Redness API Response Scheme
Haut.AI provides AI algorithms that analyze the overall skin redness and skin irritation for different facial areas and for the whole face.
Description
Our skin has a natural pink color because of our blood vessels. Increased skin redness can be associated with allergic reactions and inflammatory processes. The most common environmental factors leading to facial redness are cold air or ultraviolet radiation.
A higher skin redness level is associated with a lower value for this parameter.
"algorithm_tech_name": "redness"
area_name
area_name
The algorithm returns metrics and sub-metrics for the following facial areas:
face
forehead
nose
right_cheek
left_cheek
main_metric
main_metric
The main metric is an overall score that indicates the redness of each area_name
value
the redness score ranges from[0,100]
A higher skin redness level is associated with a lower value for this parameter. The redness can be classified into six classes based onvalue
:(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, i.e., 100 corresponds to the absence of red areas on the skin while 0 corresponds to extremely irritated skin"name": "Redness score"
"tech_name": "redness_score"
sub_metrics
sub_metrics
The algorithm returns two types of sub-metrics - Redness Global Score
and Redness Local Score
Redness Global Score
evaluates the degree of global rednesses for eacharea_name
value
the redness global score ranges from[0,100]
A higher skin redness level is associated with a lower value for this parameter"widget_type": "bad_good_line"
indicates that a higher value is better"name": "Redness Global Score"
"tech_name": "redness_global_score"
Redness Local Score
evaluates the degree of local rednesses (blood vessels, irritation, etc.) for eacharea_name
value
the redness local score ranges from[0,100]
A higher local redness level of the skin is associated with a lower value for this parameter"widget_type": "bad_good_line"
indicates that a higher value is better"name": "Redness Local Score"
"tech_name": "redness_local_score"
masks_restored
masks_restored
The algorithm returns a vectorized heatmap mask of regions with high redness for a face-aligned image.
"mask_type": "heatmap_mask"
masks_original
masks_original
The algorithm returns a vectorized heatmap mask of regions with high redness for an original image
"mask_type": "heatmap_mask"
Example (JSON)
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