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Handling policies section#

The “Handling policies” section is intended for creating, deleting, viewing policies, and editing their parameters.

Handling policies (handlers) can be static or dynamic.

If the handler is static, its parameters are specified when creating the handler.

If the handler is dynamic, then you can change its parameters when generating an event. For this, create a generate events request with a specific content type (see API Reference Manual of the LUNA PLATFORM 5 documentation). In a dynamic handler, administrator can allow users to specify parameters that change with each request. At the same time other technical parameters can be set separately and left hidden from the user. With a static handler, administrator would have to create a new handler for each new task.

The general view of the “Handling policies” section is presented below (Figure 28).

“Handling policies” section
Figure 28. “Handling policies” section

“Handling policies” section contains the following elements:

  • table of policies:
  • “Description”—policy name;
  • “Handling policy ID”—policy identifier;
  • “Handler type”—static or dynamic policy;
  • —button for editing policy parameters (1);
  • —button for deleting the policy (2);
  • “Add static” button—button for creating a static handling policy;
  • “Add dynamic button—button for creating a dynamic handling policy;
  • the number of policies displayed on the page is set by the switch in the lower right corner of the page. There can be 10, 25, 50 or 100 policies in total on one page (3).

Policy creation#

Static policy creation#

To create a static policy, click on the “Add static” button (Figure 28). A form will open to select how to create the static policy (Figure 29):

  • preconfigured typical policy templates (policies 1–6);
  • step by step custom policy (“Other”).
Selecting the template of static policy
Figure 29. Selecting the template of static policy

To quickly create simple static policies, use one of the typical policy templates.

Six standard templates are available:

  • “Policy 1. Registration of a reference descriptor (with saving to a list)”—allows user to detect a face on the frame, check Liveness, and save the face to a specified list;
  • “Policy 2. Biometric identification of faces (without saving to a list)”—allows user to detect all faces in the frame and compare them with all faces in the specified list;
  • “Policy 3. Saving the faces identified in the list to the database”—allows user to detect all faces on the frame, check Liveness, compare detected faces with all faces in the specified list, and if the comparison is successful, save the face to the specified list;
  • “Policy 4. Determination of attributes and properties of a face without identification (gender, age, emotions, etc.)”—allows user to detect all faces in the frame, perform all possible checks, and save the event;
  • “Policy 5. Saving events for unique faces for later counting”—allows user to detect all faces in the frame, check Liveness, compare the detected faces with all faces in the list of unique faces, and if this face is not in the list, save the face to this list of unique faces;
  • “Policy 6. Registration of a reference descriptor with verification of compliance of the photo with the requirements of biometric standards*—allows you to save the reference descriptor in a specific list only for those photos that have been verified in accordance with the biometric standards.

* The following checks are missing in the beta version:

  • it is not allowed to use retouching and image editing;
  • image cropping is allowed;
  • compression code: JPEG (0 x 00), PNG (0 x 03).

When user clicks on a line with a standart template (policies 1–6), a window opens for entering the main parameters of a preconfigured policy (Figure 30).

Form for entering basic parameters and creating a preconfigured static policy (policy 1)
Figure 30. Form for entering basic parameters and creating a preconfigured static policy (policy 1)

Fill in all the required parameters and click on the “Create” button. A window will open with a message about the successful creation of the policy (Figure 31).

Message about the successful creation of the “Registration of a reference BT” static policy (policy 1)
Figure 31. Message about the successful creation of the “Registration of a reference BT” static policy (policy 1)

Click anywhere outside the successful static policy generation message to navigate to the “Select the type of policy you want to create” form (Figure 29).

To create a unique static policy that requires detailed parameter settings, use the step-by-step custom policy.

When user clicks on the line with a step-by-step custom policy (“Other”), a form for step-by-step static policy creation will open (Figure 32).

“Create policy” form
Figure 32. “Create policy” form

Fill in all the required parameters and click on the “Next” button to proceed to the next step. After setting all the parameters, a window with a message about the successful creation of the policy will open.

Dynamic policy creation#

To create a dynamic policy, click on the “Add dynamic” button on the page with the list of policies (Figure 28). In the opened window, enter the name of the new dynamic policy and click “Save” (Figure 33). If you need to go back to the page with the list of handlers during creating a handler, press the Esc key on your keyboard.

