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