Settings

System settings

Parameter	Description	Type	Default value
verboseLogging	Level of log verbosity. 1 - Errors, 2 - Warnings, 3 - Info, 4 - Debug.	"Value::Int1"	0
betaMode	Enable experimental features (0 - Off, 1 - On).	"Value::Int1"	0
defaultDetectorType	Detector type: FaceDetV1, FaceDetV2, FaceDetV3.	"Value::String"	0

Verbosity level sets the upper limit of what type of messages may be printed out by the Luna SDK. For example, if user set verboseLogging to 3, it means that Errors, Warnings and Info messages will be printed out to the console. Verbose level of 0 indicates that there are no logging messages printed out at all.

Example:

<section name="system">
    <param name="verboseLogging" type="Value::Int1" x="0" />
    <param name="betaMode" type="Value::Int1" x="0" />
    <param name="detectorType" type="Value::String" text="FaceDetV1" />
</section>

Descriptor factory settings

Descriptor factory is a facility that creates descriptor extractors and matchers. Both of them utilize algorithms that require a number of coefficients ("weights") to operate properly.

Parameter	Description	Type	Default value
model	CNN face descriptor version.	"Value::Int1"	54
	Possible values: 54, 56, 57, 58, 59
useMobileNet	MobileNet is faster but less accurate. Possible values: 0 - don't use mobile net version, 1 - use mobile net version.	"Value::Int1"	0
distance	Distance between descriptors on matching. L1 faster, L2 make better precision. Possible values: L1, L2.	"Value::String"	"L2"
descriptorCount WarningLevel	Threshold, that limits the ratio of created descriptors to the amount, defined by your license. When the threshold is exceeded, FSDK prints the warning.	"Value::Float1"	0.9
calcSimilarity	Enable similarity calculation during matching process. Possible values: 1 - enable, 0 - disable.	"Value::Int1"	1
calcDistanceSqrt	Enable calculation of the square root of distance. Possible values: 1 - enable, 0 - disable	"Value::Int1"	1

Models with versions 54, 56 and 57 support just L2 distance.

Example:

<section name="DescriptorFactory::Settings">
    <param name="model" type="Value::Int1" x="54" />
    <param name="useMobileNet" type="Value::Int1" x="0" />
    <param name="distance" type="Value::String" text="L2" />
    <param name="descriptorCountWarningLevel" type="Value::Float1" x="0.9" />
    <param name="calcSimilarity" type="Value::Int1" x="1" />
</section>

FaceDetV3 detector settings

Parameter	Description	Type	Default value
ScoreThreshold	Detection score threshold (GRB) in [0..1] range.	"Value::Float1"	0.904
ScoreThresholdIR	Detection score threshold (InfraRed) in [0..1] range.	"Value::Float1"	0.784
RedetectScoreThreshold	Redetect score threshold in [0..1] range	"Value::Float1"	0.357
NMSThreshold	Overlap threshold for NMS in [0..1] range	"Value::Float1"	0.3
minFaceSize	Minimum face size in pixels.	"Value::Int1"	50
nms	Type of NMS: mean or best	"Value::String"	mean
RedetectTensorSize	Target face after preprocessing for redetect	"Value::Int1"	80
	Non-public parameter. Do not change.
RedetectFaceTargetSize	Target face size for redetect	"Value::Int1"	45
	Non-public parameter. Do not change.
paddings	Extension of rectangle for RGB mode. Do not change.	"Value::Float4"	see below
paddingsIR	Extension of rectangle for InfraRed mode. Do not change.	"Value::Float4"	see below
planPrefix	Plan prefix	"Value::String"	FaceDet_v3_5
cropPaddingAlignment	Non-public parameter. Do not change.	"Value::Int1"	64
batchCapacity	Non-public parameter. Do not change.	"Value::Int1"	16
concurrentBatchSubmission	Non-public parameter. Do not change.	"Value::Int1"	1
detectMean	Non-public parameter. Do not change.	"Value::Float3"	see below
detectSigma	Non-public parameter. Do not change.	"Value::Float3"	see below
redetectMean	Non-public parameter. Do not change.	"Value::Float3"	see below
redetectSigma	Non-public parameter. Do not change.	"Value::Float3"	see below