Form for creating dynamic policy
Figure 33. Form for creating dynamic policy

Policy editing#

Static policy editing#

The general view of the static policy editing form is shown below (Figure 34).

 Static policy editing form
Figure 34. Static policy editing form

Description of the parameters of the static policy editing form is given in the tables (Table 8-15).

Table 8. Parameters of the policy editing form: general parameters and determined attributes

Parameter

Description

Default value

General

Policy name*

Specifies the name that will be displayed in the list of other policies

-

Determined attributes

Detect face

Face detection in photo images

When enabled, the "Face descriptor" and "Basic attributes (gender, age)" options become avalible

Off

Estimate people count

Counts the number of people in the frame

Off

Face descriptor

Image processing and creation of a data set in a closed, binary format using a special extraction algorithm.

When the attribute is enabled, the options “Labels”, “Save descriptor in database”, “Save face to database”, “Attach face to list”, “Save event in cases where a face was found”, and “Display event in cases where a face was found” become available

On

Basic attributes (gender, age)

Assessment of the basic attributes of a person in the image. On

When the attribute is enabled, the “Save if” and "Call only in cases" options become available

Head position

Assessment of the head position (angles of inclination and rotation of the head left/right and up/down).

When the attribute is enabled, the options “Discard face images with head rotation/tilt angle above” become available

On

Emotion

Determination of the dominant emotion (anger, disgust, fear, happiness, neutral, sadness, surprise)

Off

Mask

Assessment of the presence or absence of a medical mask or mouth covering.

When the attribute is enabled, the filter “Process images only if detected” becomes available

Off

Image quality

Determination of quality (the presence of overexposure, blurring, underexposure, the presence of glare on the face, uneven lighting)

On

Eye direction

Assessment of the direction of a person's gaze in the image

Off

Eye status

Evaluating whether a person's eyes are open or closed in the image, as well as determining key points of the irises of the eyes

Off

Mouth status

Closed or occluded mouth detection and smile detection

Off

Perform Liveness check

Enabling Liveness check

Off

Position of 68 feature points of the face

Determination of 68 feature points of the face (requires additional time for calculations, it is used to determine emotions, eye direction or Liveness check)

Off

EXIF metadata

Defining image metadata

Off

| Detect body | Face detection in photo images | Off | +------------------------------------------------+-------------------------------------------------------------------------------------+-------------------+ | Body descriptor | Image processing and creation of a data set in a closed, | On | | | binary format using a special extraction algorithm. | | | | | | | | When the attribute is enabled, the “Labels” option becomes available | | +------------------------------------------------+-------------------------------------------------------------------------------------+-------------------+ | Body basic attributes | Gender and age estimation based on body silhouette | | +------------------------------------------------+-------------------------------------------------------------------------------------+-------------------+ | Upper body attributes based on body silhouette | Estimation of headwear, upper body clothing color, and sleeve length | | +------------------------------------------------+-------------------------------------------------------------------------------------+-------------------+ | Lower body attributes based on body silhouette | Estimation of lower body clothing type and shoe color | | +------------------------------------------------+-------------------------------------------------------------------------------------+-------------------+ | Accessories | Estimation of the presence or absence of a backpack | | +------------------------------------------------+-------------------------------------------------------------------------------------+-------------------+

Table 9. Parameters of the policy editing form: Deepfake check **

Parameter

Description

Default value

Perform Deepfake check

Determination of digital manipulations for replace one person's likeness convincingly with that of another

Off

Discard images of faces with a Deepfake score below the specified score below the specified

Ignoring images with a Liveness score below the specified value.

Possible values: from 0 to 1, where 1 is a real person, 0 - fake

0,5

Use specified Deepfake mode

Possible values:

  • Mode 1;

  • Mode 2;

The choice of mode determines what set of neural networks perform photo processing for deepfake checking.

For more information about the neural networks used in deepfake verification modes, contact VisionLabs technical support.

Mode 2

** Deepfake license required. Deepfake check is not performed on normalized (centered and cropped) images after face detection.

Table 10. Parameters of the policy editing form: image quality check

Parameter

Description

Default value

Perform face image quality check

Image format

Must be saved in .jpeg or .png format (correct verification).

