Settings#
System settings#
| Parameter | Description | Type | Default value |
|---|---|---|---|
| verboseLogging | Level of log verbosity. 1 - Errors, 2 - Warnings, 3 - Info, 4 - Debug. | "Value::Int1" |
2 |
| betaMode | Enable experimental features (0 - Off, 1 - On). | "Value::Int1" |
0 |
| defaultDetectorType | Detector type: FaceDetV2, FaceDetV3. | "Value::String" |
FaceDetV3 |
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="2" />
<param name="betaMode" type="Value::Int1" x="0" />
<param name="detectorType" type="Value::String" text="FaceDetV3" />
</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. Possible values: 58, 59, 60, 62. | Value::Int1 |
62 |
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 |
Enables similarity calculation during matching process. Possible values: 1 - enable, 0 - disable. |
Value::Int1 |
1 |
calcDistanceSqrt |
Enables calculation of the square root of distance. Possible values: 1 - enable, 0 - disable |
Value::Int1 |
1 |
batchCapacity |
Non-public parameter. Do not change. | Value::Int1 |
16 |
Models with versions 58, 59, 60, 62 support only L2 distance.
Example:
<section name="DescriptorFactory::Settings">
<param name="model" type="Value::Int1" x="62" />
<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" />
<!--Calculate similarity by default to preserve backward compatible-->
<param name="calcSimilarity" type="Value::Int1" x="1" />
<!--Calculate sqrt from distance by default to preserve backward compatible-->
<param name="calcDistanceSqrt" type="Value::Int1" x="1" />
<!--Batch capacity used by IDescriptorExtractor implementations-->
<param name="batchCapacity" type="Value::Int1" x="16" />
</section>
FaceDetV3 detector settings#
| Parameter | Description | Type | Default value |
|---|---|---|---|
ScoreThreshold |
Detection score threshold (RGB) in [0..1] range. | Value::Float1 |
0.5 |
ScoreThresholdNPU |
Detection score threshold (RGB) in [0..1] range. | Value::Float1 |
0.89 |
ScoreThresholdIR |
Detection score threshold (InfraRed) in [0..1] range. | Value::Float1 |
0.38 |
RedetectScoreThreshold |
Redetect score threshold in [0..1] range. | Value::Float1 |
0.5 |
NMSThreshold |
Overlap threshold for NMS in [0..1] range. | Value::Float1 |
0.35 |
NMSThresholdNPU |
Overlap threshold for NMS in [0..1] range. | Value::Float1 |
0.35 |
intraNMSThreshold |
Overlap threshold for intra NMS in [0..1] range. | Value::Float1 |
0.35 |
minFaceSize |
Minimum face size in pixels. | Value::Int1 |
50 |
strictlyMinSize |
Enforce Minimum face size. | Value::Int1 |
0 |
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 |
64 |
| Non-public parameter. Do not change. | |||
paddings |
Extension of rectangle for RGB mode. Do not change. | Value::Float4 |
see below |
planPrefix |
Plan prefix. | Value::String |
FaceDet_v3_a5 |
pyramidAlgorithm |
Turn On/Off the pyramid based algorithm. | Value::Int1 |
0 |
useLNet |
Whether to use LNet or not. | Value::Int1 |
1 |
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 |
If the strictlyMinSize parameter is enabled (the value is equal to 1),
all detections with a size (max of width/height ) smaller than minFaceSize will be excluded from the final result.
<section name="FaceDetV3::Settings">
<param name="ScoreThreshold" type="Value::Float1" x="0.5"/> <!-- used for RGB mode -->
<param name="ScoreThresholdNPU" type="Value::Float1" x="0.89"/> <!-- used for RGB mode -->
<param name="ScoreThresholdIR" type="Value::Float1" x="0.38"/> <!-- used for InfraRed mode -->
<param name="RedetectScoreThreshold" type="Value::Float1" x="0.5"/>
<param name="NMSThreshold" type="Value::Float1" x="0.35"/>
<param name="NMSThresholdNPU" type="Value::Float1" x="0.35"/>
<param name="intraNMSThreshold" type="Value::Float1" x="0.35"/>
<param name="minFaceSize" type="Value::Int1" x="50" />
<param name="strictlyMinSize" type="Value::Int1" x="0" />
<param name="pyramidAlgorithm" type="Value::Int1" x="1" />
<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="64"/>
<param name="useLNet" type="Value::Int1" x="1" />
<param name="paddings" type="Value::Float4" x="-0.17847424" y="0.06987534" z="0.18716485" w="0.05400637"/>
<param name="planPrefix" type="Value::String" text="FaceDet_v3_a5" />
<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>
FaceDetV2 detector settings#
| Parameter | Description | Type | Default value |
|---|---|---|---|
| FirstThreshold | 1-st threshold in [0..1] range. | "Value::Float1" |
0.51385 |
| SecondThreshold | 2-nd threshold in [0..1] range. | "Value::Float1" |
0.248 |
| ThirdThreshold | 3-d threshold in [0..1] range. | "Value::Float1" |
0.76 |
| minFaceSize | Minimum face size in pixels. | "Value::Int1" |
50 |
| strictlyMinSize | Enforce Minimum face size. | "Value::Int1" |
0 |
| 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 |
minFaceSize and scaleFactor accelerate face detection at the cost of lower recall for smaller faces.