<section name="FaceDetV3::Settings">
     <param name="ScoreThreshold" type="Value::Float1" x="0.89"/>   <!-- used for RGB mode -->
     <param name="ScoreThresholdIR" type="Value::Float1" x="0.784"/> <!-- used for InfraRed mode -->
     <param name="RedetectScoreThreshold" type="Value::Float1" x="0.357"/>
     <param name="NMSThreshold" type="Value::Float1" x="0.3"/>
     <param name="minFaceSize" type="Value::Int1" x="50" />
     <param name="nms" type="Value::String" text="mean"/> <!-- best, mean -->
     <param name="RedetectTensorSize" type="Value::Int1" x="80"/>
     <param name="RedetectFaceTargetSize" type="Value::Int1" x="45"/>
     <param name="paddings" type="Value::Float4" x="-0.18685804" y="0.09821641" z="0.199056897" w="0.07416578" />
     <param name="paddingsIR" type="Value::Float4" x="-0.12208561" y="0.12426723" z="0.15508278" w="0.06038743" />
     <param name="planPrefix" type="Value::String" text="FaceDet_v3_7" />
     <param name="cropPaddingAlignment" type="Value::Int1" x="64" />
     <param name="batchCapacity" type="Value::Int1" x="16" />
     <param name="concurrentBatchSubmission" type="Value::Int1" x="1" />
     <param name="detectMean" type="Value::Float3" x="0.0" y="0.0" z="0.0" />
     <param name="detectSigma" type="Value::Float3" x="0.0" y="0.0" z="0.0" />
     <param name="redetectMean" type="Value::Float3" x="0.0" y="0.0" z="0.0" />
     <param name="redetectSigma" type="Value::Float3" x="0.0" y="0.0" z="0.0" />
</section>

FaceDetV1 detector settings

Parameter	Description	Type	Default value
FirstThreshold	1-st threshold in [0..1] range.	"Value::Float1"	0.6
SecondThreshold	2-nd threshold in [0..1] range.	"Value::Float1"	0.7
ThirdThreshold	3-d threshold in [0..1] range.	"Value::Float1"	0.6
minFaceSize	Minimum face size in pixels.	"Value::Int1"	50
scaleFactor	Image scale factor.	"Value::Float1"	0.7
paddings	Extension of rectangle. Do not change.	"Value::Float4"	see below
redetectTolerance	Redetection threshold	"Value::Int1"	0
useLNet	Whether to use LNet or not.	"Value::Int"	1

MinSize and scaleFactor accelerate face detection at the cost of lower recall for smaller faces

Example:

<section name="FaceDetV1::Settings">
    <param name="FirstThreshold" type="Value::Float1" x="0.6"/>
    <param name="SecondThreshold" type="Value::Float1" x="0.7"/>
    <param name="ThirdThreshold" type="Value::Float1" x="0.93"/>
    <param name="minFaceSize" type="Value::Int1" x="50" />
    <param name="scaleFactor" type="Value::Float1" x="0.7" />
    <param name="paddings" type="Value::Float4" x="-0.20099958" y="0.10210337" z="0.20363552" w="0.08490226"/>
    <param name="redetectTolerance" type="Value::Int1" x="0" />
    <param name="useLNet" type="Value::Int1" x="1" />
</section>

FaceDetV2 detector settings

Parameter	Description	Type	Default value
FirstThreshold	1-st threshold in [0..1] range.	"Value::Float1"	0.6
SecondThreshold	2-nd threshold in [0..1] range.	"Value::Float1"	0.7
ThirdThreshold	3-d threshold in [0..1] range.	"Value::Float1"	0.6
minFaceSize	Minimum face size in pixels.	"Value::Int1"	50
scaleFactor	Image scale factor.	"Value::Float1"	0.7
paddings	Extension of rectangle. Do not change.	"Value::Float4"	see below
redetectTolerance	Redetection threshold	"Value::Int1"	0
useLNet	Whether to use LNet or not.	"Value::Int"	1

MinSize and scaleFactor accelerate face detection at the cost of lower recall for smaller faces

Example:

