Detections List Roll-Up¶
Class: DetectionsListRollUpBlockV1
Source: inference.core.workflows.core_steps.fusion.detections_list_rollup.v1.DetectionsListRollUpBlockV1
Rolls up dimensionality from children to parent detections
Useful in scenarios like: * rolling up results from a secondary model run on crops back to parent images * rolling up OCR results for dynamically cropped images
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/detections_list_rollup@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
confidence_strategy |
str |
Strategy to use when merging confidence scores from child detections. Options are 'max', 'mean', or 'min'.. | ✅ |
overlap_threshold |
float |
Minimum overlap ratio (IoU) to consider when merging overlapping detections from child crops. A value of 0.0 merges any overlapping detections, while higher values require greater overlap to merge. Specify between 0.0 and 1.0. A value of 1.0 only merges completely overlapping detections.. | ✅ |
keypoint_merge_threshold |
float |
Keypoint distance (in pixels) to merge keypoint detections if the child detections contain keypoint data.. | ✅ |
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 List Roll-Up in version v1.
- inputs:
Detections Stitch,Detections Combine,Seg Preview,Byte Tracker,YOLO-World Model,Google Gemini,Velocity,Dynamic Crop,Detection Offset,Identify Changes,Camera Focus,Instance Segmentation Model,Anthropic Claude,Dimension Collapse,OpenAI,SAM 3,Byte Tracker,Time in Zone,Path Deviation,VLM as Detector,Florence-2 Model,Detections Stabilizer,Google Vision OCR,Motion Detection,Google Gemini,Clip Comparison,Cosine Similarity,Detections Classes Replacement,Camera Focus,Anthropic Claude,Detections Filter,Object Detection Model,Instance Segmentation Model,Perspective Correction,EasyOCR,OpenAI,Line Counter,Buffer,Detections Transformation,VLM as Detector,SAM 3,OCR Model,Time in Zone,Byte Tracker,Keypoint Detection Model,Path Deviation,Dynamic Zone,Detections List Roll-Up,PTZ Tracking (ONVIF).md),Keypoint Detection Model,Detections Consensus,Moondream2,Size Measurement,Google Gemini,Template Matching,OpenAI,Llama 3.2 Vision,Bounding Rectangle,Clip Comparison,Gaze Detection,Identify Outliers,Time in Zone,Florence-2 Model,Detections Merge,Object Detection Model,SAM 3,Segment Anything 2 Model,Overlap Filter - outputs:
Detections Combine,Detections Stitch,Seg Preview,Byte Tracker,YOLO-World Model,Google Gemini,Velocity,Dynamic Crop,Blur Visualization,Detection Offset,Bounding Box Visualization,Keypoint Visualization,Trace Visualization,Instance Segmentation Model,Polygon Visualization,Cache Set,Ellipse Visualization,Model Comparison Visualization,OpenAI,Anthropic Claude,Triangle Visualization,SAM 3,Polygon Zone Visualization,Halo Visualization,Distance Measurement,Byte Tracker,Time in Zone,Path Deviation,VLM as Detector,Florence-2 Model,Detections Stabilizer,Circle Visualization,Email Notification,Motion Detection,Google Gemini,Clip Comparison,Camera Focus,Detections Classes Replacement,Anthropic Claude,Detections Filter,Object Detection Model,Instance Segmentation Model,Perspective Correction,VLM as Classifier,Reference Path Visualization,Corner Visualization,Color Visualization,Twilio SMS/MMS Notification,OpenAI,Stitch OCR Detections,Line Counter,Buffer,Detections Transformation,VLM as Detector,SAM 3,Roboflow Custom Metadata,Dot Visualization,Model Monitoring Inference Aggregator,Object Detection Model,Label Visualization,Background Color Visualization,Time in Zone,Classification Label Visualization,Byte Tracker,Roboflow Dataset Upload,Keypoint Detection Model,Path Deviation,Mask Visualization,Dynamic Zone,Detections List Roll-Up,Pixelate Visualization,PTZ Tracking (ONVIF).md),Line Counter,Keypoint Detection Model,Detections Consensus,Size Measurement,Webhook Sink,Grid Visualization,Google Gemini,Stability AI Inpainting,Line Counter Visualization,Crop Visualization,OpenAI,Llama 3.2 Vision,Bounding Rectangle,Icon Visualization,Clip Comparison,VLM as Classifier,Time in Zone,Florence-2 Model,LMM For Classification,Detections Merge,SAM 3,Segment Anything 2 Model,Roboflow Dataset Upload,Overlap Filter,Email Notification
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Detections List Roll-Up in version v1 has.
Bindings
-
input
parent_detection(Union[keypoint_detection_prediction,instance_segmentation_prediction,object_detection_prediction]): The parent detection the dimensionality inherits from..child_detections(list_of_values): A list of child detections resulting from higher dimensionality, such as predictions made on dynamic crops. Use the "Dimension Collapse" to reduce the higher dimensionality result to one that can be used with this. Example: Prediction -> Dimension Collapse -> Detections List Roll-Up.confidence_strategy(list_of_values): Strategy to use when merging confidence scores from child detections. Options are 'max', 'mean', or 'min'..overlap_threshold(float_zero_to_one): Minimum overlap ratio (IoU) to consider when merging overlapping detections from child crops. A value of 0.0 merges any overlapping detections, while higher values require greater overlap to merge. Specify between 0.0 and 1.0. A value of 1.0 only merges completely overlapping detections..keypoint_merge_threshold(float): Keypoint distance (in pixels) to merge keypoint detections if the child detections contain keypoint data..
-
output
rolled_up_detections(Union[instance_segmentation_prediction,object_detection_prediction,keypoint_detection_prediction]): Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object ifinstance_segmentation_predictionor Prediction with detected bounding boxes in form of sv.Detections(...) object ifobject_detection_predictionor Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object ifkeypoint_detection_prediction.crop_zones(list_of_values): List of values of any type.
Example JSON definition of step Detections List Roll-Up in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/detections_list_rollup@v1",
"parent_detection": "<block_does_not_provide_example>",
"child_detections": "<block_does_not_provide_example>",
"confidence_strategy": "min",
"overlap_threshold": 0.0,
"keypoint_merge_threshold": 0.0
}