If the strictlyMinSize parameter is enabled (the value is equal to 1),
all detections with a size (max of width/height ) smaller than minFaceSize will be excluded from the final result.
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="strictlyMinSize" type="Value::Int1" x="0" />
<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.
IndexBuilder settings#
You can build the HNSW (Hierarchical Navigable Small Worlds) index with descriptor batches and use it for a quick search of the nearest descriptor neighbors.
| Parameter | Type | Default value |
|---|---|---|
numThreads |
"Value::Int1" |
0 |
construction |
"Value::Int1" |
2000 |
search |
"Value::Int1" |
6000 |
searchForEvaluation |
"Value::Int1" |
20 |
Parameters description:
numThreads - The number of threads to be used for building or searching. If 0 or less, use the std::hardware_concurrency
construction - Internal construction value. The greater it is, the better the graph is, but the slower the construction is. Important: We do not recommend that you change the value, unless you know what you are doing.
search - Internal search value. A greater value means a slower but more complete search. Important: We do not recommend that you change the value, unless you know what you are doing.
searchForEvaluation - Evaluation index length, a greater value means a slower but more precise evaluation.
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" />
<param name="searchForEvaluation" type="Value::Int1" x="20" />
</section>
HumanDetector settings#
Human body detector.
| Parameter | Description | Type | Default value |
|---|---|---|---|
ScoreThreshold |
Detection score threshold (RGB) in [0..1] range. | Value::Float1 |
0.5 |
RedetectScoreThreshold |
Redetect score threshold in [0..1] range. | Value::Float1 |
0.12 |
NMSThreshold |
Overlap threshold for NMS in [0..1] range. | Value::Float1 |
0.4 |
RedetectNMSThreshold |
Non-public parameter. Do not change. | Value::Float1 |
0.4 |
imageSize |
Input image size in pixels. | Value::Int1 |
640 |
nms |
Type of NMS: mean or best. |
Value::String |
best |
RedetectNMS |
Redetect type of NMS: mean or best. |
Value::String |
mean |
RedetectTensorSize |
Target face after preprocessing for redetect. Non-public parameter. Do not change. |
"Value::Int1" |
110 |
RedetectHumanTargetSize |
Non-public parameter. Do not change. | Value::Int1 |
85 |
cropPaddingAlignment |
Non-public parameter. Do not change. | Value::Int1 |
64 |
batchCapacity |
Non-public parameter. Do not change. | Value::Int1 |
16 |
Example:
<section name="HumanDetector::Settings">
<param name="ScoreThreshold" type="Value::Float1" x="0.5"/>
<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="best"/> <!-- best, mean -->
<param name="RedetectNMS" type="Value::String" text="mean"/> <!-- best, mean -->
<param name="RedetectTensorSize" type="Value::Int1" x="110"/>
<param name="RedetectHumanTargetSize" type="Value::Int1" x="85"/>
<param name="cropPaddingAlignment" type="Value::Int1" x="64" />
<param name="batchCapacity" type="Value::Int1" x="16" />
</section>
Head detector settings#
| Parameter | Description | Type | Default value |
|---|---|---|---|
ScoreThreshold |
Detection score threshold (RGB) in the [0..1] range. | "Value::Float1" | 0.5 |
NMSThreshold |
Overlap threshold for NMS in the [0..1] range. | "Value::Float1" | 0.35 |
minHeadSize |
Minimum face size in pixels. | "Value::Int1" | 60 |
strictlyMinSize |
Affects minHeadSize, see below. |
"Value::Int1" | 0 |
nms |
Type of NMS: mean or best. |
"Value::String" | mean |
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 |
If strictlyMinSize=1, any detections with a size less than minHeadSize are excluded from the detection results. The size of the detection is determined by the maximum value between detection width and detection height.