<section name="FaceDetV2::Settings">
        <param name="FirstThreshold" type="Value::Float1" x="0.51385"/>
        <param name="SecondThreshold" type="Value::Float1" x="0.248"/>
        <param name="ThirdThreshold" type="Value::Float1" x="0.76"/>
        <param name="minFaceSize" type="Value::Int1" x="50" />
        <param name="scaleFactor" type="Value::Float1" x="0.7" />
        <param name="paddings" type="Value::Float4" x="-0.20099958" y="0.10210337" z="0.20363552" w="0.08490226" />
        <param name="redetectTolerance" type="Value::Int1" x="0" />
        <param name="useLNet" type="Value::Int1" x="0" />
</section>

LNet

This group of parameters is non-public. Do not change any of the parameters.

LNetIR

This group of parameters is non-public. Do not change any of the parameters.

SLNet

This group of parameters is non-public. Do not change any of the parameters.

HumanDetector settings

Human body detector.

Parameter	Type	Default value
ScoreThreshold	"Value::Float1"	x="0.45"
RedetectScoreThreshold	"Value::Float1"	x="0.12"
NMSThreshold	"Value::Float1"	x="0.4"
RedetectNMSThreshold	"Value::Float1"	x="0.3"
imageSize	"Value::Int1"	x="640"
nms	"Value::String"	text="mean"
RedetectNMS	"Value::String"	text="mean"
humanLandmarks17Threshold	"Value::Float1"	x="0.2"

Example:

 <section name="HumanDetector::Settings">
    <param name="ScoreThreshold" type="Value::Float1" x="0.45"/>
    <param name="RedetectScoreThreshold" type="Value::Float1" x="0.12"/>
    <param name="NMSThreshold" type="Value::Float1" x="0.4"/>
    <param name="RedetectNMSThreshold" type="Value::Float1" x="0.4"/>
    <param name="imageSize" type="Value::Int1" x="640"/>
    <param name="nms" type="Value::String" text="mean"/> <!-- best, mean -->
    <param name="RedetectNMS" type="Value::String" text="mean"/> <!-- best, mean -->
    <param name="humanLandmarks17Threshold" type="Value::Float1" x="0.2"/>
</section>

IndexBuilder settings

HNSW index can be built with descriptors batches and used to search nearest descriptor neighbors very fast.

Parameter	Description	Type	Default value
numThreads	Number of threads to use on build. If 0 or less, use std::hardware_concurrency value.	"Value::Int1"	0
construction	Internal construction value. The greater it is, the better is graph, but slower construction. DO NOT CHANGE, unless you know what you are doing.	"Value::Int1"	1600
search	Internal search value. Greater value means slower but more complete search. DO NOT CHANGE, unless you know what you are doing.	"Value::Int1"	1000

Example:

<section name="IndexBuilder::Settings">
    <param name="numThreads" type="Value::Int1" x="0" />
    <param name="construction" type="Value::Int1" x="2000" />
    <param name="search" type="Value::Int1" x="6000" />
</section>

Quality estimator settings

Quality estimator looks at several image parameters, like lightness (think overexposure), darkness (think underexposure), blurriness, illumination uniformity value, specularity value. Every float value is comparing with according threshold.

Parameter	Type	Default value
blurThreshold	"Value::Float1"	x="0.61"
lightThreshold	"Value::Float1"	x="0.57"
darknessThreshold	"Value::Float1"	x="0.50"
illuminationThreshold	"Value::Float1"	x="0.1"
specularityThreshold	"Value::Float1"	x="0.1"

Example:

<section name="QualityEstimator::Settings">
    <param name="blurThreshold" type="Value::Float1" x="0.61"/>
    <param name="lightThreshold" type="Value::Float1" x="0.57"/>
    <param name="darknessThreshold" type="Value::Float1" x="0.50"/>
    <param name="illuminationThreshold" type="Value::Float1" x="0.1"/>
    <param name="specularityThreshold" type="Value::Float1" x="0.1"/>
</section>

HeadPoseEstimator settings

HeadPose estimator is able to compute head pose angles in two different ways.

The first one estimates angles by 68-point face-alignment results.

The second one uses raw input image data.

Configuration block listed below allows user to define which method to use. Default configuration settings enables both estimation methods.

