Palette Consistency for Beauty Sets

BModel data-driven playbook. Use this with your audit report for faster iteration.

Use this guide to optimize beauty-relevant signals: facial readability, finish control, and expression precision.

Why This Metric Matters

Cohesion and palette consistency determine whether your book feels intentional. Inconsistent color temperature or styling drifts reduce trust and category clarity.

How BModel Measures It

BModel uses set-level variance metrics (palette consistency, temperature spread, style confidence, cohesion score) across all selected frames.

Fix It Now: 5 Actions

  1. Use one color family and repeat tonal logic across outfits.
  2. Lock white balance and avoid mixed ambient sources.
  3. Keep camera distance/lens behavior stable for sequence harmony.
  4. Group final images by category objective before submission.
  5. Drop strong single photos that break overall set narrative.

Common Mistakes

7-Day Improvement Protocol

  1. Day 1: define palette and category target.
  2. Day 2-3: shoot all frames in one controlled environment.
  3. Day 4: shortlist by visual continuity first, score second.
  4. Day 5: color-balance the final sequence uniformly.
  5. Day 6-7: re-audit and inspect cohesion/palette movement.

FAQ

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