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: Llama 3.2 Vision, SAM 3, Polygon Zone Visualization, Distance Measurement, Pixelate Visualization, Roboflow Custom Metadata, Trace Visualization, QR Code Detection, Detections Transformation, Image Threshold, Rate Limiter, Image Slicer, Icon Visualization, Stability AI Outpainting, Dynamic Zone, Clip Comparison, Model Comparison Visualization, Single-Label Classification Model, Cache Get, Stitch Images, Size Measurement, Florence-2 Model, Single-Label Classification Model, Environment Secrets Store, SAM 3, Relative Static Crop, Absolute Static Crop, SIFT Comparison, Moondream2, Florence-2 Model, LMM For Classification, Anthropic Claude, Image Blur, Stability AI Image Generation, VLM as Detector, Camera Calibration, Keypoint Detection Model, Local File Sink, First Non Empty Or Default, Detections Filter, Gaze Detection, Background Color Visualization, Keypoint Detection Model, Delta Filter, Multi-Label Classification Model, Google Gemini, Model Monitoring Inference Aggregator, Roboflow Dataset Upload, Byte Tracker, Instance Segmentation Model, VLM as Classifier, CSV Formatter, Motion Detection, Morphological Transformation, Data Aggregator, OpenAI, Barcode Detection, YOLO-World Model, JSON Parser, Clip Comparison, CogVLM, Expression, Identify Changes, Path Deviation, CLIP Embedding Model, Crop Visualization, Grid Visualization, Buffer, Bounding Rectangle, SIFT, SAM 3, Anthropic Claude, Time in Zone, Detection Offset, Qwen2.5-VL, SIFT Comparison, OpenAI, Line Counter, Detections Consensus, Path Deviation, Cosine Similarity, Blur Visualization, Perception Encoder Embedding Model, Dimension Collapse, Perspective Correction, Bounding Box Visualization, QR Code Generator, Velocity, Segment Anything 2 Model, Polygon Visualization, Dynamic Crop, Identify Outliers, LMM, OpenAI, Classification Label Visualization, Mask Visualization, Time in Zone, Google Gemini, Circle Visualization, Time in Zone, Ellipse Visualization, Image Convert Grayscale, Object Detection Model, OCR Model, SmolVLM2, Image Preprocessing, Google Vision OCR, Color Visualization, Keypoint Visualization, EasyOCR, Line Counter, VLM as Detector, Image Slicer, Property Definition, Detections Combine, Email Notification, Byte Tracker, Overlap Filter, Roboflow Dataset Upload, Triangle Visualization, Slack Notification, Object Detection Model, Detections Stabilizer, Halo Visualization, Corner Visualization, Dot Visualization, Image Contours, Detections Merge, Multi-Label Classification Model, Twilio SMS Notification, Seg Preview, Reference Path Visualization, Byte Tracker, Webhook Sink, PTZ Tracking (ONVIF).md), Detections Classes Replacement, Instance Segmentation Model, Detections Stitch, Contrast Equalization, Camera Focus, Stitch OCR Detections, Stability AI Inpainting, Line Counter Visualization, Cache Set, Template Matching, Email Notification, VLM as Classifier, OpenAI, Depth Estimation, Continue If, Background Subtraction, Label Visualization, Pixel Color Count, Dominant Color
• outputs: Line Counter, Detections Consensus, Path Deviation, Model Monitoring Inference Aggregator, Roboflow Dataset Upload, Blur Visualization, Dot Visualization, Detections Merge, Perspective Correction, Byte Tracker, Bounding Box Visualization, Pixelate Visualization, Distance Measurement, Trace Visualization, Roboflow Custom Metadata, Velocity, Byte Tracker, Detections Transformation, Segment Anything 2 Model, PTZ Tracking (ONVIF).md), Polygon Visualization, Dynamic Crop, Icon Visualization, Detections Classes Replacement, Model Comparison Visualization, Dynamic Zone, Detections Stitch, Size Measurement, Florence-2 Model, Mask Visualization, Stitch OCR Detections, Stability AI Inpainting, Time in Zone, Circle Visualization, Florence-2 Model, Ellipse Visualization, Time in Zone, Path Deviation, Crop Visualization, Color Visualization, Keypoint Visualization, Bounding Rectangle, Line Counter, Detections Combine, Label Visualization, Byte Tracker, Roboflow Dataset Upload, Overlap Filter, Triangle Visualization, Background Color Visualization, Detections Filter, Time in Zone, Detection Offset, Halo Visualization, Detections Stabilizer, Corner 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[instance_segmentation_prediction, keypoint_detection_prediction, object_detection_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"
    }
}