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

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
}