Cameras

The Cameras dashboard in the SmartFace Station is your command center for registering cameras and edge streams, access a detailed list of your devices, and effortlessly configure and manage them to meet your surveillance requirements.

Cameras dashboard

Camera Dashboard Sections

The cameras dashboard contains several sections:

  1. Title bar
  2. Selected filter area
  3. Camera and edge stream list
  4. Fulltext search
  5. Available filters

Cameras dashboard - section

Title bar

At the top of the page, you’ll find the Title Bar, which displays the name of the page - Cameras, helping you quickly identify your location within the SmartFace Station interface. Next to the dashboard name, the number of registered cameras and edge streams is displayed.

Title bar of the Cameras page

Selected filter area

Directly below the Title Bar, you’ll encounter the Selected Filter Area, but it is only visible when a filter has been applied. This section allows you to refine the camera and edge stream list by applying specific filters, customizing the displayed content according to your preferences.

Selected filters

Camera and edge stream list

The central part of the dashboard is dedicated to listing all registered cameras and edge streams. This comprehensive list provides a visual overview of your surveillance devices, making it easy to identify and access each one.

Cameras and edge streams list

To facilitate efficient device lookup, the Full-Text Search feature is available. This allows you to quickly search for specific cameras or edge streams by entering keywords or names.

Full-text search

Available filters

In addition to the Selected Filter Area, you’ll also have access to a list of Available Filters. These filters can help you further refine and categorize the devices in the camera and edge stream list based on source type and status.

Available filters

Camera management

In this part of the documentation you will explore how to effectively managing cameras within the SmartFace Station. Camera management encompasses a range of essential activities, including:

Set up new camera

The SmartFace Station allows you to register a RTSP camera in the SmartFace Platform. When registering the camera, you can set its name and configure the video source. To do so, follow these steps:

  1. Click on Cameras in the left menu panel.
  2. Click on ADD CAMERA button on the right side of the dashboard.
  3. Enter the Name and RTSP / Video source.
  4. To register a new camera, click on ADD CAMERA button.

⚠️ Please note that you may register only as many cameras as you have registered camera services on SmartFace Platform server.

Enable/Disable camera

When you enable a camera in the SmartFace Station, SmartFace Platform will start to process the video stream from the camera and the SmartFace Station will start to display notifications and successful passages. For more information about the settings, see camera sonfiguration.

To enable or disable a registered camera in the SmartFace Station:

  1. Click on Cameras in the left menu panel.
  2. Open Camera configuration by clicking on item in camera list.
  3. You may either:
    • Enable the camera, by switching on the toggle button Enabled (appears green).
    • Disable the camera, by switching off the toggle button Enabled (appears red).

Enabled camera

Disabled camera

Configure camera

The SmartFace Station allows you to configure cameras. These settings directly impact the processing of video streams by the SmartFace Platform.

To modify the camera configuration:

  1. Click on Cameras in the left menu panel.
  2. Open Camera configuration by clicking on item in camera list.
  3. Now, you can modify camera name and camera configuration parameters.

Camera configuration detail

Camera configuration sections and parameters

The camera configuration contains several sections:

When creating a camera, only the General, Detection Timing, Face processing and Video preview sections are allowed.

General section

The General section contains basic information about the camera and you can also see a preview there.
This section is always displayed and cannot be turned off or on.

General section

Parameter nameDescription
Camera NameThe name of camera
OS Service NameThe camera service name. It is read only information, assigned by the system.
RTSP/Video SourceA RTSP URL to the camera stream or video file name with full path for file location

This section contains action buttons:

  • FILTER IN HISTORY - opens History events page that displays the results for this specific camera.
  • FEEDBACK DISPLAY - opens/Copy the Feedback display link for selected camera.
  • DELETE CAMERA - allows you to delete the camera.
Detection timing section

The Detection timing section is intended for configuring time intervals for detection and extraction.
This section is always displayed and it is not possible to enable/disable it

Detection timing section

Parameter nameDescriptionDefault value
Detection / Extraction intervalBalance between resource consumption and detection frequency in miliseconds. You can choose between these options:

  • Conservative (1000 ms) - resource saving option.
  • Moderate (500 ms) - balance between resource consumption and detection frequency
  • Fast (250 ms) - low latency but resource intensive
  • Custom - you can set your own detection and extraction interval.