Possible values:

  • JPEG;

  • JPEG2000;

  • PNG;

JPEG; PNG JPEG2000;

Image size in Mb

This assessment determines the size of the image in bytes. It also compares the estimated value with the specified threshold

5120: 2097152

Image width in pixels

This assessment determines the width of the image in pixels. It also compares the estimated values with thresholds (according to ISO or custom thresholds)

180:1920

Image height in pixels

This assessment determines the width of the image in pixels. It also compares the estimated values with thresholds (according to ISO or custom thresholds)

180:1080

Image aspect ratio

This assessment determines the proportional ratio of the image width to height. It also compares the estimated value with the specified threshold

0.74:0,8

Degree of illumination uniformity

It is possible to evaluate the uniformity of illumination according to the requirements specified in the ICAO standard. It also compares the estimated value with the specified threshold (correct verification)

0.3:1

Degree of image specularity

Bright light artifacts and flash reflection from glasses are not allowed (indirect verification)

0.3:1

Degree of image blureness

The pixel colors of front-type photo images must be represented in the 24-bit RGB color space, in which each pixel has 8 bits for each color component: red, green, and blue (indirect verification)

0.61:1

Degree of absence of underexposure in the photo

An underexposure assessment is available. It also compares the estimated value with the specified threshold

0.5:1

Degree of absence of overexposure in the photo

Too much exposure assessment is available. It also compares the estimated value with the specified threshold

0.57:1

Face illumination uniformity

It is possible to evaluate the uniformity of illumination according to the requirements specified in the ICAO standard.

The face should be evenly lit so that there are no shadows or glare on the face image.

It also compares the estimated value with the specified threshold (correct verification)

0.5:1

Skin tone dynamic range

This assessment is a determination of the ratio of the brightness of the lightest and darkest areas of the face according to the requirements specified in the ICAO standard.

It also compares the estimated value with the specified threshold (correct verification)

0.5:1

Degree of uniformity of the background

This assessment determines the degree of background uniformity from 0 to 1, where:

  • 0—non-uniform background;

  • 1—uniform background;

0.5:1

Degree of lightness of the background

This rating determines the degree of background brightness from 0 to 1, where:

  • [0...0.1]—black background;

  • [0.1...0.3]—dark background;

  • [0.3...0.97]—light background;

  • [0.97...1]—white background;

0.5:1

Presence of radial distortion (Fisheye effect)

Possible values: No—the Fisheye effect is not presented in the image;

Yes—the Fisheye effect is presented in the image

No

Type of image color based on face

Possible values:

Color;

Grayscale;

Infrared—near-infrared

Color

Shoulders position

This assessment determines the position of the shoulders if they are in the frame:

Parallel

Non-parallel

Hidden

Parallel

Face width in pixels

This assessment determines the width of the face in pixels. It also compares the estimated value with the specified threshold

180:1920

Face height in pixels

This assessment determines the height of the face in pixels. It also compares the estimated value with the specified threshold

180:1080

Face offset from the top edge of the image in pixels

The image must contain a full front view of the person's head, including the left and right ear (if person has any), the top point of the forehead area and the chin (correct verification)

20:50

Face offset from the bottom edge of the image in pixels

The image must contain a full front view of the person's head, including the left and right ear (if person has any), the top point of the forehead area and the chin (correct verification)

20:50

Face offset from the left edge of the image in pixels

The image must contain a full front view of the person's head, including the left and right ear (if person has any), the top point of the forehead area and the chin (correct verification)

20:50

Face offset from the right edge of the image in pixels

The image must contain a full front view of the person's head, including the left and right ear (if person has any), the top point of the forehead area and the chin (correct verification)

20:50

Head yaw angle

Head rotation should be no more than 5° from the frontal position (correct verification)

-5:5

Head pitch angle

The image must contain a full front view of the person's head, including the left and right ear (if person has any), the top point of the forehead area and the chin (correct verification).

The tilt of the head should be no more than 5° from the frontal position (correct verification)

-5:5

Head roll angle

The image must contain a full front view of the person's head, including the left and right ear (if person has any), the top point of the forehead area and the chin (correct verification).

The inclination of the head should be no more than 8° from the frontal position (correct verification)

-8:8

Gaze yaw angle

This assessment determines the direction of gaze (yaw)

-5:5

Gaze pitch angle

This assessment determines the direction of gaze (pitch)

-5:5

Probability of smile presence

The facial expression must be neutral (indirect verification).

