Detections Merge

Class: DetectionsMergeBlockV1

Source: inference.core.workflows.core_steps.transformations.detections_merge.v1.DetectionsMergeBlockV1

The DetectionsMerge block combines multiple detections into a single bounding box that encompasses all input detections. This is useful when you want to: - Merge overlapping or nearby detections of the same object - Create a single region that contains multiple detected objects - Simplify multiple detections into one larger detection

The resulting detection will have: - A bounding box that contains all input detections - The classname of the merged detection is set to "merged_detection" by default, but can be customized via the class_name parameter - The confidence is set to the lowest confidence among all detections

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
class_name	str	The class name to assign to the merged detection..	❌

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 Merge in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Detections Merge in version v1 has.

Bindings

• input

  • predictions (Union[instance_segmentation_prediction, keypoint_detection_prediction, object_detection_prediction]): Object detection predictions to merge into a single bounding box..

• output

  • predictions (object_detection_prediction): Prediction with detected bounding boxes in form of sv.Detections(...) object.

Example JSON definition of step Detections Merge in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/detections_merge@v1",
    "predictions": "$steps.object_detection_model.predictions",
    "class_name": "<block_does_not_provide_example>"
}