Moderate (500 ms)
Face processing section

The Face processing section contains the necessary parameters for the configuration of both face detection and face extraction. The section would be enabled by default after creating the camera.

Face processing section

Parameter nameDescriptionDefault valueValue interval
Face detector resourceChoose between these resources for detection:

  • None - no face detection enabled.
  • CPU internal - face detection is performed directly in the camera process on CPU.
  • CPU external - face detection is performed remotely in Detector process on CPU.
  • GPU internal - face detection is performed directly in the camera process on GPU.
  • GPU external - face detection is performed remotely in detector process on GPU.
  • Any external - face detection is performed remotely in detector process on any resource (GPU or CPU) according to their current utilization.

CPU internal
Confidence thresholdThe confidence threshold for face detection.
You can choose between these options:

  • Include low quality faces (1200)
  • Only good faces (1500)
  • Only perfect faces (3500)
  • Custom - you can set your own threshold.

Only good faces (1500)
Min face sizeThe minimum face size necessary for detection in pixels.35
Max face sizeThe maximum face size necessary for detection in pixels.600
Max facesThe maximum number of faces detected on one frame.
⚠️Setup this value according to your use-case. Lowering this number, you can significantly increase overall processing speed.
20
Face save strategyThe strategy for saving data from all detections, you can choose from:

  • All- All faces for the detected person are stored.
  • FirstFace - Only the first detected face of a person is stored.
  • BestFace - Only the best face for the detected person is stored. Which face is the best is decided when the person is lost from tracking.
  • FirstFace, BestFace - The first and the best face for the detected person are stored.
  • MatchedOnly - Only faces which are matched against a watchlist member are stored.

⚠️Set this wisely. Strategy to save all detected objects can generate huge amount of data.

BestFace
Face detector algorithmThe algorithm for face detection. You can choose between these options:

  • Balanced - face detection using NN with algorithm that is balanced mix of speed vs. accuracy.
  • Accurate - face detection using NN with algorithm that is more accurate but slower.

Balanced
Template generator resourceChoose between these resources for template extraction:

  • CPU external - to perform the template extraction on CPU resource.
  • GPU external - to perform the template extraction on GPU resource. GPU must be present in the system.
  • ANY external - to perform the template extraction on any resource (GPU or CPU) according to their current utilization. GPU must be present in the system.

CPU external
ℹ️ Starting from version of SmartFace Platform v5_4.23, the system is capable of linking detected faces to the corresponding body. The facial and pedestrian data are stored in the database only if the "All" save strategy is chosen for both face and pedestrian detection.
Spoof detection section

The spoof detection feature is initially deactivated upon the creation of the camera. The configuration for spoof detection enables the setting of various resource types at the same time. By selecting “More resources”, additional detector resources can be chosen to enhance the spoof detection capabilities.

Spoof detection section

Parameter nameDescriptionDefault valueValue interval
Distant detector resource

Choose liveness approach for spoof detector:

  • None - no spoof detection enabled.
  • CPU external - NN based liveness for access control use-case executed on CPU.
  • GPU external - NN based liveness for access control use-case executed on GPU.
  • ANY external - NN based liveness for access control use-case executed on any resource (GPU or CPU) according to their current utilization.

None
(CPU external is automatically set when you enable the spoof detection section)
Distant Liveness Score ThresholdAnything below this value from distant liveness check will be considered as spoof.
Available only for Distant CPU external and Distant GPU external spoof detector resource.
You can choose from:

  • Default (90)
  • Custom - you can set your own value of threshold.

