Demos

AI Face Detect Demo

Test layouts that need subject-aware cropping and safer placement of text around portraits.

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AI Face Detect Demo workflow

AI Face Detect Demo is set up for teams that need repeatable, template-driven output instead of one-off manual design work.

  • Connect face-aware image crops to uploaded assets, approved templates, and API-safe render jobs.
  • Keep all remote image dependencies blocked so production renders use controlled assets only.
  • Use idempotency keys when the same request can be retried by an automation tool.

What this page covers

Test layouts that need subject-aware cropping and safer placement of text around portraits.

  • Use face position data to avoid covering the subject.
  • Preview crop behavior across different source photos.
  • Keep fallback layouts for images without a detected face.

Production checklist

Before using this workflow in a campaign, validate the template, expected dimensions, asset ownership, and output access path.

  • Render the same payload three times and compare output hashes for deterministic behavior.
  • Confirm local fonts are present in the approved whitelist before launch.
  • Monitor completed and failed jobs from the logs page during rollout.