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

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[object_detection_prediction, instance_segmentation_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
}