Detections Transformation¶
Class: DetectionsTransformationBlockV1
Block changes detected Bounding Boxes in a way specified in configuration.
It supports such operations as changing the size of Bounding Boxes.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/detections_transformation@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
operations |
List[Union[ClassificationPropertyExtract, ConvertDictionaryToJSON, ConvertImageToBase64, ConvertImageToJPEG, DetectionsFilter, DetectionsOffset, DetectionsPropertyExtract, DetectionsRename, DetectionsSelection, DetectionsShift, DetectionsToDictionary, Divide, ExtractDetectionProperty, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, ToBoolean, ToNumber, ToString]] |
Transformations to be applied on the predictions.. | ❌ |
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 Transformation in version v1.
- inputs:
Corner Visualization,Slack Notification,VLM as Detector,VLM as Classifier,Polygon Zone Visualization,Image Slicer,Cache Set,Path Deviation,Dot Visualization,Roboflow Dataset Upload,Single-Label Classification Model,Image Convert Grayscale,Dominant Color,Stability AI Image Generation,Halo Visualization,Data Aggregator,Detections Classes Replacement,Dynamic Zone,CogVLM,Camera Calibration,Email Notification,Object Detection Model,Cosine Similarity,Single-Label Classification Model,Llama 3.2 Vision,Byte Tracker,Ellipse Visualization,Pixel Color Count,Size Measurement,Bounding Box Visualization,Line Counter Visualization,Image Preprocessing,Label Visualization,Local File Sink,Image Slicer,Detections Transformation,Anthropic Claude,Crop Visualization,Detections Stitch,OCR Model,Relative Static Crop,Model Comparison Visualization,QR Code Detection,Delta Filter,Path Deviation,Detections Filter,Clip Comparison,Time in Zone,CSV Formatter,Florence-2 Model,Keypoint Detection Model,Buffer,SIFT Comparison,Florence-2 Model,Multi-Label Classification Model,Rate Limiter,Keypoint Visualization,Identify Changes,Multi-Label Classification Model,Roboflow Custom Metadata,Line Counter,Stitch Images,Circle Visualization,Background Color Visualization,Twilio SMS Notification,Property Definition,LMM,Camera Focus,Image Blur,First Non Empty Or Default,Detections Merge,Google Gemini,Detection Offset,Stability AI Inpainting,Pixelate Visualization,Line Counter,OpenAI,Detections Consensus,Gaze Detection,Distance Measurement,Absolute Static Crop,Webhook Sink,Color Visualization,Image Threshold,Polygon Visualization,VLM as Classifier,Continue If,Instance Segmentation Model,Environment Secrets Store,Classification Label Visualization,Google Vision OCR,Roboflow Dataset Upload,Expression,Cache Get,JSON Parser,Object Detection Model,Keypoint Detection Model,Trace Visualization,Clip Comparison,Identify Outliers,YOLO-World Model,Stitch OCR Detections,Byte Tracker,Perspective Correction,OpenAI,Qwen2.5-VL,Mask Visualization,Time in Zone,Dynamic Crop,Template Matching,Byte Tracker,Barcode Detection,Instance Segmentation Model,Image Contours,SIFT,Reference Path Visualization,CLIP Embedding Model,Model Monitoring Inference Aggregator,Bounding Rectangle,Triangle Visualization,Velocity,SIFT Comparison,VLM as Detector,LMM For Classification,Grid Visualization,Segment Anything 2 Model,Detections Stabilizer,Dimension Collapse,Blur Visualization - outputs:
Circle Visualization,Background Color Visualization,Corner Visualization,Bounding Box Visualization,Trace Visualization,Label Visualization,Detections Transformation,Crop Visualization,Detections Stitch,Path Deviation,Detections Merge,Dot Visualization,Detection Offset,Roboflow Dataset Upload,Model Comparison Visualization,Stability AI Inpainting,Pixelate Visualization,Line Counter,Stitch OCR Detections,Perspective Correction,Detections Consensus,Byte Tracker,Path Deviation,Detections Stabilizer,Distance Measurement,Mask Visualization,Time in Zone,Detections Filter,Color Visualization,Time in Zone,Dynamic Crop,Halo Visualization,Polygon Visualization,Byte Tracker,Detections Classes Replacement,Florence-2 Model,Dynamic Zone,Florence-2 Model,Triangle Visualization,Model Monitoring Inference Aggregator,Bounding Rectangle,Velocity,Roboflow Dataset Upload,Keypoint Visualization,Roboflow Custom Metadata,Byte Tracker,Line Counter,Segment Anything 2 Model,Ellipse Visualization,Size Measurement,Blur Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Detections Transformation in version v1 has.
Bindings
-
input
predictions(Union[keypoint_detection_prediction,instance_segmentation_prediction,object_detection_prediction]): Model predictions to transform..operations_parameters(*): References to additional parameters that may be provided in runtime to parameterize operations.
-
output
predictions(Union[object_detection_prediction,instance_segmentation_prediction,keypoint_detection_prediction]): Prediction with detected bounding boxes in form of sv.Detections(...) object ifobject_detection_predictionor Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object ifinstance_segmentation_predictionor Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object ifkeypoint_detection_prediction.
Example JSON definition of step Detections Transformation in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/detections_transformation@v1",
"predictions": "$steps.object_detection_model.predictions",
"operations": [
{
"filter_operation": {
"statements": [
{
"comparator": {
"type": "in (Sequence)"
},
"left_operand": {
"operations": [
{
"property_name": "class_name",
"type": "ExtractDetectionProperty"
}
],
"type": "DynamicOperand"
},
"right_operand": {
"operand_name": "classes",
"type": "DynamicOperand"
},
"type": "BinaryStatement"
}
],
"type": "StatementGroup"
},
"type": "DetectionsFilter"
}
],
"operations_parameters": {
"classes": "$inputs.classes"
}
}