> For the complete documentation index, see [llms.txt](https://docs.saas.haut.ai/haut.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.saas.haut.ai/haut.ai/haut.ai-features/algorithms/face-metrics-2-0/uniformness-algorithm-experimental.md).

# Uniformness Algorithm (experimental)

What the experimental Uniformness Algorithm estimates, the metrics it returns, and why foundation and other cosmetics affect it.

## About Algorithm

{% hint style="warning" %}
**Disclaimer**

The Uniformness Algorithm is experimental. Results are approximate, may vary under different conditions, and are not intended for medical diagnosis or treatment.

Skin uniformness is not a scientifically defined parameter, as many factors and pigments can influence the skin’s visual appearance. Visual uniformness may differ significantly from natural skin uniformness when cosmetics such as foundation, concealer, BB/CC creams, color correctors, or setting powders are applied before taking a photo.

The algorithm is sensitive to image quality and lighting. Insufficient spatial resolution (below 2500 pixels), uneven lighting, shadows, or reflections can affect detection and cause fluctuations in the uniformness score.
{% endhint %}

1. This Algorithm estimates the visible skin texture non-uniformness, such as eruptions, age spots, freckles, and blood vessels close to the surface, along with texture-associated skin features.
2. This Algorithm estimates indicated skin health parameters on: forehead, right cheek, left cheek areas.
3. The Main Metric for this Algorithm is the Uniformness Score, with a range from 0 to 100.
   1. Values from 80 to 100 are considered a relatively good skin condition with relatively uniform texture skin.
   2. Values from 50 to 70 are considered as skin with visible skin texture non-uniformness.
   3. Values below 50 are considered as an alerting skin condition, that might require specialist attention.
   4. Uniformness Score is a non-linear transformation of a spatial information about non-uniform skin texture clusters.
4. There are no Submetrics for this Algorithm.

***

## Algorithm API

{% hint style="warning" %}
API access is available only for <mark style="color:purple;">**Professional**</mark> plan clients
{% endhint %}

See [Uniformness Result Scheme](/haut.ai/developers/saas-api-overview/api-for-face-metrics-2.0/uniformness.md).

***

{% hint style="warning" %}
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{% endhint %}

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