Detections Filter

Class: DetectionsFilterBlockV1

Source: inference.core.workflows.core_steps.transformations.detections_filter.v1.DetectionsFilterBlockV1

Conditionally filter out model predictions.

Type identifier

Use the following identifier in step "type" field: roboflow_core/detections_filter@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]]	Definition of filtering logic..	❌

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 Filter in version v1.

• inputs: Multi-Label Classification Model, Dimension Collapse, Classification Label Visualization, Background Color Visualization, Dynamic Crop, Clip Comparison, Segment Anything 2 Model, Absolute Static Crop, LMM For Classification, Image Blur, Roboflow Dataset Upload, CogVLM, Circle Visualization, OCR Model, Clip Comparison, Template Matching, SIFT Comparison, Multi-Label Classification Model, Path Deviation, OpenAI, Stitch OCR Detections, Detections Stitch, QR Code Detection, Pixel Color Count, Detections Stabilizer, Path Deviation, Line Counter, VLM as Classifier, Time in Zone, Model Comparison Visualization, Stitch Images, Keypoint Detection Model, Bounding Box Visualization, Moondream2, Continue If, Color Visualization, Slack Notification, LMM, Llama 3.2 Vision, Instance Segmentation Model, VLM as Detector, Time in Zone, Byte Tracker, Detections Filter, YOLO-World Model, Barcode Detection, Grid Visualization, SmolVLM2, Stability AI Inpainting, Keypoint Detection Model, Cosine Similarity, Dot Visualization, Google Gemini, Detections Merge, CLIP Embedding Model, Dynamic Zone, Size Measurement, Property Definition, Roboflow Custom Metadata, Data Aggregator, VLM as Classifier, Detections Classes Replacement, Gaze Detection, Object Detection Model, Corner Visualization, Roboflow Dataset Upload, Image Preprocessing, Image Slicer, Byte Tracker, Line Counter, Label Visualization, Bounding Rectangle, Identify Outliers, Single-Label Classification Model, First Non Empty Or Default, Webhook Sink, Cache Get, Mask Visualization, Delta Filter, Google Vision OCR, Twilio SMS Notification, Buffer, Detection Offset, Model Monitoring Inference Aggregator, Florence-2 Model, Stability AI Image Generation, Cache Set, Identify Changes, Crop Visualization, VLM as Detector, JSON Parser, Velocity, OpenAI, Dominant Color, Perspective Correction, SIFT Comparison, Relative Static Crop, Ellipse Visualization, Reference Path Visualization, Anthropic Claude, Blur Visualization, Pixelate Visualization, Email Notification, Expression, CSV Formatter, Keypoint Visualization, Camera Focus, Single-Label Classification Model, Qwen2.5-VL, Florence-2 Model, Detections Transformation, Image Convert Grayscale, Image Threshold, Trace Visualization, Detections Consensus, Polygon Visualization, Triangle Visualization, Environment Secrets Store, Halo Visualization, Polygon Zone Visualization, Local File Sink, Rate Limiter, Instance Segmentation Model, Camera Calibration, SIFT, Image Contours, Line Counter Visualization, Image Slicer, Byte Tracker, Distance Measurement, Object Detection Model
• outputs: Bounding Rectangle, Blur Visualization, Pixelate Visualization, Background Color Visualization, Dynamic Crop, Keypoint Visualization, Mask Visualization, Time in Zone, Byte Tracker, Segment Anything 2 Model, Detection Offset, Model Monitoring Inference Aggregator, Florence-2 Model, Florence-2 Model, Detections Filter, Detections Transformation, Roboflow Dataset Upload, Circle Visualization, Crop Visualization, Trace Visualization, Path Deviation, Triangle Visualization, Detections Consensus, Stitch OCR Detections, Polygon Visualization, Stability AI Inpainting, Halo Visualization, Dot Visualization, Velocity, Detections Merge, Detections Stitch, Dynamic Zone, Size Measurement, Roboflow Custom Metadata, Detections Classes Replacement, Detections Stabilizer, Label Visualization, Path Deviation, Line Counter, Corner Visualization, Time in Zone, Model Comparison Visualization, Bounding Box Visualization, Roboflow Dataset Upload, Perspective Correction, Byte Tracker, Byte Tracker, Line Counter, Distance Measurement, Color Visualization, Ellipse Visualization

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Detections Filter in version v1 has.

Bindings

• input

  • predictions (Union[keypoint_detection_prediction, object_detection_prediction, instance_segmentation_prediction]): Model predictions to filter..
  • operations_parameters (*): References to additional parameters that may be provided in runtime to parametrise 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 Filter in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/detections_filter@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"
    }
}