Default (90)0 ↔︎ 100
Nearby detector resourceChoose liveness approach for spoof detector:

  • None - no spoof detection enabled.
  • CPU external- NN based liveness for selfie use-case executed on CPU.
  • GPU external- NN based liveness for selfie use-case executed on GPU.
  • ANY external - NN based liveness for selfie use-case executed on any resource (GPU or CPU) according to their current utilization.

None
Nearby liveness score thresholdAnything below this value from nearby liveness check will be considered as spoof
Available only for Nearby CPU external and Nearby GPU external spoof detector resource
You can choose from:

  • Default (90)
  • Custom - you can set your own value of threshold.

Default (90)0 ↔︎ 100
Body parts detector resourceChoose liveness approach for spoof detector.

You can choose from:

  • None - no spoof detection enabled
  • Body parts - spoof detection based on body pose (hands holding printout of static photo or a tablet)

None
Pedestrian processing section

The Pedestrian processing section contains all the necessary parameters for the configuration of pedestrian detection and extraction of pedestrian attributes.
Pedestrian processing is disabled by default after creating a camera. You can turn it on easily by clicking on the toggle switch, which sets the default values of the parameters listed below in the table. cam-pedestian-proc-on

Pedestrian processing section

Parameter nameDescriptionDefault valueValue interval
Pedestrian detector resourceChoose which detector will be used for pedestrian detection.

  • None - no pedestrian detection enabled
  • CPU external - uses special Innovatrics NN to perform the detection on CPU.
  • GPU external - uses special Innovatrics NN to perform the detection on GPU. GPU must be present in the system.
  • Any external - uses special Innovatrics NN to perform the detection on any resource (GPU or CPU) according to their current utilization. GPU must be present in the system.
  • SFE CPU external - performs the detection on CPU. It is effective if object detection is turned on at the same time.
  • SFE GPU external - performs the detection on GPU. It is effective if object detection is turned on at the same time.
  • SFE Any external - performs the detection on any resource (GPU or CPU) according to their current utilization. GPU must be present in the system. It is effective if object detection is turned on at the same time.
  • BodyParts external - uses body-parts (CPU) detector to determine where is the pedestrian is located on image

None
Confidence thresholdThe confidence threshold for pedestrian detection. You can choose from:

  • Optimal (2 500)
  • Custom - you can set your own value of threshold.

Optimal (2 500)0 ↔︎ 10 000
Min pedestrian sizeThe minimum pedestrian size necessary for detection in pixels.8020 ↔︎ 10 000
Max pedestrian sizeThe maximum pedestrian size necessary for detection in pixels.2 00021 ↔︎ 10 000
Max pedestriansThe maximum number of pedestrians detected on one frame.201 ↔︎ 1 000
Pedestrian save strategyThe strategy for saving data from all detections, you can choose from:

  • All - All information regarding to the detected pedestrian are stored.
  • Best - Only information pertaining to the pedestrian in the tracklet with the highest quality level is stored. Which pedestrian of the detected person is the best is decided when the person is lost from tracking.

⚠️Set this wisely. Strategy to save all detected objects can generate huge amount of data.

Best
Pedestrian attributes extractor resourceTurn on enhanced pedestrian attributes on selected camera. Choose which extractor will be used for pedestrian attributes extraction:

  • None - no pedestrian attributes extraction enabled
  • CPU external - use special Innovatrics NN to perform the detection on CPU.
  • GPU external - use special Innovatrics NN to perform the detection on GPU. GPU must be present in the system.
  • Any external - use special Innovatrics NN to perform the detection on any resource (GPU or CPU) according to their current utilization. GPU must be present in the system

None
ℹ️ Starting from version of SmartFace Platform v5_4.23, the system is capable of linking detected faces to the corresponding body. The facial and pedestrian data are stored in the database only if the "All" save strategy is chosen for both face and pedestrian detection.

