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:
Environment Secrets Store,Cache Set,Object Detection Model,Object Detection Model,Detection Offset,CogVLM,Ellipse Visualization,Grid Visualization,SIFT,Camera Focus,Property Definition,CLIP Embedding Model,Dot Visualization,Google Vision OCR,Clip Comparison,Identify Changes,Polygon Zone Visualization,Gaze Detection,Classification Label Visualization,Corner Visualization,Dynamic Crop,Detections Stabilizer,Label Visualization,Triangle Visualization,Dynamic Zone,Dominant Color,Time in Zone,Barcode Detection,Blur Visualization,Line Counter,Instance Segmentation Model,Webhook Sink,Cosine Similarity,Path Deviation,Relative Static Crop,Detections Consensus,Twilio SMS Notification,Crop Visualization,Qwen2.5-VL,Distance Measurement,Velocity,Circle Visualization,Keypoint Detection Model,QR Code Detection,Size Measurement,Single-Label Classification Model,Bounding Box Visualization,LMM For Classification,Image Threshold,Detections Stitch,OCR Model,Keypoint Visualization,Single-Label Classification Model,Detections Classes Replacement,Polygon Visualization,Segment Anything 2 Model,Cache Get,Image Slicer,Stability AI Inpainting,Clip Comparison,Perspective Correction,Roboflow Custom Metadata,SIFT Comparison,VLM as Detector,Image Contours,Multi-Label Classification Model,OpenAI,Absolute Static Crop,Trace Visualization,Multi-Label Classification Model,VLM as Detector,Identify Outliers,Roboflow Dataset Upload,First Non Empty Or Default,VLM as Classifier,Byte Tracker,Llama 3.2 Vision,Line Counter,Reference Path Visualization,Mask Visualization,Template Matching,Line Counter Visualization,Detections Transformation,Model Monitoring Inference Aggregator,Anthropic Claude,SIFT Comparison,Time in Zone,Instance Segmentation Model,Slack Notification,Detections Filter,Stitch OCR Detections,Pixelate Visualization,Delta Filter,Dimension Collapse,VLM as Classifier,Keypoint Detection Model,Roboflow Dataset Upload,Google Gemini,Rate Limiter,Model Comparison Visualization,Halo Visualization,JSON Parser,Byte Tracker,Expression,Image Blur,Buffer,Image Preprocessing,Background Color Visualization,Continue If,Bounding Rectangle,Pixel Color Count,Florence-2 Model,Byte Tracker,Florence-2 Model,Local File Sink,Image Slicer,Stitch Images,Stability AI Image Generation,LMM,Email Notification,Color Visualization,Path Deviation,YOLO-World Model,Data Aggregator,CSV Formatter,Image Convert Grayscale,OpenAI - outputs:
Segment Anything 2 Model,Detections Filter,Stitch OCR Detections,Stability AI Inpainting,Pixelate Visualization,Perspective Correction,Path Deviation,Roboflow Custom Metadata,Detections Consensus,Detection Offset,Roboflow Dataset Upload,Ellipse Visualization,Model Comparison Visualization,Halo Visualization,Crop Visualization,Byte Tracker,Trace Visualization,Distance Measurement,Circle Visualization,Velocity,Dot Visualization,Background Color Visualization,Bounding Rectangle,Roboflow Dataset Upload,Size Measurement,Florence-2 Model,Byte Tracker,Corner Visualization,Bounding Box Visualization,Florence-2 Model,Byte Tracker,Dynamic Crop,Line Counter,Detections Stabilizer,Label Visualization,Mask Visualization,Triangle Visualization,Dynamic Zone,Detections Transformation,Detections Stitch,Keypoint Visualization,Model Monitoring Inference Aggregator,Time in Zone,Color Visualization,Path Deviation,Blur Visualization,Line Counter,Time in Zone,Detections Classes Replacement,Polygon 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[instance_segmentation_prediction,keypoint_detection_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"
}
}