Detections Stabilizer

Class: StabilizeTrackedDetectionsBlockV1

Source: inference.core.workflows.core_steps.transformations.stabilize_detections.v1.StabilizeTrackedDetectionsBlockV1

This block stores last known position for each bounding box If box disappears then this block will bring it back so short gaps are filled with last known box position The block requires detections to be tracked (i.e. each object must have unique tracker_id assigned, which persists between frames) WARNING: this block will produce many short-lived bounding boxes for unstable trackers!

Type identifier

Use the following identifier in step "type" field: roboflow_core/stabilize_detections@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
smoothing_window_size	int	Predicted movement of detection will be smoothed based on historical measurements of velocity, this parameter controls number of historical measurements taken under account when calculating smoothed velocity. Detections will be removed from generating smoothed predictions if they had been missing for longer than this number of frames..	✅
bbox_smoothing_coefficient	float	Bounding box smoothing coefficient applied when given tracker_id is present on current frame. This parameter must be initialized with value between 0 and 1.	✅

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Compatible Blocks

Check what blocks you can connect to Detections Stabilizer in version v1.

• inputs: Line Counter, Detections Consensus, Path Deviation, Blur Visualization, SAM 3, Perspective Correction, Polygon Zone Visualization, Bounding Box Visualization, QR Code Generator, Pixelate Visualization, Distance Measurement, Trace Visualization, Velocity, Detections Transformation, Segment Anything 2 Model, Image Threshold, Polygon Visualization, Dynamic Crop, Icon Visualization, Image Slicer, Identify Outliers, Stability AI Outpainting, Model Comparison Visualization, Dynamic Zone, Classification Label Visualization, Stitch Images, Mask Visualization, Relative Static Crop, Absolute Static Crop, SIFT Comparison, SAM 3, Time in Zone, Moondream2, Circle Visualization, Ellipse Visualization, Image Convert Grayscale, Time in Zone, Object Detection Model, OCR Model, Image Preprocessing, Color Visualization, Image Blur, Stability AI Image Generation, Google Vision OCR, Keypoint Visualization, Camera Calibration, VLM as Detector, EasyOCR, Image Slicer, Line Counter, VLM as Detector, Detections Combine, Detections Filter, Byte Tracker, Overlap Filter, Background Color Visualization, Triangle Visualization, Halo Visualization, Object Detection Model, Corner Visualization, Detections Stabilizer, Dot Visualization, Image Contours, Detections Merge, Byte Tracker, Instance Segmentation Model, Seg Preview, Reference Path Visualization, Morphological Transformation, Motion Detection, Byte Tracker, PTZ Tracking (ONVIF).md), Detections Classes Replacement, Instance Segmentation Model, Detections Stitch, Contrast Equalization, Camera Focus, YOLO-World Model, Stability AI Inpainting, Clip Comparison, Line Counter Visualization, Identify Changes, Template Matching, Path Deviation, Crop Visualization, Grid Visualization, Bounding Rectangle, SIFT, Depth Estimation, Background Subtraction, Label Visualization, SAM 3, Pixel Color Count, Time in Zone, Detection Offset, SIFT Comparison
• outputs: Line Counter, Detections Consensus, Path Deviation, Model Monitoring Inference Aggregator, Roboflow Dataset Upload, Blur Visualization, Dot Visualization, Detections Merge, Perspective Correction, Byte Tracker, Bounding Box Visualization, Pixelate Visualization, Distance Measurement, Trace Visualization, Roboflow Custom Metadata, Velocity, Byte Tracker, Detections Transformation, Segment Anything 2 Model, PTZ Tracking (ONVIF).md), Polygon Visualization, Dynamic Crop, Icon Visualization, Detections Classes Replacement, Model Comparison Visualization, Dynamic Zone, Detections Stitch, Size Measurement, Florence-2 Model, Mask Visualization, Stitch OCR Detections, Stability AI Inpainting, Time in Zone, Circle Visualization, Florence-2 Model, Ellipse Visualization, Time in Zone, Path Deviation, Crop Visualization, Color Visualization, Bounding Rectangle, Line Counter, Detections Combine, Label Visualization, Byte Tracker, Roboflow Dataset Upload, Overlap Filter, Triangle Visualization, Background Color Visualization, Detections Filter, Time in Zone, Detection Offset, Halo Visualization, Detections Stabilizer, Corner Visualization

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Detections Stabilizer in version v1 has.

Bindings

• input

  • image (image): not available.
  • detections (Union[instance_segmentation_prediction, object_detection_prediction]): Tracked detections.
  • smoothing_window_size (integer): Predicted movement of detection will be smoothed based on historical measurements of velocity, this parameter controls number of historical measurements taken under account when calculating smoothed velocity. Detections will be removed from generating smoothed predictions if they had been missing for longer than this number of frames..
  • bbox_smoothing_coefficient (float_zero_to_one): Bounding box smoothing coefficient applied when given tracker_id is present on current frame. This parameter must be initialized with value between 0 and 1.

• output

  • tracked_detections (Union[object_detection_prediction, instance_segmentation_prediction]): Prediction with detected bounding boxes in form of sv.Detections(...) object if object_detection_prediction or Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object if instance_segmentation_prediction.

Example JSON definition of step Detections Stabilizer in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/stabilize_detections@v1",
    "image": "<block_does_not_provide_example>",
    "detections": "$steps.object_detection_model.predictions",
    "smoothing_window_size": 5,
    "bbox_smoothing_coefficient": 0.2
}