0:0.5

Probability of mouth occlusion

It is not allowed to cover the face with hair or foreign objects along the entire width, from the eyebrows to the lower lip (indirect verification)

0:0.5

Probability of open mouth presence

This assessment determines the state of the mouth

The mouth is closed (correct verification)

0:0.5

Smile properties

This assessment determines the state of the mouth

The facial expression must be neutral (indirect verification). Possible values:

None—smile is not found;

Smile with closed mouth;

Smile with teeth

None

Glasses

Sun glasses are not allowed (correct verification).

Possible values:

Sunglasses;

Eyeglasses;

No glasses

No glasses

Left eye state

Both eyes are open normally for the respective subject (considering behavioral factors and/or medical conditions, correct verification). It is not allowed to cover the face with hair or foreign objects along the entire width, from the eyebrows to the lower lip (indirect verification)

Possible values:

Open;

Closed;

Occluded

Open

Right eye state

Both eyes are open normally for the respective subject (considering behavioral factors and/or medical conditions, correct verification). It is not allowed to cover the face with hair or foreign objects along the entire width, from the eyebrows to the lower lip (indirect verification).

Possible values:

Open;

Closed;

Occluded

Open

Red eyes effect presence

Possible values: No—there is no red-eye effect; Yes—there is a red-eye effect

No

Distance between eye centers in pixels

The image must contain a full front view of the person's head, including the left and right ear (if person has any),the top point of the forehead area and the chin (correct verification)

The distance between the centers of the eyes must be at least 120 pixels or at least 45 pixels in accordance with paragraph 12 of the procedure for placing and updating biometric personal data in a unified biometric system (correct verification)

90:100

Horizontal head size relative to image size

This assessment determines the horizontal head size relative to the image size.

It also compares the estimated values with thresholds (according to ISO or custom thresholds)

0.5:75

Vertical head size relative to image size

This assessment determines the vertical head size relative to the image size. It also compares the estimated values with thresholds (according to ISO or custom thresholds)

0.6:0.9

The position of the center point of the face horizontally relative to the image

This assessment determines the horizontal position of the center point relative to the image.

It also compares the estimated values with thresholds (according to ISO or custom thresholds)

0.45:0.55

The position of the center point of the face vertically relative to the image

This assessment determines the vertical position of the center point relative to the image.

It also compares the estimated values with thresholds (according to ISO or custom thresholds)

0.3:0.5

Eyebrows state

The facial expression must be neutral (indirect verification).

Possible values:

Neutral;

Raised;

Squnting;

Frowning

Neutral

Headwear type

Possible values:

None;

Baseball_cap;

Beanie;

Peaked_cap;

Shawl;

Hat with earflaps;

Helmet;

Hood;

Hat;

Other

None

Presence of natural lighting

The face should be evenly lit so that there are no shadows or glare on the face image (correct verification)

Possible values:

No—the lighting is unnatural;

Yes—the lighting is natural

Yes

Table 11. Parameters of the policy editing form: filters

Parameter

Description

Default value

Perform face image quality assessment

Filters

Discard images with multiple faces

Determination of images containing multiple faces.

Possible values:

Select only one face of the best quality—process an image containing several faces, but detect only a face of the best quality;

Do not discard—detect all faces in the image;

Discard—ignore an image containing multiple faces

Do not discard

Reject descriptors with quality below the specified threshold

Ignoring low quality images.

To use the filter, you must enable the determination of the descriptor in the determined attributes

0,5

Process images only if detected

Possible values:

Missing—the event is created when there is no overlap of the face by the medical mask (no mask);

Occluded—the event is created in case of detection of face overlapping;

Medical mask—the event is created when a medical mask is detected on the face.

Several filter values can be specified.

Available only when defining the “Medical mask” attribute

-

Discard face images with head rotation angle (to the left or right, yaw) above

Ignoring images in which the person's head is turned to the left or right at a too large angle —no information will be extracted when detecting a face and evaluating the angle of head rotation.

Available only if the “Head position” attribute is enabled

30

Discard face images with head tilt angle (to the left or right, roll) above

Ignoring images in which a person's head is tilted to the left or right at a too large angle—no information will be extracted during face detection and head tilt evaluating.