<section name="HeadDetector::Settings">
<param name="ScoreThreshold" type="Value::Float1" x="0.5"/>
<param name="NMSThreshold" type="Value::Float1" x="0.35"/>
<param name="minHeadSize" type="Value::Int1" x="60" />
<param name="strictlyMinSize" type="Value::Int1" x="0" />
<param name="nms" type="Value::String" text="mean"/> <!-- best, mean -->
<param name="cropPaddingAlignment" type="Value::Int1" x="64" />
<param name="batchCapacity" type="Value::Int1" x="16" />
<param name="concurrentBatchSubmission" type="Value::Int1" x="1" />
</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" |
| usePlanV1 | "Value::Int1" |
x="1" |
| usePlanV2 | "Value::Int1" |
x="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"/>
<param name="usePlanV1" type="Value::Int1" x="1" />
<param name="usePlanV2" type="Value::Int1" x="1" />
</section>
Note: usePlanV1 toggles the Quality estimation, usePlanV2 toggles the SubjectiveQuality estimation. Note that you cannot disable both the parameters at the same time.
In case you do this, you will receive the fsdk::FSDKError::InvalidConfig error code and the following logs:
[27.06.2024 12:38:59] [Error] QualityEstimator::Settings Failed to create QualityEstimator! The both parameters: "usePlanV1" and "usePlanV2" in section "QualityEstimator::Settings" are disabled at the same time.
HeadPoseEstimator settings#
The HeadPose estimator is able to compute head pose angles using raw input image data.
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>
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_*.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>
GlassesEstimator settings#
The glasses estimator estimates what types of glasses, if any, a person is currently wearing. Estimation quality depends on threshold values listed below. These threshold values are set to optimal by default.
| Parameter | Description | Type | Default value |
|---|---|---|---|
| noGlassesThreshold | noGlasses threshold in [0..1] range. | "Value::Float1" |
1 |
| eyeGlassesThreshold | eyeGlasses threshold in [0..1] range. | "Value::Float1" |
1 |
| sunGlassesThreshold | sunGlasses threshold in [0..1] range. | "Value::Float1" |
1 |
Example:
<section name="GlassesEstimator::Settings">
<param name="noGlassesThreshold" type="Value::Float1" x="1"/>
<param name="eyeGlassesThreshold" type="Value::Float1" x="1"/>
<param name="sunGlassesThreshold" type="Value::Float1" x="1"/>
</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>
LivenessFPREstimator settings#
Thresholds are listed below.
| Parameter | Description | Type | Default value |
|---|---|---|---|
| realThreshold | threshold in [0..1] range. | "Value::Float1" |
0.6 |
<section name="LivenessFPREstimator::Settings">
<param name="realThreshold" type="Value::Float1" x="0.6"/>
</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>
NIRLivenessEstimator settings#
This estimator determines whether the person's face is real or fake (photo, printed image).
Thr image must be received from the infra-red camera.
The estimator returns a boolean answer (true - is real, false - is fake).
The estimator can be used in two modes. The first mode is fast, while the other is slower but more accurate. By default, recommended to use the more accurate mode, which is 2.
| Parameter | Description | Type | Default value |
|---|---|---|---|
| realThreshold | threshold in [0..1] range. | "Value::Float1" |
0.5 |
| defaultEstimatorMode | Configuration of plan files usage. |
Value::Int1 |
2 |
<section name="NIRLivenessEstimator::Settings">
<param name="realThreshold" type="Value::Float1" x="0.5"/>
<!-- Currently, available values to select the estimation mode are: 1 and 2. -->
<param name="defaultEstimatorMode" type="Value::Int1" x="2"/>
</section>
NIRLiveness estimation mode.
Currently, the available values to select the estimation mode are: Default, M1 and M2.
The scenario Default means the mode is specified in config file. @see ISettingsProvider.
Implementation description:
NIRLiveness Estimation Mode Enum
enum class NIRLivenessMode {
Default, // Specified in config file.
M1, // M1.
M2 // M2.
