Nabrio Help
Nabrio Help

Getting Started

Nara Overview

Understanding Nara

Using Nara

Components

Common Process InputsCombine ArraysFilter Array OutputGet Array ItemGet Array Object ItemGet Last Run ArrayGet Object ItemJSON String to ObjectBasic MathsGet Last Run Upstream OutputsMoving Number CalculationNumber RoundingNumber to StringBased64 string to ImageString to NumberTemplate StringISO Time DeltaXML String to ObjectAuto Label Object DetectionBrightnessCircle Detection1D/2D Code ReaderColor DetectionColor ThresholdContrastMultiple CropsCropDetected Zones CountersFacial Expression DetectionGender and Age DetectionDetected Objects to OCRDetected Objects TransformPeople DetectionDraw Detected ObjectsFace DetectionFace RecognitionFeature MatchingFire & Smoke DetectionFlipGeneral Object DetectionImage ClassificationImage SimilarityKey Points DetectionNumber Plate ReaderObject DetectionOCRPose EstimationResizeRotateSaturationInstance SegmentationWatershed SegmentPolygon DetectionTracker Line CountTracker Zones CountTracker HeatmapTrackerWhite Balance
Widgets

Miscellaneous

Nomenclature
Troubleshooting
Notice and DisclaimerEULA
NodesProcess

Face Detection

Slot Usage: 2

Overview

Face detection example

Face Detection node locates faces in an input image and returns bounding boxes, optional facial landmarks, and an overlay image.

Use this node to feed detected face regions into downstream nodes such as Face Recognition, blur/mosaic filters, or zone-based logic.

Input

Input Image

image required

The image frame to analyze. Connect this to an image output from an upstream camera or processing node.

Detection model

string required advanced

Face detection backend to use.

Values:

  • ONNX_YUNET (default) — ONNX YuNet; faster, recommended for most use cases.
  • TFDNN — OpenCV / TensorFlow DNN-based detector; use when ONNX_YUNET does not produce satisfactory results on your hardware.

Box Width / Box height

array advanced

Pixel [min, max] filters for face box width and height. Faces outside these ranges are discarded.

Default: [0, 100000] for each

Confidence threshold

number advanced

Minimum confidence score to keep a detected face. Shown for ONNX_YUNET and TFDNN. See Confidence Threshold for tuning guidance.

Range: 0.0 to 1.0
Default: 0.5

Overlap threshold

number advanced

NMS overlap threshold (higher allows more overlap). Shown for ONNX_YUNET and TFDNN. See Overlap threshold for tuning guidance.

Range: 0.0 to 1.0
Default: 0.3

Top K value

integer advanced

Applies only when Detection model is ONNX_YUNET. Sets the maximum number of candidate face boxes to keep before NMS is applied. Lower values reduce computation at the cost of potentially missing distant or small faces.

Range: 0 to 10000
Default: 5000

Overlay results

boolean required advanced

Whether to draw face bounding boxes on the output frame. See Overlay Results.

Default: true

Draw facial landmarks

boolean required advanced

When enabled, draws facial landmark points on the overlay for each detected face.

Default: false

Output

Overlay Image

image

Output frame from the node. If overlays are enabled, face bounding boxes and optional landmarks are drawn on this frame.

Detected Count

integer

Number of faces detected in the current frame.

Detected Faces

array

Array of face detection objects. Each object contains:

  • Bounding Box (bbox): [x, y, width, height] in image pixel coordinates.
  • Landmarks Points — landmark [x, y] points when available.
  • Landmarks Labels — labels for the landmark points.

Draw Detected Objects

Previous Page

Face Recognition

Next Page

On this page

OverviewInputInput ImageDetection modelBox Width / Box heightConfidence thresholdOverlap thresholdTop K valueOverlay resultsDraw facial landmarksOutputOverlay ImageDetected CountDetected Faces