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

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"
    }
}