Object processing section

The Object processing section contains all the necessary parameters for the configuration of object detection and possibility to choose which object types should be detected.
Object processing is disabled by default after creating a camera. You can turn it on easily by clicking on the toggle switch, which sets the default values of the parameters listed below in the table.

Object processing section

Parameter nameDescriptionDefault valueValue interval
Object detector resourceTurn on object detection on selected camera. Choose which detector will be used for object detection:

  • None - no object detection enabled
  • CPU external - use special Innovatrics NN to perform the detection on CPU
  • GPU external - use special Innovatrics NN to perform the detection on GPU. GPU must be present in the system.
  • Any external - use special Innovatrics NN to perform the detection on any resource (GPU or CPU) according to their current utilization. GPU must be present in the system.

⚠️To enable object detection, you must ensure that at least one object from the Object Type parameter is selected.

None
Confidence thresholdThe confidence threshold for object detection. You can choose from:

  • Optimal (6000)
  • Custom - you can set your own value of threshold.

Optimal (6000)0 ↔︎ 10 000
Min object sizeThe minimum object size necessary for detection in pixels.8020 ↔︎ 10 000
Max object sizeThe maximum object size necessary for detection in pixels.2 00021 ↔︎ 10 000
Max objectsThe maximum number of objects detected on one frame.201 ↔︎ 1 000
Object save strategyThe strategy for saving data from all detections, you can choose from:

  • All - All information regarding to the detected object are stored.
  • Best - Only information pertaining to the object in the tracklet with the highest quality level is stored. Which object of the detected object is the best is decided when the object is lost from tracking.

⚠️Set this wisely. Strategy to save all detected objects can generate huge amount of data.

Best
Object typeYou can choose which objects will be detected on the camera. You can choose from three categories:

  • Vehicles: Car, Bus, Truck, Motorcycle, Bicycle, Boat, Airplane, Train.
  • Animals: Bird, Cat, Dog, Horse, Sheep, Cow, Bear, Elephant, Giraffe, Zebra.
  • Other objects: Suitcase, Backpack, Handbag, Umbrella, Knife.

Video preview section

In the Video preview section, you can set the quality of the preview from the camera on the security dashboard. It also allows you to set preview profiles for detected shapes that will be displayed on the preview from the camera.

Video preview section

Parameter nameDescriptionDefault valueValue interval
Preview enabledEnable preview generation with embedded graphics. The preview is generated as an MPEG1 stream. You can define the stream quality in the Preview quality setting.Enabled
Preview qualityDefine the quality of generated stream.
You can choose from:
  • Low - 426 px, 153000 bit/s
  • Medium - 640 px, 450000 bit/s
  • High - 1280 px, 1400000 bit/s
  • Custom - you can set your own Resolution (px) and Bitrate (bit/s).

Low
Preview profilesDefine predefined profile what attributes will be displayed near to the detected or identified object.

Four predefined profiles are available and there also posiibility to set custom preview profile:

  • Minimal (bounding box)
  • AC/Security (bounding box, watchlist member name)
  • Retail (bounding box, watchlist member name, age, gender)
  • Full (bounding box, watchlist member name, age, gender, order, facesize / pedestrian size, confidence / pedestrian quality, template quality, yaw, pitch, roll)
  • Custom - you can set your own preview profile by selecting the necessary attributes from the list.
Minimal
ℹ️ Starting from version of SmartFace Platform 5_4.23, the system is capable of linking detected faces to the corresponding body. If at least one of these linked objects (face or body) is saved into the database, the related object (face or body) is also stored in the database, regardless of the set save strategy.

Delete camera

The SmartFace Station allows you to delete camera that is processed by the SmartFace Platform. To delete a camera in SmartFace Station, follow these steps:

  1. Click on Cameras in the left menu panel.
  2. Open Camera configuration by clicking on utem in camera list.
  3. Click on DELETE button and click on option OK in confirmation window.

