🔴Wrinkles Response Scheme

Haut.AI provides an AI algorithm that estimates wrinkles in different facial areas and the whole face.

The algorithm is deprecated. We suggest to use Lines algorithms that has more features and has a better accuracy

Description

Wrinkles are a sign of the aging process. As we age and are exposed to adverse environmental factors, the collagen and hyaluronic acid content of our skin decreases, causing it to lose its elasticity and moisture. These changes lead to the development of wrinkles and their higher prominence over time. The higher the value of this parameter, the fewer wrinkles you have.

"algorithm_tech_name": "wrinkles"

area_name

The algorithm returns metrics and sub-metrics for the following facial areas:

  • face

  • forehead

  • right_eye_area

  • left_eye_area

main_metric

The main metric is an overall score indicating the wrinkles for each area_name

"main_metric": {
                "value": 76,
                "widget_type": "bad_good_line",
                "name": "Wrinkles Score",
                "tech_name": "wrinkles_score",
                "widget_meta": null
            },

  • value the wrinkles score ranges from [0,100].The higher the value of this parameter, the fewer wrinkles you have. Wrinkles can be classified into six classes based on value:

    • (90,100] - Excellent

    • (80,90] - Great

    • (70,80] - Good

    • (50,70] - Average

    • (30, 50] - Poor

    • [0,30] - Bad

  • "widget_type": "bad_good_line" indicates that a higher value is better

  • "name": "Wrinkles score"

  • "tech_name": "wrinkles_score"

sub_metrics

The algorithm returns two sub-metrics - Deep Wrinkles Density and Fine Wrinkles Density that evaluate the density of deep and fine lines.

"sub_metrics": [
                {
                    "value": 1,
                    "widget_type": "density",
                    "name": "Deep Wrinkles Density",
                    "tech_name": "deep_wrinkles_density",
                    "widget_meta": null
                },
                {
                    "value": 0,
                    "widget_type": "density",
                    "name": "Fine Wrinkles Density",
                    "tech_name": "fine_wrinkles_density",
                    "widget_meta": null
                }
            ]

  • Deep Wrinkles Density evaluates the presence of deep lines in each area_name

    • value this ranges from [0,100].The higher the value of this parameter, the more deep wrinkles you have

    • "widget_type": "density"

    • "name": "Deep Wrinkles Density"

    • "tech_name": "deep_wrinkles_density"

  • Fine Wrinkles Density evaluates the presence of deep lines in each area_name

    • value this ranges from [0,100].The higher the value of this parameter, the more fine wrinkles you have

    • "widget_type": "density"

    • "name": "Deep Wrinkles Density"

    • "tech_name": "deep_wrinkles_density"

masks_restored

The algorithm returns a vectorized masks of wrinkles for a face-aligned image

  • "mask_type": "polygon_mask"

  • features

    • geometry

      • "type": "Multipolygon"

    See more on Masks here

masks_original

The algorithm returns a vectorized masks of wrinkles for an original image

  • "mask_type": "polygon_mask"

  • features

    • geometry

      • "type": "Multipolygon"

    See more on Masks here

Example (JSON)

PreviousTranslucency Result SchemeNextAPI for Recommendation Engine Application

Last updated