AI PHYSIOGNOMY CASE LIBRARY
AI Face Reading Case Library
Privacy-safe AI face reading cases organized by visible facial features, reviewable evidence and interpretive limits.
How this case library is organized
Each page begins with reviewable visible morphology and then explains traditional associations with explicit limits. Face cases use deterministic virtual illustrations. A user confirms public display when uploading a palm, and the report pages show the processed palm image.
Visible features in this collection
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Distribution of interpretation topics
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Data updated：
Content source and method：Counts come from structured visible observations and localized report fields in qualified published cases. Publication relies on user consent or verified fully synthetic provenance; synthetic examples are labeled separately. Frequencies describe this library only.
How to read face-reading cases
1. Visible evidence and interpretive limits
This library organizes each case around visible, reviewable morphology. A report first records contours, proportions, lines, positions and image-quality limits, then explains how traditional physiognomy commonly associates those observations with broader themes. Direct answers, evidence, cultural interpretations and uncertainty are kept in separate sections. Readers can trace each statement back to a visible signal and see when angle, lighting, cropping or occlusion prevents a reliable observation.
2. Physiognomy guide: how to read these features
Useful comparison starts with combinations rather than isolated labels. Face shape, forehead, brows, eyes, nose, cheek area and chin need to be read in proportion to one another. Hand shape, mounts and the major palm lines also depend on depth, continuity, crossings and differences between hands. The summary page gives a compact map of conclusions; the full analysis develops the evidence, limits, lessons and frequently asked questions. The two templates answer different reading intentions and are evaluated separately for indexability.
3. Face image privacy protected
Privacy and source quality are publishing requirements. Public face cases never expose the uploaded face photograph; they use a virtual illustration generated from the analysis result and carry a clear privacy label. Uploading a palm requires confirmation that the processed image will appear on public report pages, and the owner can withdraw the report with a private token. Blurred, strongly reflected, severely cropped or unidentifiable inputs are not converted into confident claims. Thin content, incomplete translations or broken metadata stay outside the sitemap.
4. Compare with other traditional tools
The material supports cultural study and entertainment. It cannot establish character, intelligence, illness, financial outcomes or a fixed future, and it does not replace medical, legal, investment or career advice. BaZi can provide a separate birth-time perspective, while LiuYao addresses a specific question and time window. Those tools use different inputs and limits; comparing them can broaden context without turning several cultural readings into a factual prediction.
Qualified cases are being generated. The collection becomes indexable after it reaches the content threshold.