Edge stream management

The SmartFace Station allows you to set up and configure Edge Stream that will be processed by the SmartFace Platform. In the next chapters, you can find information how to:

Set up new edge stream

The SmartFace Station allows you to register an Edge Stream camera in the SmartFace Platform. When registering the camera, you can set its name and configure the video source. To do so, follow these steps:

  1. Click on Configuration in the left menu panel.
  2. Click on ADD EDGE STREAM button on the right side of the dashboard.
  3. Enter the Edge stream name and Client ID.
  4. To create a new edge stream, click on ADD EDGE STREAM button.

⚠️ Please note that you may register only as many edge streams as you have registered edge stream services on SmartFace Platform server.

Enable/Disable edge stream

When you enable an edge stream in the SmartFace Station, SmartFace Platform will start to process the video stream from the edge stream and SmartFace Station will start to display notifications and successful passages. For more information about the edge stream configuration, see edge stream configuration.

To enable or disable a registered edge stream in the SmartFace Station:

  1. Click on Cameras in the left menu panel.
  2. Open Edge stream configuration by clicking on item in camera list.
  3. You may either:
    • Enable the Edge stream, by switching on the toggle button Enabled (appears green).
    • Disable the Edge stream, by switching off the toggle button Enabled (appears red).

Enabled edge stream

Disabled edge stream

Configure Edge stream

The SmartFace Station allows you to configure Edge streams. The Edges tream configuration directly impact the processing of video streams by the SmartFace Platform.

To modify the Edge stream configuration:

  1. Click on Cameras in the left menu panel.
  2. Open Edge stream configuration by clicking on item in camera list.
  3. Now, you can modify Edge stream name and Edge stream configuration parameters.

Edge stream configuration detail

Edge stream configuration sections and parameters

The Edge stream configuration contains several sections:

When creating an edge stream, only the General, Face processing, Messaging, Send crop images sections are enabled.

General section

The General section contains basic information about the edge stream.
This section is always displayed and cannot be turned off or on.

Health status is displayed at the top of the section. You can find more information in the chapter below.

General section

Parameter nameDescriptionDefault value
Edge stream nameThe edge stream name.Provided string
Client IDA direction to the edge stream.Provided string

This section contains action buttons:

  • ENABLED - toggle switch to enable/disable edge stream.
  • FILTER IN HISTORY - opens History events page that displays the results for this specific edge stream.
  • FEEDBACK DISPLAY - opens/Copy the Feedback display link for selected edge stream.
  • DELETE CAMERA - allows you to delete the edge stream.
Face processing section

The Face processing section contains the necessary parameters for the configuration of face detection, extraction and tracking. The section would be enabled by default after creating the edge stream.

Face processing section

Parameter nameDescriptionDefault valueValue interval
Order byIt allows you to specify the criteria for processing detected faces. You can choose to order faces by:

  • Detection confidence - prioritizes the processing of detected faces based on their detection confidence, with faces having the highest confidence being processed first.
  • Face size - prioritizes the processing of detected faces based on their size, with larger faces being processed first.

Detection confidence
Confidence thresholdThe confidence threshold for face detection.
You can choose between these options:

  • Include low quality faces (1200)
  • Only good faces (1500)
  • Only perfect faces (3500)
  • Custom - you can set your own value

Only good faces (1500)0 ↔︎ 10 000
Min face sizeThe minimum face size necessary for detection in pixels.201 ↔︎ custom positive value
Max face sizeThe maximum face size necessary for detection in pixels.2001 ↔︎ custom positive value
Max facesThe maximum number of faces detected on one frame.
⚠️Setup this value according to your use-case. Lowering this number, you can significantly increase overall processing speed.
100 ↔︎ 100
Face save strategyThe strategy for saving data from all detections, you can choose from:

  • All- All faces for the detected person are stored.
  • FirstFace - Only the first detected face of a person is stored.
  • BestFace - Only the best face for the detected person is stored. Which face is the best is decided when the person is lost from tracking.
  • FirstFace, BestFace - The first and the best face for the detected person are stored.
  • MatchedOnly - Only faces which are matched against a watchlist member are stored.