Parameter	Type	Default value
useEstimationByImage	"Value::Int1"	1
useEstimationByLandmarks	"Value::Int1"	1

Example:

<section name="HeadPoseEstimator::Settings">
    <param name="useEstimationByImage" type="Value::Int1" x="1"/>
    <param name="useEstimationByLandmarks" type="Value::Int1" x="0"/>
</section>

EyeEstimator settings

This estimator aims to determine:

• Eye state: Open, Closed, Occluded;
• Precise eye iris location as an array of landmarks;
• Precise eyelid location as an array of landmarks.

To determine more exact eye state additional auxiliary model eye_status_estimation_flwr*.plan is used. You can enable this auxiliary model through config (faceengine.conf).

Parameter	Description	Type	Default value
useStatusPlan	0 - Off, 1 - On	"Value::Int1"	1

Example:

<section name="EyeEstimator::Settings">
    <param name="useStatusPlan" type="Value::Int1" x="1"/>
</section>

AttributeEstimator settings

This estimator is able to estimate many person attributes such as:

• person's age;
• gender: male, female;

Some of estimator result values depends on threshold values listed below.

Parameter	Description	Type	Default value
genderThreshold	gender threshold in [0..1] range.	"Value::Float1"	0.5
adultThreshold	adult threshold in [0..1] range.	"Value::Float1"	0.2

Example:

<section name="AttributeEstimator::Settings">
    <param name="genderThreshold" type="Value::Float1" x="0.5"/>
    <param name="adultThreshold" type="Value::Float1" x="0.2"/>
</section>

GlassesEstimator settings

Glasses estimator estimates what types of glasses, if any, person is currently wearing. Quality of estimation depends on threshold values listed below. These threshold values set to optimal by default.

Parameter	Description	Type	Default value
noGlassesThreshold	noGlasses threshold in [0..1] range.	"Value::Float1"	0.986
eyeGlassesThreshold	eyeGlasses threshold in [0..1] range.	"Value::Float1"	0.57
sunGlassesThreshold	sunGlasses threshold in [0..1] range.	"Value::Float1"	0.506

Example:

<section name="GlassesEstimator::Settings">
    <param name="noGlassesThreshold" type="Value::Float1" x="0.986"/>
    <param name="eyeGlassesThreshold" type="Value::Float1" x="0.57"/>
    <param name="sunGlassesThreshold" type="Value::Float1" x="0.506"/>
</section>

OverlapEstimator settings

This estimator tells whether the face is overlapped by any object.

It returns a structure with 2 fields. The first is the value of overlapping in the range from 0.0 (is not overlapped) to 1.0 (maximum, overlapped), the second is a boolean answer.

The boolean answer depends on the threshold listed below. If the value is greater than the threshold, the answer returns true, else false.

Parameter	Description	Type	Default value
overlapThreshold	overlap threshold in [0..1] range.	"Value::Float1"	0.01

Example:

<section name="OverlapEstimator::Settings">
    <param name="overlapThreshold" type="Value::Float1" x="0.01"/>
</section>

ChildEstimator settings

This estimator tells whether the person is child or not.

Child is a person who is yonger than 18 years old.

The estimator returns a structure with 2 fields. The first is the score in the range from 0.0 (is an adult) to 1.0 (maximum, is a child), the second is a boolean answer.

The boolean answer depends on the threshold listed below. If the value is less than the threshold, then true is returned (the person is a child), else false (the person is an adult).

Parameter	Description	Type	Default value
childThreshold	threshold in [0..1] range.	"Value::Float1"	0.8508

Example:

<section name="ChildEstimator::Settings">
    <param name="ChildThreshold" type="Value::Float1" x="0.8508"/>
</section>

LivenessIREstimator settings

This estimator determines whether the person's face is real or fake (photo, printed image).

Image must be received from infra-red camera.

The estimator returns a boolean answer (true - is real, false - is fake).

Estimator can be used in "universal" and "ambarella" modes. The mode is chosen depending on the camera type. Thresholds are listed below.

