Devlog

A corpus of 28,756 facial and body observations over 39 peoples

2,681 portraits read by a vision model against 22 controlled vocabularies now yield 28,756 structured observations that feed the trait pages.

  • AI
  • Data
  • Research

On August 31 the corpus run completed. The corpus now covers 2,681 portraits of notable people from 39 peoples, each read by a vision model in a single call against the site's controlled phenotype vocabularies. It holds 28,756 structured observations of facial and body features, recorded as vocabulary values rather than prose.

The trait pages read from this corpus. The head and face families are dense: eyes were read on 2,423 portraits, lips and mouth on 2,413, nose on 2,410 and skin on 2,681, and every one of the 39 peoples carries enough readings in each head and face family to support a trait page.

The corpus turns a question about a people's appearance into counted observations, family by family. Every number on a trait page carries its sample size beside it.

Under the hood

  • One vision-model call per portrait, with a single composed prompt covering every photo-assessable dimension of the 22 vocabularies. The answer returns as structured JSON, one section per anatomical family.
  • Each family writes to its own observation table: one row per portrait where that family returned values, linked to the notable-person record and stamped with the vocabulary version and the analysis model.
  • Every processed portrait is marked as read, including one where a family returns no values, so each portrait passes through the reader exactly once.
  • Selection deduplicates by image, since paired catalog rows for the same people can point at the same photograph.
  • Readings by family: skin 2,681 portraits, eyes 2,423, head shape 2,416, jaw and chin 2,413, lips and mouth 2,413, nose 2,410, face proportions 2,410, neck 2,409, head hair 2,397.
structured observations
28,756
portraits read
2,681
peoples covered
39

See it on the site

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