, and the hairstyle decision connected to the analysis. The browser returns an explainable classification note that shows why more than one face-shape family may remain plausible. It does not inspect a face, accept a photograph, call a live model, create an account, or save a project.
Make an AI-style result explainable
Enter the measurement source and camera conditions alongside each ratio so the explanation can reveal weak evidence.
Score confidence separately for hairline, cheekbone, jaw, and length observations; one hidden boundary should not lower every field equally.
Record ratios with a confidence score
The useful controls for this task are ratio source, confidence, candidate families, contradictory cues, and styling objective. Keep uncertainty visible rather than turning an estimate or preference into a fact.
Keep the two nearest shape families and list which measurement separates them.
Flag contradictory cues instead of averaging them into a false single answer.
Keep contradictory cues in the output
Explain the classification in plain language: which widths are similar, where taper begins, and how much length exceeds width.
If the result changes after a small input adjustment, label it sensitive and avoid presenting the category as certain.
Worked explainable classification
Entered ratios show a longer face, broad cheekbones, and a jaw only slightly narrower than the forehead. The explanation keeps oblong, oval, and soft-diamond possibilities open, identifies the conflicting cues, and suggests hairstyle tests that would reveal personal preference.
The example is a reviewable planning record. It deliberately stops before claiming that a visual result, salon technique, or personal outcome has been verified.
Use uncertainty to plan style tests
An explainable result should show the evidence and uncertainty behind the label. If a single measurement changes the category, treat the classification as fragile and focus on styling experiments instead.
Connect each possible family to a styling experiment, not a rule about what the person should hide or correct.
Avoid personality, health, ancestry, age, gender, or identity inferences; none follow from the entered proportions.
No biometric AI runs on this page
No facial recognition, identity matching, medical inference, demographic classification, or automated photo analysis occurs. Measurements taken from selfies can be distorted and should be treated as rough.
A future vision model would need bias testing, consent, retention limits, security review, and clear confidence communication before release.
The deterministic prototype exists to test whether an explanation is more useful than a black-box label.
Questions about ai face shape detector
Why call it AI if no model is running?
The page validates the intended AI workflow with deterministic logic and clear explanations. It does not claim that live AI analysis is available.
Do you store face measurements?
No. The current site has no account, analytics, upload, or persistent project storage.
Can the result identify me or infer ethnicity?
No. Identity and demographic inference are outside scope and are not performed.
A practical handoff after the worksheet
Compare the worksheet with a neutral mirror view and professional styling judgment rather than treating the output as ground truth.
Delete the visible form contents by refreshing or closing the page; this site does not create a persistent profile.
Review the decision record before leaving
Prepare the handoff as a short decision record. State that the immediate task is to create a transparent face-proportion classification without implying biometric AI is running. Under “known,” place only details supported by user-entered ratios, visible contour notes, confidence ratings, and the hairstyle decision connected to the analysis. Under “choice,” list the alternatives created from ratio source, confidence, candidate families, contradictory cues, and styling objective. Under “open,” add everything that requires inspection of real hair, tools, technique, time, or budget. The browser result—an explainable classification note that shows why more than one face-shape family may remain plausible—is complete when those three columns remain understandable without the page. This format also makes it easier to revise one assumption after consultation without rewriting the entire idea.
Check that the preferred direction can be described without relying on a marketing label. Keep only non-sensitive notes you deliberately choose to copy. If a consultation changes the plan, record the reason—texture, density, condition, growth pattern, technique, time, cost, comfort, or preference—so a later comparison begins with better evidence rather than another vague request.
WigSay currently provides deterministic browser text only. No upload, remote fetching, live AI, facial recognition, account, payment, analytics vendor, advertising tracker, or persistent project storage is enabled. Refreshing or closing the page clears the visible interaction. If those facts change, the product, security, provider, retention, consent, legal, and pricing disclosures must change before release.
The page earns publication only while its visible wording, form behavior, result state, privacy boundary, and professional limitations remain consistent with the source code and public policies.