};
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 the [0..1] range | Value::Float1 |
0.5 |
0.4 - 0.6 |
0.96 |
0.009 |
smileThreshold |
Threshold in the [0..1] range. | Value::Float1 |
0.5 |
0.4 - 0.6 |
0.97 |
0.04 |
openThreshold |
Threshold in the [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>
Face Occlusion Estimator Settings#
The Face Occlusion estimator predicts occlusion of various face areas such as the forehead, eyes, nose, mouth, and lower face.
Estimator accuracy depends on thresholds listed below.
| Parameter | Description | Type | Default | Threshold range |
|---|---|---|---|---|
normalHairCoeff |
Threshold for hair*. | Value::Float1 |
0.15 |
0.0 - 1.0 |
overallOcclusionThreshold |
Overall threshold. | Value::Float1 |
0.07 |
0.0 - 1.0 |
foreheadThreshold |
Threshold for forehead. | Value::Float1 |
0.1 |
0.0 - 1.0 |
eyeThreshold |
Threshold for eye. | Value::Float1 |
0.15 |
0.0 - 1.0 |
noseThreshold |
Threshold for nose. | Value::Float1 |
0.2 |
0.0 - 1.0 |
mouthThreshold |
Threshold for mouth. | Value::Float1 |
0.15 |
0.0 - 1.0 |
lowerFaceThreshold |
Threshold for lower face. | Value::Float1 |
0.2 |
0.0 - 1.0 |
Note:
The normalHairCoeff parameter determines whether the presence of hair is considered when analyzing face occlusion.
- If the percentage of hair occlusion is lower than
normalHairCoeff, hair is not taken into account in the analysis. - If the hair occlusion percentage exceeds
normalHairCoeff, the excess hair occlusion is added to the overall face occlusion percentage.
Example calculation:
- Overall face occlusion score without hair: 0.05
- Overall face occlusion score with hair: 0.2
normalHairCoeff: 0.15
In this case, the resulting overall face occlusion score would be calculated as follows:
- Resulting score = 0.05 + (0.2 - 0.15) = 0.1.
Example:
<section name="FaceOcclusionEstimator::Settings">
<param name="normalHairCoeff" type="Value::Float1" x="0.15"/>
<param name="overallOcclusionThreshold" type="Value::Float1" x="0.07"/>
<param name="foreheadThreshold" type="Value::Float1" x="0.1"/>
<param name="eyeThreshold" type="Value::Float1" x="0.15"/>
<param name="noseThreshold" type="Value::Float1" x="0.2"/>
<param name="mouthThreshold" type="Value::Float1" x="0.15"/>
<param name="lowerFaceThreshold" type="Value::Float1" x="0.2"/>
</section>
DeepFake Estimator settings#
This estimator is designed to predict is the detected face on the input image synthetic or not.
Estimator accuracy depends on realThreshold and defaultEstimatorType listed below.
"DeepFakeEstimator"
| Parameter | Description | Type | Default value |
|---|---|---|---|
| realThreshold | Threshold in [0..1] range. | "Value::Float1" |
0.5 |
| defaultEstimatorType | Configuration of plan files usage. |
Value::Int1 |
2 |
Example:
<section name="DeepFakeEstimator::Settings">
<param name="realThreshold" type="Value::Float1" x="0.5"/>
<param name="defaultEstimatorType" type="Value::Int1" x="2"/>
</section>
DeepFake estimation mode.
Currently, available values for selecting estimation scenario are: Default, M1 and M2.
The scenario Default means the mode is specified in config file. @see ISettingsProvider.
Implementation description:
DeepFake Estimation Mode Enum
enum class DeepFakeMode {
Default, // Specified in config file.
M1, // M1.
M2 // M2.
};
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 below.
Thresholds for MedicalMaskEstimation#
The below parameters specify parameter thresholds in the [0..1] range and are of the "Value::Float1" type.
maskThreshold
| Threshold range | Default threshold | FPR range | TPR range |
|---|---|---|---|
| 0.65 - 0.9 | 0.65 | 0.014 - 0.01 | 0.976 - 0.886 |
noMaskThreshold
| Threshold range | Default threshold | FPR range | TPR range |
|---|---|---|---|
| 0.65 - 0.79 | 0.65 | 0.01 - 0.005 | 0.94 - 0.903 |
occludedFaceThreshold
| Threshold range | Default threshold | FPR range | TPR range |
|---|---|---|---|
| 0.5 - 0.602 | 0.5 | 0.016 - 0.01 | 0.924 - 0.881 |
Thresholds for MedicalMaskEstimationExtended#
The below parameters specify parameter thresholds in the [0..1] range and are of the "Value::Float1" type.
