Detection Offset

Class: DetectionOffsetBlockV1

Source: inference.core.workflows.core_steps.transformations.detection_offset.v1.DetectionOffsetBlockV1

Apply a fixed offset to the width and height of a detection.

You can use this block to add padding around the result of a detection. This is useful to ensure that you can analyze bounding boxes that may be within the region of an object instead of being around an object.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
offset_width	int	Offset for box width..	✅
offset_height	int	Offset for box height..	✅
units	str	Units for offset dimensions..	❌

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 Detection Offset in version v1.

• inputs: Path Deviation, Dynamic Zone, Detections Transformation, Template Matching, Distance Measurement, Detections Classes Replacement, VLM as Detector, Object Detection Model, Instance Segmentation Model, Line Counter, Byte Tracker, Keypoint Detection Model, Time in Zone, Detections Stitch, Keypoint Detection Model, Object Detection Model, Segment Anything 2 Model, YOLO-World Model, Detections Merge, Gaze Detection, Moondream2, OCR Model, Seg Preview, Byte Tracker, Path Deviation, Time in Zone, Pixel Color Count, Image Contours, Instance Segmentation Model, Detections Filter, Overlap Filter, Detection Offset, Bounding Rectangle, Google Vision OCR, EasyOCR, Line Counter, Detections Stabilizer, Time in Zone, Detections Combine, SAM 3, SIFT Comparison, VLM as Detector, Dynamic Crop, Velocity, Detections Consensus, Byte Tracker, PTZ Tracking (ONVIF).md), Perspective Correction, SIFT Comparison
• outputs: Polygon Visualization, Roboflow Dataset Upload, Background Color Visualization, Size Measurement, Dynamic Zone, Path Deviation, Detections Transformation, Corner Visualization, Model Monitoring Inference Aggregator, Detections Classes Replacement, Distance Measurement, Trace Visualization, Mask Visualization, Line Counter, Bounding Box Visualization, Model Comparison Visualization, Byte Tracker, Pixelate Visualization, Time in Zone, Florence-2 Model, Detections Stitch, Ellipse Visualization, Triangle Visualization, Segment Anything 2 Model, Crop Visualization, Detections Merge, Icon Visualization, Byte Tracker, Color Visualization, Roboflow Dataset Upload, Path Deviation, Label Visualization, Time in Zone, Keypoint Visualization, Roboflow Custom Metadata, Florence-2 Model, Blur Visualization, Dot Visualization, Overlap Filter, Detections Filter, Circle Visualization, Detection Offset, Bounding Rectangle, Line Counter, Detections Stabilizer, Detections Combine, Time in Zone, Dynamic Crop, Velocity, Detections Consensus, Stitch OCR Detections, Byte Tracker, PTZ Tracking (ONVIF).md), Halo Visualization, Stability AI Inpainting, Perspective Correction

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Detection Offset in version v1 has.

Bindings

• input

  • predictions (Union[instance_segmentation_prediction, keypoint_detection_prediction, object_detection_prediction]): Model predictions to offset dimensions for..
  • offset_width (integer): Offset for box width..
  • offset_height (integer): Offset for box height..

• output

  • predictions (Union[object_detection_prediction, instance_segmentation_prediction, keypoint_detection_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 or Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object if keypoint_detection_prediction.

Example JSON definition of step Detection Offset in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/detection_offset@v1",
    "predictions": "$steps.object_detection_model.predictions",
    "offset_width": 10,
    "offset_height": 10,
    "units": "Pixels"
}