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

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[object_detection_prediction, keypoint_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"
    }
}