maskExtendedThreshold
| Threshold range | Default threshold | FPR range | TPR range |
|---|---|---|---|
| 0.65 - 0.784 | 0.65 | 0.013 - 0.01 | 0.923 - 0.894 |
noMaskExtendedThreshold
| Threshold range | Default threshold | FPR range | TPR range |
|---|---|---|---|
| 0.65 - 0.79 | 0.65 | 0.01 - 0.005 | 0.94 - 0.903 |
maskNotInPlaceExtendedThreshold
| Threshold range | Default threshold | FPR range | TPR range |
|---|---|---|---|
| 0.65 - 0.85 | 0.65 | 0.009 - 0.005 | 0.918 - 0.833 |
occludedFaceExtendedThreshold
| Threshold range | Default threshold | FPR range | TPR range |
|---|---|---|---|
| 0.5 - 0.602 | 0.5 | 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 the [0..1] range. | "Value::Float1" |
0.5 |
| aggregationCoeff | Coefficient in the [0..1] range. | "Value::Float1" |
0.7 |
Example:
<section name="LivenessFlyingFacesEstimator::Settings">
<param name="realThreshold" type="Value::Float1" x="0.5"/>
<param name="aggregationCoeff" type="Value::Float1" x="0.7"/>
</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 |
|---|---|---|---|
| netType | NET 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" |
0.89 |
| 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" |
0.968 |
| liteRealThreshold | Threshold in [0..1] range. | "Value::Float1" |
0.5 |
| liteQualityThreshold | Threshold in [0..1] range. | "Value::Float1" |
0.5 |
| liteCalibrationCoeff | Coefficient in [0..1] range. | "Value::Float1" |
0.991 |
<section name="LivenessOneShotRGBEstimator::Settings">
<param name="netType" type="Value::Int1" x="0" />
<!--Parameters for backend version (netType == 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="0.89"/>
<!--Parameters for mobile version (netType == 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="0.968"/>
<!--Parameters for lite version (netType == 2) -->
<param name="liteRealThreshold" type="Value::Float1" x="0.5"/>
<param name="liteQualityThreshold" type="Value::Float1" x="0.5" />
<param name="liteCalibrationCoeff" type="Value::Float1" x="0.991"/>
</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>
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
colorScorewill be close to 1.0 and the second oneinfraredScore- to 0.0; - for infrared image score colorScore will be close to 0.0 and the second one
infraredScore- 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>
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>
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 |
|---|---|---|---|
| blackUpperThreshold | threshold | "Value::Float1" |
0.740 |
| blueUpperThreshold | threshold | "Value::Float1" |
0.655 |
| brownUpperThreshold | threshold | "Value::Float1" |
0.985 |
| greenUpperThreshold | threshold | "Value::Float1" |
0.700 |
| greyUpperThreshold | threshold | "Value::Float1" |
0.710 |
| orangeUpperThreshold | threshold | "Value::Float1" |
0.420 |
| purpleUpperThreshold | threshold | "Value::Float1" |
0.650 |
| redUpperThreshold | threshold | "Value::Float1" |
0.600 |
| whiteUpperThreshold | threshold | "Value::Float1" |
0.820 |
| yellowUpperThreshold | threshold | "Value::Float1" |
0.670 |
| blackLowerThreshold | threshold | "Value::Float1" |
0.700 |
| blueLowerThreshold | threshold | "Value::Float1" |
0.840 |
| brownLowerThreshold | threshold | "Value::Float1" |
0.850 |
| greenLowerThreshold | threshold | "Value::Float1" |
0.700 |
| greyLowerThreshold | threshold | "Value::Float1" |
0.690 |
| orangeLowerThreshold | threshold | "Value::Float1" |
0.760 |
| purpleLowerThreshold | threshold | "Value::Float1" |
0.890 |
| redLowerThreshold | threshold | "Value::Float1" |
0.600 |
| whiteLowerThreshold | threshold | "Value::Float1" |
0.540 |
| yellowLowerThreshold | threshold | "Value::Float1" |
0.930 |
| adultThreshold | threshold | "Value::Float1" |
0.940 |
Example:
<section name="HumanAttributeEstimator::Settings">
<param name="blackUpperThreshold" type="Value::Float1" x="0.740"/>
