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

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
}