Detections Transformation

Class: DetectionsTransformationBlockV1

Source: inference.core.workflows.core_steps.transformations.detections_transformation.v1.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, ExtractFrameMetadata, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, TimestampToISOFormat, 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: Line Counter, Single-Label Classification Model, Slack Notification, YOLO-World Model, Image Convert Grayscale, Absolute Static Crop, Perspective Correction, OpenAI, Distance Measurement, Image Slicer, OpenAI, Cosine Similarity, Halo Visualization, Corner Visualization, Email Notification, Detections Classes Replacement, Object Detection Model, Template Matching, Roboflow Dataset Upload, Overlap Filter, Dynamic Crop, Cache Set, VLM as Classifier, Depth Estimation, Dynamic Zone, Model Monitoring Inference Aggregator, Cache Get, Llama 3.2 Vision, Anthropic Claude, Crop Visualization, Blur Visualization, Dominant Color, Image Threshold, Stability AI Inpainting, Relative Static Crop, Dot Visualization, Path Deviation, Clip Comparison, Moondream2, Twilio SMS Notification, OCR Model, Data Aggregator, Google Vision OCR, Property Definition, Pixelate Visualization, Stitch OCR Detections, Image Slicer, Time in Zone, JSON Parser, Webhook Sink, Line Counter Visualization, Byte Tracker, Image Blur, Florence-2 Model, Detections Stabilizer, Delta Filter, LMM For Classification, Instance Segmentation Model, Keypoint Detection Model, Detections Stitch, Bounding Rectangle, Stability AI Image Generation, VLM as Classifier, Identify Changes, Detection Offset, Camera Focus, First Non Empty Or Default, Polygon Zone Visualization, Detections Filter, Time in Zone, Local File Sink, Grid Visualization, Instance Segmentation Model, Trace Visualization, Roboflow Custom Metadata, Continue If, Circle Visualization, Environment Secrets Store, Dimension Collapse, Clip Comparison, Triangle Visualization, QR Code Detection, Gaze Detection, Line Counter, Size Measurement, Byte Tracker, LMM, Detections Consensus, Velocity, Buffer, Stitch Images, Segment Anything 2 Model, Object Detection Model, Model Comparison Visualization, Keypoint Detection Model, SIFT Comparison, CLIP Embedding Model, Expression, CogVLM, SmolVLM2, VLM as Detector, Image Preprocessing, Pixel Color Count, Background Color Visualization, Barcode Detection, Keypoint Visualization, Color Visualization, Multi-Label Classification Model, Classification Label Visualization, Camera Calibration, Label Visualization, Reference Path Visualization, Single-Label Classification Model, Google Gemini, Roboflow Dataset Upload, Identify Outliers, Qwen2.5-VL, Multi-Label Classification Model, Detections Transformation, SIFT Comparison, Image Contours, Polygon Visualization, CSV Formatter, SIFT, Florence-2 Model, Detections Merge, Ellipse Visualization, Mask Visualization, Rate Limiter, Bounding Box Visualization, Byte Tracker, VLM as Detector, Path Deviation
• outputs: Detection Offset, Blur Visualization, Line Counter, Stability AI Inpainting, Detections Filter, Time in Zone, Dot Visualization, Keypoint Visualization, Background Color Visualization, Path Deviation, Trace Visualization, Roboflow Custom Metadata, Perspective Correction, Color Visualization, Distance Measurement, Circle Visualization, Pixelate Visualization, Stitch OCR Detections, Triangle Visualization, Halo Visualization, Label Visualization, Time in Zone, Roboflow Dataset Upload, Byte Tracker, Line Counter, Size Measurement, Byte Tracker, Corner Visualization, Detections Transformation, Florence-2 Model, Detections Stabilizer, Detections Classes Replacement, Detections Consensus, Roboflow Dataset Upload, Overlap Filter, Dynamic Crop, Polygon Visualization, Florence-2 Model, Detections Merge, Ellipse Visualization, Mask Visualization, Dynamic Zone, Velocity, Model Monitoring Inference Aggregator, Detections Stitch, Segment Anything 2 Model, Byte Tracker, Bounding Box Visualization, Bounding Rectangle, Model Comparison Visualization, Path Deviation, Crop 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[object_detection_prediction, instance_segmentation_prediction, keypoint_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 if object_detection_prediction or Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object if instance_segmentation_prediction or Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object if keypoint_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"
    }
}