⚠️Set this wisely. Strategy to save all detected objects can generate huge amount of data.

BestFace
Maximum frames lost for trackletDefines the maximum number of frames to keep lost faces in tracking. Choose between options:

  • Optimal (25)
  • Custom - you can set your own value.

Optimal (25)1 ↔︎ 65535
Tracking thresholdMinimal detection confidence threshold for tracked faces. Faces with detection confidence below this threshold are filtered out by tracking and not used for template extraction. Choose between these options:

  • Default (1000)
  • Custom - you can set your own value.

⚠️Tracking threshold should be lower than Face confidence threshold.

Default (1000)0 ↔︎ 10 000
Tracking stabilityStability is used to associate the tracklets with detections. Low stability may cause tracking to jump between detections. High stability may cause more tracklets to be created. Choose between these options:

  • Optimal (85)
  • Custom - you can set your own value.

Optimal (85)0 ↔︎ 100
Template generator resourceChoose between these resources for template extraction:

  • On Edge - to perform the template extraction on the edge device.
  • CPU on server - to perform the template extraction on CPU resource.
  • GPU on server - to perform the template extraction on GPU resource. GPU must be present in the system.
  • ANY on server - to perform the template extraction on any resource (GPU or CPU) according to their current utilization. GPU must be present in the system.

CPU on server
Spoof detection section

The spoof detection feature is initially deactivated upon the creation of the edge stream. The configuration for spoof detection allows setting only one source type at a time.

Spoof detection section

Parameter nameDescriptionDefault valueValue interval
Distant detector resource

Choose liveness approach for spoof detector:

  • None - no spoof detection enabled.
  • On Edge - spoof detection is excuted on the edge device.
  • CPU on server - NN based liveness for access control use-case executed on CPU.
  • GPU on server - NN based liveness for access control use-case executed on GPU.
  • ANY on server - NN based liveness for access control use-case executed on any resource (GPU or CPU) according to their current utilization.

None
(On Edge is automatically set when you enable the spoof detection section)
Distant liveness score thresholdAnything below this value from distant liveness check will be considered as spoof.
Available only for Distant CPU on server and Distant GPU on server spoof detector resource.
You can choose from:

  • Default (90)
  • Custom - you can set your own value of threshold.

Default (90)0 ↔︎ 100
Nearby detector resourceChoose liveness approach for spoof detector:

  • None - no spoof detection enabled.
  • On Edge - spoof detection ise excuted on the edge device.
  • CPU on server- NN based liveness for selfie use-case executed on CPU.
  • GPU on server- NN based liveness for selfie use-case executed on GPU.
  • ANY on server - NN based liveness for selfie use-case executed on any resource (GPU or CPU) according to their current utilization.

None
Nearby liveness score thresholdAnything below this value from nearby liveness check will be considered as spoof
Available only for Nearby CPU on server and Nearby GPU on server spoof detector resource
You can choose from:

  • Default (90)
  • Custom - you can set your own value of threshold.

Default (90)0 ↔︎ 100
Spoof execution on edgeDefines strategy for liveness detection. Choose from the following options:

  • On each identified face - liveness is computed for each identified face.
  • On each extracted face - liveness is computed for each extracted face.

On each identified face
Watchlists for matching and synchronisation

This section allows you to turn on watchlist synchronization on edge streams and choose specific watchlists for which matching will be performed. This section is disabled by default after creating an edge stream.

Watchlists for matching and synchronisation section

Parameter nameDescriptionDefault valueValue range
Selected watchlistsYou can select watchlists which will be synchronised to the edge stream. You can choose from All, None or specific watchlists.None (All - after enabling this section)
Matching thresholdDefines the matching score threshold for identified candidates. Candidates with a matching score below this threshold are not considered positive matches400 ↔︎ 100
Messaging

In the Messaging section, you can enable and configure messaging functionality. This allows you to set up the sending of messages containing face recognition analytics from the edge stream.
This section is enabled by default after creating an edge stream.

