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