Available only if the “Head position” attribute is enabled

40

Discard face images with head tilt angle (up or down, pitch) above

Ignoring images in which the person’s head is tilted up or down at a too large angle —no information will be extracted during face detection and head tilt evaluating.

Available only if the “Head position” attribute is enabled

30

Discard images of faces with a Liveness score below the specified

Ignoring images with a Liveness score below the specified value.

Possible values: from 0 to 1.

Available only if the “Perform Liveness check” attribute is enabled

0,5

Discard images of faces with the Liveness quality lower than the specified

Ignoring images with a Liveness quality lower than the specified.

Possible values: from 0 to 1.

Available only if the “Perform Liveness check” attribute is enabled

0,5

Process images of faces only with Liveness states

Processing images with Liveness status:

Spoof—the absence of a “live” person in the frame;

Real—the presence of a “live” person in the frame;

Unknown.

Available only if the “Perform Liveness check” attribute is enabled

-

Process images of faces only with Deepfake states

Processing images with Deepfake status:

Fake—the absence of a “live” person in the frame;

Real—the presence of a “live” person in the frame.

Available only if the Perform Deepfake check” attribute is enabled

-

Filter images based on face image quality assessment results

Filter images according to the parameters set in the "Perform face image quality assessment" setting that comply with ISO/IEC 19794-5:2011 and ICAO.

Available only when the parameter “Perform face image quality assessment*” is enabled

Off

Table 12. Parameters of the policy editing form: labels

Parameter

Description

Default value

Labels

Label name

Specify the name that will be displayed in the policy settings, including the parameters for

creating and saving an image/descriptor/event/face, adding a tag

-

Identify among

Searching for a detected person for identification among those created in the database:

  • Faces;

  • Events

Faces

Search for a descriptor

Among the events created in the database, search for a descriptor:

  • Faces;

  • Bodies

Only for "Identify among events"

Faces

Perform search by

  • “List”—specifies a list for identifying a person according to a specific control list (only for “Identify among faces”);

-

  • “Source”—specifies event source name (only for “Identify among events”);
  • “Comma-separated Face IDs”—specifies the values of identifiers of faces in LP5 in UUID format for performing an accurate search;
  • “Comma-separated event IDs”—specifies the values of the event identifiers in LUNA PLATFORM 5 in UUID format for performing an accurate search (only for “Identify among events”);
  • “User data”—specifies person’s data (up to 128 characters);
  • “Comma-separated event external IDs”—specifies the values of third-party external identifiers (only for “Identify among events”);
  • “Comma-separated face external IDs”—specifies the values of third-party external identifiers (only for “Identify among faces”);
  • “Comma-separated track IDs”—specifies the values of the track identifiers in LUNA PLATFORM 5 in the UUID format for performing an accurate search (only for “Identify among events”);
  • “Age category”—indicates the lower and/or upper limits of the age of the person (only for “Identify among events”);
  • “Gender”—indicates female or male gender (only for “Identify among events”);
  • “Emotions”—specifies anger, disgust, fear, happiness, neutral, sadness, surprise, it is possible to specify several values (only for “Identify among events”);
  • “Medical mask”—specifies the detection of the presence/absence of a medical mask, mouth overlap: medical mask, no intersection, mouth is covered, it is possible to specify several values (only for “Identify among events”);
  • “Comma-separated tags”—specifies a tag or tags (only for “Identify among events”);
  • “Similarity”—a value from 0 to 1 is specified (only for “Identify among events”);
  • “Handling policy”—specifies policy name, it is possible to specify several values (only for “Identify among events”);
  • "Comma-separated track IDs"—specifies IDs of tracks (only for “Identify among events”);
  • “Date from”—specifies the period of face creation in LUNA PLATFORM 5;
  • “Date to”—specifies the period of face creation in LUNA PLATFORM 5.
  • “Age category by body"—specifies the age range (only for “Identify among events);
  • “Gender by body"—specifies the gender (only for “Identify among events);
  • “Upper body colors"—specifies top clothing color (only for “Identify among events);
  • “Sleeve"—specifies sleeve length (only for “Identify among events);
  • “Headwear"—specifies headdress (only for “Identify among events);
  • “Headwear color"—specifies headdress color (only for “Identify among events);
  • “Backpack"—specifies backpack presence (only for “Identify among events);
  • “Lower body type"— specifies bottom clothing type (only for “Identify among events);
  • “Lower body colors"— specifies bottom clothing color (only for “Identify among events);
  • “Shoes color"— specifies shoe color (only for “Identify among events);