Parameter	Description	Type	Default value
name	universal	"Value::String"	universal
irUniversalThreshold	threshold in [0..1] range.	"Value::Float1"	0.5328
irAmbarellaThreshold	threshold in [0..1] range.	"Value::Float1"	0.76

<section name="LivenessIREstimator::Settings">
    <param name="name" type="Value::String" x="universal"/>
    <param name="irUniversalThreshold" type="Value::Float1" x="0.5328"/>
    <param name="irAmbarellaThreshold" type="Value::Float1" x="0.76"/>
</section>

HeadAndShouldersLivenessEstimator settings

This estimator tells whether the person's face is real or fake (photo, printed image). Thresholds are listed below.

Parameter	Description	Type	Default value
headWidthKoeff	threshold in [0.5..2.0] range	"Value::Float1"	1.0
headHeightKoeff	threshold in [0.5..2.0] range.	"Value::Float1"	1.0
shouldersWidthKoeff	threshold in [0.5..2.0] range.	"Value::Float1"	0.75
shouldersHeightKoeff	threshold in [1.5..5.0] range.	"Value::Float1"	3.0

<section name="HeadAndShouldersLivenessEstimator::Settings">
    <param name="headWidthKoeff" type="Value::Float1" x="1.0"/>
    <param name="headHeightKoeff" type="Value::Float1" x="1.0"/>
    <param name="shouldersWidthKoeff" type="Value::Float1" x="0.75"/>
    <param name="shouldersHeightKoeff" type="Value::Float1" x="3.0"/>
</section>

Mouth Estimator settings

Mouth estimator predicts predominant mouth state.

Estimator accuracy depends on thresholds listed below.

FPR and TPR values are specified for 0.5 threshold

"Thresholds for MouthEstimation"

Parameter	Description	Type	Default value	Threshold range	TPR	FPR
occlusionThreshold	threshold in [0..1] range	"Value::Float1"	0.5	0.4 - 0.6	0.96	0.009
smileThreshold	threshold in [0..1] range.	"Value::Float1"	0.5	0.4 - 0.6	0.97	0.04
openThreshold	threshold in [0..1] range.	"Value::Float1"	0.5	0.4 - 0.6	0.986	0.01

Example:

<section name="MouthEstimator::Settings">
    <param name="occlusionThreshold" type="Value::Float1" x="0.5"/>
    <param name="smileThreshold" type="Value::Float1" x="0.5"/>
    <param name="openThreshold" type="Value::Float1" x="0.5"/>
</section>

Medical mask estimator settings

Medical mask estimator predicts predominant mask features.

Estimator accuracy depends on thresholds listed below.

If accuracy (low FPR) is more important, TPR could be sacrificed by heightening the threshold.

Corresponding FPR and TPR values are also listed in the table below.

"Thresholds for MedicalMaskEstimation"

Parameter	Description	Type	Threshold range	FPR range	TPR range
mask	range [0..1]	"Value::Float1"	0.65 - 0.9	0.014 - 0.01	0.976 - 0.886
noMask	range [0..1]	"Value::Float1"	0.65 - 0.79	0.01 - 0.005	0.94 - 0.903
occludedFace	range [0..1]	"Value::Float1"	0.5 - 0.602	0.016 - 0.01	0.924 - 0.881

"Thresholds for MedicalMaskEstimationExtended"

Parameter	Description	Type	Threshold range	FPR range	TPR range
maskExtended	range [0..1]	"Value::Float1"	0.65 - 0.784	0.013 - 0.01	0.923 - 0.894
noMaskExtended	range [0..1]	"Value::Float1"	0.65 - 0.79	0.01 - 0.005	0.94 - 0.903
maskNotInPlaceExtended	range [0..1]	"Value::Float1"	0.65 - 0.85	0.009 - 0.005	0.918 - 0.833
occludedFaceExtended	range [0..1]	"Value::Float1"	0.5 - 0.602	0.016 - 0.01	0.924 - 0.881

Example:

<section name="MedicalMaskEstimatorV3::Settings">
        <param name="maskExtendedThreshold" type="Value::Float1" x="0.65"/>
        <param name="noMaskExtendedThreshold" type="Value::Float1" x="0.65"/>
        <param name="maskNotInPlaceExtendedThreshold" type="Value::Float1" x="0.65"/>
        <param name="occludedFaceExtendedThreshold" type="Value::Float1" x="0.5"/>
        <param name="maskThreshold" type="Value::Float1" x="0.65"/>
        <param name="noMaskThreshold" type="Value::Float1" x="0.65"/>
        <param name="occludedFaceThreshold" type="Value::Float1" x="0.65"/>
</section>

RedEyeEstimator settings

Red eye estimator evaluates whether person's eyes are red in a photo or not. Red eye estimation depends on threshold value listed below. These threshold value set to optimal by default.

