Eye Area Condition Result Scheme

Haut.AI provides a set of AI algorithms that estimate the condition of the skin in the eye area.

Description

Eye Area Condition Algorithm

algorithm_tech_name

eye_area_condition

area_name

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

• face

• left_eye_area_outer

• right_eye_area_outer

main_metric

The main metric is an overall score that indicates the condition of the skin around the eyes in each area_name

"main_metric": {
                "value": 43,
                "widget_type": "bad_good_line",
                "name": "Eye Area Condition",
                "tech_name": "eye_area_condition",
                "widget_meta": null
            },

• value The eye area skin condition score ranges from [0,100]. A higher value in this parameter is associated with less prominent eye bags, lacrimal grooves, and dark circles.

• The score 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": "Eye Area Condition"

• "tech_name": "eye_area_condition"

sub_metrics

The algorithm returns three sub-metrics - Dark Circle Score,Eye Bags Score, and Lacrimal Groove Score that evaluate the condition of the skin in the eye area

"sub_metrics": [
                {
                    "value": 42,
                    "widget_type": "bad_good_line",
                    "name": "Dark Circle Score",
                    "tech_name": "dark_circles_score",
                    "widget_meta": null
                },
                {
                    "value": 45,
                    "widget_type": "bad_good_line",
                    "name": "Eyes Bags Score",
                    "tech_name": "eyes_bags_score",
                    "widget_meta": null
                },
                {
                    "value": 47,
                    "widget_type": "bad_good_line",
                    "name": "Lacrimal Groove Score",
                    "tech_name": "lacrimal_groove_score",
                    "widget_meta": null
                }
            ]

• Dark Circle Score evaluates the presence of dark circles for each area_name

  • value ranges from [0,100].The higher the value of this parameter, the less prominent the dark circles

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

  • "name": "Dark Circle Score"

  • "tech_name": "dark_circles_score"

• Eyes Bags Score evaluates the presence of eye bags for each area_name

  • value ranges from [0,100].The higher the value of this parameter, the less prominent the eye bags

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

  • "name": "Eye Bags Score"

  • "tech_name": "eyes_bags_score"

• Lacrimal Groove Score evaluates the presence of lacrimal grooves for each area_name

  • value ranges from [0,100].The higher the value of this parameter, the less prominent the lacrimal groove

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

  • "name": "Lacrimal Groove Score"

  • "tech_name": "lacrimal_groove_score"

masks_restored

The algorithm returns three vectorized masks "name": "Dark Circles Mask","name": "Eyes Bags Mask" and "name": "Lacrimal Groove Mask" for dark circles, eye bags, and lacrimal groove objects on a face-aligned image. All masks are polygon_masks

• "mask_type": "polygon_mask"

• features

  • geometry

    • "type": "Multipolygon"

  See more on Masks here

masks_original

The algorithm returns three vectorized masks "name": "Dark Circles Mask","name": "Eyes Bags Mask" and "name": "Lacrimal Groove Mask" for dark circles, eye bags, and lacrimal groove objects on an original image. All masks are polygon_masks

• "mask_type": "polygon_mask"

• features

  • geometry

    • "type": "Multipolygon"

  See more on Masks here

Example (JSON)

106KB

eyesbags.json

Open

eye_area_condition.json