METHODOLOGY · TRUST CENTER

How Style Look Lab approaches analysis

The shared standards behind every analysis—and a clear path into the detailed method for each product that is actually available.

SHARED ACROSS PRODUCTS

The rules before the result

01

Check the input

A useful result starts by asking whether the submitted evidence is clear enough for the question being answered.

02

Separate evidence from judgment

Observable signals, deterministic transformations, and model interpretation do different jobs and should remain distinguishable.

03

Keep uncertainty visible

Confidence describes support in the available evidence. It is not a guarantee, a laboratory reading, or a statistical accuracy claim.

04

State the boundary

Every method explains what photos can distort, what the analysis does not infer, and when a retake or real-world check matters more.

05

Test for avoidable bias

Skin depth, ethnicity, age, or body size must not become shortcuts for a styling category that should be based on relevant evidence.

06

Give the user control

Photos have a stated purpose and retention policy. Account tools provide export, and support handles verified deletion requests.

DETAILED METHODS

Read the method behind each live analysis

AVAILABLE NOW · VERSION 2026.08

Body Shape Classification

How four circumference measurements, ratios instead of fixed inch differences, published cut-off lines, two-candidate handling at the boundaries, and the sources behind each threshold fit together. The result names a proportion group; it does not rank one.

The six groups, and why six rather than the more common five, are laid out in the guide to the six body shapes.

Sources & limitations

The cited color-science sources support measurement concepts and known image limitations. They do not establish the 12-season system as a biological or medical classification.

  1. CIE 256:2025 — Measurement of Human Skin ColourMeasurement conditions and limits for human skin colour.
  2. He et al. (2022) — Facial skin colour from digital imagesEvidence on estimating facial skin colour from images.
  3. Wang et al. (2018) — Skin colour measurement variabilityShows why location and measurement conditions affect readings.
  4. Sharma, Wu & Dalal (2005) — The CIEDE2000 color-difference formulaReference for perceptual colour-difference calculations.
  5. Google — Improving skin tone representation with the Monk Skin Tone ScaleGoogle’s introduction to the 10-tone representation scale; it does not define undertones or validate this site’s questionnaire.