Each filled field imposes a search restriction—the comparison will be successful only if all the search conditions are met

Location (only for “Identify among events”)

“District”;

“Area”;

“City”;

“Street”;

“House number”;

“Longitude (-180…180)”;

“Accuracy (0…90)”;

“Latitude (-90…90)”;

“Accuracy (0…90)”

-

Filter search result by

“Gender”—specifies the gender for which the face comparison is performed;

“Age category”—specifies the lower and/or upper limits of the age of the face is indicated for comparison;

“Liveness”—specifies Liveness state (Spoof, Real or Unknown)

-

Additional search parameters

“The maximum number of similar ones in the search results”;

“Accuracy threshold”—a value from 0 to 1

-

Table 13. Parameters of the policy editing form: save parameters

Parameter

Description

Default value

Save parameters

Save face sample

Saving the event without creating a face in the LUNA PLATFORM 5 database.

If enabled, images are saved unconditionally in the database.

For selective saving, you must specify: “Save if”:

  • “Gender”—the gender of the face in the image matches the specified;

  • “Age category”—the age of the face in the image matches the specified limits;

  • “Liveness”—specifies Liveness state (Spoof, Real or Unknown);

  • “Deepfake”—specifies Deepfake check (Fake or Real);

— “Save face image in cases where a face was found”:

  • “Labels”—the list of labels, specifies the names of labels (the image is saved when the settings of labels are met);

  • “With precision”—the lower and/or upper limit of the satisfaction of the comparison result with the

parameters specified in the comparison (from 0 to 1)

On

Save body sample

Saving the event without creating a face in the LUNA PLATFORM 5 database. If enabled, images are saved unconditionally in the database.

For selective saving, you must specify: “Save if”:

  • “Gender”—the gender of the face in the image matches the specified;

  • “Age category”—the age of the face in the image matches the specified limits;

  • “Liveness”—specifies Liveness state (Spoof, Real or Unknown);

  • “Deepfake”—specifies Deepfake check (Fake or Real);

— “Save body image in cases where a body was found”:

  • “Labels”—the list of labels, specifies the names of labels (the image is saved when the settings of labels are met);

  • “With precision”—the lower and/or upper limit of the satisfaction of the comparison result with the parameters specified in the comparison (from 0 to 1)

On

Save descriptor in database

Saving the created descriptor in the LUNA PLATFORM 5 database. If enabled, the unconditional saving of the descriptor in the database is performed.

For selective saving, specify the parameters (for more information see description of “Save face sample ” parameter).

Off

— “FaceAttributes storage time”—indicates the time in seconds after which the descriptor will be deleted from the database

-

Save original image in database

Saving the original image in the LUNA PLATFORM 5 database.

Off

— “Use external link as original image URL”—if enabled, the link to the external image is stored in the address of the original image, thus avoiding image duplication in the database.

If a biometric sample was sent in the request and it was stored in the Image Store, then the link to it will be indicated in the address of the original image.

For selective saving, specify the parameters (for more information see description of “Save face sample ” parameter)

Off

Save face in database

Saving the face detected in the image in the LUNA PLATFORM 5 database with the creation of a face in the database.

Saving is possible only when the option “Save descriptor in database” is enabled. If enabled, the unconditional saving of the descriptor in the database is performed

For selective saving, specify the parameters (for more information see description of “Save face sample ” parameter)

Off

— "Attach face to list"—adds the saved face to the control list or lists in LUNA PLATFORM 5. Possible only if the option “Save descriptor in the database” is enabled.

For selective saving, specify the parameters (for more information see description of “Save face sample ” parameter)

Off

Save event in database

Saving the detection/identification event in the LUNA PLATFORM 5 database.

If enabled, all events are stored unconditionally in the database.

For selective saving,specify the parameters (for more information see description of “Save face sample ” parameter)

On

Receive and display an event in the “Last events” section

Displaying an event in the “Last events” section.

For selective displaying of events, specify the parameters (for more information see description of “Save image in database” parameter)

On

Table 14. Parameters of the policy editing form: tagging parameters

Parameter

Description

Tagging parameters

Tag name*

Assigning a tag of the given name when conditions are met.