<param name="blueUpperThreshold" type="Value::Float1" x="0.655"/>
<param name="brownUpperThreshold" type="Value::Float1" x="0.985"/>
<param name="greenUpperThreshold" type="Value::Float1" x="0.700"/>
<param name="greyUpperThreshold" type="Value::Float1" x="0.710"/>
<param name="orangeUpperThreshold" type="Value::Float1" x="0.420"/>
<param name="purpleUpperThreshold" type="Value::Float1" x="0.650"/>
<param name="redUpperThreshold" type="Value::Float1" x="0.600"/>
<param name="whiteUpperThreshold" type="Value::Float1" x="0.820"/>
<param name="yellowUpperThreshold" type="Value::Float1" x="0.670"/>
<param name="blackLowerThreshold" type="Value::Float1" x="0.700"/>
<param name="blueLowerThreshold" type="Value::Float1" x="0.840"/>
<param name="brownLowerThreshold" type="Value::Float1" x="0.850"/>
<param name="greenLowerThreshold" type="Value::Float1" x="0.700"/>
<param name="greyLowerThreshold" type="Value::Float1" x="0.690"/>
<param name="orangeLowerThreshold" type="Value::Float1" x="0.760"/>
<param name="purpleLowerThreshold" type="Value::Float1" x="0.890"/>
<param name="redLowerThreshold" type="Value::Float1" x="0.600"/>
<param name="whiteLowerThreshold" type="Value::Float1" x="0.540"/>
<param name="yellowLowerThreshold" type="Value::Float1" x="0.930"/>
<param name="adultThreshold" type="Value::Float1" x="0.940"/>
</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" |
0.2 |
| portraitStyleThreshold | threshold in [0..1] range | "Value::Float1" |
0.35 |
| hiddenShouldersThreshold | threshold in [0..1] range | "Value::Float1" |
0.2 |
<section name="PortraitStyleEstimator::Settings">
<param name="notPortraitStyleThreshold" type="Value::Float1" x="0.2"/>
<param name="portraitStyleThreshold" type="Value::Float1" x="0.35"/>
<param name="hiddenShouldersThreshold" type="Value::Float1" x="0.2"/>
</section>
HumanFace detector settings#
| Parameter | Description | Type | Default value |
|---|---|---|---|
| humanThreshold | Threshold in the [0..1] range. | "Value::Float1" |
0.5 |
| nmsHumanThreshold | Threshold in the [0..1] range. | "Value::Float1" |
0.4 |
| faceThreshold | Threshold in the [0..1] range. | "Value::Float1" |
0.5 |
| nmsFaceThreshold | Threshold in the [0..1] range. | "Value::Float1" |
0.3 |
| associationThreshold | Threshold in the [0..1] range. | "Value::Float1" |
0.5 |
| minFaceSize | Minimum face size in pixels. | "Value::Int1" |
50 |
| strictlyMinSize | Enforce Minimum face size. | "Value::Int1" |
0 |
| batchCapacity | Non-public parameter. Do not change. | "Value::Int1" |
8 |
| cropPaddingAlignment | Non-public parameter. Do not change. | "Value::Int1" |
64 |
If the strictlyMinSize parameter is enabled (the value is equal to 1),
all detections with a size (max of width/height ) smaller than minFaceSize will be excluded from the final result.
<section name="HumanFaceDetector::Settings">
<param name="humanThreshold" type="Value::Float1" x="0.5"/>
<param name="nmsHumanThreshold" type="Value::Float1" x="0.4"/>
<param name="faceThreshold" type="Value::Float1" x="0.5"/>
<param name="nmsFaceThreshold" type="Value::Float1" x="0.3"/>
<param name="associationThreshold" type="Value::Float1" x="0.5"/>
<param name="minFaceSize" type="Value::Int1" x="50"/>
<param name="strictlyMinSize" type="Value::Int1" x="0" />
<param name="cropPaddingAlignment" type="Value::Int1" x="64" />
<param name="batchCapacity" type="Value::Int1" x="8" />
</section>
Landmarks detector settings#
| Parameter | Description | Type | Default value |
|---|---|---|---|
| useLNet | To detect Landmarks68 | "Value::Int1" |
1 |
| useSLNet | To detect Landmarks5 | "Value::Int1" |
1 |
<section name="LandmarksDetector::Settings">
<param name="useLNet" type="Value::Int1" x="1" />
<param name="useSLNet" type="Value::Int1" x="1" />
</section>
Note
Please pay attention, both parameters cannot be disabled at the same time.