Messaging section

Parameter nameDescriptionDefault valueValue interval
StrategyDefines the messaging strategy. Choose from the following options:

  • On new and interval - message is sent when a new face is detected or the interval is expired.
  • On new and interval best - message is sent when a new face is detected or the interval is expired.
    ⚠️Unsupported in current version.

On new and interval
IntervalDefines the time interval in milliseconds for sending messages. The message is sent at least each milliseconds. Choose from the following options:

  • Optimal (250) - message is sent at least each 250 ms.
  • Custom - you can set your own value.

Optimal (250)1 ↔︎ 65535
Allow empty messagesEnables sending empty messages, for debugging purposes. An empty message indicates that no faces have been detected or tracked.
⚠️This section is only visible if you have the Service info display turned on.
Disabled
Logging

The Logging section allows you to configure logging settings for the system. Here, you can specify the level of detail for logging information. Logging is disabled by deafult.

Logging section

⚠️This section is only visible if you have the Service info display turned on.
Parameter nameDescriptionDefault value
Log levelSpecifies the log level. Supported values are:

  • Off - logging is turned off.
  • Error - only error messages are logged.
  • Warning - additionally warning messages are logged.
  • Info - additionally info messages are logged.
  • Debug - additionally debug messages are logged.
  • Trace - additionally trace messages are logged.

Info
Send crop images

The Sending crop Images section allows you to enable the transmission of cropped images of detected faces. These cropped images can be utilized for various purposes such as post-processing or storage on the server or cloud infrastructure. This section is enabled by default.

Send crop images section

Parameter nameDescriptionDefault valueValue range
Image qualityImage quality for image formats that support compression. Low quality corresponds to a high compression ratio, resulting in reduced image quality but smaller file sizes. Maximum quality refers to images with no compression applied, preserving the highest possible image quality but resulting in larger file sizes.

  • Optimal (90%)
  • Custom - you can set your own value.

Optimal (90%)0% ↔︎ 100%
Max sizeDefines the maximum size of the face in the crop area in pixels. Choose from the following options:

  • Optimal (50px)
  • Custom - you can set your own value.

Optimal (50px)0px ↔︎ 500px
FormatSpecifies the format of the cropped images. Choose from the following options:

  • Optimal (JPEG)
  • RAW
  • PNG

Optimal (JPEG)
Send full frame images

This section enables users to choose whether to send full-frame images. You should consider that enabling this feature consumes a significant amount of bandwidth. Therefore, it’s advised to enable this section only for debugging purposes.

Send frame section

Parameter nameDescriptionDefault valueValue interval
Image qualityImage quality for image formats that support compression. Low quality corresponds to a high compression ratio, resulting in reduced image quality but smaller file sizes. Maximum quality refers to images with no compression applied, preserving the highest possible image quality but resulting in larger file sizes.

  • Optimal (90%)
  • Custom - you can set your own value.

Optimal (90%)0% ↔︎ 100%
ResolutionDefines the resolution of the face in the crop area. Choose from the following options:

  • Source - the resolution of the full-frame images is determined by the source, maintaining the original resolution of the captured images.
  • High definition (1080p)
  • Resource saving (720p)
  • Custom - you can set your own value for width and height.

SourceWidth in range 0 ↔︎ 5000

Height in range 0 ↔︎ 5000
FormatSpecifies the format of the full-frame images. Choose from the following options:

  • Optimal (JPEG)
  • RAW
  • PNG

Optimal (JPEG)
License

In the License section, you can upload your license file using the provided upload area. This section also displays information regarding the current state of the license and the Hardware ID (HWID) associated with the edge device.
More information about how to upload license via REST API you can find here.