In the absence of parameter specifications, the assignment is unconditional.

Save if

“Gender”—the gender of the face in the image matches the specified;

“Age category”—the age of the face in the image matches the specified limits;

“Liveness”—specifies Liveness state (Spoof, Real or Unknown);

“Deepfake”—specifies Deepfake check (Fake or Real)

Add a tag for each case where a face was found

“Labels”—the list of labels, specifies the names of labels;

“With precision”—the lower and/or upper limit of the satisfaction of the comparison result with the

parameters specified in the comparison (from 0 to 1)

* Required field

Table 15. Parameters of the policy editing form: callbacks

Callbacks allows you to send generated events (notifications) to the third-party system at the specified URL. A mechanism for notifications is based on the principles of HTTP webhooks. They provide asynchronous interaction between systems, allowing external services to react to the emergence of events.

Parameter

Description

Default value

Add callback

Type

Protocol type when creating a notification

HTTP

URL

Address of the external system where the notification will be sent

-

Authorization type

Selecting the type of authorization into an external system and setting up authorization data.

The basic type of authorization requires specifying login and password to enter an external system

Basic

Timeout (seconds)

Maximum time to wait for a request to complete

60

Request body format

Data interchange format: JSON or MessagePack

application/json

HTTP Headers

HTTP Request Headers

-

Call only in cases where

Conditions for sending notification

Activated when determination of basic attributes (gender, age) is enabled, see the Table 9

— Gender:

  • Female;

  • Male;

— Age category:

  • below 18;

  • from 18 to 44;

  • from 45 to 60;

  • above 60;

Activated when Liveness check is enabled, see the Table 9

— Liveness:

  • Spoof;

  • Real;

  • Unknown;

Activated when Deepfake check is enabled, see the Table 10

— Deepfake:

  • Fake;

  • Real.

Call only in cases where a person or body has been found

  • “Labels”—the list of labels, specifies the names of labels (the image is saved when the settings of labels are met);

  • “With precision”—the lower and/or upper limit of the satisfaction of the comparison result with the parameters specified in the comparison (from 0 to 1)

Adding a label#

To create a label, click on in policy editing form (Figure 35).

Labels
Figure 35. Labels

If you need to identify faces among other faces in the label, then select “Faces” for “Identify among” field in the window for the parameter adding (Figure 36). If you need to identify among events, select “Events” for “Identify among” field (Figure 37).

Form for creating a label. Identify among faces
Figure 36. Form for creating a label. Identify among faces
Form for creating a label. Identify among events
Figure 37. Form for creating a label. Identify among events

Fill in all the required parameters and click on the “Add” button at the bottom of the form.

Label editing#

Editing of the label is performed by clicking on the button in the line (Figure 35).

A general view of the form for editing the label is shown below (Figure 38).

“Edit label” form
Figure 38. “Edit label” form

Edit the parameter values and click on the “Change” button.

Label deleting#

Deletion of the label is performed by clicking on the button in the line (Figure 35).

Tag adding#

To create a tag, click on in policy editing form (Figure 39).

Tagging parameters
Figure 39. Tagging parameters

A general view of the form for creating a tag is shown below (Figure 40).

“Add new tag” form
Figure 40. “Add new tag” form

Fill in all the required parameters and click on the “Add” button at the bottom of the form.

Tag editing#

Tag editing is performed by clicking on the button in the line (Figure 39).

A general view of the tag editing form is shown below (Figure 41).

“Edit tag” form
Figure 41. “Edit tag” form

Edit the values of the tag parameters and click on the “Change” button.

Tag deleting#

Deletion of the tag is performed by clicking on the button in the line (Figure 39).

After finishing editing the policy, click on the “Save” button in the upper right corner (Figure 34).

Dynamic policy editing#

To edit a dynamic policy, first click on the button on the page with a list of policies (1 in Figure 28). Then in the editing form change the name of the policy and click “Save” (Figure 42).

Form for dynamic policy editing
Figure 42. Form for dynamic policy editing

Policy deleting#

Deleting a policy is performed by clicking on the button in the line (2 in the Figure 28).

Confirm the action in the pop-up window—click on the “Delete” button or cancel the action by clicking on the “Cancel” button (Figure 43). After successful deletion, a corresponding notification will appear.

Policy deletion confirmation
Figure 43. Policy deletion confirmation