Parameter	Description	Type	Default value
redEyeThreshold	redEyeThreshold threshold in [0..1] range.	"Value::Float1"	0.5

Example:

<section name="RedEyeEstimator::Settings">
        <param name="redEyeThreshold" type="Value::Float1" x="0.5"/>
</section>

Depth Estimator settings

Depth estimator performs liveness check via depth image. It exposes different threshold parameters where each one of them let you configure estimator for your specific use case.

Parameter	Description	Type	Default value
maxDepthThreshold	maximum depth distance threshold in mm. Should be in [0..inf] range.	"Value::Float1"	3000
minDepthThreshold	minimum depth distance threshold in mm. Should be in [0..maxDepthThreshold] range.	"Value::Float1"	100
zeroDepthThreshold	percentage of zero pixels in input image. Threshold in [0..1] range.	"Value::Float1"	0.66
confidenceThreshold	score threshold above which person is considered to be alive. Threshold in [0..1] range.	"Value::Float1"	0.89

<section name="DepthEstimator::Settings">
    <param name="maxDepthThreshold" type="Value::Float1" x="3000"/>
    <param name="minDepthThreshold" type="Value::Float1" x="100"/>
    <param name="zeroDepthThreshold" type="Value::Float1" x="0.66"/>
    <param name="confidenceThreshold" type="Value::Float1" x="0.89"/>
</section>

LivenessFlyingFaces Estimator settings

This estimator tells whether the person's face is real or fake (photo, printed image).

It returns a structure with 2 fields.

The first one is the value in the range from 0.0 (is not real) to 1.0 (maximum, real), the second is a boolean answer.

The boolean answer depends on the "realThreshold". If the value is greater than the threshold, the answer returns true, else false.

Parameter	Description	Type	Default value
realThreshold	threshold in [0..1] range.	"Value::Float1"	0.98
aggregationCoeff	coefficient in [0..1] range.	"Value::Float1"	0.5

Example:

<section name="LivenessFlyingFacesEstimator::Settings">
    <param name="realThreshold" type="Value::Float1" x="0.98"/>
    <param name="aggregationCoeff" type="Value::Float1" x="0.5"/>
</section>

LivenessRGBM Estimator settings

This estimator tells whether the person's face is real or fake (photo, printed image).

It returns a structure with 2 fields.

The first one is the value in the range from 0.0 (is not real) to 1.0 (maximum, real). The second is a boolean answer.

The boolean answer depends on the "threshold". If the value is greater than the threshold, the answer returns true, else false.

This estimator work is based on background accumulation. So the "backgroundCount" parameter is the amount of the frames for the background calculation.

Other parameters are implementation specific, they are not recommended to change.

Parameter	Description	Type	Default value
backgroundCount	frames count	"Value::Int1"	100
threshold	threshold	"Value::Float1"	0.8
coeff1	Non-public parameter. Do not change.	"Value::Float1"	"0.222"
coeff2	Non-public parameter. Do not change.	"Value::Float1"	"0.222"

Example:

<section name="LivenessRGBMEstimator::Settings">
    <param name="backgroundCount" type="Value::Int1" x="100"/>
    <param name="threshold" type="Value::Float1" x="0.8"/>
    <param name="coeff1" type="Value::Float1" x="0.222"/>
    <param name="coeff2" type="Value::Float1" x="0.222"/>
</section>

LivenessOneShotRGBEstimator settings

This estimator tells whether the person's face is real or fake (photo, printed image). Thresholds are listed below.

Liveness protects from presentation attacks - when user tries to cheat biometric system by demonstrating fake face to the face capturing camera, but not from image substitution attacks - when fake image is sent directly to the system, bypassing the camera.

