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

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"
}