Upload license

Follow these steps to upload your license for Edge stream:

  1. Obtain your license in CRM.
  2. Open the SmartFace Station.
  3. Click on Cameras in the left menu panel.
  4. Open Edge stream configuration by clicking on item in camera list.
  5. Go to License section and identify the designated upload area provided for uploading license file.

  1. Drag and drop your license file or click on “choose file” button to select the license file from your local system.

  1. After the upload process is complete, click on the Save button.
    After a few seconds, the license status and HWID will be updated. if everything is fine, the license status will be valid and the upload area will be hidden.

License Status

It reflects license validity for Edge stream:

  • Valid - The uploaded license is verified and valid (green badge).
  • Not valid - The uploaded license is found to be invalid (red badge).
  • Not provided - No license has been uploaded (orange badge).

Health status of the Edge stream

The Edge Stream’s health status reflects its current operational state and license validity. It can be found at the top of the configuration detail section, next to the header.

Health status of Edge stream (Online & License not provided)

Operational state

  • Online - The Edge stream is actively connected (green indicator).
  • Offline - The Edge stream is disconnected (red indicator).
  • Disconnected - The Edge stream is disconnected (orange indicator).
  • Unknown - The connection status of the Edge stream is unknown (orange indicator).

License Status

  • License valid - The uploaded license is verified and valid (green badge).
  • License invalid - The uploaded license is found to be invalid (red badge).
  • License not provided - No license has been uploaded (orange badge).

Healthy is displayed (green indicator), when Edge stream is online with valid license. In other cases, the relevant statuses are displayed for both the operational status and the license status.

Healthy status of Edge stream (Online & License valid)

Delete Edge stream

The SmartFace Station allows you to delete edge stream that is processed by SmartFace Platform.

To delete an edge stream in SmartFace Station:

  1. Click on Cameras in the left menu panel.
  2. Open Edge stream configuration by clicking on item in camera list.
  3. Click on DELETE button and click on option OK in confirmation window.

Feedback display

SmartFace Station is designed to provide valuable information to both your security staff and the individuals passing through your access points. This includes notifications about successful passages and unsuccessful access attempts. To enhance the user experience, SmartFace Station allows you to display this information directly to the person accessing the point through a feedback display. This feature can be enabled on a mobile device (tablet) positioned near your access points or on any other device capable of running the Chrome browser.

Example of the feedback display installed next to a speedgate.

Available notifications

The feedback display offers following screens with showing notifications about recognized events:

  • Welcome screen - A person was identified and access was granted.
  • Put on mask screen - A person was identified, but access was not granted due to missing face mask.
  • Access not allowed screen - A person was not identified as a member of any watchlist and passage is not allowed.
  • Access not granted screen: A person was identified as a member of a restricted watchlist or a spoof was detected and passage is not allowed.
  • SmartFace logo screen: The default screen shown after the notification was displayed.
  • Error screen: The error screen is displayed when a problem occurs.

Welcome screen

Put on mask screen

Access not allowed screen

Access not granted screen

SmartFace logo screen

Error screen

Enable feedback display

The feedback display is accessible through the web browser and is available per camera. To access the feedback display open camera details on Configuration screen:

  1. Open SmartFace Station.
  2. Go to Cameras in the left menu.
  3. Click on the desired camera or edge stream.
  4. Click on the button OPEN or COPY LINK to open the feedback display screen in the new tab of your browser or copy the url link for the feedback display screen:

Feedback display prerequisites

The feedback display feature is designed to be used on a mobile device. It is vital to the proper function of the feedback display that the SmartFace Platform and Access Controller is visible from the device where feedback display is running, ie. mentioned modules are accessible from the device. Please take in an account that feedback display URL and a port can be changed when KeyCloak authentication is deployed on your server. For more information about the KeyCloak see Authentication and user management chapter.

We also recommend to use a kiosk mode on your mobile device installed in the field to prevent people in front of your access points to interact with the mobile device.