LivenessOneShotRGBEstimator supports images, which are captured on Mobile devices or Webcam (PC or laptop). Correct working of the estimator with other source images is not guaranteed.

Supported shooting mode: cooperative, which means that user must interact with the camera and look at it.

User scenarios examples: authentication in mobile application, confirmation of transactions with biometric facial verification.

Image resolution minimum requirements:

• Mobile devices - 720 × 960 px
• Webcam (PC or laptop) - 1280 x 720 px

Parameter	Description	Type	Default value
useMobileNet	use mobile version	"Value::Int1"	0
realThreshold	threshold in [0..1] range.	"Value::Float1"	0.5
qualityThreshold	threshold in [0..1] range.	"Value::Float1"	0.5
calibrationCoeff	coefficient in [0..1] range.	"Value::Float1"	0.94
mobileRealThreshold	threshold in [0..1] range.	"Value::Float1"	0.5
mobileQualityThreshold	threshold in [0..1] range.	"Value::Float1"	0.5
mobileCalibrationCoeff	coefficient in [0..1] range.	"Value::Float1"	0.99

<section name="LivenessOneShotRGBEstimator::Settings">
    <param name="useMobileNet" type="Value::Int1" x="0" />
    <!--Parameters for backend version (useMobileNet == 0) -->
    <param name="realThreshold" type="Value::Float1" x="0.5"/>
    <param name="qualityThreshold" type="Value::Float1" x="0.5" />
    <param name="calibrationCoeff" type="Value::Float1" x="0.94"/>
    <!--Parameters for mobile version (useMobileNet == 1) -->
    <param name="mobileRealThreshold" type="Value::Float1" x="0.5"/>
    <param name="mobileQualityThreshold" type="Value::Float1" x="0.5" />
    <param name="mobileCalibrationCoeff" type="Value::Float1" x="0.99"/>
</section>

Credibility Estimator settings

Credibility estimator is trained to predict reliability of a person. It does so by returning a score value between [0;1] which will be closer to 1 if a person is more likely to be reliable and closer to 0 otherwise. Along with the output score value estimator also returns an enum value, which will give a plain answer if a person is reliable or not for a user convenience. Credibility estimator sets this enum value by comparing an output score with a reliability threshold value listed in faceengine.conf file. User can modify this threshold in CredibilityEstimator::Settings section:

Parameter	Description	Type	Default value
reliableThreshold	threshold	"Value::Float1"	0.5

Example:

<section name="CredibilityEstimator::Settings">
    <param name="reliableThreshold" type="Value::Float1" x="0.5"/>
</section>

Natural Light Estimator settings

Natural Light estimator is trained to predict natural of light on the face image.

It does so by returning a score value between [0;1] which will be closer to 1 if a light is more likely to be natural and closer to 0 otherwise.

Along with the output score value estimator also returns an enum value, which will give a plain answer if a person is reliable or not for a user convenience.

NaturalLight estimator sets this enum value by comparing an output score with a reliability threshold value listed in faceengine.conf file. User can modify this threshold in NaturalLightEstimator::Settings section:

Parameter	Description	Type	Default value
naturalLightThreshold	threshold	"Value::Float1"	0.5

Example:

<section name="NaturalLightEstimator::Settings">
        <param name="naturalLightThreshold" type="Value::Float1" x="0.5"/>
</section>

Fish Eye Estimator settings

Fish Eye estimator is trained to predict fish eye effect on the face image.

It does so by returning a score value between [0;1] which will be closer to 1 if a fisheye effect is more likely to be applied to the image and closer to 0 otherwise.

Along with the output score value estimator also returns an enum value, which will give a plain answer if a person is reliable or not for a user convenience.

Fish Eye estimator sets this enum value by comparing an output score with a reliability threshold value listed in faceengine.conf file. User can modify this threshold in FishEyeEstimator::Settings section:

Parameter	Description	Type	Default value
fishEyeThreshold	threshold	"Value::Float1"	0.5

Example:

<section name="FishEyeEstimator::Settings">
    <param name="fishEyeThreshold" type="Value::Float1" x="0.5"/>
</section>

BlackWhite Estimator settings

Estimator checks if image is color, grayscale or infrared.