In this case, you will receive the error code (fsdk::FSDKError::InvalidConfig), and logs like below:
[30.08.2022 15:47:15] [Error] [FaceLandmarksDetector] Failed to create FaceLandmarksDetector! The both parameters: "useSLNet" and "useLNet" in section "LandmarksDetector::Settings" are disabled at the same time.
Orientation Estimator settings#
Orientation estimator detects an orientation of the input image.
| Parameter | Description | Type | Default value |
|---|---|---|---|
batchCapacity |
Non-public parameter. Do not change. | Value::Int1 |
16 |
Crowd estimator settings#
| Parameter | Description | Type | Default value |
|---|---|---|---|
| defaultEstimatorType | Type of the estimator | "Value::String" |
TwoNets |
| detectorType | Type of detector | "Value::String" |
HumanDetector |
| minHeadSize | Target minHeadSize | "Value::Int1" |
6 |
| batchCapacity | Non-public parameter. Do not change. | "Value::Int1" |
1 |
| cropPaddingAlignment | Non-public parameter. Do not change. | "Value::Int1" |
0 |
| lowThreshold | Non-public parameter. Do not change. | "Value::Float1" |
0.1 |
| upThreshold | Non-public parameter. Do not change. | "Value::Float1" |
100 |
There are next possible values for the defaultEstimatorType parameter:
-
Single - working mode with one network usage
-
TwoNets - working mode with two networks usage
<section name="CrowdEstimator::Settings">
<!-- Available types are: Single, TwoNets -->
<param name="defaultEstimatorType" type="Value::String" text="TwoNets"/>
<!-- Available types are: HumanDetector, HeadDetector -->
<param name="detectorType" type="Value::String" text="HumanDetector"/>
<param name="minHeadSize" type="Value::Int1" x="6"/>
<param name="batchCapacity" type="Value::Int1" x="1"/>
<param name="cropPaddingAlignment" type="Value::Int1" x="0"/>
<param name="lowThreshold" type="Value::Float1" x="0.1"/>
<param name="upThreshold" type="Value::Float1" x="100"/>
</section>
LivenessDepthRGBEstimator settings#
LivenessDepthRGBEstimator estimator performs liveness check via pair of depth image and RGB 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" |
0.5 |
<section name="LivenessDepthRGBEstimator::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="0.5"/>
</section>
DepthLivenessEstimator settings#
DepthLivenessEstimator performs liveness check for a face depth warp image. It exposes different threshold parameters that let you configure the 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. Should be in [0..1] range. | "Value::Float1" |
0.66 |
| confidenceThreshold | score threshold above which person is considered to be alive. Should be in [0..1] range. | "Value::Float1" |
0.5 |
- Pixels greater than maxDepthThreshold are zeroed out/excluded from estimation.
- Pixels less than minDepthThreshold are zeroed out/excluded from estimation.
- If the percentage of zero pixels in input image is greater than zeroDepthThreshold, the whole image is zeroed out, even if there are some good pixels, and the estimator returns a score close to 0.
<section name="DepthLivenessEstimator::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="0.5"/>
</section>
FightsEstimator settings#
FightsEstimator estimator performs a fight detection on the several frame sequences from the target video. It exposes different parameters where each one of them let you configure estimator for your specific use case.
| Parameter | Description | Type | Default value |
|---|---|---|---|
| batchSize | count of frames in one sequence (batch) | "Value::Int1" |
5 |
| minBatchCount | minimum sequences (batches) count | "Value::Int1" |
5 |
| cropSize | internal crop size. do not change it! | "Value::Int1" |
224 |
| threshold | score threshold above which the video is considered to contain a fight. Threshold in [0..1] range. | "Value::Float1" |
0.5 |
| scoreNorm | normalization parameter. do not change it! | "Value::Float1" |
1.8 |
<section name="FightsEstimator::Settings">
<param name="batchSize" type="Value::Int1" x="5"/>
<param name="minBatchCount" type="Value::Int1" x="5"/>
<param name="cropSize" type="Value::Int1" x="225"/>
<param name="threshold" type="Value::Float1" x="0.5"/>
<param name="scoreNorm" type="Value::Float1" x="1.8"/>
</section>