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:
Anthropic Claude,Detections Consensus,Detections Merge,Instance Segmentation Model,Dynamic Zone,Dynamic Crop,VLM As Detector,VLM As Detector,Google Gemini,SAM 3,Path Deviation,Detection Offset,Line Counter,Byte Tracker,Segment Anything 2 Model,Object Detection Model,Template Matching,Path Deviation,Google Vision OCR,Bounding Rectangle,Detections Stitch,Instance Segmentation Model,Clip Comparison,Detections Filter,Google Gemini,Detections Stabilizer,PTZ Tracking (ONVIF).md),Camera Focus,Detections Combine,Object Detection Model,Anthropic Claude,Llama 3.2 Vision,Keypoint Detection Model,Buffer,Byte Tracker,Identify Changes,Detections Classes Replacement,Dimension Collapse,Camera Focus,Time in Zone,Velocity,Moondream2,Seg Preview,Identify Outliers,Florence-2 Model,Clip Comparison,OpenAI,Byte Tracker,SAM 3,Detections List Roll-Up,OpenAI,Motion Detection,Size Measurement,Cosine Similarity,Time in Zone,Keypoint Detection Model,Gaze Detection,EasyOCR,Perspective Correction,Anthropic Claude,SAM 3,Detection Event Log,Detections Transformation,OCR Model,YOLO-World Model,Overlap Filter,Time in Zone,Google Gemini,OpenAI,Florence-2 Model - outputs:
Mask Visualization,Classification Label Visualization,Detections Consensus,Detections Merge,Instance Segmentation Model,Webhook Sink,Email Notification,VLM As Detector,SAM 3,Detection Offset,Corner Visualization,Segment Anything 2 Model,Halo Visualization,Object Detection Model,Trace Visualization,Clip Comparison,Instance Segmentation Model,Google Gemini,VLM As Classifier,Roboflow Dataset Upload,PTZ Tracking (ONVIF).md),Color Visualization,Dot Visualization,Polygon Visualization,Object Detection Model,Anthropic Claude,Buffer,Byte Tracker,Detections Classes Replacement,Velocity,Halo Visualization,Florence-2 Model,Blur Visualization,Label Visualization,Twilio SMS/MMS Notification,Ellipse Visualization,OpenAI,Model Monitoring Inference Aggregator,Detections List Roll-Up,OpenAI,Model Comparison Visualization,Background Color Visualization,Size Measurement,Keypoint Detection Model,Polygon Visualization,SAM 3,Bounding Box Visualization,Overlap Filter,Icon Visualization,Time in Zone,Google Gemini,Florence-2 Model,Roboflow Dataset Upload,Anthropic Claude,Dynamic Zone,Dynamic Crop,VLM As Detector,Google Gemini,Path Deviation,Byte Tracker,Line Counter,Cache Set,Stability AI Inpainting,Path Deviation,Triangle Visualization,Bounding Rectangle,Detections Stitch,Detections Filter,Grid Visualization,Detections Stabilizer,Camera Focus,Detections Combine,Llama 3.2 Vision,LMM For Classification,Keypoint Detection Model,Line Counter Visualization,Distance Measurement,Time in Zone,Circle Visualization,Seg Preview,Clip Comparison,Email Notification,Byte Tracker,SAM 3,Time in Zone,Line Counter,Roboflow Custom Metadata,Stitch OCR Detections,Perspective Correction,Anthropic Claude,Pixelate Visualization,Reference Path Visualization,Keypoint Visualization,VLM As Classifier,Detection Event Log,Polygon Zone Visualization,YOLO-World Model,Stitch OCR Detections,Crop Visualization,Motion Detection,OpenAI,Detections Transformation
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[instance_segmentation_prediction,object_detection_prediction,keypoint_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
}