Estimator accuracy depends on thresholds listed below.

Parameter	Description	Type	Default value
colorThreshold	threshold in [0..1] range	"Value::Float1"	0.5
irThreshold	threshold in [0..1] range.	"Value::Float1"	0.5

Estimator outputs ImageColorEstimation which consists of 2 scores and color image type as enum with possible values: Color, Grayscale, Infrared.

• For color image score colorScore will be close to 1.0 and the second one infraredScore - to 0.0;
• for infrared image score colorScore will be close to 0.0 and the second oneinfraredScore - to 1.0;
• for grayscale images both of scores will be near 0.0.

So colorThreshold is responsible for separating Color and Grayscale images; irThreshold is responsible for separating Infrared and Grayscale images.

<section name="BlackWhiteEstimator::Settings">
        <param name="colorThreshold" type="Value::Float1" x="0.5"/>
        <param name="irThreshold" type="Value::Float1" x="0.5"/>
</section>

Portrait Style Estimator settings

This estimator is designed to evaluate the status of a person's shoulders in the original image.

Estimator accuracy depends on the threshold listed below.

Parameter	Description	Type	Default value
notPortraitStyleThreshold	threshold in [0..1] range	"Value::Float1"	0.25
portraitStyleThreshold	threshold in [0..1] range	"Value::Float1"	0.5
hiddenShouldersThreshold	threshold in [0..1] range	"Value::Float1"	0.25

<section name="PortraitStyleEstimator::Settings">
        <param name="notPortraitStyleThreshold" type="Value::Float1" x="0.25"/>
        <param name="portraitStyleThreshold" type="Value::Float1" x="0.5"/>
        <param name="hiddenShouldersThreshold" type="Value::Float1" x="0.25"/>
</section>

Background Estimator settings

This estimator is designed to evaluate the background in the original image.

Estimator accuracy depends on the thresholds listed below. The scores are defined in [0,1] range. If two scores are above the threshold, then the background is solid, otherwise the background is not solid.

Parameter	Description	Type	Default value
backgroundThreshold	threshold in [0..1] range	"Value::Float1"	0.5
backgroundColorThreshold	threshold in [0..1] range	"Value::Float1"	0.3

<section name="BackgroundEstimator::Settings">
        <param name="backgroundThreshold" type="Value::Float1" x="0.5"/>
        <param name="backgroundColorThreshold" type="Value::Float1" x="0.3"/>
</section>

Human Attribute Estimator settings

Human Attribute estimator is trained to predict a bunch of human attributes on the human image.

Human Attribute estimator sets outwear color bool values and age by comparing an output score with a corresponding threshold value listed in faceengine.conf file. User can modify this threshold in HumanAttributeEstimator::Settings section:

Parameter	Description	Type	Default value
blackThreshold	threshold	"Value::Float1"	0.885
blueThreshold	threshold	"Value::Float1"	0.180
greenThreshold	threshold	"Value::Float1"	0.120
greyThreshold	threshold	"Value::Float1"	0.380
orangeThreshold	threshold	"Value::Float1"	0.040
purpleThreshold	threshold	"Value::Float1"	0.080
redThreshold	threshold	"Value::Float1"	0.160
whiteThreshold	threshold	"Value::Float1"	0.285
yellowThreshold	threshold	"Value::Float1"	0.100
adultThreshold	threshold	"Value::Float1"	0.967

Example:

<section name="HumanAttributeEstimator::Settings">
    <param name="blackThreshold" type="Value::Float1" x="0.885"/>
    <param name="blueThreshold" type="Value::Float1" x="0.180"/>
    <param name="greenThreshold" type="Value::Float1" x="0.120"/>
    <param name="greyThreshold" type="Value::Float1" x="0.380"/>
    <param name="orangeThreshold" type="Value::Float1" x="0.040"/>
    <param name="purpleThreshold" type="Value::Float1" x="0.080"/>
    <param name="redThreshold" type="Value::Float1" x="0.160"/>
    <param name="whiteThreshold" type="Value::Float1" x="0.285"/>
    <param name="yellowThreshold" type="Value::Float1" x="0.100"/>
    <param name="adultThreshold" type="Value::Float1" x="0.967"/>
</section>